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Scaling online graduate programs: an exploratory study of insourcing versus outsourcing

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Scaling online graduate programs: an exploratory study of insourcing versus outsourcing

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Scaling Online Graduate Programs: An Exploratory Study of Insourcing Versus
Outsourcing
by
Ammar Dalal

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

May, 2021

© Copyright by Ammar Dalal 2021
All Rights Reserved

The Committee for Ammar Dalal certifies the approval of this Dissertation

Douglas Lynch
Jennifer Phillips
Helena Seli, Committee Chair

Rossier School of Education
University of Southern California
2021

iv

Abstract
Substantial recent growth in online graduate programs has garnered the attention of the higher
education community. Given their limited resources and capability, institutions seeking to scale
their online graduate programs need to consider whether to insource or outsource this initiative.
The purpose of this study was to identify the knowledge and institutional influences affecting the
decision-making process of Online Program Leaders (OPLs) in the selection of a sourcing
strategy for scaling online graduate programs. The study participants were institutional leaders at
various private non-profit master’s and doctoral universities with decision-making power and
responsibility for source selection and implementation. Data was collected through surveys,
interviews, and document analysis. The results and findings demonstrated that OPL knowledge
of resources, structure, and capability was highly influential in source selection. The prevailing
negative perception of online learning among institutional members, existing policies and
procedures such as new program approval process and graduate program budget models, and the
lack of adequate communication were identified as barriers in source selection and
implementation. The study provides general recommendations for institutions seeking to scale
their online graduate programs. They include ensuring OPLs possess and maintain a high level of
knowledge of resources, capability, and structure; establishing a strategic vision for scaling; and
leveraging institutional culture to overcome scaling obstacles.

v

Dedication
To my daughters, Zoeya and Samiya. Thank you both for being dad’s source of motivation, joy,
and respite. I hope this work serves to inspire you and helps you strive for everything you aspire
to achieve in your life. Please believe that you are loved and supported and know that nothing is
ever impossible. I love you both very much!

vi

Acknowledgements
This dissertation would not have been possible without the support, guidance, and
encouragement of my dissertation committee. I thank my chair, Dr. Helena Seli, for mentoring
me throughout the process thoughtfully and gracefully. I also want to thank my committee
members, Dr. Jennifer Phillips and Dr. Douglas Lynch, for their support and constructive
feedback supporting my research work. A special thank you to Dr. Lynch, who exposed me to a
whole new world of higher education outside of my bubble, ultimately inspired my research
topic. Finally, I want to thank all my professors and support staff at Rossier for making my
doctoral program journey a rewarding experience.
This accomplishment represents the support, well wishes, and prayers of many of my
colleagues, friends, and family that span four states and three countries. I feel boundless
gratitude for their impact on my life and their encouragement during this journey. To so many of
you, thank you.
A special thank you to my colleagues at LMU and SCU for their leniency, support, and
understanding as I endeavored to balance this degree and work's demands.
To Dr. Jayson Boyers, I am deeply grateful for your friendship and mentorship. Your
guidance, wisdom, and endless support mean so much to me.
I am incredibly blessed to stand high on the shoulders of so many people in my family. I
want to begin by thanking all my in-laws who have supported me in so many ways. Thank you,
Shireen and Komail Saifee, for your support during our transition from San Jose to Los Angeles.
I want to especially thank my father-in-law and mother-in-law, Fazle Hasan and Nasreen Hyderi,
who put their lives on hold to support my family for the better part of the last three years. Their
help made everything possible, including this dissertation. I am deeply grateful to you both,
Ammi and Abba.
To my brother, Adnan, and my sister-in-law, Sarena, thank you for your support and
encouragement throughout my doctoral program journey. Adnan, thank you for being an
inspiration to me and for your patience and understanding. I am grateful for the bond we share as
brothers.
To my parents, Shabbir and Tasneem Dalal, I do not have enough words to express my
love and gratitude for everything you have done for me. I am immensely thankful for your

vii

sacrifices that have allowed me to get here today. I truly hope this moment fills your heart with
pride and happiness.
Finally, I want to thank my soulmate, Aleya. Aleya, I owe much gratitude for your
sacrifices throughout this journey. There are so many things I need to thank you for doing the
past three years – raising our toddler, welcoming our second child, moving to a new city,
changing jobs, weathering a global pandemic on the frontlines. Any one of these actions by itself
would be praiseworthy, but you did them all while supporting me with a smile, unlimited care,
and love. I am in awe of everything you do for our family. Our daughters are fortunate to have
you as their role model. I look forward to all that life has in store for us. I love you!

viii

Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. xi
List of Figures .............................................................................................................................. xiii
List of Abbreviations ................................................................................................................... xiv
Chapter One: Overview of the Study .............................................................................................. 1
Background of the Problem ................................................................................................ 1
Field Context ....................................................................................................................... 4
Description of Stakeholder Groups ..................................................................................... 5
Stakeholder Group for the Study ........................................................................................ 6
Purpose of the Study and Research Questions .................................................................... 7
Importance of the Study ...................................................................................................... 7
Overview of the Conceptual and Methodological Framework ........................................... 8
Definitions........................................................................................................................... 8
Organization of the Project ................................................................................................. 9
Chapter Two: Review of the Literature ........................................................................................ 10
Rise of Online Graduate Programs ................................................................................... 10
Impact of the COVID-19 Pandemic ................................................................................. 12
Scaling Online Graduate Programs ................................................................................... 13
Scaling Externally with an Online Program Manager ...................................................... 18
Scaling through Internal Capacity Building ..................................................................... 22

ix

Clark and Estes’ (2008) Knowledge, Motivation and Organizational Influences’
Framework ............................................................................................................ 23
Online Program Leaders’ Knowledge and Institutional Influences .................................. 24
Conceptual Framework ..................................................................................................... 33
Summary ........................................................................................................................... 35
Chapter Three: Methodology ........................................................................................................ 36
Research Questions ........................................................................................................... 36
Overview of Methodology ................................................................................................ 36
Data Collection, Instrumentation, and Analysis Plan ....................................................... 38
Data Analysis .................................................................................................................... 45
Ethics and Role of the Researcher .................................................................................... 46
Chapter Four: Results and Findings .............................................................................................. 49
Participating Stakeholders ................................................................................................ 49
What Knowledge and Skills do Online Program Leaders (OPLs) Utilize in Selecting
Whether to Insource or Outsource the Delivery of Online Graduate Programs at
Scale? .................................................................................................................... 53
How do Institutional Influences Impact Online Program Leaders (OPLs) in Selecting
Whether to Insource or Outsource the Delivery of Online Graduate Programs at
Scale? .................................................................................................................... 78
Findings from Document Analysis ................................................................................... 91
Summary of Results and Findings .................................................................................... 94
Chapter Five: Recommendations and Discussion......................................................................... 96
Discussion of Findings and Results .................................................................................. 96

x

Recommendations for Practice ....................................................................................... 105
Limitations and Delimitations ......................................................................................... 111
Recommendations for Future Research .......................................................................... 112
Conclusion ...................................................................................................................... 113
References ................................................................................................................................... 116
Appendix A: Survey Protocol ..................................................................................................... 130
Appendix B: Interview Protocol ................................................................................................. 135
Appendix C: Document Analysis Protocol ................................................................................. 140

xi

List of Tables
Table 1: Knowledge Influences 28
Table 2: Institutional Influences 32
Table 3: Data Sources 37
Table 4: Survey Participants’ Institutional Profile Breakdown 51
Table 5: Survey Participants’ Title Breakdown 51
Table 6: Survey Participants’ Breakdown by Academic Discipline 52
Table 7: Interview Participants’ Demographic Profiles 53
Table 8: Survey Results for Level of Familiarity with Institutional Resources 55
Table 9: Survey Results for Ranking of Institutional Resources 57
Table 10: Survey Results for Knowledge of Institutional Resources in Source Selection 59
Table 11: Survey Responses to Main Reason for Scaling Strategy Selection 60
Table 12: Survey Results for Level of Familiarity with Institutional Structural Factors 63
Table 13: Survey Results for Knowledge of Structural Factors in Source Selection 65
Table 14: Survey Results for Level of Familiarity with Institutional Capability Factors 67
Table 15: Survey Results for Knowledge of Capability Factors in Source Selection 70
Table 16: Survey Responses to Main Reason for Scaling Strategy Selection 71
Table 17: Summary of Entities Used for Capability Assessment 74
Table 18: Survey Results for Satisfaction in Institutional Support for Scaling Implementation 79
Table 19: Survey Results for Institutional Leadership Communicating Importance of Scaling 81
Table 20: Survey Results for Influence of Culture in Source Selection 83
Table 21: Institutional Considerations for Supporting OPLs 90
Table 22: Institutional Strategic Plans for Scaling Online Graduate Programs 93

xii

Table 23: Summary of Knowledge Influences and Related Results and Findings 100
Table 24: Summary of Institutional Influences and Related Results and Findings 105

xiii

List of Figures
Figure 1: Conceptual Framework for Exploring OPL Selection Capacity Page Number 34

xiv

List of Abbreviations
HEI Higher Education Institutions

OPL Online Program Leader

OPM Online Program Manager

1

Chapter One: Overview of the Study
A growing interest in graduate programs combined with declining undergraduate
enrollment has prompted many higher education institutions (HEIs) to expand their graduate
offerings. Institutional leaders keen on expanding graduate programs emphasize a need to offer
more online programs (Blagg, 2018). Online programs, which accounted for 29% of all graduate
degrees in 2013, have quickly grown to 40% in 2017 (Blagg, 2018). Despite this remarkable
recent growth, online programs' successful scaling remains limited to a few institutions. For
example, in the fall of 2016, almost half of all online students were enrolled at just 235 out of
1,103 institutions (Carnegie Foundation for the Advancement of Teaching, 2019; Seaman et al.,
2018). Furthermore, 10 institutions, representing 0.21% of all institutions, accounted for over
10% of all online program enrollments (Seaman et al., 2018). Some institutions’ inability to scale
their online graduate programs poses a challenge to their competitiveness in a dynamic
technology-driven graduate education landscape. This study will explore the considerations
institutions face when deciding whether to insource or outsource their online graduate programs.
Background of the Problem
Graduate education has become a significant part of a traditionally undergraduate-
oriented higher education ecosystem. Freshmen undergraduate enrollment has generally been
declining in the past decade. Down seven percent since 2010, this downward trend is expected to
continue for the foreseeable future (National Center for Education Statistics, 2019). In contrast,
graduate enrollment has increased by six percent in the past decade (Ma et al., 2020). This
growth can be attributed to a few factors. Access to graduate student aid, including federal loans,
institutional grants, federal work-study, and federal veteran’s benefits, is understood to be a
pivotal contributor to the increase in graduate student enrollment (Ma et al., 2020). Since 2010,
2

total graduate student aid increased by two percent, and notably, grants such as institutional and
private grants increased by 27% (Ma et al., 2020).
Similarly, the availability of graduate student loans, which make up approximately two-
thirds of total graduate student aid, has also made graduate education generally more accessible
(Ma et al., 2020). Another reason for the rise in graduate enrollment is the broad perception of
improved earning potential and specialization associated with possessing a graduate degree. This
perception has fueled interest in pursuing a graduate degree even as its resulting career-specific
outcomes generally remain unclear (Smith et al., 2010; Okahana & Hao, 2019). Some studies
have shown that master’s degree holders in business and education fields earn higher salaries
than their bachelor’s degree-holding counterparts (Baum et al., 2013; Gándara & Toutkoushian,
2017). Others have pointed that in some engineering and scientific research occupations, where
only a bachelor’s degree is required for entry, almost one-third of workers hold a master's degree
(Okahana & Hao, 2019). Furthermore, a 2018 Bureau of Labor Statistics report projects a 17%
employment increase in master’s-level occupations and a 13% increase in doctoral and
professional-level occupations by 2026, well-above the seven percent projected average
employment increase in all occupations (Torpey, 2018). The popularity of graduate degrees and
student aid availability has contributed to its attractive value proposition for many HEIs.
A notable aspect of graduate education’s growth is in online graduate programs. The past
few decades have seen technological advancements in every arena, including higher education,
which has increased flexibility for students in online courses (Braun, 2008; Rovai & Downey,
2010). Technological advancements have also led to the creation of new online learning and
delivery models adopted by many HEIs to expand graduate programs beyond their physical
campus (Blagg, 2018; Dziuban et al., 2016; Palvia et al., 2018). These enhanced capabilities and
3

accessible graduate student aid, and the positive value proposition of a graduate degree have
contributed to significant growth in online graduate degrees (Hoffman et al., 2019; Murray,
2019). Online master’s degrees, according to one estimate, have quadrupled since 2004 (Blagg,
2018).
The growth of online graduate education has increased its visibility to university leaders
and yielded attention from the higher education community. There is a growing body of research
on online graduate education, but the focus has primarily been remedial. Some studies have
focused on identifying retention issues and persistence challenges of online graduate students
(Gazza & Hunter, 2014; Perry et al., 2008). Others have assessed online teaching challenges and
developed promising faculty practices to enhance pedagogical practices in online classes
(Getzlaf et al., 2009; Kebritchi et al., 2017). Some studies have also evaluated all online
learning's general perception and its effectiveness for learning and career outcomes (Braun,
2008; DeFleur & Adams, 2004). However, previous research has not adequately explored the
institutional management of online graduate programs. One management aspect, and the focus of
this study, is whether HEIs should develop internal capacity to start new or grow existing online
graduate programs or outsource them.
Previous research has outlined some common barriers inhibiting an institution’s ability to
scale its online graduate programs. These are broadly classified into cultural, resource,
capability, and structural barriers (Chen, 2009; Owusu-Ansah et al., 2011; Ryan & Young, 2015;
Saba, 2011; Simonson et al., 2011). Cultural barriers include the lack of a shared vision for
scaling online graduate programs, stemming from long-held perceptions among some faculty and
administrators that it is an inferior form of learning (Chen, 2009). Furthermore, institutions are
challenged by inadequate resources needed to acquire technology, build support services, and
4

offer training to effectively implement and operate multiple online graduate programs (Chen,
2009; Simonson et al., 2011). Some institutions are resistant because they lack the appropriate
capability to plan for costs, accessibility, faculty concerns, federal and state regulations, and
academic and student support operations (Owusu-Ansah et al., 2011). Lastly, an institution's
operational structure modeled on creating shared governance (Berger 2002) creates structural
barriers that hinder initiatives to respond to current online graduate education trends (Saba,
2011).
Field Context
According to the National Center for Education Statistics (NCES), over 16% of all
master’s degrees and 12% of all doctorate degrees are offered online (2015). Generally,
institutions choose one of two ways to manage their online graduate programs. Some institutions
opt to operate their online graduate programs exclusively in-house through investments in
technology, staff, and support services (Maloney & Kim, 2019). Some institutions opt to partner
with an external vendor to outsource one or more of these capabilities. Online Program
Managers (OPMs) are the most common institutional partners for online graduate program
management. They offer various services ranging from new student recruitment and establishing
online learning platforms to technology support and student retention and placement (Hall, 2019;
Mattes, 2017; Murray, 2019). The nature of an outsourcing partnership varies by the needs and
objectives of the institution. While the exact number of OPM partnerships is unclear, one
estimate indicates that as of 2020, there have been at least 696 university-OPM partnerships
(Holon IQ, 2020).
Scaling, or to scale, refers to growing or expanding in a balanced and usually profitable
way (Merriam-Webster). Such growth or expansion of online graduate education is highly
5

dependent on an institution’s goals and objectives. As such, the degree of scaling online graduate
programs is unique to each program and institution. In the context of this study, scaling refers to
growing student enrollment in one or more existing online graduate programs, adding new online
graduate programs, or both. A complete evaluation of scaling online graduate programs would
focus on all institutions' decision-making processes for selecting the appropriate scaling strategy.
However, this study focused on 567 private non-profit master’s and doctoral universities. This
selection's rationale was tied to this study's purpose, which necessitates examining institutions
that have demonstrated commitment to graduate education while incentivizing them to scale
them through online delivery. Private institutions enroll a majority (61%) of online graduate
students (Seaman et al., 2018). Master’s and doctoral universities include institutions that award
at least 20 research or scholarship doctoral degrees and institutions that award fewer than 20
research or scholarship doctoral degrees but at least 30 professional practice doctoral degrees
(Carnegie Foundation for the Advancement of Teaching, 2019).
Description of Stakeholder Groups
Much like any institutional innovation initiative, the successful scaling of online graduate
programs is supported by multiple institutional stakeholders. The decision of whether to build
internal capacity or partner externally impacts at least three key stakeholder groups: institutional
administrators, faculty, and students. Institutional administrators are senior-level leaders who
oversee essential institutional functions. They include Chief Online Learning Officers (COLOs),
Deans, Associate, and Vice Provosts, Administrative and Academic Vice Presidents, and Chief
Technology Officers (CTOs). This group reports to the institution’s highest leadership levels,
such as the Provost, President, and Board of Trustees. This group can influence a decision, and
these stakeholders are primarily responsible for ensuring that online graduate programs are
6

delivered successfully. The second stakeholder group, faculty, is also an essential part of the
decision-making process and collectively, they hold considerable power to influence institutional
leadership. Faculty continue to be essential to online graduate programs during the creation of
coursework and execution of the in-class experience and student support. The third key
stakeholder group in this context is the students who enroll in an online graduate program. The
cost of their program, learning experience, ability to persist, and career outcomes can be affected
by the quality of online graduate programs offered by their institution because of the decision to
scale internally or with an external partner.
Stakeholder Group for the Study
While all stakeholders' collective efforts enable successful scaling of online graduate
programs, it is critical to explore the role institutional administrators play in selecting whether to
insource or outsource scaling. Therefore, this study's stakeholders were institutional
administrators at private non-profit master’s and doctoral universities. In the context of this
study, this group of institutional administrators who hold various types of leadership positions
was referred to as Online Program Leaders (OPLs). OPLs’ knowledge of institutional resources,
structure, and capability is essential to their decision-making process of insourcing or
outsourcing scaling. Moreover, they need to navigate institutional influences that either hinder or
support their decision-making process and their ability to ensure that the chosen option is
implemented successfully. Failure to address these challenges could result in the improper
selection and implementation of the chosen alternative, consequently preventing the successful
scaling of online graduate programs.
7

Purpose of the Study and Research Questions
This study focused on exploring the process of selecting a sourcing strategy once an
institution had decided to scale its online graduate programs. While a complete evaluation study
would focus on all online graduate program stakeholders, for practical purposes, the stakeholders
of this analysis were OPLs at private non-profit master’s and doctoral institutions. The analysis
focused on their knowledge and institutional influences impacting their decision-making process
to deliver successful online graduate programs. The research questions that guided this study
were the following:
1. What knowledge and skills do OPLs utilize in selecting whether to insource or
outsource the delivery of online graduate programs at scale?
2. How do institutional influences impact OPLs in selecting whether to insource or
outsource the delivery of online graduate programs at scale?
Importance of the Study
The purpose of this study was to explore OPLs’ selection process regarding whether to
scale online programs internally or with an external partner. Current literature does not offer
insight into the key considerations involved in such decision-making. As a result, some
institutions may be hesitant to pursue scaling their online graduate programs or might fail to
scale appropriately (Derousseau, 2015; Hillman & Corkery, 2010; Kowalewski & Hortman,
2019). In both scenarios, institutions face considerable negative consequences. They may not be
able to respond appropriately to increasing demand for online graduate programs and capitalize
on the opportunity to generate additional revenue (Marcus, 2017). They also leave themselves
vulnerable to competition (Porter & Graham, 2016) and shortfalls from declining traditional
undergraduate enrollment (National Center for Education Statistics, 2019). The decision on how
8

best to scale online graduate programs holds far-reaching and long-lasting implications for
institutions (Amirault, 2012). OPLs charged with advising institutional leadership about the best
alternative and guiding its implementation need to have sufficient knowledge and institutional
support (Kowalewski & Hortman, 2019). This study explores the impact of these considerations
on OPLs and proposes some best practices for implementation.
Overview of the Conceptual and Methodological Framework
This study utilized the Clark and Estes’ (2008) gap analysis framework, which helps
identify organizational goals and their alignment with the knowledge, motivation, and
organizational influences. The conceptual framework was adapted to explore knowledge
influences and organizational influences of the institutions they serve. The influences were
generated based on higher education context-specific as well as a general learning theory. A
mixed-methods explanatory sequential methodological framework consisting of quantitative and
qualitative methods was. A survey of OPLs at 567 private non-profit doctoral universities
followed by interviews with 12 OPLs and document analysis of their institutional and unit-level
strategic plans and training materials was conducted.
Definitions
Graduate education: A general term refers to all post-baccalaureate education, including but not
limited to master’s and doctoral degrees – research, scholarship, and professional practice, post-
baccalaureate certificates, and post-master certificates.
Graduate schools: A term colloquially used to refer to institutional units that oversee graduate
education based on the field of study (Okahana & Zhou, 2019)
Online graduate program: A term refers to the instructional delivery mode, time, and flexibility
of a graduate program (Mayadas, Miller & Sener, 2015). In this context, the term refers to
9

master’s and doctoral programs where courses are delivered primarily through a web-based
learning platform.
Online Program Manager (OPM): A general term commonly used to describe a company,
usually for-profit, facilitates online education programming. The services provided include but
are not limited to a learning management system (LMS), enrollment management, marketing,
and student support.
Organization of the Project
This study is organized into five chapters. This chapter provided essential concepts and
terminology used in the context of online graduate education. The field context of graduate
education with a description of key stakeholders and this study's framework was also described
in this chapter. Chapter 2 provides a review of the current literature surrounding the study's
scope. Topics of barriers related to scaling online graduate programs and deciding whether to
build internal capacity or utilize an external partner will be explored along with OPLs’
knowledge and organizational influences impacting this selection. Chapter 3 details the
methodology of participant selection, data collection, and analysis. In Chapter 4, the data is
assessed and analyzed to explore common themes and differences between OPLs at institutions
with different sourcing strategies. Chapter 5 concludes the study with a discussion and
recommendations for practice and future research.
10

