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Building a unicorn: management of innovation, collaboration, and change in a Silicon Valley start-up

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Building a unicorn: management of innovation, collaboration, and change in a Silicon Valley start-up

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BUILDING A UNICORN:
MANAGEMENT OF INNOVATION, COLLABORATION, AND CHANGE
IN A SILICON VALLEY START-UP

by

Kristen Laura Guth

MA, University of Southern California, 2015
MA, University of Illinois at Urbana-Champaign, 2012
BA, Wake Forest University, 2008

________________________________________________________

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMMUNICATION).

Los Angeles, California
August 2017

Approved by:
Dr. Patricia Riley
Dr. Andrea B. Hollingshead
Dr. Daren C. Brabham

© 2017
Kristen Laura Guth
ALL RIGHTS RESERVED
ii
ABSTRACT

Kristen Laura Guth:
Building a Unicorn: Management of Innovation, Collaboration, and Change
in a Silicon Valley Start-up
1

(Under the direction of Dr. Patricia Riley)

This dissertation explores the communicative dimensions and implications of early-stage
organizing and technological innovation by examining collaboration and sensemaking of change
in a start-up. Nascent organizations in gestation or infancy experience high rates of failure: 50
percent of new businesses fail in the first five years and 90 percent of start-ups collapse along the
way to becoming fledgling new firms. Survival of these start-ups may depend on
communication: how their members recognize and utilize expertise, describe flexible visions of
building innovations, and sensemake for resiliency when navigating exit and the resultant churn
of highly-skilled members. Central questions about these communication dynamics arise, such
as: How do groups of experts in start-ups coordinate and manage knowledge, especially in the
context of dispersed technological resources and the rapid entry and exit of globally distributed
contractors? How do members of a small start-up team understand the meaning of members’
exits before, during, and after their departure? The dissertation analyzes data collected during an
ethnographic case study of the entire gestation phase of a Silicon Valley start-up in the 12
months leading up to its launch of an online platform product in the real estate investment sector.
The two empirical chapters feature specific contributions about process to communication theory
and practitioners involved in the ecosystem of start-ups. First, the dissertation provides an
examination of organizational socialization, specifically exit, with newfound clarity provided by

1
Unicorn refers to a private tech startup company valued at one billion US dollars or more and was coined by
Aileen Lee in 2013. Lee, A. (2013, November 2). Welcome to the unicorn club: Learning from billion-dollar
startups. Tech Crunch. Retrieved from https://techcrunch.com/2013/11/02/welcome-to-the-unicorn-club/
iii
sensemaking of role embeddedness in the start-up. Second, the dissertation extends transactive
memory theory to emphasize role negotiation in the development of transactive memory
systems. The research presented offers direction for future theoretical-based inquiries into
communication patterns as early-stage organizations develop and change over time.
Recommendations are provided for policy and practice in the management and support of
communication in start-ups. The dissertation contributes to filling gaps in the literature on start-
ups through new research on dynamics unique to young, early-stage start-ups and
communication processes within these organizations.
Keywords: organizational communication, start-up, collaboration, technology,
innovation, entrepreneurship, strategy, management

iv
DEDICATION

In dedication to my friends and family, without whose never-failing sympathy and
encouragement, nourishment and shelter, mentoring, and support, this dissertation would never
have been attempted or completed.
v
EPIGRAPH

Allons! whoever you are come travel with me!
Traveling with me you find what never tires.

The earth never tires,
The earth is rude, silent, incomprehensible at first, Nature is rude and incomprehensible at first,
Be not discouraged, keep on, there are divine things well envelop’d,
I swear to you there are divine things more beautiful than words can tell.

-- Walt Whitman, Song of the Open Road

vi
ACKNOWLEDGEMENTS

In my experience, the acknowledgements of dissertations often include a list of people
whom have donated copious time, treasures, and talents to the creation not of a dissertation
manuscript alone, but of the doctoral candidate themselves. I am no different. I am in grateful
debt and would like to recognize the people and institutions that helped my research and writing
over many years of graduate study. There is no better place than in my dissertation to
acknowledge the support I have received from a large set of people located all over the world in
the culmination of my doctorate. Countless individuals have offered thoughts that have shaped
this dissertation. For offering helpful conversations about research over the years, I thank Peter
Monge, Janet Fulk, Manuel Castells, M. Scott Poole, John C. Lammers, Noshir Contractor,
Patrice Buzzanell, Paul Leonardi, Cythnia Stohl, Sally Jackson, Stan Deetz, Dave Tewksbury,
Heather Canary, Michelle Shumate, Edward Palazzolo, Jennifer Gibbs, and Matt Weber.
I have benefitted from feedback given by organizers and participants at conferences
during which I presented chapters, including meetings of the Academy of Management
Organizational Communication and Information Systems Doctoral Consortium and the
Organizational Communication Mini Conference at Northwestern University. Faculty and peers
who attended the Oxford Internet Institute Summer Doctoral Programme offered helpful
comments on the topic of study. A presentation during an Annenberg Research Seminar at the
University of Southern California also shaped the dissertation.
Generous financial support from the School of Communication at the Annenberg School
for Communication and Journalism of the University of Southern California (USC), the
vii
University of Southern California Graduate School, and the University of Southern California
Graduate Student Government aided the research.
The questions of innovation and change behind this study first developed more than a
decade ago when I was beginning my professional career during college. I sought to understand
and adapt my work processes to meet the radical shifts that new technologies brought to
organizations. Around the 2008 election cycle, during which the power of social networks and
Internet tools transformed politics (Dutta & Fraser, 2008; Miller, 2008; Stirland, 2008), I worked
in news, public relations, and public affairs—industries that faced disruptions from the adoption
or development of technologies to manage online interaction. I struggled to find room to explore
better ways of working with these changes in the bottom-line-driven culture of industry. I was
lucky to receive encouragement from Scott Poole to pursue my questions about technological
and organizational change in graduate school at the University of Illinois at Urbana-Champaign
(UIUC). As my master’s degree adviser, Scott offered an unfathomable depth of knowledge on
technological and organizational change processes, philosophical understandings of
methodological diversity, and helped to demystify the technique of theory construction. The
mentorship I received from my committee members—Scott, John Lammers, and Christian
Sandvig—to understand micro-to-macro shifts in organizing, technology, and policy imprinted
my research and continues to influence my approach.
As my dissertation adviser, Patricia (Patti) Riley has been a tremendous source of
intellectual and social support at the School of Communication. Her acumen and resolute
expectations have influenced each section of this manuscript. I am indebted to Patti for her
willingness to counsel me in conducting field research. Beyond the dissertation, Patti has
unwaveringly guided me through academia as a constant and dedicated mentor. She has an
viii
unfailing confidence in my abilities to improve myself and contribute to the discipline. I cannot
thank her enough for the weekly conversations, countless email exchanges, and readings of my
papers and chapters.
Similar to Patti, other faculty at Annenberg West offered a blend of encouragement, high
expectations, and scholarly freedom. I am especially grateful for the support and encouragement
provided by the two other members of my dissertation committee—Andrea B. Hollingshead and
Daren C. Brabham. Each offered stimulating conversation and helpful feedback on the research
design and manuscript drafts. Andrea guided me through the literatures on group
communication—transactive memory, team collaboration, and group cognition—that form a
component of the dissertation’s foundation. Daren offered insight on the close-knit relationship
between academic research and professional industry and the process of dissertation production.
He believed in my ability to generate meaningful research that would appeal to both scholars and
practitioners with implications for theory that could inform policy or practice. The committee
members offered their mentorship selflessly and the knowledge I present in this manuscript is
refined because of their diligent efforts. Any remaining mistakes are mine alone.
I received training from a broad array of expert research faculty at Annenberg to whom I
owe much. For his prescient and rigorous instruction during the first three years of my doctoral
studies, and for chairing my qualifying exams, I extend thanks to Peter Monge. I am grateful to
Peter and Janet Fulk for their mentorship, as well as guidance through the Annenberg Networks
Network (ANN) research group. Manuel Castells’ encouragement to view network relationships
as a means of inquiry helped my research frameworks improve by sparking new ideas about the
power structures of technological change. As methodology gurus, Lynn Miller and Sheila
Murphy offered truly generous expertise in statistics, and in survey construction and validation
ix
as well as in focus groups, respectively. I thank François Bar for presence of mind to focus the
Annenberg Innovation Lab research on truly important questions about technological creativity
with lighthearted but sincere commentary, and for his cheerful demeanor. Each of my committee
members contributed greatly to my education, as well, through their leadership in edification
through research. With Patti’s direction of the Scenario Lab, I learned to examine how
organizations facing new dynamics on social media construct narratives in response to
challenges. Using mixed methods, Andrea and I explored the way that businesses respond to
customer reviews online. Daren and I spent years on a Social Sciences and Humanities Research
Council (SSHRC) grant working on questions of design in crowdsourcing and among technology
start-up founders. These studies emerged from research questions in applied settings, and have
indelibly shaped the way I understand communication as embedded in context.
Other incredible scholars from various departments at USC shared their skills and
contributed greatly to my growth. The sociology department at the Dornsife College of Letters,
Arts, and Sciences was decisive in my erudition. Paul Lichterman familiarized me with the
ethnographic method in practice and essentially made this dissertation’s research design possible
with conscientious direction on method as I began to collect data. As boundary spanners between
academia and the start-up world, James Bottom, the Project Director at Blackstone LaunchPad
USC and Incubate USC, and Dr. Ashish Soni, the Founding and Executive Director of Digital
Innovation at the Viterbi Startup Garage, provided incredible insight into practitioner vocabulary
and processes peculiar to the industry. From the Department of Management and Organization in
the Marshall School of Business, Kyle Mayer, one of my qualifying exam committee members,
offered a deep understanding of scholarship, academic careers, and research in strategic
management. My colleagues in the Experiential Learning Center at the Marshall School of
x
Business were also invaluable sources to me for learning and practicing a pedagogical
perspective that values student-centered education.
Beyond the campus of USC, several people and organizations aided my development as a
scholar. Conversations at the Web Science Summer School hosted by the University of
Southampton and several network science conferences hosted by USC’s Annenberg Networks
Network (ANN), the Science of Networks in Communities (SONIC) at Northwestern University,
and the Developing Effective Leaders, Teams, & Alliances (DELTA) lab at the Georgia Institute
of Technology greatly aided in my exploration of methods and theories to analyze complexity.
Several projects and presentations led by renowned public intellectuals and colleagues during my
research position at the Berkman Klein Center for Internet and Society at Harvard University
helped me to decipher an interdisciplinary stance toward the impact of policy on technological
change in my work. I have continued to learn from my University of Illinois at Urbana-
Champaign (UIUC) cohort at the Center for Peoples and Infrastructures at the Coordinated
Science Laboratory, founded and co-directed by Christian Sandvig, about how to examine the
social norms, market structures, public policies, and human capabilities in the new kinds of
interaction between people and information technology infrastructures. The research on new
technology implementation that I conducted at the Institute for Computing in Humanities, Arts,
and Social Sciences (I-CHASS) under the guidance of M. Scott Poole continues to remain
formative.
Friends and confidants helped sustain the intellectual endeavors I pursued in many ways.
Though I completed the bulk of this academic labor, and certainly the typing of the manuscript
(Daro, 2017), I relied on many compatriots in various ways during the project’s research and
production. I owe a great deal to one of my closest friends, Andrew Harris, and his wife,
xi
Margaret Fero, for their gracious invitation to host me at their Berkeley home while I collected
data in the Bay area. Impromptu visits starting in 2012 to Andrew’s blue Victorian row house
apartment in Haight-Ashbury, down the street from Craig of Craigslist, allowed my intrigue with
the start-up scene in San Francisco to take root. Without the remarkable generosity of an “open
house” at Andrew and Maggie’s home, I most certainly would not have been able to afford the
expense of this research. Additionally, without their unending friendship and access to their start-
up and Silicon Valley vocabularies, both professionally and socially, I might have been lost. I
thank them for their time and meticulous review of my manuscript. My close friend, Jacob
Bathanti, also provided indelible remarks in his proofreading of this manuscript. I thank other
lifelong friends who patiently witnessed this project’s development, including Mitra Shultz, Lana
Worobec, Katie Tertell, Raha Dastgheyb, Caitlin McCormick, Rachelle Betancourt, and Brittany
Wyche.
Graduate school friends have provided tremendous intellectual support and camaraderie
since I began my degrees. At the University of Southern California, special commendation is
owed to Christina Hagen and Katherine Elder for an incredible amount of good-natured
dependability. Many people have formed my academic family during my doctoral studies,
including Sandra Evans, Allison Noyes Soeller, Laurel Felt, Kristen Steves, Catherine Duffy,
Nathalie Meréchal, Joel Lemuel, Andrew Schrock, Kevin Driscoll, Alex Leavitt, Joshua Clark,
Xin Wang, Emma Bloomfield, LeeAnn Sangalang, Leila Bighash, Lien Denoo, Matthew Young,
Jovanna Rosen, my 2012 Annenberg cohort, Annenberg alumni, and the broader doctoral
community. From our days together at the University of Illinois, I have been privileged to
continue friendships with Julius Riles, Elizabeth Carlson, Yannick Atouba, Andrew Pilny,
Katherine Cooper, Mattea Garcia, Vincent Pham, Katie Irwin, and Erin Watley. Within the
xii
discipline, the friendly encouragement I have received from Casey Pierce and Jeffrey Treem has
been indispensable. I developed a closeness with several other dissertating scholars as we faced
solidarity in writing, including Julia Raz, Whitney Burke, Amelia McNamara, Kristie Soars, and
Sara Lyness Reifel. Thank you to my friends who all helped me achieve this dissertation with
balance and humor.
On a personal note, I would like to thank my immediate and extended family for their
love and support. To my mother, Elaine Jessee Guth, J.D., I owe a debt of gratitude for her
encouragement of my writing from a young age and her commitment to support my ambitions.
She helped me envision myself pursuing a doctorate, and her daily support of my writing was
imperative to the dissertation’s completion. To my younger sister, Susan Paige Guth, and her
husband, Patrick Melton, I appreciate the messages of support and care packages from Italy
during my doctoral program. To my Aunt Frances Jessee, I appreciate her inspiration to explore
new cultures, travel widely, and research history and relevance through library resources and
cultural landmarks. My grandparents, Dorothea Elizabeth Guth and Dr. Theodore Edwin Francis
Guth, always encouraged my pursuit of advanced degrees; I hope that they would have been
proud that I attained my own doctoral hood. Finally, I posthumously thank my father, David
Alan Guth, who, after having earned his juris doctor, published a book in the 1980s to help
people navigate the small claims court process in North Carolina. My discovery of the book for
the first time at home during the winter break in 2015 reaffirmed my seemingly innate dedication
to practical implications in theory-driven research. The values of pursuing, sharing, and applying
knowledge run in the family.
I set aside special appreciation for Sean Michael McGarvy, who could not have imagined
the adventure he began when we met 11 years ago. He has patiently offered practical
xiii
reinforcement and intellectual support to buoy me during moments of discouragement,
exhaustion, or self-doubt. He has read many versions of many papers, listened to my reflections
about my findings and the research process, and generally extended himself as a sounding board,
adviser, and friend. To him I owe thanks for the encouragement to maintain a dedication to my
writing, as well as the reminders for self-care. Sean’s optimistic outlook and kindness ground me
in knowing that my challenges and accomplishments are shared. I appreciate his journalistic
curiosity, particularly because it prompted direct questions that forced me to gain my footing for
each next step in my journey over several years. I did not always know the direction I was
headed, but I am thankful that he is beside me for whatever comes along next on the open road.
Finally, I would like to thank my informants, both people and organizations, for
generously sharing their time, experience, and materials for the purposes of this ethnographic
research. I remain in awe of their willingness to allow a graduate student to observe and
investigate the daily workings of their roles in developing a new enterprise. I cannot thank them
or the companies by name because I have promised confidentiality in exchange for their candid
reflections and viewpoints. I am thankful to each of them for charitably sharing their
perspectives and expertise with me, especially those employed or affiliated with Collaborative
Wealth, Incorporated (a pseudonym). I hope that the confidence they placed in me to use their
contributions wisely and to good ends has been realized.
xiv
LIST OF TABLES
Table 1.1: Top Ten Private Companies Valued at $1 Billion USD or More Headquartered
in the United States………………………………………………………………… 5
Table 3.1: Unstructured Interviews with Founders………………………………………… 55
Table 3.2: Summary of Structured Interviews Regarding the Development of
CoWealth, Inc. …………………………………………………………………….. 57
Table 3.3: Tools Used in CoWealth Communication and Platform Development………… 64
Table 4.1: Tensions in Three Organizational Disengagement Cases……………………… 96
Table 4.2: Case Summary of Organizational Disengagement Process…………………….. 117
Table 4.3: Sensemaking and Sensegiving about Exits based on Role Relationship
to Organization……………………………………………………………………... 119
Table 5.1: Data Analysis Procedures………………………………………………………. 140
Table 5.2: Categories and Codes of TEP Unit Development Episodes…………………… 142

xv
LIST OF FIGURES

Figure 3.1. CoWealth Ideation Phase Timeline 2009-2015………………………………… 33
Figure 3.2. CoWealth Gestation Phase and Research Timeline August 2015-
February 2016………………………………………………………………………. 34
Figure 3.3. CoWealth Gestation Phase and Research Timeline March 2016-
April 2017…………………………………………………………………………... 35
Figure 3.4: CoWealth Organizational Chart September 2015……………………………… 43
Figure 3.5: CoWealth Organizational Chart September 2015-March 2016……………….. 44
Figure 3.6: CoWealth Organizational Chart April-July 2016…………………………….... 45
Figure 3.7: CoWealth Organizational Chart August-September 2016…………………….. 47
Figure 5.1: Model of Transactive Memory System Development with Role Negotiation… 165
Figure 5.2: Task-Expertise-Person Unit Development with Role Negotiation……………. 166

xvi
LIST OF ABBREVIATIONS

CoWealth, Inc. Collaborative Wealth, Incorporated
CEO Chief Executive Officer
CTO Chief Technology Officer
REIT Real Estate Investment Trust
TM Transactive Memory
TMS Transactive Memory System
xvii
TABLE OF CONTENTS
ABSTRACT……………………………………………………………………………...… ii
DEDICATION……………………………………………………………………………... iv
EPIGRAPH………………………………………………………………………………… v
ACKNOWLEDGEMENTS………………………………………………………………... vi
LIST OF TABLES…………………………………………………………………………. xiv
LIST OF FIGURES………………………………………………………………………... xv
LIST OF ABBREVIATIONS……………………………………………………………… xvi
CHAPTER 1: Introduction
Abstract…………………………………………………………………………….. 1
Problem Background
Industry Relevance…………………………………………………………..3
Academic Relevance……………………………………………………….. .7
Problem Statement…………………………………………………………………. 10
Purpose of the Study……………………………………………………………….. 11
Significance of the Study…………………………………………………………... 11
Primary Research Questions……………………………………………………….. 12
Research Design……………………………………………………………………. 12
Theoretical Frameworks…………………………………………………………… 13
Scope, Assumptions, Limitations, and Delimitations……………………………… 14
Definition of Terms………………………………………………………………… 16
Quotations…………………………………………………………………………...16
Chapter Summaries………………………………………………………………… 17

CHAPTER 2: Communication Flux in Organizational Change Processes
Relational Ontology…………………………………………………………………20
Sociomateriality……………………………………………………………………..22
Sociomateriality and Sensemaking………………………………………………….23
Sociomateriality and Knowledge Management……………………………………..25

CHAPTER 3: Innovation Management, Collaboration, and Productivity at CoWealth, Inc.
Introduction………………………………………………………………………… 27
The Product Concept……………………………………………………………….. 28
The Context………………………………………………………………………… 29
The Technology……………………………………………………………. 32
The Organization…………………………………………………………... 38
Ethnographic Methods for Longitudinally Studying Rapid Change………………. 48
Punctuated Ethnography…………………………………………………….51
xviii
CoWealth Development Activities………………………………………………… 52
Interview Data……………………………………………………………… 54
Unstructured Interviews……………………………………………. 54
Semi-structured Interviews………………………………………… 56
Observation………………………………………………………………… 59
Participant Observation……………………………………………. 59
Non-Participant Observation………………………………………. 61
Archival Data………………………………………………………………. 62

CHAPTER 4: Too Lean for Loyalty: Managing Uncertainty and Tensions amidst Organizational
Disengagement
Abstract…………………………………………………………………………….. 70
Introduction………………………………………………………………………… 71
Organizational Disengagement…………………………………………………….. 72
Uncertainty Reduction Through Sensemaking…………………………………….. 74
Embedded and Liminal Relationships……………………………………………... 78
Method
Research Strategy and Setting……………………………………………... 81
Data Collection…………………………………………………………….. 84
Data Analysis………………………………………………………………. 85
Findings……………………………………………………………………………..86
First Case: Design Firm Exit………………………………………………. 87
Role Definition before Exit………………………………………... 87
Critical Incident for Exit…………………………………………… 92
Sensemaking and Sensegiving Post-Exit…………………………... 93
Paradox and Tensions……………………………………………… 94
Second Case: Founder Exit………………………………………………… 97
Role Definition before Exit………………………………………... 98
Role Uncertainty Leading to Exit………………………………….. 98
Sensemaking Post-Exit…………………………………………….. 103
Paradox and Tensions……………………………………………… 105
Third Case: Contractor Exits………………………………………………. 107
Role Definition and Planning Before Turnover…………………… 109
Turnover as Ongoing Critical Incident……………………………. 112
Sensemaking Post-Exits…………………………………………… 113
Dilemma and Dialectics……………………………………………. 115
Conclusion…………………………………………………………………………. 116
Implications………………………………………………………………… 120
Limitations and Future Research…………………………………………... 120
Acknowledgements………………………………………………………………… 121

CHAPTER 5: Expertise Role Negotiation: The Change Agent of Transactive Memory
Abstract……………………………………………………………………………. 122
Introduction………………………………………………………………………… 124
Transactive Memory Systems……………………………………………………… 128
Transactive Memory System Development………………………………... 130
xix
Expertise Role Negotiation……………………………………………….... 133
Method
Research Strategy and Setting……………………………………………... 136
Data Collection…………………………………………………………….. 138
Data Analysis………………………………………………………………. 139
Findings……………………………………………………………………………. 141
Assessing Convergence……………………………………………………. 148
Task-Expertise-Person Unit Evaluation……………………………………. 150
Task-Expertise-Person Unit Construction…………………………………. 154
Task Creation………………………………………………………. 154
Task-Expertise-Person Unit Matching…………………………………….. 156
Task-Expertise-Person Unit Utilization……………………………………. 159
Conclusion…………………………………………………………………………. 162
Acknowledgements……………………………………………………………….... 167

CHAPTER 6: Conclusion
Summary of Project Goals…………………………………………………………. 168
Major Findings……………………………………………………………………... 169
Implications…………………………………………………………………………171
Advice for Ethnographers…………………………………………………………...173
Future Research……………………………………………………………………..176
Conclusion…………………………………………………………………………..178

REFERENCES…………………………………………………………………………….. 180
APPENDIX A: Expanded Table 7.1 of Private Companies Valued at $1 Billion USD or More
Headquartered in the United States…………………………………………………225

APPENDIX B: Table 7.2 of Top Ten Cities for Technology Start-ups Ranked by 2011 USD
Amount Invested in Companies…………………………………………………….229

APPENDIX C: Interview Question Guide………………………………………………… 230
APPENDIX D: Glossary…………………………………………………………………... 232
1
CHAPTER 1: INTRODUCTION

“We are what we pretend to be, so we must be careful about what we pretend to be.”
-- Kurt Vonnegut, 1966
(Vonnegut, 1966/2009)
2

Nascent organizations in gestation or infancy experience high rates of failure: 50 percent
of new businesses fail in the first five years (Duncan & Handler, 1994; Robison, 2014) and 90
percent of start-ups collapse along the way to becoming fledgling new firms (Marmer,
Herrmann, Dogrultan, Berman, Eesley, & Blank, 2012). Founders report their start-ups failed
because they did not assemble the right team and encountered disharmony among team members
(CB Insights, 2014). Despite these ominous data, municipalities and universities around the
United States have made significant infrastructural investments in innovation districts (Katz &
Wagner, 2014a) to encourage entrepreneurship in the form of high-tech start-ups because of their
impressive impact on economic growth (Kane, 2010; Reynolds & White, 1997). Survival of
these start-ups may depend on communication: how their members recognize and utilize
expertise, describe flexible visions of how to build their innovations, and sensemake for
resiliency when navigating exit and the resultant churn of highly-skilled members. I examine
questions that are central to understanding these communication dynamics, including: How do
members of a small start-up team understand the meaning of members’ exits before, during, and
after their departure? How do groups of experts in start-ups coordinate and manage knowledge,

2
I invoke here Vonnegut’s reflection on the balance between fantasy and reality in
representation. He added this statement as part of an introduction to one of his novels, Mother
Night, five years after its publication.
2
especially in the context of dispersed technological resources and the rapid entry and exit of
globally distributed contractors?
While many communication research studies about group dynamics have relied on
convenient sampling of student workgroups (Seibold & Meyers, 2007) or ahistorical
experimental groups (Poole & Garner, 2013), more knowledge is needed about workgroups and
start-ups in situ with real-world perspective and context (Zahra, Wright, & Abdelgawad, 2014).
Furthermore, a methodological need has been identified for longitudinal research about
organizations focused on process rather than outcomes (Aldrich, 2001) and ethnography in
particular (Watson, 2011). The dissertation analyzes data collected during an ethnographic case
study of a Silicon Valley start-up, Collaborative Wealth, Incorporated, or CoWealth (a
pseudonym), over a period of 12 months leading up to the company’s launch of an online
platform product in the real estate investment sector. The start-up is comprised of a highly
creative group of globally distributed experts who use multiple technologies to iterate and refine
their product while simultaneously building a new venture. The two empirical chapters presented
each accomplish specific contributions about process to communication theory and practitioners
involved in the ecosystem of start-ups, including entrepreneurs, engineers, university
administrators, civic professionals, and public servants. First, the dissertation provides an
examination of organizational disengagement—exits—with newfound clarity provided by
sensemaking of role embeddedness. Second, the dissertation reconstructs transactive memory
theory to emphasize role negotiation in the development of transactive memory systems. The
research presented offers direction for future theory-based inquiries into communication patterns
as early-stage organizations develop and change over time. The general field of interest for this
dissertation is the communication discipline, but readers working in the fields of
3
entrepreneurship, strategy, social psychology, and sociotechnical systems may also find the work
appealing. Recommendations are provided for policy and practice in the management and
support of communication in start-ups.
Problem Background
Industry Relevance
When conjuring thoughts of start-ups, the popular imagination may drift to scenes and
images from the widely acclaimed Home Box Office, Inc. series Silicon Valley set in Northern
California. More specifically, many find familiar the logos of high-tech start-ups-turned-global
corporations featured in the show’s title sequence—Google, Facebook, Twitter, Apple—both as
users and researchers. The show’s opening promulgates the perception that the Silicon Valley
ecosystem is replete with recognizable high-tech brands and organizations within a very close
proximity. In fact, Silicon Valley serves as a synecdoche to describe an area that has historically
predominated the southern half of the San Francisco Bay Area (Sturgeon, 2000) but now spans
four different cities: San Jose, Palo Alto, San Francisco, and Oakland. Furthermore, the area
hosts thousands of high-tech company headquarters at a range of different levels of
organizational development, including ideation, gestation, infancy, fledgling new firms, and
established enterprises. Silicon Valley “is as much a state of mind as it is a physical place”
(Markoff, 2009). Radical innovation and a culture of fearlessness (Stewart, 2015) in the United
States start-up scene are inextricably tied to Silicon Valley (Castells, 2010b). The Silicon Valley
high-tech scene specifically embodies a strict social hierarchy based on employer, entrepreneur
status, and online followers (Marwick, 2013). The culture of Silicon Valley can be ruthless, and
the churn of employees poached to competitors or those working 80 hours a week combined for
their employer and side projects evokes a hustle mentality throughout the region. The riches
4
accumulated in California-based engineering feats represent a new type of gold mine and feed
into an historic mantra popularized by Horace Greeley: to strike it rich, entrepreneurs and
engineers must “go west, young man” and woman (Cross, 1995). There, such enterprising
individuals might strike gold by building a unicorn, the moniker given to a private start-up
company valued at one billion U.S. dollars or more, and joining the herd of such companies (see
Table 1.1 for abbreviated top ten and Appendix A for entire list; Lee, 2013; Griffith & Primack,
2015). Though many companies exit at impressive nine-figure amounts in Silicon Valley (Paley,
2017), unicorns captivate because they represent an extreme of entrepreneurial success.
The unicorn herd is not limited to Silicon Valley, however, as many cities across the
United States, have experienced high-tech start-up growth and are building infrastructure to
potentially support their own unicorns. While most members of the unicorn herd are
headquartered in Silicon Valley, some states beyond California host unicorns, including New
York, Connecticut, New Jersey, Massachusetts, Illinois, Texas, Utah, Arizona, Florida, Georgia,
and North Carolina (see Table 1.1 and Appendix A). In 2011, the National Venture Capital
Association ranked the top 10 cities for tech start-ups (Graham, 2012). In rank order based on the
amount invested into companies that year, the top cities included the San Francisco area, Calif.;
Boston, Mass.; New York City, N.Y.; Los Angeles area, Calif.; Washington, D.C.; San Diego,
Calif.; Chicago, Ill.; Austin, Texas; Boulder and Denver, Colo.; and Seattle, Wash. (see
Appendix B). These cities were also home to other established and recognizable high-tech
companies, such as TripAdvisor (Boston), LivingSocial (Washington), Orbitz (Chicago), and
Amazon (Seattle). Since that ranking was published, other high-tech companies have built
satellite offices in many of these start-up-friendly cities, transforming the locations into tech
hubs. For instance, Adobe software set up a Salt Lake City area office, chipmaker Intel created a
5
Table 1.1
Top Ten Private Companies Valued at $1 Billion USD or More Headquartered in the United States
Rank Company Valuation
(billion USD)
Sector Headquarters Founded CEO
City State
1 Uber $62.0 Software San Francisco Calif. 2009 Travis Kalanick
2 Airbnb $25.5 Software San Francisco Calif. 2008 Brian Chesky
3 Palantir $20.5 Software Palo Alto Calif. 2004 Alex Karp
4 Snapchat $16.0 Media Venice Calif. 2011 Evan Spiegel
5 SpaceX $12.0 Aerospace Hawthorne Calif. 2002 Elon Musk
6 Pinterest $11.0 Media San Francisco Calif. 2010 Ben Silbermann
7 Dropbox $10.0 Software San Francisco Calif. 2007 Drew Houston
8 WeWork $10.0 Business services New York N.Y. 2010 Adam Neumann
9 Theranos $9.0 Health Palo Alto Calif. 2003 Elizabeth Holmes
10 Intarcia Therapeutics $5.5 Health Boston Mass. 1997 Kurt Graves
Source: Nusca, A. (2016, January 19). The unicorn list. Fortune. Retrieved on February 14, 2017 from http://fortune.com/unicorns/
6
facility in Portland, Ore., and both Apple and Google have created campuses in Austin, Texas
(Athwal, 2015). Other cities that were slated to become tech hubs in 2015 included Dallas,
Texas; Seattle, Wash.; Chicago, Ill.; and Miami, Fla.
The increase in the spread of high-tech start-ups and backing by venture capital has
demanded a shift in training the labor force to encourage innovation, collaboration, and
entrepreneurialism that universities have been eager to meet. Many universities house long-
standing offices of technology transfer to license and commercialize intellectual property
generated by faculty research activities on their campuses, especially for biotechnology (Powell,
Koput, & Smith-Doerr, 1996). Redirecting efforts toward student entrepreneurs in high-tech,
universities are now building cross-campus collaboration, experiential programs, dedicated
workspace, and mentorship programs to produce start-ups and start-up founders among their
student bodies (Houser, 2014). Private and public non-profit universities have increasingly built
data science programs (Thompson, 2017). Academic institutions are also often involved in the
urban planning trend of “innovation districts,” which are “geographic areas where leading-edge
anchor institutions and companies cluster and connect with start-ups, business incubators, and
accelerators. Compact, transit-accessible, and technically-wired, innovation districts foster open
collaboration, grow talent, and offer mixed-used housing, office, and retail” (Katz & Wagner,
2014a; Katz & Wagner, 2014b). In 2016 alone, an innovation quarter was opened at Wake Forest
University (Schneider, 2015), Purdue Research Foundation launched a billion dollar investment
partnership on a 15-20 year construction project for an innovation district on the Purdue
University campus (Sequin, 2016), and Virginia Polytechnic Institute and State University
announced plans to build its own innovation district next to downtown Blacksburg (Pastor,
7
2016). Many corporations have also begun to launch accelerator programs to engage with start-
ups across industries (Kanbach & Stubner, 2016).
Although universities and corporations provide buffers for the risk of start-ups and new
businesses, many of these nascent organizations still vanish in the early stages of development.
About half of all new businesses founded in the United States succeed as an operating entity
(Duncan & Handler, 1994; Robison, 2014). For start-ups, only 10 percent succeed, and those that
do typically encounter several near-death experiences along the way (Marmer, Herrmann,
Dogrultan, Berman, Eesley, & Blank, 2012). Founders of failed start-ups reported that the third
most frequent reason for start-up failure is not assembling the right team and the twelfth most
frequently cited reason is disharmony among team members (CB Insights, 2014). Yet, start-ups
are almost solely responsible for job and employment growth, and also impact innovation and
economic growth more broadly (Kane, 2010; Reynolds & White, 1997). The process of
developing efficient and effective processes of communication in start-ups is critical to enable
scaling into a larger organization. Survival of these start-ups may depend on communication:
how their members recognize and utilize expertise, describe flexible visions of building
innovations, and sensemake for resiliency when navigating exit and the resultant churn of highly-
skilled members. As investment increasingly flows to incubate or accelerate start-ups and
entrepreneur training, more knowledge is needed about the communication processes that affect
and shape creative, educational, and economic outcomes within early-stage start-ups.
Academic Relevance
Extensive scholarly research examines factors that contribute to the success or failure of
start-ups on a micro level, concentrating in particular on founders, but the literature has less to
say on many of the dynamics unique to young, early-stage start-ups as groups and organizations.
8
My research aims to contribute to filling this gap. On an intrapersonal level, influences on the
creativity and career trajectories of business founders, leaders, and entrepreneurs have been
extensively studied. Factors like life history, human capital, financial capital, interpersonal
networks, and organizational context have fueled self-employment (Carroll & Mosakowski,
1987). Leadership styles among business leaders and entrepreneurs have also received extensive
study (Avolio & Bass, 1995; Avolio & Luthans, 2006; Baron, 2007; Baum & Locke, 2004;
Renko, Tarabishy, Carsrud, & Brännback, 2015; Singh & Fleming, 2010). Entrepreneurs
organize new ventures through a series of actions that are dependent not only on the attributes of
the founders (Gartner, 1988), but also on the nature of the opportunity and the organizing process
itself (Delmar & Shane, 2002).
On group and organizational levels, the literature offers a rich understanding of the
dynamics of stable, older, and established groups, based on research conducted in organizational
and group communication (Buzzanell, 2010; Lester, Meglino, & Korsgaard, 2002; Leonardi,
2012; McPhee & Zaug, 2000; Poole, Seibold, & McPhee, 1985).Majchrzak, Javenpaa, and
Hollingshead (2007) point out that transactive memory systems theory has been applied to more
stable than emergent groups (pp. 151). Alliance formation and consequent information sharing
with older organizations improve a start-up’s performance (Baum, Calabrese, & Silverman,
2000). New foundings are also impacted by the nature of their growth (Bamford, Dean, &
Douglas, 2004). Young organizations face a liability of newness, or a greater risk of failure than
older organizations, because they depend on the cooperation of strangers, have low levels of
legitimacy, and are unable to compete effectively against established organizations
(Stinchcombe, 1965). Although younger, developing organizations present data collection and
9
analysis challenges to researchers, including the risk of a research site’s complete dissolution, the
emergence of organizing and patterns of change evidenced in them deserves further attention.
The popular literature is replete with books about the process of start-up organizing.
Some are the variety in which famous founders are asked to reflect on their start-ups’ early days,
often with rose-colored glasses, and divulge inside stories about the windfalls and pitfalls of the
path to success (Livingston, 2007; Wasserman, 2012). Practical guidebooks from the dot-com
era are filled with case studies of successful start-ups from ideation to IPO, promise “invaluable
lessons” to entrepreneurs, and have become legendary in Silicon Valley (Nesheim, 2000; Nokes,
2000). Famous founders themselves, like Peter Thiel (2014) of Paypal, or Silicon Valley veterans
(Blank, 2013), continue to set down their thoughts about how to propel start-ups into successes.
Such reminisces can spawn ideas that are subsequently perpetuated; for example, in the wake of
the Great Recession, the concept of a lean start-up, inspired by lean or just-in-time
manufacturing principles, became a best-selling idea (Ries, 2011).
Yet despite the attention paid to these phenomena, gaps remain in the literature about
new and young organizations in development. Scholars have called for more longitudinal
research to study organizing from a process perspective. Aldrich (2001) advocates for process-
oriented theorizing and research to capture dynamic organizational processes. Rather than
outcome-driven, this research was event-driven research to examine the way in which change
unfolds during development (Van de Ven & Engleman, 2004). Organizational change is the
transition an entity undergoes in a planned alteration of its strategic plan or structure (e.g.,
merger, acquisition, joint venture). The number and frequency of organizational changes that
entities endure have increased over time (Lewis, 1999), with these changes sometimes triggered
by market losses or failure of organizational adaptation (Weick & Quinn, 1999). Themes within
10
the research on organizational change have varied focus on issues regarding content, context,
process, and outcomes (Armenakis & Bedeian, 1999).
This dissertation advances the study of groups and burgeoning organizations through
three distinct modes: groups in natural environments, investigated with a process lens, and with
the ethnographic method to provoke theory improvement. Methodological choices in the
research design were made with deliberate effort to address literature gaps and scholarly calls.
Many studies on groups rely on convenient student groups (Seibold & Meyers, 2007) and
ahistorical experimental groups rather than workgroups in situ (Poole & Garner, 2013).
Entrepreneurship scholars have called for start-ups to be researched in their natural settings to
understand their founding contexts, organizational structures, functions, and performance (Zahra,
Wright, & Abdelgawad, 2014). This dissertation seeks to contribute to the research on groups in
natural settings.
Despite the long-standing divide between organizational studies and anthropological
work (Bate, 1997), scholars have expressed a need for ethnographic process research in
organization and management studies (Watson, 2011). Case studies have the potential to provoke
new ideas and build on existing theories (Eisenhardt, 1989a; Siggelkow, 2007). The case study
approach is an appropriate method of choice to understand dynamics of context as they inform
theoretical reconstruction (Stake, 1995; Yin, 2014). This dissertation approaches a specific case
that is made with an understanding of the case as a theoretical construct to illuminate theory
improvement (Ragin, 1992).
Problem Statement
The gap in knowledge about communication processes in the messy in-between of early
stage or nascent organizations in the gestation phase of development must be addressed. Most
11
research on start-ups has emerged from work on entrepreneurship, and has not adequately
accounted for communication processes in organizing. This dissertation focuses on an early-
stage organization in gestation to examine the development of transactive memory systems,
sensemaking of organizational turnover, and group decision-making to extend communication
theory application.
Purpose of the Study
This study aims to theorize the process of exits in organizational socialization stage
models and provide theory improvement to the model of transactive memory development by
using the context of the entire gestation phase of a start-up.
Significance of the Study
By filling this gap in our knowledge, this study intends to improve the human condition
with a deeper understanding of the socialization, collaboration, and decision-making factors that
enhance group performance, and particularly, early-stage organizations. It offers a better
understanding of the organizing that occurs at the level between the individual founder and the
full-fledged organization. In particular, the third chapter presents a methodological innovation
that I have termed “punctuated ethnography” as an emerging methodological approach to
organizations that operate extensively online and offline. I define punctuated ethnography as a
systematic recording of culture planned during observations at specific periods of time and
supplemented with other data types to capture dynamic change. The fourth chapter offers an
investigation of paradox and dilemmas faced in organizational disengagement, and presents
sensemaking processes as an uncertainty reduction technique that depend on the embeddedness
of the worker to the organization. The fifth chapter theorizes two models, including a Model of
Transactive Memory and Role Development and a Model of Task-Expertise-Person (TEP) Unit
12
Development, to improve the development of transactive memory systems within groups.
Communication scholars and practitioners will be able to use the knowledge provided to improve
processes within groups and organizations faced with organizational change.
Primary Research Questions
The primary research questions of this case study seek to examine aspects of
organizational change and innovation management. The first empirical chapter of this
dissertation focuses on the process and meanings communicated before, while, and after
members exited the start-up. The three research questions this portion of the research explores
are: How do tensions emerge that lead to organizational change (i.e., departures)? How does
definition of roles interact with the sensemaking and sensegiving of exit? and How does an
early-stage start-up maintain fluidity after an exit transition has occurred? The second empirical
portion of this dissertation focuses on transactive memory system development, with the key
research question: How does expertise role negotiation influence the development of a
transactive memory system?
Research Design
The research design utilized in this dissertation is ethnography of a case study at a single
site, Collaborative Wealth, Incorporated, or CoWealth (a pseudonym), in the Silicon Valley
region of Northern California. Data collection was conducted during a 12-month period to
capture the entire gestation period of the start-up from beginning to end. The case used multi-
sited fieldwork and drew on interviews, observation, and archival documents; documents were
collected in-person as well as virtually from sources such as digital audio conference or
videoconference meetings, project management software, and emails. Informants included three
founders, three employees, and several contractors, users, and investors. I carried out structured
13
and unstructured interviews with informants in order to understand beliefs and opinions about
their role at Collaborative Wealth (CoWealth) and development occurring at CoWealth and on
its platform. While collecting participant observation and nonparticipant observation data, I
closely explored and recorded notes about the field setting and informants’ behavior and
interaction therein. Informants would often mention diagrams, presentations, documents, and
emails during interviews or observation, and I subsequently pursued these in order to add them to
my archival data collection. These collection techniques resulted in a dataset of 37 unstructured
interviews with the three founders, 24 semi-structured interviews with 22 informants (two
founders were interviewed twice), 56 field note documents with 173 pages of text, 4,211 minutes
of transcribed recordings, and more than 300 documents. The methodology of data collection is
further detailed in the methods components of the second chapter. Within each chapter, a defined
subset of the data corpus is described for analytical clarity.
Theoretical Frameworks
The foundational theoretical frameworks in this dissertation arise from a relational
ontology. The second chapter delves into the way in which structuration, the process of
organizing, and sociomateriality together serve as a framework in the dissertation to understand
change in organizations. Sociomateriality denies the separation of technology, work, and
organization (Orlikowski & Scott, 2008) and views organizing as an emergent process
(Orlikowski, 1992). The empirical chapters span two areas of social interaction in group
communication and organizational communication, including organizational socialization and
knowledge management using sociomateriality as a lens. The study presented in the fourth
chapter proposes an examination in tensions and paradox that lead to organizational exits, and
the sensemaking process as an uncertainty reduction technique that proceeds differently for
14
members based on the embeddedness of their role in the organization. The study presented in the
fifth chapter is the first to examine transactive memory system development ethnographically
and proposes a new theoretical model to account for role negotiation during the development of
task-expertise-person units.
Scope, Assumptions, Limitations, and Delimitations
The scope of this study included an ethnography of any person or organization involved
with the development of CoWealth at its offices in Start-up Capital, California, or in the
surrounding Silicon Valley area. As a start-up, the findings in this dissertation relate specifically
to early-stage or nascent organizations in gestation or infancy, but are further applicable to
conditions or places other than those defined in the study through the means of theory
improvement, detailed in the discussions and conclusions of each empirical chapter.
The assumptions made within this dissertation are self-evident truths about the
informants. I assumed that informants answered my interview questions truthfully based on their
personal experience and accurately to the best of their abilities. Over time as we became more
familiar, I negotiated with the founders to have account access to private workgroups on all
significant forums for development, including Zepelin for design, Confluence for engineering,
and Slack and Skype for workgroup communication, as well as many others detailed in the
second chapter. I operated under the assumption that the interaction and work I observed on
these platforms did not attempt to obscure any comment or item from me. I assumed the archival
documents that I acquired during and after interviews or meetings, as well as those requested
after document review, were intact and unaltered representations of actual communication and
work product.
15
Limitations of this dissertation included the type of data I was able to procure, partly
inhibited by my own language deficiencies and the pace of the start-up’s technology
development. Many but not all of the people involved in CoWealth, including the three founders,
shared a cultural background and were bilingual in English and their arterial language. I was only
fluent in English, and not privy to the statements made in other languages employed at the start-
up. Second, although I had planned to collect quantitative data about the interaction of users
within the platform, the CoWealth platform was not fully operable by the conclusion of the
study, and thus prevented collection of online data. CoWealth’s process of development matches
the extended timeline of many other innovation processes (Berkhout, van der Duin, Hartmann,
Ortt, 2007; Oppong, 2016), though I learned more about this world as I entered into it, changed
my thinking accordingly, and shifted the research design from the original proposal. Timing is
one of the gambles of longitudinal field research (Hargittai, 2009; Luker, 2008; van Maanen,
1988, 2011); although maturation of an organization is expected, events that occur in its
development (e.g., history effects) may alter the focus of research, but not the internal validity, of
the original research purpose. The dissertation data collection period finished as CoWealth had
completed its proof of concept and design, but not implementation, of a minimum viable
product. Future research aims to examine the design of the platform through its iterative
development.
Delimitations on the research design that I imposed deliberately on the research included
the setting of CoWealth as a case. There are many start-ups emerging in various locations that
one might observe, and my choice to examine CoWealth was made based on a relationship of
convenience: knowing a board advisor of the company who could grant me access to the
founders. Additionally, I had means by which to travel to Northern California and stay there
16
during periods of participant observation. Finally, the last choice I made in the design of this
study, knowing that the ethnographic method prefers and technological innovation requires
longitudinal study, was to curtail data presented in this study to a finite period of 12 months for
the purposes of allowing time for analysis and completing the dissertation. Data collection
continues with an aim to contribute additional analysis about technological development in
CoWealth following the dissertation manuscript filing.
Definition of Terms
A few significant terms that I employ in the writing of this manuscript have polysemic
interpretations or resemble industry vocabulary. Words and phrases from social science research
methods or theory are comingled with those from the applied vocabularies of software
engineering, start-up management, and real estate throughout the dissertation. I provide
definitions throughout the manuscript but also in the appended glossary.
Quotations
The beginning of each chapter, except the third, opens with a quotation from a figure
famous for his contributions to art and literature. These quotations, from Kurt Vonnegut, Johann
Wolfgang von Goethe, Samuel Beckett, and Vincent Van Gogh, represent each chapter’s
analytical themes, and reinforce the larger connection to relational ontology in the dissertation as
a whole. I intentionally took quotations from outside the frames and pages of creative works that
these figures produced, aside from the last quotation. Rather, I invoke their musings on the
process of creation and development during the progression of their lifework. These quotations
and excerpts offer the introspection of authors, artists, playwrights, and philosophers as they
approached and drew connections in life around them. Likewise, I hope these musings inspire
17
perambulation between our starting- and end-points, on the in-between and messy nature of
becoming and organizing.
Chapter Summaries
This introduction presented the background of the problem, research design, and scope,
assumptions, limitations, and delimitations. The format of the remaining chapters of this
dissertation is a thesis composed of potential papers, wherein each chapter represents an article
for potential publication, with the exception of the introduction and conclusion chapters. This
project is divided into one theoretical chapter, one methodological chapter, and two empirical
studies. The second chapter presents relational ontology and sociomateriality as a framework for
“Communication Flux in Organizational Change Processes.” The empirical studies use a
multimethod analysis of qualitative data. Empirical chapters are constructed to be stand-alone
research articles and share some thematic content in the introduction and methods sections.
Together, these studies examine the organizational change in a start-up during its growth and
design of communication, technology, and organization, using sociomateriality as an overarching
lens.
I introduce CoWealth in depth in the third chapter, “Innovation Management,
Collaboration, and Productivity at CoWealth, Inc.” The chapter elucidates details about the case,
including the company platform, the real estate investment industry in which it was competing,
the contextual trends from which it launched, and the technology and the organization CoWealth
was developing. The chapter also outlines the longitudinal ethnographic methodology employed
in the collection of data, which included interviews, observations, and archival documents. A
series of organizational charts detail changing structural relationships in the start-up, and a table
18
of technologies and how they were used reveals the complexity and interrelatedness of software
development tasks for members.
Following this review of the case and the methodology, the next two chapters present
empirical innovations that examine structure, decisions, and sensemaking in a descending
analytical scale from macro to micro processes in the start-up. The study that makes up the
fourth chapter, “Too Lean for Loyalty: Managing Uncertainty and Tensions amidst
Organizational Disengagement,” focuses on organizational exits, and examines the tensions that
emerge before exits, the critical incidents and rationale used as reasons for exits, and the
sensemaking techniques to manage uncertainty within the start-up after exits. Three exits from
CoWealth that I observed during my fieldwork were analyzed to research how a start-up copes
with the churn generated by member departures and fortifies resiliency amidst the performance
pressures of a highly competitive market. Liminal and embedded members are found to induce
different sensemaking and exit processes through paradox and tensions.
Drawing further on the picture of change structures elucidated in the previous chapter, the
fifth chapter, “Expertise Role Negotiation: The Change Agent of Transactive Memory,”
examines the coordination of knowledge and negotiation of roles in a context of evolving tasks.
The match between task, expertise, and people formed during planning meetings among
members of the engineering team were analyzed. Two task assignment strategies by the Chief
Engineer and four expertise claim strategies by members are identified as mechanisms by which
roles are negotiated both in the start-up and the developing transactive memory system. A
theoretical model, the Model of Transactive Memory and Role Development, is proposed to
account for the role negotiation process within the model of transactive memory development. I
also discuss a second model, the Model of Task-Expertise-Person Unit Development, with role
19
negotiation about the development processes within creating the match and cementing the
relationships between task, expertise, and people on a team.
The dissertation concludes with the sixth chapter, which presents a summary of the
project goals, a review of emergent themes, and a discussion of limitations on this study and
directions for future research. Policy and practice recommendations in the management and
support of communication in start-ups and early-stage organizations are provided.
Supplementing these chapters, the final pages include an expanded version of Table 1.1 that
displays all private companies valued at $1 billion USD or more headquartered in the United
States, an appended interview guide, and a glossary.

20

CHAPTER 2

Communication Flux in Organizational Change Processes

In nature we never see anything isolated, but everything in connection with something else which
is before it, beside it, under it and over it.
-- Johann Wolfgang von Goethe, June 5, 1825
(Eckermann, 1848/1998)
3

Relational Ontology
My research framework for this dissertation relies on a relational ontology to examine
communication flux, and connect the social and the material, in organizational change processes.
The relationships enacted between artifacts and people (or more formally, agents) in practices
and processes reveal meanings and yet cannot be separated from those meanings. I define
“communication flux” as the interaction that enables and enacts these relationships. As I
analyzed more detailed processes with a sociomaterial lens, other theoretical frameworks
emerged as useful to help me decompose the unfolding events and their significance. The
dissertation enclosed attempts to analyze change in a start-up whereby its members are
constrained and enabled by the material properties of the technologies upon which they rely and
develop for communication, collaboration, and innovation.

3
To open my framework on relational ontology, I quote a vignette of a philosophical discussion.
Goethe is poised in conversation with a friend about a tree he sees, and remarks on the changes
to its appearance based on surroundings and circumstance. He concludes that all elements that
we perceive are encased by our own experience and therefore inseparable.
21
Relational ontology focuses analysis on the meanings enacted in the process of practice
between entities, such as between people and technologies (Schultze, 2017). Relational
theories—such as structuration and adaptive structuration, sensemaking, and sociomateriality—
view reality in “dynamic, continuous and processual terms” (Emirbayer, 1997, p. 281). As
Schultze explains, “with entities secondary, their identities, meaning and significance are derived
from their role in the dynamically unfolding process of practice. People and things are thus
brought into being through everyday activity” (2017, p. 61). Meaning and matter are entangled
and emerge through the relationships and performances that constitute them (Scott &
Orlikowski, 2014). The enactment of phenomena places entities in interdependent and
indeterminate relationships (Barad, 2007). Performances are constitutively intertwined with
everyday material-discursive practices and sociomaterial infrastructure (Schultze, 2017).
Within relational ontology, three central theoretical frameworks have shaped my
approach to understanding interactive processes of communication flux in organizations
generally, and in the case of CoWealth’s development and innovation in particular. Structuration
(Giddens, 1979, 1984) and adaptive structuration theory (DeSanctis & Poole, 1994) propose a
constitutive influence of interaction between structure and people on the production and
reproduction of social systems at micro-, meso-, and macro-levels simultaneously. In their
adaption of Giddens’ theory, DeSanctis and Poole emphasized that the use of information
technologies form impressions about their roles and utilities in the activities of groups and
organizations. These perceptions influence use and the social aspects of technology influence the
interaction among people. Similarly, the constructivist approach of actor network theory (Latour,
1999, 2005) emphasizes the relational ties between and agency of people, ideas, processes, and
objects in creating social situations. In combination, this first group of theories focused my
22
examinations on agencies of structures and people, as well as rules and resources, in my analysis
of change.
A second group of theories—on the process of organizing (Weick, 1974), organizational
information theory (Weick, 1979), and sensemaking (Weick, 1995)—helped connect my study of
communication flux at the level of personal information management to process-driven
organizing. Weick defines organizing as a “consensually validated grammar for reducing
equivocality by means of sensible interlocked behaviors” and an assembly of ongoing
interdependent actions into certain sequences to generate outcomes (1979, p. 3). In order to
reduce equivocality, people engage in sensemaking. Sensemaking is an ongoing process that
forms when people make retrospective understanding of the situations in which they find
themselves, and consequently shapes organizational structure and behavior. Together, these
Weickian theories helped me understand the non-linearity and interdependent process of
organizing and organizational adaption to change.
Sociomateriality
Finally, sociomateriality is the framework I employed most directly to help understand
the communication flux presented in my research. Sociomateriality recognizes not only the
construction of organizations through social reality, but duly gives emphasis to the matter and
form of the technologies in use for organizing (Orlikowski, 2007). The sociomaterial approach
reifies the importance of artifacts, including digital technologies, in the process of organizing.
Materiality can describe both tangible and intangible artifacts that have practical instantiation
and significance (Leonardi, 2010). People using artifacts in practice generate the relations in
sociomateriality and its study entails a practice perspective in research (Orlikowski, 2000).
Sociomateriality denies the separation of technology, work, and organization (Orlikowski &
23
Scott, 2008) and views organizing as an emergent process (Orlikowski, 1992). This perspective
acknowledges interactions between people and material artifacts, as well as the mutually
constitutive relationship between the social and material (Leonardi & Barley, 2008, 2010; Scott
& Orlikowski, 2013). Communication scholars have asserted that the material and symbolic
aspects of organizations are realized through communication (Arnaud & Fauré, 2016; Ashcraft,
Kuhn, & Cooren, 2009; Cooren, 2015). As research on sociomateriality has proliferated,
researchers have linked it with three important topics explored in this dissertation, including
sensemaking and coordination.
Sociomateriality and Sensemaking
The sociomateriality of sensemaking is one area in which scholars have recently
expanded their examinations, which relates directly to the fourth chapter of my dissertation. The
combination of the discursive turn and the practice perspective has resulted in a focus on
sensemaking in both strategy as sociomaterial practice (Balogun, Jacobs, Jarzabkowski, Mantere,
& Vaara, 2014; Kaplan & Orlikowski, 2013), strategy-as-practice, and strategic communication
(Thomas & Stephens, 2015). Research on sociomaterial sensemaking focuses on crises as a
result of failed technologies (Berthod & Müller-Seitz, 2017), entanglement with the materiality
of natural environments (Good, 2016), or practice breakdowns (Loohuis & Ehrenhard, 2014).
Distributed communication in global software development companies has been examined as
collective sociomaterial sensemaking (Vidolov & Kelly, 2009). Scholars have also examined
strategic sensegiving through visual representations (Garreau, Mouricou, & Grimand, 2015;
Hultin & Mähring, 2014) and prospective sensemaking through material practices (Stigliani &
Ravasi, 2012), which highlight the sociomateriality of the organizing process with future-
24
oriented temporality. My dissertation contributes to this growing body of knowledge with a study
of the sociomaterial sensemaking of organizational disengagement.
Organizational socialization stage models have theorized phases by which a person
anticipates entry, enters, assimilates, and departs from an organization (Jablin, 1987). Most
research about organizational socialization has focused on role entry (Waldeck & Myers, 2008)
and neglected the exit process (Davis & Myers, 2012). Furthermore, the meaning of exits for
both those who leave (e.g., leavers) and those who stay (e.g., stayers) is rarely discussed (Cox &
Kramer, 1995). Two models of organizational disengagement (Ebaugh, 1988; Jablin, 1987,
2001) focus on members who choose to leave an organization, or voluntary exits, and do not
account for involuntary exits. Processes of member exit may be different for embedded, full-time
employees and for loosely connected contractors. Regardless of the locus of control for the exit
decision or the status of the worker, the turnover and churn create uncertainty in the
organization, which members manage through communication (Kramer, 2004). The study
presented in the fourth chapter proposes an examination of tensions and paradox that lead to
exits, and the sensemaking process as an uncertainty reduction technique that proceeds
differently for members based on the embeddedness of their role in the organization. The three
research questions the research explores are: How do tensions emerge that lead to organizational
change (i.e., departures)? How does a role definition interact with the sensemaking and
sensegiving of exit? and How does an early-stage start-up maintain fluidity after an exit
transition has occurred? The first empirical portion of this dissertation focused on the process
and meanings communicated before, during, and after members exited the start-up.

25
Sociomateriality and Knowledge Management
A second area that scholars have associated with sociomateriality is knowledge
management, which includes transactive memory, and which I explore in my fifth chapter. Some
of these studies link the relationship of artifacts to the creation of routines, such as those to
manage knowledge in organizations (Leonardi, 2011; Pentland & Feldman, 2008). One study,
focused on healthcare workers coordinating telepresence of phsyciains through video robots,
examines material constitution of technology in knowledge work (Beane & Orlikowski, 2015).
Most studies focus on knowledge sharing and coordination through social media, whether about
visibility (Leonardi, 2014), knowledge acquisition (Leonardi, 2015, 2017), knowledge transfer
(Choi, Huang, Palmer, & Horowitz, 2014; Leonardi & Meyer, 2015), and information sharing
(Rode, 2016). Among boundary-spanning teams using enterprise social media, one study found
that although team members recognized information, the systems only provided limited support
for information search and coordination (van Osch & Steinfeld, 2016). Research thus far also
suggests tacit knowledge may be less likely to transfer in social web tools (Panahi, Watson, &
Partridge, 2013).
Within knowledge management theories, transactive memory theory has emerged in team
cognition research about information and decision-making as an explanation for the process of
expertise sharing and coordination that allocates cognitive labor in groups. A transactive memory
system (TMS) develops organically among group members as a way to encode, store, retrieve,
and communicate information, and has been linked to group effectiveness (Hollingshead, 1998a).
As members orchestrate their work together, the transactive memory system matures with
increasing levels of expertise specialization, reliability of other members’ expertise (or
credibility), and coordination on tasks and between expertise areas (Lewis, 2003; Majchrzak,
26
Jarvenpaa, & Hollingshead, 2007; Moreland & Argote, 2003). Brandon and Hollingshead (2004)
outline a model of the development process of transactive memory systems in three stages with
cyclical processes: cognitive interdependence, development of task-expertise-person (TEP) unit
relations, and convergence on a shared mental model. The second empirical portion of this
dissertation explores the research question: How does expertise role negotiation influence the
development of a transactive memory system? The study presented in that chapter is the first to
examine transactive memory system development ethnographically, and proposes a
reconstruction of the theoretical model to account for role negotiation during the development of
task-expertise-person units with two models.

27

CHAPTER 3

Innovation Management, Collaboration, and Productivity at CoWealth, Inc.

In many technology start-ups, it seems analytically impossible to disentangle the
organization from its technology product. Development of the organization and the technology
are not entirely separate and must be considered as mutually constitutive. As Leonardi (2012)
notes, the processes of development, implementation, and use of technology are often perceived
as temporally sequenced after one another, but in reality their activities overlap in the larger
organizational context. The rapid iterations and incremental development that a high-tech start-
up experiences provide a unique context to study the interrelations between changes in an
organization and the technology it uses as well as produces, with specific attention to innovation
management and organizational development. In answer to calls for bridging the study of groups
that are also organizations in applied contexts, with longitudinal data, and across multiple
platforms (Poole, Putnam, Seibold, 1997; Seibold, 2000; Simpson & Seibold, 2008), this
research aims to make a contribution with a rich ethnography, and presents a methodological
innovation that I term punctuated ethnography, a method that connects observation of online and
offline communication processes.
The case of the platform developed by Collaborative Wealth, Incorporated (CoWealth; a
pseudonym, as are all other names used herein) provides an opportunity to understand the
interrelationships between technology and organizational development. The company was in the
beginning stages of developing and implementing its platform, as well as growing its company
28
with new employee hires and the active cultivation of a user base. This research was conducted
at a single site, CoWealth, and was approved by the appropriate Institutional Review Board. Data
was collected over a 12-month period to capture the gestation of the start-up from beginning to
end. The case used multi-sited fieldwork with observation, interviews, and archival documents
collected in-person as well as virtually from sources such as digital audio conference or
videoconference meetings, project management software, and emails. In this chapter, I provide
an overview of the context and trends that spurred the creation of CoWealth, a preview of the
technology that would eventually become its platform, a description of the organization and its
changes, and my data types and collection techniques.
The Product Concept
CoWealth’s product, or new technology idea, was to build a platform that would enable
people to form groups, pool their money together, and purchase real estate property in a co-
ownership agreement, with one investor leading the group to make decisions on investment goals
for the property. By encouraging people to join together online and agree to property investment
terms, CoWealth aimed to provide access to real estate wealth generation at a lower financial
entry point. Usually, investors in real estate are excluded legally to those with over $200,000.
CoWealth’s vision for its technology was to enable collaborative property ownership as a means
of investment for wealth building for anyone at more affordable price points. CoWealth’s goals
included education about real estate investments as well as group decision-making and
negotiation, all supported by legal agreements between investors.
The concept of the platform product evolved in August 2016 to provide users with the
option of investing in a residential property, either a single family home or condo, in three ways.
Rent Ready is the first and original option, which offers users an option to purchase a turnkey
29
residential property and have CoWealth’s affiliated company, PropertyPros, manage renters to
provide a steady income. Turnkey properties are fully renovated, and grew in popularity during
the housing market decline in 2007 and 2008 when home buying was cheaper than renting
(turnkey property, n.d.). Later during development, a second option, Flipping, emerged at
CoWealth to allow users to purchase a home in need of repair, then use PropertyPros to manage
its renovation, and resell it for a profit (flipping, n.d.). The third option, Improvement Income, is
a combination of the first two options, and allows users to renovate a property and then rent it.
The CoWealth landing page on its user site explains the process of investment and outcome
goals, and provides a virtual space for users to indicate interest in a particular option. The
CoWealth concept was distinct from both real estate investment trusts (REITs), in which money
invested does not translate to ownership, and from mortgages, in which the bank owns the
property and a home buyer invests with monthly payments to the bank, because users end up
owning the properties.
CoWealth was not the first company, however, to enter the online real estate investment
market. Various other start-up companies, based on different kernel concepts, shared the
competitive real estate investment space with CoWealth, such as Fundrise (c. 2012). The
founders named other realty websites that inspired CoWealth design, including RedFin (c. 2006),
Zillow (c. 2006), Trulia (c. 2004), and REALTOR.com (c. 1994). Additionally, CoWealth
identified a crossover into similar target users with peer-to-peer lending companies that trade in
securities, such as LendingClub (c. 2007).
The Context
The CoWealth product was developed in a context of real estate property ownership
turmoil and significant shifts in technology, catalyzed by the sharing economy, crowdsourcing,
30
and crowdfunding. To understand the impetus for the creation of the platform requires a review
of recent financial history and technology-enabled trends. Spurred by defaults on the subprime
home mortgage sector and plummeting mortgage-backed securities, the Great Recession
devastated the United States economy between December 2007 and June 2009 (Rich, 2013). The
ensuing global financial crisis wreaked havoc on international finance between September 2008
and 2010 (The Economist, 2013a). Monetary policy was in a state of upheaval, causing interest
rates to spiral downward worldwide (The Economist, 2013b). Jobs disappeared, consumerism
plateaued, wealth evaporated, and the global economy came to a near standstill. Concurrent with
sharply rising unemployment rates in the United States, which peaked at 10 percent in October
2009 (Rich, 2013), owning property of any sort became an expense many people could not
afford.
As a way to make daily costs more affordable, start-up companies began creating
business models on the principles of a new trend: the sharing economy (The Economist, 2013c).
The sharing economy is based on the idea of collaborative consumption (Botsman & Rogers,
2010), in which every individual can borrow or rent assets owned by another person, which
enables on-demand access for a price (Radcliffe, 2014; The Economist, 2013d). In the sharing
economy, private goods or services are suddenly transformed into club goods (Buchanan, 1965;
Olson, 1965), where ownership is rented to any paying customer. The sharing economy replaces
the value of ownership in the market economy with the value of access (Rifkin, 2001) by pooling
the resources of the crowd. Start-ups-turned-corporations, in areas such as home rentals
(AirBnB) and chauffeured transportation (Lyft), have profited immensely from the new
dynamics of the sharing economy. Some argue that collaborative consumption in the sharing
economy provides a social safety net based on trust (Tanz, 2014) and spreads cost and risk of
31
ownership over larger pools of people (Rampell, 2015). Others call the sharing economy a form
of “disaster capitalism” for its lack of consumer protections and labor regulations (Le Tellier,
2014). The new “crowd-based capitalism” (Sundararajan, 2016) shifted day-to-day economic
activity paradigmatically.
Emerging companies of the sharing economy were driven by the rise of two concepts that
predated the recessions and were enabled by technology: crowdsourcing and crowdfunding.
Crowdsourcing brings together people with a variety of knowledge and resources to produce
information toward a common goal through an online platform (Castells, 2009, 2010a; Howe,
2006; Surowiecki, 2005). Companies such as Threadless and Innocentive, and Amazon’s
Mechanical Turk service, have thrived based on the creative production of the crowd (Brabham,
2013). More specifically targeted to financial contributions, crowdfunding is “the practice of
funding a project or venture by raising money from a large number of people, each of whom
contributes a relatively small amount, typically via the Internet” (crowdfunding, 2007). Both
crowdsourcing and crowdfunding utilize large networks of people to solve a problem through
contributions: information for crowdsourcing and money for crowdfunding. Crowdfunding
websites such as GoFundMe, Kickstarter, Indiegogo, and Kiva have served as platforms for
fundraising in exchange for small incentives or rewards on projects across several industries
(GoFundMe, 2016). As part of a larger policy trend to help spur economic growth in the United
States in the recession’s aftermath, the Jumpstart Our Business Start-ups (JOBS) Act became law
in April 2012 to ease securities regulations and enable funding of U.S. small businesses. Title III,
the Capital Raising Online While Deterring Fraud and Unethical Non-Disclosure
(CROWDFUND) Act, allows companies to use crowdfunding to issue equity or securities in
32
exchange for monetary contributions, and industry analysts devoted attention to its impact on
technology start-ups (Robles, 2012).
In sum, in a challenging global financial landscape between 2007 and 2010, the sharing
economy emerged based on relatively recent innovations: gathering the crowd online, rethinking
the market economy, and policy on crowdfunding. The public began to trust many activities
online, including collaboration about ideas with other people they had never met and fundraising
toward a goal by sending money through platforms. With the backdrop of the recession, and
keen interest in innovations to generate wealth, the stage was set for an introduction of the
platform’s technology.
The Technology
In the wake of the recession around 2009, the ideas of grouping people together,
contributing money online, and owning a small piece of a good all came together as the Chief
Executive Officer (CEO) and Chief Technology Officer (CTO) began discussing the formation
of the CoWealth company and development of the platform. Their idea was not crowdfunding by
definition, but an innovation on the concept—groupfunding—whereby small groups of people
could invest in purchasing a property together. Busy with full-time jobs in other technology
companies, they continued to ideate on CoWealth until 2015 when another founder joined, the
Chief Engineer. A timeline of the ideation and gestation phases of CoWealth and data collection
is presented in Figures 3.1, 3.2, and 3.3. The CEO and CTO had worked together in a previous
start-up together, and the CTO and Chief Engineer had worked together previously in another
company, but this was the first start-up they had all started together. By October 2015, the
founders stated the company’s mission in an investor slide deck: “to enable the sharing economy
for millennials and the diminishing middle class to foster their economic growth” through
33

Figure 3.1. CoWealth Ideation Phase Timeline 2009-2015.

34

Figure 3.2. CoWealth Gestation Phase and Research Timeline August 2015-February 2016.