Chapter Two: Review of the Literature
This literature review's findings are best understood in a general context of institutional
decision-making for outsourcing or insourcing online graduate programs. Each institution has
unique distinguishing characteristics such as mission, structure, resources, type of graduate
programs, quality of teaching and research, and technology capabilities. These characteristics are
commonly known to influence deciding and implementing the best way to deliver online
graduate programs. This literature review has four main aspects: common barriers preventing
scaling of online graduate programs, considerations for scaling online graduate programs;
considerations for scaling in partnership with an Online Program Manager (OPM); and
considerations for scaling through internal capacity building. The Clark and Estes (2008) gap
analytic framework will be introduced to examine Online Program Leader (OPL) knowledge and
organizational influences impacting their decision-making.
Rise of Online Graduate Programs
As discussed earlier, graduate education has grown on account of accessibility to
graduate student aid and its perceived value to enhance students’ professional advancement
opportunities (Baum et al., 2013; Gándara & Toutkoushian, 2017; Ma et al., 2020). Online
graduate education has benefitted from the same factors, and advances in information technology
and communication systems have made the online delivery of courses attainable for most
institutions. While online learning has existed in the form of distance education since the mid-
1800s (Verduin & Clark, 1991), the comparatively recent advent of the internet and subsequent
developments in learning technology have revolutionized online higher education. Since the
1990s, higher education has witnessed increased utilization of learning management systems
(LMS), growth of massive open online courses (MOOCs), and a surge in online enrollments
11

(Daniel, 2012; Dziuban et al., 2016). Simultaneously, new technology has allowed synchronous
and asynchronous online course delivery and the adoption of new teaching models (Chen et al.,
2010; Palvia et al., 2018). These developments have collectively enabled willing institutions to
expand online program offerings to enroll students previously considered to be unreachable.
Generally, graduate students are full-time workers with family, financial, and time
constraints (Palvia et al., 2018). The flexibility of online learning allows them to fit class time
and coursework seamlessly into their busy schedules. The popularity of online learning among
graduate students is gleaned from the latest federal data on online education enrollments, which
showed that in 2018, nearly 40% of graduate students were enrolled in some form of online
coursework, up by almost 8% from 2017 (National Center for Education Statistics, 2019). The
same reported indicated that nearly 30% of all graduate students in 2018 chose to pursue a fully
online graduate program (National Center for Education Statistics, 2019). This upward trend is
expected to continue as students, 25 years old and above, are expected to rise (Hoover, 2017).
The rise of online graduate programs has presented both an opportunity and a challenge
to some institutions. On the one hand, they are incentivized to accelerate their online graduate
programs due to future undergraduate education challenges. Some expect a pronounced decline
in new undergraduate student enrollment in the next decade. This outcome is due to skepticism
about the value of a college degree, increasing cost, an unwillingness to incur significant debt,
and perceived insufficient support for low-income and minority students (Grawe, 2018; Hoover,
2017). On the other hand, some institutions are not fully equipped to accelerate their online
graduate programs. The lack of administrative support, resources, and understanding of online
pedagogy have hindered institutional efforts to capitalize on this opportunity (Chow & Croxton,
12

2017; Kentnor, 2015). More significantly, institutional culture, particularly faculty acceptance of
online learning's value and legitimacy, remains (Lloyd et al., 2012; Allen & Seaman, 2016).
Impact of the COVID-19 Pandemic
This study was conducted amid the COVID-19 global pandemic, which was declared a
public health emergency in January 2020 (World Health Organization, n.d.). To curb the spread
of the deadly virus causing this pandemic, higher education institutions, much like all of society,
were forced to suspend all in-person activities (Marsicano et al., 2020). Institutions quickly
pivoted from in-person to online learning to adapt to the situation. This transition was
challenging for all institutions due to its abrupt nature and the lack of adequate infrastructure to
promptly train faculty and staff with varying technological preparedness levels (Hodges et al.,
2020). Institutional leaders faced various challenges due to this abrupt disruption. A notable
consequence felt immediately by most institutions was in overall student enrollment, which fell
by 3.3% from fall 2019 to fall 2020 (National Student Clearinghouse Research Center, 2021).
During the same period, undergraduate enrollment dropped 4.4%, and freshman enrollment
declined by as much as 13% (National Student Clearinghouse Research Center, 2021).
While undergraduate enrollment suffered one of its worst declines in recent years,
graduate enrollment improved by 2.9% from fall 2019 to fall 2020 (National Student
Clearinghouse Research Center, 2021). While it is unclear precisely what caused this surge in
graduate student enrollment, some have credited to online delivery of graduate courses and its
resulting flexibility as one of the main reasons for its popularity among graduate students
(Gallagher & Palmer, 2020). Simultaneously, some institutions solicited Online Program
Managers (OPMs) to shift to emergency online learning. According to one estimate, the first half
of 2020 saw an unprecedented 51 new OPM-institutional partnerships (Holon IQ, 2020). These
13

two factors' confluence has led to some speculation that expanding the online graduate programs
will become an integral part of several institutions’ post-pandemic plans (Gallagher & Palmer,
2020; Teräs et al., 2020).
Scaling Online Graduate Programs
The rise of online graduate programs can generally be attributed to a few entrepreneurial
faculty and staff efforts within each institution. A recent study conducted by a consulting firm,
Gartner, found that most online graduate programs have grown out from individual units within
institutions (Morgan, 2019). Such individualized initiatives have created inefficiencies, such as
multiple OPMs working with various graduate programs at the same institution, causing
duplication of learning services and cost inefficiencies (Morgan, 2019). These inefficiencies can
impede institutions’ rising student expectations and response to competition. This section will
present common barriers preventing the scaling of online graduate programs, followed by
considerations institutions for deciding whether to outsource this effort or not.
Common Barriers Preventing Scaling of Online Graduate Programs
A 2017 survey of 110 top academic administrators, including deans, vice presidents, and
provosts, revealed institutional culture, resources, and structure as significant barriers to
innovation (Magda & Buban, 2018). Driven by dynamic technological advancements, online
graduate education represents an opportunity for institutional innovation. The culture at most
institutions is defined by a service model supporting residential undergraduate students and has
remained unchanged for the past two decades (Burnette, 2015; Chen, 2009; Hanna, 1998). A
shift in institutional culture is essential for growing online graduate programs. However, it also
causes concern among tenured faculty and seasoned staff who are likely to experience a shift in
their roles and responsibilities (Lloyd et al., 2012; Simonson et al., 2011). Furthermore, the push
14

from institutional leadership to rapidly grow online graduate programs may lead to a lack of
shared vision and clear strategic goals for all stakeholders (Simonson et al., 2011). Efforts to
scale quickly can be met with resistance, resulting in a lengthier than expected implementation
timeline and additional resources investment.
Another common barrier that prevents most institutions from successfully delivering
online graduate programs at scale is limited resources. Scaling requires significant investment in
technology and human resources to sustain program quality and provide adequate student and
faculty support (Chen, 2009; Morgan, 2019). Most institutions do not have sufficient
technological infrastructure, such as a learning management system (LMS) and student
information system (SIS), to manage multiple online classes and troubleshoot technology issues
(Chow & Croxton, 2017; Owusu-Ansah et al., 2011). Furthermore, retaining a growing number
of online students requires additional support staff (Owusu-Ansah et al., 2011).
In addition to resource barriers, institutions are challenged by a lack of capability for
scaling online graduate programs. They lack the technical expertise and internal support needed
to develop, implement, and scale these programs (Cifuentes et al., 2018). More significantly,
faculty making the transition to online teaching is constrained by competing priorities, such as
conducting research and publication to gain tenure (Lloyd et al., 2012; Hoyt & Oviatt, 2013;
Wright, 2014). Collectively, these challenges prevent key institutional stakeholders from
developing sufficient capability to scale efficiently. A final common barrier hindering scaling
efforts is institutional structure. Some studies have indicated that most institutional structures are
not conducive for scaling online graduate programs (Berger, 2002; Hanna, 1998; Saba, 2011).
They are structured to prioritize residential students' teaching and support (Saba, 2011).
Supporting distant graduate students requires restructuring institutional operations. However, the
15

shared governance model, requiring multiple stakeholder approvals (Hoyt & Oviatt, 2013;
Berger, 2002), can curtail institutional efforts to innovate in preparation for supporting online
graduate students.
Considerations for Scaling Online Graduate Programs
A comprehensive evaluation of institutional capacity and readiness would entail assessing
all operational areas with all stakeholders. However, this study focuses primarily on two key
considerations impacting the successful delivery of online graduate programs at scale:
developing strategic goals for scaling and conducting an internal capacity analysis. Collectively,
these considerations address various aspects of the common barriers described above.
Developing Strategic Goals for Scaling Online Graduate Programs
Research literature emphasizes that online graduate programs' successful scaling begins
with developing a strategic goal (Piña et al., 2017; Hirumi, 2005; Rovai & Downey, 2010). A
first step in establishing a strategic goal for successful scaling is determining an institutional
approach for producing quality online graduate programs (Rovai & Downey, 2010). This
approach serves as a foundation for decision-making and informs the potential impact of internal
or external scaling. Drawing upon industrial approaches for measuring quality, Hirumi (2005)
stressed that promoting learner satisfaction, enhancing the learning experience, and retaining
learners are essential for creating quality online graduate programs. These three elements inform
an assessment of the capacity needed to support online graduate students' anticipated growth and
guide the allocation of resources to address shortcomings.
The next step in establishing a strategic goal involves analyzing decision factors.
Whereas research literature does not identify decision factors specific to online graduate
programs' scaling, some studies have provided insight into other institutional operations aspects
16

(Moloney & Tello, 2008; Phipps & Merisotis, 2005; Stallings, 2001). They point to various
considerations: faculty and staff performance consideration, institutional financial impact,
expectations of service, level of risk and potential exposure involved in each alternative,
alignment with institutional mission, and institutional control over intellectual property are some
of the factors (Moloney & Tello, 2008; Phipps & Merisotis, 2005; Stallings, 2001). For instance,
institutions desiring control over intellectual property are likely to favor internal capacity
building versus outsourcing (Moloney & Tello, 2008). On the other hand, institutions with fewer
financial resources may be hesitant to invest in learning technology acquisition or enhancement
and are likely to favor outsourcing (Stallings, 2001). Each factor influences institutional
capability to anticipate, prepare, and respond to potential challenges in their decision to insource
or outsource scaling of online graduate programs.
Internal Capacity Analysis
As referenced earlier, for the past two decades, most institutions' operating model has
been centered on servicing residential undergraduate students (Hanna, 1998). This model
consists of a few key features like a primarily residential student body; extensive physical
facilities including classrooms; library, and a physical plant; non-profit financial status; full-time
faculty primarily focused on teaching and scholarship; and institutional effectiveness evaluation
tied to measurements of inputs such as endowments, faculty qualifications, and resource
enhancements (Hanna, 1998). This model is no longer conducive to institutions aiming to
respond swiftly to a dynamic and hypercompetitive online learning environment. Besides, each
institution’s unique operating model and structure lend to various operational gaps needing
additional support, either through internal capacity building or outsourcing (Hillman & Cokery,
2010).
17

Literature reveals a few different models for conducting internal capacity analysis in
preparation for scaling online graduate programs. Piña’s (2017) diagnostic model, adapted from
industrial-organizational development (OD) theory developed by Cummins and Worley (2015),
has suggested an analysis of three significant components – inputs, design components, and
outputs. The first component, inputs, includes all human and non-human resources such as
students, employers, community, regulations, institutional finances, technology, and finances
(Piña, 2017). In this context, institutions can measure their inputs by determining ideal future
students' characteristics, analyzing regulatory constraints, and understanding institutional
finances and stakeholder involvement to identify best practices for scaling online graduate
programs.
The second component of Piña’s (2017) diagnostic model, the design component,
involves analyzing the institutional operating framework that will transform inputs into outputs.
This framework informs the scaling scope and includes strategy, structure, human capital, and
culture (Piña, 2017). In the context of scaling, an analysis of strategy involves understanding the
institutional mission and objectives for scaling online graduate programs. Analysis of
institutional culture could reveal potential shortcomings of operating in a shared governance
model (Dubnick, 2014), requiring multiple stakeholder approvals for change initiatives.
Similarly, analyzing institutional structure can lead to an accurate determination of critical
infrastructural needs for scaling. The third component of this diagnostic model, outputs, refers to
a collection of expected scaling outcomes and includes a measure of enrolled students, retention
rates, graduation rates, and program reputation (Piña, 2017). In this context, institutions can
apply the tenants of expected outcomes to determine whether an internal capacity building or
outsourcing is ideal for managing online graduate programs' scaling.
18

Piña’s (2017) diagnostic model, rooted in industrial organization development theory,
offers a comprehensive framework for analyzing institutional capacity in preparation for scaling
online graduate programs. However, other methods of assessment exist, both from outside and
within higher education. One such method, proposed by the Online Learning Consortium (OLC),
is called the Quality Scorecard for Administration of Online Programs. This scorecard provides
standards and benchmarks to evaluate online programs' administrative quality (Online Learning
Consortium, 2019). In the context of delivering quality online graduate programs at scale,
institutions could utilize categories such as institutional support, technology support, course
development, faculty support, and student support to determine gaps in institutional capacity. An
analysis of such gaps can generate a comprehensive list of capacity requirements and determine
whether internal capacity building or outsourcing is the best way to scale.
Scaling Externally with an Online Program Manager
A popular option among institutions electing to outsource their online graduate programs
is partnering with an Online Program Manager (OPM). OPMs absorb the upfront costs of
launching these programs, making it possible for institutions to quickly launch their online
graduate programs with little to no investment (Hoffman, 2012; Morgan, 2019; Springer, 2018).
OPMs have become a prominent part of the online learning ecosystem, which is estimated to
generate $1.5 billion in revenue while serving over 20 million online students (Mattes, 2017).
The mostly private nature of such partnerships, especially with private institutions, has resulted
in the lack of adequate research and understanding of what makes an OPM-based online graduate
program scaling strategy viable.
19

Understanding OPM Partnerships
OPMs are educational technology companies that can service every operational aspect of
an institution. Such services include but are not limited to recruitment and enrollment
management, student management systems, core technology infrastructure, learning management
systems, digital library, learning analytics, assessment, and relationship management (Hall 2019;
Murray, 2019; Williamson 2020). OPMs invest their technology capital and services without
charging upfront fees in exchange for a share of tuition revenue generated from the partnership
Hall 2019; Murray, 2019; Springer 2018). This arrangement has made them an attractive partner
for most institutions who lack the financial resources to acquire that capability. Over the last two
decades, at least 60 OPMs have emerged as prominent partners for scaling online programs in
higher education (Holon IQ, 2020).
In general, there are two types of OPM partnerships. The first one, considered to be the
more popular type of partnership, involves OPM offering a comprehensive service package
based on institutional needs in exchange for a predetermined percentage of tuition revenue for a
specified period (Springer, 2018; Morgan, 2019). Some estimates suggest that, depending on the
number of services requested, OPMs seek somewhere between 30% and 80% of tuition revenue
for as many as five to eight years (Murray, 2019; Straumsheim, 2015). The second type of OPM
partnership is fee-for-service. In this arrangement, an OPM offers one or more of its services for
a flat fee (Springer, 2018). This agreement's private nature does not allow for public disclosure
of the terms of the agreement, making it difficult to know the institution's level of financial
investment (Berman, 2019). This partnership can help institutions with the financial resources
invest in acquiring short-term capabilities to ramping up their scaling efforts.
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Outcomes of an OPM Partnership
The mostly private nature of OPM partnerships has allowed only a limited understanding
of the possible outcomes of OPM partnership for institutions. However, some outsourcing
studies have broadly outlined both positive and negative outcomes of an OPM partnership. A
commonly stated positive outcome of such partnership is that it enables institutions to instantly
respond to competition and internal pressure for growing graduate programs (Hall, 2019; Sang,
2010). Secondly, outsourcing enables institutions to focus on their core strengths of teaching and
scholarship (Kowalewski & Hortman, 2019; Yarbrough, 2011). OPMs specialize in the online
delivery of programs and can provide support at scale, thus making faculty transition to online
teaching seamless. Finally, outsourcing prevents institutions from committing significant
financial resources to acquire and maintain technology infrastructure (Wekullo, 2017;
Williamson, 2020). Partnering with OPMs allows institutions to leverage their core strength of
teaching and scholarship while preserving their financial resources.
While outsourcing can be advantageous, adverse outcomes are critical to consider. By
outsourcing operations, institutions lose control of the quality, efficiency, and effectiveness of
the services OPMs provide (Herath et al., 2010). For example, since OPMs manage online
students' recruitment of multiple programs at various institutions, individual institutions may
only get partial access to their ideal candidate pool. On the other hand, since OPMs present
themselves as agents of the institution, improper recruitment practices could harm institutional
reputation. More significantly, the advantage of no upfront costs in OPM partnerships could
prove costly if enrollment is below projected targets. Since institutions give up somewhere
between 30% and 80% of tuition revenue, they need to enroll a significantly high number of
students consistently to realize decent financial gains (Berman, 2019).
21

The sudden rise of OPMs in higher education has brought negative attention to them.
Some skeptics cite OPM’s profit-driven goals and lack of accountability as being at odds with
institutions' core mission (Mattes, 2017). They argue that OPMs who take significant portions of
tuition revenue leave institutions with no opportunity to reduce tuition costs that could make
their programs more accessible (Lee, 2017). Furthermore, in some partnership arrangements,
OPMs themselves set the tuition price and determine the ideal class size (Berman, 2019).
Consequently, institutions may be compelled to prioritize growth over program quality, leaving a
lasting negative impact on their reputation long after that. These concerns have resulted in
scrutiny from the Government Accountability Office (GAO) that has questioned OPMs business
practices' legality, and have recently launched a comprehensive analysis of OPM partnerships
(Lederman, 2021; McKenzie, 2020).
While the potential benefits and pitfalls of an OPM partnership can be understood more
broadly, the lack of transparency has prohibited a comprehensive understanding of such
agreements. For example, the fundamental question of whether an OPM partnership ultimately
benefits graduate students remains unknown. The lack of transparency has been met with
growing calls for complete disclosure of partnership agreements and additional government
oversight (Lederman, 2021). Given the lack of transparency of OPM partnerships, institutions
inclined to partner with OPMs should weigh these outcomes in the context of mission and vision.
When aligned with institutional objectives and needs, such a partnership can be very beneficial
to scale quickly and compete effectively in a dynamic graduate education market (Maloney &
Kim, 2019; Springer, 2018). However, such a partnership also needs constant monitoring and
evaluation. Institutional leaders who possess a proper understanding of OPM partnerships and
22

their overall institutional impact are well-positioned to select the best vendor and formulate a
partnership that delivers on institutional goals (Wekullo, 2017).
Scaling through Internal Capacity Building
While OPM partnerships have been a popular choice for scaling online graduate
programs over the past two decades (Baines & Chiarelott, 2010; & Berman, 2019), the prospect
of giving up significant tuition revenue and the lack of transparency has prompted some
institutions to look for alternatives. One such alternative is to build internal capacity by acquiring
or enhancing technology infrastructure and a support system for online faculty and students
(McClure & Woolum, 2006). Though institutional needs and financial resources vary, capacity-
building initiatives generally take a lot more time to achieve than outsourcing (Hoffman, 2012).
Although the literature about internal scaling is limited, there are a few known positive
outcomes for institutions. First, institutional leadership has complete control over the quality,
efficiency, and effectiveness of online learning and support operations (McClure & Woolum,
2006). This control allows them to scale at their own pace and align with their mission and
vision. Second, since institutions get to keep their entire tuition revenue (McClure & Woolum,
2006), there is no pressure to secure consistently high enrollments by lowering admission
standards. Consequently, the program and institutional reputation can remain intact. On the other
hand, this financial flexibility allows institutions to reduce tuition costs and increase the
accessibility of their programs.
Most institutions possess limited resource capabilities with multiple priorities to fulfill.
The building or enhancing existing technology infrastructure represents significant financial
commitment over a considerable period (Moloney & Oakley, 2010). Furthermore, the internal
capacity building does not end with merely enhancing technology. Institutions will also need to
23

consider investments for sustaining the operational framework that supports online learning at
scale. For example, real-time student support requires 24/7 technical support staff (Osika et al.,
2009). Faculty will also need ongoing support for course development, design, and
implementation (Green et al., 2009). These significant financial commitments represent
opportunity costs for institutions, which could be challenging to sustain in the long run.
Institutions inclined to pursue internal capacity building to scale online graduate programs
should weigh the tradeoffs that come with building internal capacity. Although limited, the
literature suggests that internal scaling can be an expensive and long-term endeavor (Moloney &
Oakley, 2010; &. Osika et al., 2009).
Clark and Estes’ (2008) Knowledge, Motivation and Organizational Influences’
Framework
The Clark and Estes (2008) gap analytic model was adapted to develop a conceptual
framework for this study. This model allowed a systematic analysis of organizational goals and
helped identify gaps between actual and desired performance (Clark & Estes, 2008). The gap
analysis process consists of six steps: defining measurable goals, identifying gaps in
performance, theorizing possible causes for gaps, validating gaps, developing solutions, and
assessing outcomes. The model allows potential causes for performance gaps to be analyzed
through three types of influences: knowledge, motivation, and organizational factors.
Most organizational challenges are confronted without a proper understanding of their
underlying causes (Clark & Estes, 2008). Consequently, these causes are either misdiagnosed or
ignored, leading to inaction or implementation of unsuitable solutions. Gap analysis is designed
to study the potential underlying causes of performance challenges to avoid creating unsuitable
solutions. Identified solutions are implemented along with an evaluation plan. Successful scaling
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of online graduate programs depends mainly on its ability to deliver quality online education
attributed to its reputation (Means et al., 2009). Hence, this study utilized the gap analytic model
to identify Online Program Leaders' (OPLs) strengths and weaknesses in the context of their
capacity to select the best approach to scale online graduate programs. The model suggests
analyzing three influences: knowledge, motivational, and organizational influences. This study's
scope was limited to understanding the process OPL’s utilize in source selection for scaling. As
such, examining motivational influences did not fit the scope of inquiry. Therefore, the
researcher examined OPL knowledge and organizational influences only. Since OPLs at higher
education institutions are the stakeholders of focus, organizational influences will be referred to
as institutional influences for the remainder of this study.
Online Program Leaders’ Knowledge and Institutional Influences
This section presents the assumed knowledge and institutional influences impacting
OPLs’ selection process for insourcing or outsourcing online graduate programs. Six assumed
influences, including three knowledge and three institutional influences, were analyzed. Each
influence is presented next and inspected using the methodology described in chapter three.
Knowledge Influences
It is important to examine an individual’s knowledge since it directly impacts their ability
to perform well and achieve set objectives (Clark & Estes, 2008). In this context, OPLs charged
with guiding online graduate programs' scaling need to understand the selected alternative's
institutional implications for scaling (Amirault, 2012). A systematic analysis of their knowledge
gaps will help them address these gaps and clarify whether their institution is best suited to scale
by internal capacity building or external partnerships.
25

Knowledge influences are categorized as factual, conceptual, procedural, or
metacognitive (Krathwohl, 2002). Factual knowledge refers to knowledge of basic terminology
and specific details or understanding of the task (Krathwohl, 2002). Conceptual knowledge refers
to knowledge of principles, theories, and models related to the task (Krathwohl, 2002).
Procedural knowledge is knowledge of subject-specific skills, techniques, and algorithms, and it
informs how the task should be carried out (Krathwohl, 2002). Finally, metacognitive knowledge
refers to an individual’s understanding of their knowledge of a particular set of tasks and their
awareness about it (Krathwohl, 2002). Since this study explored OPLs’ selection process in the
context of the effective delivery of online graduate programs, the following section will focus on
conceptual knowledge. Conceptual knowledge in this context refers to an OPL’s understanding
of their institutional resources, structure, and scaling capability.
Online Program Leaders’ Knowledge of Resource Implications of Scaling Decision
The ability to determine gaps in institutional resources for scaling online graduate
programs can be beneficial for OPLs. A few diagnostic models facilitate the measurement of
institutional financial, technology, and personnel resources (Morgan, 2019; Piña, 2017). These
models could provide clarity on resource needs and assist with planning on acquiring them. For
example, a clear understanding of current finances and financial goals could help determine if
the institution can afford a sustained investment in building or enhancing the operational
framework needed to serve a higher number of online graduate students at scale. OPLs need
conceptual knowledge about measuring institutional resources before making their selection for
leadership approval.
OPLs can also benefit from understanding the implication of scaling using each sourcing
alternative. If resource assessment leads OPLs to decide on internal capacity building, they could
26

benefit by knowing what functional areas will be most impacted (Hoffman 2012; Krathwohl,
2002). For example, if additional student services staff are needed, OPLs will need to work with
student affairs staff to manage the process of hiring, training, and monitoring them. On the other
hand, if the best way to address shortcomings in institutional resources is through external
partnerships, OPLs will be better prepared to negotiate the agreement's scope, price, and the
expected outcome (Morgan, 2019). As a result, the institution can expect to have a successful
partnership to deliver successful online graduate programs at scale.
Online Program Leaders’ Knowledge of Structural Implications of Scaling Decision
Despite serving as senior-level institutional leaders, many OPLs do not fully understand
their institutional structure’s potential impact on entrepreneurial initiatives such as scaling online
graduate programs (Nworie, 2012). This lack of conceptual knowledge makes it difficult for
OPLs to select the correct alternative and poses a challenge in successfully implementing the
chosen option (Krathwohl 2002; Nworie, 2012). OPLs need to have a conceptual understanding
of the role institutional structure plays in enabling or hindering online graduate programs'
scaling.
OPLs can benefit from having an in-depth understanding of their institution’s shared
governance model, a model that most graduate programs operate. In essence, this model requires
informal and formal agreement from multiple stakeholders before a significant initiative is
undertaken (Berger, 2002; Dubnick, 2014). In the context of this study, an OPL’s decision to
select internal capacity building for scaling would require support from graduate program faculty
and staff, as they are vital partners in ensuring that potential shortcomings are addressed
(Hoffman, 2012; Morgan, 2019). On the other hand, selecting to outsource scaling by partnering
with an OPM could be supported by those eager to scale quickly without investing significant
27

resources (Moloney & Tello, 2008). Before making their final selection, OPLs need to
understand how best to build consensus and support.
Online Program Leaders’ Knowledge of Institutional Capability for Scaling
In addition to having in-depth knowledge of resource and structural implications of
insourced or outsourced scaling, OPLs can benefit from knowing their institution’s capability for
scaling online graduate programs. This conceptual knowledge refers to their ability to analyze
and evaluate institutional objectives for scaling (Amirault, 2012; Krathwohl, 2002). Possessing
this ability could help OPLs define the scope of the initiative and develop clear goals for success.
Consequently, outsourcing OPLs can be better prepared to enlist key performance outcomes
required of an external partnership. On the other hand, insourcing OPMs can develop a plan
outlining the support needed from key internal stakeholders.
OPLs can benefit from understanding institutional capability as it might inform the
selection of the most effective alternative. Past research has lacked detailed exploration models
to assist analysis of source section for scaling online graduate programs. However, one model,
designed by the Online Learning Consortium (OLC), offers a benchmarking model that can be
modified and applied for analysis. There are seven significant factors outlined in this model, and
four factors that apply to OPL knowledge of institutional capability are administration support,
technology support, student support, and faculty support (Online Learning Consortium, 2019). In
this context, the administration support factor refers to an analysis of the institutional mission,
vision, strategic plan, governance structure, systematic processes, resource allocation, policy,
guidelines, and regular assessment protocols (Online Learning Consortium, 2019). The
technology support factor refers to analyzing whether the current technology framework and
future enhancement plans are desired for scaling (Online Learning Consortium, 2019). Similarly,
28

faculty support and student support factors refer to examining whether the institution has
established clear standards for teaching and learning, proper access to academic and non-
academic resources, and a system to receive and implement feedback for continuous
improvement (Online Learning Consortium, 2019). Despite its perceived benefits, the model has
not been the subject of past research, and consequently, its robustness, applicability, and impact
have not been verified.
This study explored OPL's conceptual knowledge of institutional resources, structure, and
capability for scaling online graduate programs. These knowledge influences serve as a
framework for evaluating insourcing and outsourcing alternatives. Once an option is selected,
these influences can inform implementation and impact desired scaling outcomes. Table 1
summarizes knowledge influences and associated knowledge types affecting OPL knowledge for
choosing the appropriate scaling alternative.

Table 1
Knowledge Influences
Assumed knowledge influence Knowledge type
OPL knowledge of resource implications of scaling decisions. Conceptual
OPL knowledge of structural implications of scaling decisions. Conceptual
OPL knowledge of institutional capability for scaling. Conceptual

29

Institutional Influences
Another element of the gap analytic model and a determinant of an individual’s
performance is their organizational influences (Clark & Estes, 2008). According to Gallimore
and Goldenberg (2001), organizational influences are categorized in cultural models and cultural
settings. Both cultural models and cultural settings are interconnected and collectively contribute
to the organization's overall culture that influences an individual’s knowledge (Clark & Estes,
2008; & Gallimore & Goldenberg, 2001). This study examined one cultural model and two
cultural setting influences.
Institutional Priority for Scaling Online Graduate Programs
Institutional priority for scaling online graduate programs represents a cultural model
influence. A cultural model is an established collective mindset of individuals within an
organization (Clark & Estes, 2008). It consists of shared values, including mission, vision,
strategic plans, and overall organizational philosophy (Schein, 2010). Over time, these values
develop into a set of shared assumptions that determine the organization’s behavior and approach
in response to a change initiative (Schein, 2010). In addition to an overall cultural model,
individual units may also have their cultural models with more assumptions unique to their
members (Schein, 2010). To ensure the organizational culture is managed appropriately, Schein
(2010) argued that leaders need to have a comprehensive understanding of the cultural models
that prevail within their organization.
Sourcing strategy selection for scaling online graduate programs is impacted by several
institutional factors driven by an institution’s articulated vision and objectives (Chaney et al.,
2010; Elloumi, 2004; Simonson et al., 2011). Institutional leadership can prioritize scaling online
graduate programs by including them in the strategic plan. Institutional strategic plans embody
30

an institution’s collective resolve to its most pressing challenges, inform its topmost priorities,
inform resource allocation, and instigate action (Martin & Kumar, 2018; Piña, 2017). In this
context, leadership can articulate their vision for scaling online graduate programs and align it
with the overall institutional mission (Chaney et al., 2010). Consequently, institutional processes
can evolve to promote greater interdepartmental collaboration, resolve structural issues, foster
creativity, and increase resource sharing (Magda & Buban, 2018; Martin & Kumar, 2018).
Collectively, these actions can create an institutional culture supporting OPLs not just sourcing
strategy selection but also for their online graduate students (Chaney et al., 2010; Rovai &
Downey, 2010).
Institutional Resource and Structural Support for Scaling
Institutional resource and structural support for scaling represent a cultural setting
influence. The cultural setting consists of tangible artifacts that include structures, systems, and
processes informed by an organization’s cultural model (Schein, 2010). Despite being tangible
and observable, they are often complex to decipher as they reflect individual rationalizations or
aspirations (Schein, 2010). Therefore, before commencing a change initiative, organizational
leaders need to understand these underlying assumptions informing performance and preparing
to mitigate the anxiety released when challenged (Schein, 2010).
To ensure that the selected alternative is implemented successfully, institutional
leadership needs to provide OPLs with the necessary resources and structural support. One way
to do so is by setting clear vision, goals, and methods to measure scaling progress (Clark &
Estes, 2008). In this context, identifying the scaling of online graduate programs as a top
institutional priority would result in the articulation of clear objectives and expectations and
signal its importance of allocating the appropriate resources. Following goal setting, institutional
31

leadership needs to ensure that institutional structure and critical business processes align (Clark
& Estes, 2008). Once scaling online graduate programs is identified as a crucial institutional
goal, the technological and support services framework may need reorganization, resulting in
restructuring business units and personnel reassignment (Saba, 2011). Institutional leadership can
prepare stakeholders to accommodate such substantial changes to ensure the seamless
implementation of scaling online graduate programs occurs regardless of the chosen alternative.
Institutional Communication of Scaling Online Graduate Programs
Institutional communication of scaling online graduate programs also represents a
cultural setting influence. As discussed before, the cultural setting consists of tangible artifacts
that include structures, systems, and processes informed by an organization’s cultural model
(Schein, 2010). These elements affect people’s perception of the organization and their
interactions (Gallimore & Goldenberg, 2001). Leaders can use effective communication to
clarify and reinforce organizational goals, manage expectations, establish clear and consistent
rules of engagement, and foster internal collaboration (Schein, 2010).
To ensure that the best alternative for scaling online graduate programs is selected,
institutional leaders need to support OPLs by regularly emphasizing their importance for
graduate programs' financial sustainability. As discussed before, institutional leadership can
articulate the importance of scaling online graduate programs by making it a critical strategic
priority. They can reinforce this importance through constant and candid communication about
the process used to select an appropriate strategy and its foreseeable impact (Sener, 2010). Each
scaling alternative is likely to cause structural, resource, and personnel changes, which could
have a disharmonizing effect on the prevailing cultural model (Amirault, 2012; Shelton &
Saltsman, 2005). Institutional leaders can preempt such disruption by building trust through
32

proactive communication at various stages of their decision-making process (Schein, 2010). In
addition to outgoing, assertive communication, institutional leadership can encourage open
communication lines by inviting formal and informal feedback from all stakeholders (Waters et
al., 2003). Such communication helps creates a culture of trust among stakeholders while also
helping leadership develop situational awareness (Waters et al., 2003). Thus, institutional
leadership can prepare OPLs to adapt their selection approach to stakeholders' needs and
appropriately address any concerns.
This study explored the impact of institutional priorities for scaling online graduate
programs and its articulation in the context of selecting the best scaling alternative. It also
explores how resource and structural support provisions for scaling influence OPL’s selection of
insource or outsourced sources. Table 2 provides a summary of the institutional influences that
impact OPLs scaling decisions.

Table 2
Institutional Influences
Assumed institutional influence Institutional influences
Cultural Model Influence Institutional leadership needs to prioritize the scaling
of online graduate programs.
Cultural Setting Influence Institutional leadership needs to provide resource and
structural support in implementing the selected
sourcing strategy.
Cultural Setting Influence Institutional leadership needs to regularly emphasize
the importance of scaling online graduate programs to
ensure graduate programs are sustainable.

33

Conceptual Framework
Thus far, knowledge and institutional influences were explored individually to assess
their impact on OPL capacity to selecting insourcing or outsourcing to scale online graduate
programs. In this section, a conceptual framework portraying these influences as interdependent
connections is presented. According to Merriam and Tisdell (2016), a conceptual framework is
used to present literature, experiential knowledge, and theories in a guided structure. This study’s
conceptual framework is adapted from the Clark and Estes (2008) gap analytic model. This
study's research questions explore relationships between OPL knowledge and the institutional
influences that impact the final selection.

34

Figure 1
Conceptual Framework for Exploring OPL Selection Capacity

The conceptual framework diagram demonstrates an interdependent relationship between
institutional culture and OPL’s knowledge. At the center of this framework are OPL knowledge
influences. OPLs need to understand the resource and structural implications of scaling online
Instituional Influences
Institutional leadership needs to
prioritize the scaling of online
graduate programs.
Institutional leadership needs to
provide resource and structural
support in implementing the selected
sourcing strategy.
Institutional leadership needs to
regularly emphasize the importance
of scaling online graduate programs
to ensure graduate programs are
sustainable
Knowledge Influences
OPL knowledge of resource
implications of scaling decision.
OPL knowledge of structural
implications of scaling decision.
OPL knowledge of institutional
capability for scaling.
OPL capacity for selecting whether to insource or outsource scaling of
online graduate programs.
35

graduate programs while also knowing their institutional capability before deciding whether to
build internal capacity or partner with an OPM. While knowledge is essential to their selection
process, institutional influences also play a critical role in creating a purpose for OPLs. For their
selected alternative to be successful, OPLs need to be supported by all stakeholders, especially
institutional leadership. Institutional leadership can provide this support by establishing scaling
online graduate programs as an institutional strategic goal. They can reinforce this importance by
providing OPLs with the resources and structure necessary to ensure the chosen alternative's
successful implementation. Finally, through consistent and effective communication, they can
ensure that the entire institution supports OPLs throughout the process.
Summary
The literature review examined various considerations impacting OPLs’ decision-making
capabilities when selecting the best alternative for scaling online graduate programs. Literature
outlined common barriers that prevent scaling of online graduate programs, critical
considerations for scaling, considerations for scaling in partnership with an OPM, and
considerations for scaling through internal capacity building. The gap analytic framework (Clark
& Estes, 2008) was utilized to build a conceptual framework outlining the interdependent
relationship between OPLs’ knowledge and institutional influences in the context of their scaling
decision. Chapter three presents the study’s methodological approach for data collection,
instrumentation, assumed OPL knowledge, and institutional influences.
36

Chapter Three: Methodology
This study utilized a mixed-methods sequential explanatory design for data collection.
Quantitative and qualitative methods were used to explore Online Program Leader (OPL)
knowledge and institutional influences impacting their source selection process. This chapter
begins with an outline of research questions and an overview of the methodology. Data
collection, instrumentation, and analysis for each of the methods used are presented next. The
chapter concludes with a discussion on ethics and the researcher's role.
Research Questions
The purpose of this study was to identify the knowledge and institutional influences
affecting OPLs’ decision-making process in the selection of insourcing or outsourcing scaling of
online graduate programs. The following research questions guide this study:
1. What knowledge and skills do OPLs utilize in selecting whether to insource or outsource
the delivery of online graduate programs at scale?
2. How do institutional influences impact OPLs in selecting whether to insource or outsource
the delivery of online graduate programs at scale?
Overview of Methodology
This mixed-methods sequential explanatory study applied a two-phase design involving
quantitative and qualitative methods. The first phase consisted of a survey of OPLs at 567 private
non-profit master’s and doctoral universities. In the second phase, an interview with 12 OPLs,
followed by a document analysis of strategic plans and training materials, was conducted. This
design enabled quantitative and qualitative methods to address various aspects of this study’s
research questions (Creswell, 2016). Additionally, the quantitative method facilitated the
identification and purposeful selection of participants for the qualitative methods of interview
37

and document analysis. Table 3 below outlines the methods used to answer the three main study
questions.

Table 3
Data Sources
Study questions Survey Interview Document
analysis
What knowledge and skills impact OPLs in selecting
whether to scale online graduate programs through
insourcing or outsourcing?
X X X
What institutional influences affect OPLs’ selection
regarding whether to insource or outsource scaling of
online graduate programs?
X X X

38

Data Collection, Instrumentation, and Analysis Plan
Survey
The quantitative phase of this study utilized a simple random cluster sampling survey.
This section will describe participating stakeholders, survey instrumentation, and data collection
methods. Survey validity and reliability are discussed last.
Participating Stakeholders
The random cluster sampling survey technique involved sampling all eligible participants
within a unit or group, called a cluster (Fink, 2015). In the context of this study, the cluster
consisted of Online Program Leaders (OPLs) at private non-profit master’s and doctoral
universities. The Carnegie classification, a widely used framework for grouping roughly
comparable institutions, was used to identify 567 institutions (The Carnegie Foundation for the
Advancement of Teaching, 2019). The OPL cluster consisted of senior-level institutional
administrators, including Chief Online Learning Officers (COLOs), Deans, Associate or Vice
Provosts, Administrative and Academic Vice Presidents, and Chief Technology Officers (CTOs).
These stakeholders were selected primarily due to their responsibility for selecting an appropriate
sourcing strategy and ensuring that the scaling was successfully implemented. There were two
selection criteria for survey participation. First, participants had to identify as being actively
employed by one of 567 private non-profit master’s and doctoral institutions. Second,
participants needed to indicate that they were either individually or as part of a group or
committee tasked with sourcing strategy selection for final approval. Responses from
participants were excluded if they indicated their role was limited to merely supporting the
selection process.
39

Instrumentation
The survey instrument consisted of 21 questions, including Likert-type items,
dichotomous, and open-ended questions. The survey's demographic questions were designed to
identify stakeholder role and level of responsibility, institution's classification, the current status
of the scaling initiative, and the selected sourcing strategy. The survey focused on exploring OPL
assumed knowledge and institutional influences. Questions pertained to the role of OPL
knowledge of institutional resources, structure, and capability in evaluating scaling alternatives.
Questions also focused on understanding the connection between OPLs’ sourcing strategy
selection and institutional culture for scaling online graduate programs. Lastly, questions
considered OPLs’ understanding of their institutional priorities for scaling online graduate
programs. Towards the end of the survey, participants were asked if they would be willing to
participate in a confidential follow-up interview. If the respondent selected yes, indicating their
willingness to be interviewed, they were requested to provide their name and an email address.
Appendix A presents the survey instrument.
Data Collection Procedures
The data collection process commenced following the approval of USC’s Institutional
Review Board (IRB). An informed consent form via a USC IRB-approved information sheet and
an online self-administered Qualtrics questionnaire was disseminated to participants. Due to the
vast array of OPL roles, participation solicitations were distributed through a variety of channels.
Listservs of various professional higher education organizations, such as the Online Learning
Consortium (OLC), EDUCAUSE, the National Association of Graduate Admission
Professionals (NAGAP), and the University Professional and Continuing Education Association
(UPCEA), were utilized. The researcher also utilized LinkedIn to solicit responses from their
40

professional network. Data collected from the Qualtrics questionnaire was downloaded and
stored on a password-protected laptop and a password-protected portal storage drive. Both
devices were maintained securely by the researcher.
Ensuring the anonymity of participants and their institutions was essential for this study.
Before completing the survey, each participant was asked to provide informed consent. After
reviewing the information sheet (Appendix A), participants indicated they provided their consent
to participate by clicking “yes.” The survey did not request identifiable data, except from
respondents who agreed to participate in the follow-up interview. They were asked to provide
their name and email address for interview selection and scheduling interviews. Participants
were assured that this data would be held confidentially by the researcher and only until the
conclusion of the data analysis phase. The identifiable data, along with survey responses, was
promptly deleted following the conclusion of this study. Finally, all IRB policies, procedures,
and requirements were adhered to in order to protect the participants' data.
Validity and Reliability
The results of quantitative research methods need to provide valid and reliable knowledge
for practical application (Merriam & Tisdell, 2016). Validity refers to the accuracy with which a
method measures what it is supposed to measure (Salkind, 2015). Reliability refers to the
consistency with which the method measures what it is supposed to measure under the same
circumstances (Salkind, 2015). Validity and reliability are critical to dissipate doubts about a
study's outcomes (Salkind, 2015). In the context of this study, validity refers to the extent to
which the survey can measure OPL institutional influences. At the same time, its reliability
centers on being able to measure these influences with consistency. Triangulation of multiple
sources of data was conducted to ensure validity and reliability. The process consists of
41

comparing and crosschecking data collected in this survey with data collected in follow-up
interviews and document analysis (Creswell, 2016; Patton, 2014). To further ensure survey
validity and reliability, the researcher adapted some questions and prompt responses from
existing valid surveys from two studies closely related to this study's topic (Creswell, 2016;
Patton, 2014). The researcher’s dissertation committee reviewed the survey before IRB approval.
Interviews
The qualitative research phase of this study began with conducting 12 interviews. The
rationale for 12 interviews was to reach data saturation and conduct meaningful analysis about
OPL knowledge and institutional influences in the context of source selection for scaling online
graduate programs. This section will describe participating stakeholders, interview
instrumentation, and data collection methods. The discussion follows with a description of
ensuring the credibility of the research findings and the researcher's trustworthiness.
Participating Stakeholders
This study utilized purposeful sampling in selecting participants for an interview. A
unique sample was selected based on the participants' essential attributes concerning the
phenomenon of interest (Merriam & Tisdell, 2016). Exploring OPLs’ knowledge and
institutional influences that impact their source selection process was the focus of this study. As
described earlier, the stakeholder group was OPLs at private non-profit master’s and doctoral
universities. There were two selection criteria for interview participation. First, participants had
to identify as being actively employed by one of 567 private non-profit master’s and doctoral
institutions. Second, participants needed to indicate that they were either individually or as part
of a group or committee tasked with sourcing strategy selection for final approval. Responses
42