35

Figure 3.3. CoWealth Gestation Phase and Research Timeline March 2016-April 2017.
36
collaboration online for property investment (CoWealth, archival document, 2015). The platform
would be developed to support this mission and, as of the submission of this manuscript, the beta
version was launched with public access in April 2017. The platform was designed and built by
CoWealth with guidance from the founders and the help of employees, contractors, and user and
investor feedback. There were several opportunities to assess the discussion that occurred within
CoWealth about the direction of the company as realized through the development of the
platform. The purpose of this study was to accurately depict the development of CoWealth as a
company with a larger aim of also studying the development, implementation, and use of the
platform. The data on technology strategy presented here captured only the beginning stages of
the platform development. Data on the platform’s implementation and use is currently being
collected in order to continue to develop my research on CoWealth.
The central idea of the platform technology was that people would group together online,
whether or not they knew each other personally, and make a property purchase together. Users
were first sorted by selecting their market (e.g., Startupsville, Middle America) and then
neighborhood, or one of the three investment concepts to pursue: Rent Ready, Flipping, or
Improvement Income. Next, users would search for groups that already had leaders directing a
property investment and join as a follower, or start a group of their own to lead and pitch their
investment deal to other users. CoWealth did not own the properties that were available to users
to search. Instead, the search database of properties aimed to use real-time market data on
properties similar to or drawn from common multiple listing services (MLS) that real estate
brokers use to share basic information about available properties. Although properties shown in
the search results were associated with the preferences that users described, such as within a
price range or an estimated return on investment percentage, the groups that formed were
37
separate from the exact properties on the market. Formation of a group based on investment
goals rather than investment in a specific property prevented market turnover from dissolving the
group and forcing members to start a new one.
The public-facing landing website launched on October 28, 2015, but revealed little about
CoWealth beyond its basic property investment idea. For the majority of data collection during
this study, the platform was not fully operable and in stealth mode, meaning it was not fully
accessible, and indeed was intentionally hidden from potential users, competitors, and the
general public until a beta launch because of its highly competitive market (stealth mode, 2016a,
2016b). Stealth mode is a standard phase in start-ups from ideation to a fully operating company,
and does not preclude management from speaking generally about the company to media or
investors in preparation for a successful launch (Lagorio-Chafkin, 2014). Four select users were
invited to join an investment opportunity for one property in Startupsville, Middle America for a
proof of concept outside of the platform using emails and phone calls to manage the deal. Proof
of concept is a demonstration to verify that the principles that undergird the idea work with real
world application among the target user population, showing feasibility (proof of concept, n.d.).
After several groups of people had closed on investment properties together by July 2016, the
proof of concept had been achieved with enough sample cases to proceed. Development on the
platform moved toward realizing the CoWealth vision, but as the founders encountered new
challenges during the proof of concept and subsequent stages, the vision shifted, resembling a
moving target more than a finite endpoint to build a minimum viable product. In accordance with
the lean start-up (Ries, 2011), a minimum viable product is a version of a new product, in this
case the CoWealth platform, with just enough features to gather validated learning about
customers (Ries, 2009). The development of a minimum viable product is a gradual process of
38
change, but progresses from a product that works with minimal features, like a skateboard or
scooter, to a product that works with a larger number of features, like a motorcycle or car
(Kniberg, 2016). An analogy for the changing goals in the development of CoWealth’s product
would be running a marathon with a planned course for which you’ve trained, but having the
course change and new challenges arise on the way to a new finish line that might shift again.
Thus, the product’s “definition of done” morphed as the organization gleaned more information
about how to direct its growth. Iterative redesign of the platform’s looks and workflow
developed over the next several months, both of which were subject to several changes.
CoWealth began offering a few trusted users a selection of property investments in Startupsville,
Middle America through a minimalistic platform interface in August 2016. The company
expected to offer at least 10 properties in two or three U.S. cities by its public platform launch in
April 2017. The company achieved offering several properties, but not 10, in only one city,
Startupsville, by its launch.
The Organization
Groups are important at CoWealth not only because they are the foundation to evolving
its technology and innovative funding paradigm, but also because the organization of CoWealth
is the size of a group at its start. My initial entrée into the company was an introduction by a
board advisory member of CoWealth. CoWealth was a small, growing, but globally-distributed,
early-stage high-tech start-up organization headquartered in a city I refer to throughout this study
as Start-up Capital, California in Silicon Valley. Most of CoWealth’s workforce was located
between San Francisco and San Jose, California, also known colloquially as Silicon Valley.
Many but not all of the people involved in CoWealth, including the three founders, shared a
39
cultural background and were bilingual in English and their arterial language. The company was
then in the development process for its platform.
During the fall of 2015, I interviewed the three founders of CoWealth through Skype
phone-conferencing, and they told me about their plans for the platform. A timeline of
CoWealth’s development and The technology of the platform seemed interesting: it was a new
concept for groupfunding, or getting a group of people together to invest in a real estate property
based on the ideas of crowdsourcing and the sharing economy. The founders believed that the
technology would enable wealth generation after a recession. The company was in the beginning
stages of development. The CEO imbued social responsibility into the start-up vision with the
immediate plans of helping millennials recover in a poor economy, and long-term plans to create
a non-profit foundation that would help create affordable housing. Similar to other strong female
leaders (Stelter, 2002), the CEO had an intention to create a company with an emphasis on the
value of relationships and other people, both in structure and function. After some preliminary
interviews with the CoWealth founders, I determined that the CoWealth platform would be an
ideal subject of study for my research on the relationship between innovation management and
organizational growth. The platform’s development would coincide with my data collection for
this study, although the major implementation event, the public launch in April 2017, would be
reserved for future research. The platform was specifically designed to change real estate
investment, and because CoWealth provided a natural laboratory in which to observe the
management of people and technical resources in the platform’s development, the research
seemed promising. The data on business strategy presented here captured the establishment of
the CoWealth company in its start-up phase.
40
CoWealth had completed early stages of investment funding with 11 investors by the
conclusion of data collection. The funding rounds completed included bootstrapping or self-
funding, where all three founders contributed money, and founder, friends, and family funding,
where eight people close to the founders contributed money (Conti, Thursby, & Rothaermel,
2013; Root, 2016). The company completed these two initial rounds of funding in June 2015 and
raised $1 million USD. The start-up began a campaign for seed funding, or the first round of
raising outside capital from angel investors and venture capitalists, and bridge funding, raising
money from existing investors, in May 2016; this round of funding had not finished at the
conclusion of data collection for this research. A Series A round of funding, or the first
significant round of venture capital funding where class A stock in the company is sold in
exchange for investment (Series A financing, n.d.), and used by the company to optimize the
product and user base (Delventhal, 2015) was slated to begin in the first calendar quarter
between January 1 and April 1, 2017. Although the October 2015 plans outlined the official beta
launch for the second quarter of 2017 with properties in 10-20 major U.S. markets and global
membership on the platform (CoWealth 201510 slide deck), CoWealth had expanded its
investment concepts and would likely introduce investment opportunities in two or three markets
to its users by that time. The company was not yet listed on Crunchbase, a publicly accessible
database of start-ups in different stages of development managed by TechCrunch, at the
conclusion of data collection or submission of this manuscript. The exclusion of CoWealth from
Crunchbase meant that its stealth mode was successful, as the start-up was not widely discussed
in tech circles.
The founders, employees, and contractors at CoWealth’s office in Start-up Capital,
California were responsible for the design and development of the platform that allows people to
41
form groups, contribute money to a collective account, and use that money to co-purchase and
own real estate property. Broadly speaking, start-up roles at the CoWealth office were divided
into two general specialties: business strategy and technology strategy. The founders often noted
that they “wear many hats” in the data, in that the duties associated with certain roles are not
necessarily exclusive. The business strategy was managed by the founding Chief Executive
Officer (CEO) and supported by a wholly owned subsidiary property management company, a
business development employee, a leading user, and a set of contractors ranging across legal
counsel, accountants, company investors, realtors, and property managers. The CEO guided the
company's direction, including operations, business development, finances, revenue generation,
sales and customer service, product and content marketing, advertising plans, recruiting
personnel in everything except technical specialties, and the company culture. CoWealth
established a subsidiary property management company—PropertyPros—to manage the legal
documentation, property insurance, and day-to-day maintenance of the properties in which users
had collaboratively invested. The acting PropertyPros Chief Operating Officer (COO) and the
business development representative were often located at the CoWealth office to assist the CEO
in managing customer service.
The second specialty in CoWealth was the area of technology strategy. The technology
strategy was managed by two founders, the CTO and the Chief Engineer, and supported by back-
end developers, front-end developers, user experience (UX)/user interface (UI) designers, and a
quality assurance (QA) tester. The CTO coordinated the technology strategy with the business
strategy, monitored technology trends to keep the company’s product relevant, and conducted
user experience (UX) research on user needs to direct a natural flow through the platform. The
Chief Engineer managed the product by creating production requirements to maximize the
42
business value, recruited personnel in technical specialties, and worked with back-end
developers, front-end developers, and user interface (UI) designers to fulfill those needs. Back-
end developers construct the scaffolding of the platform by gathering requirements, writing code,
and proposing solutions across areas such as algorithm queries, database management, and
security encryption. Front-end developers create and maintain the visual display of the platform,
implementing the design with code and proposing solutions to issues as they arise. User
experience and user interface designers focus on developing the best possible user experience by
thinking through the product flow from one webpage to the next and also creating the layout of
each individual screen with consistent visual elements. In what is usually one of the last steps,
the quality assurance (QA) tester analyzes the implemented product to discover flaws and
suggests improvements before the platform launches and is publicly accessible. QA serves the
function of making sure that stopgaps are removed in favor of more in-depth functionality.
I constructed CoWealth’s organization chart at different time intervals of the study,
presented in Figures 3.1-3.5. The charts represent the period before the study (pre-September
2015), the first seven months (September 2015 through March 2016), the following four months
(April through July 2016), and the final two months (August and September 2016). The chart
intervals are uneven in time periods because the focus of analysis was not on fiscal or calendar
quarters, but on significant shifts in the company structure over time. I checked these
organizational charts with the CEO and Chief Engineer to be sure that they matched the
organizational structures at those times. Most of those represented on the chart became
informants. Because the company was small and informants often mentioned others that engaged
in work but were not necessarily co-located, it is imperative to display on the chart the entire
contracted network of people and companies CoWealth brought in to assist with its work. Many
43

Figure 3.4. CoWealth organizational chart September 2015.
During this period, the founders evaluated the implications of the Crowdfund Act while they were in stealth mode. The founders
began visiting properties in Startupsville in mid-December.

44

Figure 3.5. CoWealth organizational chart September 2015 through March 2016.
During this time, the start-up was in stealth mode developing its pilot. CoWealth had rented headquarters space in an incubator.
Differences of vision between the founders emerged and the work was focused on a proof of concept as well as developing algorithms
for the platform.
45

Figure 3.6. CoWealth organizational chart April to July 2016.
46
During this time, CoWealth was undergoing significant redesign while the CEO traveled extensively for fundraising. As the product
development was expanding into mobile application development, the start-up contracted a realtor in Startupsville to begin creating
inventory for the platform.

47

Figure 3.7. CoWealth organizational chart August to September 2016.
The exit of the CTO meant significant restructuring for CoWealth and a new set of redesign plans were developed for the platform
launch.
48
other individuals, groups, and companies with which CoWealth engaged in its search for growth,
such as people interviewed for personnel positions or a consultant involved in establishing a joint
research center with another company in another country, are not included. The names of the
company, its platform, its affiliations, groups, and people are disguised to protect the company’s
confidentiality. Throughout this manuscript, I refer to specific people or companies who reappear
using either their job title and description or a given name, in which case I have assigned a
pseudonym.
Ethnographic Methods for Longitudinally Studying Rapid Change
The logic of inquiry I employ in my organizational ethnography is the extended case
study based on the methodological standards of groundedness, interpretive validity, and
theoretical imagination (Lichterman, 2002). Case studies have the potential to provoke new ideas
and build on existing theories (Siggelkow, 2007; Eisenhardt, 1989a), and this study approaches a
specific case that has been selected with an understanding of the case as a theoretical construct to
illuminate theory improvement (Ragin, 1992; Stake, 1995). Ethnographers negotiate anonymity
and confidentiality in multiple ways, and a plan of agreement was necessary for this research. I
approached CoWealth founders about whether to anonymize their company after the first few
unstructured interviews. It was agreed that the research would be confidential for the dissertation
manuscript. In the paragraphs that follow, I review my data collection; the standards of
groundedness, interpretation, and theoretical imagination as employed in this research; and
introduce a methodological innovation that I refer to as punctuated ethnography method.
Distinct from research that involves predictive hypotheses, “ethnographers collect data
without always knowing its meaning or significance in advance” (Boellstorff et al., 2012, p. 83)
and undertake an iterative process of thematic analysis after data collection (Charmaz, 2014;
49
Saldaña, 2016; Strauss & Corbin, 1998). I incorporated in-person and virtual data from a range
of data sources to capture elements of the start-up in its ongoing activities. Building on the
peopled ethnography model proposed by Fine (2003), which focuses on small group
ethnography, this study focused on a group of founders, engineers, designers, and investors
(Brown-Saracino, Thurk, & Fine, 2008). Rather than observing interactions only in person, as
with traditional ethnography, or observing only digital communication through the Internet, as
with netnography (Kozinets, 1998), I combine the two methods. Members of the start-up were
dispersed geographically, but used several technologies to interact and coordinate to pursue a
common objective. I used network ethnography (Howard, 2002) or connected ethnography
(Hine, 2015) to capture these online interactions. The documentary traces that users leave when
using systems to design and develop were captured using the method of trace ethnography
(Geiger & Ribes, 2011). Trace ethnography examines the metadata information about the
sequence of user actions and events in an online space to analyze behavior and communication
as an ethnographer would in the offline world. For the online observation components of this
study, traces of users’ interactions with each other and with the platform were imperative for a
holistic representation of the CoWealth case.
Using the extended case study logic, I constructed social-scientific arguments grounded
in multiple types of qualitative data and approached my setting with theoretical preconceptions.
Ethnography is “a holistic project [in which] we seek to understand shared practices, meanings,
and social contexts, and the interrelations among them” (Boellstorff, Nardi, Pearce, & Taylor,
2012, p. 67) by observing, recording, and analyzing everyday activities captured in written field
notes (Emerson, Fretz, & Shaw, 2011). During data collection, I maintained enough distance as a
“professional stranger” (Agar, 1981) to stay attentive to the mundane flow of action. I separated
50
field notes from personal reactions and insights to include them alongside more general research
notes (Boellstorff et al.,2012, p. 86). In the chapters that follow, I present empirical evidence
from my observations to ground claims I make about what people said or did at CoWealth. The
detail I provide about how CoWealth members lived and worked together as shown through
experience-near data (Geertz, 1974; Kohut, 1978) bolsters my interpretive validity.
To develop interpretation, I created conceptual categories during analysis of the data.
These categories captured my interpretation of how people at CoWealth made associations to
organize experiences and interactions between people and other people, between people and
ideas, between people and places, and between people and things. The validity of my
interpretations emerged from their iterative and evolving nature during data collection. I tested
interpretations by creating explanations about the interactions I had observed, and attempted to
find evidence that confirmed or denied these understandings during the next observation. Watson
(2012) notes that “we can only create successful organisational ethnographies if, in every study,
we give full consideration to the broader ‘social organisation’ as well as to the more local
‘formal organisation’” (p. 17). In other words, organizational ethnography should recognize
society and culture within and around formal organizations. Watson (2012) also proposes that an
“organisational ethnographer should approach the field equipped with a bank of conceptual
resources…theoretical concepts are ingredients that go into the ethnographic mix, alongside and
in interaction with observed fieldwork episodes and recorded/remembered utterances and
conversations” (p. 19). My emic conceptual categories, based in the language particular to
CoWealth, enabled more etic generalization, in the language of the scholarly community, to
theories about groups and companies encountering change or in the early stages of development
51
(Pike, 1967). Rather than a singularly inductive approach, theoretical perspectives were
incorporated deductively into the interpretation and analysis of data collected.
Finally, my research relied on theoretical imagination to link the people and activity at
CoWealth to an interesting social science conversation through the extended case method. Using
CoWealth as the site of study, the conversations I join are about organizational disengagement
and transactive memory development. The representation of social reality and culture in the start-
up implicated my perspective in what was studied and discovered, and as such, used the voice of
the confessional tale in reporting this organizational ethnography research (Van Maanen, 1988,
2011).
Punctuated Ethnography
Watson (2011) draws attention to the need for ethnographic process research in
organization and management studies. Longitudinal ethnographic research is a deliberate and
disciplined undertaking (Barley, 1990). Historically, ethnographers spent a year in the field to
become fluent in the culture they were studying, but contemporary fieldwork in a familiar
language or well-known field site may be completed in less than a year as long as the research
timeline fits “the temporal structures of those we are studying and their activities” (Boellstorff et
al., 2012, p. 88-89). The research in this dissertation included shorter time periods of systematic
observation to study CoWealth through a new approach I introduce here: punctuated
ethnography. Punctuated ethnography proposes to undertake a systematic recording of culture,
but rather than carrying out observations at a field site for an uninterrupted extended period of
time, visits are planned at specific time points and supplemented with other data types to capture
dynamic change. In practice, this method means that researchers observe changes in groups and
organizations at a pace that matches development in those entities. Observations should be paced
52
to match the rate of change in the subject under study: change in co-located dyads may occur
more quickly than in large, multi-national corporations. Within the context of a globally-
distributed start-up, punctuated ethnography meant that I physically stepped into the organization
at regular intervals (at least once a month), but also observed weekly meetings and online
communication systems remotely, and initiated weekly calls with founders to capture meanings
that would not appear if I only observed face-to-face interaction. Periodic observations in both
in-person and online contexts allowed an understanding of the start-up’s complexities in a frame
that revealed challenges and achievements over time and across mediums. I paired traditional
ethnography with netnography (Kozinets, 2010) to understand the start-up as it changed. My
window of punctuation included the time before, during, and after a moment because it was
important to capture not only the event but also the rumination surrounding it as people made
sense of processes and events occurring in the organization. My observation data crossed modes
because I followed the impact of decisions and changes in members’ conversations, which
occurred in-person and online. In some instances when I learned of a significant event
retrospectively during one of my observations, I would jot down in my observation notes to ask
further follow-up questions and pursue an understanding of how members responded to and
thought about the event, punctuating the ethnography with a focused inquiry.
CoWealth Development Activities
The three CoWealth founders granted me access to observe the management of its
organization and development of its platform. I initiated weekly interviews with the CoWealth
founders starting in September 2015. I arrived at the CoWealth office for the first time in January
2016 and spent several days observing the work of the founders and their contractors. During this
initial foray into the observation portion of my data collection, I observed a highly creative group
53
of experts who contributed their work, through several collaborative technologies, to a vision
that shifted with continued development.
The circumstances necessitated using a few techniques to collect data that would allow
me to understand the relationship between technological and organizational growth. The data
sources were (1) unstructured and semi-structured interviews, (2) participant and non-participant
observation, and (3) archival data. As I hope the following pages make evident, two features of
the research design proved particularly beneficial in bolstering validity through interpretive
analysis: the triangulation of participant with non-participant observation and with interviews
and archival documents (Eisenhardt, 1989a). The data set resulted in a corpus of 4,211 minutes
of transcribed recordings. Engineers who were not involved with the start-up or my sample
helped interpret start-up or coding jargon throughout the study. The bulk of the quotations and
excerpts from field notes are presented verbatim in this manuscript. When I corrected grammar
or added words, I indicated my changes in brackets. Some quotations were truncated from the
original excerpt, and others were rewritten to improve readability.
I tracked three co-founders, three employees, 10 contractors, two contracted design firms,
and four advisors in addition to the larger network of people and companies upon which
CoWealth relied. In line with bona fide group theory (Putnam & Stohl, 1990), observing the
group beyond the formal organizational boundaries enabled an understanding of the dynamics of
the firm’s rapid change at these early stages. I included anyone involved with the start-up as long
as they stayed active on projects with the start-up, and tracked when they joined and left as best I
could.

54
Interview Data
Using a combination of unstructured and semi-structured interviews, I collected data
about the start-up for a period of 12 months beginning in September 2015. Interviews were
conducted to compare what people “say they do,” or beliefs and opinions, and “what they do,” or
actions, noted in participant observation (Boellstorff et al., p. 92).
Unstructured interviews. I began the interview process with recurring weekly virtual
conference calls with the three founders in September 2015 through the Skype phone
conferencing application. I interviewed the founders together about progress made each week.
Sometimes an advisor joined the interviews to provide additional insight. I conducted these
unstructured interviews each week for 52 weeks, or 12 months, beginning on September 3, 2015
and ending on August 30, 2016. Interviews did not occur during weeks in which the founders
were not available or field visits were made, resulting in 37 interviews that varied in duration
between 15 and 64 minutes (M=42.81, SD=14.04). All of these interviews were recorded on a
computer recorder with the consent of the informants and the total 1,541 transcribed minutes
were used as raw data for analysis. Table 3.1 summarizes the unstructured interviews, including
the date, informants present, and the length of each interview.
The interviews did not have a systematic guide but generally began with the same starting
point: a review of activities in the start-up since the last call or field visit. Before each interview,
I reviewed my notes during the previous interview to bring up projects mentioned, and
constructed questions for the interview. Interview questions focused on events that occurred
during my absence, as these interviews supplemented participant and non-participant
observation.

55
Table 3.1.
Unstructured Interviews with Founders and Board Advisor.
Informants Present
Date CEO CTO Chief Engineer Board Advisor Length (min.)
2015
September 3 X (not recorded)
September 22 X 48
October 8 X X X 28
October 20 X X X 58
October 29 X X 49
November 12 X X 19
December 3 X X 46
December 11 X X 28
2016
January 6 X X 59
January 13 X X X 59
January 20 X X 25
January 27 X X 53
February 3 X X X 52
February 10 X 19
February 17 X X 47
February 22 X X 64
February 24 X X X 50
March 2 X X X 45
March 10 X X X 21
March 17 X X X 37
April 6 X X X 58
April 13 X 36
April 20 X X X 57
April 27 X X 36
May 11 X X X 52
June 1 X X X 56
June 15 X X X 25
June 22 X X 52
June 29 X X 25
July 13 X X 58
July 20 X X 33
July 27 X X 49
August 3 X X 46
August 17 X X 57
August 24 X 33
August 29 X 15
August 30 X X 46

56
Semi-structured interviews. I began the semi-structured interview process by
identifying informants: each founder named other people involved in the network of the start-up.
My method was purposive sampling, where I selected people to be included in interviewing
according to the heterogeneity that they brought in offering a diverse set of ideas from
CoWealth’s network. As will be discussed in upcoming chapters, start-ups often have a broad
network of contacts across a range of specialties whom are involved at various levels of
participation. Contact information for employees, contractors, partners, investors, and contracted
firms were requested from the CEO and other founders. Because I had started collecting data at
the beginning of the start-up’s development, I was able to capture all individuals involved
directly in the start-up. Because a start-up network often changes, however, some contacts that
were very casually involved in the start-up were not interviewed. Using this method, I
interviewed the founders twice, and all other informants once. I conducted interviews with
informants at one design firm that contributed to designing the platform. I also conducted several
interviews with other people who were not members of CoWealth but had invested in the
company or were users of the platform (and sometimes both). They were users of the platform in
that they had completed the proof of concept with the company, but hadn’t actually used the
platform. Table 3.2 provides a summary of the interviews I conducted with each group and the
number of informants interviewed. I conducted 24 interviews with 22 informants: the three
founders (two interviewed twice), two advisors, eight developers, three PropertyPros employees,
three designers, one accountant in finance, one language consultant in sales and marketing, and
one user.
In each interview, I sought from informants their view of the development occurring at
CoWealth and its platform. The interview protocol was nearly identical for all participants,
57
Table 3.2.
Summary of Semi-structured Interviews Regarding the Development of CoWealth, Inc.
Group interviewed
Founder Advisory
Board
Development Property
Management/
Falcon
Design Finance Sales &
Marketing
User Total
Number of interviews 5 2 8 3 3 1 1 1 24
Number of informants 3 2 8 3 3 1 1 1 22
Note: One of the designers counted above was an account manager the design firm contracted by CoWealth. One of the property
management persons was an independent real estate agent in Startupsville, Middle America.
58
except for the founders, who received an additional set of questions, and two of whom were
interviewed twice, once at the beginning of the interview data collection and once at the end of
the study. I began each interview asking about their impression of CoWealth, including its
mission, its origin story, its connection to technological trends, and their vision of its future.
Next, I asked about the nature of their work, the way in which they found the company,
collaboration and information sharing in their work, and their impression of the company’s most
important priorities and improvements. Finally, I asked informants about their employment and
professional background, formal education or training, and ongoing self-education efforts on
topics related to their work at CoWealth. Founders were also asked about the motivations for the
foundation of CoWealth (mission and vision), hiring practices for the growth of the organization,
and design choices made about the platform and partners. Appendix C provides the interview
guide. Using these questions, I aimed to uncover the shifting structure of relationships to work in
the start-up, their feelings about management of innovation, and their aspirations for the
platform.
Most interviews were conducted on-site in the start-up’s office and recorded on a digital
voice recorder, though some were conducted on a phone call via the Skype application and
computer recorded; all were recorded and transcribed with the consent of the informant, with the
exception of four informants who preferred not to have their interview recorded. In these cases, I
took notes as close to verbatim as I could during those interviews. The interviews lasted from 18
to 91 minutes (M=45.96, SD=19.46) and the total 1,103 transcribed minutes were used as raw
data for analysis. An initial round of interviews were conducted between January 15 and January
27, 2016 with everyone but the CEO, one PropertyPros employee, two developers (Lily and
Pamela), one legal advisor, and one board member, but all were observed in interaction. Another
59
set of interviews occurred between June 6 and August 29, 2016. For two of the founders, I
conducted interviews at the beginning of interview data collection in January 2016 and at the
close of the study at the end of July or beginning of August 2016.
Observation
Using a combination of participant and non-participant observation, I captured
observations of the start-up for a period of eight months beginning in January 2016. The
naturalistic research of ethnographic observation “depends on patient, careful and imaginative
life study” (Blumer, 1954, p. 10) with “specific, objective bench marks” (p. 9). Participant
observation requires the acknowledgement of my own subjectivity in the data collection. During
participant observation, I engaged in ongoing activities with informants. In non-participant
observation, I did not take an active part in the situations I observed. I was often able to digitally
record interaction captured during both types of observation. I documented events and my
observations of them in field notes in accordance with Emerson, Fretz and Shaw (2011), jotting
notes of key words and phrases, writing field notes that described the physical context and
behavior of people involved, and journaling my personal reactions and assessments, including
methodological notes about carrying out the research.
Participant observation. Participant observation occurred in a few settings, but I
focused mostly on the work done in CoWealth’s office, located in an incubator. An incubator
provides a supportive environment for start-ups with physical resources—such as flexible rental
space and leases, shared administrative services, and equipment—and social networks of
business and technical advisors for assistance in finance, business planning, marketing, legal
consulting, and development or manufacturing (Peters, Rice, Sundararajan, 2004). CoWealth
took advantage only of the office management resources provided by the incubator, such as the
60
office space and the conference rooms, relying on its own social networks of contacts for the
development of its business and platform. Although it was housed in an incubator, CoWealth
used its leased space as if in a generic office building and did not seek out mentors or guidance
from the incubator. Other settings of participant observation data collection were carpool trips on
the way to or from the office, and the surrounding area between San Jose and San Francisco on
visits with founders to relevant locations, or with contractors and investors that work with the
start-up.
I made several field visits to CoWealth, either once or twice a month, beginning in
January 2016 and continuing through August 2016. I opportunistically joined meetings, phone
conversations, social functions, and training sessions. During the 8 months, I produced 56 field
note documents of 173 pages of text. Another source of field data was the transcripts of founder
planning meetings, together or separately with staff and advisors, which were audio-recorded in
the field. Recordings included in the dataset were those made during the seven months between
January 3 and July 6, 2016 when all three founders were present; the CTO exited the start-up at
the end of July before the final field visit. In total, 30 recordings were captured that varied in
duration between 5 and 160 minutes (M = 52.33, SD = 44.75). All of these meetings were
recorded with the consent of the informants, and the total 1,567 transcribed minutes were used as
raw data for analysis. Occasionally, there were significant events in the area that CoWealth staff
attended. One of these was the one-day AirBnB annual tech conference, OpenAir, on June 8,
2016 that reviewed new developments in the company’s platform, but also sought to generate
conversation with speakers of Taskrabbit, Cisco, Affirm, and Fin on topics such as the future of
work and reputation, technology trends, and research on trust. The CTO, the Chief Engineer, the
algorithm developer, and the business development representative attended.
61
Non-participant observation. During observation periods in which I played no active
role, I took field notes and digitally recorded interactions via a virtual recorder for phone and
video conferencing. There were two separate threads of development activity that I observed:
specific design meetings, which focused exclusively on building the look and feel of the
platform, and the more inclusive product development calls, which included everyone working
on the platform.
Design meetings occurred at two time points and covered two different projects: the
public landing website that everyone can see and the internal platform users see after they log
into the website. When the design firm began their design work on the outward-facing corporate
website for CoWealth in May 2016, I was able to join an initial call where the founders talked
with the account manager at the design firm about the scope of work. I continued to get updates
about the design firm’s work during my field visits. The second group of design meetings
occurred after the design firm was no longer a contractor, and CoWealth’s focus shifted to a
redesign of the internal platform instead. CoWealth had hired a new UX/UI designer in August
and by mid-month had a series of calls about the redesign that were frequent, about every other
day. I recorded five of the redesign meetings between August 16 and 28, 2016, which were
between 14 and 44 minutes (M=26.40, SD=11.41), and the total 132 minutes were used as raw
data for analysis.
Product team meetings were usually initiated by the Chief Engineer via Skype for the
entire team to join, including members located in other countries. These weekly development
video conference calls were the touch point of a sprint, a one- or two-week repeatable work
cycle in the Scrum method of Agile software development (Rising & Janoff, 2000; Schwaber,
2004). During these calls, a retrospective, a discussion of positive and negative feedback on
62
process during the previous sprint, was carried out before moving onto sharing screens to
consider next steps in development or teach others about an aspect of programming functionality
(Ambler, 2013). The development meetings began in early April 2016 as the Chief Engineer
began to direct more of the technical team for product development. I recorded these videos
beginning on April 25 through August 29, 2016 for a total of 14 calls, which were between 23
and 87 minutes (M=60.31, SD=16.07) and the total 792 minutes were used as raw data for
analysis.
Archival Data
During observation and interviews, informants drew diagrams and referenced
presentations to potential investors and users, documents on planning and trends, and emails
about work collaboration that were generated during the development of CoWealth’s strategic
direction and its online platform. During and after interviews or meetings, I asked informants
whether I could retain a digital copy or capture a digital image or screenshot of these documents.
When informants could not locate the documents to which they referred, I followed up a few
days later via email to acquire the documents. Many of my requests were fulfilled. When I read
through these documents, invariably other documentation was referenced and I would return to
informants to locate the additional material. During reviews of these documents, I developed
additional questions about the organization or the platform development, and I would note them
to ask to the founders in my unstructured interviews.
I analyzed more than 300 documents about the development of the organization and its
technology platform produced in several work tools. Documents on business strategy included
business plans, investor slide presentations, legal briefs, PropertyPros workflows, Startupsville
maps, trifold board sketches, property investor agreements, and employment contract templates.
63
Documents that were collected on technology strategy included development emails, usability
testing scripts, screenshots of the platform, feature specifications, and wire frame designs from
the design firm. These data revealed emphasis on certain issues and suppression of others in the
business strategy direction, and shifts in the concept of the technology and its visualization over
time. Additionally, screenshots of the platform were captured at various points in time to capture
changes in the platform user interface as different prototypes were developed. These were
designated as artifacts.
The work completed at CoWealth and with their contractors spread across several tools.
A total of 66 tools were referenced or accessed during interviews and observation about the work
processes of CoWealth. These tools each had their own technical vocabularies and interfaces
based on various levels of assumed expertise about users. CoWealth created this complex
infrastructure of many products because the start-up wanted to limit any unnecessary financial
expenditure; the tools were used within the free trial limits provided by the manufacturers of the
systems. A routinized pattern among the tools emerged, and despite its ungainliness, it operated
as a temporary mechanism for CoWealth. For communication, the start-up mostly relied on
Slack between team members, Chrome Gmail application for email, and Skype for video and
phone call conferencing. The central tools that the start-up referenced in collaboration on internal
development included Zeplin for design mockups of the user platform, and Atlassian Confluence
and JIRA for keeping track of development. Another tool that CoWealth used for development
of the public website in collaboration with the design firm was Basecamp.com, which allowed
CoWealth to share design specifications and feedback, as well as the actual wire frame plans and
design preferences. Table 3.3 provides a summary of the tools, their described use, and
informants that reported them.
64
Table 3.3.
Tools Used in CoWealth Communication and Platform Development
Described Use
Development Reported by
Tool Collaboration,
Communication
Design Third Party
Library
Language Front-end Back-end CTO Chief
Engineer
Design
firm
Adobe PDF*
✔

Adobe Sign
✔
X
Basecamp
✔
X X
Cell phones
✔
X
Chrome Gmail
Application
✔
X
Confluence
✔
X
Dropbox
✔
X
Google Hangouts
✔
X
Google Sheets*
✔

Harvest.com
✔
X
IntelliJ
✔
X
Invision
✔
X
Jenkins
✔

✔
X X
JIRA
✔
X
Maven
✔
X
Microsoft Excel*
✔

Microsoft
PowerPoint*
✔

Microsoft Word*
✔

Sketch App
✔ ✔
X X
Skype
✔
X X
Slack
✔
X X
65
Table 3.3 cont.
Described Use
Development Reported by
Tool Collaboration,
Communication
Design Third Party
Library
Language Front-end Back-end CTO Chief
Engineer
Design
firm
Sync.com*
✔

Wunderlust.com
✔
X
Zeplin
✔ ✔
X X
Adobe After
Affects

✔
X
Adobe Illustrator
✔
X
Adobe Photoshop
✔
X
Flinto
✔
X
Keynote
✔
X
Paint Code
✔
X
Principle
✔
X
Quicktime
✔
X
Amazon Web
Services

✔
X
Apache Tomcat
✔
X X
Postgres
✔
X X
CSS/SCSS
✔
X X
HTML
✔
X X
Java
✔
X X
JavaScript
✔
X X
Python
✔
X X
R
✔
X
Shell scripts
✔
X
SQL
✔
X
66
Table 3.3 cont.
Described Use
Development Reported by
Tool Collaboration,
Communication
Design Third Party
Library
Language Front-end Back-end CTO Chief
Engineer
Design
firm
AngularJS
✔
X
Anjularjs
✔
X
Bootstrap
✔
X
Jasmine
✔
X
JSPM
✔
X
Karma
✔
X
npm
✔
X
Protractor
✔
X
Apache Java
libraries (e.g.,
commons,
httpclient)

✔
X
c3p0
✔
X
Flyaway
✔
X
Google APIs
✔
X
Guice
✔
X X
Hibernate
✔
X
Jacoco
✔
X
Jersey
✔
X
Junit
✔
X
Maven
✔
X
mockito
✔
X
Quartz
✔
X
Shiro
✔
X
67
Table 3.3 cont.
Described Use
Development Reported by
Tool Collaboration,
Communication
Design Third Party
Library
Language Front-end Back-end CTO Chief
Engineer
Design
firm
slf4j
✔
X
Swagger
✔
X
Note: *indicates tools that were not explicitly mentioned by an informant but were observed in use
68
The CTO mentioned five systems, nine collaboration tools, and five programming
languages used in his CoWealth work. The CTO reported that most systems they used relied on
the Java programming language, including Apache Tomcat as a servlet engine to support web
applications, Anjularjs and Bootstrap for front-end coding frameworks, Guice as a dependency
injection framework, and the Postgres database. The collaboration tools mentioned included
Atlassian JIRA, Confluence, Jenkins for building and continuous integration, IntelliJ for an
integrated development environment, Maven, Slack, Zeplin, Sketch, and Skype. Languages used
in the development were Java, Python, JavaScript, HTML, and CSS.
The Chief Engineer separated 15 tools for backend Java and six tools for frontend
JavaScript. For backend Java development, tools included Maven for project management, Guice
for inversion of control, Jersey as a REST API, Hibernate for object/relational mappings, Junit
for testing, Jacoco for Java code coverage, mockito for as a mock for testing, quartz as a
scheduler, Shiro for security, Swagger for interactive API documentation, c3p0 for connection
protocol, apache Java libraries (e.g., commons and httpclient), slf4j for logging, various Google
APIs for map, contact, and OAuth (Open Authorization), and Flyway for database migration. For
frontend JavaScript development, the Chief Engineer mentioned Angular JS, JavaScript Package
Management (JSPM), another JavaScript package management system needed by JSPM called
npm, Protractor for integration tests, Jasmine for unit tests, and Karma as a unit test runner.
Finally, the design firm account manager explained that systems in its work included nine
design tools and 11 collaboration and communication tools. Adobe Photoshop for mockups,
Adobe Illustrator for illustration, Adobe After Affects for Animation, Sketch App and Paint
Code for mockups, and Principle, Flinto, Quicktime, and Keynote for interaction prototypes. For
collaboration and communication, the design firm used Skype and Google Hangouts for client
69
facing video over internet protocol (VOIP) and video chats, Chome Gmail application for
primary external communication, Slack for internal team chat (and guest client accounts for
some projects), cell phone for client and internal communication, Adobe Sign for contracts,
Harvest.com for invoicing, forecasting, and time tracking, Basecamp.com for client facing
project management, Wunderlist for collaborative task management, Dropbox for client and
internal file sharing, and Invision for application design projects and sharing work in progress
with clients.