from participants were excluded if they indicated their role was limited to merely supporting the
selection process.
The researcher aimed to investigate a range of patterns and differences in OPL
knowledge and institutional influences for scaling online graduate programs. To achieve this, a
maximum variation sampling was utilized (Merriam & Tisdell, 2016). A total of 12 participants
were selected for the interview and divided into three main subgroups. The first subgroup
consisted of four outsourcing OPLs and the second subgroup consisted of four insourcing OPLs.
The third subgroup of four OPLs was added after survey responses revealed a third sourcing
strategy where institutions simultaneously utilized insourcing and outsourcing. Next, and to the
extent that it was possible, each subgroup consisted of two central and two graduate schools
OPLs. Furthermore, within each subgroup, OPLs whose institutions represented the three highest
Carnegie classifications were randomly selected. No financial reward was promised to
participate in the survey. While 12 participants may appear to be a limited sample size, it was
appropriate due to the high-ranking position each OPL held and the scope of their responsibility
in selecting an appropriate sourcing strategy (Merriam & Tisdell, 2016).
Instrumentation
OPL interviews were conducted using a semi-structured interview format. This study has
measured variables, OPL knowledge, and institutional influences subject to a respondent’s
interpretation. Therefore, a semi-structured interview format is most suitable for adequate
exploration (Merriam & Tisdell, 2016). While the order of interview questions was
predetermined, the open-ended nature of questions allowed the researcher to deviate from the
order when necessary and probe further for a deeper understanding of certain concepts (Merriam
& Tisdell, 2016). Interviews were scheduled for 45-60 minutes each and consisted of 16
43

interview questions plus probes. Participants were asked about their knowledge of institutional
resources, structure, and capability. They were also asked to share their understanding of
institutional influences related to scaling and their impact on selecting a sourcing strategy.
Collectively, questions allowed exploration of assumed knowledge and institutional influences.
Appendix B outlines the interview instrument in detail.
Data Collection Procedures
An interview protocol facilitated systematic data collection with consistency (Patton,
2014). The interview instrument and information sheet for informed consent were emailed to
each participant in advance of the interview (Appendix B). The instrument outlined interview
instructions, questions and included a confidentiality statement and a statement of appreciation
for participation (Creswell & Creswell, 2017). All interviews were conducted virtually, using the
Zoom conference platform. Conducting a telephone interview was an alternative for participants
who did not have access to or preferred not using Zoom. All participants agreed to be
interviewed via Zoom. To protect the interviewee’s identity, the researcher destroyed all
recordings after this study. Before commencing the interview, each participant was requested to
review the information sheet, ask clarifying questions, and provide verbal informed consent.
Furthermore, the interviewee was afforded the option to mask their identity in the Zoom session.
The interview recording commenced once the interviewee granted explicit permission.
Credibility and Trustworthiness
Generating credible and trustworthy analysis for application in professional practice was
vital to this study. Therefore, the researcher ensured that data was collected and analyzed
ethically and truthfully. Credibility refers to evidence that study findings are accurate and
authentic (Merriam & Tisdell, 2016). Trustworthiness relates to the researcher and implies that
44

the research was conducted logically, consistently, and ethically (Merriam & Tisdell, 2016).
Credibility and trustworthiness were primary considerations at every stage in the research
process, including interview design, data collection, and analysis. The interpretative nature of
interview data, researcher bias in the form of misjudgment, misinterpretation, and
misunderstanding of participants' responses and feelings were considered (McEwan & McEwan,
2003). Triangulation between the preliminary quantitative survey and the qualitative interview
and document analysis was used to ensure the findings' credibility (Creswell & Creswell, 2017;
Patton, 2014). Interviewees were extended an opportunity to review their interview transcription
to confirm the accuracy of their statements. One interviewee made this request, and their
interview transcript was sent via email. The researcher allowed interviewees to review the
transcription to confirm the accuracy of their statements. Additionally, at the beginning of the
interview, the researcher disclosed their bias and positionality in this study's context in the ethics
section. The goal of such disclosure, known as reflexivity, was not to eliminate but acknowledge
and understand research bias and use it in a productive manner (Merriam & Tisdell, 2016).
Document Analysis
Institutional strategic plans, graduate school strategic plans, and OPL training materials
were analyzed in this study. The scope of this analysis was restricted to documents from
institutions represented by the 12 participating OPLs. Strategic plans generally are publicly
accessible and openly shared through an institution’s website. Typically, these plans span a three
to five-year period, serve as an indicator of the institution’s top priorities, and guide the
allocation of its resources (Uzarski & Broome, 2019). OPL training materials consisted of
various aids and tools used in assessing institutional resources, structure, and capability for
scaling online graduate programs.
45

Data Collection Procedures
The selection of strategic plans and training materials was guided by the study’s research
questions and emerging findings from the survey and interview data (Merriam & Tisdell, 2016).
Document analysis was conducted to reveal consistencies and inconsistencies with data collected
through other methods (Maxwell, 2013). One key concept explored in both the survey and
interviews was the importance institutions place on online graduate programs' scaling. Strategic
plans guide resource allocation and reveal institutional capability (Uzarski & Broome, 2019),
both of which are part of assumed OPL knowledge and institutional influences. Strategic plans
also provide an institutional and graduate school outlook of anticipated challenges and
opportunities (Uzarski & Broome, 2019). Analysis of such outlook illuminated the underlying
connection between institutional influences, sourcing strategy selection, and scaling challenges.
Institutional and graduate school strategic plans were through institutional websites.
Training materials were requested from interview participants during their interview. During
analysis, documents were downloaded and stored on the researcher's password-protected laptop
and a password-protected portal storage drive. To maintain the interview participants'
confidentiality, the researcher destroyed all collected documents at the study’s conclusion.
Findings were reported using pseudonyms individual and institutional anonymity in the analysis
of collected data.
Data Analysis
Data analysis was conducted to understand the meaning of the data collected (Merriam &
Tisdell, 2016). Analysis began with quantitative data gathered through the survey of OPLs at 567
non-profit master’s and doctoral universities. Survey results were analyzed using standard
descriptive statistics such as mean, median, and mode (Salkind, 2017). Closed-ended ordinal
46

survey items are analyzed using percentage and frequency (Salkind, 2017). Inferential analysis
was conducted to identify statistically significant relationships in responses based on certain OPL
characteristic variables. A ranked ANOVA test was conducted on selected sourcing strategy
responses, the Carnegie classification of their institution, and their graduate school's academic
discipline. A t-test was conducted on responses based on OPL role. Open-ended survey items
were coded and categorized in the same manner as data collected through qualitative interviews
and tallied using Microsoft Excel. Survey results will be discussed in narrative form and
displayed through tables in Chapter 4.
This study's qualitative data included data collected through interviews with 12 OPLs and
document analysis of their institution’s strategic plans and training materials. Qualitative data
were analyzed by coding data and identifying themes to answer research questions (Merriam &
Tisdell, 2016). Coding and categorization were based on OPL knowledge and institutional
influences, as outlined in this study’s conceptual framework. Answers were coded and
categorized using NVIVO. Interview themes were contextualized through survey responses.
Institutional documents were used alongside survey and interview data to provide institutional
context and insight into certain aspects of the process, leading to selecting a sourcing strategy.
Documents also provided information to analyze respondents’ perceptions and guard against
potential bias (Patton, 2014). Interview and document analysis findings will be discussed in
Chapter 4.
Ethics and Role of the Researcher
A research's findings' reliability and credibility depend on the researcher's credibility who
collects and analyzes that data (Patton, 2014). Ethical research practices such as respect and
goodwill for participants are critical to ensure credibility. These practices were followed
47

throughout the study in the form of obtaining informed consent to participate, emphasizing
voluntary participation, safeguarding the confidentiality, and permitting participants the right to
withdraw at any time without penalty (Kruger & Casey, 2009; Merriam & Tisdell, 2016; Rubin
& Rubin, 2012). These practices were also applied to the recording and storage of data for the
duration of the study. To ensure ethical data collection, the researcher extended respect for all
participants, honored promises made, avoided coercion, and did not harm participants (Rubin &
Rubin, 2012).
This field study was conducted with a focus on online graduate programs in higher
education. The researcher is a senior-level higher education administrator at one of the 567 non-
profit master’s and doctoral universities identified in the study's stakeholder group. However, the
researcher holds neither the position nor the level of responsibility needed to influence
institutional decision-making in the context of how best to scale online graduate programs.
Despite the potential risks associated with the researcher’s relationship with some stakeholders,
either at his current institution or previous institutions, no explicit exclusion criteria on such a
selection basis were applied.
The researcher holds a pragmatic worldview primarily concerned with applying
solutions, using multiple approaches to solving problems, and open to different assumptions
(Creswell & Creswell, 2017). In this study, the researcher assumes that scaling online graduate
programs, whether through insourcing or outsourcing, is inherently beneficial for most graduate
programs and their institutions. While such an assumption may be valid for some graduate
programs and institutions, others may deem the endeavor unnecessary or contradictory with their
mission and identity. As an experienced higher education administrator and a doctoral candidate
in an online program managed through outsourcing with an Online Program Manager (OPM),
48

the researcher is aware of the impact of his experiential knowledge on this study. As such, the
researcher holds a favorable view of outsourcing online graduate programs with OPMs.
However, the researcher does not favor any particular OPM. To minimize the impact of these
assumptions and biases, the researcher relied on peer review and feedback from his dissertation
committee throughout the research design, data collection, and analysis phase (McEwan &
McEwan, 2003; Probst & Berenson, 2014).
49

Chapter Four: Results and Findings
This study explored the decision-making process of Online Program Leaders (OPLs) in
selecting insourcing or outsourcing the scaling of online graduate programs. The analysis
focused on OPLs’ knowledge and institutional influences. While a complete exploration would
include all institutional stakeholders, this study focused mainly on OPLs responsible for
selecting a sourcing strategy. Two research questions guided the focus of this study:
1. What knowledge and skills do OPLs utilize in selecting whether to insource or outsource
the delivery of online graduate programs at scale?
2. How do institutional influences impact OPLs in selecting whether to insource or
outsource the delivery of online graduate programs at scale?
This mixed-methods sequential explanatory study consisted of a survey followed by
interviews with OPLs at private non-profit doctoral and master’s universities. The researcher
developed the survey protocol to measure OPL knowledge of institutional resources, structure,
and capability and explore their perception of institutional influences. The semi-structured
interview protocol allowed further investigation of these results and identified common themes
among OPLs whose institutions chose the same sourcing strategy. Document analysis was
conducted to analyze OPL knowledge influences related to assessing institutional readiness for
scaling and institutional influences impacting their sourcing selection process.
Participating Stakeholders
The study sample consisted of OPLs at 567 private non-profit doctoral and master’s
universities. They included senior institutional leaders such as Chief Online Learning Officers
(COLOs), Deans, Associate or Assistant Deans, Associate or Vice Provosts, Administrative and
Academic Vice Presidents, and Chief Technology Officers (CTOs). The study began with a
50

survey that was distributed in three ways. First, the researcher sent an email to 1681 eligible
OPLs through Qualtrics. Second, a link to the survey was also shared through listservs of three
professional higher education associations. Lastly, the researcher shared a survey link through
his LinkedIn social media account. A total of 147 total responses were received, of which 107
responses met the survey criteria. Thirty-two (32) participants indicated their interest in a follow-
up interview.
Survey Participants
The 107 survey participants represent various doctoral and master’s universities. Table 4
below provides a breakdown of the institutions by Carnegie classification. Forty-four OPLs from
the third tier of this classification, Doctoral/Professional Universities, make up the largest group
(41.12%) of participants. OPLs hold various roles broadly classified into two categories,
centralized and graduate school. Sixty-eight graduate school OPLs (63.55%) serve as Dean,
Assistant, or Associate Dean at a graduate school, whereas 39 centralized OPLs (36.45%) hold
various positions within their university’s central administration. Business and education Deans
make up most of the 68 graduate school OPLs. Additional details of OPL roles are listed in
Tables 5 and 6.
Survey participants were asked to indicate the sourcing strategy utilized to scale online
graduate programs. Fifty-eight OPLs indicated their institution chose to insource scaling, while
24 OPLs revealed outsourcing as their institution’s selected strategy for scaling. The typical
outsourcing strategy consists of partnering with an Online Program Manager (OPM) for a three-
to-seven-year period. The OPM invests in all the upfront costs of launching new online graduate
programs in change for a portion of the tuition revenue, typically 50%. Twenty-five OPLs said
their institution used both sourcing strategies simultaneously. The most common manifestation
51

of this strategy is referred to as fee-for-service. The institution purchases or leases specific
capabilities from an outside vendor for a fee and without any long-term partnership agreement.

Table 4
Survey Participants’ Institutional Profile Breakdown (N = 107)
Institution by Carnegie Classification Results
Percentage Frequency
R1: Doctoral Universities 10.28% 11
R2: Doctoral Universities 12.15% 13
D/PU: Doctoral/Professional Universities 41.12% 44
M1: Master’s Colleges and Universities 14.02% 15
M2: Master’s Colleges and Universities 13.08% 14
M3: Master’s Colleges and Universities 9.35% 10

Table 5
Survey Participants’ Title Breakdown (N = 107)
Title Results
Percentage Frequency
Assistant/Associate/Vice Provost 20.56% 22
Assistant/Associate/Vice President 9.35% 10
Chief Information Officer (CIO) or Chief Technology
Officer (CTO)
3.74% 4
Chief Online Learning Officer (COLO) 2.80% 3
Dean of a School/College 40.19% 43
Assistant/Associate Dean of School/College 11.21% 12
Other (please explain) 12.15% 13
Note. 13 participants selected “other” and provided their titles. All 13 titles indicate that these
OPLs hold positions within a graduate school or college.

52

Table 6
Survey Participants’ Breakdown by Academic Discipline (N = 68)
Academic discipline Results
Percentage Frequency
Business 18 26.50%
Engineering 5 7.40%
Education 15 22.10%
Social sciences and the humanities 2 2.90%
Health 1 1.50%
School of Professional Studies 10 14.70%
Other (please explain) 17 25.00%

Interview Participants
Interviews with 12 OPLs followed the conclusion of the survey. Interview participants
were selected with maximum variation sampling. Such selection aimed to investigate common
themes and differences in knowledge and institutional influences among a range of OPLs whose
institutions chose different sourcing strategies. As mentioned previously, 25 of the 107 survey
participants indicated that their institution used insourcing and outsourcing strategies.
Consequently, a third sourcing strategy, “both,” was added to interview selection criteria and
referred to as such in findings and results discussions. The 12 interview participants represent the
three sourcing strategies equally. Within each subgroup, OPLs represent the Carnegie
classification's top three tiers and various central and graduate school positions. Table 7 presents
interview participants’ demographic profiles. This study's scope did not involve investigating the
number of existing Online Program Manager (OPM) partners and OPM partnerships. However,
during the interview, some non-insourcing OPLs indicated partnering with at least one OPM.
These OPMs are referred to in the following results and findings using pseudonyms.
53

Table 7
Interview Participants’ Demographic Profiles
Participant Title Sourcing strategy Carnegie
classification
Participant 1 Associate Dean Insource R2
Participant 2 Director of Academic Innovation Insource R1
Participant 3 Dean Insource R1
Participant 4 Dean Insource D/PU
Participant 5 Dean of Graduate Programs Outsource R2
Participant 6 Dean Outsource R1
Participant 7 Director of Online Learning Outsource R1
Participant 8 Chief Online Learning Officer Outsource D/PU
Participant 9 Associate Provost Both D/PU
Participant 10 Associate Provost Both D/PU
Participant 11 Dean Both R2
Participant 12 Vice Provost Both R2

What Knowledge and Skills do Online Program Leaders (OPLs) Utilize in Selecting
Whether to Insource or Outsource the Delivery of Online Graduate Programs at Scale?
The researcher explored what knowledge guides OPLs in selecting a sourcing strategy for
scaling online graduate programs. The mixed-methods study approach consisted of a survey and
interviews to evaluate the role of such knowledge in assessing institutional resource, structure,
and capability readiness for scaling. The researcher also studied the impact of this knowledge in
their final selection of the sourcing strategy. Finally, two additional knowledge influences
emerged during data collection: OPL confidence in the sourcing strategy selection process and
the role of OPL awareness of the institutional context in overcoming scaling obstacles.
Knowledge Results and Findings
The researcher used survey data and interview findings to analyze assumed conceptual
knowledge influences. The survey data allowed analysis of OPLs’ foundational knowledge of
54

institutional resources, structure, and capability for scaling online graduate programs. Inferential
analysis was conducted on survey data to identify statistically significant relationships in
responses based on selected sourcing strategy, the Carnegie classification of their institution,
their role, or their graduate school's academic discipline. Interview findings were used to explore
further the degree to which this knowledge impacted their final selection of the sourcing strategy.
OPL Knowledge of Institutional Resources
The study explored three aspects of OPL knowledge of institutional resources: OPL
familiarity with funding, staffing, and technology; identification of resources most critical for
scaling; and the role of their knowledge of institutional resources in determining sourcing
strategy. As discussed earlier, these three aspects of OPL knowledge can be critical in providing
clarity for resource planning and determining the scaling initiative's long-term sustainability
(Morgan, 2019; Piña, 2017). In general, OPLs indicated being highly familiar with institutional
resources and identified funding as the most critical scaling resource. They also indicated that
their knowledge of institutional resources highly influenced source selection.
Extensive Knowledge of Institutional Resources. Survey participants were asked to
describe their level of familiarity with three institutional resources in the context of scaling
online graduate programs - funding, staffing, and technology. Respondents indicated having
significant familiarity with all these resources. Ninety percent (n = 86) of respondents said they
were either “moderately familiar” or “extremely familiar” with institutional funding. Similarly,
95.79% (n = 91) and 91.58% (n = 87) of respondents said that they were either “moderately
familiar” or “extremely familiar” with staffing and technology, respectively. Table 8 presents a
detailed breakdown of these results. The inferential analysis revealed no statistically significant
relationships in the degree of knowledge of institutional resources based on respondents’ selected
55

sourcing strategy, the Carnegie classification of their institution, their role, or their graduate
school's academic discipline.

Table 8
Survey Results for Level of Familiarity with Institutional Resources (N = 95)
Resource factors Results
Percentage Frequency
Funding
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
1.05%
8.42%
33.68%
56.84%
1
8
32
54
Staffing
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
4.21%
23.16%
72.63%
0
4
22
69
Technology
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
8.42%
30.53%
61.05%
0
8
29
58

56

Results were confirmed by interviewees who, at various points during the interview,
alluded to critical details about funding, staffing, and technology in the context of scaling online
graduate programs. A quarter of all interviewees are directly involved in planning these
resources' availability. Participant 9, whose institution is leveraging OPM services for a fee, said
that “a huge part of my charge is how to maximize and optimize the use of resources to ensure
we are partnering in the right way.” Participants 2 and 3 indicated that they serve on a budget
committee dedicated to ensuring all graduate programs are managed effectively. As a result, they
understand and leverage the financial model to generate funds for building internal capacity for
scaling. Participant 8, whose institution outsources its online graduate programs completely,
indicated that they developed a three-year plan outlining staff and technology requirements and
expected utilization along with the OPM. The plan outlined costs that were factored into the
program’s operating budget and consequently played a critical role in setting the tuition rate.
Identification of Funding as the Most Critical Scaling Resource. Survey participants
were asked to rank six institutional resources in the order of their importance for scaling online
graduate programs. Respondents ranked funding as the top resource, followed by instructional
design support and hardware and software support infrastructure. Faculty technology support,
course management system and staff development were the lowest-ranked institutional
resources. Table 9 provides a summary of these rankings.

57

Table 9
Survey Results for Ranking of Institutional Resources (N = 94)
Resource factors Results
Median rank Average of rankings
Funding
1
2.36
Instructional Design Support
2
2.52
Hardware and Software Support Infrastructure 3 3.37
Faculty Technology Support 4 3.66
Course Management System 5 4.5
Staff Development 6 4.59

Note. A six-point ranking scale was used, with 1 being the most important while 6 being the least
important resource.

Interviewees affirmed this result by also revealing funding as the most critical resource
for scaling online graduate programs. Insourcing interviewees offered a different perspective
than their outsourcing counterparts about the essential role of funding in this context. Insourcing
interviewees attributed the availability of funding as being advantageous to build sufficient
internal capacity. As Participant 2 stated, “We knew we could access all of our financial
resources, which was huge for hiring instructional designers and representatives.” Participant 4
echoed the same confidence for insourcing by saying that “having a budget to hire an admission
team and invest in marketing allowed us to grow two online programs simultaneously.”
Outsourcing interviewees also pointed to funding as the most critical scaling resource.
However, in their case, the lack of funding created scaling challenges. Participant 5 said that
their institution chose to partner with an OPM because “we simply didn’t have the marketing
budget to front the cost that we would need to market those programs at scale.” The lack of
appropriate funding also posed a challenge for recruitment efforts at Participant 6’s institution,
58

who said that “frankly, we just didn’t have the money to hire a team to pull off that level of
recruiting an OPM can do.” Outsourcing, therefore, became the only viable option for these
institutions.
Interviewees using both sourcing strategies also indicated funding to be crucial but to a
much lesser degree. Their institutions needed to fund the capacity building and recruitment
efforts only partially. For example, Participant 11 said that “it was easy to allocate money to
student support and technology support services because we were great at recruitment and
instructional design.” Similarly, Participant 12 indicated that they needed an OPM to support
marketing efforts for just one of their nine online graduate programs. Although funding was
limited in these instances, the impact was minimal due to existing capabilities. The narrow scope
of support needed to launch an online graduate program resulted in minimal impact.
Source Selection Highly Influenced by Knowledge of Resources. Respondents
indicated they were highly influenced by the knowledge of institutional resources when selecting
a sourcing strategy. Ninety-one percent (n = 86) of respondents said their knowledge of
institutional resources was “very influential” or “somewhat influential,” while only 9.47% (n =
9) indicated some or no influence in source selection (Table 10). This result was affirmed in their
response to an open-ended survey question regarding the main reason they selected to insource
or outsource. Outsourcing respondents indicated a lack of funding and staffing as the main
reason for their selection. Insourcing respondents indicated that their institution had adequate
staffing and support services. Respondents using both strategies indicated their institution was
amid transitioning from outsourcing to insourcing. A few selected responses are provided in
Table 11. The inferential analysis revealed no statistically significant relationships in the impact
of knowledge of institutional resources on source selection based on respondents’ selected
59

sourcing strategy, the Carnegie classification of their institution, their role, or their graduate
school's academic discipline.

Table 10
Survey Results for Knowledge of Institutional Resources in Source Selection (N=95)
How influential is (or was)
your knowledge of resources
(funding, staffing, technology)
in selecting whether to
insource or outsource scaling
efforts?
Results
Percentage Frequency
Very Non-Influential
Somewhat Non-Influential
Somewhat Influential
Very Influential
4.21%
5.26%
31.58%
58.95%
4
5
30
56

60

Table 11
Survey Responses to Main Reason for Scaling Strategy Selection
In a few words,
describe the main
reason why your
institution chose to
insource or outsource
the scaling of online
graduate programs.
Sourcing strategy Responses
Outsourcing
Chose to outsource three years ago to an OPM
because of the unwillingness and inability to
invest appropriately to scale online graduate
programs at that time.
We outsourced initially because we did not have
the capital to support scaled growth.
Insourcing
The School of Professional Studies has its own
distance learning department for instructional
design and pedagogical support and our own
marketing team, so we tend not to outsource.
Both
Doing both; needed OPM revenue to launch
internal scaling of online division.
We entered online more than a decade ago
through an OPM partnership. This was driven by
the need for external funding and low internal
capabilities and expertise. Today, we are
examining how we can build upon what we have
learned and invest more internally to build
greater capabilities and expertise.

Interview findings confirmed these results. In making a final selection of whether to
outsource, insource, or use both strategies to scale their online graduate programs, all
interviewees said their knowledge of institutional resources was critical. They analyzed staffing
levels, the state of technology, and the availability of funds before selecting the appropriate
strategy. Interviewees also indicated that they conducted a periodic review of institutional
resources to ensure that the select strategy is adequately supported.
61

Two insourcing interviewees reported collaborating with central online learning units
within their institution to scale and support online graduate programs. These units provide
comprehensive management of online all programs, including marketing, enrollment
management, technology, and student support. The presence of these resources and capabilities
led the interviewees to select insourcing. Interviewees leveraged this unit’s services to
understand and determine the allocation of resources. Participant 2 said that “when we were
building two healthcare online master’s degrees, Smart Online (pseudonym) helped me decide
how many instructional designers I needed.” Participant 1 affirmed this by saying, “I came into
my role not knowing how much it would cost to recruit online. But I worked closely with Quick
Online (pseudonym) for the first six months and came up with a budget for my Dean.”
Outsourcing interviewees pointed to the lack of funding and staffing resources as the
main reason for choosing to partner with an OPM. It was evident throughout the interview that
they thought their institution was not prepared to undertake scaling efforts on their own. As
stated earlier, Participants 5 and 6 indicated that lack of funding to market, recruit, and enroll
students was the main reason for outsourcing. While illustrating a failed initial attempt to scale
their first two online master’s programs, Participant 7 pinned the failure on underestimating
financial and personnel needs. They said, “we tried to do it all on our own, and there was so
much pressure to enroll quick and big that our marketing dollars ran out in six months, and one
admissions representative was just not enough.” Consequently, both programs were put on a
hiatus. They added, “that was painful, but we learned a lot,” and “we now know what it takes to
go online from scratch.” Recognizing that the institutional resources were inadequate for scaling
multiple online graduate programs, they chose to partner with an OPM.
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OPL Knowledge of Institutional Structure
Two aspects of OPL knowledge of institutional structure were explored. They were OPL
familiarity with structural factors related to scaling and the role of OPL knowledge of
institutional structure in determining sourcing strategy. Knowledge of such factors can help
OPLs select the appropriate scaling alternative and overcome potential obstacles related to
securing agreement from multiple stakeholders during scaling implementation (Berger, 2002;
Nworie, 2012). OPLs reported being generally highly familiar with their institutional structure.
However, they indicated that their knowledge of institutional resources did not significantly
impact source selection.
High Level of Familiarity with Prevailing Institutional Structure. Survey participants
were asked to describe their level of familiarity with three structural factors in the context of
scaling online graduate programs: shared governance structure, new program approval policy,
and institutional communication processes. Respondents indicated a high level of familiarity
with their institution’s prevailing structure. Ninety-four percent (n = 89) of respondents said that
they were either “moderately familiar” or “extremely familiar” with the shared governance
model overseeing graduate programs. Similarly, 98.95% (n = 94) said the same about their
institution’s new program approval policy. Finally, 93.69% (n = 89) of respondents said they
were either “moderately familiar” or “extremely familiar” with their institution’s communication
processes. Table 12 presents a detailed breakdown of these results. The inferential analysis
revealed no statistically significant relationships in familiarity with an institutional structure
based on respondents’ selected sourcing strategy, the Carnegie classification of their institution,
their role, or their graduate school's academic discipline.

63

Table 12
Survey Results for Level of Familiarity with Institutional Structural Factors (N=95)
Resource factors Results

Percentage Frequency
Shared Governance Structure
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
6.32%
23.16%
70.53%
0
6
22
67
New Program Approval Policy
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
1.05%
16.84%
82.11%
0
1
16
78
Institutional Communication
Processes
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
1.05%
5.26%
27.37%
66.32%
1
5
26
63

Interview findings confirmed survey results. Most interviewees provided detailed insights
about the role of shared governance in launching new or scaling existing online graduate
programs. Participant 5 outlined their role as a partner to individual graduate schools. In the
context of deciding which program to scale, they said, “I help them Deans think through whether
programs should be delivered online or not” and “ultimately it is completely their decision.”
Choosing to outsource with an Online Program Manager (OPM) was approached in the same
way. They said, “we tell them whether it's likely to be more profitable or not, what kind of
expectations they can have for enrollment if they use an OPM. But we still leave it in their hands
for making those decisions.” This perspective was consistent among central office interviewees.
Participant 9 described how they handled disagreements with graduate Deans opposed to scaling
a program or starting a new program with significant enrollment challenges. As an example, a
program under consideration appealed to Participant 9. They said, “We made a financial model
more than once and understood what it would take, and it was a heavy lift. I had talked about a
64

significant upfront investment from the OPM to help make that happen.”. However, they said,
“the Dean didn’t support it, so it didn’t move forward.”
Participant 6, Dean of a graduate school, described leading their efforts to launch new
online graduate programs. Per the agreement with their OPM, the college is required to start at
least one new online graduate program every year for seven years. Speaking of the challenge
posed by a cumbersome new program approval process, Participant 6 said, “it takes so much
back and forth and a thousand years to get approval, and then we are left to scramble to launch
quickly.” However, Participant 11, who serves on the institution’s new program approval
committee, provided a different perspective. They highlighted the responsive and efficient
process as a strength. They indicated that “we have a robust process to evaluate program
proposals, especially since we started an automated system. It has been much easier to give
feedback and see changes made in a timely manner.”
Source Selection Somewhat Influenced by Knowledge of Structure. Respondents’
knowledge of the structural factors was much less influential than institutional resources in
selecting a sourcing strategy. Sixty-three percent (n = 60) of respondents said their knowledge of
structural factors was “very influential” or “somewhat influential.” At the same time, 36.84% (n
= 35) indicated it was “somewhat non-influential” or “very non-influential” in source selection
(Table 13). The inferential analysis revealed no statistically significant relationships in the
impact of knowledge of institutional structure on source selection based on respondents’ selected
sourcing strategy, the Carnegie classification of their institution, their role, or their graduate
school's academic discipline.

65

Table 13
Survey Results for Knowledge of Structural Factors in Source Selection (N=95)
How influential is (or was)
your knowledge of structure
(shared governance, new
program approval policy,
communication processes) in
selecting whether to insource
or outsource scaling efforts?
Results
Percentage Frequency
Very Non-Influential
Somewhat Non-Influential
Somewhat Influential
Very Influential
11.58%
25.26%
38.95%
24.21%
11
24
37
23

Interview findings were consistent with survey results. Interviewees indicated that their
knowledge of institutional structure was less influential than their knowledge of resources and
capability. Participant 5, who revealed a lack of institutional resources for internal scaling, said
that shared governance had no impact on their selection. They said, “I knew I had to bring
everyone on board and convince them that the OPM route is best for us,” but also added that they
“did not factor the structure because we had no other choice.” Participant 2, an insourcing
interviewee, indicated that the institutional structure only partially drove their choice. They
portrayed their institutional structure as an asset for internal scaling and said, “I felt that our
online program approvals would be prioritized over other programs.” Despite that sentiment,
they added that “the decision to stay in-house was largely driven by having a decent marketing
budget and great instructional designers.” This perspective was echoed by other interviewees
who acknowledged institutional structure's role for successful scaling but not critical for
decision-making.
OPL Knowledge of Institutional Capability
The study explored three aspects of OPL knowledge of institutional capability related to
scaling online graduate programs: OPL familiarity with capability factors, the role of OPL
knowledge of institutional capability in deciding sourcing strategy, and the internal and external
66

entities involved in assessing institutional scaling capability. OPLs indicated possessing an in-
depth understanding of their institution’s capabilities. As discussed earlier, such knowledge can
help OPLs develop the scaling initiative's scope, develop clear goals for success, and enlist key
performance measurements (Amirault, 2012). They also indicated that their understanding of
institutional capability significantly impacted source selection. Finally, OPLs reported that
various entities were involved in helping them assess institutional capability.
In-Depth Understanding of Institutional Capability. Survey participants were asked to
describe their level of familiarity with five institutional capability factors in the context of
scaling online graduate programs: strategic plan(s), staff technological expertise, faculty
pedagogical expertise, student support systems, and faculty support systems. Respondents
indicated strong familiarity with their institution’s capability to scaling online graduate
programs. Ninety-nine percent (n = 94) of respondents said that they were either “moderately
familiar” or “extremely familiar” with their institution’s strategic plan. Similarly, 88.32% (n =
84) and 91.58% (n = 87) said they were either “extremely familiar” or “moderately familiar with
staff technology and faculty pedagogy expertise. Ninety-two percent (n = 87) of respondents said
they were either “moderately familiar” or “extremely familiar” with their institution’s student
support systems, and 93.69% (n = 89) said the same about faculty support systems. Table 14
presents a detailed breakdown of these results.
The inferential analysis revealed no statistically significant relationships in the degree of
knowledge of institutional capability based on respondents’ selected sourcing strategy and the
Carnegie classification of their institution. However, respondents in central roles appeared to be
more familiar with two capability factors than their graduate school counterparts. Respondents (n
= 46) in centralized roles reported a higher level of familiarity with staff technological expertise
67

(M = 3.57, SD = 0.58) than graduate school respondents (n = 49) (M = 3.20, SD = 0.79), p =
.012. Similarly, respondents in centralized roles (n = 46) reported a higher level of familiarity
with student support systems (M = 3.59, SD = 0.62) compared to graduate school respondents (n
= 49) (M = 3.31, SD = 0.65), p = .034.

Table 14
Survey Results for Level of Familiarity with Institutional Capability Factors (N = 95)
Resource factors Results

Percentage Frequency
Strategic Plan(s)
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
1.05%
20.00%
78.95%
0
1
19
75
Staff Technological Expertise
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
1.05%
10.53%
37.89%
50.53%
1
10
36
48
Faculty Pedagogical Expertise
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
8.42%
24.21%
67.37%
0
8
23
64
Student Support Systems
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
0
8.42%
38.95%
52.63%
0
8
37
50
Faculty Support Systems
Not at all Familiar
Slightly Familiar
Moderately Familiar
Extremely Familiar
-
6.32%
34.74%
58.95%
0
6
33
56

68

Interview findings confirmed most of the survey results. Interviewees appeared to be well
informed of the various capability factors and their role in scaling online graduate programs. To
further examine their knowledge about staff technological expertise and student support systems,
interviewees were asked to elaborate on their understanding of these two factors. Interviewees in
centralized roles, Participant 2, Participant 7, and Participant 11, appeared to be more familiar
with these two factors primarily due to their responsibilities. They all reported overseeing units
that support the instructional design and online student support of online graduate programs.
Participant 11 eluded to strengthening their student support services by saying, “since we started
growing online two years ago, I have added new support staff and reorganized schedules. We
now provide round the clock help to students for anything class-related or general support.”
Participant 2 highlighted the vital role played by their instructional designers by saying, “my
team understands how to design online courses, but most of all have the patience to work with
our faculty.”
Findings also confirmed the results of the inferential analysis of two capability factors.
Graduate school interviewees appeared to be less familiar with student support systems and staff
technological expertise. However, they were more familiar with other capability areas such as
faculty pedagogical expertise and faculty support systems. Participant 1, an Associate Dean,
shared that a significant part of their role was to ensure their faculty had access to training and
development opportunities to be effective online teachers. They said, “I have developed an
internal training program based on Quality Matters (QM) standards, and I require all online
faculty to go through it once a year.” They added that their institution adopted this training to
prepare all faculty to teach online during the COVID-19 pandemic.
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Source Selection Highly Influenced by Understanding of Capability. Respondents
indicated their understanding of institutional capability in scaling online graduate programs was
highly influential in selecting the sourcing strategy. Eighty-nine percent (n = 85) of respondents
said their knowledge of institutional resources was “very influential” or “somewhat influential.”
In contrast, only 10.60% (n = 10) of respondents indicated it was “somewhat non-influential” or
“very non-influential” in source selection (Table 15). This result was affirmed in their response
to an open-ended survey question regarding the main reason they selected to insource or
outsource. Outsourcing respondents indicated a lack of marketing and instructional design
capability as the main reason for their selection.
On the other hand, insourcing respondents identified instructional design and delivery
systems as a strength. They attributed this to having significant experience with conducting
online learning that resulted in steady infrastructure development. Respondents using both
strategies indicated they were leveraging their academic, operational strengths such as
instructional design and faculty support while seeking external assistance in marketing and
recruitment. A few selected responses are provided in Table 16. The inferential analysis revealed
no statistically significant relationships in the impact of knowledge of institutional capability on
source selection based on respondents’ selected sourcing strategy, the Carnegie classification of
their institution, their role, or their graduate school's academic discipline.

70

Table 15
Survey Results for Knowledge of Capability Factors in Source Selection (N=95)
How influential is (or was)
your knowledge of capability
(strategic plans, technological
and pedagogical expertise,
support systems) in selecting
whether to insource or
outsource scaling efforts?
Results
Percentage Frequency
Very Non-Influential
Somewhat Non-Influential
Somewhat Influential
Very Influential
3.20%
7.40%
36.80%
52.60%
3
7
35
50

71

Table 16
Survey Responses to Main Reason for Scaling Strategy Selection
In a few words,
describe the main
reason why your
institution chose to
insource or outsource
the scaling of online
graduate programs.
Sourcing strategy Responses
Outsourcing
Instructional design is the main reason we chose
to outsource. Secondary to that is marketing and
recruitment. Our OPM can reach a much broader
audience more effectively that our in-house
M&C folks can, based on resources.
There were two major factors. First, we are
relatively new to the space and felt that working
with a partner would help us learn and
eventually bring work in-house. Second, we
have what we consider a weak internal
marketing team and felt they were incapable of
effectively helping us launch and scale a new
program.
Insourcing
Our university has other colleges with well-
established online programs. We have a unit
called [University Name] University Online.
They do all the marketing and recruitment for
online programs. They also have a small team of
instructional design and multi-media specialists.
We chose to insource grad programs because we
have a strong internal system to develop the
programs and the quality and cost were better.
Both
We are insourcing (instructional design, faculty
development, retention services) and outsourcing
(marketing, recruitment, enrollment). We know
that often the most difficult piece of the puzzle is
student recruitment. Having an outside partner
gives us knowledge, capabilities, and ability to
scale that we don't have.

According to interviewees, institutional capability factors were highly influential in
source selection. Insourcing interviewees indicated that, besides resources, their institutional
72

capability allowed them to scale internally. As discussed previously, Participants 1 and 2
leveraged their central online learning unit for staff technological and faculty pedagogical
expertise and student support systems. Participant 1 said, “when we decided to grow online,
there was a well-established Quick Online(pseudonym) unit.” Elaborating further on the unit’s
capabilities, they said, “They have all the marketing and recruiting for online programs, but also
have a team of instructional design and multimedia services. So, we didn’t outsource with an
external company.”
On the other hand, outsourcing interviewees shared that they felt the capability for
scaling was generally lacking. Participant 7 highlighted their institution’s weakness in student
support systems by saying, “We tried two learning management systems (LMS) in five years but
couldn’t get either to work well,” and “leadership refused to invest in another system.”
Participant 8 indicated that instructional design was an area of their institution’s weakness. They
said, “we were new to online and didn’t have any understanding of instructional design or how
much technical staff to hire.” Their institution also wanted to scale quickly, and hence, “we felt it
was best to let the OPM handle all of it for us.” Interviewees using both sourcing strategies
generally indicated that institutional capability dictated the service or factor that needed to be
outsourced. Participant 11, for example, indicated that “our instructional design team is
exceptional, so I am contracting with an OPM only to help us with technical support and student
services.”
Identification of Various Entities Involved in Assessment of Institutional Capability.
Interviewees were asked to describe whether they sought expertise in assessing institutional
capability for scaling online graduate programs. Three types of assessment partners emerged –
internal consultants, external consultants, and professional associations (Table 17). Two
73

interviewees referred to their central online learning unit as the primary stakeholder in assessing
capability. As indicated previously, this unit provides comprehensive oversight and services of
online learning. Others pointed to creating an internal committee of staff and faculty to assess
capability. For example, Participant 12 said, “I lead a committee of graduate faculty, IT staff, and
enrollment management that meets every month to discuss our needs for online graduate
programs.” The scope of the committee, they said, includes “projecting instructional design
needs, technology support for class and other services, support staff for new programs,” and
“assessment of feedback from current students regarding their online learning experience.”
Some interviewees indicated using external consultants to develop a strategic plan for
scaling online graduate programs. Participant 5 said, “I am currently working with Go Online
Now (pseudonym) to develop a comprehensive plan for online.” According to them, this plan is
comprehensive, and a key component is to “plan and budget for all our service needs for the next
three years.” They added, “we have an aggressive growth plan, and I want to ensure that
leadership understands what it will take to get there. Go Online Now (pseudonym) is helping me
outline these needs based on market research and peer evaluation.” Similarly, other participants
indicated relying on paid consultants to develop a comprehensive scaling plan that considers all
institutional capability factors.
Participant 2, an insourcing interviewee, said that “I rely on the Online Learning
Consortium (OLC) and Quality Matters to make sure we provide quality instruction.” They
added, “OLC has engaged with us several times on matters of capacity and help us build a model
which tells us what we need per 50 online students.” This model, they believe, has allowed for
setting clear scaling expectations with institutional leadership. Speaking to their use of Quality
Matters, Participant 2 said, “we use them to certify new online instructors and provide annual
74

instructional training.” Other interviewees indicated a similar reliance on professional
institutions to explore best practices around capability assessment and enhancement.

Table 17
Summary of Entities Used for Capability Assessment
What sort of expertise, if any,
did you use to assist in the
assessment of institutional
capability for scaling online
graduate programs?
Entity type Description
Internal Consultants
Central Online Learning Unit, Staff
and Faculty Committee
External Consultants Specialized Consulting Firm
Professional
Associations
Quality Matters, UPCEA, Online
Learning Consortium, EDUCAUSE

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Additional Findings
Two additional findings of OPL knowledge emerged during data analysis. The first
finding pertains to OPL confidence in the process utilized to determine the appropriate sourcing
strategy. Data suggests OPLs are highly confident of their selection process and raised concerns
about their institution’s cultural challenges for embracing online graduate education. The second
finding highlights the importance of OPL awareness of their institutional context as a critical
way to overcome scaling challenges.
OPLs’ Mostly High Confidence in Source Selection Process
During their interview, most interviewees described their high level of confidence in the
process that led to a sourcing strategy's eventual selection. They were also outlined a few aspects
of the process that went well or could have gone better. A common reason for the high level of
confidence was their ability to build trust and collaborate with various stakeholders. Participant
11 highlighted their highly collaborative approach by saying, “I got everybody together at the
table. Our Deans, IT, Admissions, Marketing and Communication, Campus Services, Finance,
were all involved through the process.” That collaboration proved to be helpful for
implementation. “I am glad they walked away from the process knowing they had a say and were
ready to support our efforts,” they said, signaling buy-in from these units.
As described by several interviewees, a related outcome of the sourcing selection process
was clarifying scaling objectives. Most interviewees indicated that, at the onset, there was no
institutional strategic plan about scaling online graduate programs. Participant 7 said, “there was
never a sort of strategic plan for online learning,” while Participant 5 said, “our strategic plan
was to increase our online presence, but no specifics were spelled out.” Participant 3 said that “I
felt like I was building a plane while flying it,” while referring to the lack of strategic direction
76

and goals for scaling online graduate programs. Going through the selection process helped
clarify institutional scaling goals and, in some cases, led to the creation of a scaling-specific
strategic plan. Participant 3 added that “I just finished putting together a five-year strategic plan
for online programs, including a plan to go from 14 to 27 online programs.” Participant 11 said
that “online programs are 100% part of my school’s overall strategic plan and now the
university’s five-year strategic plan.” While interviewees felt confident about their selection
process, they also expressed concerns about their institution’s mindset for partnering with an
external vendor. Participant 3, an insourcing interviewee, said that some stakeholders viewed
online learning as an inferior form of learning. Specifically, they indicated that the process of
growing their online graduate program “revealed how unprepared we were to embrace a new
way of learning.” These findings are further discussed in the section on institutional culture.
Awareness of Institutional Context as Critical to Overcome Scaling Challenges
Interviewees were asked to share their suggestions for fellow Online Program Leaders
(OPLs) embarking on the process of selecting a sourcing strategy. Understanding institutional
context and operating effectively within it emerged as the most emphasized recommendation.
Participant 1 said, “it is important to consider your institution and the way it works, and also the
realities on the ground.” They recommended considering a few essential factors by saying,
“think of how faculty works, how the governance structure works, and what type of financial
support you are going to be able to expect.” Participant 9 stressed the importance of increased
collaboration with multiple stakeholders to identify potential challenges. They said, “use the
shared governance structure to get many voices at the table,” and added that hearing multiple
perspectives will help identify “low-hanging fruit and help focus on getting those early wins.”
77

Both participants indicated that this collaboration helped overcome obstacles during strategy
implementation.
Interviewees also suggested that OPLs assess the state of technology at their institution
carefully. Pointing to an initial assessment misstep, Participant 5 revealed, “I miscalculated our
collective understanding of the various systems and platforms, and how to best use them.” They
added “I wish I had conducted some assessment to know if we were ready to serve more online
students.” Their faulty optimistic assumption delayed strategy implementation. Most online
faculty and support staff had to undergo additional training on operating the administrative
technology systems for supporting online students. While the results of a more thorough
assessment would not have impacted their source selection, Participant 5 said, “I would not have
lost valuable time and saved everyone unnecessary frustration.”
Another notable finding in the institutional awareness context is the graduate program
approval policy and process. Interviewees in central roles indicated benefitting from having a
strong understanding of the critical stakeholders, process timeline, and new program approval
requirements. Participant 7 accounted for the approval timeline in new program launches. They
said, “I keep track of where the program is at with the academic program review committee
(APRC) and manage expectations with our OPM accordingly” and added, “it keeps us on track
to launch marketing as soon as the approval is complete.” Other interviewees’ comments echoed
the same opinion, and Participant 8 added that the relationship with the entity in charge of
program approvals is “the most underrated aspect of starting new programs.”
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How do Institutional Influences Impact Online Program Leaders (OPLs) in Selecting
Whether to Insource or Outsource the Delivery of Online Graduate Programs at Scale?
The purpose of this study was to explore knowledge and institutional influences
impacting OPL decision-making for selecting the appropriate scaling strategy. Understanding the
interaction between institutional culture and setting and its impact on OPL knowledge is critical.
Survey results and interview findings were analyzed to investigate whether institutional
influences helped or hindered OPLs' selection process.
Institutional Results and Findings
The researcher used survey data and interview findings to analyze OPLs’ institutional
influences. The survey data allowed analysis of institutional procedures and policies,
communication levels, and cultural barriers for scaling online graduate programs. Inferential
analysis was conducted on survey data to identify statistically significant relationships in OPL
responses based on selected sourcing strategy, the Carnegie classification of their institution,
their role, or their graduate school's academic discipline. Interview findings were used to explore
further the degree to which institutional influences impacted OPLs’ final selection of the
sourcing strategy.
Institutional Procedures and Policies as Unconducive for Scaling
Survey participants were asked to indicate their satisfaction level in receiving
institutional support for implementing the chosen scaling strategy. They rated four factors:
financial resources, human resources, technological resources, and policy support. Only 47.2%
(n = 42) of respondents indicated that they were “extremely satisfied” or “somewhat satisfied”
with financial resources, and similarly, 44.9% (n = 40) with human resources. Technological
resources and policy support factors received slightly more favorable ratings. Similarly, only
79

55% (n = 49) of respondents indicated that they were “extremely satisfied” or “somewhat
satisfied” with technological resources, and 59.5% (n = 53) with policy support. Table 18
presents a detailed breakdown of these results. The inferential analysis revealed no statistically
significant relationships in the level of satisfaction for the support received during scaling
implementation based on respondents’ selected sourcing strategy, the Carnegie classification of
their institution, their role, or their graduate school's academic discipline.