70
CHAPTER 4

Too Lean for Loyalty:
Managing Uncertainty and Tensions amidst Organizational Disengagement

This study focuses on an early-stage organization and tracks process and meanings
communicated before, during, and after organizational disengagement. A longitudinal 12-month
ethnographic research design presents three cases of exit in a Silicon Valley start-up: a design
firm’s termination of a contract, the dismissal of a founder, and the regular exit and reentry of
contractors. Tensions of contradiction, dilemma, and paradox in role performances of members
in the organization are examined as a precursor to organizational change and exit. During the
sensemaking process, informants reveal critical incidents and evaluation about role performance
as reasons for exits. Finally, the process of sensemaking about member exits is examined as an
uncertainty reduction technique that proceeds differently for members based on the
embeddedness of their role in the organization, and the impact of this process on resiliency of
the start-up is considered.
Keywords: Organizational Exit/departure; Organizational Socialization; Embeddedness;
Liminality; Role; Ambiguity; Workforce; Start-ups

71
Too Lean for Loyalty:
Managing Uncertainty and Tensions amidst Organizational Disengagement

To find a form that accommodates the mess, that is the task of the artist now.
-- Samuel Beckett, 1961
(Driver, 1961)
4

Organizational disengagement is a key construct that encompasses the process by which
members exit an organization (Jablin, 2001), and yet has received scant attention (Davis &
Myers, 2012). A difficult and stressful experience, the exit of a coworker produces uncertainty in
the organization at dyadic, group, organizational, and interorganizational levels. Both new hires
and veteran employees navigate the uncertainty of disengagement (Gallagher & Sias, 2009;
Miller & Jablin, 1991). Organizational members manage uncertainty by communicating about
the implications of change in the social fabric of their organization, including their roles,
relationships, and culture (Kramer, 2004). Sensemaking and sensegiving processes enable
members in the organization to interpret the meaning of exits and restructure coordination
(Gioia, & Chittipeddi, 1991; Weick, Sutcliffe, & Obstfeld, 2005). The sensemaking of
uncertainty generated by exits, however, may operate differently for exiting members and their
colleagues based on the embeddedness of their role in the organization, in turn generating
different tensions in organizational settings.

4
In this interview excerpt with a journalist from the Columbia University Forum, the expatriated
Beckett sits at a Parisian café across from a Roman Catholic church. He speaks about the tension
in art between mess and form in its organization and production. Fittingly, his observation
frames my chapter on organizational disengagement.
72
This study examines and articulates tensions in exits with an early-stage organization that
organizes around projects as work is completed (Weick, 1996). A framework of organizational
contradictions and tensions (Putnam, 1986; Tretheway & Ashcraft, 2004) is used to understand
the dynamics that enable sensemaking about exits. Findings are based on a 12-month
ethnography of a start-up organization in Silicon Valley from the beginning to end of its
gestation. The contribution of this study is twofold. First, it contributes a preliminary model that
combines embeddedness with exit and sensemaking. Second, it complements existing research
on organizational disengagement with qualitative field methods to tease out the tensions at play
in an early-stage organization. The next two sections explore research on organizational
disengagement, uncertainty reduction through sensemaking, and embedded and liminal roles,
followed by three research questions. I then discuss the research setting and methods, followed
by the study’s findings and implications.
Organizational Disengagement
Organizational socialization and membership negotiations in organizations have
generated a new wave of interest in communication, both in terms of theorizing (Dailey, 2016a,
2016b; Kramer, 2010; Scott & Myers, 2010) and new measures (Gailliard, Myers, & Seibold,
2010; Myers & Oetzel, 2003), though much of it has been concentrated on assimilation of
newcomers and role entry into organizations (Waldeck & Myers, 2008). Behind these
developments, three theories explain organizational socialization: uncertainty reduction (Kramer,
2004), social exchange (Cox & Kramer, 1995), and social identity theories (Ashforth, 2001).
Although communication can transform organizational environments to empower and retain
employees (Allen, 2016), communication used to manage uncertainty reduction may prove
unsuccessful (Kramer, 2004) and generate or increase the probability of member departures.
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Organizational socialization stage models have sought to explain the ways that members
understand, enter, assimilate, and depart from organizations (Jablin, 1987). The final
organizational socialization phase of exit has been theorized with two models of organizational
disengagement. Theorized from the perspective of a stayer witnessing a leaver’s exit, Jablin
(1987) proposed a linear 3-stage model that included a preannouncement, announcement, and
actual exit. Jablin (2001) clarified that his model examines only voluntary exit. From the
perspective of a leaver during the decision-making process to depart, Ebaugh (1988) proposed a
linear 4-stage model with doubts, weighing alternatives, a turning point, and creating an exrole
after the exit. These models have both been posited for voluntary exits (Jablin, 2001).
Most of the research to date examines voluntary exits, where the member leaves of their
own accord for reasons such as taking a new job, transferring, or retiring. When a person initiates
an exit voluntarily, the individual may not want have wanted to enact their role as communicated
by others and found a more appealing role elsewhere (Katz & Kahn, 1978). March and Simon
(1958) placed the catalyst for employee departure on the perceived ease and desirability of
movement in the decision to participate in an organization. Influencing factors and management
of the voluntary turnover of employees (Ballinger, Cross, & Holtom, 2016; Mossholder, Settoon,
& Henagan, 2005) and volunteers (Kramer & Danielson, 2017; Kramer, Meisenbach, & Hansen,
2013) continues to generate prolific research. The peer-influences coworkers use to encourage
voluntary turnover among peers includes avoiding communication to decentralize peers in the
organization’s communication networks (Cox, 1999) for motives of personal gain, altruism,
organizational enhancement, and climate improvement (Sollitto, 2014). In contrast, research on
involuntary exits, where members exit as a result of dismissal or restructuring because of a role
dispute, seems almost nonexistent. When an organization initiates an involuntarily exit for a
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person through termination, it may be because expectations of their role performance were
unfulfilled. Involuntary exits have received noticeably less attention, possibly because of the
performance sensitivity or personal nature of job dismissal.
People who depart the organization are leavers and those who remain are stayers
(Bluedorn, 1978). Research has probed stayers’ attitudes after colleagues depart (Krackhardt &
Porter, 1985), their intent to remain on a team (Bayazit & Mannix, 2003), and their job
involvement after layoffs (Brockner, Grover, & Blonder, 1988). Leavers, too, have been
examined as they transition out of the organization (Davis & Myers, 2012) or as a result of
termination, layoffs, and resignation (Steel & Lounsbury, 2009). A wide breadth of exit types has
been explored, including resignation (Cohen, 1993), retirement (Avery & Jablin, 1988; Cude &
Jablin, 1992; Feldman, 1994), and membership expiration (Davis & Myers, 2012; Dess & Shaw,
2001; Lee, Mitchell, Wise, & Fireman, 1996). However, the meaning of exits for employees who
are departing has only recently begun to receive attention (Rothausen, Henderson, Arnold &
Malshe, 2015), and the meaning of these exits for those left behind is rarely discussed (Cox &
Kramer, 1995).
In sum, few studies have examined organizational disengagement, and those that have
tended to focus on voluntary exits for those departing the organization. The meanings of
involuntary exits for both those departing and those staying in the organization have received
little attention.
Uncertainty Reduction through Sensemaking
Regardless of voluntariness, the entering and exiting of workers generates uncertainty for
the entire organization, both new hires and veteran employees (Gallagher & Sias, 2009; Miller &
Jablin, 1991). Uncertainty is the degree that situations are unpredictable or cannot be understood
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(Baxter & Montgomery, 1996). Organizational workers experience strategic, structural, and job
related uncertainty (Bordia, Hobman, Jones, Gallois, & Callan, 2004). Uncertainty Reduction
Theory suggests that uncertainty drives individuals or groups to search for information and
alleviate the aversive cognitive state (Berger & Calabrese, 1975). Accordingly, the uncertainty in
turn induces information seeking from supervisors, coworkers, subordinates, friends, and family
(Teboul, 1994), and the restructuring of work interactions to reduce uncertainty (Kramer, 2009).
Role expectations, norms, and organizational structure may become clearer as a result (Scott &
Myers, 2010). Different organizational members, such as veterans and newcomers, however,
may experience low motivation to retrieve information themselves due to their status in the
organization (Kramer, 1999). Uncertainty may also be different for voluntary and involuntary
exits. Members communicate to manage their uncertainty during times of organizational change
(Allen, Jimmieson, Bordia, & Irmer, 2007; Kramer, 2004, 2009). This study argues that a
component of this communication to manage uncertainty occurs through sensemaking.
Sensemaking is a process that occurs when individuals seek to understand and interpret past
enactments and construct interpretations to guide action forward (Weick, Sutcliffe, & Obstfeld,
2005). The central question driving sensemaking is, “how can I know what I think until I see
what I say?” (Weick, 1995). Sensemaking is (1) grounded in individual identity construction, (2)
retrospective about a past experience, (3) enacted whereby meaning is created through action in
environments, (4) social and mediated through talk, discourse, and conversation, (5) ongoing in
language and action, (6) focused on and by extracted cues, and (7) plausible rather than accurate
(Weick, 1979, 1995).
Organizational leadership must manage several employee stakeholder issues surrounding
full-time employee exits as a result of dismissal, termination, layoff, redundancy, and retirement
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(Clarkson, 1995). Other stakeholder issues inevitably arise during the turnover generated by the
exit of part-time, temporary, or contract employees. When employees fail to receive quality
information about the circumstances of change, they feel uncertain (Brashers, 2001). In the
absence of information communicated by management to dispel uncertainty, rumors become
associated with unsuccessful change communication (Covin & Kilmann, 1990; DiFonzo, &
Bordia, 1998; Smeltzer, 1991). Consequently, when faced with the uncertainty of turnover,
organizational leaders also engage in sensegiving to shape the sensemaking process and
interpretation (Gioia & Chittipeddi, 1991). Sensegiving is the process of influence “sensemaking
and meaning construction of others toward a preferred redefinition of reality” (Gioia &
Chittipeddi, 1991, p. 442). Founders’ experiences become organizational assets when they
distribute information about them, and also use them to interpret the ongoing context (Oe &
Mitsuhashi, 2013). For organizations engaged in knowledge work, environmental shifts or crises
are instrumental in the sensemaking processes that fuel creativity in organizational settings and
creative advances (Drazin, Glynn, and Kazanjian, 1999). Furthermore, organizations that favor a
particular capability may fail in their ability to adapt (Weick, 2005). The organizational leaders
both sensemake and sensegive the meaning of exits in the organization’s reality. While
sensegiving has been conceptualized in the context of a single organization taking leadership of
meaning construction, sensegiving can engage all relevant stakeholders (Weber, Thomas, &
Stephens, 2015). The processes of sensemaking and sensegiving are bound in dynamic
communication, and the process of change can be seen as a negotiation (Isabella, 1990) between
these modes of interpretation. Sensemaking and sensegiving are particularly useful for members
in navigating uncertainty associated with turnover as well as interpreting and redeveloping
strategy.
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Uncertainty dialectics in organizational disengagement are communicatively structured
and managed through tensions created by a diverse set of stakeholders (Putnam, 2003;
Tretheway & Ashcraft, 2004). Organizations become discursive constructions that build the
foundation of social reality (Fairhurst & Putnam, 2004). Ambiguity, a situation in which several
interpretations are plausible, can be managed strategically in an organization to enable serving
multiple interests (Eisenberg, 1984, 2007; Jarzabkowski, Sillince, & Shaw, 2010). Some tensions
that arise from ambiguity and uncertainty may be resolved. Communicative tensions that
contribute to sensemaking and sensegiving about uncertainty resulting from change include
dualities, dilemmas, contradictions, and paradox (Stoltzfus, Stohl, & Seibold, 2011). A dilemma
can be resolved by weighing the positive and negative value of choices to resolve upon one that
is advantageous (Stoltzfus, Stohl, & Seibold, 2011, p. 351). Dualities are complementary forces
but when framed as pairs of oppositional positions, can become paradoxes (e.g., self-
interest/collective good, dependence/autonomy) (p. 352). Contradictions are “incompatible
opposites that negate each other and exert tensions within a process” (Stohl & Cheney, 2001;
Stoltzfus, Stohl, & Seibold, 2011, p. 352). Paradox occurs when the reality and expectations of
perceived reality do not align, which exist simultaneously and persist over time through the
accumulation of messages and activities (Stohl & Cheney, 2001; Stoltzfus, Stohl, & Seibold,
2011, p. 352). Seo, Putnam and Bartunek (2004) proposed four methods to manage paradox
during organizational change, including a selection of one pole of the paradox dichotomy while
ignoring the other, dividing attention equally among the poles, integrating or synthesizing the
poles, or transcending either to view the deeper connections between them. These options closely
emulate different positions in the classic dialectic theory structure. Yet paradoxes can be
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managed by communicating an emphasis on connection during planned change (Barge, Lee,
Maddux, Nabring, & Townsend, 2008).
Embedded and Liminal Relationships
Start-ups are not very large at their beginning gestation stage, usually due to a lack of
financial capital, and often employ workers that are in various positions of involvement as full-
time employees and contractors. Although aiming to be more than temporary organizations,
start-ups rely on the concept of swift trust used in quick starting groups and teams (Meyerson,
Weick, & Kramer, 1996). As opposed to building trust slowly over time with repeated
interactions, a group assumes trust initially and verifies or adjusts trust later. In the case of start-
ups, swift trust is used when hiring contractors based on purported skillsets: the ability to fulfill
the position requirements are assumed present until demonstrated otherwise. Additionally, not all
start-up workers are co-located with the headquarters office, leading to challenges of creating
and maintaining trust (Jarvenpaa & Leidner, 1998; Kramer, 1999). When a member departs, the
turnover causes churn to reverberate in the organization at a higher degree than it would in a
larger organization. Uncertainty generated by departures in a small organization extends to the
impact on the organization’s resiliency (Buzzanell, 2010). Globally distributed contractors
manage tensions between autonomy and connectedness, inclusion and exclusion, and
empowerment and disempowerment (Gibbs, 2009). Groups establish explicit restrictive norms
(e.g., be on time) and implicit permissive norms (increase quality) (Zander, 1976), and these
norms might be differently invoked for members based on embeddedness.
The sensemaking processes for exits may diverge depending on the relationship of the
member to the organization. Distinctions between volunteers and employees in organizations
rely on the basis of tangible and intangible benefits as well as different psychological contracts
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about level of involvement (Kramer & Danielson, 2017; Kramer, Meisenbach, & Hansen, 2013).
Similarly, part-time employees and contractors differ from full-time employees in level of
involvement, organizational knowledge, and satisfaction (Sollitto, Martin, Dusic, Gibbons, &
Wagenhouser, 2016).
Organizations can reasonably expect the most involvement from full-time employees and
less from part-time employees and contractors. Employees who both receive and give help to
others, and also form a greater number of ties with coworkers, are more embedded (Brass, 1995;
Burt, 2001; Feeley & Barnett, 1997) and less likely to depart (Mossholder, Settoon, & Henagan,
2005). Leadership identity is constructed through relationships, forcing leaders to be embedded
in their organizations (Marchiondo, Myers, & Kopelman, 2015). Employees who have time for
advising activities and forming many ties are usually employed full-time whereas part-time
employees may view their role—and be viewed—more functionally, as fulfilling an
organizational need. A normalized component of career training at universities, full-time but
short-term—liminal—internships have been incorporated as requirements into many
undergraduate degrees as a means of symbiotic workforce socialization for employers and
potential employees (Dailey, 2016b). Unsurprisingly, organizational commitment and
performance have been linked directly to perceived quality of intern-manager work relationship
(Blau, 1988). In the ongoing development of work itself, an organization co-constitutively and
iteratively develops the roles of its workers under certain demands, including time pressure
(Meiners, 2004; Wrzesniewski & Dutton, 2001).
Whereas full-time employees can be seen as the most involved and embedded, part-time
employees and contractors enter liminal states relative to their organizations. Liminality denotes
the position of individuals for whom organizational boundaries and belongings are unclear
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(Zabusky & Barley, 1997; Borg & Söderlund, 2013). The concept of liminality originated in an
anthropological study of cultural ceremonies to describe the temporary transitional period
between the social statuses of childhood and adulthood (van Gennep, 1909/1960). Liminality
exists when a member does not or expects soon not to have a role in an organization (Ashforth,
2001, p. 136). In organizational settings, liminality can be long-standing, especially for those
with the project-oriented careers (Weick, 1996). People in liminal states, or liminars, can
concurrently hold several roles with psychological contracts (Svensson & Wolvén, 2010), as is
often the case for workers who are employed part-time or based on contract work.
For part-time and contract workers who are less embedded, critical incidents may
highlight the turning point of the exit decision for either the organization or the member. Critical
incidents are those experiences or events that contribute positively or negatively to an activity or
phenomenon (Flanagan, 1954). Focal events such as critical incidents highlight the associations
between actions and reveal the way these actions constitute social order (Feldman & Orlikowski,
2011; Feldman, Pentland, D’Adderio, & Lazaric, 2016).
This research examines both voluntary and involuntary exits, and how role expectations
are different for liminal and embedded workers. This study focuses on an early-stage
organization (start-up) and tracks process and meanings communicated before, during, and after
exits. In small organizations, embedded members are hired with a willingness to be flexible and
liminal contractors are hired to perform an expert role, whether in engineering or research or
sales management. Consistent with the structural functional Taylorism of the turn of the 1900s,
both embedded and liminal knowledge workers are contracted in technocratic roles based on
expertise specialization of their proclaimed profession. The roles of contractors are based on
technical expertise specialization, and as such atomize their identity in the organization based on
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a techno-rationality. Contractors fill a specific role in a metaphorical machine. When a
component of that machine goes missing, the machine must continue. The uncertainty generated
by exits is navigated both by leavers and stayers through sensemaking. The three research
questions of this study are:
RQ1: How do tensions emerge that lead to organizational change (i.e., departures)?
RQ2: How does a role definition interact with the sensemaking and sensegiving of exit?
RQ3: How does an early-stage start-up maintain fluidity after an exit transition has
occurred?
Method
Research Strategy and Setting
Studying the meanings of exits in an early-stage organization required a research setting
that allowed data collection of an organization that underwent turnover at various points in time.
Silicon Valley provided a geographic location with a large sample of companies undergoing high
rates of turnover, and churn has a particularly significant impact on start-ups due to their small
size. Venture labor in innovative industries glorifies risks, and company flexibility is privileged
at the expense of employee stability (Neff, 2012), establishing a precarious labor dynamic
(Brophy, 2006). Free-agency employment is widely accepted as the norm, and functions on the
basis of at-will or psychological contracts (Rousseau, 1990, 1995). As a system that employs
knowledge workers, the demonstration and performance of knowledge competence secure work
identities, but the slipperiness of the knowledge domains that are valued or trendy inserts further
ambiguity into the venture labor market (Alvesson, 2001). Immediately following the dot-com
bust, Pfeffer (2001) outlined four factors that produce continuous technology innovation at the
cost of high turnover as well as other management issues in Silicon Valley: at-will employment,
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extensive use of outside contractors, stock options as compensation, and long working hours.
Without benefits, workers may be cobbling together four or five contract projects to earn a
living. Additionally, stock options are a loose form of compensation, as the amount of equity
stake can be diminished when new members receive the benefit. Further, stock options do not
serve as an immediate form of payment because they materialize into monetary worth only after
the start-up develops into a fledgling company. The free-agency model of employment instills a
liminal connection between employees and employers based on the idea of career resilience. The
emphasis of liminal state contractors also aligns with the “lean start-up” movement, which
emphasis innovation with rapid testing, few resources, and continuous adjustment (Ries, 2011).
Reliance on temporary workforces has become a longstanding form of professional practice in
Silicon Valley and spread globally to other industries (Barley & Kunda, 2006; Gossett, 2006).
Located within the at-will employment culture of Silicon Valley, the start-up
Collaborative Wealth (a pseudonym, as are all other names for entities and informants used
herein) had several features that make it an apt subject for the study of exit and churn. First, the
headquarters office of Collaborative Wealth (CoWealth) was located inside a Silicon Valley
incubator. CoWealth had undergone its conception starting in 2009, and by 2015 had just begun
its gestation phase of development at the time of data collection. Largely out of financial
necessity, as with many start-ups that begin in Silicon Valley garages, the three founders had
adopted an at-will employment model with few (only three) employees and several contractors.
As a result, liminal connections were the norm and turnover was fairly regular for contractors.
The varieties of embeddedness in worker relationships provided an excellent natural setting to
observe various exit types. Additionally, the team comprised both co-located members who
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could work at the office or remotely nearby, and globally distributed members who worked with
the start-up team via a remote connection exclusively.
Second, the majority of CoWealth’s employees were liminal. Other than the founders,
who were most embedded, the company employed three employees on contract and everyone
else, including paid contractors and unpaid advisors, worked on the basis of a psychological
contract or liminal engagement. The founders were three nascent entrepreneurs—a Chief
Executive Officer (CEO), Chief Technology Officer (CTO), and Chief Engineer—who played
pivotal roles in the development of CoWealth. The CEO and CTO had worked together
previously in a start-up together, as had the CTO and Chief Engineer. Each founder contributed
to long-term strategic vision documents and wrote daily notes to either enact or delegate
completion of tasks with their team, providing sensegiving to the team. The structure of the
founder team included a female CEO and two male founders, a Chief Technology Officer and a
Chief Engineer. The network of resources that CoWealth drew from included investors, property
managers (related to their product), engineers, designers, accountants, and legal counsel. The
commentary produced by the founders provided an excellent opportunity to gain insights into the
sensegiving of the founders at various points in CoWealth’s development.
Third, I received longitudinal access to CoWealth to study the meanings of exits with the
consent of the founders and members. This study is based on a 12-month ethnography of
CoWealth. Conversations with members in meetings during fieldwork, and in interviews before,
during, and after exits provided insight into how exits were rationalized and sensemaking
contributed to resiliency.

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Data Collection
The research focuses on a naturalistic case of sensemaking about exits based on role
relations. Qualitative data were collected through a longitudinal case study approach to
understand dynamics of context (Yin, 2014). The setting was approached with theoretical
preconceptions as an extended case study (Lichterman, 2002). Case studies have the potential to
provoke new ideas and build on existing theories (Eisenhardt, 1989a; Siggelkow, 2007). This
study approaches a case that is made with an understanding of the case as a theoretical construct
to illuminate theory improvement (Ragin, 1992; Stake, 1995). Three exit cases are presented that
reveal triggers for and sensemaking of exits based on liminal and embedded role relations. To
ensure interpretive validity, software engineers who were not part of the informant sample
helped interpret terminology in the data throughout the study.
The flexibility afforded by case study research and ethnographic methodology in an
organization (Watson, 2011) resulted in a rich collection of data that spans interviews,
observations, and archival documents. I conducted a 12-month longitudinal ethnographic case
study from September 2015 to August 2016 to capture the gestation period of the start-up from
beginning to end. During that time, three types of exits were observed, including an external
contracted design firm, one founder, and several engineering contractors. Anyone involved with
CoWealth was included as long as they stayed active on projects with the start-up, and their
entries and exits were tracked, including three co-founders, three employees, 10 contractors, two
contracted design firms, and four advisors. Forty weekly meetings with the founders, which were
unstructured interviews, and 14 weekly videoconference meetings of the engineering team,
which were non-participant observation, were recorded and transcribed for analysis. During field
visits between January and August 2016, I took extensive field notes of observations according
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to the method described by Emerson, Fretz, and Shaw (2011). Formal and informal team
planning meetings were audio-recorded in the field and transcribed for analysis. In addition, I
conducted 24 interviews with 22 informants who were involved in the start-up, which lasted
from 18 to 91 minutes (M=45.96, SD=19.46). I interviewed the CTO and the Chief Engineer
once at the beginning and once at the conclusion of field data collection. The interviews
employed semi-structured, open-ended questions to provide consistency and allow for the
incorporation of issues offered by informants (Miles & Huberman, 1994). The interview protocol
addressed the following issues: perceptions of CoWealth’s direction, including mission, vision,
competitive advantage, and strategy; the history and development of the CoWealth
organizational structure; descriptions of informants’ previous training, company role, and job
activities; stories of milestones and challenges experienced; perceptions of task coordination
among informants; and evaluations of CoWealth’s priorities. Interviews were also transcribed for
analysis. The dataset resulted in 3,568 minutes of transcribed audio for analysis. More than 300
archival documents were collected and included investor presentations, website designs,
screenshots of tools in use, business planning documents, news articles, communication
exchanges on email or chat messaging systems, and employment contracts. This particular article
draws from interactions with members and discussions of exits during participant and non-
participant observation, personal reflections on exits during the unstructured and semi-structured
interviews, and field notes to capture the tensions of reasoning and sensemaking processes for
organizational disengagement.
Data Analysis
From the data, I developed meaningful categories that described the data in the categories
and integrated these emergent concepts into a theoretical framework (Corbin & Strauss, 1990;
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Strauss & Corbin, 1998). Rather than exclusively the inductive discovery process of grounded
theory (Glaser & Strauss, 1967), the coding methods that were used provided a balance between
induction, deduction, and verification from a constructionist perspective (Charmaz, 2014). I
coded critical incidents (Flanagan, 1954), which were defined as the events used as evidence in
exit justification and sensemaking, throughout the data.
I used thematic analysis for theoretical reconstruction as outlined by Ragin (1992).
Interview transcripts, field transcripts, and field notes were analyzed using NVivo content
analysis software. The constant comparative method was used, moving between data and
emerging theoretical reconstruction. First, I reduced the data with selective coding to examine
exit-related episodes. Then I focused on theory development to identify emergent codes with
line-by-line coding. From that coding, themes emerged that developed the broader categories of
tensions and dialectical tensions. After multiple iterations of these coding steps, a larger thematic
structure emerged. As a process-focused study of organizational change and innovation, the
findings are presented with narratives of multiple exit cases (Poole, Van de Ven, Dooley, &
Holmes, 2000). Analysis highlights paradoxical tensions (Poole & Van de Ven, 1989; Putnam,
1986) as the generative mechanisms for change in organizational disengagement.
Findings
I examine three cases of exit, including a contracted design firm, the full-time Chief
Technology Officer, and individual contractors in design and engineering. In each case, a brief
summary is provided followed by role expectations established before exit, the meanings of
critical events or reasons for departures understood during exit, and the sensemaking that
occurred after exit. Figures 3.1-3.4 illustrate the change in the organizational structure due to
both exits and entries during the 12 months of observation. Although these charts show a
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seeming level of stability of interaction during the period of months that they represent, the
relationships with contractors were not always as constant as these charts would appear to
indicate.
First Case: Design Firm Exit
The first exit case is the voluntary exit of the design firm, which ended its contract after
2.5 months with CoWealth in mid-June 2016. After the start-up had interviewed design firms,
the founders cultivated a relationship with this particular firm. The design firm account manager
reported that CoWealth had approached the firm with interest in its designs and its “budget
portfolio” through online research, essentially cold-calling the firm. He began correspondence to
understand plans for the CoWealth corporate website and explain the firm’s process of scoping
projects and agreeing to terms for the design. The first videoconference meeting on April 4
acquainted the design firm account manager, the design firm team, and the CoWealth
management group to begin work on the contract. In the ensuing months, CoWealth designated
an employee without design experience to manage the product with the design firm. The
employee provided feedback to the design firm questioning the value of its work, and in
response, the design firm terminated the liminal relationship. The critique served as a critical
incident (Flanagan, 1954) that forced a change for the start-up in a loss of their design firm.
Role Definition before Exit. On the initial April 4 videoconference meeting to discuss
the contract, the CoWealth founders established the expectations for the role of the design firm
as a contractor in designing the company’s website and platform. There were two designs
initiated by CoWealth – the public-facing corporate brand website and the password-protected
interface design for users on the platform. The founders discussed two tasks with the design firm
account manager: work for the corporate website, and a more complicated feature, the
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dashboard, on the internal user platform. First, the scope of work was reviewed in the meeting.
Originally, CoWealth had proposed the creation of an online video that the CEO said would be
“time consuming,” thus costing more, and that “we want to take that out [of the contract] in order
to fit the [development] schedule.” The account manager responded, “we have to be really clear
about the scope of work” and explained that “user experience design is more of the structure, the
layout, the flow the user would take…a layout of every page and feature and function” and did
not include animations, videos, or motion graphics. The account manager was referring to user
interface design, which is how the product is laid out and the website architecture for
information presentation (Covert, 2014; Ming, 2014). The CEO acknowledged the limitations of
the work she was purchasing in the “fixed quote” contract, emphasizing the transactional and
liminal nature of the relationship. She responded that although the founders knew what they
wanted for the corporate website, they had only a “big picture” conceptual idea rather than
specifics about content or logics. The CEO clarified two conceptual goals for the corporate
website to the account manager: to convey information about the company on the corporate
website and a presentation of the dashboard analytics on the internal user platform. The founders
of CoWealth expected not only the finished design presentation but also help with conceptual
design to organize the underlying logics of user experience. User experience design is design
aimed to craft the way a product feels (Ming, 2014). The account manager clarified that the firm
offered user interface expertise on execution of layout only, not content. The account manager
said,
…it would be comfortable for us to scope the dashboard based on what you’ve already
built…so then we know it’s not a moving target as far as…there could be many, many
user goals [for each feature]…to take what you’ve already built and then make it, polish
it in a [user interface] solution—look and feel solution—then that’s pretty straightforward
and we can be very confident about risk and scope.

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When he said “risk,” the account manager meant financial costs and “scope” referred to the
outlined work to be completed. The CEO agreed and said “we will work on the contents…and
you help us to display it.” Both CoWealth and the design firm misunderstood the particulars of
the design areas to which they were agreeing.
Next, the meeting moved to a discussion of the liminal contractual agreement between
CoWealth and the design firm. On the terms of the contract, the CEO asked for a cap on the costs
of time and material, to which the account manager said, “certainly…so there’s less risk for you
guys.” The account manager suggested an upfront payment for a 1-2 week retainer of 40 to 80
hours of work for the design team and said “if there’s any hours unused, we refund them” but if
the design team exhausts the first retainer, “we’re happy to say, ‘Oh well here’s your wire frames
and you can find another designer’” or expand the scope of work. The CEO said, “…like you
just proposed…if everything’s fine [and] working well, we can continue.” The account manager
said he would revise the fee schedule and contract to incorporate the cap and said, “I’m
optimistic that it will all work out and then we’ll be on the same page as we’re designing and
we’re understanding what the expectations are at some point.” Based on this agreement arranged
by the account manager, CoWealth and the design firm had entered into a liminal contract for
user interface design that was fixed on a cost basis that allowed flexibility. The CoWealth
founders interpreted scope flexibility about the range of tasks the design firm could take on,
potentially including logics and content of the presentation, whereas the account manager
interpreted scope flexibility about the amount of work within user interface design specifically.
Last, the details of the CoWealth product and vision were discussed with the design firm.
The account manager introduced CoWealth to four members of the design team and then the
CEO and Chief Engineer began to talk through the project and ideas for the work in detail.
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During the description, the account manager again clarified, “we’re not doing website
development but we’re delivering essentially a sketch format…[and] as we’re going through the
process, we’re going to ask for the content.” The CEO confirmed with the account manager that
she should start preparing the content immediately. At one point in the conversation, the CEO
explained the vision for the product and said that it might “help a little bit for your design [team]
to think about the message” to which the account manager responded, “we’ll make that our own
internal discovery and then we’ll tailor the visual design for that message.” Toward the end of
the call, the CEO said, “Just keep in mind that we are very open to any suggestion and very open
minded,” indicating a desire for original ideas from the design firm about the logic and content
of CoWealth’s platform. Before the call concluded, the Chief Engineer wanted to confirm the
work process with the account manager:
Chief Engineer: I just want to clarify that the work and style is more like you guys
take initiative, you make a proposal, and then we do the review about
that. When we all agree on something, then we move forward.

Account
Manager:
Yes.

Chief Engineer: The only time we should speak up loudly is that we don’t agree on
something we really need to change, right? Is that okay?

Account
Manager:
That’s the way we like to engage, yeah.

Though left open as to the kind of initiative the design firm would make, the Chief Engineer and
CEO felt it would be on the conceptual and technical levels of design, whereas the account
manager understood that the design team would take initiative on the outlined scope of work, or
the user interface. The founders and account manager agreed to written communication for
updates on progress and feedback. The account manager reviewed the project management
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system they would use, and the CEO said that she would be away on travel to fundraise and it
would be difficult for her to communicate feedback, but she would email. This videoconference
was vital for establishing expectations for the role of the design firm, and the divergence between
the more embedded arrangement CoWealth wanted and the liminal engagement it offered.
As CoWealth continued its relationship with the design firm, the firm maintained the
liminal role it had outlined, and the operations of CoWealth changed to provide more support to
the design firm than the founders had originally anticipated. The account manager had regular
videoconference meetings with the CoWealth team, but usually relied on online systems to
communicate ideas and feedback quickly, including text and visuals, about the structural design
of the website. After a month, the CoWealth founders re-assigned one employee to help with the
conceptual design logics and content design of the website for the user interface on the internal
platform. The Chief Engineer explained during the May 2 engineering meeting, “We started
having a [user interface] design [firm]. [The CEO] did something: Martin is going to take over
and do more [content creation and logic] design work for us [of the internal website].” Although
not trained in user experience or user interface design, or the conceptual design of user logics,
Martin was assigned to manage the feedback relationship with the design firm and provide
insight about the functionality and content of the platform. On a May 17 videoconference call
between the founders, Martin, and the design firm, the CEO said, “I told Martin to put [this
point] in the comments…about some ideas” for an interactive animated feature that could adjust
to data entered by users. Martin explained the concept more fully, to which the account manager
said, “you guys will have a lot more homework to do because that means you will have to come
up with a lot more content to target all those demographics.” Martin said in response, “I guess
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before we dive too deep…in your opinion, do you think something like that would be more or
less effective?” The account manager said, “I think it is effective. It’s just a lot more work.”
For the next month, Martin previewed updated product design pages and commented on
the May 31 engineering meeting, “I still have one thing I need to figure out, which is [how these
pages are going to connect].” The Chief Engineer emphasized the reliance on Martin in his new
role: “So after you finish the whole design, we [will] probably need to do a review. And after
that, I will write [tasks] to break down [assignments].” The next week during the June 6 meeting,
Martin again updated the engineering team on finalized aspects of the product design. The Chief
Engineer introduced a product design change that would affect both the programming and the
user interface design and asked for Martin’s opinion, to which he responded, “I mean it’s a little
hard to say right now.” For other elements, Martin would review his ideas about how pages of
the product functionality would operate and both the Chief Engineer and Martin expressed a
preference for ease and simplicity. The Chief Engineer said, “When we have [an issue], we
address it [then],” establishing a trial and error system of development for user interface logic
they did not have the capacity to design.
Critical Incident for Exit. With mounting pressure to define the product concept, train
himself in user experience and user interface design, and manage coordinating between the
engineering team and design firm with efficient communication, Martin’s feedback became curt
and uncharitable. The design firm account manager recalled during his interview:
With the CoWealth relationship, it went a bit south. There was some feedback given and
it wasn’t well received by my team… 5-6 hours of time spent and then feedback from
Martin [was] that they could have done it themselves or sooner or faster. There was
personal offense, and there was a reaction to end the engagement and I was responsible to
end the engagement…

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The design firm account manager explained that his firm ended the contract based on feedback
that operated as a critical incident.
Sensemaking and Sensegiving Post-Exit. The founders were disappointed in the design
firm’s reluctance to assist with product design at a deeper level, but did not discuss the ended
contract with the design firm in-depth beyond what it meant functionally for CoWealth’s
workload. During the June 27 engineering meeting shortly after the design firm ended the
contract, Kevin, the CoWealth algorithm developer, reflected positively: “Martin and Cindy
[worked on] our corporate website design and I think…it’s pretty decent—it looks pretty good.”
The comment prompted the Chief Engineer to explain:
I probably need to update everybody—we tried to contract a UI team in Sacramento to
cover the website design but, last week, they decided to terminate the contract with
us…we ha[d] some feedback for them—we kind of complained about things they did. It
seems they didn’t take it very well so they want[ed] to terminate the contract. They have
finished the wire frame and, also, they just started the visual design so that’s why we
cannot switch to another designer, Cindy. She is helping us try to finish the whole thing.

During a field visit, when I brought up the topic of the design firm’s cessation of the contract in
private conversation with Martin on July 6, he expressed apprehension about the way that the
contract had ended but did not place blame on the design firm. In the interview with the design
firm account manager, he reflected, “…I think we fell short for CoWealth because we couldn’t
help…what their product was, and how the public would see them.” The design firm was
completing the work it had been contracted for and CoWealth had contracted a freelance
designer, Cindy, to complete the user experience design.
The design firm account manager made sense of the ended contract by talking about risks
and expectations:
[CoWealth] took risks by signing with a design and development agency in terms of
upfront costs. It’s always risky signing with a design studio…A lot of times when we get
into design endeavors, we can’t meet expectation or communicate the expectation. We
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mitigate our risk asking for retainers upfront… [CoWealth] had an expectation of
copywriting and general marketing strategy and as [user experience and user interface]
designers. We’re used to having very detailed instructions…there was an expectation of
additional services that my team wasn’t prepared for providing. Because the
communication wasn’t as clear to hear what was needed.

Paradox and Tensions. As highlighted in the April 4 meeting, the design firm and the
CoWealth founders diverged in terms of their expectations of the liminal state relationship.
CoWealth wanted more embeddedness and investment in product design, but within the
transactional nature of hourly rates for user interface design, the design firm was not equipped to
deliver to meet CoWealth’s needs. Before the exit, at the outset of the contract, the role
definition of the design firm in the work of CoWealth produced a paradoxical tension that caused
two separate structural changes. The reality of the contract and the founders’ expectations of the
perceived contract did not align and persisted over time. The contracted work the design firm
offered on user interface design had a clearly defined scope of work without any “moving
target[s]” to curb any additional financial costs. The transactional nature of the contracting
relationship, which was based on a fixed price with caps on time and materials, reconstituted the
liminal relationship with the design firm. The account manager outlined three possible outcome
realities in their relationship, including early completion, on-time completion, and an extension
for additional work. The design firm presented a clear contract with potential scenarios. The
CoWealth CEO, although agreeing to provide content for the design firm, reiterated an attitude
“open to suggestions” in which she outlined an abstract concept with two general goals for the
website: to inform about the company and present one of its platform features. The CoWealth
Chief Engineer also believed that the design firm would “take initiative” and established a
feedback style that was open to disagreement. Rather than mirroring the clarity that the design
firm account manager provided, the CoWealth founders emphasized the flexibility and
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dynamism that is familiar in software development contexts with continuous revision. Despite
contracting a liminal relationship, the CoWealth founders expected more strategic contributions
about content and product from the design firm. When content and product direction
expectations were initially unmet, this paradox generated the first change. The founders
reassigned a full-time employee, Martin, to manage the product design and content as well as the
relationship with the design firm. His inexperience in design, however, did not resolve the
tension because he could not supply the knowledge needed to fill the gap between CoWealth’s
ambitions and the design firm’s need for concrete direction. Consequently, the paradoxical
tension continued to build through the user interface design feedback cycle. The paradox caused
a second change and was resolved when a critical incident, personal offense to feedback by
Martin, prompted the design firm’s exit. The account manager summed up the relationship by
saying that it “went south.”
In the sensemaking about this exit, the informants revealed four contradictions and
dialectical tensions that fueled the paradoxical shifts (see Table 4.1). When the design firm
account manager sensemade about the critical incident, he emphasized the time invested by his
team and the reaction that the work had not been completed quickly enough, and that non-experts
could complete the task at the level of quality produced. The Chief Engineer also pointed to the
feedback as the critical incident, but while sensegiving to his engineering time, instead referred
to the design firm’s inability to accept criticism. The dialectical tension that emerged about the
knowledge workers’ product was between competence and incompetence. Further sensemaking
on the incident, the account manager of the design firm explained that the start-up took a risk in
hiring them. He said there are always “upfront costs” because the design firm must mitigate the
risks of its creative outputs in accepting contract-based work. Although the tension about
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Table 4.1.
Tensions in Three Organizational Disengagement Cases
Main Stakeholders
Tension Design Firm Founders Contractors
Competence vs. Incompetence X X X
Expectation vs. Reality X X
Risky vs. Safe X X
Costly vs. Free X
Transparent vs. Secret X
Autonomy vs. Connectedness* X
Detached vs. Involved* X
Equitable vs. Inequitable* X
Permanent vs. Temporary* X
Note: * indicates dialectical tensions or subdialectics proposed by Gibbs (2009)

financials between costly and free emerged during the initial contract meeting in the valuation of
creative labor, the contradictions inherent in the explicit contract highlighted the tension between
risky and safe in the liability of those outputs matching expectations. Although CoWealth’s
expectation for suggestions and feedback about its product was clearly articulated, the design
firm account manager continued to explain the firm had communicated it was not equipped to
meet more abstract needs of providing product content strategy, in terms of copyrighting or
marketing, in addition to user interface design. CoWealth founders viewed the contract as more
embedded in the strategic direction for its future rather than only the translation of its vision into
the information architecture of a website. The contract, however, was established as a liminal
engagement with potentially three outcomes, and a critical incident brought the relationship to an
end. The dialectical tension that emerged was between expectation and reality. In the
sensemaking and sensegiving processes about the design firm exit, four dialectical tensions
emerged from the ongoing paradox.

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Second Case: Founder Exit
The second exit case was an unexpected and involuntary exit: the CTO, a founder, was
fired at the end of July 2016. The CEO and the CTO were friends and had been invested in
CoWealth since they began thinking about the company together in the CTO’s backyard after the
housing bubble and during the Great Recession’s height in the summer of 2009. The central idea
of CoWealth was to allow people to build wealth in real estate by pooling money with others and
purchasing properties as investments. The CEO commented during fieldwork in February 2016
that “an idea stays an idea unless you act on it.” After ideation over 6 years and early in the
process of organizing, the CTO had brought the Chief Engineer into the company because the
two had worked together well at another company. When CoWealth began gestation in late 2015,
the CTO managed several aspects of the business, including product development and the Chief
Executive Officer (CEO) role of CoWealth’s subsidiary company, PropertyPros (see Figures 3.1
and 3.2). During the early months of 2016, however, the CoWealth CEO began to reevaluate the
CTO’s contributions to the team’s success and progress, especially during the time she spent on
travel raising capital to fund CoWealth. By April, the CEO directed a close friend and heavily
involved investor to essentially take over the CTO’s role with PropertyPros, but under a separate
title of Chief Operating Officer of PropertyPros. The CTO also shared responsibilities for
research and development with the Chief Engineer, while focusing exclusively on product
management activities (see Figure 3.6). As the CTO’s limited involvement with the design firm
became clearer, and as Martin became more involved in product design even after the design
firm disengaged, his leadership role was questioned, he was fired, and the Chief Engineer
absorbed his responsibilities in early August (see Figure 3.7). The CTO no longer managed the
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company’s day-to-day activities, but remained on the CoWealth Board with an equity stake,
though without a controlling interest in the company.
Role Definition before Exit. Though the official roles of the founders were flexible,
each founder had a specialty focus. The CEO had been trained in sales and management, while
the CTO and Chief Engineer, were trained technically in software development and computer
engineering. Within those swaths of expertise, the founders defined areas of work that would
assist in building CoWealth into a successful company. The CEO managed friends and family
funding as well as venture capital and angel fundraising, legal and tax issues, finances, marketing
and business development, and communicated the vision and culture of CoWealth to internal and
external stakeholders. As one of the central figures in its ideation, the CTO managed the real
estate relationships that would be essential in translating the product concept into a tangible
reality with properties as inventory. The CTO also oversaw research and development of the
product, though he did not have any prior experience with product management at an equivalent
level of authority. During fieldwork, the CEO explained that the CTO’s role was “to plan for the
whole technology, when things need to happen. [The CTO] needs to be technically savvy plus
very organized on who to hire and what to do and implement the CEO’s vision.” The Chief
Engineer did not initially operate with responsibilities on par with his founding counterparts and
focused almost exclusively on software development and patenting. While they worked on their
niche areas, often remotely, the founders sought to coordinate their efforts through asynchronous
communication and phone or videoconference meetings.
Role Uncertainty Leading to Exit. The CTO set the expectations for his role to oversee
the product design through user experience research, which is ongoing research about the
usability of the website as reported by potential users that informs the design process (Farrell,
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2017). During the May 2 meeting, the CTO managed the product and later said on the call, “This
[task] is a design [one] so…I think I’ll call a meeting to review. Basically, it’s about…what we
learn from the real users is that… sometimes people don’t click [on the sales pitch].” The CTO
did not communicate about the research findings or translate them to tangible user experience
design, which is design aimed to change the way a product feels (Ming, 2014). Later during the
May 17 meeting with the founders, Martin, and the design firm, the CTO remained silent and
before the close of the call, the CEO asked him if he had any comments to the design firm about
its user interface, to which he said, “No. Not much,” and the CEO questioned, “Not much?
Okay.” Rather than speak to the CTO about design, she asked Martin to call her immediately
following the call about progress with and feedback for the design firm.
Months before, the CTO’s interpretation of his role had begun to impact the functioning
and definition of other members’ roles in CoWealth and had instigated the need to hire a design
firm. At the time of a late February morning breakfast meeting between the CEO and a close
investor friend, the CTO was managing the entire design. The CEO reported that the CTO was
not sharing information about the new designs before they were completed. She said, “My
corporate training is being professional and being transparent in my communication. I’m doing
more than I need to as a CEO: I give them reports immediately after phone calls and [investor]
meetings.” The CTO had turned down interviews in the CEO’s search for a new user interface
designer. He did not approve hiring a replacement for the current contractor, Meryl, who he was
also involved with personally and whose limited availability was an obstacle for design at
CoWealth. The Chief Engineer, who had worked well with the CTO before, had told the CEO
that he “is frustrated…he’s surprised because it’s totally different now with [him] as CTO,”
insinuating the CTO’s more authoritarian attitude. The CEO reported that the CTO would
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“change the code after [the Chief Engineer] had written it [to prevent its implementation] and
[the Chief Engineer] is getting really pissed off.” The CEO contrasted her recent experiences to
her past working experiences with the CTO, when he reported to her, as easy going and without
issue on technical execution. The investor commented that the problem was the arrogance
associated with the CTO’s quick ascension from staff to founder to C-suite management. The
CEO expressed concern about the personnel issues she now faced between the staff and the
CTO, and said, “I’m working hard to resolve the differences and keep the relationships stable”
and later, “He’s not a bad guy, just stubborn.”
The performance of the CTO’s role had started to inhibit the CEO’s ability to perform her
tasks. The CEO noted the divergence between herself and the CTO in interpreting the platform
design plan that had been set in November 2015. She began talking about the platform, saying, “I
don’t understand why it’s so hard to explain to [the CTO],” and further that he preferred a level
of detail displayed that she did not. Because the CTO felt joint ownership of the kernel idea, he
believed that his vision for the platform would be privileged during the development process.
The CEO said she had created an interactive demonstration to explain the CoWealth product in
presentations to investors because the website lacked the appropriate functionality to provide
more information, persuade investment, and because “I want everything to be transparent.” The
CEO said she did not send investors links to the real website because “it’s empty” and lacked
content, which she had assumed would be the CTO’s role to develop. She recalled, “In response
he sent a long lecture via email and said we should use the website and ‘eat our own dog food.’”
She was taken aback by the dogfooding slang, which is an engineering expression that a
company should use its own product to test and promote the product (Harrison, 2006). During a
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meeting with an investor, the investor commented that the CTO “speaks in clichés,” implying a
lack of originality. Angrily, the CEO confided:
I’m the one doing the selling and [he’s] telling me I should use only a little bit of
information. He’s tying my hands behind my back!...[He] is setting me up for failure and
I get all the blame from investors. And [he] will also blame me that I cannot sell to
people. I have nothing to show.

The CEO’s comments indicate that the CTO was not facing the gap between the interactive
demonstration and the working technical product, and avoided confronting this gap because it
would reflect on his failures in guiding the product.
In response to this shifting role ambiguity, the result of the CTO’s lack of previous
project management experience, the CEO in turn questioned her own leadership: “If [the CTO]
wants to be CEO and the shareholders approve, I’m fine with it. No bad feelings. But I have to
get [the company] to a certain point. I like to build things, and then someone else can manage it.”
The investor and CEO quickly agreed, however, that most people would withdraw their
investments because they are connected to CoWealth through her, implying her imperative
centrality in the company. The CEO mentioned that one of the CTO’s investors, a friend from
high school, wanted him fired due to the lack of product progress on the website. She said, “My
friends invest in the company and they believe in me. [The CTO’s] friends haven’t invested.”
She reported that most of the engineers at CoWealth had experienced issues working with him.
The CEO mentioned that she would like to replace him with a new CTO, and then have the
shareholders vote on it. She said, “This is what we call a management nightmare.” The CTO’s
departure portended imminently, but was delayed for a few more months.
Whereas earlier in the year, he had been one of the most verbose voices in development
conversations, by early April, the CTO was not actively participating in group meetings unless
asked for his opinion. In the absence of the CEO due to fundraising travel, the dynamics shifted
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from the CTO leading to the Chief Engineer leading. In a carpool with me on the morning of
June 6, the CEO said, “[The Chief Engineer] is good and happy…[but] he’s very tired since he’s
the one doing all the technical things...and starting to do the first draft of the patent.” She also
commented that the CTO had not been keeping track of the ledger or company receipts in her
absence for two months. She said,
I don't know how to communicate with [the CTO]. He's sitting there and waiting for
everyone else to do the work. I had an open talk with him after I came back from
[fundraising travel]. Why do you want to keep everything in secret? It's like you hire
someone to work on the mobile because none of us have this expertise. What else have
you been doing these 2 months?... Even though I have been doing 6 jobs I've been
keeping them updated with the phone plus a report…He just shakes his head and I don't
know what that means. So this is a challenge because I don't know what happened to him.

After arriving at the office, the CEO corralled the CTO and the Chief Engineer into a private
conference room for a heated, closed-door 5-minute conversation about accountability, saying,
“Do I ever fail you guys?...Out of this whole company, I am the only one standing here trying to
hold the whole thing. [Otherwise] everything drops…How hard is it to learn? I can learn, and so
I learn it.” On the drive home the following day, the CEO recounted that legal counsel had
informed her earlier about a money-wiring problem with PropertyPros about which the CTO had
not informed her , and it put all company members in “danger” legally. Essentially, money from
property investors was being sent to PropertyPros in escrow, though PropertyPros was a
subsidiary and not an independent third party as required by law. She commented that she felt
pressure to explain to investors the reasons for firing the CTO. She said,
I respect[ed] him a lot at the beginning, and we sat down and threw around a lot of ideas
together [and decided on one]. Now the situation has turned sour and I feel personally
responsible. I feel sad not angry. He’s not trying to improve and keep improving [his
skills]. He’s status quo with five to 10 years ago. I know that if he [were] in another
company, he would [have been] fired a long time ago. This is a dilemma.

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Later in the month, on June 22, despite not having a firm platform structure and design, the CTO
mentioned continuing plans for a mobile application development in a founder meeting. During
an early July fieldvisit, the CTO expressed enthusiasm for an opportunity to expand CoWealth to
a satellite research office in Toronto, Canada. At the end of the month, he was asked to leave the
company because of his inability to lead the team in a unified direction under the CEO’s
guidance.
Sensemaking Post-Exit. Due to the sensitive nature of the founder’s exit for CoWealth,
much of the sensemaking data about the exit was derived during one of the weekly founder
meetings immediately afterward and founder interviews. Internally to other members of the
CoWealth company, the remaining two founders sensegave the CTO’s exit as an absence for
personal leave and it was not widely discussed. The CTO reported about his role transition
before disengagement in his late July interview that “it used to be [that] I work close with the
developers on the [frontend] and then I saw [the Chief Engineer] taking up some of those
responsibilities, and I got freed up…[to focus on] the mobile part.” Then he engaged in
sensemaking about his own departure from the organization before his leave had been
announced. The CTO said:
There’s a lot of decisions we need to make collectively with the founders. There will be
times we view things differently, the way we do things…[and] the laser focus might be
different. The hardest part is really is having an open mind to discuss and get to a
decision I think. And also like how we see the sort of expectation of what we want to
achieve doing one thing. Why are we doing that, what do we expect, and what does it
mean to us? If we have a different view, the challenge is how do we resolve this
difference? How we more over time get to a point where we converge? I would think it’s
probably very common in start-ups, we all feel it’s important to us and then come from
different backgrounds.

The CTO’s comments reflected his perspective on founder decision-making and leadership, and
tensions in understanding and interpretation that emerge with different expertise vocabularies.
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Personally, the CEO and the Chief Engineer made sense of this exit very differently.
After the CTO’s exit, the CEO, who was trained in management and sales, talked about
transparency in the team and that the communication style preferred by the CTO was unfair
because it left her ill-informed for her communication with stakeholders. She said she could not
risk losing the company but thought that they would always lead it together. In late August
during her interview, the CEO replayed the conversation with the CTO:
Last month I had to talk to [the CTO] to leave the company…I try to communicate with
him, explain to him, we as a team, we should have transparency. It’s not fair I don’t even
know what is his next move. He never tells anyone…what is the plan for the next
project…I’m the one who faces the [venture capitalist]…this is not fair to our investors
and [I] can’t gamble the company…I feel that we set up this company together, and we
should be together forever, but this situation was really hard for me, and two to three of
the investors got upset, and this is my fiduciary duty that I have to do it. I’m a good
friend of [his] but I have to make this decision. And it’s really difficult for me.

The Chief Engineer approached the CTO’s exit differently from the CEO, possibly because he
wanted to be recognized for taking on CTO-level responsibilities. During the August 3 call, the
Chief Engineer expressed that he desired a clear message that revealed the exit on the basis of
fact. For him as an engineer, programming code is explicit and obvious, and data represents
truth. The Chief Engineer said:
Our official message is that he’s going to take a personal leave. There’s no
timeline…After [the CEO] comes back, there are lots of legal documents we need to
finish. And then the message can be different when we talk to investors and it doesn’t
need to be a personal leave message. Internally, the message is he’s going to take a
personal leave. Outside I don’t think [the CEO] is talking to investors about this yet.
After the legal paperwork is finished, I personally feel the correct message, I don’t know
if the CEO is going to take it, but we had three partners, we restructured, we fired our
partner, is going to be my message. I want to have a strong message, I don’t want to have
a very weak message.

One of CoWealth’s advisors later guided a more careful message of the CTO’s transition,
offering that perhaps the CTO had found an appealing opportunity to pursue elsewhere.
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Paradox and Tensions. The founder’s involuntary departure from CoWealth manifested
from a paradox about the defined responsibilities and expectations of the CTO role as an
embedded member in the organization. The flexibility of the founder roles created a space for
duality about the interpretation of the CTO’s role. For the CTO, his job was to pursue activities
that materialized his vision for CoWealth, whereas the CEO believed his job was to manage the
technological development in the shape of her vision. Essentially, the founders developed a plan
in November 2015 that outlined generalities of the product functionality. The plan was meant to
serve as a unifying object for the development of the product, but it became a symbol of
divergence in the CEO and CTO’s product management strategies. The departure between the
visions of the product by the CEO and the CTO materialized in the CEO’s demonstration tool for
investors and the CTO’s accessible but “empty” website. The depiction of what CoWealth was to
become, as a company and a service, was under contest between its two creators. The differences
in strategic direction were becoming more visible as the CTO’s vision was utilized in navigating
work internal to the company, including the Chief Engineer’s code, and the CEO’s tool was used
to illustrate the company and its product goals to external stakeholders. The CTO’s plan of
product development incorporated pilot research with users and mobile application development
that did not realize as tangible contributions on the website. Seeing himself as an equal
counterpart with, rather than a subordinate directly reporting to, the CEO, and in charge of
technical development while the CEO worked on the aspects of running the business, the CTO
managed his work and team with a diminishing amount of communication. The design firm that
was contracted to develop a different component of the company’s online presence, the public-
facing corporate branding website, pushed the CEO and CTO differences to the limit as the firm
asked for CoWealth to produce copywriting about itself. The paradox of uncertainty about the
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CTO generated by his expected and performed roles created a dilemma for the CEO. Because the
CTO was viewed as an embedded role, many activities over time, rather than one specific critical
incident, culminated in resolving the paradox with a leadership change. Data collecting during
six months between February and July revealed that the CEO weighed the positive and negative
aspects of firing the CTO carefully, including the depth of his embeddedness with investors and
workers, to find an advantageous resolution for the company. To resolve the tensions in the
company, the CEO decided that she should would fire the CTO and find a replacement later.
In the sensemaking about this exit, the founders revealed six contradictions and
dialectical tensions that embodied the paradox (see Table 4.1). When the CTO sensemade about
his departure from CoWealth, he discussed decision-making, open-mindedness, and resolving
differences between viewpoints. The CTO did not reflect on the uncertainty of his role, because
for him it was not in question. Instead, he focused on the decision and information sharing
processes at CoWealth. The CTO mentioned the gap between anticipation and achievement of
the desired outcome, and highlighted the dialectic between expectation and reality. In the
recognition of differing perspectives, the CTO also expressed a contradictory tension between
autonomy and connectedness. Before the exit, as the CEO was sensemaking about her decision
to fire the CTO, she expressed concerns that the communication between them was not
forthright, despite her efforts to send regular reports. She described a tension between
transparency and secrecy, where she felt that the CTO was not providing an explanation for his
time or activities. In contrast, the CEO described her communication as open with a purpose of
keeping the team updated, signaling the dialectical tension between autonomy and
connectedness. She then questioned his commitment to the company, suggesting that while she
takes responsibility for several task areas, he delegates to others on the team or hires new
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workers, and revealing the dialectical tensions between detachment and involvement as well as
competence and incompetence. After the exit, the CEO sensemade about her conversation with
the CTO in presenting the decision to fire him. She reiterated the values of transparency and
openness in communication, and said that he created tensions of secrecy and autonomy at the
cost of connectedness. In establishing her decision grounded in stable judgment, she invoked a
dialectical tension between equitable and inequitable when she spoke of fairness and duty. Later
on, she continued to retrospectively sensemake about the CTO’s departure, stating that his exit
should have occurred long before it did. The Chief Engineer sensemade about the CTO’s exit
from the vantage point of messaging to different stakeholders in order to convey the true story of
events. He spoke about the internal company message and the message to investors as potentially
being different: the internal message needed to smooth over the transition whereas the external
message could explain the chronology of events. His comments about sensegiving to
stakeholders highlighted the dialectical tension between transparency and secrecy in a message
used for various purposes. The CTO spoke about “correct” and “strong” messages that explained
the restructuring that resulted in a founder’s departure. He equated a “weak” message with one
that did not expose the facts. In this latter contrast, the CTO focused on a sense of justice in the
tension of equitable and inequitable messaging for the company.
Third Case: Contractor Exits
The final exit case represents a category of exits with liminal state contractors. These
turnovers with engineer and design contractors were voluntary, based on external factors, or
involuntary, based on a shift in the start-up’s strategic direction. The CTO and Chief Engineer,
who were both full-time employees, led the research and development unit of CoWealth. Within
their staff, they had three full-time employees and 10 contractors that were tracked during the
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year of data collection (see Figures 3.4-3.7). Cost was a large factor in the reasoning for hiring
both interns and contractors, as opposed to full-time employees, in the context of the start-up’s
limited funds. For instance, the CEO, in speaking about a legal advisor mentioned, “He’s
wonderful…he’s trying to find a cost effective way to help us.” In another meeting, the Chief
Eningeer was contemplating hiring and said, “I don’t think we have enough money to hire a
[full-time] Bay Area engineer. This is quite expensive. So, I guess we are very conscious about
that.” Similar to the practices of many start-ups in Silicon Valley, CoWealth fostered internships
to develop talent and connect with research and training offered by universities to support its
own development. There were many instances of turnover, including entries and exits into the
organization. Members of CoWealth were an extension of the wider cultural norms of Silicon
Valley, evaluating people on the team and whether or not they were meeting the terms. No real
disruption was caused by the comings and goings of contractors, and no members reflected the
turnover as anything out of the ordinary. The most interesting aspect of this third case is not the
drama of turnover, but its normalization.
Kevin was the longest tenured non-founder full-time member; he began as an intern in
August 2015 and later became an employee. Two other full-time employees joined the team
during data collection, including Martin for business development in mid-March 2016, and user
interface designer Chelsea in August 1, 2016. The rest of the staff was comprised of contractors.
Many contractors had full-time jobs or pursuits such as graduate school that sidelined the work at
CoWealth as a liminal engagement. Some had multiple freelance projects with different
employers to balance. Some also offered limited availability because they were not co-located in
the same area, time zone, or continent. For contractors, vacations, holidays, other work, graduate
school—all of these were priorities over the work at CoWealth and inhibited growth at the start-
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up at the pace the founders wanted. The Chief Engineer also restructured work to accommodate
the absences or delays in outputs by the contractors.
Role Definition and Planning Before Turnover. Full-time employees and part-time
contractors confessed during interviews to an invisible accessory choice in their start-up uniform:
many hats. The metaphor of many hats emerged to explain the several defined roles individual
members performed in CoWealth. The CTO said in his January 18 interview, “Being agile and
very open minded…In the early part of the game, [we] wear multiple hats.” In his July 29
interview, the CTO returned to the hats metaphor, saying, “I kind of look at myself as creating
the business…from an idea; [I] sort of look at myself as [an] entrepreneur. And so I think we
wear multiple hats all the time.” As the CEO explained in an earlier quotation, she was also
performing six different jobs. As a small group of people, the full-time employees also embraced
the flexibility afforded to CoWealth by assuming the responsibilities of several desired roles
within the company. In his interview June 6, Martin said,
I don’t think I have a very clearly defined role because we are so small. There’s a lot that
needs to be done. I think limiting myself, or saying that these are my set responsibilities,
slows down a lot of progress. So my responsibilities come down to doing whatever needs
to be done to move the business forward…I have to wear a lot of hats to keep up and try
to get everything done and push everything forward.

In Chelsea’s August 11 interview, she commented about CoWealth, “They’re a good group of
people to work with. So I feel like that overrides all the challenges…that are bothering me. It’s a
good learning experience because you get to wear multiple hats.” For part-time contractors, too,
the hats metaphor provided a common understanding from which to understand the functions
they were hired to fill, and the ones they adopted in the course of business. In her January 15
interview, the investor turned part-time PropertyPros Chief Operating Officer said, “I have three
hats. I have one company investor [hat], one property investor [hat], and then the PropertyPros
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[hat].” The following day, the user interface designer Meryl said, “Everybody just—well, me as
a contractor, I’m just doing my thing—but they definitely wear many hats. It’s typical for [a]
start-up…[I’m a] designer, [and] probably a little bit of product manager, too.” The hats
metaphor allowed founders, full-time employees, and contractors to consider themselves as
adaptable to different needs that arose during CoWealth’s growth.
The Chief Engineer often tried to mimic this flexibility in role definition in the planned
schedule of work, specifically foreseeing and adjusting around minor absences on the team that
would disrupt task completion. Turnover resulted from the assimilation of new contractors, as
well as the unavailability of contractors that were already socialized as part of the team. If
contractors that CoWealth had established a relationship with were not available, for however
long or brief a period, those contractors exited; when they became available again, they reentered
CoWealth indeterminately. With this flexibility, CoWealth kept a roster of fairly regular expert
contractors entering and exiting the company as needed and able to make contributions. As an
exiting member, the CTO reflected in his late July interview that the CoWealth structure had
been “simple” because the time of consultants and contractors had been purchased on a
functional resource-needs basis, though the Chief Engineer was responsible for aligning staff
availability with work schedules. Despite the change in individual contributors, the CTO said, “I
think it’s stayed pretty much the same…There’s [been] some turnover. Some of our contractors
that were with us before, the contract expired and then people get busy. We’ve [also] had some
new members.”
The Chief Engineer often planned around known and upcoming periods of unavailability
for the staff. The work that had been assigned to a contractor found stability in reassignment to a
full-time employee. For instance, at the May 9 meeting, the Chief Engineer said about a part-
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time contractor, “…Adrian is going to go to school in August. So I already have like two, maybe
a little more than two months. And Martin is going to take over for a while.” After Adrian’s
departure during the August 29 call, during the task assignment part of the meeting, the Chief
Engineer planned the workload in accordance with his upcoming exit: “I don’t want to plan too
many [tasks]…since Adrian is in school, it’s mainly Martin and me to [review tasks for
accuracy].”Another way he would work around absences was to ask for deliverables before
departure. In another July 18 meeting, the Chief Engineer asked, “So, Lily, you are leaving on
Thursday. Right?...do you think you can finish these three—actually, four [tasks]?” Holidays
were another threat to task coordination. In a June 27 meeting, the Chief Engineer foresaw a
potential meeting conflict with Independence Day in the U.S. and asked the team, “you guys
want to have a meeting or do you want to postpone to Tuesday?” Although the first two
responses were ambivalent from Lily and Asher, Khalil preferred the postponement, and the
Chief Engineer agreed to move the meeting and send an email to the team.
The Chief Engineer clearly understood the liminal engagements and terms to which he
could expect contractors to complete their work. By August 29, the structure of the team had
changed with several exits and the Chief Engineer accommodated by suggesting moving the
meeting time. He explained,
We used to have lots of contractors helping out, but right now it’s only Harvey and
Asher, and Asher is on East Coast time, so he’s three hours ahead of us…I’m thinking
about moving [the meeting] to 4:00 p.m….Harvey cannot attend the meeting, so I can
have a session with him to explain everything. Do you guys want to do that [for the
weekly meeting]?

The other three members at the meeting agreed. Another element that the Chief Engineer built
into the meeting time, in order to increase cohesion among members, was a tool or technique
demonstration. The Chief Engineer had noticed the difficulty in organizing the globally-
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distributed team, and he introduced his demonstration idea during the August 1 weekly meeting.
He noted,
I realize [that]…since we have people in different locations [and] we don’t work in the
same office, I find that sometimes we don’t have enough communication. Like, after I
implement [something, I find that] lots of people don’t know [about it]. So, I allocated
some time [during] each week’s meeting for people to do a simple demo…Most of the
time people don’t touch…code they don’t know…so we want to get people more familiar
with the product. Make sense?

With a liminal state understanding, the Chief Engineer had no choice but to work around
commitments to higher priorities his contractors had made, subjecting the progress of the
CoWealth product to the unevenness of available staff support.
Turnover as Ongoing Critical Incident. The staff held flexible roles and controlled
their presence at CoWealth through voluntary exits and reentries that did not privilege the start-
up’s objectives, and resulted in confusion and delays. The Chief Engineer made sense about exits
as he experienced them and moderated the workload accordingly. For instance, during the May 2
meeting, the Chief Engineer asked, “…is Meryl still working on this [task]? Because last
[meeting] she said she’s going to go on vacation…” to which Meryl replied on the call, “Hey,
yeah.” During the same meeting, the Chief Engineer said, “Since Adrian is not here, I don’t
know [about this task] – because…Adrian answers to [Quality Assurance] and he’s in [another
country].” The next meeting on May 9, Meryl was indeed on vacation, the CTO was late to the
meeting because he was managing a customer sale, and the Chief Engineer said during the roll
call, “we have everybody else.” As he was setting up the May 17 engineering meeting, the Chief
Engineer said, “Kevin is not going to join. He took two days off, today and tomorrow. He went
to somebody’s graduation, I think…it’s out of town.” During the May 31 call, the Chief Engineer
roll called, “I think we have everybody. Khalil and Lily [are] not available right now so I guess
[we’ll] just get started.” On the August 1 meeting, as he did in most meetings, the Chief Engineer
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ran through the current roster at the beginning, “It looks like we have Kevin, Asher, Chelsea, and
Harvey. I think Martin is still coming back [from a start-up-related trip]…on the airplane. Lily is
traveling. Adrian was working on his Driver’s License today; not sure if he’ll join later.”
The constant entering and exiting did not provide the Chief Engineer with the ability to
know with certainty those members of his team who were on the call, exacerbated by poor
international videoconference connection. During the June 6 meeting, the Chief Engineer asked,
“Travis, [do] you have any update on this [issue]? Is Travis with us? Looks like he is not. So,
[CTO]…you had a meeting with Travis today, right? Do you know what’s going on?” The CTO
said he would follow up with Travis on the issue. Absences were a common occurrence that the
Chief Engineer had to work around. In what was not an uncommon practice, the Chief Engineer
assigned a task to an absent member during the June 6 meeting:
I think I’m going to give this [task] to Asher. He’s not in the meeting today. I will talk to
him and figure out how many [tasks] he can finish. I think since he is both frontend and
backend engineer, he can probably take care of all that. If he cannot, I’ll ask…who is
going to support the backend.

In a review of the tasks during the August 1 meeting, the Chief Engineer said, “This [task] was
originally assigned to Lily, but since she is traveling, I will probably take a look. Or, if Asher can
finish [his tasks] early we can let him take a look.” When updating on a task assignment in the
June 6 meeting, Khalil told the Chief Engineer, “So I couldn’t work on these because…[I] was
short of time on the weekend…I want to start right back on [this task] today.” The work had to
be restructured on the team due to a flurry of exits that varied in reasoning and in the period
before a reentry.
Sensemaking Post-Exits. In considering the contractor exits from a management
perspective, the Chief Engineer sensemade about the process of turnover and the ultimate costs
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of contractors. In an unstructured weekly interview with the founders on April 13, after the
departure of user interface engineer Pamela, the Chief Engineer said,
It looks [like] this part-time work doesn’t really work well. We have been doing this part-
time for nine months, and our [user interface] is delayed, the [user interface] design is
delayed, development work is delayed. So it doesn’t seem to be worth it… From this past
year, I always feel I need one senior engineer who I can talk to about technologies, how
things should be done. I find I’m the only one that can make decisions. It’s hard for me to
do everything.

The nonexistence of a support staff that the Chief Engineer could reliably turn to for advice and
as a sounding board delayed several of the CoWealth initiatives. By April 20, the Chief Engineer
reported he was searching a website called UpWork for a full-time engineer, although he said
“it’s just lots of freelancers.” He began interviewing candidates located in Eastern Europe that
were personally recommended to him through the portal by April 27.
Contractors that had exited the organization reflected on their experiences at CoWealth as
an opportunity for personal edification and as a chance to consider the management strategies
they experienced. One female engineer, Pamela, who was contracted as a part-time engineer for
user interface design from July 2015 to February 2016, and moved on from CoWealth to a real
estate corporate competitor afterward, said of her experience:
I learned a lot from [the CoWealth design change]…since [user interface] is what I really
like to do, it was fun to actually do it…I guess the worst thing: I didn’t have any available
time, at all…I was working for my [San Francisco start-up] company and also during the
weekends [for CoWealth]. It was really hard…I knew they [CoWealth] were waiting on
stuff from me, but my full time job was my priority. And it was really hard to have no
time and know that people are depending on you.

This engineer reported that she was working on weekends for the start-up in addition to her full-
time job. She was struggling to articulate the user interface design in a way that coalesced with
the founders’ vision. She decided to begin work at a corporate competitor located nearby. She
thought of her time at CoWealth as a learning opportunity.
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Another male engineer, Khalil, was hired part-time for mobile application development
in April 2016. Khalil worked full-time for another company and managed five total outside
projects, including CoWealth. He reflected, “My hardest part of my work with CoWealth is
finding time to complete what I commit to. It’s more [because] I’ve been juggling a whole bunch
of other organizations.” Ironically, he recommended against the hiring of contractors for
CoWealth:
Since most of, a lot of, people are part time, it’s difficult getting time and for people to
respond quickly…having a team of people who are part-time is not very optimal. I would
say focus on hiring full time people…it’s going to be the primary day job, [and] they also
would have a vested interest in your being successful. Operating with a mix of full-time
and part-time, I worry that we’re setting ourselves up for failure. People could either
jump ship or people like me who are not in a very good state health-wise might just say
that I’m tired, I’m not feeling well, and drop out. That’s the risk that CoWealth carries.