Table 18
Survey Results for Satisfaction in Institutional Support for Scaling Implementation (N = 89)
Resource factors Results

Percentage Frequency
Financial resources
Extremely Dissatisfied
Somewhat Dissatisfied
Neither Satisfied or Dissatisfied
Somewhat Satisfied
Extremely Satisfied
7.87%
25.84%
19.10%
42.70%
4.49%
7
23
17
38
4
Human resources
Extremely Dissatisfied
Somewhat Dissatisfied
Neither Satisfied or Dissatisfied
Somewhat Satisfied
Extremely Satisfied
7.87%
29.21%
17.98%
39.33%
5.62%
7
26
16
35
5
Technological resources
Extremely Dissatisfied
Somewhat Dissatisfied
Neither Satisfied or Dissatisfied
Somewhat Satisfied
Extremely Satisfied
2.25%
22.47%
20.22%
34.83%
20.22%
2
20
18
31
18
Policy support
Extremely Dissatisfied
Somewhat Dissatisfied
Neither Satisfied or Dissatisfied
Somewhat Satisfied
Extremely Satisfied
4.49%
14.61%
21.35%
43.82%
15.73%
4
13
19
39
14

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Interview findings supported the survey results and suggested that underwhelming
institutional support in these areas was due to prevailing policies and procedures. Two resources
interviewees were least satisfied with were financial and human. Participant 6, a graduate school
Dean, attributed their financial challenges to the institution’s revenue model for funding graduate
programs. They said, “the way my institution works is to show me you are bringing the revenue
and show me an onslaught of students, and then I'll get you the support.” This lack of financial
support proved to be initially challenging during scaling. They added, “since we were doing
everything in-house, our goals were very modest, to begin with, but I also needed to hire more
instructional designers. I had to move funds from other areas to make this happen.” Participant 4,
another graduate school Dean, attributed their institution’s budget model for the lack of
collaboration between stakeholders in various graduate programs and within the institution. They
said, “our budget-driven concerns continue to prevent sharing of resources, whether market
research, best practices, or even staff.” They added, “we are not nimble enough to respond to the
new learning environment,” and “I wish we could work more closely with one another.”
Importance of Scaling Online Graduate Programs Weakened by Inadequate Communication
Survey participants were asked whether institutional leadership regularly communicates
the importance of scaling online graduate programs. Respondents were roughly split in their
answers. Out of 93 total responses, 57% (n = 53) said that leadership regularly communicates the
importance of scaling, while 43% (n = 40) disagreed. The inferential analysis revealed no
statistically significant relationships in perceived adequacy of such communication based on
respondents’ selected sourcing strategy, the Carnegie classification of their institution, their role,
or their graduate school's academic discipline. Emails, town halls, and annual meetings were
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identified as the most common communication modes by respondents who believed there was
adequate communication from institutional leadership (Table 19).

Table 19
Survey Results for Institutional Leadership Communicating Importance of Scaling (N=144)
Communication mode Results
Percent Count
Emails 27.78% 40
Annual Meetings 22.92% 33
Town halls 22.22% 32
Newsletters 11.81% 17
Other (please explain) 9.72% 14
Social Media 5.56% 8
Note. Common answers to “other” were Board of Trustees meeting, leadership meetings, and
cabinet councils, indicating that communication took place in group meetings.

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Interviewees were less than satisfied with their leadership’s communication about the
importance of scaling their online graduate programs. They also thought that leadership took a
passive role and attributed it to the general lack of attention to support graduate programs.
Participant 8 said, “graduate programs are mostly an afterthought because we are just 20% of the
overall student population.” Participant 1 echoed the same sentiment by saying, “we are growing
graduate programs, but at the moment, the focus is squarely on undergraduate.” They added that
“emails from the President and Provost never account for our graduate students.” This feedback
was consistent among most participants. Interviewees said that this lack of communication made
it challenging for them to obtain support at various stages. Participant 8 experienced a delay in
selecting an external partner and said, “I couldn’t get our finance and legal departments to review
OPM contracts as quickly as I hoped.” Participant 1 reported experiencing significant challenges
onboarding their new students, saying, “our student services units treated online students as if
they were on campus. It's like they had no clue what the difference was.”
More than half of the interviewees expressed optimism for improved communication in
the future. Participant 12 said, “I think we are at the point where graduate programs cannot be
ignored by leadership.” The COVID19 pandemic, according to them, “has put a spotlight on
growing our graduate programs and especially online.” They concluded by saying, “I see a
change already, and I believe the President is going to be more vocal about growing graduate
programs.” Participant 2, who discussed nearly doubling their institution’s online graduate
enrollment in just two years, believed their leaders would take a more active role in future
communications. They said, “our recent success has our Provost excited. He has been sharing the
results with the entire university community and wants to open more doors.” Similarly, other
interviewees expected their leaders to become more active in promoting scaling initiatives
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throughout the institution. Consistent with survey responses, interview findings indicated emails
and annual meetings as the most common communication modes.
Institutional Culture as a Significant Scaling Barrier
Respondents overwhelmingly indicated that their institutional culture played a critical
role in selecting the sourcing strategy. Ninety-eight percent (n = 87) of respondents said
institutional culture either “strongly influenced,” “moderately influenced,” or “somewhat
influenced” their source selection, while only 2.25% (n = 2) indicated no influence in source
selection (Table 20). The inferential analysis revealed no statistically significant relationships in
institutional culture's impact as a scaling barrier based on respondents’ selected sourcing
strategy, the Carnegie classification of their institution, their role, or their graduate school's
academic discipline.

Table 20
Survey Results for Influence of Culture in Source Selection (N=89)
Please rate the degree to which
institutional culture will (or has)
influence(d) your selection of
insourcing or outsourcing
scaling of online graduate
programs.
Results

Percentage Frequency
Not at all Influenced
Somewhat Influenced
Moderately Influenced
Strongly Influenced
2.25%
20.22%
32.58%
44.94%
2
18
29
40

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Two common cultural barriers emerged from interview findings: faculty resistance to
online teaching and institutional perception of expanding online learning as contradicting
institutional mission and values. Interviewees unanimously identified resistance to online
teaching from some faculty as the most significant cultural barrier in selecting and implementing
their scaling strategy. Insourcing interviewees indicated spending most of their time persuading
faculty to embrace online teaching. While describing some tenured faculty members’
dispositions to launching new online programs, Participant 1 said, “we have some programs with
powerful entrenched faculty saying there is no way in hell that I will teach online.” Participant 7
said, “what’s ironic is that some of our business faculty were most opposed to going online.”
Participant 10 said, “I would get laughed at in faculty meetings every time I brought up going
online.” Participant 12 described the process of convincing faculty as “long and draining” and
added that “I went to every faculty senate meeting for about a year and presented data and
market research about the online opportunity.” Some interviewees indicated that the resistance
eventually faded. Participant 2 credited their successful scaling efforts for this and said, “seeing
our incredible enrollment calmed many faculty members.”
Similarly, Participant 10 noted that three years into steady online growth, their faculty
“finally see the opportunity for us to have a bigger footprint and reach new students.”
Participants also indicated that the COVID-19 pandemic and the resulting switch to fully online
teaching had also helped lessen the opposition to online programs. Participant 10 alluded to some
faculty developing a liking for online teaching by saying, “COVID pushed them to learn how to
teach remotely, but a few months in, I have heard some they that kind of like it.” They added that
this enthusiasm was also evident in their “packed weekly Zoom training sessions” that their
faculty received well.
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Some interviewees identified institutional perception against starting or growing online
graduate programs as a cultural barrier. Three participants representing faith-based institutions
indicated that they experienced resistance from institutional leaders who generally felt that online
learning directly opposed the institution’s mission. Participant 5 said, “I was reminded several
times that online classes were diluting our institutional mission. Many in the President’s cabinet
wanted to stay on-campus only.” Similarly, Participant 12 expressed meeting resistance with
several high-level institutional leaders who characterized online learning as “not our way of
doing things.” One outsourcing interviewee, Participant 5, experienced resistance to partnering
with an OPM. They said, “many people felt and still feel that partnering with a profit-driven
entity runs against identity.” Interviewees also stressed that this negative perception is still
prevalent among several skeptical stakeholders. On the other hand, some interviewees felt that
the complete switch to online teaching in response to the COVID-19 pandemic might have led
some institutional stakeholders to soften their stance against having online graduate programs.
Participant 5 said, “our graduate programs did pretty good going fully online in the fall. That has
definitely raised some eyebrows in leadership.” They added, “The Provost has already asked me
to put together a plan and see which programs can have a 100% online track.” This general sense
of optimism was echoed by other interviewees who felt that the pandemic had created an
opportunity to overcome the cultural barriers hindering online graduate programs' growth.
Additional Findings
In addition to exploring institutional influences impacting OPL decision-making for
selecting sourcing strategy, three notable themes emerged. The first finding suggests that the
selected sourcing strategy resulted in minimal structural changes to the apparatus supporting
online graduate programs. Secondly, student enrollment goals are linked directly to the selected
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sourcing strategy. Finally, OPLs provided various institutional considerations to support the
source selection process and strategy implementation adequately.
Minimal Structural Impact of Selected Sourcing Strategy
While describing the role their knowledge of institutional structure played in source
selection, interviewees indicated that their selected strategy had minimal impact on the
prevailing structure. Participant 3 said, “we have done a good job of growing by staying lean and
collaborating across various departments” and projected no imminent structural changes by
saying, “I don’t think that changes unless we decide to get more aggressive this year.” However,
they anticipate steadily increasing current instructional design and student support staffing.
Similarly, outsourcing interviewees also indicated their existing structure would remain
unchanged for the foreseeable future. Content with their OPM partnership, Participant 7 said that
“we have a perfect relationship with our partner. We take care of what happens in class, and they
take care of everything else”. They added that “I don’t see us making any changes for the next
few years.”
While most interviewees anticipated no significant structural changes soon, a notable
exception came from one interviewee currently using both strategies. Participant 11 expects to
insource scaling and soon fully support their online graduate programs without an external
partner. They said, “we have slowly been preparing to bring everything in-house,” referring to
building an internal marketing and recruitment team dedicated to scaling online graduate
programs. Elaborating on this transition’s status, they said that the team has “been learning from
our vendor” and “I am adding more programs to their portfolio with every new admission cycle.”
They anticipate completing this transition in the next few months. Even when their institution
becomes fully capable of insourcing, Participant 11 believes that they will continue the current
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partnership in a limited way, primarily for “ongoing technology assessment and new program
market analysis.”
Student Enrollment Goals Driven by Selected Sourcing Strategy
Interview findings suggest that student enrollment goals are directly related to the chosen
sourcing strategy. Insourcing interviewees indicated having low or modest expectations about the
pace of scaling their online graduate programs, while outsourcing interviewees indicated having
more aggressive growth objectives. Participant 3, an insourcing interviewee, said that “I have no
pressure to grow these programs fast.” Similarly, Participant 4 indicated having modest growth
expectations and said, “we decided to keep things in-house knowing full well that it would take
time.” Participant 2 indicated tying enrollment expectations to resource availability. They said,
“the Provost has my plan, and I have detailed what it would take to expand enrollment. If they
are willing to invest, we can grow faster.” Insourcing interviewees generally communicated an
expectation of slow and steady scaling of their online graduate programs.
Outsourcing interviewees indicated having considerably higher expectations for student
enrollment because of partnering with an OPM. Participant 7 attributed their shared revenue
agreement with the OPM as the main reason for this expectation. They said, “the OPM gets half
our tuition revenue, so we have to get twice as many students to make our budget goal.” Other
interviewees with similar revenue-sharing agreements indicated having higher enrollment goals
to offset the unrealized revenue gap. Another reason for high enrollment expectations, according
to Participant 5, was leadership’s vision and desire for immense growth. They revealed that their
new President, fueled by recent scaling success, has set their sight on becoming a top-five, by
volume, institution. The President “wants us to be the (faith-based) version of Sunshine State
University (pseudonym),” referring to a highly prominent university with one of the largest
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online graduate student body. In partnership with the OPM, they plan to accelerate enrollment
growth by launching at least five new graduate programs in the next year and doubling out-of-
state online graduate student recruitment.
Institutional Considerations for Supporting Scaling Initiatives
Interviewees were asked to suggest steps an institution could take to support their OPLs
to ensure the right strategy has been selected and implemented. A common theme that emerged
from the answers to this question was that institutional leadership needs to be firmly supportive
of their OPLs. Participant 5 characterized this support by saying, “I think supporting that leader
who is assessing if they're going to do this in a partnership or internally and helping them lead
that exploration is a must.” Elaborating on their own experience, they said, “I felt reassured by
my bosses that I had their support knowing full well that there would be some mistakes initially.”
Similarly, Participant 5 said that institutions new to starting online graduate programs should
consider “hiring a person specifically to focus on everything it takes to assess the landscape,
figure out what is needed to scale, and bring everyone together.” They added that “my position
was created to help all graduate programs and particularly, online. I am glad I get to be the one
voice for all our campus partners and our vendors.”
Interviewees also provided various suggestions for institutional consideration. Strategic
considerations included establishing a clear strategic direction for scaling, innovating graduate
education management, and cultivating a collaborative environment among all graduate
programs. Notably, the importance of establishing a strategic plan for scaling online graduate
programs was confirmed by survey findings from 93 respondents. Including scaling online
graduate programs in institutional strategic plans was important, according to 85.04% (n = 79) of
respondents. Similarly, 79.57% (n = 74) of respondents felt it was important to include scaling in
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graduate colleges’ strategic plans and 80.64% (n = 75) in individual graduate programs’ strategic
plans. Two tactical considerations, revising the graduate program operational budget model and
consistent communication, emerged from the findings. These considerations are outlined in
Table 21.

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Table 21
Institutional Considerations for Supporting OPLs
Consideration Related finding
Establish a strategic goal for
scaling online graduate
programs.
Participant 3 said, “I think we have to have a strategic
direction from the top of the university, and it comes from
the decision-making level.”

Participant 9 said, “having clear expectations from the top
down in terms of the charge of the university, and the move
to online and the importance it has and folds into the
strategic plan is very important.”
Take an innovative approach
to manage all graduate
education.
Participant 3 said, “be more entrepreneurial, think about
more interesting ways to give flexibility and innovation to
graduate students and faculty.”

Participant 11 said, “encourage individual entrepreneurial
and competitive individual intellect. Ask them to share
what's working, what's not working, and find organic
solutions.”
Cultivate a collaborative
ecosystem.
Participant 4 said, “we have to find ways to work together as
a university and collaborate to leverage our talent.”
Revise the graduate program
operations budget.
Participant 4 said, “figure out a finance model on the back
end that doesn’t stop innovation for graduate programs.”

Participant 6 said, “there needs to be financial incentive for
growing programs. The university has to afford us the
opportunity to use additional revenues instead of putting it in
reserves.”
Communicate consistently and
transparently.
Participant 7 said, “leadership needs to work on
communication with the broader faculty group and be
transparent about their intentions.”

Participant 11 said, “transparency, like open institutional
communication and ability to speak truth, like those are
things where there's a lot of organizational cultural stuff that
can be done.”

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Findings from Document Analysis
The researcher aimed to analyze two types of documents to examine OPLs’ knowledge
influences impacting their souring selection process. The first document, OPL training materials,
was intended to explore OPLs’ process to assess institutional resources, structure, and capability
for scaling online graduate programs. Some interviewees mentioned using resource planning
systems and related tools to determine resource availability and structural readiness. However,
interviewees declined to share any related documents due to their proprietary nature. Some
interviewees referenced using various tools for assessing pedagogical capability. For example,
several participants referenced using rubrics and training certification from Quality Matters, a
nationally recognized online learning association. Improving the quality of online instruction and
providing professional development opportunities was identified as these tools' purpose. Since
these tools serve a purpose outside the scope of analysis in this study, no documents were
requested. Document analysis related to OPL knowledge influences could not be performed due
to a lack of access to relevant OPL training materials.
The second set of documents, institutional and graduate school strategic plans, were
analyzed to explore the impact of institutional influence on OPLs’ sourcing strategy selection.
Specifically, these documents were reviewed to determine whether scaling online graduate
programs were included in the strategic plan, and if so, what was the highest-level priority
assigned to it. A total of 12 institutional strategic plans representing each of the interviewees
were collected from the institutions’ websites. Further, four out of six possible graduate school
strategic plans were also collected from the colleges’ websites. All institutional plans utilized a
five-year timeline, while graduate school strategic plans typically followed a three-year timeline.
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At the time of this analysis, most strategic plans were nearing completion of their five- or three-
year timeline.
Only six of the 12 strategic plans analyzed made some reference to scaling online
graduate programs. The analysis also revealed significant variance in the level of importance
assigned to scaling. Table 22 provides a detailed listing of the six institutional strategic plans
analyzed. One institution appeared to identify scaling its online graduate programs as a subset of
one of its highest strategic goals. The institution aimed to create a central unit focused on
developing and supporting all online programs. Two institutions made direct reference to
growing their online graduate programs as a second-level initiative. Finally, three institutions
referenced growing their online graduate programs as a third-level tactic. Only Institution 5
provided a specific action by indicating their plan to launch a new nursing graduate program in
online and on-campus modalities. However, none of the other strategic plans offered any specific
information, such as a timeline or a specific number of graduate programs under consideration
for scaling.
Analysis of all the four graduate school strategic plans revealed no reference to scaling
their online graduate programs. Just one strategic plan referred to growing out-of-state graduate
student enrollment. However, there was no further information. Consequently, it is unclear
whether such growth is expected to increase student capacity in existing online graduate
programs or expand recruitment efforts to bring out-of-state students to on-campus programs.
The analysis of institutional and graduate school strategic plans revealed that scaling online
graduate programs is generally not a stated priority for most institutions. The analysis confirmed
one of the institutional influences result and finding related to inadequate communication from
institutional leadership about scaling urgency. It also reaffirmed a common institutional
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consideration suggested by several OPLs, namely establishing a clear strategic direction for
scaling online graduate programs.

Table 22
Institutional Strategic Plans for Scaling Online Graduate Programs
Institution Highest level of
strategic plan
Relevant text
Institution 1 Strategic Plan Goal Establish a new centralized entrepreneurially
focused unit to develop a “virtual” university
that responds to market demands for fully
online programs.
Institution 2 Initiative for Strategic
Goal
Develop a coherent overall portfolio of
selected research-degree master’s programs,
interdisciplinary graduate/professional
offerings, and market-distinctive graduate
online/hybrid programs, and establish
appropriate infrastructure to support academic
quality for the new portfolio of programs.
Institution 3 Initiative for Strategic
Goal
We will address these challenges by expanding
all learning options, including online and
hybrid learning.
Institution 4 Tactic for Initiative Develop, offer, and promote innovative
undergraduate and graduate online programs.
Institution 5 Tactic for Initiative Launch a Doctorate of Nursing Practice online
and residential degree.
Institution 6 Tactic for Initiative Transform Online and Hybrid graduate
education.