Both the management and staff perspectives agreed that the contractor model was untenable for
CoWealth.
Dilemma and Dialectics. The three dialectical tensions posed by contractors’ entries and
exits highlighted the dilemma that the Chief Engineer began to assess (see Table 4.1). Although
part-time workers enabled the start-up to keep expenditures low for labor, the liminal
engagements posed significant costs to the Chief Engineer’s time available to manage workers
and plan delivery of the product around frequent exits and reentries. The Chief Engineer
commented, “It’s hard for me to do everything,” including direct the product calendar, the staff
availability and assignments, the patent development, and his own engineering contributions to
the platform. In the sensemaking among both the Chief Engineer and Khalil, full-time workers
were contrasted favorably to part-time contractors for several reasons, including that they
afforded the company a stable knowledge source; had a primary job focus; had a vested interest
in the company’s success; and enabled more efficient communication. The comparison between
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embedded and liminal relationships made by informants brought out the dialectical tension
between permanent and temporary states. In his search for a full-time engineer, in which he
found many freelance professionals, the Chief Engineer also emphasized the tension of
competence and incompetence. The Chief Engineer sensemade about the consequences of
liminal contractors in delayed work products. Khalil sensemade more directly about the further
risks of a mix of part-time and full-time workers on CoWealth’s staff, including workers
“jumping ship” and, ultimately, company failure. Pamela added the immense pressure of
working full-time with a part-time job where a worker is hired based on their skillset as a
dependable function of their role. Discussion about the start-up’s labor model revealed again the
dialectical poles of risky and safe. These contradictions between the expectations of CoWealth’s
ability to achieve its product development uninterrupted and the disruptions posed by the
turnover and churn on the team forced a management dilemma on the Chief Engineer. Although
he valued the breadth of expertise offered by the contractors, the depth of an experienced full-
time staff would yield the efficiency in coordination needed for continuous, agile development
processes. Because the resolution to this dilemma, hiring additional full-time employees, would
cause increased financial costs for the start-up, the Chief Engineer continued to manage a mixed
staff.
Conclusion
The analysis offers a tension-centered understanding of organizational departure through
three cases. The first research question asked about the tensions that emerge and lead to
organizational disengagement. Across three separate cases of exits, across liminal relationships
with a design firm and engineering contractors and an embedded relationship with a founder, two
types of tensions emerged that led to change (see Table 4.2). The contradictions of paradox
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Table 4.2.
Case Summary of Organizational Disengagement Process
Exit Process
Exit Case Tension Before: Role Definition During: Reason After: Sensemaking
Firm Resolved
Paradox
Liminal; Transactional
for user interface
design
Feedback (critical
incident)
Terminated contract,
delivery of wire
frames
Founder Resolved
Paradox
Embedded; Divergence
symbolized in product
plan
Role uncertainty Personal leave
communicated
internally; Fiscal
duty
Contractors Ongoing
Dilemma
Liminal; “Many hats”
metaphor for expertise
across knowledge
domains
Turnover (ongoing
critical incident)
Increased value of
full-time employees

resolved and catalyzed change in the relationships between CoWealth and its design firm and
founder. The dilemma about labor remained unresolved due to the resource constraints of the
start-up and inability to hire a staff that was comprised of only full-time workers. The findings
illustrate that the tensions regarding competence emerged commonly across all three exit cases.
The design firm and founders mentioned tensions about expectations, while the design firm and
contractors mentioned contradictions of risk. The other tensions that emerged were based on the
individual cases.
The second research question asked about the interaction of role definition with
sensemaking and sensegiving of exit in the start-up. In the first case, the relationship of the
design firm to CoWealth was liminal in that it was based on the outlines of an explicit contract
with a transactional basis on time and materials. CoWealth founders developed expectations of a
deeper, more embedded relationship in a psychological contract with the account manager of the
design firm. As a limited engagement, however, feedback proved to provide grounds for
termination as a critical incident. The central paradox of the design firm’s contracted services
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and CoWealth’s expectations resolved upon the design firm’s departure. In the second case, the
embedded relationship of the CTO relied upon a convergent understanding of his role in the
company. The role uncertainty generated by the CTO performing a role that did not align with
the CEO’s understanding of that role manifested in the divergent enactment of the product plan
and created a paradox. The CTO’s exit was not the culmination of a specific critical incident but
the resolution of a dilemma faced by the CEO. In the third case, engineering contractors who
were liminal part-time workers were expected to perform flexible roles to meet the task needs of
the start-up. The metaphor of wearing “many hats” emerged as a cultural norm within the start-
up to describe the expectations of workers. Turnover presented an ongoing critical incident that
the Chief Engineer faced when revising the development plan for the product to accommodate
short and long periods of absence from a regular roster of contractors. The Chief Engineer faced
a dilemma that was not resolved at the end of data collection due to the limited resources of the
start-up.
Among the cases, there was retrospective sensemaking about two different kinds of role
relationships to the start-up: liminal and embedded (see Table 4.3). The relationship of the design
firm and the contractors to CoWealth was liminal. Sensemaking of the exits of liminal
contractors was retrospective based on the critical incident; the rumination of liminal exits was
not as in-depth or lengthy because reasons seemed concrete and tangible. Sensegiving for exits
of liminal contractors used concrete reasons, such as other employment or feedback. The
tensions around the design firm and contractors centered on competence, risk, cost, expectation,
and permanence. The relationship of the CTO to CoWealth was embedded. Sensemaking for the
CTO’s exit was prospective by the CEO and retrospective by all founders because of the
considerable role embeddedness of the CTO as a founder. For instance, after the CTO was
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Table 4.3.
Sensemaking and Sensegiving about Exits based on Role Relationship to Organization
Stakeholders
Design Firm, Contractors CTO/Founder
Relation to Organization Liminal Embedded
Sensemaking for Exits Retrospective based on critical
incident
Prospective and retrospective
Sensegiving for Exits Concrete reasons (i.e., feedback,
other employment)
Abstract reasons (i.e., working
relationship with team)
Dialectical tensions • Competence vs.
Incompetence
• Expectation vs. Reality
• Risky vs. Safe
• Costly vs. Free
• Permanent vs. Temporary
• Competence vs.
Incompetence
• Expectation vs. Reality
• Transparent vs. Secret
• Detached vs. Involved
• Autonomy vs. Connectedness
• Equitable vs. Inequitable

dismissed, the CEO talks about how his departure should have been made a long time before it
did. Sensegiving of exits for the CTO used abstract reasons, such as the working relationships
with the team or information sharing. Because of the embeddedness of the CTO, extensive
sensemaking and sensegiving was generated among the founders. Dialectical tensions for the
CTO focused on expectations, competency, detachment, transparency, connectedness, and
equitability. In sum, for members in liminal relationships with the organization, there arises an
expectation that the projects these workers are on will be completed or they will leave. For
members that are more central to the company, hesitation arises because a significant investment
has been made, resulting in more sensegiving and sensemaking.
The third research question asked about maintaining fluidity after an exit transition.
Sensemaking was involved for both role relationships in exits. Fluidity was maintained by
exploring the environment for replacements of liminal workers because the employment was
based on expertise specialization (March, 1991), similar in some ways to replacing a machine
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part. For embedded relationships, with actors whose roles were more difficult to replace, fluidity
was maintained by sensegiving from management (Gioia & Chittipeddi, 1991). Changing C-suite
level partners requires more sensemaking because it could also incur more information-seeking
from external stakeholders.
Implications
The role relationships and seismic impact of exits in small, early-stage organizations
make them unique contexts in which to understand uncertainty reduction through sensemaking
and sensegiving. Pressures on efficiency and effectiveness exacerbate tensions about role and
expertise expectations. When studying the impact of organizational disengagement on both
leavers and stayers, the liminality or embeddedness of the role must be incorporated in analyses.
Additionally, beyond information seeking, sensemaking about tensions leading up to, during, and
after exits can provide another method of uncertainty reduction and stability in an organization.
Limitations and Future Research
Exits, specifically the firings or abrupt endings to contracts like those presented in this
study, whether they are the result of critical incidents or ongoing role uncertainty are not easy to
discuss in the field because there is often a sense of awkwardness or an emotional attachment to
the departure. The range of data types used to illustrate the picture of sensegiving and
sensemaking about exits reveals that when the exit is perceived to be sensitive, conversation
about it may be scant. Thus, despite efforts to collect robust amounts of data on sensitive exits,
little data was initially available, necessitating the collection of a range of data types through
ethnographic methods.
Another part of future research could be a meta-analysis of recent literature using the
stages of Jablin’s (1987) model: anticipatory socialization, entry, assimilation, and
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disengagement/exit. The analysis could cover types of entry and exit, such as internships during
anticipatory socialization and rotational programs during entry, as well as member relations, such
as among new hires and veterans during entry, and stayers and leavers during exit. Future work
could also theorize an exit stage model based on role (for embedded and liminal connections)
and voluntariness with sensemaking and sensegiving processes building on Jablin (1987) and
Ebaugh (1988).
Acknowledgements
This research was partially funded by entities at the University of Southern California,
including the School of Communication at the Annenberg School for Communication and
Journalism, the Graduate School, and the Graduate Student Government. This manuscript was a
portion of the author’s dissertation project. I am thankful to participants for their helpful
comments on an earlier version of this work that was presented at the 2016 Organizational
Communication Mini Conference at Northwestern University in Chicago. The author thanks the
informants who graciously gave their time and expertise.

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CHAPTER 5

Expertise Role Negotiation: The Change Agent of Transactive Memory

Start-up organizations experience many challenges in developing efficient and effective
processes during their growth into fully-fledged corporations. While only half of all new
businesses founded in the United States succeed in the first five years, start-ups face an even
harsher landscape: about 1 in 10 survive. Much remains to be learned about the precarious
dynamics of high-tech start-ups that balance innovation through complicated dynamics such as
iterative development, multiple technologies, and employee turnover, as well as fiduciary
concerns, including capital investments, investor expectations, and financial solvency.
Organizational theories have the potential to contribute a better understanding of how start-ups
develop systems of coordination for knowledge, people, resources, tasks, and technology,
thereby substantially improving the potential success rate for future small businesses. I apply an
organization science theory—transactive memory theory, which is a theory about knowledge and
expertise coordination in groups—to better understand the development of efficient systems in
start-ups. While convergence of accuracy, sharedness, and validation is the optimal state of
transactive memory systems, the dynamics of these various levels have not been studied in a
developmental context for organizations. Many studies of transactive memory instead revolve
around stable organizations that have already created working transactive memory systems that
can be specified ex ante. My application of this theory to a start-up requires extending the theory
to incorporate negotiations of expertise roles by members and their performance of those roles in
the developing knowledge management system.
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Keywords: transactive memory; emergence; coordinating start-ups; teams; group
processes; expertise

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Expertise Role Negotiation: The Change Agent of Transactive Memory

For the great doesn’t happen through impulse alone, and is a succession of little things that are
brought together… And the great isn’t something accidental; it must be willed.
-- Vincent Van Gogh, October 22, 1882
(Van Gogh Museum, 1882/2009)
5

High-tech start-ups are different from established companies that operate with routinized
structures and communication patterns among members in that they face a higher risk of
company death. About half of all new businesses founded in the United States fail as an
operating entity in the first five years (Duncan & Handler, 1994; Robison, 2014). Only 10
percent of start-ups across industries make it to the five-year mark, and those that do encounter
several near-death experiences along the way (Marmer, Herrmann, Dogrultan, Berman, Eesley,
& Blank, 2012). Among the reasons given by founders for the failure of their start-ups, the third
most frequent reason for start-up failure is not assembling the right team and the twelfth most
frequently cited reason is disharmony among team members (CB Insights, 2014). Yet, start-ups
are almost solely responsible for job growth, and also impact innovation and economic growth
more broadly (Kane, 2010; Reynolds & White, 1997). In early developmental stages,
organizations can succumb to challenges posed by beginning operations, and of forming and
defining group membership, tasks, roles, and expertise. Organization science theories of

5
In the quoted passage, Van Gogh writes to his brother (and patron) about meticulous and
deliberate organization based on principle and discipline. His words open my chapter on the
development of knowledge coordination.
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knowledge coordination, however, have generally been applied to more stable groups and
organizations (Austin, 2003; Majchrzak, Javenpaa, & Hollingshead, 2007).
After initial conception and ideation, but before becoming fledgling new companies,
high-tech start-ups are characterized by an aura of exciting unpredictability. High-tech start-ups
initiate and maintain continuous iterative development strategies aimed at contributing an
innovative product that delivers a group of activities that are new to a set of users in a particular
setting (Rogers, 1995). They coordinate between high levels of interdependence among discrete
experts using limited resources. Entrepreneurs organize new ventures through a series of actions
that are dependent not only on the attributes of the founders (Gartner, 1988), but also on the
nature of the opportunity and the organizing process itself (Delmar & Shane, 2002). Start-up
founders often develop shared cognition during the development of strategy (Ensley & Pearce,
2001). Key decision-makers in an organization interpret and process information differently in
volatile versus stable contexts (Dutton & Jackson, 1987). In volatile environments, such as those
that start-ups face, founders must understand many changing factors to buffer the start-up from
setbacks or losses, and require the use of more information in decision-making to guide the start-
up (Rau, 2006). Founders seek to establish operations in high-velocity environments in which
“changes in demand, competition, and technology are so rapid and discontinuous that
information is often inaccurate, unavailable, or obsolete” (Eisenhardt, 1989b, p. 544). The need
to reduce uncertainty and adapt to these dynamics often requires company founders, or nascent
entrepreneurs (Reynolds, Carter, Gartner, & Greene, 2004), to create efficient and flexible work
routines (Feldman & Pentland, 2003). Founders must contend with imperfect answers and
leadership decisions in an entrepreneurial environment where people, products, and profits face
certain trade-offs (Horowitz, 2014). The needs in terms of tasks, people, and knowledge are
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unpredictable in a start-up, and arrangements for coordinatig expertise shift with moving outlines
of the product design.
During this initial phase of the start-up’s growth, known as gestation, processes are
complex and nonlinear (Liao, Welsch, & Tan, 2005). Gestation can last anywhere from one
month to 10 years, though many complete gestation within three years (Reynolds & Miller,
1992). During this period, task definitions and assignments change, members join and leave,
roles shift, and simultaneous projects are undertaken. The founders can be described as leading a
metaphorical expedition through the uncharted territory of new possibilities, which may turn
back to exploit existing opportunities, strengthening the organization as it forms (March, 1991).
Although it is impossible to define precisely the order of activities in a start-up, some patterns
common to gestation at the organizational level can be identified . Start-ups engage in many
activities spread out over time, adding more activities over time (Lichtenstein, Carter, Dooley, &
Gartner, 2007). Technology-based nascent entrepreneurs engage in less marketing and more
planning, legitimacy establishment, and resource acquisitions than founders of non-technology
companies (Liao & Welsch, 2008). At the group level of the start-up team, the development of
efficient work systems directly contests the start-up’s flexibility to change direction, yet these
systems must be established to enable effective performance.
Gestating organizations present an operational environment that seeks to form order from
chaos, not just in terms of innovating a product, but also in terms of coordinating members’
expertise. When employed in knowledge work in Silicon Valley, members often contribute to the
high-tech start-up’s product under at-will or psychological contracts (Pfeffer, 2001; Rousseau,
1990, 1995; Svensson & Wolvén, 2010). The ability to depart and return to the team fosters an
unclear group identity that emphasizes the leadership of the founders in establishing commitment
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to the shared vision and a sense of resiliency (Buzzanell, 2010). Start-up members often
represent a diverse set of perspectives with specialized knowledge in software engineering,
product management, graphic and user experience design, technical documentation, business
development, fundraising, marketing, finance, operations, human resources and recruiting, and
customer relations and support. The expertise present among members is a necessary but not
sufficient condition for a high-quality start-up product; in addition, this requires effective
management of these interdependencies (Faraj & Sproull, 2000). Members usually have a mutual
connection before they join the start-up team, often a friend or former colleague. Members may
operate remotely and often rely on coordination through distributed task systems to communicate
with the team about their work and collaboration. Members of a start-up are united in a shared
goal, but face obstacles to expertise coordination through an unclear reward structure, changing
group membership, expertise, and skills, and limited time to communicate information they have
(Majchrzak, Javenpaa, & Hollingshead, 2007, p. 149). The internal dynamics of start-ups and
development process for expertise coordination within them remains unclear. How is information
shared and knowledge advanced in a start-up that is in a period of rapid change (gestation)?
Organizational scientists have not examined the coordination of expertise in start-ups,
which contend with high levels of volatility and reconfigurability amidst conditions of limited
resources and fierce competition. Start-ups must develop efficient and effective processes of
coordination to enable them to scale up into larger organizations. Survival of these start-ups may
depend on how the group can recognize and utilize expertise among members.
In this article, I focus on a high-tech start-up in gestation and how it develops a
coordination system for expertise. The objective of this article is to present a theoretical
extension regarding the model of transactive memory development using the context of start-up
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organizations, in which there are several competing, high-priority tasks. I offer an extension of
the model of transactive memory development by incorporating role negotiation, and further
detail the processes of TEP unit construction, evaluation, and utilization in a new model with two
assignment strategies and four expertise claim strategies.
Transactive Memory Systems
Transactive memory theory, which lies within the larger body of knowledge management
theory, and is grouped under information and decision-making theory, offers an explanation for
expertise sharing and coordination to divide cognitive labor within a team. Transactive memory
builds on the metaphor of computer information processing to describe how people in groups
learn, store, use, and coordinate information to accomplish tasks at individual, group, and
organization levels (Wegner, 1987). Essentially, transactive memory theory explains how people
know who knows what in a team, and then how people decide who will do what to engage in
more efficient processes and performance. Transactive memory is a form of shared cognition
within a team. A transactive memory system (TMS) is the shared system that develops naturally
in groups as a way to encode, store, retrieve, and communicate information (Hollingshead,
1998a). Whereas transactive memory refers to the identified patterns that exist in a person’s
mind, a transactive memory system is based on the interaction of people’s individual transactive
memories (Lewis, 2003). People in a group build a pattern of exchange between each other and
objects (e.g., computer software, files) for information they need, and then remember that pattern
and routinize it at a group level, without conscious effort. The cognitive interdependence
perceived by members motivates and sustains a transactive memory system that allows the group
to function, especially for tasks that are complex, nonroutine, and require extensive coordination
(Levine & Moreland, 1999; Moreland, 1999). Transactive memory has been positively related to
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group effectiveness in naturally occurring groups (Austin, 2003; Hollingshead, 2000; Hsu, Shih,
Chiang, & Liu, 2012; Rulke, Zaheer, & Anderson, 2000), virtual groups (Hemetsberger &
Reinhardt, 2006; Kanawattanachai & Yoo, 2007), and laboratory experimental groups
(Hollingshead, 1998b; Lilyg, Moreland, & Argote, 1995; Moreland, Argote, & Krishnan, 1996,
1998; Moreland & Myaskovsky, 2000).
Although Wegner initially conceptualized transactive memory as a theory between
intimate couples or dyads (Peltokorpi, 2008; Wegner, Erger, & Raymond, 1991), a TMS can be
thought of as a network of people who share knowledge through relationships (Jarvenpaa &
Majchrzak, 2008; Wegner, 1995). In these relationships, each member becomes responsible for
certain information, reducing individual cognitive burden while sharing access to a larger pool of
information too sizeable for any one person to maintain through others in the group (Brandon &
Hollingshead, 2004). Information sharing occurs in the transactions, or the communications
between people, and the information itself is viewed as distributed in a knowledge structure to
accomplish task work (Mohammed & Dumville, 2001, p. 103). The allocation and retrieval
processes of information have been explored extensively in communication (Hollingshead,
1998a, 1998c; Palazzolo, 2005; Palazzolo, Serb, She, Su, & Contractor, 2006; Yuan, Fulk, &
Monge, 2007). Communication was one of the first elements linked to TMS development
(Hollingshead & Brandon, 2003; Ren & Argote, 2011), especially for its role in aiding and
supporting cognitive interdependence in the group (Hollingshead, 2001). The strength of
communication ties between people mediates the relationship between directory development
and expertise exchange (Yuan, Fulk, Monge, & Contractor, 2010). A TMS becomes established
when communication between people enacts their transactive memory in the use of information
for completion of tasks in the group.
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Group composition and diversity of knowledge is vital for the development of expertise
in transactive memory systems (Moreland, 1999). Expertise is the know-what, know-how, and
know-why of a knowledge domain (Quinn, Anderson, & Finkelstein, 1996). A person assumes
responsibility for a knowledge domain and becomes viewed as an expert over time as knowledge
becomes increasingly specialized (Wegner, GuiLilyo, & Hertel, 1985). People come to rely on
specific people for access to other knowledge domains in a TMS. As a co-constitutive
communication construct, expertise is established when a person asserts knowledge about or
proficiency on a subject and people surrounding that person use cues available to infer his or her
authority and experience, and then accept rather than reject it (Treem & Leonardi, 2016).
Expertise is attributed to someone by relevant others in the conduct of practice (Yoon, Gupta, &
Hollingshead, 2016) and is a claim to knowledgeability that is negotiated with reference to the
situation in which the claim is made (Kuhn & Rennstam, 2016). Expertise specialization reduces
cognitive strain on a person and redundancy of information in the group (Majchrzak, Jarvenpaa,
& Hollingshead, 2007). The coordinated action between members that is essential to a TMS
requires an understanding not only of who holds what information, but also how that knowledge
fits together (Cannon-Bowers, Salas, & Converse, 1993; Hinsz, Tindale, & Vollrath, 1997).
Members, however, often fail to share or recognize and use other members’ knowledge (Liao,
Jimmieson, O’Brien, & Restubog, 2012).
Transactive Memory System Development
Transactive memory systems are naturally occurring and grow into mature, efficient
systems of coordination over time. The level of development achieved by a TMS can be
determined based on three indicators (Lewis, 2003; Moreland & Argote, 2003). The first
indicator is memory (or expertise) specialization, which is the tendency for groups to delegate
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responsibility and for group members to concentrate on different aspects of the task (Majchrzak,
Jarvenpaa, & Hollingshead, 2007). The second indicator is credibility, which refers to members’
beliefs about the reliability of other members’ relative knowledge or expertise. The third
indicator is task (or expertise) coordination, which is the ability of team members to orchestrate
their work efficiently and effectively based on their knowledge of who knows what in the group.
The greater the presence of these three indicators—memory specialization, credibility, and task
coordination—the more developed and valuable the TMS system is for coordinating activity
among group members. Lewis (2003) outlines how these three analytical elements of the TMS
construct can assist in differentiating between low- and high-performing teams, diagnose issues
with a TMS in those teams, and offer guidance on team composition and knowledge utilization.
The process by which a TMS develops in a group has typically been examined as a linear
progression from immature to mature knowledge coordination between people. The concept of
dynamic development in TMS has only recently emerged with the model of transactive memory
development (Brandon & Hollingshead, 2004), despite several theories that have promoted
nonlinear group development (Gersick, 1988; McGrath, 1991; Poole, 1983). The model of
transactive memory development accounts for evolving cyclical and linear aspects of transactive
memory by emphasizing the role of tasks. In a TMS, group members must not only understand
who knows what, but who is responsible for doing what (Brandon & Hollingshead, 2004, p.
635). Intragroup communication is a form of information processing (Wegner, 1987), and
different tasks (Steiner, 1966) require different types of activity (Larson & Christensen, 1993).
According to the model of transactive memory development proposed by Brandon and
Hollingshead (2004), establishing cognitive interdependence is the first of two steps in creating
transactive memory. Cognitive interdependence can result from a group reward structure
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favoring specialization and integration, a task structure where the outputs and inputs of team
members overlap (Thompson, 1967), or cognitive simplification. The cognitive interdependence
among members feeds into the second step of transactive memory development, when
connections are formed between tasks (T), expertise (E), and people (P) in a TEP unit. A full
TEP unit serves as a heuristic to answer questions such as who should ask a question, or where
information should be stored. A partial TEP unit, however, in which one component is missing,
is not helpful for building a TMS. For instance, if a person knows which members of a group are
engineers, but not how engineering applies to the task (i.e., an E-P relation), or knows that the
group task requires engineers (i.e., a T-E relation), but does not know who engineers are on the
team, transactive memory development may be hindered. Brandon and Hollingshead (2004) note
that a T-P relation is less problematic than E-P or T-E relations, because a basic understanding of
expertise can be constructed by observing a group member’s responsibility for a task. A person
modifies and creates TEP units iteratively through related cycles of (1) construction when a TEP
unit is built, (2) evaluation when a TEP unit is judged as acceptable or in need of reconstruction,
and (3) utilization when a TEP unit is employed for a purpose. Outcomes from the utilization
process are then fed back into construction and evaluation to further develop a TEP unit. A TMS
is of greatest utility when many of these TEP units are commonly understood among group
members, similar to a collective representation of a task (Poole, 1985). In such a situation,
members converge on how accurately a member’s TEP units reflect the true relations in the
group, and the degree to which TEP units are shared across group members. Members validate
the transactive memory system by participating in the system that the TEP units build.
Communication among members facilitates shared understanding of TEP units and leads to the
formation of the TMS, impacting group performance.
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Brandon and Hollingshead emphasized that the TEP is “an ongoing, dynamic hypothesis,
rather than a statement of fact, because the relationships between task, expertise, and person can
change over time in a group” (2004, p. 635). Kanawattanachai and Yoo (2007) confirmed that
task-related communication among members plays an important role in the development of the
TMS among virtual teams. Once the TMS is established, however, task-related communication
becomes less important, likely because the TEP units are stabilized in utilization. Although Ariff,
Milton, Bosua, and Sharma (2012) develop a TEP scale to measure unit formation, research
about TEP units is relatively sparse. I add to this research by exploring the generative
mechanisms that enable the change in these TEP relations and change the broader TMS structure
and group performance.
Expertise Role Negotiation
The partial relationship of person to task (i.e., a T-P relation) poses the least hindrance to
a functional TEP unit, and yet the T-P relation clearly provides the easiest way to newly
designate expertise (E) among members in a group and form a full TEP unit in a developing
TMS. The members of start-up in gestation, and the tools they use, are constantly changing as
the organization takes shape through strategic trial and error, shifting the resources available in
the TMS structure. Leaders or start-up founders can make their TEP units visible by assigning a
person to a task, allowing other members to infer expertise about that person. In start-up
environments with many changing factors, founders’ knowledge about the capabilities and
shortcomings of their start-up team essentially allows founders to identify value-adding activities
(Rulke, Zaheer, & Anderson, 2000). As leaders, founders provide downward communication to
start-up members about job instructions, job rationale, start-up procedures and practices,
feedback about member performance, and indoctrination of goals (Katz & Kahn, 1966, pp. 239-
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241), but the majority of their communication to members concerns task issues (Jablin, 1978).
Founders’ assessment of the expertise that resides in members of the team enables the
assignment of people to tasks (i.e., a T-P relation) and could generate the formation of TEP units
by identifying member expertise to other team members.
Members, however, can structure their own roles in TEP units through volunteering or
offering their expertise and taking on tasks. Members upwardly communicate about what needs
to be done and how it can be done (Katz & Kahn, 1966; Jablin, 1979) during cycles of TEP unit
construction and modification. These moments where members assert their expertise may be
accomplished in-person or virtually, as many start-up members work remotely. Asynchronous
information communication technologies may be helpful for team members in communicating
about and avoiding interpersonal role conflict in asserting expertise, knowledge, or skills (Ariff,
Milton, Bosua, & Sharm, 2011; Carte & Chidambaram, 2004). In matching people with tasks
and expertise, members may respond online to a posted question with their experience
(Mansingh, Osei-Bryson, & Reichgelt, 2014) or volunteer to complete a task and thereby self-
select as an expert into a TEP unit in the group (Hemetsberger & Reinhardt, 2006). Thus,
members can offer their expertise for certain tasks, helping to structure the commonly
understood TEP units.
Members may in fact be negotiating their roles through T-P relations. Role negotiation
occurs when people interact with the purpose of altering expectations about how a role should be
enacted and evaluated (Miller, Jablin, Casey, Lamphear-Van Horn, & Ethington, 1996, p. 296).
Founders and managers may use equivocal messaging (Eisenberg, 1984) to allow members to
develop their role within the expectations of forward motion toward the start-up’s goals. While
receiving role expectations from others, members simultaneously seek to modify these
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expectations and engage in role-making when they pursue competing expectations (Graen, 1976;
Miller, Johnson, Hart, & Peterson, 1999). Role ambiguity or conflict results from mixed
feedback about performance, inability to negotiate informally about others’ influence in defining
their role, and others’ breaking or neglecting to fulfill contracts or negotiated functions (Katz &
Kahn, 1978; Miller & Jablin, 1991). Specific changes to the tasks that members take on require
founders to agree or co-orient (Jablin & Krone, 1987), bolsters the individualization of the role
(Schein, 1968), and, most importantly given the swift pace of change prevalent in start-ups,
allows for member adjustment and organizational adaptation (Graen & Scandura, 1987; Miller,
Johnson, Hart, & Peterson, 1999). As the start-up develops, the role differentiation among team
members working in software development increases, and team members’ mental models about
the group’s work and each other’s expertise tend to diverge (Levesque, Wilson, & Wholey,
2001). Thus, members may renegotiate their role within the organization from the ground up
through TEP units as the organization shifts course. The negotiation may be subtle as TEP units
are not organized deliberately in such terms by organizational members, but emerge at a
theoretical level of organization in groups as tasks are assigned and expertise is designated
among people.
Start-ups in the gestation phase and organizations in early development stages experience
growth and adaption with renewed or diminishing emphasis on the tasks and resources
associated with particular roles as strategy changes. Additionally, start-ups rely on the concept of
swift trust used in quick starting groups and teams (Meyerson, Weick, & Kramer, 1996). As
opposed to building trust slowly over time with repeated interactions, a group assumes trust
initially and verifies or adjusts trust later. In the case of start-ups, swift trust is used when hiring
people based on purported skillsets: the ability to fulfill the position requirements and its tasks
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are assumed present until demonstrated otherwise. Consequently, renegotiation of role
expectations and duties in the start-up (e.g., founder, engineer, designer, business developer)
likely redefines TEP involvement or conscription and has an impact on TMS development. For
start-ups with constantly changing team membership, however, role negotiation may also
provide the mechanism for broader TMS change due to membership turnover. The central
question asked in this study was: How does expertise role negotiation influence a TMS?
Method
Research Strategy and Setting
Aldrich (2001) advocates for process-oriented theorizing and research to capture dynamic
organizational processes. Rather than outcome-driven, the research pursued in this study is
event-driven research to examine the way in which change unfolds during development (Van de
Ven & Engleman, 2004), focused in this study on TMS development. Entrepreneurship scholars
have called for start-ups to be researched in their natural settings to understand their founding
contexts, organizational structures, functions, and performance (Zahra, Wright, & Abdelgawad,
2014). There have been a limited number of studies on transactive memory systems in
workgroups (Austin, 2003; Hollingshead, 2000; Hsu, Shih, Chiang, & Liu, 2012; Rulke, Zaheer,
& Anderson, 2000), and none examine the process of TMS development. Beyond laboratory
settings, organizations in the field “often tackle problems with no unique or known solutions, and
their tasks vary across projects and teams” (Lewis, 2003, p. 589). This study employs the
recommendation provided by Majchrzak, Javenpaa, and Hollingshead (2007) to examine TMS in
context with a group that experiences change. It is the first to scrutinize TMS development
ethnographically, and responds to a need for ethnographic research in management (Watson,
2011). This paper examines the organizing process around knowledge management, with
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particular attention to processes in which the product to be launched is innovative, (i.e., that the
product not been created before and involves new processes), in its natural environment.
Studying the underlying processes of transactive memory system development required a
research setting that allowed for longitudinal analysis of an organizational system. High-tech
start-ups operate in a manner similar to a group of diverse experts. The start-up Collaborative
Wealth (a pseudonym, as are all other names used herein) had several features that made it
purpose suitable subject for this study. First, Collaborative Wealth (CoWealth) had been
conceived starting in 2009, and by 2015 had transitioned into the gestation phase of
development. Start-up activities for CoWealth during data collection included founders leasing
facilities for its headquarters office inside an incubator in Silicon Valley, opening a bank
account, committing full-time to business at the exclusion of other ventures, hiring employees to
work for wages, investing personal money, seeking funding, applying for patents, and preparing
a business plan (Carter, Gartner, & Reynolds, 1996). At the time of data collection, CoWealth
was producing a proof of concept, which is a demonstration to verify that the principles that
undergird its product idea work with real world application among its target user population. The
platform was not publicly operable and the start-up was in stealth mode, which refers to the low
profile adopted by start-ups when developing a unique product (Miller & Wedell-Wedellsborg,
2013; stealth mode, 2016b).
Second, the founders were three nascent entrepreneurs—a Chief Executive Officer
(CEO), Chief Technology Officer (CTO), and Chief Engineer—who played pivotal roles in the
development of CoWealth. The CEO and CTO had previously worked together in a start-up, as
had the CTO and Chief Engineer. Each founder contributed to long-term strategic vision
documents and wrote daily notes to either enact tasks, or to delegate completion of tasks to their
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team. The team included three employees, several rotating contractors, and a number of unpaid
advisors. The documents produced by the founders provided an excellent opportunity to gain
insights into their contemporaneous thinking and the structure of task completion at various
points in CoWealth’s development.
Third, I procured longitudinal access to CoWealth to study the process of TMS
development and shifts in long-term knowledge sharing structures with the consent of the
founders and members. Observations of the team working together during meetings provided
insight how expertise was negotiated in the TMS structure. The work completed at CoWealth
and with their contractors spread across several tools. A total of 66 tools were referenced or
accessed during interviews and observation about the work processes of CoWealth. These tools
each had their own technical vocabularies and interfaces based on various levels of assumed
expertise about users. CoWealth created this complex infrastructure of many products because
the start-up wanted to limit any unnecessary financial expenditure; the tools were used within the
free trial limits provided by the manufacturers of the systems. A routinized pattern among the
tools emerged, and despite its ungainliness, it operated as a temporary mechanism for TMS
development at CoWealth. An unusual but outstanding aspect of CoWealth was that unlike many
start-ups, the company began to build a communication infrastructure of impromptu meetings in
the office whenever possible and regular, scheduled meetings to include distributed workers
beginning in April 2016.
Data Collection
To analyze CoWealth’s development of transactive memory, I used a longitudinal case
study design (Eisenhardt, 1989a). I approached my setting with theoretical preconceptions as an
extended case study (Lichterman, 2002). Case studies have the potential to provoke new ideas
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and build on existing theories (Siggelkow, 2007). This study approaches a specific case with an
understanding of the case as a theoretical construct to enable theory improvement (Ragin, 1992;
Stake, 1995). The case covers the emergence of a transactive memory system in a context where
role negotiation is concurrent with an organization’s early stages of development. I present an
emerging transactive memory system, followed by theoretical reconstruction of the model of
transactive memory development that accounts for role negotiation in organizations that are in
early stages of growth.
The data presented in this chapter is a subset of a larger body of 12 months of
ethnographic research that included data sourced from observations, interviews, and archival
documents collected in-person as well as virtually from sources such as phone calls, video
meetings, project management software, and emails. To ensure interpretive validity, software
engineers who were not part of my sample helped interpret terminology in the data throughout
the study.
Data collected included the recordings and transcripts of 14 engineering team meetings
that occurred on a weekly basis between April and August 2016. The meetings were between 23
and 87 minutes (M=60.31, SD=16.07) and the total 792 minutes were used as raw data for
analysis. I observed but did not participate in these meetings. One of the start-up co-founders, the
Chief Engineer, led meetings on which all start-up software engineers, design team members,
and a quality assurance member participated when able. Occasionally, one of the other co-
founders, the Chief Technology Officer, participated in the call.
Data Analysis
I iteratively moved between data and emerging theoretical reconstruction using the
constant-comparative technique and thematic analysis (Glaser & Strauss, 1967). Analysis of data
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Table 5.1.
Data Analysis Procedures
Analysis Stage Description Outcome
1. Data reduction 1 Restrict coding to set of episodes
involving full or partial TEP
units
337 episodes
2. Theory
reconstruction
2 Identify downward communication
assignment strategies of task and
expertise (T-E) by Chief
Engineer
Two assignment
strategies:
exploiting some
known expertise,
exploring potential
capability
3 Identify upward communication
strategies for expertise (E)
claims in role negotiation
Four expertise claim
strategies:
requesting, advising,
avoidance,
demonstration

aligned with Swedberg’s (2014) idea of building social theory from observation with naming to
concept formation and explanation to theoretical reconstruction (Eliasoph & Lichterman, 1999).
In the first step of analysis, I reduced the data to isolate specific episodes of interaction involving
the assignment of tasks. In the final two steps, I used theoretical reconstruction in the data by
examining the interaction around the construction, evaluation, or utilization of partial or full TEP
units (see Table 5.1).
The first step of analysis involved selective coding of meeting transcripts (and field
notes) to focus on communication in which informants talked about expertise or tasks. An
interaction qualified as a TEP unit if it involved communication between two or more people on
the start-up team and the conversation was directly related to tasks, expertise, or people for the
progress of work in the start-up. I began each unit of analysis at the first instance of negotiation
and ended it when the informants switched to another task or ended communication about work.
The coding criteria were initially broad to capture the range of interaction involving TEP units
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and yielded a total of 337 instances (see Table 5.2). The analysis focuses on the process of TMS
development to illuminate the ways in which role negotiation and tasks are coordinated among a
group of experts.
Findings
In addition to establishing cognitive interdependence within the group, staying on the
team and achieving more responsibility involves the discussion of the reward structure in early
stage organizations. In CoWealth, these discussions were managed one-on-one with the Chief
Executive Officer. Thus, expertise specialization was particularly important to elevate one’s
status on the team.
In an effort to both create a task structure and simplify the cognitive demands on the
globally distributed engineering team at CoWealth, the Chief Engineer scheduled a weekly
videoconference meeting. Based on the previous months of observation, an operational TMS had
not yet existed on the engineering team, delaying progress, and the weekly meetings were an
attempt to launch an implicit but operational TMS. During this meeting work in progress and
completed work was reviewed. The product team relied on a version of the Agile development
framework and its nomenclature to allow for cognitive simplification, one of the prerequisites for
cognitive interdependence. Agile methodology prescribes a regular check-in point after an
interval of time, known as a sprint. At CoWealth, the sprint occurred weekly. As the sprint
meetings were engineering-focused, the general expertise area under discussion was software
programming, though members on the engineering team within the start-up specialized in
various expertise areas within that knowledge domain. During the sprint and at the sprint
meetings, members discussed the intricacy and interrelatedness of work units for platform
development in a nested-term task structure: tasks within stories, and stories within epics. For
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Table 5.2
Categories and Codes of TEP Unit Development Episodes
Category Code Definition Example Episodes
Assessing
Convergence
The final step in the TMS
development cycle where levels of
accuracy, sharedness, and
validation in a group are assessed.