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Summary of Results and Findings
The data analysis focused on exploring knowledge and institutional influences impacting
Online Program Leaders (OPLs) in selecting a sourcing strategy for scaling online graduate
programs. The analysis revealed that OPLs are highly knowledgeable about three critical
institutional elements: resources, structure, and capability. The analysis also revealed that, with
few exceptions, there are no statistically significant differences in OPL knowledge based on their
selected sourcing strategy, their role, their institution’s Carnegie classification, or their graduate
academic discipline. The exceptions were institutional capability factors, where central OPLs
indicated being more familiar with staff technology expertise and student support systems than
their graduate school counterparts.
OPLs’ knowledge of institutional resources and capability is highly impactful in their
final selection of a sourcing strategy, but institutional structure knowledge is relatively less
impactful. OPLs identified funding as the most critical scaling resource and indicated utilizing
various internal and external entities to assess scaling capability. The analysis also revealed two
additional findings. OPLs indicated feeling highly confident of the process utilized for selecting
the appropriate sourcing strategy. They also indicated that being aware of institutional context is
essential to overcome challenges.
The analysis demonstrated that institutional procedures and policies are unconducive to
scaling. They indicated that while institutional leadership considers scaling online graduate
programs a top priority, they do not communicate consistently and with the appropriate sense of
urgency. Institutional culture, predisposed to perceiving online learning as inferior and counter-
mission, was a significant barrier for scaling online graduate programs. The analysis also
revealed three additional findings related to institutional influences. OPLs indicated that their
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selected strategy had minimal impact on the structure supporting online graduate programs. They
also revealed sourcing strategy as a driver of student enrollment goals. It was outsourcing the
scaling of online graduate programs that led to higher enrollment goals, whereas insourcing
resulted in low or modest enrollment expectations. Finally, OPLs provided various institutional
considerations to support the source strategy selection and its implementation.

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Chapter Five: Recommendations and Discussion
This field study focused on identifying and exploring Online Program Leaders’ (OPLs’)
knowledge and institutional influences impacting selecting a sourcing strategy to scale online
graduate programs. Chapter 1 introduced the problem of a lack of adequate research related to
scaling online graduate programs. Chapter 1 also introduced the stakeholders and institutions
identified for this study and the Clark and Estes (2008) gap analytic conceptual framework.
Chapter 2 outlined a literature review of common scaling barriers, considerations for insourcing
and outsourcing scaling, and considerations for a partnership with an Online Program Manager
(OPM). The gap analytic framework (Clark & Estes, 2008) was used to identify three knowledge
and three institutional influences for data collection and analysis. In Chapter 3, the methodology,
design, instrumentation of this mixed-methods sequential exploratory study were presented. In
Chapter 4, the analysis from triangulated data collected through surveys, interviews, and
document analysis was presented. This final chapter, Chapter 5, discusses the results and
findings in the context of the literature reviewed for this study. The data analyzed are reviewed
through the lens of the three knowledge and three influences identified earlier. This discussion is
followed by three general recommendations for practice that OPLs and institutional leadership
can utilize once a decision to scale online graduate programs has been made. The chapter closes
with a discussion of the limitations and delimitations, followed by recommendations for future
research.
Discussion of Findings and Results
In this section, the data analyzed is discussed in the context of the knowledge and
institutional influences identified. The section begins with a discussion of results and findings
related to the three knowledge influences: OPL knowledge of resource implications for scaling,
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OPL knowledge of structural implications for scaling, and OPL knowledge of institutional
capacity for scaling. These are followed by a discussion of the three institutional influences:
Institutional leadership’s prioritization of the scaling of online graduate programs, institutional
leadership’s ability to provide resource and structural support in implementing the selected
sourcing strategy, and institutional leadership’s consistent emphasis of the importance of scaling
online graduate programs.
Knowledge Influences
The knowledge influences identified for this study focused on OPL knowledge of
institutional resources, structure, and capability of scaling online graduate programs. OPLs’
knowledge of resources such as funding, staffing, and technology was assumed to be impactful
in selecting whether to insource, outsource, or use a combination of both strategies for scaling.
Similarly, OPLs’ ability to identify existing gaps in each of these resources was assumed to be
crucial to informing their selection. Survey results and interview findings confirmed the critical
role of such knowledge. Survey and interview participants suggested that they possess extensive
knowledge of their institutional resources. Obtaining funding was identified as being most
critical for scaling. Finally, OPL knowledge of institutional resources played a significant role in
sourcing strategy selection. Notably, the decision to outsource scaling and partner with an Online
Program Manager (OPM) was driven by the lack of resources to conduct adequate marketing and
student recruitment. The results and findings suggest that to successfully scale their online
graduate programs, OPLs need to sufficiently identify institutional resource gaps before
determining the best sourcing strategy to fill these gaps.
OPL knowledge of prevailing institutional structure was also assumed to play an essential
role in scaling online graduate programs' objectives. The role of shared governance and its
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resulting impact on the collective use of institutional resources and capability were understood to
impact source selection. The data collected through surveys and interviewees indicate that OPLs
are highly familiar with the prevailing institutional structure. Participants outlined the process
used to build consensus for scaling a program or a set of programs and detailed how
disagreements about whether to scale a particular program are managed. Structural challenges
related to program approval policy and institutional communication were also highlighted.
Finally, survey respondents and interviewees indicated that the prevailing institutional structure
only somewhat influenced the source selection strategy. These results and findings suggest that
OPL knowledge of structural implications for scaling online graduate programs is essential.
OPLs seeking to make a scaling decision should consider the potential impact of the processes
and policies driven by their institution’s governance structure when making a scaling decision
and anticipate their impact on the implementation process.
OPLs’ knowledge of institutional capability for scaling online graduate programs was
another influence assumed to impact their source selection. OPLs’ ability to understand
institutional objectives for scaling, analyze the current level of technological expertise, and
assess student and faculty support systems' state was assumed to be critical factors for source
selection. The results and findings revealed that OPLs possess an in-depth understanding of
institutional capability for scaling. OPLs in centralized roles reported having a higher level of
familiarity with student support systems and staff technological expertise than their graduate
school counterparts. The results and findings also point to OPLs’ knowledge of capability factors
playing a critical role in influencing their decision to select whether to insource, outsource, or
use a combination of the two strategies for scaling. Finally, findings also suggest OPLs relying
on various internal and external entities to evaluate their institutional capability for scaling.
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Two additional findings related to OPL knowledge influences were discovered during the
data collection process. The first finding indicated that interviewees were highly confident in the
source selection process. They indicated being satisfied with their ability to evaluate institutional
resources and capabilities and consider the role institutional structure played in their decision-
making. This suggests that OPLs at institutions evaluating sourcing alternatives for scaling
should be knowledgeable in evaluating gaps in resources and capabilities. For example, OPLs
should be aware of the level of access they can have to instructional designers and subject matter
experts. The second finding illustrated the critical role institutional awareness played in
overcoming scaling challenges. Interviewees highlighted the need for possessing an
understanding of the overall institutional context of the scaling initiative. This suggests that
OPLs seeking to scale their online graduate programs should prepare to navigate challenges
posed by unknown institutional factors such as policies and procedures that could hinder their
scaling objectives. One such factor is accreditation, and OPLs should account for the time,
resource investments, and additional steps involved in obtaining accreditation for one or more
online graduate programs concurrently.
A notable consideration in the discussion of OPL knowledge findings and results is
related to the lack of assessment of such knowledge. The data collection scope was limited to
respondent and interviewee self-reported estimate of their knowledge and its impact in their
selection process. As such, there was no assessment conducted to test their level of such
knowledge and its utilization. For example, survey respondents were asked to rate their level of
familiarity with institutional funding for scaling and provide additional perspective during their
interview. However, they were not assessed in any formal and objective manner, such as via a
test, to validate the self-reported level of familiarity with institutional funding. It is possible that
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respondents and interviewees might have misjudged or misrepresented their actual level of
familiarity with institutional funding.
The results and findings of knowledge influences discussed here suggest that OPLs at
institutions considering scaling should know the resources, structure, and capability. Their
knowledge of these factors can facilitate gap analysis and influence the selection of an
appropriate scaling strategy. Such knowledge can also be valuable once a sourcing strategy has
been selected for implementation. Table 23 summarizes the assumed knowledge influences and
their related results and findings.

Table 23
Summary of Knowledge Influences and Related Results and Findings
Assumed knowledge
influence
Related results and findings
OPL knowledge of
resource implications of
scaling decisions.
OPLs have extensive knowledge of institutional resources.

OPLs identified funding as the most critical scaling resource.

OPLs’ source selection is highly influenced by knowledge of
resources.
OPL knowledge of
structural implications
of scaling decisions.
OPLs are highly familiar with the prevailing institutional structure.

OPLs’ source selection is somewhat influenced by knowledge of
structure.
OPL knowledge of
institutional capability
for scaling.
OPL’s have an in-depth understanding of institutional capability.

OPLs source selection is highly influenced by their understanding of
capability.

OPLs identified various entities involved in the assessment of
institutional capability.
Additional Findings
OPLs were highly confident in their source selection process.

OPLs identified institutional awareness as critical for overcoming
scaling challenges.

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Institutional Influences
This study's institutional influences focused on institutional support for OPLs in their
source selection process and implementation. The role of institutional leadership, such as the
President, Provost, Board of Trustees, and cabinet members with final decision-making
authority, was the focus. Three institutional influences were identified. The first influence
pertains to the impact of institutional leadership prioritizing scaling online graduate programs.
The second influence focused on the need for institutional leadership to provide resource and
structural support for scaling. The third influence emphasized the role of effective
communication for scaling online graduate programs successfully. The findings and results
suggest that, besides approving a sourcing strategy, institutional leadership can play an active
role in supporting OPLs in scaling strategy selection and implementation.
The literature review revealed that prioritizing online graduate programs' scaling can
influence institutional culture and encourage all stakeholders to support OPLs in source selection
and successfully implementing the scaling strategy. Results and findings suggest that
institutional culture is a significant barrier to scaling online graduate programs. Faculty
resistance to online teaching and institutional perception of expanding online learning
contradicting mission and values emerged as two examples of cultural barriers. Findings suggest
that institutional leadership can help overcome cultural barriers by clearly articulating their
support for scaling online graduate programs in institutional strategic plans. Such articulation,
findings suggest, can help align scaling vision with institutional mission and allow appropriate
resource allocation.
Institutional leadership’s support for OPLs in the form of availability of resources and a
supportive structure was also assumed to implement the selected sourcing strategy successfully.
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As discussed earlier, funding was identified as the most critical resource for scaling, and OPLs’
knowledge of existing gaps in institutional resources played a critical role in their source
selection and implementation. Findings and results also suggest that institutional structure often
posed challenges in the implementation of the scaling strategy. Respondents highlighted
procedures and policies, such as the new program approval policy and the graduate program
budget model, as being inconducive for scaling. Only about half of the survey respondents
indicated being sufficiently satisfied with the level of financial, human, and technological
resources and policy support for scaling. Similarly, interviewees outlined their frustrations with
the lack of support at various stages of the decision-making and implementation process. The
findings and results suggest that institutional leadership can better support OPLs by providing
adequate resources and creating supportive policies and scaling procedures.
This study's final institutional influence focused on the impact of institution-wide
communication of the importance of scaling online graduate programs. The literature review
revealed that institutional leadership’s clear and consistent communication to all institutional
stakeholders about the purpose of scaling online graduate programs and the process employed to
make a source selection could build trust. Furthermore, soliciting input from the institutional
community through formal and informal means could help make institutional culture more
conducive to scaling. The results and findings suggest that while leadership considered scaling
online graduate programs as an institutional priority, their communication often fell short of
OPLs’ expectations. Over 40% of survey respondents indicated that institutional leadership’s
communication was less than satisfactory. Findings suggest a common reason for this was due to
the prioritization of undergraduate education over graduate education. However, looking ahead,
participants expressed some optimism for graduate programs receiving more attention from
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institutional leadership. They credited the general success and growth in graduate enrollment
during the switch to fully online classes in response to the COVID19 pandemic.
Two additional findings related to institutional influences emerged during the data
collection process. The first finding pertains to the impact of the scaling decision on the
prevailing institutional structure. The results and findings indicated that the prevailing
institutional structure supporting online graduate programs had remained mostly unchanged.
With one notable exception, most institutions had not changed or made plans to change the
structure despite the prospect of serving a significant number of online graduate students. The
exception was at an institution currently shifting from outsourcing to insourcing their online
graduate programs. The interviewee indicated that they anticipated upcoming changes in
management structure and the addition of support staff. This finding suggests that if leadership at
currently outsourcing institutions are considering a shift to insourcing, they should consider
planning for possible changes to the current structures supporting online graduate programs and
be prepared to make additional investments. The second additional finding pertains to the impact
of sourcing strategy on student enrollment goals. The results and findings indicated that
outsourcing institutions generally had loftier enrollment goals compared to insourcing
institutions. For example, insourcing institutions appeared to have modest expectations for
enrollment growth in the short-term, whereas outsourcing institutions appeared to be looking for
rapid enrollment growth. Accordingly, leadership at institutions yet to select a sourcing strategy
might factor desired enrollment outcomes into the decision-making process for selecting the
appropriate sourcing strategy.
The literature reviewed earlier in this study indicated that, thus far, some online graduate
programs have grown due to individual campus units' efforts, such as faculty and staff within a
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particular graduate program (Morgan, 2019). Consequently, some challenges such as duplication
of learning services and cost inefficiencies have occurred (Morgan, 2019). The results and
findings affirmed these challenges and pointed to a need for active leadership involvement in the
scaling process. Respondents and participants felt institutional leaders needed to make
institutional resources and capabilities more accessible and negate cultural obstacles for scaling
online graduate programs by prioritizing scaling and consistent institution-wide communication.
Therefore, institutional leaders have an opportunity to participate in the scaling process and
consider their role to be greater than being final decision-makers in the selection process.
Institutional leaders can influence institutional culture, build support for scaling throughout the
institution, and help create an environment more conducive to implementing the selected scaling
strategy. Table 24 summarizes the assumed institutional influences and their related results and
findings.

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Table 24
Summary of Institutional Influences and Related Results and Findings
Assumed institutional influences Related results and findings
Institutional leadership needs to prioritize
the scaling of online graduate programs.
Institutional Culture is a Significant Scaling
Barrier

Institutional Considerations for Supporting Scaling
Initiatives
Institutional leadership needs to provide
resource and structural support in
implementing the selected sourcing
strategy.
Institutional Procedures and Policies as
Unconducive for Scaling
Institutional leadership needs to regularly
emphasize the importance of scaling online
graduate programs to ensure graduate
programs are sustainable.
Importance of Scaling Online Graduate Programs
Weakened by Inadequate Communication
Additional Findings
Minimal Structural Impact of Selected Sourcing
Strategy

Student Enrollment Goals Driven by Selected
Sourcing Strategy

Recommendations for Practice
This study focused on exploring Online Program Leaders’ (OPLs’) knowledge and
institutional influences that impact selecting a sourcing strategy for scaling online graduate
programs. The recommendations for enhancing OPL knowledge and institutional support for
selecting a sourcing strategy and supporting its implementation have two critical considerations.
First, the recommendations provided here are general and would need to be adapted to suit every
institution’s unique characteristics and circumstances. This study focused on OPLs from 567
private non-profit institutions, but the data collected lacks the level of homogeneity that warrants
specific recommendations. For example, the institutions represented by the 12 OPL interviewees
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had varying levels of experience with online learning. Some institutions appeared to have an
extensive history of offering various online learning programs and consequently had in-built
capabilities for scaling online graduate programs. Their OPLs also appeared to be able to
anticipate better and resolve institutional, cultural challenges. On the other hand, some
institutions had only recently committed to offering online degrees and programs, and their OPLs
appeared to possess a relatively lesser understanding of the cultural barriers. Given the broad
spectrum of engagement with online learning, offering general recommendations seemed most
appropriate.
The second consideration is related to the scope of this study. As discussed earlier, this
study focused on institutions desiring to scale their online graduate programs. The researcher has
acknowledged that scaling may not be in every graduate program or institution's best interest.
The researcher also recognizes that scaling online graduate programs may contradict certain
institutions' mission and objectives. As such, the researcher does not intend to promote scaling
online graduate programs at institutions that deem it unfeasible or undesirable. Instead, the
recommendations provided here are intended to serve as a starting point for OPLs and
institutional leaders planning to scale online graduate programs only after the decision to pursue
such an initiative is made. This section presents three recommendations for OPLs and their
institutional leaders.
Ensuring High Level of OPL Knowledge of Resources, Capacity, and Structure
The results and findings revealed the importance of OPL knowledge of their institutional
resources, capacity, and structure in selecting the appropriate scaling strategy. For OPLs to
decide whether to outsource, insource, or use a combination of the two strategies, they need to
identify existing gaps in institutional resources and capacity. Knowing resource and capability
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gaps allows OPLs to determine whether the institution will afford sustained investments in
building the operational framework needed to support a higher online graduate student
population (Amirault, 2012; Hoffman, 2012; Morgan, 2019). It is also essential for them to
understand how best to leverage the institutional share governance system to gain support from
all stakeholders (Nworie, 2012). Therefore, it is recommended that OPLs ensure they acquire and
maintain a high level of knowledge of the resources and capability available for scaling online
graduate programs and an in-depth understanding of the institutional structure that will support
such efforts.
The OPL stakeholder group for this study consisted of individuals holding various formal
roles. Very few of them are solely responsible for facilitating the development and scaling of
online graduate programs. Most of them have roles that consist of various responsibilities, and
managing online graduate programs is one of many such responsibilities. For example, most
Academic Deans oversee all programs in their academic discipline, including online graduate
programs. They may not possess enough related expertise and relevant experience to analyze
resource availability and scaling capacity thoroughly. OPLs should consider using a diagnostic
model to assist with such analysis. In this context, Piña’s (2017) diagnostic model, which
involves diagnosing inputs such as human capital, finance, and technology, could help some
OPLs. Alternatively, as Dechant and Dechant (2010) proposed, a systems-based model could be
used to analyze and align several institutional dimensions, including resources and structure.
Similarly, if a critical consideration of scaling includes benchmarking, OPLs should consider
using the Quality Scorecard for Administration of Online Programs (Online Learning
Consortium, 2019).
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Establishing a Strategic Vision for Scaling Online Graduate Programs
The results and findings revealed the need for institutional leadership to establish a clear
strategic direction and objectives for scaling online graduate programs. Most respondents
indicated that including online graduate programs in the institutional strategic plan is essential to
selecting a scaling alternative and implementing it. To a lesser degree, respondents also felt it
would help include online graduate programs in graduate colleges’ strategic plans and individual
graduate program’s strategic plans. Clark and Estes (2008) posited that having a clear vision,
goals, and ways to measure progress are vital elements for success for an initiative. Establishing
a strategic direction for scaling online graduate programs could help institutions align such
objectives with the overall institutional mission, inform resource allocation priorities, and
support such programs' long-term sustainability (Piña et al., 2017; Rovai & Downey, 2010).
Therefore, it is recommended that institutional leadership create a strategic vision for online
graduate programs and make them an integral part of the institutional strategic plan.
Institutional leadership can instigate creating a strategic vision through a collaborative
effort between various institutional graduate education stakeholders. They could adapt the
methods generally used in institutional strategic planning. Hill et al. (2009) proposed a
collaborative strategic planning framework that can be adapted. The framework outlines various
steps in five major phases, including building a planning committee, gathering information,
creating a communication plan, and developing the process (Hill et al., 2009). The second phase
involves gathering input from various campus units and creating a preliminary report, followed
by the third phase of holding smaller listening sessions with leadership units for additional
feedback (Hill et al., 2009). Following data gathering and analysis, the fourth phase consists of
proposing a finalized plan for approval (Hill et al., 2009). The fifth and final phase consists of
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implementing the plan, including sharing the plan with all stakeholders and developing metrics
to measure performance (Hill et al., 2009). If adopted, this model could allow the institution to
engage in a comprehensive and collaborative effort to build a sustainable strategic plan for
scaling online graduate programs. It could also signal the importance of scaling online graduate
programs to the entire institution and serve as a resource and capacity allocation guide.
Leveraging Institutional Culture to Overcome Scaling Obstacles
The study results indicate that OPLs viewed existing institutional culture as a barrier to
successful scaling online of graduate programs. One of the common barriers outlined was the
generally negative perception of expanding graduate online earning among many stakeholders.
Some respondents indicated that institutional stakeholders view scaling online graduate programs
as directly opposed to institutional missions and values. However, this perception appears to be
shifting, and the impact of the COVID19 pandemic has eased many stakeholders’ concerns about
online learning in graduate programs. Furthermore, findings suggest that institutional leaders
appear to favor expanding online graduate learning due to its financial and strategic advantages.
Given the appearance of a natural point of inflection in online graduate education for some
institutions, it is recommended that institutional culture be leveraged to overcome known barriers
for scaling online graduate programs.
Institutional leadership and Online Program Leaders (OPLs) can collectively leverage the
existing conditions to influence institutional culture to support scaling online graduate programs.
Kezar (2001) proposed various research-based principles of change that could create a sense of
urgency and focus on scaling. The principles outlined are based on a study of various higher
education change models (Kezar, 2001). In this context, three principles are recommended:
laying the groundwork, communicating informally, and relying on the shared governance
110