Staff Availability Chief Engineer notes schedule
availability of staff.
“So this [story]: investment display
identity. Is Meryl still working on
this? Because last [meeting] she
said she’s going to go on vacation.”
22
Product Strategy Chief Engineer discusses tasks in the
context of user experience strategy
in the product.
“So here we need actually two input
boxes. One is the address. Another
one is the listing price. So when the
user clicks on the ‘Convert to Deal’
here is what’s going to happen…”
6
TEP Evaluation The process by which feedback and
commentary is given about the
performance and function of a
TEP unit.

Task Finished Members share comments about tasks
completed.
“After a whole bunch of analysis, I
finally got the first draft of the
[platform] notifications [finished].”
9
Task Delayed (include
didn’t work)
Members provide personal reasons
for delays in task completion.
“I don’t have much time so I didn’t
really look at a lot [of stories]
myself.”
25
Missing Resources Members identify missing resources
for unfinished tasks.
“Right now the problem is that we
don’t have their files, but we do
have their history.”
2
Lessons Learned Chief Engineer provides broader
takeaways from the past week of
tasks.
“I think one lesson we learned is we
have to clean up the [quality
assurance coding] environment
once in a while.”
3
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Category Code Definition Example Episodes
Need to Discuss Chief Engineer decides that further
discussion of a task is needed after
the meeting.
“In this [task], basically Adrian
reported an issue that is we treat the
username as case sensitive, but he
thinks it should be case insensitive.
This is something we need to
discuss before we do anything.”
21
Coordination Members comment about how they
are working together.
“I have been working with Michael. I
was hoping that Michael was going
to send over something yesterday
but he hasn’t so I’ll ping him
again.”
25
Questioning Members bring up questions about
task and process.
“So here’s a question I have…even
though we are calling ourselves
Agile, we seem to be going into
waterfall mode. So my question to
the team as a whole is how can we
not do it waterfall?”
24
TEP Construction The process by which groups use
relevant information to build
either partial or full TEP units
cyclically.

Task Creation Chief Engineer creates tasks aimed to
provide users with the ability to
definitively perform a function or
proceed through a logic flow on
the platform.
“For this story, it’s for our investment
detail page. We need to add a
button.”
17
Dependent Task Chief Engineer identifies tasks that
are dependent on another task.
“After you finish the whole design, we
probably need to do a review. And
after that, I will write stories to
break down the stories to smaller
pieces.”
1

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Category Code Definition Example Episodes
Missing Information Chief Engineer identifies tasks that
have missing information.
“This [story] is for exception
handling. We don’t have any
tasks…Yeah, and you also need to
talk to him about this one.”
2
Need to Discuss Chief Engineer identifies tasks that
require further conversation.
“Now when I look at this one [story],
it’s probably not so
straightforward… We will talk
about this tomorrow, this week.”
3
Unresolved Task Chief Engineer identifies tasks that
are incomplete.
“I don’t know… I'll just leave it like
this [in the notes]. Say if we want
to put a new address or update the
email here.”
2
Task Creation by
Members
Members create tasks. “Again, this should be pretty
straightforward. If there’s an
update on a particular issue or you
need to close out a particular issue
or add comments, you just add
activity and it will be added to the
timeline.”
6
Bug Fixes by QA Adrian creates tasks by finding
problems to correct during quality
assurance testing.
“So whenever I select a different
language, the sign in page did not
display the corresponding language
correctly.”
11
TEP Matching The process by which groups connect
tasks with people.

Exploiting assignment Chief Engineer assigns the task to a
person without much discussion,
implies high-credibility expertise.
“I’m going to upload the document
and I’ll give this [story] to Lily.”
34
Exploring assignment Chief Engineer asks the team broadly
about the task, then narrows in to
identify a potential person.
“So that is a security issue. So who is
going to take this? Maybe I should
give this to Harvey? Harvey, do
you think you can take this?”
9
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Category Code Definition Example Episodes
Self assignment Chief Engineer assigns tasks to
himself.
“I assigned this story to me. It’s more
about finding out how we want the
application to behave.”
9
Tool assignment Chief Engineer assigns tasks to tools. “Last week we set up the [continuous
integration (CI)] that can do unit
testing. So right now if anybody
checks in the code, CI is going pull
the source code and do a build.”
4
Member assigning
other members
Members assign tasks to other
members.
“Can you assign it to Asher and let me
finish up the homepage because I
already spent time on it?”
1
Expertise Claims The process by which members assert
a claim about their expertise
specialization.

Requesting Members assert expertise by asking
for task assignments.
“You can just assign it back to me,
and then I will take a look at it.”
4
Advising Members assert expertise by
providing recommendations about
task or process.
“Whenever I try to push [code
updates] and the server complains,
then that’s the time I do the file
from the ID.”
2
Avoidance Members avoid assignment of tasks
based on non-expert knowledge.
“I don’t know JavaScript either.” 2
Demonstration Members assert expertise through
presenting skills or knowledge in a
specialized area.
[Screensharing with the team] “So
every time you upgrade a version
or you add a library, it will change
the package.json, that’s the only
thing you need to check.”
7
TEP Utilization The process by which a TEP can be
used, or when a member can ask a
question or give information to
another member.

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Category Code Definition Example Episodes
Workflow Review Chief Engineer facilitates meeting
and workflow.
“Let’s go through our routine first and
then we have a few things we want
to talk about.”
19
Releases Chief Engineer discusses the release
updates (i.e., code tasks completed
but not yet in public use) to the
platform from the backend.
“I [thought we could] cut a branch
next week, but it looks like we have
a few more stories to handle, so we
need to postpone it to May 30.”
10
Sprint Length Chief Engineer proposes changes to
the length of time between the
team’s sprint meetings.
“We want to try a two-week sprint. Is
that good for everybody? In the
past, we [didn’t] have a lot of
people, so the progress was not that
fast. Maybe we [should] try a two-
week sprint and give product
manager, QA, more time to accept
stories and do testing.”
3
Story Schedule Chief Engineer comments on
managing the workload of stories
in the sprint.
“So if you look at that the current
sprint on the backlog we have 68
[stories]. Now we’re down to 15
[stories].”
25
Workflow Review by
Members
Members comment on workflow. “I think the current process will work
fine with just a little bit more fine
tuning. Maybe also responding a
little bit earlier to the questions…”
21
Workflow Clarification Members suggest alterations to work
processes.
“Maybe we can come up with a
common guideline on what to do so
that each of us can go over it and
make sure we are following the
right procedure.”
8

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instance, the project for a new product could contain an epic such as “new website frontend”
with stories such as “write copy for page A” or “code template for pages,” which could each
have tasks embedded within them in order to accomplish those stories. Usually within a week,
the task structure outlined a schedule where the product team worked on multiple stories, which
were composed of several tasks. Before implementation, designated quality assurance members
checked on the completed development work to determine whether it met the criteria for the
story to function properly with users. If the work was rejected due to problems, new tasks to fix
these bugs were created within a story for the next sprint. If the work was accepted, those stories
branched off from the larger body of ongoing development work and were then implemented in a
release to the website. Every three to four weeks, updates to the platform were released online.
The Agile framework served as a backdrop for cognitive simplification and task structure
between members, and in combination with the reward structure of the start-up, enabled the team
to establish cognitive interdependence and the foundation for the formation of a TMS.
With cognitive interdependence established, the start-up clarified the cadence of its
product work to support the development of a TMS. The sprint meetings provided an explicit and
routinized task structure with clearly defined segments; the weekly forum gave members space
to strengthen their individual expertise specialization, credibility, and task coordination
collectively. When explaining the meeting process to a new engineer, the Chief Engineer said,
“in each meeting we will talk about – we have [a] ritual.” The Chief Engineer directed the
weekly sprint meetings and limited them to under an hour and 30 minutes. There were five parts,
called rituals in Agile Scrum terminology, that made up the weekly sprint meetings. These
components of the sprints allowed for the implicit formation of the mental model and
coordination of TEP units among team members. First, the opening allowed space to discuss
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factors that might be enhancing or detracting from the accuracy, sharedness, and validation of the
group’s mental model of task interdependence. The second and third meeting segments, the
retrospective and a review of the week’s previous work, enabled TEP evaluation, TEP
utilization, and claims of expertise among members negotiating their roles. Fourth, task creation
and the matching of people and expertise to tasks supported TEP construction for the upcoming
week’s sprint plan. Finally, a demonstration of a task or technique enhanced TEP expertise
credibility and specialization on the team. After each of the five sections and at several points
throughout the meeting, the Chief Engineer made time for questions from the rest of the team,
felicitously encouraging TEP development.
Assessing Convergence
Assessing the convergence, or level of accuracy, sharedness, and validation of a
transactive memory system in a group (Brandon & Hollingshead, 2004, p. 634), is the final step
in the cycle of TMS development. During fieldwork, I observed two levels of TEP units in
discussion during sprint meetings that supported the development of an effective shared mental
model in the engineering team. Because tasks were highly interrelated between members of the
team, it was essential for the group to discuss individually-assigned tasks, for which a person
was responsible for completing. These task discussions implicitly formed TEP units and also
contributed to the development of the group’s task coordination system of encoding, storage, and
retrieval. The second level of coordination in TEP development was the macro-organization of
those TEP units and involved the interaction between the team members during the meeting to
coordinate and utilize individually-assigned tasks in the workflow. Beyond tasks that
demonstrated their expertise in engineering, members would offer their expertise on the
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coordination of task structure between members, which had the effect of strengthening cognitive
interdependence.
Meetings began with a discussion of members’ availability to work on tasks or
foreseeable changes to availability—such as when the sprint schedule collided with holidays and
a member joined or departed the team—or issues that affected the whole team. During data
collection, two remotely-located software engineers and one co-located design team member
were introduced during the second month (May) of sprint meetings, and one co-located design
team member was introduced during the fifth and final month (August) of sprint meetings during
data collection. The Chief Engineer noted the intermittent unavailability of one engineer because
he perceived she brought highly credible expertise specialization to the team. When she returned,
the Chief Engineer said, “Before we go to the retro, first, Lily's back. So, basically, Lily was on
vacation for about three weeks. Now she is back.” At other times, when members could not
attend the meeting for personal reasons, the Chief Engineer explained this absence to the team,
saying, for instance, “He took two days off, today and tomorrow. He went to somebody’s
graduation,” or mentioning that the availability of a quality assurance member would be greatly
diminished when he began a nearby graduate school program. With general awareness of
member availability, planning could accommodate shifts in workload or deadlines, but
acknowledgement and discussion of member availability and resources were necessary for task
coordination. For instance, the Chief Engineer said to the team, “This [task] was originally
assigned to Lily but since she is traveling, I will probably take a look [at the task]. Or, if Asher
finishes early, [he can].” These entrances and exits of members on the team were important as
notifications because they enabled the team to converge on a shared mental model despite the
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presence of new members or absences of existing members that might have otherwise
invalidated the formation and convergence of the developing TMS.
Task-Expertise-Person Unit Evaluation
In the model of TMS development, Brandon and Hollingshead (2004) argue that TEP
units should be viewed as working hypotheses of a group’s shared mental model. The authors
posit that when a group member’s task fails to operate properly, credibility is negatively
impacted, and leading group members reassess a TEP relation. The leading members may
require a reconstruction of low-credibility or partial TEP units from the responsible member.
They may also decide whether to reorganize the hierarchy of members on a TEP unit based on
newfound credibility status, essentially demoting a member. Evaluation is the process by which
feedback and commentary is given about the performance and function of a TEP unit.
Sprint meetings launched first into TEP evaluation with a retrospective component during
which members reflected on processes that did or did not proceed accordingly during the
weeklong sprint. The Chief Engineer familiarized a new engineer with the meeting process: “For
this format, what we’re going to talk about is what went well in the last week, what didn’t go
well, and what can be done differently. Different people have different opinions. So who wants
to go first?” This component of the meeting was devoted to evaluating task completion
explicitly, and TEP units implicitly, on the team. He further commented during the meeting, “So
for the ritual what we do is, because most of the people are remote, usually, I just share my
screen. When people talk, I’ll just keep writing and keep the record.” The Chief Engineer took
notes in an accessible shared document, and also shared the document on his screen in the video
conference call, to coordinate knowledge among members while simultaneously building a
storage repository that could be referenced later.
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Members often shared positive comments about progress in their task in short comments
at the beginning of the evaluation period during the retrospective. For instance, one engineer
reported, “After a whole bunch of analysis, I finally got the first draft of the [platform]
notifications [finished]. If everybody could just take a look at it and provide a comment, I’ll
modify. That, to me, was a big thing.” Generally, the team did not offer as much valence-laden
reflection on larger issues because their expertise role often related, on a more micro level,
directly to the TEP units in which they were involved. The Chief Engineer implored his team
members to speak up about obstacles they encountered, saying at one point “I really want to hear
[about] problems we had so that we know what we didn’t do right, and we can fix either the
process or something else.” The Chief Engineer, possibly because of his position’s ability to
oversee the various TEP units of the TMS working together, delivered broader takeaways from
the past week. For instance, “I think one lesson we learned is we have to clean up the [quality
assurance coding] environment once in a while. Otherwise you cannot reliably test [developed
processes].” Unless it was a catastrophic problem for the team, individual task issues were
usually revealed, immediately following the initial retrospective, in the sections of the meeting
on previous and new tasks.
Next, the Chief Engineer reviewed specific previous tasks and stories and engaged
members about their performance through the week’s TEP units. Designated specifically to gain
deeper clarity about tasks, the review was a group conversation where the Chief Engineer asked
about story and task progress, completion, or issues, and established the evaluation phase of TEP
units. Even if there had been an earlier meeting between a smaller group of the members, the
Chief Engineer explained the value of coordinating: “Maybe we [should] just go through the
stories because [even though] we already had a meeting today…I think it's better if everybody
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has some kind of [common] understanding.” In task review, members felt able to express a need
for clarification on tasks. While evaluating TEP units, this part of the meeting served as a
unifying and inclusive component of expertise and task coordination in the team.
Some of the common reasons that TEP units did not accomplish their tasks were detailed
in the meetings. Engineers indicated several factors that posed obstacles to task completion.
Often, they provided reasons for delays that were not related to their knowledge domain
competence. Missing resources impeded task completion: “Right now the problem is that we
don’t have their files, but we do have their history” or “Meryl needed a working math [formula]
on some [user interface design element]. I think she’s still working on that.” Time management
was an issue for the Chief Engineer, who reported, “I don’t have much time so I didn’t really
look at a lot [of stories] myself.” Explaining why one task had not been completed, one engineer
said, “I was short on time this weekend.” Engineers often reemphasized their commitment to
TEP completion to negate designations of low-credibility on an expertise area. When asked
about the status of tasks, they often made future commitments to excuse a late delivery, invoking
time or work units, rather than gaps in expertise specialization. One engineer said “I know I need
to finish it or complete it…maybe tomorrow before noon” and another said “I [will] test it when
we do the next [programming] cleanup.”
Engineers, however, admitted when a task required additional training or a search for
relevant expertise beyond their own and the team’s purview and did not seem to face low-
expertise credibility attachments. One engineer said, “I don’t have a complete solution and it’s a
work in progress for me.” An exchange between an engineer and the Chief Engineer illuminated
how the knowledge-based innovation in which they were engaged required an aspect of self-
tutoring:
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Engineer: For the past week, I didn’t control my progress…so I spent too much
time on research…[and] I cannot [complete] those stories as
expected.

Chief Engineer: …that’s hard to say if it it’s a good thing or a bad thing. I think no
one is an expert on [that task]…Work close on those stories. [You]
probably need about one more day to finish?

Engineer: Yeah.

Rather than being responsible for knowing the full depth or breadth of expertise for the range of
tasks individual members were assigned, engineers were encouraged to problem-solve and
solution-find. They were not at risk for losing credibility when the expertise was not available
elsewhere on the team.
During evaluation, two types of elements emerged that could fill the P of the TEP unit:
people (P) based on their expertise or tool objects (O) depending on their functionality. For
instance, the Chief Engineer explained
Last week we set up the [continuous integration (CI)] that can do unit testing. So right
now, if anybody checks in on the code, CI is going to pull the source code and do a build.
If there is any unit test failure, it’s going to send out an email to whoever checked in [at]
that time.

Team experts were able to encode tool objects to perform the functions of both storage and
retrieval in their stead. Objects were transformed from passive items into actors, called into use
when a member needed them, to generate work on behalf of the team. While the capabilities of
encoded programming tools increased team efficiency in retrieval, the team also worked with
limitations on communication and storage tools they employed. The team used the free versions
of many products essential to their programming work to keep costs low, but these tools placed
caps on utility. Members considered the designed constraints and freedoms of tool objects in
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completing their work and evaluating others, both people and objects, on their TEP unit
performances.
Task-Expertise-Person Unit Construction
Brandon and Hollingshead (2004) posit that groups use relevant information to build
either partial or full TEP units cyclically. Importantly, they suggested that having one or two
components of a TEP unit, such as the task or the expertise, could imply the other components
necessary in a work group. In their explanation, tasks are created and assigned top-down by
leading members and revised based on a recurring cycle through the TEP unit evaluation and
utilization process. In software development, however, members iterate on an innovative project
that evolves with improved ideas and tasks that are created top-down by a Chief Engineer, as
well as bottom-up by other members as they discover functionality issues or introduce new
design-based logics for users on the platform.
Task Creation. Not necessarily separate from the review of the last sprint’s progress on
stories, newly generated stories and tasks were introduced during the fourth segment of the
meetings about the next week’s task agenda. Task creation emanated from engineering and
design planning, and from quality assurance bug issues. These tasks were aimed to provide users
with the ability to definitively perform a function or proceed through a logic flow on the
platform. The Chief Engineer would explain new stories about engineering with all members by
detailing the tasks required. For instance, he introduced one new story by saying, “For this story,
it’s basically our investment detail page. We need to add a button…on our link. When we click
on that, it goes to [another] page…The definition…[is] in the state Java.” In this example, the
story was the investment page that displayed details and the task was creating a clickable button
that would lead users to another page using the coding language Java. A member of the platform
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design team often outlined the logic of higher-level design stories without specifying engineering
tasks. Using a screen share to show a page design as a visual tool, the platform design member
explained, “…any sort of activity that happens…will be tracked here…Then the timeline on the
right will change and reflect the specific activities with whichever event is selected. It should be
pretty straightforward. Nothing too complicated here.” The quality assurance member explained
a new iteration of an old task with bugs to be fixed, a result of problems encountered while
testing the usability. One quality assurance member explained,
On the account page, User A can change his email address and, currently, if User A is
typing in an email address [that points] to another user[,]… the system will send out the
email change confirmation email to the User B's email address. When User B clicks on
it[,]… it goes to an error page as shown in the attachment. So if User A is changing his
email address and typing in an email address corresponding to another User B, the system
should not allow him to do so.

The quality assurance member introduced tasks that were bug fixes or corrections to current
platform functionality. In all of these instances, the construction of the task was itself a TEP unit,
using members’ knowledge to construct tasks that would later be assigned to individuals or
groups of members.
Task creation was sometimes only a partially achieved TEP unit because members could
not always solidify the quality assurance and design problems or pose identifiable engineering
solutions. Sometimes, task ideas or problems were presented partially articulated. One design
team member responded to the presentation of an idea, “I don’t think it’s the same thing. I don’t
think we’re talking about the same problem.” Often, more discussion was needed outside of the
meeting to clarify tasks and complete task creation:
Engineer: I tried to reproduce about the bug as what [the quality assurance
member] mentioned. But I didn’t – I cannot reproduce a bug. So I
didn’t see the error as what you described.

Chief Engineer: Okay. Let’s have an offline meeting to talk about this.
156

Quality
Assurance
Member:
Yeah.

Chief Engineer: So we can go over what the problem is.

Sometimes, tasks also changed as a result of problems identified on the platform. When the
quality assurance member suggested a task modification on the shared document, the Chief
Engineer responded, “Yeah, I agree. And that is my fault. Yesterday, I changed something…so
I’m trying to delete the [task] we’re not using.” With the start-up, knowledge workers’ work is
innovation, and that includes facing problems that require input from more than one expert on
the team.
Task-Expertise-Person Unit Matching
After task creation, the Chief Engineer would record the stories and tasks on the shared
document, explain them, and assign those that were ready, matching people to tasks and forming
TEP units. The Chief Engineer used two strategies in TEP unit relation matching: exploiting a
high-credibility expertise or exploring a potential expert capability. When exploiting a high-
credibility expertise, the Chief Engineer often assigned the task to a person without much
discussion: “I want Kevin to help with the testing” or “But as for now, it’s just assigned to you”
or “Maybe you can work on this [task], too, after you finish those three.” Sometimes he would
ask the member, but the selection often implied high-credibility expertise on the team and a non-
choice for that member. For instance, he said, “So we have customers complaining about this but
I don’t know how to fix it…Do you think you can handle this, Lily?” The engineer replied,
“Yeah, I think I could…Yeah, this is where I said last meeting that we need to [make] some
improvement on that page. Yeah okay, I’ll take a look.” When the Chief Engineer explored a
157
potential expertise on the team by matching a person to a task, he would ask the team broadly
about the task, then narrow in to identify a potential person: “So that is a security issue. So who
is going to take this? Maybe I should give this [task] to Harvey? Harvey, do you think you can
take this?” and “So is this still a problem?...Asher, do you mind if I assign this to you?” In these
separate cases, the engineers each responded, “I can take a look.” The response to the Chief
Engineer when assigned a task that did not necessarily fall in the member’s expertise purview
was often to “take a look,” and members were careful not to promise completion. For some tasks
of higher priority, the Chief Engineer assigned them to himself to form the TEP unit. When
reviewing tasks he sometimes provided explanations of these self-assignments such as, “I
assigned this story to me. It’s more about finding out how we want the application to behave”
and “I guess…I understand this better, so I’ll just assign this to myself” and “I’ll assign this to
me. I need to figure out how it should work.” The accuracy with which the Chief Engineer
distributed knowledge responsibilities to team members bestowed credibility on himself as a
manager and on team members by acknowledging their skillset, and enhanced the effectiveness
of the transactive memory development.
TEP unit matching was not always top-down by the Chief Engineer, but also bottom-up
as members claimed expertise by volunteering responsibility for tasks during meetings. There
were several moments during the sprint meeting in which members could assert a claim about
their expertise specialization using the strategy of requesting a task. During task reviews, one
engineer said, “Yeah, just assign it to me. I’ll double check” and the quality assurance member
said, “You can just assign it back to me. And then I will take a look into it.” The Chief Engineer
rarely rejected members’ requests for tasks; this happened twice in the dataset, with the rationale
that the Chief Engineer could reassign the task to another member and pause the task until
158
further information could be acquired. Members also recognized the expertise specialization of
others on the team to assist in matching. For instance, the Chief Engineer asked, “I think we
should assign this to Asher, right?” when Asher was not at a meeting. Recognizing Asher’s
expertise specialization, another engineer responded, “Yes. Those [tasks] are for the [user
interface (UI)].” Later during the meeting, the Chief Engineer assigned Asher two more tasks
because “those are UI issues.” In another meeting while discussing a task, another engineer
asked the Chief Engineer, “Can you assign it to Asher and let me finish up [another task],
because I already spent time on it?” In the online shared document the team used for
coordination, engineers were also given the ability to assign tasks, once they had completed the
programming, to the quality assurance members before testing. As a more diffused process, this
was not always well orchestrated. One quality assurance member clarified the TEP matching
process:
One more thing to remind everybody [about]…when I was working [in the system]…I
found some tests being completed that [were] marked as [quality assurance] had seen
them. If you forget you assigned them to me or Martin, it’s fine. But please remember to
mark as resolved if you’ve finished working on [the task]. We will assign those resolved
issues to ourselves [to review].

The bottom-up assignment process was encouraged by the Chief Engineer as part of the Agile
framework. For one task, he said to an engineer, “When you fix the logic on the server side, you
can assign this to either Asher or me [and] we can fix the front end.” TEP units were often
formed not only by the Chief Engineer, but also by members of the team as they sifted through
interrelated tasks during sprint meetings.

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Task-Expertise-Person Unit Utilization
The TEP development model (Brandon & Hollingshead, 2004) outlines a cycle of
utilization whereby a member can employ information stored in a full or partial TEP unit.
Utilization is when a member can ask a question or give information to another member.
The engineering team shared ideas about who knew what on the team, especially as they
matched people to tasks and formed TEP units. As an emerging TMS, other moments during the
sprint meetings revealed that members still needed to determine expertise specialization on the
team, and opened opportunities for three more types of expertise claims: advising, avoidance,
and demonstration.
Frequently during the review of the previous week’s tasks and the TEP unit evaluation,
next steps on task completion would be coordinated between members, and questions and
resolutions would be exchanged. Team members negotiated the roles they could play in the
macro-organization of TEP units, which comprised the developing transactive memory system,
by revealing their knowledge domains beyond the tasks they were assigned, which had formed
other implicit TEP units. At the organizational level, because tasks often rolled into the next
sprint if unfinished, the organization of TEP units, and the sprint meeting itself as a macro-
organization system, became a discussion topic that recurred over several sprint meetings. At
least three engineers and a design team member offered their advice on managing the workload
differently than the Chief Engineer. On one call, Lily said, “I think in terms of improving the
process, …we have to improve the way we do planning…We [should] try not to think about
hours [tasks take]” and recommended the Agile method of adding a Fibonacci point system to
tasks based on their complexity. In this system, the points assigned to a story generally
correspond to the number of working days needed for one person to complete it at the rate of six
160
hours a day. Another engineer chimed in, “What we should think about before we assign
[points], we need to have a baseline…So I think if we go back and stratify what we’ve already
done…to have some idea [of] what complexity looks like.” The design team member responded
in the meeting,
I think the reason why we’re rolling things over is because they may be done but [don’t]
get a chance to be tested until the next week…making the change to two to three day
builds might help…because I’ve worked in teams where we did look at hours.

Lily explained, “Because if you think about hours, your velocity [of work output] could never
improve because that’s all you have, 40 hours. But if you go with Fibonacci, then…we can chart
our velocity.” The Chief Engineer chose to adopt the Fibonacci system for stories, but not the
two-week sprint that members also recommended in this dialogue. During a later call, another
engineer commented, “I think we…rush promoting [quality assurance] to production. So I think
we need to plan a little bit better with the resource level for the actual job…I think we need to
standardize [the timing].” The Chief Engineer took note of these recommendations and adapted
the system to provide at least 24 hours for coordination between the tasks.
Members established claims to their expertise and refashioned the shape of their role on
the team with the strategy of advice-giving on specific tasks that may not have been directly
assigned to them. After one member demonstrated a way to resolve conflicts in merging work on
the same task and emphasized commenting, Lily said, “Normally, I don’t use much commenting
[on my programming tasks].” When another engineer asked for more information, Lily explained
the contingency in which she would comment on her work. When members did not have the
specialty on hand, they often conducted research to self-teach or increase efficiency and expand
their domain of knowledge. One engineer reported, “Now I just need to put things together…I
found a good library out there that we can use. So I don’t have to do everything from scratch.”
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Members avoided expertise specializations that they did not want to assume under their
role. The Chief Engineer excluded a quality assurance member from a task based on both
available time and expertise, saying to the team, “I don’t think [the quality assurance member]
knows JavaScript, and [he] is going to go to school in August. So I already have…maybe a little
more than two months. And Martin is going to take over for a while.” Martin was quick to tell
the team, “I don’t know JavaScript either.” Establishing an absence of expertise specialization
was an essential component of the role negotiation process, especially in an environment where
self-education and learning to develop expertise was encouraged. Not all opportunities for
expertise claims were taken in this emerging TMS, despite encouragement of member input and
self-education. For instance, the Chief Engineer and an engineer discussed a task and expertise
specialization:
Chief Engineer: So who’s the expert on Git?

Engineer: (long pause) You.

Chief Engineer: Well no…I was trying to fix [it] last year, but I couldn’t. I couldn’t
figure out how it works…I tried a few things but it still doesn’t
work…So who knows how to rewrite the Git history so we can
[complete this task]? No one? Okay. That’s fine. I guess we’ll just
leave it for now until we find someone who can do it.

In this case, no team member claimed expertise or offered to learn this specialty as part of their
role. The Chief Engineer recognized that the gap in expertise would remain unfulfilled until
additional members with this specialization could be added to the team. Members assessed and
remembered expertise credibility, whether claimed or avoided, and understood where to retrieve
the information in the developing TMS.
In the fifth, concluding, segment of the sprint meetings, the Chief Engineer or a team
member demonstrated a task or technique as a way to bridge understanding and coordinate
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expertise on the team. Members shared their screens and delivered their presentations at the
advance invitation of the Chief Engineer. He explained to the team,
I realize [that] in the past since we have people in different locations [and] we don’t work
in the same office I find that sometimes we don’t have enough communication. Like after
I implement [some task], lots of people don’t know [about it]. So, I allocated some time
during each week’s meeting for people to do a simple demo. It could be just a feature
[and] how it works. Most of the time people don’t touch [the] code [if] they don’t know
such a feature [exists,] so we want people to get more familiar with the product.

As mentioned earlier, one engineer demonstrated resolving conflicts in the codebase, but he also
demonstrated another programming task on deployment. At one meeting, the Chief Engineer
requested a demonstration from a team member, saying,
I want Lily to do a demo on the JSPM. I think…the only person who understands that is
probably Lily. I know a little bit but not that much, so maybe Lily can do a demo, just to
show us how it works.

The Chief Engineer also delivered demonstrations on supporting multiple languages in the
platform and a marketing page for an aspect of the product. These demonstrations enhanced
expertise credibility of members on the team and allowed them to claim domain knowledge in
the developing TMS.
Conclusion
The central finding of this study is that people use expertise claims to negotiate TEP units
and their role in developing transactive memory systems. As the application of existing theories
alone to a new setting does not contribute meaningful theoretical development (Corely, & Gioia,
2011; Whetten, 1989), these findings counter four basic assumptions of the model of transactive
memory development proposed by Brandon and Hollingshead. The first assumption is that a
degree of routinization in terms of resources and people is assumed in the organization already.
As Majchrzak, Javenpaa, and Hollingshead (2007) outlined, knowledge coordination among
dynamic groups that respond amidst constant change are relevant in everyday contexts. Some of
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the problems encountered by the engineering team at CoWealth could be broken down into
smaller tasks for TEP units, while other could not. As the vision for the platform shifted to
incorporate new innovative features, or necessitated halting development of other aspects such as
the mobile and tablet software applications, coordination became essential to for collaboration on
tasks that challenged the ability of members to establish routines as different expertise specialties
were called upon.
The second assumption is that organizations have stable access to the resources to
encode, store, and retrieve knowledge, and that if they do not, they can find them to build the
TMS. Although the engineering team of CoWealth had some systems in place, the members
faced entry and departure of colleagues, limits on the capacity of tools used, and the uncertainty
of funding in the start-up environment. Many early stage organizations encounter volatility in the
resources and capacities available, and while efficient coordination, implicitly a TMS, may be
sought to improve performance, contextual factors may inhibit its full realization.
The third assumption is that the group leader formulates all tasks necessary for the
development of a TMS, and builds TEP units for the group to accomplish this. As I found during
fieldwork, engineering tasks were often determined by the Chief Engineer as the leader, and also
created by design and quality assurance due to the intensity of task interrelatedness. The Chief
Engineer used two assignment strategies to match T-P relations in a top-down communication
style, including exploiting existing expertise and exploring expertise capabilities. Members
asserted expertise claims as they requested tasks, gave advice, avoided domains, demonstrated
techniques, and negotiated their expertise credibility and roles on the team in constructing TEP
relations.
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The fourth and final assumption is that TEP units are constructed of relations between
tasks, expertise, and people. This team frequently used objects such as automated programming
that would perform tasks on behalf of the team, indicating that objects could perform expert roles
once encoded. Dismissing the passivity of objects in TEP utilization borrows from the central
tenet of Actor Network Theory (Latour, 2005). Objects and tools as actors had a significant
presence in the software development of this engineering team. As more firms rely on automated
processes for many functions, TEP units need to recognize their role. I suggest extending the
model of the TEP unit to allow for objects to be recognized in a task-expertise-person/object
(TEP/O) unit. TEP/O units, unlike TEP units, allow for task and expertise to be related to people
or objects in the coordination of knowledge. In software development, tool objects are not only
passive repositories, but can also be actively programmed to produce or enact certain tasks,
removing some of the workload of storage and retrieval from experts who encode the tools.
These findings suggest two key implications. First, I have adapted the model of
transactive memory development to incorporate role negotiation as the generative mechanism of
structural TMS change (see Figure 5.1). This first model is the Model of Transactive Memory
and Role Development. Second, the findings inform a model of the distinct aspects of the
construction, evaluation, and utilization phases of TEP units in a developing TMS (see Figure
5.2). This second model is the Model of TEP Unit Development.
This study presents a first step in understanding role negotiation as the change
mechanism of TEP units in transactive memory system development. The model of transactive
memory development proposed by Brandon and Hollingshead (2004) aids in understanding of
the linear and cyclical phases necessary for a group’s performance to achieve increased
efficiency. The theoretical reconstruction proposed in this study incorporates role negotiation and
165

Figure 5.1
Model of Transactive Memory System Development with Role Negotiation
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Figure 5.2
Task-Expertise-Person Unit Development with Role Negotiation

its expertise claim strategies. By doing so, it aids in defining specific ways that members
structure patterns of communication and information exchange in early-stage organizations. Four
expertise claim strategies, which served to reinforce or renegotiate members’ roles on the team,
manifested during TEP unit development: requesting, advising, avoidance, and demonstration.
These expert claims and the group-facilitated TEP unit matching show that the style of working
was collaboratively assembled in the engineering team. Sometimes expert claims were denied or
team members stated explicit domains that they did not know, but the structures of knowledge
management were as flexible as the organization. Members of teams and organizations enact
agency to shape their roles and the structures in which they participate, and expertise
167
specialization, credibility, and coordination may reveal the central mechanisms by which their
commitment flourishes.
Acknowledgements
This research was partially funded by entities at the University of Southern California,
including the School of Communication at the Annenberg School for Communication and
Journalism and the Graduate School. I offer thanks for helpful comments on an earlier version of
this work that was presented at the 2016 Academy of Management annual meeting from
conference participants in the Organizational and Communication Information Systems division
doctoral consortium. I am grateful to Dr. Andrea Hollingshead for her encouragement to develop
this manuscript as a portion of the dissertation project. I thank the informants who graciously
gave their time and expertise.

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CHAPTER 6: CONCLUSION

Ever tried. Ever failed. No matter. Try again. Fail again. Fail better.
-- Samuel Beckett, 1983
(Beckett, 1996/1983)

Start-ups are early-stage organizations that take risks while innovating ideas in motion.
Processes and structures in start-ups are re-constituted by people, activities, technologies,
communication, and goals. Samuel Beckett’s “fail better” line has, over time, been removed
from its unforgiving context in Worstward Ho, and adopted widely or reincarnated in various
hopeful forms by start-ups in Silicon Valley (Beauman, 2012; O’Connell, 2014). For instance, to
inspire quick, if imperfect, innovation, Facebook developed the mantra, “move fast and break
things” (Murphy, 2014). Similarly, though I present an initial attempt to understand organizing
and communication processes in this dissertation, my future work will seek to “fail better” in
moving toward deeper understanding of these phenomena. Below, I present a summary of this
project’s goals; major findings; implications for crowdfunding, technology firms, and start-ups;
advice for ethnographers; future research; and a conclusion.
Summary of Project Goals
The primary motivation of this dissertation arose from an interest in critical issues faced
by young start-ups in fiercely competitive business settings. The stakes of success are high, with
investments from founders, friends, and family tethered to the start-up’s journey at its early
stages of gestation. The likelihood of success for start-ups is also slim with only one in 10
succeeding to become a fully-fledged firm. The internal dynamics of knowledge management
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and organizational socialization can contribute to resiliency in a start-up, but research has often
failed to examine these phenomena in real workgroups. Scholars have called for more
organizational ethnography, particularly of real-world entrepreneurs, to better understand the
process of organizing and improve theory about process and change for better outcomes. The
strength of the punctuated ethnography approach was to gauge the pace of data collection with
the research site itself, allowing a longitudinal rather than cross-sectional approach to
understanding communication during organizational gestation. The approach also delimited the
amount of data collected, but not all episodes were captured in the dataset.
There are three central contributions of the dissertation. First, this study presents a
methodological innovation of punctuated ethnography. Second, this study also theorizes the
process of exits and disengagement in organizational socialization stage models in the context of
a gestating start-up. Finally, using transactive memory theory and the disengagement step of
organizational socialization stage models, this dissertation contributes to theory improvement to
the model of transactive memory development, based on longitudinal ethnography.
Major Findings
The major findings from each of the empirical chapters indicate the importance of
process in organizational change. As a case study approach, this ethnography sought to
understand the instances of and interrelations between shared practices, meanings, and social
contexts (Boellstorff, et al., 2012) at CoWealth. The boundary conditions for the findings
presented are specific to the case, but the theory improvement about knowledge management
development is generalizable to early-stage or nascent organizations and young start-ups focused
on building foundational infrastructure and dealing with churn from member departures.
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Furthermore, the findings of this dissertation may be generalized to older, established, but small,
organizations that experience departures of personnel and seek to maintain resiliency.
Amidst the upheaval of turnover and churn, CoWealth’s resiliency and coping
mechanisms to stem uncertainty are the focus of the fourth chapter. Three separate exit cases are
examined, including the paradoxes and tensions that forced structural shifts and disengagement
at CoWealth, as well as the aftermath of sensemaking to reduce any potential threats to the start-
up’s survival. Findings revealed several dialectical tensions related to the embeddedness of
member roles, where more concrete critical incidents were used retrospectively to sensemake for
the exit of more liminal contractors and more abstract reasoning was used to sensemake for the
dismissal of a founder. The differences in sensemaking reveal that organizations often struggle
more to overcome the loss of central management figures from their staff than they do to justify
the exits of task-based workers, due to the contributions executives make to strategic vision.
Changing C-suite level partners requires more sensemaking because it could also incur more
information-seeking from external stakeholders.
The fifth chapter investigated the role negotiation process as a component of the
development of a transactive memory system. Focusing on knowledge coordination, I present a
Model of Transactive Memory and Role Development, which reconstructs the Brandon and
Hollingshead (2004) model to include role negotiation within the model. Findings from the field
about the expertise claims that workers make about the roles they take on in the organization
informed this model. I also present a Model of TEP Unit Development, which specifies the
processes that occur at each of the task-expertise-person steps of the TEP unit, as well as their
relationship with role negotiation in a cyclical model. As a more fine-grained approach to the
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TEP unit, the model illuminates the nuance in workgroups as they develop their systems of
coordination.
Implications
I present implications of this study for the business of crowdfunding as well as
technology firms and start-ups. Crowdfunding, at its basic, the gathering of small financial
contributions together toward a larger monetary goal, derives its power from collective action.
CoWealth’s concept of grouping people for decision-making about investments blends the idea
of crowdfunding with many more volitional choices for the group to consider. The risk for users
is not just financial; different choices interpersonal dynamics can also derail such endeavors.
Managing the decision-making process among several people is not easy, even for experienced
groups. As new technological concepts develop and blend crowdfunding with more complicated
group dynamics, crowdfunding arenas expand and the need to manage interactions and risk
increases.
For start-ups and technology firms aiming to transform new ideas into tangible products
in Silicon Valley or elsewhere, the major findings of the dissertation bear on issues of trust and
collaboration between people as they innovate on a vision that may change as they work and
simultaneously develop their organization. Here, I present recommendations for policy and
practice in the management and support of communication in start-ups. CoWealth faced both
monumental and incremental decisions on a daily basis with experts who were equipped to use a
variety of specific skills. The professional and individualized training that workers receive
provides frameworks with particular expert vocabularies for them each to view their own
incarnation of the same vision. Each person views the same project through a different lens, and
these various interpretations generate problems in execution of the vision when they create
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misunderstanding. Communication strategies can bring these multiple points of view together in
a way that that overrides individual expertise vocabulary, avoiding some of the potential pitfalls
of miscommunication and fragmented visions.
Communication strategies that may alleviate some of these misunderstandings among
experts revolve around creating common ground. Coordination requires shared information and
an establishment of common ground through communication (Clark & Brennan, 1991).
Grounding is a collective process where people realize a mutual belief, and the presentation and
acceptance of information through the process of grounding keeps teams focused and organized.
Grounding relies on two factors including purpose, or the group’s task and goals, and medium,
such as face-to-face, telephone, e-mail, and video conferencing. The choice of medium carries
constraints, including copresence, visibility, audibility, contemporality, simultaneity,
sequentiality, reviewability, and revisability. The process of grounding also carries associated
costs for formulation, production, reception, understanding, start-up and delay, asynchrony,
speaker change (turn-taking), display, fault, and repair—all communication-associated costs.
With teams distributed across time zones or regions, start-ups and early-stage technology firms
face higher costs than other young firms that are centrally located. Distributed teams must find
ground in mediums that allow flexibility for participation, but this entails tradeoffs with
connection or availability issues. Constraints might inflate costs for grounding. Nevertheless,
investing in efforts to absorb these intangible costs by creating routines that allow regular check-
ins allow team members to stay firmly grounded and move forward on work that otherwise
might be experienced as disparate. Investment, both financial and personal, in building and
maintaining a feasible and easy-to-use communication infrastructure—such as utilizing chat,
email, phone, videoconferencing, and face-to-face meetings that support asynchrony and
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synchrony—reduces the cost of communication and focuses attention on the tasks at hand.
Without proper investment in communication as a support system, efforts to work together
become laborious and ineffective. Tools for communication are just as foundational as the other
assets used in the business, such as languages for coding, project management and
implementation software, or financial and accounting software. In sum, coordination relies on
communication, and thus requires careful thought about the development of a communication
infrastructure that can support progress about collaborative tasks and projects. For both leaders
of, and workers in, start-ups and other small, rapid-paced firms, a talented team needs good tools
to execute its productivity, but good tools are of little use without a talented team to use them.
Investment in both tool infrastructure and team skillset is crucial to enable a company’s forward
motion.
Advice for Ethnographers
To researchers studying start-ups, I offer advice about the management of an
ethnographic research project, relationships, and data acquisition. Plans for research are often
written in accordance with Institutional Review Board criteria, which often require a distinct,
procedural outline. For me, this meant scheduling my punctuated visits to the field site and
having my timeline available to the review board, my committee members, CoWealth staff, and
my hosts by the time of my dissertation proposal defense. Ethnography is an exciting method due
to its unpredictability, both in terms of the relationships that develop and events that occur in the
process of observation. While my visits were prepared with airport rides, flight tickets, metro
fare, a place to stay, packed breakfasts and lunches, and a way to travel to my site, the start-up’s
schedule responded to changes as it developed. One of my visits occurred while the CEO was on
travel to fundraise. The trip could have been viewed as poorly timed, but instead, I explored the
174
company as its members worked together in her absence and communicated with her as her
schedule allowed. Rather than challenges, I began to view alterations to my well-laid plans as a
result of CoWealth’s more immediate decision-making as opportunities to explore the company
under different, realistic conditions. To researchers, I suggest developing an observation plan
with flexibility: the subject of study may require changes to the observation schedule plans, and
those changes are acceptable because the research, after all, must follow the subject of study.
To research coordinators, principal investigators, and labs supporting punctuated
ethnographic work: a substantially larger amount of financial and logistical support is required
than may be expected for some traditional forms of ethnography. Rather than one long period
immersed in the day-to-day of everyday action, punctuated ethnography requires multiple
immersive periods over time to understand change. My site of study required travel by plane,
train, and car. Consequently, there were times I made compromises on logistical independence –
but not research independence. For instance, I often relied on a two-hour commute that was a
combination of Bay Area Rapid Transit (BART) and carpooling with the CEO or other startup
team members to the office. Each of the visits I planned for observation required extensive
coordination to be able to arrive at the site of study, which was usually the office, but sometimes
relocated for meetings or other company events. Adaptability and flexibility were crucial to
capture the observations, but necessitated changes in plans that can become expensive when
made last minute.
Patient persistence without expectations is necessary in ethnography. People bring their
own apprehension, misgivings, and concerns to any research endeavor about them or something
in which they are invested. As I worked to achieve consent from informants, not all responded as
acceptingly or quickly as the founders. After months of fieldwork, I reflected in my notes on
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April 3, 2016: “Getting a lawyer with a PhD to sign an IRB-approved consent form is like trying
to pet a tiger.” The legal advisor did consent a few months before the end of the data collection
period, and even participated in an interview (although unrecorded). A few other interview
participants did not want their interviews recorded either, and I adapted by taking extensive
verbatim notes. In the process, I learned the value of the phrases “control is an illusion,” but
“always be prepared” on the off chance that your luck turns, someone changes their mind, and
you get the data you need.
I would recommend that researchers place ethics first, and err toward self-sufficiency
when establishing boundaries and independence to the point that it does not impact the ability to
engage in practices and rituals of the people under study. There were moments when I navigated
an ethnographer’s professional distance (Agar, 1981), especially financially, while cultivating
relationships with informants as a colleague. When possible, I covered the cost of my
participation in CoWealth’s work-related activities, such as the entry fee to the AirBnb OpenAir
conference on June 8, 2016. In planning my trips, I declined the CEO’s gracious offers to host
me at her home and instead lived with my close friends, who were impartial parties to the
research, during my field visits. Staying at the home of the CEO would have given me access to
the CEO’s personal life, but would have been outside the scope of participating in the dynamic
between the CEO and the rest of the company, the latter of which was the focus of my work. My
living arrangement also allowed time to rest and recover from hours in the field each day. I
engaged in social events with the CoWealth team, including group meals and a March 5, 2016
evening outing to the iconic Fenton’s Creamery, made famous by its appearance in the Disney-
Pixar movie Up! In these social instances during my visits, I engaged with the group to enable a
richer understanding of meaning and interpretation in behaving as a member of CoWealth.
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The ethnographic methodology extends beyond observation alone into other forms of
data collection, and I would advise researchers to consider the value of interviews, audio
recordings, and transcriptions of audio recordings. Interviews are a separate type of data that may
prove helpful to triangulate with observation. For researchers studying groups for whom
technology products are a key part of daily work, interviewing individual CoWealth members
about the technologies and tools they use revealed understandings of everyday action in the
company I would not have observed otherwise. I found that no two people reported the same
understanding of the tools used at CoWealth; individuals afforded only a fragmented picture of
processes. To achieve a total picture of how the company’s members used its systems for
business processes, it was necessary to survey the tools in use by individuals, and I compiled
those mentioned into a single reference document. Understanding which programs and services
they were using, including through direct questions I made in systematic interviews, was an
important step to accessing those systems for observation in the study. Transcribed audio
recordings were also invaluable as my research progressed from observation notes into analysis
of meetings and the construction of theoretical arguments. With consent, audio recordings are
cheaply made and are relatively easy to collect and archive. Transcriptions of recordings
expedite the process of analysis and assist in establishing the groundedness of a study with
verbatim evidence.
Future Research
There are many avenues that communication scholars could explore for future research
on early-stage organizing of groups and organizations.
I have continued data collection with CoWealth in order to extend this research in the
future with additional studies. The current study, with data collected between September 2015
177
and August 2016 (see Figures 3.2 and 3.3), focused on gestation and development in the start-up,
including transactive memory and organizational socialization. Although specific directions for
further research were outlined at each of the chapter conclusions, there remains considerable
scope to complete additional research. Potential questions include: how does the C-suite manage
TEP development? How do the limitations of technologies inhibit coordination? How do
software development frameworks, such as Agile and Waterfall, comparatively order process
and tasks, and further enable productivity? How do multiple visions of innovation motivate
members, while also creating tension during the development process? The rich dataset collected
during this time period allows further investigations into the individual team members’ use and
understanding of technologies from structurational and sensemaking perspectives (DeSanctis &
Poole, 1994; Gephart, 2004).
Further research would focus on the start-up’s launch, beginning in April 2017. Planned
aspects of the study include social network analysis of group decision-making in the start-up’s
platform, affordances and communication design of the platform, social media analytics of
online branding, and user surveys and interviews. A later study could bring together the full
cycle of technology innovation through the triumvirate of development, implementation, and use
as the start-up vision scales and expands globally. The data needs would include quantitative
historical data and user data. Quantitative historical data may be collected from the backend
database of the platform to analyze its design and construction. Data may be collected using the
Python coding language. Key performance indicators, such as Alexa ranking and Google
ranking, could be examined. Another source of quantitative historical data may be social media
advertising by CoWealth and about CoWealth. Social media data could be collected, filtered,
clustered, and coded through a trained learning-based machine classification tool, the Texifter
178
software called DiscoverText. Data of user interaction within groups of users and between users
could be collected with particular focus on team decision-making and voting in groups. Data
could also be collected on the training of users and pilot testing of the platform.
Other studies of the early stages of start-ups could reveal the true variance of
development processes. One way to complete this would be a quantitative survey with start-up
staff. The survey could investigate the networks of resources that each entrepreneur and staff
member draws from with an ego-centric survey, nominating multiple names of people or
companies, and the functional resources they provide. Social network data could be analyzed in
UCINET or R and R studio, with visualization in Gephi. The survey could also solicit
descriptions of leadership styles in start-ups, especially for social entrepreneurship entities, and
link these longitudinally to start-up outcomes. Additionally, investigating the dynamics of
entrepreneurial teams (Cooney, 2005; Klotz, Hmieleski, Bradley, & Busenitz, 2014) and the
resources of accelerators and incubators, and their effect on start-up success could be another
avenue for research. Data collection could be conducted through Qualtrics online survey
software. Survey answers could be analyzed in SPSS Statistics v. 20. Observational methods
could examine processes in start-ups, with attention to the role of technology in the organizing
process from a practice lens (Orlikowski, 1992, 2000).
Conclusion
Start-ups are inherently disruptive and risky. They inspire, challenge, entertain, innovate,
and have the potential to create products that change lives—once they succeed. To grow from an
early-stage organization and survive ideation and gestation into infancy does not guarantee long-
term survival, but early processes can be path-determinant. Effective communication strategies
179
and attention to social dynamics are the under-explored elements in the early stages of these
businesses, but they can buoy them through volatility that might otherwise sink a company.
180
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225
APPENDIX A: EXPANDED TABLE OF PRIVATE COMPANIES VALUED AT $1 BILLION USD OR MORE
HEADQUARTERED IN THE UNITED STATES

Table 7.1
Private Companies Valued at $1 Billion USD or More Headquartered in the United States
Company Valuation
(billion USD)
Sector Headquarters Founded CEO
City State
Uber $62.0 Software San Francisco Calif. 2009 Travis Kalanick
Airbnb $25.5 Software San Francisco Calif. 2008 Brian Chesky
Palantir $20.5 Software Palo Alto Calif. 2004 Alex Karp
Snapchat $16.0 Media Venice Calif. 2011 Evan Spiegel
SpaceX $12.0 Aerospace Hawthorne Calif. 2002 Elon Musk
Pinterest $11.0 Media San Francisco Calif. 2010 Ben Silbermann
Dropbox $10.0 Software San Francisco Calif. 2007 Drew Houston
WeWork $10.0 Business services New York N.Y. 2010 Adam Neumann
Theranos $9.0 Health Palo Alto Calif. 2003 Elizabeth Holmes
Intarcia Therapeutics $5.5 Health Boston Mass. 1997 Kurt Graves
Lyft $5.5 Software San Francisco Calif. 2012 Logan Green
Stemcentrx $5.0 Health San Francisco Calif. 2008 Brian Slingerland
Stripe $5.0 Financial services San Francisco Calif. 2010 Patrick Collison
Zenefits (dba YourPeople) $4.5 Software San Francisco Calif. 2013 Parker Conrad
Social Finance (aka SoFi) $4.0 Financial services San Francisco Calif. 2011 Michael Cagney
Vice Media $4.0 Media New York N.Y. 1994 Shane Smith
Tanium $3.7 Software Emeryville Calif. 2007 David Hindawi
Credit Karma $3.5 Software San Francisco Calif. 2007 Kenneth Lin
Jawbone (dba AliphCom) $3.3 Hardware San Francisco Calif. 1999 Hosain Rahman
CloudFlare $3.2 Media San Francisco Calif. 2009 Matthew Prince
Machine Zone $3.1 Software Palo Alto Calif. 2008 Gabriel Leydon
Bloom Energy $3.0 Energy Sunnyvale Calif. 2001 K.R. Sridhar
DocuSign $3.0 Software San Francisco Calif. 2003 Keith Krach
Fanatics $3.0 Retail Jacksonville Fla. 1995 Doug Mack
Legendary Entertainment $3.0 Media Burbank Calif. 2005 Thomas Tull
226
Table 7.1 (cont.)
Company Valuation
(billion USD)
Sector Headquarters Founded CEO
City State
Moderna Therapeutics $3.0 Health Cambridge Mass. 2011 Stéphane Bancel
Wish (dba ContextLogic) $3.0 Retail San Francisco Calif. 2011 Peter Szulczewski
Slack $2.9 Software San Francisco Calif. 2009 Stewart Butterfield
InMobi $2.5 Media San Francisco Calif. 2007 Naveen Tewari
Mozido $2.4 Financial services Austin Texas 2008 R. Todd Bradley
Houzz $2.3 Media Palo Alto Calif. 2009 Adi Tatarko
AppDynamics $2.0 Software San Francisco Calif. 2008 David Wadhwani
Avant $2.0 Financial services Chicago Ill. 2012 Al Goldstein
Blue Apron $2.0 Software New York N.Y. 2012 Matt Salzburg
Domo $2.0 Software American Fork Utah 2010 Josh James
Github $2.0 Software San Francisco Calif. 2008 Chris Wanstrath
Instacart $2.0 Software San Francisco Calif. 2012 Apoorva Mehta
Magic Leap $2.0 Hardware Dania Fla. 2011 Rony Abovitz
NantHealth $2.0 Health Culver City Calif. 2007 Patrick Soon-Shiong
Nutanix $2.0 Hardware San Jose Calif. 2009 Dheeraj Pandey
SurveyMonkey $2.0 Software Palo Alto Calif. 1999 Zander Lurie
Prosper Marketplace $1.9 Financial services San Francisco Calif. 2006 Aaron Vermut
Zocdoc $1.8 Health New York N.Y. 2007 Oliver Kharraz, MD
The Honest Co. $1.7 Consumer goods Los Angeles Calif. 2011 Brian Lee
AppNexus $1.6 Media New York N.Y. 2007 Brian O’Kelley
MongDB $1.6 Software New York N.Y. 2007 Dev Ittycheria
Apptus $1.5 Software San Mateo Calif. 2006 Kirk Krappe
BuzzFeed $1.5 Media New York N.Y. 2006 Jonah Peretti
InsideSales $1.5 Software Provo Utah 2004 David Elkington
Mu Sigma $1.5 Software Northbrook Ill. 2004 Dhiraj Rajaram
MuleSoft $1.5 Software San Francisco Calif. 2006 Greg Schott
Oscar Health Insurance $1.5 Financial services New York N.Y. 2013 Mario Schlosser
Tango $1.5 Software Mountain View Calif. 2009 Eric Setton
Cloudera $1.4 Software Palo Alto Calif. 2008 Tom Reilly
227
Table 7.1 (cont.)
Company Valuation
(billion USD)
Sector Headquarters Founded CEO
City State
Deem $1.4 Retail San Francisco Calif. 1999 Patrick Grady
Jet $1.4 Retail Hoboken N.J. 2013 Marc Lore
FanDuel $1.3 Media New York N.Y. 2009 Nigel Eccles
Medallia $1.3 Software Palo Alto Calif. 2001 Borge Hald
Thumbtack $1.3 Media San Francisco Calif. 2009 Marco Zappacosta
Auction.com $1.2 Retail Irvine Calif. 2007 Timothy R. Morse
Automattic $1.2 Media San Francisco Calif. 2005 Matt Mullenweg
DraftKings $1.2 Media Boston Mass. 2011 Jason Robins
Eventbrite $1.2 Retail San Francisco Calif. 2006 Kevin Hartz
Evernote $1.2 Software Redwood City Calif. 2007 Phil Libin
NJOY $1.2 Consumer goods Scottsdale Ariz. 2006 Paul Sturman
Okta $1.2 Software San Francisco Calif. 2009 Todd McKinnon
Sprinklr $1.2 Software New York N.Y. 2009 Ragy Thomas
Warby Parker (dba Jand) $1.2 Retail New York N.Y. 2010 Dave Gilboa,
Neil Blumenthal
Actifio $1.1 Software Waltham Mass. 2009 Ash Ashutosh
Anaplan $1.1 Software San Francisco Calif. 2006 Fred Laluyaux
Docker $1.1 Software San Francisco Calif. 2010 Ben Golub
Gusto (formerly
ZenPayroll)
$1.1 Software San Francisco Calif. 2011 Josh Reeves
MediaMath $1.1 Software New York N.Y. 2007 Joe Zawadzki
Nextdoor $1.1 Media San Francisco Calif. 2010 Nirav Tolia
Proteus Digital Health $1.1 Health Redwood City Calif. 2001 Andrew Thompson
Uptake $1.1 Software Chicago Ill. 2008 Brad Keywell
23andMe $1.0 Health Mountain View Calif. 2006 Anne Wojcicki
Adaptive Biotechnologies $1.0 Health Seattle Wash. 2009 Chad Robins
Alteryx $1.0 Software Irvine Calif. 2010 Dean Stoecker
AppDirect $1.0 Retail San Francisco Calif. 2009 Daniel Saks; Nicolas
Desmarais
228
Table 7.1 (cont.)
Company Valuation
(billion USD)
Sector Headquarters Founded CEO
City State
Carbon3D $1.0 Manufacturing Redwood City Calif. 2013 Joseph DeSimone
Coupa Software $1.0 Software San Mateo Calif. 2006 Rob Bernshteyn
Datto $1.0 Software Norwalk Conn. 2007 Austin McChord
Illumio $1.0 Software Sunnyvale Calif. 2013 Andrew Rubin
JustFab $1.0 Retail El Segundo Calif. 2010 Adam Goldenberg;
Don Ressler
Kabam $1.0 Media San Francisco Calif. 2006 Kevin Chou
Kabbage $1.0 Financial services Atlanta Ga. 2009 Rob Frohwein
Lookout $1.0 Software San Francisco Calif. 2007 John Hering
MarkLogic $1.0 Software San Carlos Calif. 2003 Gary Bloom
Pluralsight $1.0 Business services Farmington Utah 2004 Aaron Skonnard
Qualtrics $1.0 Software Provo Utah 2002 Ryan Smith
Razer $1.0 Media Carlsbad Calif. 1998 Min-Liang Tan
Red Ventures $1.0 Business services Charlotte N.C. 2000 Ric Elias
Shazam $1.0 Media New York N.Y. 2002 Rich Riley
SimpliVity $1.0 Software Westborough Mass. 2009 Doron Kempel
Twilio $1.0 Software San Francisco Calif. 2007 Jeff Lawson
Udacity $1.0 Education Mountain View Calif. 2012 Sebastian Thrun
Vox Media $1.0 Media New York N.Y. 2011 Jim Bankoff
Zeta Interactive $1.0 Software New York N.Y. 2007 David Steinberg
Zscaler $1.0 Software San Jose Calif. 2008 Jay Chaudhry
Source: Nusca, A. (2016, January 19). The unicorn list. Fortune. Retrieved on February 14, 2017 from http://fortune.com/unicorns/
Note: dba means doing business as; aka means also known as.

229
APPENDIX B: TABLE 7.2 OF TOP TEN CITIES FOR TECHNOLOGY START-UPS RANKED BY
2011 USD AMOUNT INVESTED IN COMPANIES

Table 7.2.
Top Ten Cities for Technology Start-ups Ranked by 2011 USD Amount Invested in Companies.
Rank Location Companies Headquartered Start-
ups
2011 Investments
City State USD Amount Companies
1 San Francisco area Calif. Apple, Facebook, Google, Twitter 3,442 $11.8 billion 430
2 Boston Mass. TripAdvisor, Kayak, Carbonite 700 $2.8 billion 285
3 New York City N.Y. Foursquare, Tumblr, Fab.com 1,844 $2.7 billion 332
4 Los Angeles area Calif. Demand Media, Break Media, Viddy
Citysearch, Electronic Arts
1,507 $2 billion 129
5 Washington D.C. LivingSocial 261 $979 million 146
6 San Diego Calif. Qualcomm, Slacker 329 $915 million 89
7 Chicago Ill. Groupon, Orbitz, Motorola 556 $750 million 79
8 Austin Texas Dell, Photodex, BedandBreakfast.com 487 $646 million 70
9 Boulder/Denver Colo. Mapquest, Photobucket 395 $584.6 million 85
10 Seattle Wash. Microsoft, Amazon, Zillow, T-Mobile 441 $580 million 96
Source: Graham, J. (2012, August 24). Top cities for technology start-ups. USA Today. Retrieved from
http://usatoday30.usatoday.com/tech/columnist/talkingtech/story/2012-08-22/top-tech-startup-cities/57220670/1
230
APPENDIX C: INTERVIEW GUIDE

For CoWealth Founders, Employees, and Contractors

Company Information
• How did you find out about CoWealth?
• Describe the CoWealth business in your own words.
• What is CoWealth’s mission?
• What does CoWealth offer that’s better than competitors?
• Tell me how the company began.
• How is CoWealth connected to current technological trends (e.g., the sharing economy,
crowdfunding)?
• How does CoWealth display innovativeness?
• How does CoWealth display proactiveness?
• How does CoWealth display risk management?
• Tell me about how you see the future of CoWealth.
o [Followup] How about in five years?
• Is there anything else I should know about the direction of the company?

Work in Company
• What is your official title?
• Tell me about your role in CoWealth.
• How did you get involved in CoWealth?
• What do you like best about your work with CoWealth?
• What is the hardest part of your work with CoWealth?
• What kinds of expertise do you see in the CoWealth colleagues around you?
• How do you collaborate with members of the CoWealth company?
• How do you share your updates?
• How do company members share information with you?
• Tell me about milestones that you have experienced with the start-up.
• Tell me about a time that you experienced a challenge in working with the start-up.
• What should be CoWealth’s most important priorities?
• What improvements would you make to CoWealth?
• Is there anything else you’d like to add about your work at CoWealth?

Professional Background
• How many years in total have you worked in start-ups?
• When did your career in start-ups begin?
• What types of previous organizations have you worked for?
• What degrees and/or professional certifications do you have?
• What conferences or events (e.g., Meetups) do you attend regularly related to your work with
CoWealth?
• What newsletters, trade press, or blogs do you read that are related to your work with
CoWealth?

231
For Founders Only
• What are the investment concepts of CoWealth?
• What is the vision of CoWealth?
• What is the target market for CoWealth?
• How is the company structured?
• What is the nonprofit division of CoWealth?
• What do you hope your company and your platform can do in the future?
• What are your immediate goals or priorities for CoWealth?
• How many investors in the company does CoWealth currently have?
• How many property investors in the company does CoWealth currently have?
• How many property investment groups does CoWealth have?
• Can you tell me who your company contracts with and why?
• Can you describe the expertise and qualities you seek in your contractors?

For Founders Only [Second Interview]
• How has the employee structure changed?
• How have roles evolved?
• How many technologies do you use in your work specifically?
• Knowing what you know now about start-up companies, if you were to be begin another
company, what would be the biggest lesson you would bring from your CoWealth
experience?
• What has surprised you?
• What has frustrated you?

For CoWealth Users Only
• What is your impression of CoWealth?
• How do you think CoWealth could add value to your life?
• Describe your user experience when using the CoWealth platform.
• If you were to suggest changes to the CoWealth platform, what would they be?
• How well do you think your group works together in making decisions about the investment?
• Do you communicate with other CoWealth users outside of the platform about CoWealth
business issues (not unrelated or personal issues)?
• How did you hear about CoWealth?
• What are other start-up companies have you been involved with?
o [Followup] Did they utilize new communication or information technologies?
• How do you hear about these start-ups?
• Did you know any of the other investors in your group prior to working with CoWealth?
o [Followup] How did you know them?
• What is your job title?
• What industry do you work in?

232
APPENDIX D: GLOSSARY

This is list of terms and their corresponding definitions related to the research context. Inclusion
of specific terms was subjective, relating to language used in this manuscript, colloquialisms
used for social platforms, vernacular designations used by the organization, and vocabulary
commonly invoked in technology design.
Bootstrapping/Self-funding – the first of the start-up investment stages “in which a founder
invests his or her money to begin the start-up journey” (Root, 2016).
Crowdfunding – “the practice of funding a project or venture by raising money from a large
number of people, each of whom contributes a relatively small amount, typically via the
Internet” (crowdfunding, 2007)
Crowdsourcing – “an online, distributed problem-solving and production model that leverages
the collective intelligence of online communities to meet specific organizational goals”
by blending bottom-up creative process with top-down management (Brabham, 2013, p.
xix)
Design – “an activity of transforming something given into something preferred through
intervention and invention” (Aakhus, 2007, p. 112).
Design thinking – “a methodology that imbues the full spectrum of innovation activities with a
human-centered design ethos. …innovation is powered by a thorough understanding,
through direct observation, of what people want and need in their lives and what they like
or dislike about the way particular products are made, packaged, marketed, sold, and
supported” (Brown, 2008, p. 86).
Designerly knowing – a fundamental form of human intelligence in which the limits of a
problem are defined with regard to people, processes, and products and the nature of a
possible solution suggested (Cross, 2006).
Expertise – know-what, know-how, and know-why of a knowledge domain (Quinn, Anderson,
& Finkelstein, 1996).
Flipping – “a type of real estate investment strategy in which an investor purchases properties
with the goal of reselling them for a profit. Profit is generated either through the price
appreciation that occurs as a result of a hot housing market and/or from renovations and
capital improvements” (flipping, n.d.).
Friends and Family funding – the second phase of the start-up investment stages; founders
reach out to people close to them for a monetary contribution (Root, 2016).
High-velocity market – markets in which “changes in demand, competition, and technology are
so rapid and discontinuous that information is often inaccurate, unavailable, or obsolete”
and selecting the best resources and experiences is key for an organization’s survival
(Eisenhardt, 1989b, p. 544). In these markets, organizations rely on new knowledge and
are structured simply to allow for emergent adaptation (Eisenhardt & Martin, 2000, p.
1116).
Human agency –the capacity for intentional action by human entities to form and realize goals
(Leonardi, 2012)
Incubator – a place that provides a supportive environment for start-ups with physical
resources—such as flexible rental space and leases, shared administrative services, and
equipment—and social networks of business and technical advisors for assistance in
finance, business planning, marketing, legal consulting, and development or
manufacturing (Peters, Rice, Sundararajan, 2004).
233
Material agency – the capacity for unintentional action by nonhuman entities (Leonardi, 2012)
Minimum viable product – a version of a new product with just enough features to gather
validated learning about customers (Ries, 2009).
Organizational change – the transition an entity undergoes in a planned alteration of its
strategic plan or structure.
Process approach – the sequence or pattern in a series of events to arrive at an outcome is
explained (Poole, 2004)
Proof of Concept (POC) – “a demonstration, the purpose of which is to verify that certain
concepts or theories have the potential for real-world application. POC is therefore a
prototype that is designed to determine feasibility, but does not represent deliverables”
(poc, n.d.).
Real estate investment trust (REIT) – a security that invests in real estate through property or
mortgages allowing small and large investors to acquire ownership in commercial
properties such as houses and apartment complexes (Root, 2015).
Retrospective – feedback on process during the previous sprint in the Scrum method of Agile
software development (Ambler, 2013).
Seed funding – the third start-up investment stage but “the first phase of raising outside capital”
from Angel Investors and venture capitalists (Root, 2016).
Series A round of funding – the first significant round of venture capital funding where class A
stock in the company is sold in exchange for investment and the company is producing
revenue (series A financing, n.d.). Generally, series A is “useful in optimizing product
and user base” (Delventhal, 2015).
Sharing Economy – interrelated production and consumption activities in which individuals can
borrow or rent assets owned by another person, enabling on-demand access for a price
(Radcliffe, 2014; The Economist, 2013b).
Social entrepreneurial organization (SEO) – “…combine social and financial missions,
generating revenue through market-based efforts, and directing such efforts toward social
causes including poverty alleviation, issue-based education, and international
development” (Grimes, 2010, p. 763).
Sprint – a one- or two-week repeatable work cycle in the Scrum method of Agile software
development (Rising & Janoff, 2000; Schwaber, 2004).
Stealth Mode – “an IT business strategy in which software, hardware or a IT product/service is
intentionally hidden from the market, competitors or general public until a predefined or
completion date. It is the practice of keeping a product or service under wraps,
specifically in highly competitive markets” (stealth mode, 2016a).
Triangulation – the confirmation of findings or the same phenomenon in the multiple sources
derived from complementary research designs (Jick, 1979).
Turnkey property – “a fully renovated home or apartment building that an investor can
purchase and immediately rent out” (turnkey property, n.d.).
Variance approach – linear models of variables are employed to represent attributes of change
(Poole, 2004)

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Asset Metadata

Creator Guth, Kristen Laura (author)

Core Title Building a unicorn: management of innovation, collaboration, and change in a Silicon Valley start-up

School Annenberg School for Communication

Degree Doctor of Philosophy

Degree Program Communication

Publication Date 07/07/2019

Defense Date 04/07/2017

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag collaboration,entrepreneurship,innovation,management,OAI-PMH Harvest,organizational communication,start-up,strategy,technology

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Riley, Patricia (committee chair), Brabham, Daren C. (committee member), Hollingshead, Andrea B. (committee member)

Creator Email kguth@usc.edu,kristen.guth@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c40-395111

Unique identifier UC11264233

Identifier etd-GuthKriste-5489.pdf (filename),usctheses-c40-395111 (legacy record id)

Legacy Identifier etd-GuthKriste-5489.pdf

Dmrecord 395111

Document Type Dissertation

Rights Guth, Kristen Laura

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

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