structure. Institutional leadership and OPLs could begin by laying the groundwork with the
institutional community through a self-assessment that asks “what,” “how,” and “why” questions
(Kezar, 2001). In this context, answers to some questions might be readily available as most
institutions have been providing online learning exclusively during the COVID19 pandemic
(Marsicano et al., 2020). Building on this groundwork, institutional leadership, and OPLs should,
in addition to formal communication, seek to create synergy and momentum through informal
communications (Kezar, 2001). In addition to building positive momentum, OPLs could leverage
the shared governance both in decision making for source selection and implementing the scaling
process. As Kezar (2001) suggested, institutions are more likely to create change and adapt in the
presence of a functional shared governance process that involves administrators and faculty.
Applying these three principles could lay the cultural foundation to support decision-making
about resource, structure, and capability factors for selecting an appropriate scaling strategy for
online graduate programs and assist with implementing it.
A notable stakeholder group in this cultural change endeavor is tenured faculty. Tenured
faculty have a longstanding affiliation with their institution that typically outlast the tenure of
institutional leaders. This faculty-leadership relationship dynamic poses a unique challenge for
OPLs and their institutional leaders who need their support to ensure scaled online programs
maintain the level and quality of learning experience associated with the institution. However, as
some study participants revealed, this group appeared reluctant to embrace online graduate
programs' scaling. Therefore, OPLs and institutional leaders will need to be prepared to carefully
navigate this relationship dynamic and get the most support possible.
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Limitations and Delimitations
The quality of a study is impacted by its limitations and delimitations. Limitations refer
to the shortcomings of a study because of matters beyond the researcher's control (Simon &
Goes, 2013). Delimitations refer to the study's inherent characteristics, such as the conceptual
framework that defines its scope (Simon & Goes, 2013). There are two limitations to this study.
The first pertains to participant misinterpretation of survey and interview questions. These
questions were reviewed for clarity, but it is possible that participants may have misunderstood
them. The second limitation is the accuracy of self-reported data. The participants may have been
less than truthful or forthcoming in answering survey and interview questions.
The first delimitation of this study is related to its scope of inquiry. As mentioned
previously, the study focused on institutions seeking to scale their online graduate programs. The
researcher intended to explore the selection process for a sourcing strategy if a decision to scale
was already made. As such, there was no attempt made to understand whether an institution or a
graduate program ought to scale or not.
Another delimitation of this field study was its stakeholder group, namely Online
Program Leaders (OPLs), at 567 non-profit doctoral universities. The sample lacks homogeneity
in two ways. The institutions represented in the respondent and interviewee data appear to have
varying engagement levels with online graduate programs. Some institutions have been offering
online learning in various forms for several years, whereas others have only recently committed
to this endeavor. Thus, institutional resources, capability, cultural influences are highly variable.
The OPL stakeholder group represents various institutional officers and has varying exposure to
online graduate programs depending on their roles’ proximity to online graduate programs.
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Hence, the OPL knowledge level for resources, structure, and capability for scaling online
graduate programs is also highly variable.
This study's final delimitation is in its literature review scope, which focused on four
common institutional influences: culture, structure, resources, and capability. For practical
reasons, the scope was limited to exploring these factors mainly from an internal perspective. A
comprehensive study should include exploring external influences like competition, labor market
trends for graduate degree holders, national and state accreditation.
Recommendations for Future Research
The limitations and delimitations inform the recommendations for future research of this
study. This study was conducted during the COVID-19 pandemic, with all higher education
institutions transitioning to fully online instruction. As discussed earlier, the transition has
positively impacted graduate student enrollment (National Student Clearinghouse Research
Center, 2021). Although early, the results suggest an opportunity for institutions to consider
scaling their online graduate programs. Future studies could uncover the reasons for the rise in
graduate enrollment during this shift to fully online instruction. Studies could also explore the
long-term impact of this transition on the future of scaling online graduate programs. An
essential consideration of such studies would be to account for the financial and technological
investments institutions have already made to shift to fully online instruction (Hodges et al.,
2020).
Future studies could focus on a more homogenous sample of OPLs and institutions. For
example, some studies could focus exclusively on OPLs in similar roles, such as Academic
Deans or Directors of Online Learning. Instead of focusing on institutions, future studies could
focus on exploring online graduate programs at various institutions within a single academic
113

discipline such as business, education, and engineering. These studies could explore internal and
external influences that impact source selection and propose a framework for OPLs to utilize in
their source selection process.
A final recommendation for future studies pertains to sourcing strategy. This study began
an exploration of two distinct sourcing strategies for exploration: insourcing and outsourcing.
During data collection, a third strategy involving the use of both insourcing and outsourcing
emerged. Future studies could focus on learning OPL knowledge and institutional influences
related to each sourcing strategy. As referenced earlier, research on institutional outsourcing
partnerships with Online Program Managers (OPMs) remains scarce (Lederman, 2021;
McKenzie, 2020). Therefore, future research could focus on a comprehensive analysis of OPM
partnership from an OPL knowledge and institutional influences standpoint. Similarly, research
has yet to uncover several aspects of scaling online graduate programs through insourcing.
Future studies in this area could explore institutions' models to plan investments in internal
capacity building, develop scaling milestones, and formulate enrollment targets. Finally, future
studies could focus on learning how certain institutions use a combination of insourcing and
outsourcing to fill gaps in resources and capabilities while also maintaining control of their
scaling efforts.
Conclusion
This study focused on exploring Online Program Leaders' decision-making process n
selecting insourcing or outsourcing online graduate programs' scaling. Online graduate programs
have experienced significant growth in the last few years (Blagg, 2018). Several factors,
including technological advancement, access to graduate student aid, and the positive value
proposition of holding a graduate degree, have fueled this growth (Baum et al., 2013; Hoffman et
114

al., 2019; Ma et al., 2020; Murray, 2019). Higher education leaders view scaling online graduate
programs as an opportunity to advance the institution’s strategic and financial objectives
(Dziuban et al., 2016; Palvia et al., 2018). Despite the growing interest in online graduate
programs, current research does not adequately explore online graduate programs' management
from OPLs’ perspective. Furthermore, current research does not explore the process used by
OPLs in evaluating scaling options such as insourcing or outsourcing. The study attempted to
begin addressing this gap, starting with OPL knowledge and institutional influences impacting
selecting a sourcing strategy.
The study utilized the Clark and Estes (2008) gap analysis framework to identify and
explore gaps in alignment between institutional goals and OPL knowledge and institutional
influences. A mixed-methods sequential explanatory design for data collection was used for this
study. A survey of OPLs at 567 private non-profit master’s and doctoral universities followed by
an interview with 12 OPLs and document analysis of strategic plans and training materials was
conducted.
The data analysis revealed that OPLs are highly knowledgeable about three critical
scaling factors: resources, structure, and capability. The analysis also revealed that, with few
exceptions, there are no statistically significant differences in OPL knowledge based on their
selected sourcing strategy, their role, their institution’s Carnegie classification, or their graduate
academic discipline. OPLs’ knowledge of institutional resources and capability appeared highly
impactful in their final selection of a sourcing strategy. Institutional influences also appeared to
be impactful in OPL decision-making. The analysis revealed institutional culture as a significant
barrier, particularly at institutions predisposed to negative online learning perceptions. However,
the COVID19 pandemic that forced all institutions to shift to complete online learning appeared
115

to be reducing this negative perception. Data findings suggested that current processes and
policies were generally unconducive for scaling online programs. Findings also suggested
institutional leaders had not prioritized and adequately communicated the importance of scaling
online graduate programs.
The study suggests three general recommendations to commence the process for source
selection to scale online graduate programs. The first recommendation is ensuring OPLs
maintain a high level of knowledge of resources, capacity, and structure. To accomplish this,
OPLs can use a diagnostic model such as Piña’s (2017) diagnostic model and Dechant and
Dechant’s (2010) systems-based model. The second recommendation is to establish a strategic
vision for scaling online graduate programs. Institutional leaders can use institution-wide
strategic planning tenets to facilitate a strategic planning process for online graduate programs.
As an example, Hill et al.’s (2009) collaborative strategic planning framework was proposed.
The third and final recommendation is to leverage institutional culture, particularly in the current
COVID19 pandemic, to overcome scaling obstacles. It is suggested OPLs and institutional
leadership utilize three of Kezar’s (2001) research-based principles of change to influence
culture. They include laying the groundwork, communicating informally, and relying on the
shared governance structure.
This study's recommendations stem from a combination of OPL knowledge and
institutional influences related to making a scaling decision for online graduate programs.
Specific implementation models and evaluation plans cannot be generalized due to each
institution’s distinct characteristics and circumstances (Kezar, 2001). Hence, the general
recommendations proposed in this study will need to be adapted by OPLs, institutional leaders,
and other stakeholders to meet their specific scaling challenges.
116

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130

Appendix A: Survey Protocol
My name is Ammar Dalal, and I am a doctoral candidate at the University of Southern California
(USC). I am conducting a study to explore practices for scaling online graduate programs. This
survey is being conducted to collect information regarding the institutional-level and graduate
college-level process of selecting whether to insource or outsource scaling of online graduate
programs.

The survey is intended to capture the perspectives of institutional leaders who play a critical role
in making such a selection. I am looking for individuals in the following positions to be a part of
the study:
o Assistant/Associate/Vice Provost
o Assistant/Associate/Vice President
o Chief Information Officer (CIO) or Chief Technology Officer (CTO)
o Online Learning Officer/Director
o Dean of a Graduate School/College
o Assistant/Associate Dean of Graduate School/College

You are invited to complete this survey if you hold any of the positions mentioned above. The
survey consists of 22 questions and is estimated to take approximately 7 to 10 minutes to
complete. You may choose to skip a question or end the survey at any time without explanation.

This exempt research has been reviewed and approved by an Institutional Review Board (IRB) at
USC. For additional details, please view this information sheet. You may talk to them at (323)
442-0114 or email them at IRB@usc.edu. All information submitted to this survey will be
treated as confidential and will only be used for research or statistical purposes by the
researcher.

Thank you in advance for your contribution. To acknowledge your consent to participate in this
survey, click “NEXT” below.
131

Survey Questions
Demographic questions:
1. Which of the following describes your institution’s status?
• Public
• Private Non-Profit
• Private For-Profit

2. Which of the following Carnegie classifications describes your institution type? (Please click here to
look up your institution)
• R1: Doctoral Universities – Highest research activity
• R2: Doctoral Universities – Higher research activity
• D/PU: Doctoral/Professional Universities
• M1: Master’s Colleges and Universities – Larger programs
• M2: Master’s Colleges and Universities – Medium programs
• M3: Master’s Colleges and Universities – Smaller programs
• Baccalaureate Colleges
• Baccalaureate/Associate's Colleges
• Associate's Colleges
• Special Focus Institutions

3. Which of the following best describes your current title?
• Assistant/Associate/Vice Provost
• Assistant/Associate/Vice President
• Chief Information Officer (CIO) or Chief Technology Officer (CTO)
• Chief Online Learning Officer (COLO)
• Dean of a School/College
• Assistant/Associate Dean of School/College
• Other (please explain)

4. Please select the field of study that best describes your academic college:
• Business
• Law
• Medical School
• Engineering
• Education
• Nursing
• Library and information studies
• Social sciences and the humanities
• Fine arts
• Public affairs
• Health
• Science
• School of Professional Studies
• Other (please explain)

5. Which of the following best describes your role in selecting whether to insource or outsource scaling of
online graduate programs?
• I am involved in the data gathering and analysis process but do not play a role in the final
selection
132

• I serve on an institutional or college-based committee in the approval process of the final
selection
• I am part of an executive team charged with recommending a final selection for approval
• I am solely responsible for recommending a final selection for institutional approval

6. Please describe this role briefly.

7. Which of the following statuses best describe the nature of scaling online graduate programs in your
graduate school?
OR
Which of the following statuses best describe the nature of scaling online graduate programs at your
institution?
• No desire to scale online graduate programs
• Plans to scale online graduate programs are under consideration
• Scaling initiative for one or more online graduate programs is currently in progress
• Already achieved the desired scaling

8. Which of the following sourcing strategy is (or was) being utilized to scale online graduate programs?
• Outsourcing with an external partner such as Online Program Manager (OPM)
• Insourcing by building internal capacities such as technology and support services
• Other (please explain)

Knowledge Influences:
9. Concerning the scaling of online graduate programs, please rate your level of familiarity with the
following institutional areas. (1 – Not at all familiar, 2 – Slightly familiar, 3 – Moderately familiar, 4 –
Extremely familiar)
• Shared Governance Structure
• New Program Approval Policy
• Institutional Communication Processes
• Funding
• Staffing
• Technology
• Strategic Plan(s)
• Staff Technological Expertise
• Faculty Pedagogical Expertise
• Student Support Systems
• Faculty Support Systems

10. Please rank the following institutional resources in the order of their importance for scaling online
graduate programs. (Rank order)
• Hardware and Software Support Infrastructure
• Instructional Design Support
• Staff Development
• Faculty Technology Support
• Course Management System
• Funding

11. Which of the following are (or were) utilized in selecting whether to outsource or insource online
graduate programs? (Yes/No)
• Strategic plan for online programs
• Marketing plan to promote online programs
133

• Needs assessment plan for faculty and student needs
• Evaluation plan for ongoing assessment

12. How influential is (or was) your knowledge of the following institutional factors in selecting whether
to insource or outsource scaling efforts? (Very influential, Somewhat influential, Somewhat non-
influential, Very non-influential)
• Structure (shared governance, new program approval policy, communication processes)
• Resources (funding, staffing, technology)
• Capability (existence of strategic plans, technological and pedagogical expertise, support
systems)

Institutional Influences:
13. How important is (or was) it to include scaling of online graduate programs as a strategic goal in the
following areas. (Not at all important, Slightly important, Very important, Extremely Important)
• Institutional strategic plan
• College-based strategic plan
• Individual graduate program strategic plan

14. Does institutional leadership regularly communicate the importance of scaling online graduate
programs to stakeholders? (Yes/No)

15. If yes, please indicate how such communication takes place. Check all that apply:
• Emails
• Newsletters
• Townhalls
• Annual Meetings (Convocation, State of the University)
• Social Media
• Other (please explain)

16. Please rate the degree to which institutional culture will (or has) influence(d) your selection of
insourcing or outsourcing scaling of online graduate programs.
• Strongly
• Moderately
• Somewhat
• Not at all

17. Please rate your level of satisfaction in receiving institutional support in the following areas during the
implementation of the chosen scaling alternative. (Extremely satisfied, Somewhat satisfied, Neither
satisfied nor dissatisfied, Somewhat dissatisfied, Extremely dissatisfied)
• Financial resources
• Human resources (staffing)
• Technological resources
• Policy support

18. Please rank the following factors in terms of the barrier they pose for scaling online graduate
programs. (1 being the most significant barrier, 4 being the least significant barrier)
• Cultural factors (resistance to online teaching, risk-averse mindset, a perception that online
learning is inferior)
• Structural factors (shared governance, new program approval policy, communication processes)
• Resource factors (funding, staffing, technology)
134

• Capability factors (existence of strategic plans, technological and pedagogical expertise, support
systems)

19. In a few words, describe the main reason why your institution chose to insource or outsource the
scaling of online graduate programs. (Open-ended)

Demographic question:
20. Please indicate the name of your institution.

This information will only be used so that your responses can be compared by selected institutional
characteristics. The name of your institution will be kept confidential and no direct reference will be made
in results.

Interview Selection Questions:
21. Would you participate in continued research on scaling online graduate programs? (Yes/No)

The continued study would include participation in a 45-60-minute confidential interview via Zoom.

22. Please provide the following contact information. (If yes is the answer to the previous question)
• Name
• Email

135

Appendix B: Interview Protocol
Interview invitation:
Dear (Participant Name),
Thank you again for your willingness to participate in an interview via Zoom and share
additional information with me. Please review the attached information sheet for more details.

If you remain willing to participate in the interview, please respond to this email and indicate
which of the following times suit your availability. Details about the Zoom meeting will follow.

· (Two to three interview dates and times provided)

If these times do not suit your availability, please suggest a few times that would be suitable, and
I will do my best to accommodate. Thank you in advance for your contribution. I look forward to
speaking with you soon.

Sincerely,
Ammar

Pre-Interview:

Greetings, and thank you for voluntarily participating in this interview. This study is being
conducted to explore practices for scaling online graduate programs. This study aims to
understand the process that leads an institution to insource or outsource the scaling initiative.

The interview will take approximately 45 to 60 minutes. Please note that anything you share here
will remain completely confidential. Findings reported in this study will not be associated with
you or your institution's name. Furthermore, your participation is entirely voluntary, and you
may choose to skip any question and end the interview at any time without explanation.

With your consent, I would like to record the audio and video of our interview. You have the
option to mask your identity. If you prefer not to have your interview video be recorded in
Zoom, only audio will be recorded on a separate recording device. The recording will be used
solely for transcription, and you will have the opportunity, if you so choose, to review it for
accuracy. At the end of this study, all recorded video and audio will be destroyed.

Once again, thank you for your willingness to participate. Before I begin recording, I would like
to request your permission to be recorded. Please confirm so by saying “yes.”

136

Informed Consent
This exempt research has been reviewed and approved by an Institutional Review Board (IRB)
at USC. For additional details, please view the information sheet pasted below. You may talk to
them at (323) 442-0114 or email them at IRB@usc.edu. All information submitted to this survey
will be treated as confidential and will only be used for research or statistical purposes by the
researcher.
University of Southern California Rossier School of Education
INFORMATION SHEET FOR EXEMPT RESEARCH
STUDY TITLE: Scaling Online Graduate Programs
PRINCIPAL INVESTIGATOR: Ammar Dalal
FACULTY ADVISOR: Helena Seli, PhD
You are invited to participate in a research study. Your participation is voluntary. This
document explains information about this study. You should ask questions about anything
that is unclear to you.
PURPOSE
The purpose of this study is to explore knowledge and organizational influences affecting higher
education leaders’ selection process of whether to insource or outsource scaling of online
graduate programs. The rationale for this field study is to contribute to the growing body of
literature in the field of scaling online master’s and doctoral programs at institutions desiring to
expand their graduate program offerings.
PARTICIPANT INVOLVEMENT
If you decide to take part, you will be asked a series of questions regarding this topic for about
45-60 minutes via Zoom conferencing. The session will be recorded after your expressed
consent. You have the option to mask your identity for the session. You can participate in this
session even if you decline to be recorded.
PAYMENT/COMPENSATION FOR PARTICIPATION
You will not be compensated for your participation. Participation in this study will require no
monetary cost to you.
CONFIDENTIALITY
The members of the research team and the University of Southern California Institutional
Review Board (IRB) may access the data. The IRB reviews and monitors research studies to
protect the rights and welfare of research subjects. When the results of the research are
published or discussed in conferences, no identifiable information will be used. Your name will
never be used in any public dissemination of these data (publications, presentations, etc.).
The interview will be recorded solely for transcription purposes. A third-party transcribing
service may be used to transcribe the interview. You can review your interview recording or
transcript upon request. Recordings will be deleted promptly at the conclusion of this study.
137

INVESTIGATOR CONTACT INFORMATION
If you have any questions about this study, please contact Ammar Dalal (Principal
Investigator) via email at adalal@usc.edu or Dr. Helena Seli (Faculty Advisor) via email at
helena.seli@rossier.usc.edu.
IRB CONTACT INFORMATION
If you have any questions about your rights as a research participant, please contact the
University of Southern California Institutional Review Board at (323) 442-0114 or email
irb@usc.edu.
Version Date: 11/18/2020 Page 1 of 1 USC IRB Information Sheet Template Version Date: 07/27/2019

138

Interview Questions
Opening questions:
1. Does your institution outsource or insource delivery of online graduate programs?

2. Why did your institution choose to outsource (or insource)?

3. What are some of the more common barriers to scaling online graduate programs at your
institution?

Knowledge Influences:
4. Describe the selection process for scaling online graduate programs at your institution.
• What are some major steps involved?
• Who is involved?
• What is the timeline for making a decision?

5. Describe your process for assessing resource readiness to scale online graduate programs.
• What diagnostic model, if any, was used?
• What resources appeared to be adequate?
• What resources appeared to have shortcomings?

6. Describe the relationship between institutional resources and selecting whether to insource or
outsource scaling efforts.
• What areas were most impacted?

7. Please describe the structure supporting online graduate programs.
• Whose primary responsibility is it to manage online graduate programs?
• What staff, if any, are dedicated to supporting online graduate programs?
• What type of support do they provide?

8. What impact, if any, did (or would) the selection of insourcing or outsourcing have on the
prevailing structure for online graduate programs?
• What teams were reorganized as a result of the selection?

9. Please describe your process for assessing institutional capability for scaling online graduate
programs.
• What tools or guides were used in the process?
• How, if at all, was benchmarking used in this process?

10. What sort of expertise, if any, did you use to assist in the assessment of institutional
capability for scaling online graduate programs?
• What professional associations or consultants, if any, were leveraged to facilitate
assessment?

11. What impact, if any, did outsourcing (or insourcing) have on institutional capability?
• What areas were most impacted?
• What gaps in capability were addressed?
139

12. Can you describe your level of confidence in the process of selecting whether to outsource or
insource?
• What aspects of the process went as expected?
• What aspects could use more attention and improvement?

Institutional Influences:
13. Please describe the role your institution’s structure played in determining whether to insource
or outsource scaling.
• How did the shared governance model impact the process?
• How did you build a consensus to support the selected alternative?

14. How do you expect the decision to insource (or outsource) will impact goals for scaling?
• Has the decision changed expectations regarding timeline and cost for achieving the
desired level of scaling?

15. In reflecting on your experience, what steps do you believe an institution can take to better
support online program leaders to ensure online graduate programs are scaled successfully?

16. What advice would you give to a peer whose institution is currently assessing whether to
insource or outsource scaling?
• What are some significant considerations?
• What are some recommended tools for the assessment?
• What are some unexpected internal or external challenges?

140

Appendix C: Document Analysis Protocol
Knowledge Influences:
1. Training materials
o Review training materials to determine what resources OPLs utilize in assessing
institutional resources, structure, and capability in advancing scaling initiatives.

Institutional Influences:
2. Institutional and College Strategic Plans
o Review the institutional strategic plans to determine the highest-level priority
assigned to the growth of online graduate education.
o Review college strategic plans for comments that reveal the commitment of resources
and support for scaling online graduate programs.

Abstract (if available)

Abstract Substantial recent growth in online graduate programs has garnered the attention of the higher education community. Given their limited resources and capability, institutions seeking to scale their online graduate programs need to consider whether to insource or outsource this initiative. The purpose of this study was to identify the knowledge and institutional influences affecting the decision-making process of Online Program Leaders (OPLs) in the selection of a sourcing strategy for scaling online graduate programs. The study participants were institutional leaders at various private non-profit master’s and doctoral universities with decision-making power and responsibility for source selection and implementation. Data was collected through surveys, interviews, and document analysis. The results and findings demonstrated that OPL knowledge of resources, structure, and capability was highly influential in source selection. The prevailing negative perception of online learning among institutional members, existing policies and procedures such as new program approval process and graduate program budget models, and the lack of adequate communication were identified as barriers in source selection and implementation. The study provides general recommendations for institutions seeking to scale their online graduate programs. They include ensuring OPLs possess and maintain a high level of knowledge of resources, capability, and structure

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Strengthening community: how to effectively implement a conflict resolution and peer mediation program on a secondary school campus: an evaluation study

Asset Metadata

Creator Dalal, Ammar (author)

Core Title Scaling online graduate programs: an exploratory study of insourcing versus outsourcing

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Publication Date 04/06/2021

Defense Date 03/25/2021

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

Tag graduate programs,graduate recruitment,Higher education,learning management system,OAI-PMH Harvest,online learning,online program administration,OPM

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Seli, Helena (committee chair), Lynch, Douglas (committee member), Phillips, Jennifer (committee member)

Creator Email adalal@usc.edu,ammard@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c89-438632

Unique identifier UC11666633

Identifier etd-DalalAmmar-9412.pdf (filename),usctheses-c89-438632 (legacy record id)

Legacy Identifier etd-DalalAmmar-9412.pdf

Dmrecord 438632

Document Type Dissertation

Rights Dalal, Ammar

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...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA