User acceptance of computer-based VoIP phone service: an application of the technology acceptance model

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Content USER ACCEPTANCE OF COMPUTER-BASED VOIP PHONE SERVICE:
AN APPLICATION OF THE TECHNOLOGY ACCEPTANCE MODEL
by
Namkee Park
____________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(COMMUNICATION)
August 2007
Copyright 2007 Namkee Park
ii
DEDICATION
To My Parents and Wife
iii
ACKNOWLEDGEMENTS
The last six years for my doctoral study have been a succession of hopes and
disappointments. During that time, needless to say, many people have helped me
successfully finish my study, and I hope this humble work justifies their help and
support.
First and foremost, I would like to express my deepest respect and
appreciation to Dr. Margaret McLaughlin, who has been my advisor, committee
chair, and more importantly, lifetime mentor. She has always believed in me and
encouraged me to overcome all kinds of hurdles throughout my doctoral study.
Without her encouragement and rapid and insightful responses to my numerous
drafts, I would not have been able to finish this study within the time available.
Peggy has set high standards as a human being, scholar, and teacher for me to follow
for the rest of my life.
I am also tremendously indebted to Dr. Kwan Min Lee for his strong support
and guidance. Academic discussions through various research projects and personal
interactions with him have not only made my study much more productive but also
inspired me in many aspects. My sincere gratitude also goes to Dr. Albert Skip Rizzo
for his agreement to be my committee member and insightful comments for my
dissertation. I would also like to thank Dr. Michael Cody for his invaluable help and
support for my job search.
iv
I have greatly benefited from other faculty members for my intellectual
training and growth at USC. Dr. Francois Bar and Dr. Peter Monge showed me not
just the rigor of academic discipline but also the joy of achievements. In addition, I
would like to express my deep gratitude to Dr. C. Ann Hollifield at the University of
Georgia and Dr. Kyu Ho Youm at the University of Oregon for their precious
guidance and encouragement, which are more than I deserve.
Words are not enough to thank my parents who have long waited for their
son’s success with wholehearted supports and patience. Their unlimited sacrifice and
unwavering love have enabled me to reach this point. Finally, I wish to thank my
wife, Seon-Mi Choi, who has gone through every turn of my study and always been
supportive. Undoubtedly, most accomplishments during my doctoral study are hers.
v
TABLE OF CONTENTS
DEDICATION ii
ACKNOWLEDGEMENTS iii
LIST OF TABLES viii
LIST OF FIGURES ix
ABSTRACT x
CHAPTER I: INTRODUCTION
Research Background
Purposes of the Study
Chapter I Endnotes
1
1
5
7
CHAPTER II: LITERATURE REVIEW
Technology Acceptance Model as a Theoretical Framework
Uses and Gratifications Approach
Uses and Gratifications Approach and Media Studies
Motivations for Telephone Use
Diffusion Theory
Factors of Technology Adoption from Diffusion Theory
Demographics
Technology Cluster
Communication Needs
Innovative Attitude
The Social Presence Model and Media Richness Theory
Computer and Internet Self-Efficacies
8
8
12
12
14
17
18
18
18
19
20
22
25
CHAPTER III: HYPOTHESES AND RESEARCH MODEL
Hypotheses from the TAM
Perceived Ease of Use
Perceived Usefulness
Attitude toward Using
Hypotheses with Independent Factors
Computer and Internet Self-Efficacies
Technology Cluster
Innovative Attitude
28
28
28
29
30
31
33
34
35
vi
Communication Needs
Perceived Cost Effectiveness
Perceived Quality
System Functions
Media Richness
Motivations
Hypotheses for Non-Users
Demographics
Hypotheses from the Variables of Individual Differences
Chapter III Endnotes
36
37
37
38
39
40
43
43
44
46
CHAPTER IV: RESEARCH METHOD
Sampling
Online Survey over Other Methods
Advantages of Online Survey
Disadvantages of Online Survey
Survey Administration
Measurement of Variables
Data Analysis
Chapter IV Endnotes
47
47
48
48
49
50
52
61
64
CHAPTER V: RESULTS
Descriptive Statistics
Users of Computer-Based VoIP Phone Service
Non-Users of Computer-Based VoIP Phone Service
Comparison between Users and Non-Users
Exploratory Factor Analysis for Motivations
Analyses of Structural Equation Modeling for Users
Tests of the Overall Model
Tests of Hypotheses
Model Revision
First Revision: Deleting Non-Significant Paths
Second Revision: Adding Relevant Paths
Third Revision: Making the Model Parsimonious
Direct and Indirect Effects
Multiple Regression Analysis for Non-Users
65
65
66
67
71
73
75
78
79
83
84
85
89
93
96
CHAPTER VI: CONCLUSION AND DISCUSSION
Summary of Findings and Discussion
Research Implications
Limitations and Suggestions for Future Research
98
98
107
108
vii
REFERENCES 111
APPENDIX 128
viii
LIST OF TABLES
Table 5-1: Adoption and Use of Computer-based VoIP Phone Service 70
Table 5-2: Factor Analysis for Motivations 74
Table 5-3: Zero-Order Correlations 77
Table 5-4: Means and Standard Deviations 78
Table 5-5: The Paths Added through the Model Revision Process 88
Table 5-6: Comparison of Hypothesized and Revised Models 92
Table 5-7: Direct and Indirect Effects 95
Table 5-8: Multiple Regression: Predictors of Behavioral Intention 97
ix
LIST OF FIGURES
Figure 2-1: Technology Acceptance Model (TAM) 11
Figure 3-1: Hypothesized Research Model 42
Figure 5-1: LISREL Results for the Hypothesized Model 80
Figure 5-2: LISREL Results for the Final Model 91
x
ABSTRACT
The recent few years have witnessed remarkable growth in the use of
computer-based VoIP phone service, which allows computer users to talk to other
people at no or little cost via calls through an Internet connection. Employing a
theoretical framework from the technology acceptance model (TAM), the uses and
gratifications approach, diffusion theory, and the theory of media richness, this study
aims to examine the process of adoption and use of computer-based VoIP phone
service, and further derive the determinants of technology acceptance by looking at
user characteristics.
A nationwide online survey was conducted in the U.S., yielding a total
sample size of 1,656 of which the valid number of computer-based VoIP phone
service users was 309. Results from structural equation modeling analyses showed
that users’ perceived ease of use had a significant impact on perceived usefulness,
which in turn affected their attitude toward using computer-based VoIP phone
service, as the TAM suggested. However, users’ perceived usefulness of the
technology did not exhibit a direct influence on actual use of the technology,
contrary to expectation.
Among the exogenous variables utilized in the current study, the motivations
for communication and instrumental use played the most important role in the
explanation of adoption and use of computer-based VoIP phone service. The
xi
motivation for entertainment, however, had negative effects on perceived ease of use,
perceived usefulness, and attitude toward using the technology. In the case of system
characteristics, perceived cost effectiveness affected all dependent variables either
directly or indirectly, confirming that cost reduction would be the greatest attraction
of computer-based VoIP phone service. In addition, users of the technology
exhibited higher Internet self-efficacy, owned more communication technology
products, and showed greater innovative attitude than non-users.
Findings of the study offer both theoretical and practical implications. The
study proposes an integration of the TAM and the uses and gratifications approach
by incorporating motivations as critical constructs that facilitate perceived ease of
use and perceived usefulness. Moreover, the study suggests that the vendors of
computer-based VoIP phone service need to develop unique features and functions
beyond the cost advantage of the technology.
1
CHAPTER I
INTRODUCTION
Research Background
The rapid development of the Internet and related information and
communication technologies (ICTs) has fueled not only creation of various new
applications but also convergence of existing communication technologies. Among
these new applications or combinations of previous technologies with the Internet,
the advent of voice over Internet protocol (VoIP) phone service is not a surprise in
that it is a mixture between one of the most common communication technologies,
the telephone, and the Internet, the engine of the current communication revolution.
VoIP, also called IP telephony or Internet telephony, is a digital form of voice
transferring via the Internet: the user’s voice is transformed into packet data and
carried through the Internet to reach the person(s) at the other end. Although early
forms of VoIP came out in the late 1990s, it is only recently that the technology
gained sufficient momentum to be successful in the market, largely thanks to the
diffusion of broadband Internet access services such as cable modem or DSL. There
are, of course, some other reasons for VoIP to be widely used in recent years. To
start with, the greatest attraction of VoIP is cost reduction. Because voice
transmission in VoIP is similar to email transmission except that Internet connections
in VoIP must be fast enough to send and receive the flow of packets without delay,
2
the cost for making calls via VoIP is almost free or at least very cheap if the two
endpoints are connected to the Internet. In addition to the relatively low cost of VoIP
phone service, another advantage is that regardless of users’ location, calls can be
placed and received as long as they are connected to the Internet. Moreover, VoIP
phone services can be easily integrated with other services available on the Internet,
including conference calling, file exchange, or even video conversation. For these
reasons, both consumers and businesses are attracted to the disruptive technology.
More than 1.9 million consumers in the U.S. are enjoying VoIP phone services at a
lower price than traditional landline phone services (Arensman, 2006). Businesses
have already embraced VoIP services with the aim of using a single network to carry
both voice and data within and between offices. In fact, more than one-third of large
North American companies have adopted VoIP as of late 2006 (The Economist,
2006).
VoIP essentially comes with two types of services: hardware-based VoIP and
software-based (more frequently called computer-based) VoIP. Hardware-based
VoIP phone service allows users to plug a standard phone into a converter box
(analog telephone adaptor), which in turn connects to the users’ cable modem or
DSL, or home router. Thus, hardware-based VoIP phone service is not much
different from traditional landline phone service except for the use of the Internet
instead of the Public Switched Telephone Network (PSTN). Hardware-based
systems provide not only better voice quality and reliability compared to software-
3
based VoIP service but also emergency 911 access,
1
similar to the traditional phone
service. Currently, Vonage is a popular service provider in the market for hardware-
based VoIP phone service, and telephone and cable companies such as Verizon,
AT&T, or Comcast also provide such services.
By contrast, software-based or computer-based VoIP phone service (this
study will use the term “computer-based” hereafter) lets computer users talk to other
people using software installed on the client ends, together with microphones,
speakers, and frequently webcams. Many computer-based VoIP phone packages are
free or provided at a very affordable price, attracting more users to the technology. In
most cases, computer-to-computer calls through VoIP phone service are free, while
computer-to-phone or phone-to-computer services can be offered at a significantly
lower price than regular phone services.
2
Further, combined with the unique
functions of video conversation, conference calling, data or file transmission, and
integration with instant messaging services, computer-based VoIP phone service has
seen remarkable growth in the past several years. For instance, a leading computer-
based VoIP phone service, Skype, claims more than 100 million users worldwide
and more than 6 million in the U.S., as of early 2006 (Rampell, 2006). The company
was acquired by eBay for $2.6 billion in 2005, with the potential for further success
down the road. Moreover, Internet giants such as Google, Yahoo, and MSN have
also provided beta versions of the service for their huge potential user bases.
4
The recent popularity of computer-based VoIP phone service attracts much
academic interest from communication researchers given that the technology may
integrate two domains of communication studies, point-to-point communication
through telephone conversations and computer-mediated communication through
video conversations. For computer-mediated communication researchers in
particular, computer-based VoIP phone service offers a unique venue for research
given that the relative lack of nonverbal cues, which has been a defining
characteristic of computer-mediated communication (Daft & Lengel, 1984; Short,
Williams, & Christie, 1976; Steinfield & Fulk, 1987; Trevino, Lengel, & Daft, 1987),
may disappear or be significantly reduced should users of computer-based VoIP
phone service employ video conversations (see Chapter II for a fuller discussion of
this issue).
Despite the recent upsurge of computer-based VoIP phone service and the
technology’s potential to be an interesting target of communication research, few
academic studies about the use of the technology have been located. This is partly
because computer-based VoIP phone service is in an early stage of technology
diffusion. However, the technology’s relative infancy and a lack of existing studies
suggest the need for a comprehensive investigation of users’ dispositions toward the
technology. As many studies about technology diffusion and user adoption illustrate,
the best time to account for a new technology’s user characteristics is its early stage
of diffusion, because the technology’s novelty may disappear as it reaches a critical
5
mass (Kang, 2001; Robertson & Kennedy, 1968). Thus, an investigation about users’
adoption and use of computer-based VoIP phone service will help provide a
theoretical contribution to existing theories about diffusion of communication
technologies, and further illuminate the process of technology adoption and use in
the context of computer-mediated communication.
Purposes of the Study
At the current stage of computer-based VoIP phone service, the key questions
include the following: 1) what are the factors that influence users’ adoption and use
of the technology?; 2) what are people’s motivations to use the technology?; and 3)
how has the technology changed the ways in which people use telephone service?
The ultimate goal of this study is to examine the process of adoption and use of
computer-based VoIP phone service, and further derive the determinants of
technology acceptance by looking at user characteristics. More specifically, this
study has the following three purposes with respect to the investigation of people’s
use of computer-based VoIP phone service.
First, this study will identify the factors that affect users’ acceptance of
computer-based VoIP phone service. It will include not only users’ personal and/or
psychological factors related to technology adoption but also system characteristics
that are embedded in computer-based VoIP phone service.
6
Second, the current study will compare users and non-users of computer-
based VoIP phone service with regard to some variables that may facilitate (or hinder)
people’s use of the technology. By comparing users and non-users, this study will
investigate the differences in personal/individual characteristics between the two
groups.
Finally, related to the first and second goals, this study aims to suggest a
model that explains the dynamics of user acceptance of computer-based VoIP phone
service. Considering that a significant amount of diffusion research in new
communication technologies has been accumulated, it is quite surprising that there
have been few theoretical models which go beyond profiling users’ characteristics
with regard to the adoption of new technologies. The current study will try to build a
theoretical model that explains individual users’ cognitive and affective factors that
affect computer-based VoIP phone service adoption and use.
The study is organized as follows. The next chapter discusses relevant
literature with respect to the factors that affect the adoption and use of computer-
based VoIP phone service. Based on the literature review, hypotheses and a research
model will be developed in Chapter III. Next, Chapter IV will discuss the
methodology for hypothesis testing and model building. Findings of the study are
presented in Chapter V. Finally, in Chapter VI, interpretations and discussions of the
findings along with theoretical and practical implications of the study are presented.
7
Chapter I Endnotes
1. Lack of the emergency 911 service has been pointed out as one of the critical
disadvantages of VoIP phone service. The Federal Communications Commission
(FCC) in the U.S. imposed 911 obligations on providers of hardware-based VoIP
service in June 2005. However, 911 calls using VoIP phone service are handled
differently than 911 calls using regular phone services. For detailed information on
these differences, see FCC’s consumer fact sheet on VoIP and 911 services at
http://www.voip911.gov.
2. As of early 2007, a computer-based VoIP phone service company, Skype’s
computer-to-phone service (SkypeOut) can be used at $29.95 per year with unlimited
calls within the U.S. and Canada, while the company’s phone-to-computer service
(SkypeIn) can be used at $38 per year.
8
CHAPTER II
LITERATURE REVIEW
This chapter reviews existing literature and theories relevant to the study of
the adoption and use of computer-based VoIP phone service. As an overarching
theoretical framework, I employ the Technology Acceptance Model. Then, I
introduce the uses and gratifications approach and diffusion theory to complement
the Technology Acceptance Model. Other relevant theories that may come into play
to explain the adoption and use of computer-based VoIP phone service are also
presented.
Technology Acceptance Model as a Theoretical Framework
Understanding why people accept or reject a new information or
communication technology has been one of the most challenging issues in the study
of new technologies (Swanson, 1988). Among the various efforts to understand the
process of user acceptance of information systems, the Technology Acceptance
Model (TAM) introduced by Davis (1986) is one of the most cited theoretical
frameworks. The model aims not only to explain key factors of user acceptance of
information systems but also to predict the relative importance of the various factors
in the diffusion of technological systems (Davis, Bagozzi, & Warshaw, 1989).
According to Davis, Bagozzi, and Warshaw (1989), the model is an attempt to derive
9
“the determinants of computer acceptance that is general, capable of explaining user
behavior across a broad range of end-user computing technologies and user
populations, while at the same time trying to be parsimonious and theoretically
justified” (p. 985).
The TAM is theoretically rooted in the theory of reasoned action (Ajzen &
Fishbein, 1980; Fishbein & Ajzen, 1975), which has been applied to predicting and
explaining user behaviors across a wide variety of domains. According to the theory
of reasoned action (TRA), a person’s performance of a specified behavior is
determined by his or her behavioral intention to perform the behavior, and behavioral
intention is jointly determined by the person’s attitude and subjective norm
concerning the behavior in question (Ajzen & Fishbein, 1980; Fishbein & Ajzen,
1975). Following the logic of the TRA, the TAM explores the factors that affect
behavioral intention to use information or computer systems, and suggests a causal
linkage between two key variables—perceived usefulness and perceived ease of
use—and users’ attitude, behavioral intention, and actual system adoption and use
(Davis, 1986 [see Figure 2-1]). Perceived usefulness is defined as “the prospective
user’s subjective probability that using a specific application system will increase his
or her job performance within an organizational context,” while perceived ease of
use refers to “the degree to which the prospective user expects the target system to be
free of effort” (Davis et al., 1989, p. 985). In addition to these two main determinants,
the TAM suggests that external factors can have significant effects on users’
10
adoption as they are mediated through these two perceptions. As Figure 2-1
illustrates, the TAM is a path model that identifies the impact of external factors such
as system design characteristics, user characteristics, task characteristics, nature of
the development or implementation process, political influences, organizational
structure, and so on (Ajzen & Fishbein, 1975). The TAM suggests that information
system usage is determined by behavioral intention, which is viewed as being jointly
determined by the user’s attitude toward using the system and perceived usefulness
(Davis et al., 1989). It is notable, however, that perceived ease of use has only an
indirect effect on behavioral intention to use as illustrated in Figure 2-1. Although
the original TAM suggested that “perceived ease of use operates through perceived
usefulness” (Davis, 1989, p. 332), some studies have questioned the variable’s direct
effect on actual use (e.g., Keil, Beranek, & Konsynski, 1995), and in fact some of the
studies have proved that perceived ease of use could have a direct effect on actual
system use (e.g., Gefen & Straub, 2000).
Since Davis’ (1986) introduction of the model, many studies have been
conducted applying it in a variety of information technology usage settings, testing
its appropriateness and modifying it in different contexts. Past research on the TAM
has largely focused on personal computer usage or relatively simple software
applications such as e-mail, word processing programs, spreadsheet software, and the
Windows operating system (e.g., Chau, 1996; Davis, 1993; Davis et al., 1989; Doll,
Hendrickson, & Deng, 1998; Mathieson, 1991). Recently, in line with the
11
development of the Internet and Internet-based technologies, applications of the
TAM have been made in the areas of: organizational contexts (e.g., Hu, Chau, Sheng,
& Tam, 1999; Igbaria, Zinatelli, Cragg, & Cavaye, 1997; Venkatsh & Davis, 1996),
e-commerce (e.g., Jiang, Hsu, & Klein, 2000), telemedicine (e.g., Chau & Hu, 2002;
Karahanna, Straub, & Chervany, 1999), and digital library systems (e.g., Davies,
1997; Hong, Thong, Wong, & Tam, 2002; Thong, Hong, & Tam, 2002). These
studies taken as a whole have concluded that the TAM is not only a powerful and
parsimonious model for representing the determinants of system usage but also a
valuable tool for system planning, since the system designers can have some degree
of control over ease of use and usefulness (Taylor & Todd, 1995).
Figure 2-1. Technology Acceptance Model (TAM).
External
Variables
Perceived
Usefulness
Perceived
Ease of Use
Attitude
toward
Using
Behavioral
Intention to
Use
Actual
System
Use
12
Uses and Gratifications Approach
Uses and Gratifications Approach and Media Studies
Although the TAM is a well-documented model for explaining technology
acceptance by users, the model has been unable to account comprehensively for the
factors that affect users’ acceptance of technology systems because of the original
model’s intended generality and parsimony. That is, one of the TAM’s weaknesses is
its lack of explicit inclusion of antecedent variables that influence perceived ease of
use and perceived usefulness (Dishaw & Strong, 1999). Davis (1989), who originally
introduced the model, also claimed that research should explore other variables that
could affect perceived ease of use, perceived usefulness, and actual use. Thus, it is
necessary to search for other constructs in order to enrich the explanation of users’
acceptance of technology systems depending on specific technology adoption
contexts. One compelling complementary theoretical framework to fill this gap is the
uses and gratifications approach (Blumer & Katz, 1974; Katz, Blumler, & Gurevitch,
1974; Palmgreen, 1984; Palmgreen, Wenner, & Rosengren, 1985; Rosengren, 1974;
Rubin, 1986, 1993, 1994; Windahl, 1981), which has been widely researched for
decades in the area of media effects. Although the approach focuses primarily on
why and how people use media, its emphasis on individual media users’ activities
and choices makes it suitable for application to the adoption and use of other
technologies as well. More specifically, the following principal assumptions of the
approach (Rubin, 2002) illustrate its aim to explain the reasons why people use mass
13
media including the Internet: 1) people’s selection and use of media is goal-directed,
purposive, and motivated; 2) people select and use media to satisfy their felt needs or
desires, suggesting that they are active communicators; 3) social and psychological
factors guide, filter, or mediate people’s communication behavior; and 4) people’s
own initiative mediates the patterns and consequences of media use. These
assumptions of the approach emphasize the role of people’s initiative and activity,
and consequently focus on motivation—which can be defined as a general
disposition that influences the actions people take to fulfill a need or want (Rubin,
1993)—as a factor that accounts for their selective choice and subjective
interpretation of media messages. Because people are said to be actively aware of
their choices of media and technology, they are assumed to exhibit motivations to
use particular media or technology (Infante, Rancer, & Womack, 1993). In other
words, strongly motivated media or technology users engage in more activities and
experience greater satisfaction when using media or technology as compared to
weakly motivated users (Lin, 1993). In sum, the approach views motivation as driven
by felt needs and individual differences (Rosengren, 1974) and as playing a critical
role in increasing people’s behavioral intention and actual use of media.
Research based on the uses and gratifications approach has been extensively
applied for more than 40 years to a variety of new media and new communication
technologies, including VCR (Cohen, Levy, & Golden, 1988; Rubin & Bantz, 1987),
cable television (Bantz, 1982), bulletin board systems (James, Wotring, & Forrest,
14
1995; Rafaeli, 1986), the World Wide Web (Ferguson & Perse, 2000), online
services (Lin, 1999), and the Internet in general (Miller, 1996; Papcharissi & Rubin,
2000). In the case of Internet use in particular, many researchers argued that the uses
and gratifications approach could be a productive means of better understanding of
the relationship between the individual users and technology in the era of the Internet
(e.g., Morris & Ogan, 1996; Newhagen & Rafaeli, 1996), and past research has
shown how users’ various motivations for information, communication, surveillance,
and entertainment have influenced their online activities and Internet use.
Motivations for Telephone Use
In addition to applicability of this perspective to the fields of mass media and
the Internet, it has been claimed that the approach needs to be adopted to examine a
variety of other new communication technologies (e.g., Rubin, 2002; Ruggiero, 2000;
Williams, Strover, & Grant, 1994). The study of the telephone has also utilized the
approach for the last several decades, although it has not been as extensive compared
to the studies of other communication technologies (see Dimmick, Sikand, &
Patterson, 1994). The study of the telephone based on the uses and gratifications
approach has mostly focused on identifying the key motivations for its use.
Keller (1977) and Noble (1987) employed the uses and gratifications
approach, differentiating telephone uses into two broad motives or gratifications:
intrinsic (or social) and instrumental (or task-oriented) uses. According to them,
15
intrinsic motivations of telephone use refer to calls for socializing including chatting,
gossiping, maintaining family contacts, and having a sense of security, while
instrumental motivations include calls of utility such as making appointments,
ordering products, information seeking, and so on. Singer (1981) also distinguished
between the “social” and the “practical” uses of the telephone. In a similar fashion,
Claisse and Rowe (1987) categorized the telephone uses as having “functional” and
“relational” motives. Fischer (1988) also classified the uses of the telephone as
“practical” and “social.” Although the terms for the motivations of telephone uses
are slightly different from each other, all of these studies generally differentiate the
motivations with “social” and “instrumental” functions. Meanwhile, Williams,
Dordick, and Jesuale (1985) added the motivation of fun or entertainment, while
Dimmick, Sikand, and Patterson (1994) extended the motivations with the
“reassurance” function, the use of the telephone to fulfill one’s psychological needs
for feeling secure. Further, O’Keefe and Sulanowski (1995) claimed that telephones
become a mixed mass media, interpersonal communication channel, listing
sociability, entertainment, acquisition, and time management as key motivations of
using telephones. In addition to the uses of the traditional landline telephone, Leung
and Wei (2000) investigated the uses of cell phones in Hong Kong and identified
fashion/status, affection/sociability, relaxation, mobility, and immediate access as
key motivations. In a study of instant messaging use, Leung (2001) claimed that the
16
motivations of affection, entertainment, relaxation, fashion, inclusion, sociability,
and escape account for college students’ uses of ICQ.
In the case of computer-based VoIP phone service, it is reasonable to assume
that users have specific motivations—which could correspond to individual
differences and external factors in the TAM—that drive them to adopt and use the
technology. In addition, the aforementioned assumptions of the uses and
gratifications approach can be easily modified and utilized to explain the adoption
and use of computer-based VoIP phone service. Users who adopt and use computer-
based VoIP phone service would be also goal oriented—whether their adoption and
use are for socializing, work-oriented, or just for fun—and motivated by various
purposes to enhance their communication with others. However, given the many
options in today’s complex technology environment (e.g., various telephone services
including landline and cellular phones), a thorough understanding of individuals’
motivations for the use of computer-based VoIP phone service has not yet been
achieved, and many questions about users’ adoption and use remain unanswered.
Thus, it is expected that the uses and gratifications approach will not only provide a
meaningful theoretical explanation to facilitate a clear understanding of the
relationship between individual users and the adoption and use of computer-based
VoIP phone service, but also help address the weaknesses of the TAM.
17
Diffusion Theory
Considering that computer-based VoIP phone service is an innovation based
on the convergence of the Internet and the telephone, diffusion theory may offer
clues about who would be likely to be early adopters and what their characteristics
might be. Diffusion theory, a theory of diffusion of innovations, has long been a
general theory of how new ideas or technologies are adopted or rejected. According
to Rogers (2003), diffusion is “the process in which an innovation is communicated
through certain channels over time among the members of a social system” (p. 5) and
innovation is “an idea, practice, or object that is perceived as new by an individual or
other unit of adoption” (p. 12). Broadly speaking, diffusion theory addresses the
characteristics of innovations and those who adopt them (Atkin, Jeffres, &
Neuendorf, 1998). In other words, the theory provides a systematic explanation for
how new innovative technologies are communicated, evaluated, adopted, and
reevaluated by users (Williams, Strover, & Grant, 1994).
Studies based on diffusion theory are extensive. Since Rogers’
conceptualization of the diffusion of innovations and accumulation of research
findings, the efforts to examine the adoption characteristics of new innovations have
continued. Especially in the area of information and communication technologies,
the research covers a wide range of new technologies including VCR (Reagan, 1987;
Scherer, 1989), personal computer (Danko & MacLachlan, 1983; Dickerson &
Gentry, 1983; Dutton, Rogers, & Jun, 1987; Lin, 1998), videotext (Ettema, 1984,
18
1989; Lin, 1994), DBS (Bruce, 1996), HDTV (Dupagne, 1999), the Internet (Atkin,
Jeffres, & Neuendorf, 1998), digital cable (Kang, 2002), and terrestrial digital
television (Atkin, Neuendorf, Jeffres, & Skalski, 2003; Chan-Olmstead & Chang,
2006).
Factors of Technology Adoption from Diffusion Theory
Demographics
According to diffusion theory (Rogers, 1995, 2003), adoption of
technological innovations is a function of people’s social locators, media use patterns,
uses of other technologies, and peoples’ communication needs. Many studies have
found that demographic variables are associated with new media or technology
adoption and use behaviors (e.g., Atkin & LaRose, 1994; Dickerson & Gentry, 1983;
Dutton, Rogers, & Jun, 1987; Ettema, 1984; Krugman, 1985; Lin, 1998; Steinfield,
Dutton, & Kovaric, 1989). These studies collectively conclude that adopters tend to
be upscale, better educated, and younger than non-adopters. The findings from these
studies affirm Rogers’ (1995) socio-economic generalizations about early adopters.
Technology Cluster
Among the various factors that affect adoption of technological innovations,
of more importance with respect to computer-based VoIP phone service are use of
other technologies and communication needs. According to Rogers (1995), “all
19
technology clusters consist of one or more distinguishable elements of technology
that are perceived as being closely interrelated” (p. 15). This suggests that adoption
of one technology is likely to stimulate the use of functionally similar technologies
(Atkin & LaRose, 1994; LaRose & Atkin, 1992). Utilizing Rogers’ concept of
technology cluster, Lin (1998) argued that computer adoption was related to Internet
adoption intentions as well as a technology adoption index (composed of 14
communication media). Regan (1987) also found that adoption of a given media
innovation was most powerfully related to adoption of other technologies such as
videotext, personal computers, CDs, and cable. Ettema (1984) similarly claimed that
the adoption of new text services was related to adoption of other innovations.
LaRose and Atkin (1992) also noted that use of audiotext was related to functionally
similar information services such as videotext and 1-900 numbers. In the same
fashion, Dickerson and Gentry (1983) claimed that experiences with other computer-
related products and services played an important role in purchasing personal
computers. In sum, it can be argued that adoption of an innovation might be
stimulated by the acquisition of a “trigger” innovation (Dozier, Valente, & Severn,
1986).
Communication Needs
Research on communication technology adoption indicates that
communication needs are primary determining factors. For instance, Jeffres and
20
Atkin (1996) examined communication needs with two variables: 1) the need to send
messages to large audiences via mass media; and 2) the need to engage in
interpersonal communication over computer/telephone or some other technologies.
They also argued that the Internet represents a combination of opportunities for
interpersonal communication, group communication, organizational communication,
and mass communication. Further, they claimed that researchers need to shift the
focus toward communication variables and away from technological hardware for
the study of adoption of innovations. Rafaeli and LaRose (1993) claimed that
communication needs are the most compelling predictor for the use of bulletin board.
Similarly, Neuendorf, Atkin, and Jeffres (1998) argued that communication needs
are more important than social locators such as education or income. Jeffres and
Atkin (1996) also argued for a balanced research focus between technical factors and
personal communication factors. Given that computer-based VoIP phone service is
not just a technological innovation with the advent of the Internet, but also an
application with which users’ communication needs can be fulfilled, it is necessary
to put equal emphasis on both technical and personal communication factors.
Innovative Attitude
Another important concept from diffusion theory is innovativeness, which
Rogers (1995) defines as “the degree to which an individual is relatively earlier in
adopting an innovation than other members of a social system” (p. 22). Put
21
differently, the characteristics of earlier adopters may be different from those of later
adopters or non-adopters because of the degree of their adoptive innovativeness. In
fact, the causes of innovative attitude have their psychological roots in an
individual’s novelty-seeking motives (Hirshman, 1980), and these roots of
innovative attitude include personal characteristics such as venturesomeness and
communication usage patterns (Foxall & Bhate, 1991). Rogers (1995) classified
adopters into five categories based on adoptive innovativeness: innovators (2.5%),
early adopters (13.5%), early majority (34%), late majority (34%), and laggards
(16%).
Previous research found that individuals’ adoptive innovativeness is an
important determinant in the adoption dynamics. For instance, Lin (1998) discovered
that computer adopters exhibited the highest degree of need for innovative attitude
(e.g., willingness to try new technology, keeping up with new technology, etc.)
compared to likely adopters and non-adopters.
These factors of technology adoption will be integrated with other factors
from other theoretical perspectives employed in the current study, and a more
elaborated theoretical model will be presented in the next chapter.
22
The Social Presence Model and Media Richness Theory
Recent research about the selection and use of communication technologies
or media suggests that such factors as assessment of needs fulfillment,
appropriateness, and peer evaluations of media have been found to determine
adoption and use, while the attributes of technologies or media are not the primary
determinant (Flanagin & Metzger, 2001). Nevertheless, the social presence model
and media richness theory, which emphasize the attributes of technologies or media
as a factor in selecting the technologies or media in question, are expected to provide
useful insight into the explanation of the adoption and use of computer-based VoIP
phone service, given the theories’ applications in the contexts of organizational
communication during the last several decades.
The social presence model (Short, Williams, & Christie, 1976) claims that
communication technologies or media vary in their social presence, “the feeling that
other actors are jointly involved in communicative interactions” (p. 65). According
to the model, communication technologies or media can be arrayed along a
continuum from low (e.g., numeric data) to high social presence (e.g., face-to-face),
and users of the technologies or media select the specific medium that they perceive
to have the highest social presence. In other words, users’ perceptions of social
presence affect technology adoption motives and outcomes (Perse & Courtright,
1993; Rice, 1993). For instance, Perse, Burton, Kovner, Lears, and Sen (1992) found
23
that college students’ rating of computers in social presence and their use have a
linear relationship.
Similar to the social presence model, media richness theory (Daft & Lengel,
1984) proposes that individuals distinguish communication technologies or media
from “lean” to “rich,” based largely on the intrinsic properties such as their speed of
feedback, variety of channels, personalness of source, and richness of language used.
More specifically, according to the theory, there are four factors that influence media
richness: 1) the ability of the medium to transmit multiple cues (e.g., vocal inflection,
gestures); 2) immediacy of feedback; 3) language variety; and 4) the personal focus
of the medium. Depending on what kind of properties a medium possesses, the
medium can be characterized as “lean” or “rich.” Thus, different technologies or
media are ranked on how rich they are, usually in the following order (“lean” to
“rich”): formal written communication, personal written communication, electronic
mail, telephone, and face-to-face interaction (Steinfield & Fulk, 1987; Trevino,
Lengel, & Daft, 1987). Thanks to the fact that many studies from media richness
theory were conducted in organizational settings, the theory also claims that
individuals seek to match the richness of a communication medium with the
complexity of the task for which it is used (Flanagin & Metzger, 2001).
Since the introduction of the theory by Daft and Lengel (1984), a number of
studies have tested the propositions of the theory in a variety of contexts. However,
conflicting evidence has been found. Trevino, Lengel, Bodensteiner, Gerloff, and
24
Muir (1990) found that participants in their study ranked the media in the order
predicted by media richness theory. Trevino, Lengel, and Daft (1987) also found that
participants were more likely to use face-to-face interaction for ambiguous
communications and to use written or electronic media for unambiguous
communications, supporting the key argument of the theory. Similarly, Daft, Lengel,
and Trevino (1987) and Russ, Daft, and Lengel (1990) found that, in studies of
hypothetical communication incidents, participants who matched the richness of the
medium to the message content were more likely to be rated as high performers in
their organizations.
By contrast, Rice and Shook (1990) found that media use patterns by job
level were inconsistent with media richness theory’s predictions, while Markus
(1988) found that electronic mail, which was regarded as a lean medium, was used
for communication tasks that involved high degrees of ambiguity. Faced with these
contrasting findings, Fulk and Boyd (1991) emphasized that researchers must first
clarify the core processes that drive media richness theory, and then explain how the
dimensions of richness combine to produce media richness. They also noted that
research on media richness is more supportive to traditional media rather than new
media. In a similar fashion, Markus (1994) claimed that media richness theory is
fairly well able to predict perceptions and use of older communication technologies
but predicts newer media behaviors less reliably.
25
Computer and Internet Self-Efficacies
In addition to the theories discussed above, this study employs computer and
Internet self-efficacies as factors that affect the adoption and use of computer-based
VoIP phone service. Past research has shown that computer self-efficacy plays an
important role in understanding and using computer-related technologies or
applications (Salanova, Grau, Cifre, & Llorens, 2000). Computer self-efficacy,
which refers to an individual’s perceptions about his or her ability to use a computer
to perform a computing task successfully (Compeua & Higgins, 1995), is a construct
derived from the general concept of self-efficacy (Bandura, 1986). According to
Bandura’s (1997) social cognitive theory, self-efficacy is the belief “in one’s
capabilities to organize and execute the courses of action required to produce given
attainments” (p. 3). It should be noted, however, that self-efficacy is not a measure of
skill; instead, it represents individuals’ beliefs that they can achieve desired
outcomes with the skills they possess (Eastin & LaRose, 2000). In plain terms, the
concept of self-efficacy claims that people who have confidence in their ability to do
something are more likely to do well in their task performance.
Since Bandura’s conceptualization of self-efficacy, a number of studies
across a variety of disciplines examined the relationship between self-efficacy with
respect to using computers and a variety of computer behaviors (e.g., Burkhardt &
Brass, 1990; Gist, Schwoerer, & Rosen, 1989; Hill, Smith, & Mann, 1987; Webster
& Martocchio, 1992). Moreover, recent years have seen more serious investigations
26
about the relationship between computer self-efficacy, an application of self-efficacy
to computer use, and computer-related technology behaviors. Findings from these
investigations abound. For example, Marakas, Yi, and Johnson (1998) suggested that
computer self-efficacy affects not only a person’s perceptions of his or her ability to
perform a computing task but also his or her intentions toward future use of
computers. Ellen, Bearden, and Sharma (1991) found that individuals with high
computer self-efficacy exhibited less resistance to technological change and greater
acceptance of new information technologies than those with lower computer self-
efficacy. Similarly, Zhang and Espinoza (1998) demonstrated that students with
higher computer self-efficacy showed greater desire to enroll in computing courses
than those with lower computer self efficacy. In addition, Potosky (2002) found a
positive relationship between computer self-efficacy and training performance in a
database-programming course.
Internet self- efficacy is a more recent construct which specifically focuses on
Internet use. Similar to computer self-efficacy, Internet self-efficacy is Internet
users’ self-perceived confidence in using the Internet to perform tasks successfully.
In addition, Internet self-efficacy is also more about confidence in finding
information or troubleshooting search problems but less about specific Internet skills
such as writing HTML, given that self-efficacy is not a measure of skill (Eastin &
LaRose, 2000). Previous studies found positive relationships between Internet self-
27
efficacy and task performance (Nahl, 1996, 1997) and between Internet self-efficacy
and the amount of Internet use (Ren, 1999).
The reason why the present study distinguishes computer self-efficacy and
Internet self-efficacy is as follows: it is expected that a person who has high
computer self-efficacy is likely to possess high Internet self-efficacy as well.
However, it may not be necessarily true that a person who has high Internet self-
efficacy possesses high computer self-efficacy. Although some people feel confident
about their ability to find information on the Internet, they may feel uncomfortable
troubleshooting computer problems or installing computer hardware.
Based on the theoretical perspectives relevant to the adoption and use of
computer-based VoIP phone service, the next chapter will develop hypotheses and
research questions for the current study.
28
CHAPTER III
HYPOTHESES AND RESEARCH MODEL
This chapter discusses the hypotheses derived from the literature review and
develops a research model for the current study. Drawing from the theoretical
propositions of the TAM, the uses and gratification approach, diffusion theory, and
the theory of media richness, this study proposes the following hypotheses with
respect to adoption and use of computer-based VoIP phone service. In addition, the
study examines the factors that affect non-users’ behavioral intention to use the
technology employing diffusion theory.
Hypotheses from the TAM
Perceived Ease of Use
As already explained in the previous chapter, perceived ease of use refers to
the degree to which an individual believes that using a particular system would be
free of physical and mental effort. A considerable amount of research over the past
decades supported the significant effect of perceived ease of use on behavioral
intention, either directly or indirectly through its effect on perceived usefulness (e.g.,
Agarwal & Prasad, 1999; Davis, Bagozzi, & Warshaw, 1989; Hu, Chau, Sheng, &
Tam, 1999; Jackson, Chow, & Leitch, 1997; Venkatesh, 1999; Yi & Hwang, 2003).
Thus, this study hypothesizes that perceived ease of use of computer-based VoIP
29
phone service would have a positive effect on perceived usefulness and attitude
toward using the technology.
Hypothesis 1a: Perceived ease of use will have a positive effect on the
perceived usefulness of computer-based VoIP phone service.
Hypothesis 1b: Perceived ease of use will have a positive effect on attitude
toward using computer-based VoIP phone service.
Perceived Usefulness
Perceived usefulness is operationalized as the degree to which an individual
believes that using a particular system would enhance his or her job performance.
Users’ behavioral intention to use an information system is fueled, to a large extent,
by the perceived usefulness of the system (Davis et al., 1989). There is also extensive
empirical evidence that supports the significant effect of perceived usefulness on
behavioral intention (e.g., Agarwal & Prasad, 1999; Davis et al., 1989; Hu et al.,
1999; Jackson et al., 1997; Venkatesh, 1999; Yi & Hwang, 2003). However, given
that many people have already been using computer-based VoIP phone service, it
would be less meaningful to examine the effect of perceived usefulness on
behavioral intention: rather, it would be more appropriate to look at the impact of
perceived usefulness on actual system use.
1
As described in Chapter I, there are more
than 100 million people worldwide who use a computer-based VoIP phone service,
Skype, and more than 6 million in the U.S., as of early 2006 (Rampell, 2006).
30
Therefore, an examination of the relationship between perceived usefulness and
actual system use would highlight the variables’ applicability in the context of
computer-based VoIP phone service. Thus, the following hypotheses were proposed.
Hypothesis 2a: Perceived usefulness will have a positive effect on attitude
toward using computer-based VoIP phone service.
Hypothesis 2b: Perceived usefulness will have a positive effect on actual use
of computer-based VoIP phone service.
Attitude toward Using
Although the TAM originally hypothesized that attitude toward using an
information system would lead to behavioral intention to use the system and actual
system use, few empirical studies have tested this proposition. Interestingly, however,
the findings that a user’s adoption and use of a particular communication technology
or medium is attributable to attitudes toward the technology or medium have been
discussed by the uses and gratifications approach (e.g., Palmgreen & Rayburn II,
1982; Rubin, 1986). In addition, the relationship between motivations and attitude
toward a medium has also been discussed from the perspective of the media effects
research tradition (Rayburn II, 1996). It is also notable that the theory of reasoned
action, which has been a theoretical root for the TAM, also claims that an
individual’s own beliefs or attitudes are a driver of a specific behavior (Ajzen &
Fishbein, 1980). In other words, attitude positively affects behavior or behavioral
31
intentions (Ajzen & Fishbein, 1980). Thus, in the context of computer-based VoIP
phone service, attitude toward using the technology was hypothesized to have a
positive impact on actual use of the technology.
Hypothesis 3: Attitude toward using computer-based VoIP phone service will
have a positive effect on actual use of the technology.
Hypotheses with Independent Factors
This study classifies three different types of independent variables
(exogenous variables in structural equation modeling): 1) individual differences, 2)
systems characteristics, and 3) motivations. These types of independent variables are
expected to influence actual use of computer-based VoIP phone service. Dillon and
Watson (1996), in the context of human computer interaction, reviewed individual
differences and concluded that predictive power could be gained by incorporating
individual differences. In a similar research setting, Miller and Thomas (1999)
identified interface characteristics as a major component of effective human
computer interaction. Thong, Hong, and Tam (2002) identified three different sets of
independent factors including interface characteristics, organizational context, and
individual differences in their investigation of the adoption of digital library systems.
Similarly, Hong, Thong, Wong, and Tam (2002) examined the adoption and use of
digital library systems with two distinctive predictors, individual differences and
system characteristics.
32
Following these previous studies, the current study identifies three types of
predictors. First, the predictors of individual differences in the present study include:
1) computer self-efficacy; 2) Internet self-efficacy; 3) technology cluster; 4)
innovative attitude; and 5) communication needs. The last three individual difference
variables are from diffusion theory.
Second, the predictors of system characteristics include: 1) perceived cost
effectiveness of computer-based VoIP phone service; 2) perceived quality of
computer-based VoIP phone service; 3) system functions; and 4) media richness.
The first three predictors are derived from the characteristics of computer-based
VoIP phone service, which are quite different from those of regular phone services.
Finally, a third set of predictors is about motivations from the uses and
gratifications approach. Although the variable of motivations can be classified as
another type of individual difference variable, this study separated the motivation
variables because motivation itself may have several different types and
subcategories. However, it is hard to predetermine what kind of motivations would
affect adoption and use of computer-based VoIP phone service. As will be discussed
later, this study will propose a research question to explore possible motivations for
using computer-based VoIP phone service, and then the motivations will be
identified from the survey question items that ask users’ specific motivations for
using the technology.
33
Computer and Internet Self-Efficacies
Research on computer-aided technology emphasizes an important role played
by computer self-efficacy in understanding and using computer-related technologies
or applications (Salanova, Grau, Cifre, & Llorens, 2000). In addition, studies that
utilized the TAM also claimed that computer self-efficacy would affect behavioral
intention through perceived ease of use (Thong et al., 2002). Moreover, various
studies have documented that computer self-efficacy can influence system usage
through behavioral intention (e.g., Compeau, Higgins, & Huff, 1999; Hill, Smith, &
Mann, 1987; Igbaria, Guimaraes, & Davis, 1995; Venkatesh & Davis, 1996).
Similarly, literature in library and information science also indicates that computer
literacy increases usage of information retrieval systems (Davies, 1997; Jacobson &
Fusani, 1992; Mark & Jacobson, 1995). Thus, it is expected that computer self-
efficacy facilitates people’s perception of ease of use with respect to computer-based
VoIP phone service. In the same fashion, Internet self-efficacy is also expected to be
a positive predictor for perceived ease of use of computer-based VoIP phone service.
Hypothesis 4a: Computer self-efficacy will have a positive effect on
perceived ease of use of computer-based VoIP phone service.
Hypothesis 4b: Internet self-efficacy will have a positive effect on perceived
ease of use of computer-based VoIP phone service.
34
Technology Cluster
The uses and gratifications approach claims that each communication
medium and technology competes with other forms of communication or functional
alternatives as a supplement, complement, or substitute (Rosengren & Windahl, 1972;
Rubin, 2002). For instance, the Internet is a functional alternative to face-to-face
communication for those who are anxious about interpersonal interaction
(Papacharissi & Rubin, 2000) or when face to face communication is not available or
inconvenient to the users. However, when it comes to the adoption and use of media
or technologies, technological systems are rarely adopted in isolation. Rather, as
claimed in the previous chapter, adoption of a technology is likely to be stimulated
by use of functionally similar technologies (Atkin & LaRose, 1994; LaRose & Atkin,
1992). Neuendorf, Atkin, and Jeffres (1998), for instance, applied Rogers’ notion of
technology cluster to the adoption of audiotext information services, and found that
the use of audiotext was related to functionally similar technologies such as
videotext, ATMs, and 800 numbers. The concept of technology cluster leads to the
hypotheses in which a positive relationship is expected between the use of other
technology products and perception of ease of use and usefulness in using computer-
based VoIP phone service.
Hypothesis 5a: People who own more technology products will exhibit a
greater perceived ease of use of computer-based VoIP phone service.
35
Hypothesis 5b: People who own more technology products will exhibit a
greater perceived usefulness of computer-based VoIP phone service.
Innovative Attitude
Past diffusion studies have proved that one of the distinguishable
characteristics between earlier adopters of a new technology and later adopters or
non-adopters is the degree of their adoptive innovativeness. Accordingly, people’s
innovate attitude has been utilized as a personal variable in investigations of new
technology adoption (Lin & Jeffres, 1998). For example, Lin (1998) reported that
computer adopter groups presented the highest degree of need for innovativeness
(e.g., willingness to learn new ideas, willingness to explore new technology, and
keeping up with new technology) compared with likely-adopters or non-adopters.
That is, an individual who has a strong innovative attitude is more likely to perceive
a new technology easier to use and more useful if it provides new features and
functions. Also, she or he is more likely to show corresponding behavioral patterns
(Lin & Jeffres, 1998). Drawing from these discussions, the following hypotheses
deal with people’s innovative attitude in the adoption of computer-based VoIP phone
service.
Hypothesis 6a: People’s innovative attitude will have a positive effect on
perceived ease of use of computer-based VoIP phone service.
36
Hypothesis 6b: People’s innovative attitude will have a positive effect on
perceived usefulness of computer-based VoIP phone service.
Hypothesis 6c: People’s innovative attitude will have a positive effect on
actual use of computer-based VoIP phone service.
Communication Needs
As explained in the previous chapter, research on communication technology
adoption indicates that users’ needs are primary determining factors (Neuendorf,
Atkin, & Jeffres, 1998). In addition, a number of studies have suggested that users’
communication needs are a powerful determinant of adoption of the Internet (James,
Wotring, & Forrest, 1995), computers (Perse & Courtwright, 1993), bulletin boards
(Rafaeli & LaRose, 1993), videotext (Reagan, 1987; Lin, 1994b), audio information
services (LaRose & Atkin, 1992; Neuendorf, Atkin, & Jeffres, 1998), cable (Jacobs,
1995; LaRose & Atkin, 1988; Reagan, 1991), and ISDN (Jeffres & Atkin, 1996).
Thus, it is expected that the more users have communication needs, the more they
are likely to perceive usefulness of computer-based VoIP phone service and the more
they are likely to use the technology. The following hypotheses were proposed:
Hypothesis 7a: People’s communication needs will have a positive effect on
perceived usefulness of computer-based VoIP phone service.
Hypothesis 7b: People’s communication needs will have a positive effect on
actual use of computer-based VoIP phone service.
37
Perceived Cost Effectiveness
In the realm of diffusion theory, cost has almost always been a primary factor
in the adoption of an innovation (Reagan, 2002). For average technology users or
customers, early adoption of an innovation is generally costly and often unaffordable
(Kang, 2003). As described earlier, however, no cost or at least low cost is one of the
major advantages of computer-based VoIP phone service over regular phone systems
including landline and cellular phones. Thus, it is expected that users’ perception of
the low cost of computer-based VoIP phone service will positively affect perceived
usefulness of the technology, and ultimately lead to actual use of it.
Hypothesis 8a: Perceived cost effectiveness of computer-based VoIP phone
service will have a positive effect on perceived usefulness of the technology.
Hypothesis 8b: Perceived cost effectiveness of computer-based VoIP phone
service will have a positive effect on actual use of the technology.
Perceived Quality
Computer-based VoIP phone service has significantly improved sound
quality during the last couple of years in conjunction with increased broadband
Internet access by cable modem or DSL. However, quality here does not mean an
absolute level of quality. Rather, it is an acceptable level of quality given the
service’s cost, or a comparable quality in relation to alternative means of making
38
calls. In other words, it is about how users of computer-based VoIP phone service
perceive the quality of the technology. It is expected that users’ perception of the
improved quality of computer-based VoIP phone service in recent years will
facilitate people’s perceived usefulness of the technology.
Hypothesis 9: Perceived quality of computer-based VoIP phone service will
have a positive effect on perceived usefulness of the technology.
System Functions
What kind of new and unique functions a new communication technology
provides would be an important factor for the technology to be widely adopted and
disseminated. According to the literature on diffusion theory, relative advantage or
perceived utility is one of the five dominant attributes of innovations; relative
advantage, complexity, compatibility, trialability, and observability (Rogers &
Shoemaker, 1971). Rogers (1995) also noted that greater perceived utilities provided
by a new technology would increase the probability that the technology would be
adopted. For instance, LaRose and Atkin (1991) demonstrated that people’s intention
to adopt pay-per-view services was most strongly associated with its perceived
benefits such as lack of commercials and convenient access. In the case of computer-
based VoIP phone service, there are a couple of unique and valuable functions
including video conversation, conference calling, data or file transmission, and
integration with instant messaging services, as described in Chapter I. It is expected
39
that these functions of computer-based VoIP phone service will enhance users’
perception of the technology’s usefulness. Thus, the following hypothesis was
proposed.
Hypothesis 10: System functions of computer-based VoIP phone service will
have a positive effect on perceived usefulness of the technology.
Media Richness
Although recent research suggests that such factors as assessment of needs
fulfillment, appropriateness, and peer evaluations of technologies or media provide a
better explanation for adoption and use of the technologies or media (Flanagin &
Metzger, 2001), a considerable number of studies indicate that media richness could
be also an important system characteristic of communication technologies or media.
However, as discussed in the previous chapter, there have been inconsistent findings
with respect to the effects of media richness on adoption and use of communication
technologies or media. Some studies have supported the propositions of media
richness theory (e.g., Daft, Lengel, & Trevino, 1987; Russ, Daft, & Lengel, 1990;
Trevino, Lengel, Bodensteiner, Gerloff, & Muir, 1990; Trevino, Lengel, & Daft,
1987), whereas other studies have provided contrasting findings (e.g., Boyd, 1991;
Markus, 1988; Rice & Shook, 1990) or cast doubt on the applicability of the theory
to new technologies or media (e.g., Markus, 1994). Thus, the current study set up the
following research question.
40
RQ 1: How does media richness of computer-based VoIP phone service affect
adoption and use of the technology?
Motivations
As illustrated in Chapter II, the uses and gratifications approach presumes
that people’s technology or media selection is motivated by the expectation that it
will fulfill their needs (Rosengren, 1974; Rubin, 2002), and hence, they are assumed
to exhibit motivations to use a particular technology or medium (Infante, Rancer, &
Womack, 1993). According to this proposition, users of computer-based VoIP phone
service are also expected to have specific motivations to adopt and use the
technology in the ever-changing technology/media environment. However, it is hard
to know what kind of motivations users of computer-based VoIP phone service
would have a priori, given that each new technology or medium has its own unique
characteristics that meet different types of motivations. For instance, Leung (2001)
and Leung and Wei (1999, 2000) found a motivation to be fashionable among users
of pagers, cellular phones, and ICQ, which is quite different from other motivations
examined for other technologies. Based on this understanding, the current study set
up the following research question.
RQ 2: What motivations are related to computer-based VoIP phone service
and how do they affect adoption and use of the technology?
41
To sum up, integrating the literature and hypotheses described above, the
proposed research model in this study is presented in Figure 3-1.
42
Figure 3-1. Hypothesized Research Model.
Innovative
attitude
Comm needs
Perceived cost
effectiveness
Perceived
quality
System
functions
Media
richness
Motivations
Perceived
ease of use
Perceived
usefulness
Attitude
toward using
Actual
system use
H4a
H4b
H5a
H5b
H6a
H6b
H6c
H7a
H7b
H8a
H8b
H9
H10
H1a
H1b
H2a
H2b
RQ1
RQ2
Computer
self-efficacy
Internet
self-efficacy
Technology
cluster
H3
43
Hypotheses for Non-Users
Thus far, I have developed the hypotheses for users of computer-based VoIP
phone service. Given that the technology is a new innovation that has been rapidly
diffused in recent years, however, it would be equally interesting to examine the
factors that predict non-users’ behavioral intention to use the technology in the future.
In order to capture such factors, this study employs two sets of variables: 1)
demographics that have been utilized in the diffusion research, and 2) individual
difference variables that were applied for the hypotheses for users in the previous
section. The following are the reasons of employing only individual difference
variables, among the three sets of variables for users (i.e., individual differences,
system characteristics, and motivations), for the hypotheses for non-users. First, non-
users may not be familiar with the functions of computer-based VoIP phone service,
which in turn may not generate meaningful findings from the variables of system
characteristics. And second, related to the first reason, since non-users may not be
familiar with the functions of the new innovation, they are unlikely to have
developed specific motivations for using the technology.
Demographics
A number of studies that used diffusion theory as their theoretical framework
have focused on demographic variables to identify early adopters of innovations
(Rogers, 1983, 1995, 2003). Rogers (1995) claims that early adopters of new
44
communication technologies are likely to be younger, to be better educated, and to
have higher income than later adopters or non-adopters. Past studies have supported
the role of demographic variables in the adoption and use of innovations. For
instance, Dutton, Rogers, and Jun (1987) argued that social status was a central
determinant of adoption and use of personal computers and cable technologies. Lin
(1998) also found that the adopters of personal computers were younger, more
educated, and more upscale than likely adopters or non-adopters. Thus, the following
hypotheses with respect to demographics were proposed.
Hypothesis 11a: Age will be a negative predictor for non-users’ behavioral
intention to use computer-based VoIP phone service in the future.
Hypothesis 11b: Education will be a positive predictor for non-users’
behavioral intention to use computer-based VoIP phone service in the future.
Hypothesis 11c: Income will be a positive predictor for non-users’
behavioral intention to use computer-based VoIP phone service in the future.
Hypotheses from the Variables of Individual Differences
This study hypothesized that the variables of individual differences would be
predictors for adoption and use of computer-based VoIP phone service (i.e.,
computer self-efficacy, Internet self-efficacy, technology cluster, innovative attitude,
and communication needs). It is also expected that these variables affect non-users’
45
behavioral intention to use computer-based VoIP phone service in the future. Thus,
the following hypotheses were set forth for non-users of the technology.
Hypothesis 12: Computer self-efficacy will be a positive predictor of non-
users’ behavioral intention to use computer-based VoIP phone service in the
future.
Hypothesis 13: Internet self-efficacy will be a positive predictor of non-users’
behavioral intention to use computer-based VoIP phone service in the future.
Hypothesis 14: Technology cluster will be a positive predictor of non-users’
behavioral intention to use computer-based VoIP phone service in the future.
Hypothesis 15: Innovative attitude will be a positive predictor of non-users’
behavioral intention to use computer-based VoIP phone service in the future.
Hypothesis 16: Communication needs will be a positive predictor of non-
users’ behavioral intention to use computer-based VoIP phone service in the
future.
46
Chapter III Endnotes
1. In fact, many studies that empirically tested the TAM did not examine actual
system use, which had been identified as the final construct in the original TAM’s
path model (e.g., Chau & Hu, 2002; Hong et al., 2002; Thong et al., 2002).
47
CHAPTER IV
RESEARCH METHOD
This chapter illustrates data collection methods and analysis procedures used
to test the hypotheses and answer the research questions outlined in the previous
chapter. To collect data for the purposes of the current study, an online survey was
conducted. In order to analyze the collected data, I conducted structural equation
modeling (SEM) and multiple regression analyses.
Sampling
This study used an online survey, having all Internet users as the population.
Given that users of computer-based VoIP phone service need to have an Internet
connection, it is not only appropriate to have all Internet users as the population but
also reasonable to employ an online survey as the method. In order to collect data
from respondents, this study used an online panel provided by the Media Research
Lab at the University of Texas at Austin. The panel is an opt-in, informed consent,
privacy-protected resource of over 20,000 respondents who regularly participate in
Web-based research (Daugherty, Lee, Kim, & Outhavong, 2005). The panel was
created to provide academic scholars conducting social science research with access
to adult participants, and it has been composed of registered persons who have
agreed to participate in online research (Daugherty, Lee, Kim, & Outhavong, 2005).
48
According to the Media Research Lab, study participants are randomly selected
unless researchers request a different method. The Lab’s management process,
however, is designed to minimize researchers’ individual requests sent to panel
members, in order to avoid panel members’ burnout and annoyance, which may
cause members to drop out or not to participate in studies (Daugherty, 2007).
Online Survey over Other Methods
It is necessary to discuss advantages and disadvantages of online surveys in
order to understand the characteristics and limitations of the sample obtained for the
current study.
Advantages of Online Survey
The online survey method has a couple of advantages over other methods.
First of all, it is easy to access to unique populations (Wright, 2005). By taking
advantage of the ability of the Internet, it is possible to access groups and individuals
who would be difficult, if not possible, to reach through other channels (Garton,
Haythornthwaite, & Wellman, 1999; Wellman, 1997). As mentioned above, users of
computer-based VoIP phone service need to have an Internet connection first of all,
and thus, the population for a study of computer-based VoIP phone service should be,
by nature, the people who use the Internet. Therefore, an online survey would be the
49
best option to conduct the current study given that online surveys can be conducted
with the people who use the Internet.
Other advantages of online surveys include saving time and money (Wright,
2005). In addition, online surveys provide an easier and more immediate means of
response (Flaherty, Honeycutt, & Powers, 1998). Both the request for participation in
an online survey and responses to the online survey can be transmitted via the
Internet in a shorter time compared to mail surveys. Moreover, recent online survey
services or software packages make it possible to easily transfer electronic responses
to a data file ready for statistical analyses, which in turn reduces time spent on
entering and transcribing data. In addition to the advantage of saving time, the online
survey method eliminates or significantly reduces the need for paper, postage,
printing, and other costs compared to traditional paper-and-pencil surveys (Llieva,
Baron, & Healey, 2002; Watt, 1999; Witmer, Colman, & Katzman, 1999; Wright,
2005). Some studies have reported that the cost of using online surveys is estimated
to be between 5% and 20% of paper surveys (Sheehan & Hoy, 1999; Weible &
Wallace, 1998).
Disadvantages of Online Survey
Online surveys have disadvantages as well. The disadvantages are mostly
related to sampling issues. First of all, in online surveys, it is hard to obtain a
sampling frame in which every subject in the population has an equal chance of
50
being selected for participation. Even if an email list can be obtained from the
desired population, there may be some possibility of having people who have
multiple email addresses or invalid/inactive email addresses, which makes random
sampling online problematic (Andrews, Nonnecke, & Preece, 2003; Couper, 2000).
Another problem with online surveys is that reported response rates are
inconsistent (Sheehan, 2001). Some studies have found that response rates in online
surveys are equal to or better than mail surveys (e.g., Stanton, 1998; Thompson,
Surface, Martin, & Sanders, 2003), whereas other studies found lower response rates
(e.g., Smith, 1997; Tse, 1998). To make it worse, spam blocking systems make it
harder for online surveys to reach the target respondents, and consequently, it is
difficult to obtain not only a sufficient number of responses but also representative
responses from the intended population.
Recognizing these weaknesses of online surveys, this study tried to minimize
possible problems by employing an established online panel operated by the
University of Texas, Austin, as mentioned earlier. However, it should be noted that
there still may exist some problems inherent in online surveys.
Survey Administration
The online survey for the current study was conducted in a four-week time
frame from April 2 to April 29, 2007. An email invitation, which included a link to
the survey questionnaire on SurveyMonkey (http://www.surveymonkey.com), was
51
sent on April 2 to 9,000 panel members. However, 2,250 invitations were returned
because they were sent to invalid email addresses, indicating that the number of valid
invitations delivered was 6,750. After one week, the number of responses was 715,
of which the number of computer-based VoIP users was 131. Although the response
rate at this point was more than 10%, the number of users was short of the number
for meaningful statistical analyses. Thus, a follow-up email was sent to the same
panel on April 11. One more week with the same panel provided a total number of
1,024 respondents, of whom the number of computer-based VoIP users was 215.
Aiming to collect data from more than 300 users, a second wave of the online survey
was sent to another panel of 5,000 on April 19. When the survey was closed 10 days
later, the total number of participants was 1,656 of which the number of computer-
based VoIP phone service users was 327. In sum, the email invitations for the current
survey were sent to the total of 11,750, and the number of participants was 1,656, a
response rate of 14.1% (1,656 / 11,750).
The email invitations for the current study were made with a financial
incentive in order to stimulate a high return rate; four cash prizes totaling $150 were
provided to the winners from the pool of respondents. It has been noted, however,
that providing a monetary incentive to raise response rates could raise another
problem. As Wright (2005) properly pointed out, there may be multiple responses
from the same participants who try to increase their chances of winning the prizes.
Nevertheless, financial incentives in survey studies have been not only a very
52
common strategy to increase the response rates but also a way to compensate
respondents for their time and effort in participating in the surveys (Aaker, 1997).
Measurement of Variables
The online survey instrument included the following variables. The specific
questions that measured each variable are described below.
Computer self-efficacy was measured based on the level of agreement,
anchored by a 7-point Likert scale (1 = strongly disagree; 2 = disagree; 3 =
somewhat disagree; 4 = neutral; 5 = somewhat agree; 6 = agree; 7 = strongly agree),
with the following 10 statements
1
:
1) I feel confident using a user’s guide for computer software when help needed;
2) I feel confident using a user’s guide for computer hardware when help
needed;
3) I feel confident learning how to use a variety of technological features of
computer software;
4) I feel confident understanding terms related to computer hardware;
5) I feel confident understanding terms related to computer software;
6) I feel confident troubleshooting computer problems;
7) I feel confident getting software up and running;
8) I feel confident learning to use new computer programs;
53
9) I feel confident learning advanced skills related to programs (software); and
10) I feel confident describing the functions of computer hardware (e.g.,
keyboard, monitors, disk drives, CPU, etc.) (Cronbach’s alpha = 0.96).
Internet self-efficacy was measured with the following statements anchored
by a 7-point Likert scale ranging from “strongly disagree” to “strongly agree”:
1) I feel confident understanding terms related to Internet hardware (e.g., cable
modem, wireless Internet router, etc.);
2) I feel confident understanding terms related to Internet programs (e.g., Web
browser, Java applications, etc.);
3) I feel confident describing the functions of Internet hardware;
4) I feel confident troubleshooting Internet problems;
5) I feel confident explaining why some functions do not work well on the
Internet;
6) I feel confident using the Internet to gather information; and
7) I feel confident learning advanced skills related to a specific Internet program
(e.g., Java, Flash, etc.) (Cronbach’s alpha = 0.93).
Technology cluster was measured by asking respondents whether they own
or subscribe to any of a list of 10 communication technology products. They
included a personal computer (desktop or laptop), broadband Internet access (at
54
home or at work), a PDA, cell phone, video game player (e.g., PlayStation, Xbox,
etc.), DVD player (including a computer-attached DVD player), digital camera
(including a cellphone-attached camera), camcorder, device for podcasting (e.g.,
iPod), and a DVR (e.g., TiVo). These 10 items were coded as dummy variables (0 =
no, 1 = yes). The number of items owned was then summed to reflect the extent of
each respondent’s technology ownership.
Innovative attitude was measured by asking respondents the following four
questions:
1) On a scale of 1 to 7 where 1 means not technically progressive at all, or low
tech, and 7 means very technically progressive, or high tech, how would you
rate yourself?
2
;
2) I enjoy trying out new technologies;
3) I like to introduce new technologies to my friends or colleagues; and
4) I consider myself a modern person who is usually up-to-date on new
technologies.
3
Again, respondents were told to respond on a scale of 1 to 7, where 1 means
strong disagreement, 7 means strong agreement, and 4 is neutral, for the last three
statements (Cronbach’s alpha = 0.90).
55
Communication needs were measured with the following three statements
anchored by a 7-point Likert scale ranging from “strongly disagree” to “strongly
agree”
4
:
1) I spend a lot of time talking with friends and associates about things I find
interesting, like hobbies, personal interests, or current issues;
2) I often feel the need to express myself to others; and
3) If there is some way I can send a message to others, I will do it regularly
(Cronbach’s alpha = 0.80).
The questions for motivations were gleaned from past studies that
investigated various motivations for using new communication technologies
(Dimmick, Sikand, & Patterson, 1994; Leung, 2001; Leung & Wei, 2000; O’Keefe
& Sulanowski, 1995). Then, the questions were modified for the current study of
computer-based VoIP phone service. Since it is not clear what motivations users of
computer-based VoIP phone service have, the questions were factor-analyzed for
further statistical analyses (see Chapter V for the result of an exploratory factor
analysis). Nineteen statements were used to measure motivations, anchored by a 7-
point Likert scale ranging from “strongly disagree” to “strongly agree” (see
Appendix survey questionnaire section 7).
56
Perceived cost effectiveness was measured with the following two statements
anchored by a 7-point Likert scale ranging from “strongly disagree” to “strongly
agree”:
1) It is cheaper to use computer-based VoIP phone service compared to
traditional services; and
2) I have saved a lot of money since I used computer-based VoIP phone service
(Cronbach’s alpha = 0.72).
Perceived quality was an index composed of the following five statements
anchored by a 7-point Likert scale ranging from “strongly disagree” to “strongly
agree”:
1) When talking through computer-based VoIP phone service, there is no delay
in hearing the voice from the other side;
2) When talking through computer-based VoIP phone service, it is clear enough
to hear the voice from the other side;
3) The quality of computer-based VoIP phone service is better than that of
landline-based phone service;
4) The quality of computer-based VoIP phone service is better than that of
mobile phone service; and
5) The quality of calls via computer-based VoIP phone service is below my
expectation (reverse-coded) (Cronbach’s alpha = 0.85).
57
System functions were measured with the following six statements anchored
by a 7-point Likert scale ranging from “strongly disagree” to “strongly agree”:
1) Video conversation with a webcam makes computer-based VoIP phone
service more valuable;
2) Computer-based VoIP phone service is valuable because I can chat with one
or more persons during calls;
3) Computer-based VoIP phone service is valuable because I can do other tasks
on the computer simultaneously even during conversation with people;
4) Computer-based VoIP phone service is valuable when I make long-distance
calls;
5) Computer-based VoIp phone service is valuable when I make international
calls; and
6) Computer-based VoIp phone service is valuable because I can attach and
send files or photos (Cronbach’s alpha = 0.75).
Media richness was measured with the following statements anchored by a 7-
point Likert scale ranging from “strongly disagree” to “strongly agree”
5
:
1) Computer-based VoIP phone service helps me communicate quickly with my
communication partner(s), giving and receiving timely feedback;
58
2) Computer-based VoIP phone service helps me and my communication
partner(s) better understand each other;
3) With computer-based VoIP phone service, I can easily deliver a variety of
different cues beyond spoken messages;
4) With computer-based VoIP phone service, I can easily customize messages to
my personal circumstances;
5) I feel closer to the person I am talking to when I use computer-based VoIP
phone service than when I use traditional phone service;
6) I feel more casual when I use computer-based VoIP phone service than when
I use traditional phone service;
7) I am involved in less conflict during conversation when I use computer-based
VoIP phone service than when I use traditional phone service; and
8) I tend to talk about less official things when I use computer-based VoIP
phone service than when I use traditional phone service (Cronbach’s alpha =
0.88).
Perceived ease of use was measured with the following five statements
anchored by a 7-point Likert scale ranging from “strongly disagree” to “strongly
agree”:
1) It is easy to have an account and phone number from computer-based VoIP
phone service;
59
2) Using computer-based VoIP phone service does not require a lot of effort;
3) I find computer-based VoIP phone service easy to use;
4) I find it easy to get computer-based VoIP phone service to do what I want it
to do; and
5) Using computer-based VoIP phone service is a convenient way to make
phone calls (Cronbach’s alpha = 0.91).
Perceived usefulness was an index composed of the following four
statements anchored by a 7-point Likert scale ranging from “strongly disagree” to
“strongly agree”:
1) I find computer-based VoIP phone service to be useful for my personal
communication with others;
2) Using computer-based VoIP phone service improves my personal
communication with others;
3) Using computer-based VoIP phone service increases my productivity; and
4) Using computer-based VoIP phone service enables me to make my calls
more effectively (Cronbach’s alpha = 0.85).
Attitude toward using the technology was measured with the following three
statements anchored by a 7-point Likert scale from “strongly disagree” to “strongly
agree”:
60
1) I use computer-based VoIP phone service as much as possible;
2) I use computer-based VoIP phone service whenever it is available;
3) Computer-base VoIP phone service is my first choice when I want to make a
call (Cronbach’s alpha = 0.89);
Actual system use was measured by the following question: If you are
currently using computer-based VoIP phone service, approximately how many hours
do you use the service in a typical week? The participants were asked to fill in with
the number of hours.
Behavioral intention to use for non-users was measured with the following
two statements anchored by a 7-point Likert scale ranging from “strongly disagree”
to “strongly agree”:
1) I will use computer-based VoIP phone service in the near future.
2) I will not use computer-based VoIP phone service as long as regular phone
services (landline or mobile phone) are available (reverse coded) (Cronbach’s
alpha = 0.75).
In addition to the measures of these variables, demographic variables such as
gender, race, income, education, and the variables for computer and Internet use
61
including years of using computers and time spent on using the Internet per day were
also measured.
Data Analysis
The data analyses for the current study have two parts: analysis for users and
analysis for non-users of computer-based VoIP phone service. For the analysis for
users, the current study employs three sets of independent variables (exogenous
variables for structural equation modeling analyses): 1) individual differences; 2)
system characteristics; and 3) motivations. For the analysis for non-users, however,
this study uses the variables of individual differences only. As described in the
previous chapter, non-users may not be familiar with the system characteristics of
computer-based VoIP phone service, and thus, they are unlikely to have developed
specific motivations for using the technology.
The variables of individual differences include: computer self-efficacy,
Internet self-efficacy, technology cluster, innovative attitude, and communication
needs, which were described above. The variables of system characteristics include:
perceived cost effectiveness, perceived quality, system functions, and media richness.
Finally, motivation variables will be factor-analyzed in the next chapter as
mentioned earlier.
For the analysis for users, this study used structural equation modeling
(Bollen, 1989; Jöreskog & Sörbom, 1996) to test the theoretical model presented in
62
Figure 3-1. The chi-square goodness-of-fit test is the traditional criterion employed
to determine acceptance or rejection of the hypothesized model. A good fit is
represented by a nonsignificant chi-square value (i.e., the difference between
theoretical and empirical models, between expected and observed relationships, can
be attributed to chance alone). However, chi-square is strongly affected by sample
size and is difficult to interpret (Jöreskog & Sörbom, 1996). Thus, researchers are
urged to use multiple criteria. The following criteria were used to evaluate how well
the proposed model fits the observed correlation matrix (Bentler, 1988): 1) the chi-
square statistic (nonsignificant); 2) the goodness-of-fit index (GFI) and the adjusted
goodness-of-fit index (AGFI) (close to 1.00); 3) the Bentler-Bonett Normed Fit
Index (NFI, greater than .90); 4) the Comparative Fit Index (CFI, greater than .90);
and 5) the root mean square error of approximation (RMSEA, less than .05).
Additionally, this study used the ratio of chi-square to degrees of freedom
and the chi-square difference test to assess the hypothesized model. When the ratio
of chi-square to degrees of freedom is less than 5, it is conventionally accepted as a
good fit (Wheaton, Muthen, Alwin, & Summers, 1977). In the chi-square difference
test, “the difference between two chi-squares (
2
d
) is itself distributed as chi-square
with degrees of freedom equal to the difference in degrees of freedom of the two
models (df
d
)” (Monge, Bachman, Dillard, & Eisenberg, 1982, pp. 517-522). The
interpretation of the chi-square difference test is that a significant decrease in chi-
square relative to a decrease in degrees of freedom indicates an improvement in the
63
fit of the model (Monge, Bachman, Dillard, & Eisenberg, 1982). Finally, the
significance of individual paths was assessed using t ratios.
The unfolding procedure this study employed began by testing the
hypothesized structural model using LISREL 8.80, a statistical program that tests
structural equation models. Then, all nonsignificant paths were deleted and the
revised structural path model was obtained.
For the analysis of non-users, this study used multiple regression analyses
having the individual difference variables as independent variables and behavioral
intention to use computer-based VoIP phone service as the dependent variable, in
order to look at the factors that might affect non-users’ future intention to use the
technology.
64
Chapter IV Endnotes
1. The items for computer self-efficacy were suggested by Compeau and Higgins
(1995), Eastin and LaRose (2000), the GVU 10th survey (GVU, 1999), and Nahl
(1996).
2. This statement was modified from Kang (2002).
3. The last two statements were modified from Atkin, Jeffres, and Neuendorf (1998)
and Jeffres and Atkin (1996).
4. These statements were modified from Atkin, Jeffres, and Neuendorf (1998) and
Jeffres and Atkin (1996).
5. These statements were modified from Dennis and Kinney (1998).
65
CHAPTER V
RESULTS
This chapter presents the results of the current study. First, descriptive
statistics from the obtained data are presented. Second, the structural equation
modeling analyses with the data from users of computer-based VoIP phone service
are discussed. Then, the hypotheses developed in Chapter III are tested. The revision
of the model from the structural equation modeling analyses and its processes are
explained. Finally, the factors that affect non-users’ behavioral intention to use the
technology in the future are explored.
Descriptive Statistics
As mentioned in the previous chapter, the total number of participants was
1,656 and the number of computer-based VoIP phone service users among the
participants was 327 (19.74%). It can be said that these 19.74% of users from the
whole participants are located between the categories “early adopters” (13.5%) and
“early majority” (34%), according to Rogers’ (1995) classification of the five
categories of adopters, indicating that computer-based VoIP phone service is still in
an early stage of adoption.
66
Users of Computer-Based VoIP Phone Service
Among 327 users from the survey, only 309 users were valid participants for
statistical analyses. The rest did not answer more than half of the survey questions,
and thus they were deleted for further analyses. Of these 309 users there were 162
female participants (52.4%) and 144 male participants (46.6%), while three did not
indicate their gender. The average age of the participants was 40.02 (SD = 11.52).
With respect to the distribution of ethnicity, the number of “White, not of Hispanic
origin” was 222 (71.8%), “African American, not of Hispanic origin” was 9 (2.9%),
“Hispanic” was 16 (5.2%), “Asian or Pacific Islander” was 43 (13.9%), “Other” was
17 (5.5%), and two participants did not indicate their ethnicity.
With respect to annual income, the sample had a median income category of
“$40,001 to $60,000.” Seventy-seven computer-based VoIP users (24.9%) reported
that their income was in the category “$20,001 to $40,000,” while 58 users (18.8%)
indicated that their annual income was between $40,001 and $60,000. Forty-three
users (13.9%) reported income of “$60,001 to $80,000,” and 36 users (11.7%)
indicated that their income was in the range “$80,001 to $100,000.” Thirty-seven
users (12%) indicated that their income was more than $100,000.
As for the level of education, 35.9 % (111) of the users indicated that they
received a college degree (either 2 years’ associate degree or 4 years’ bachelor’s
degree), followed by “some college, no degree” (18.8%, 58 users), and “master’s
degree” (18.1%, 56 users).
67
With respect to the use of computer-based VoIP phone service, it was found
that users employed the technology more than 11 times per week on average (M =
11.58, SD = 32.90), while the median for the frequency of using the technology was
4. The time spent with the technology was more than 5 hours per week on average
(M = 300.31, SD = 553.05 in minutes), while the median for the time using the
technology was 2 hours (120 in minutes). In addition, users spent about 30 minutes
for each call (M = 30.81, SD = 47.52), while the median time using the technology
for each call was 20 minutes. Meanwhile, in terms of the experience of using
computer-based VoIP phone service, about half of the users have been using the
technology for less than 1 year (153 users, 49.5%), while about 80% of the users
(78.9%) have been using the technology for less than 2 years (244 users). Only
20.4% of the users (63) have been using it more than 2 years. Two users did not
answer the question about the experience of using the technology. Table 5-1
summarizes users’ adoption and use of computer-based VoIP phone service.
Non-Users of Computer-Based VoIP Phone Service
As described earlier, there were 1,329 non-users of computer-based VoIP
phone service among the participants in this study. The survey results from these
1,329 non-users indicate that there were 864 female participants (65.8%) and 450
male participants (34.2%), while 15 participants did not indicate their gender.
Compared to users of computer-based VoIP phone service, the ratio of female
68
participants who did not use computer-based VoIP was much higher. Average age of
non-users was 43.42 (SD = 12.65), indicating that non-users were slightly older than
users. Regarding the distribution of ethnicity, the number of participants who were
“White, not of Hispanic origin” was 1,101 (83.4%), “African American, not of
Hispanic origin” was 49 (3.7%), “American Indian or Alaska native” was 7 (0.5%),
“Hispanic” was 45 (3.4%), “Asian or Pacific Islander” was 73 (5.5%), “Other” was
45 (3.4%), and 9 participants did not report their ethnicity.
With respect to annual income, non-users had a median income category of
“$40,001 to $60,000” similar to users. Two hundred and thirty non-users of
computer-based VoIP service (17.3%) reported that their income was in the category
“less than 20,000.” Two hundred and ninety eight non-users (22.4%) reported that
their income was in the category of “$20,001 to $40,000,” while 291 non-users
(21.9%) indicated that their annual income was between $40,001 and $60,000. One
hundred and ninety-four non-users (14.6%) reported “$60,001 to $80,000,” and 127
non-users (9.6%) indicated “$80,001 to $100,000.” One hundred and sixty five non-
users (12.4%) indicated that their income was more than $100,000.
As for the level of education, 36.2 % (481) of the non-users reported that they
received a college degree (either 2 years’ associate degree or 4 years’ bachelor’s
degree), followed by “some college, no degree” (19.5%, 259 non-users), “master’s
degree” (14.1%, 187 non-users), and “high school graduates” (13.5%, 180 non-users).
These descriptive statistics indicate that there are no significant differences between
69
users and non-users of computer-based VoIP phone service with respect to
demographics except for age: users of computer-based VoIP phone service were
younger (M = 40.02, SD = 11.52) than non-users (M = 43.42, SD = 12.65), t(496.07)
= -4.58, p < .001.
70
Table 5-1
Adoption and Use of Computer-Based VoIP Phone Service
Items N Frequency
(%)
M SD Median
Experience of using computer-based VoIP phone service
Less than 6 months
From 6 months to 1 year
From 1 year to 1 and half year
From 1 and half year to 2 years
From 2 years to 2 and half years
From 2 and half years to 3 years
More than 3 years
Times using computer-based VoIP phone service per week
Time spent on using computer-based VoIP phone service per week
(minutes)
Time spent on using computer-based VoIP phone service per call
(minutes)
307
309
309
309
76 (24.6)
77 (24.9)
51 (16.5)
40 (12.9)
23 (7.4)
18 (5.8)
22 (7.1)
11.58
300.31
30.81
32.91
553.05
47.52
4.00
120.00
20.00
71
Comparison between Users and Non-Users
In addition to demographic variables, there are a few additional variables in
the current study that need to be compared between users and non-users of computer-
based VoIP phone service. These variables, including time spent on computer and
the Internet as well as individual differences (i.e., computer and Internet self-
efficacies, technology cluster, innovative attitude, and communication needs), were
compared based on t tests.
With respect to computer and Internet use, 64.1% (198) of users of computer-
based VoIP phone service reported that they have used a computer more than 10
years, while 46.9% (145) of users indicated that they have used the Internet more
than 10 years. Almost 90% (88.7%, 274 users) reported that they have used a
computer more than 6 years, while 82.2% of users (254) indicated that they have
used the Internet more than 6 years. The participants also spent almost 5 hours using
the Internet per day (M = 4.90, SD = 3.27).
In the case of non-users of computer-based VoIP phone service, 66.3% (881)
of non-users reported that they have used a computer more than 10 years, while
44.8% (595) of non-users indicated that they have used the Internet more than 10
years. Almost 90% (89%, 1,182 non-users) reported that they have used a computer
more than 6 years, while 83% of non-users (1,103) indicated that they have used the
Internet more than 6 years. The participants also spent slightly more than 4 hours
using the Internet per day (M = 4.15, SD = 2.91). With regard to amount of time
72
using the Internet per day, there was a significant difference between users and non-
users, t(428.86) = 3.71, p < .001.
Meanwhile, with respect to the variables of individual differences in the
current study, there were significant differences between users and non-users of
computer-based VoIP phone service. Users of computer-based VoIP phone service
exhibited higher computer self-efficacy (M = 5.50, SD = 1.02) than non-users (M =
5.21, SD = 1.18), t(517.74) = 4.35, p < .001. Similarly, users of computer-based
VoIP phone service exhibited higher Internet self-efficacy (M = 5.44, SD = 1.03)
than non-users (M = 4.98, SD = 1.18), t(512.23) = 6.86, p < .001. In addition, users
of computer-based VoIP phone service owned more communication technology
devices (M = 6.95, SD = 1.69) than non-users (M = 6.09, SD = 1.70), t(1636) = 8.08,
p < .001. Moreover, users of computer-based VoIP phone service exhibited greater
innovative attitude (M = 5.48, SD = 1.01) than non-users (M = 4.80, SD = 1.21),
t(533.42) = 10.25, p < .001. Finally, users of computer-based VoIP phone service
exhibited greater communication needs (M = 5.39, SD = 1.01) than non-users (M =
5.10, SD = 1.09), t(487.17) = 4.44, p < .001. Based on these findings, it can be said
that users of computer-based VoIP phone service are more confident in using
computers and the Internet, possess more communication technology devices,
believe themselves to be innovative in using communication technologies, and have
greater communication needs compared to non-users.
73
Exploratory Factor Analysis for Motivations
In Chapter IV, this study included 19 questions to explore motivations that
drive people to use computer-based VoIP phone service. In order to search for
underlying structures from those questions that were asked to users of computer-
based VoIP phone service, an exploratory factor analysis was conducted. By using
an orthogonal varimax rotation method, which assumes that all factors are
mathematically independent (Hair, Anderson, Tatham, & Black, 1998), the current
study extracted three motivations for using computer-based VoIP phone service
(motivations for communication, entertainment, and instrumental use). These
motivation items are generally consistent with those found in past studies (e.g.,
Claisse & Rowe, 1987; Fischer, 1988; Keller, 1977; Noble, 1987; Singer, 1981;
Williams, Dordick, & Jesuale, 1985). However, the motivation for fashion, which
had been found in recent studies with new technologies (Leung, 2001; Leung & Wei,
2000), was not separated from the motivation for entertainment in the current study.
Loadings of variables on factors and eigenvalues are presented in Table 5-2.
Based on the exploratory factor analysis, summed scales were made for
subsequent multivariate analyses, that is, structural equation modeling. Cronbach’s
alphas from the summed scales are also presented in Table 5-2. The three variables
derived from the factor analysis were hypothesized to be positive predictors of
perceived usefulness and actual system use, based on the discussions about the uses
and gratifications approach in the previous chapters.
74
Table 5-2
Factor Analysis for Motivations
Factor loadings Questions
1 2 3
Factor 1: Motivation for entertainment
I use computer-based VoIP phone service in order to relieve boredom by calling people.
I use computer-based VoIP phone service because it is entertaining.
I use computer-based VoIP phone service in order to kill time.
I use computer-based VoIP phone service in order to gossip or chat.
I use computer-based VoIP phone service because sometimes I just like to talk.
I use computer-based VoIP phone service because it is a status symbol.
I use computer-based VoIP phone service in order to look cool.
I use computer-based VoIP phone service in order to avoid looking old-fashioned.
I use computer-based VoIP phone service because using it relaxes me.
.797
.752
.748
.702
.678
.655
.623
.600
.528
Factor 2: Motivation for instrumental use
I use computer-based VoIP phone service in order to get information about products and services.
I use computer-based VoIP phone service in order to order products.
I use computer-based VoIP phone service in order to buy tickets for travel or special events.
I use computer-based VoIP phone service in order to schedule appointments.
.898
.886
.873
.839
Factor 3: Motivation for communication
I use computer-based VoIP phone service in order to feel involved with what is going on with other people.
I use computer-based VoIP phone service in order to let others know I care for them.
I use computer-based VoIP phone service in order to communicate with friends and family.
I use computer-based VoIP phone service in order to keep up-to-date on people and events.
I use computer-based VoIP phone service in order to stay in touch with people I do not see very often.
I use computer-based VoIP phone service in order to enjoy the pleasure to talking to people.
.828
.818
.818
.782
.747
.685
Eigenvalue 8.29 3.49 1.89
Cronbach’s alpha .91 .94 .90
75
Analyses of Structural Equation Modeling for Users
Prior to analyses of structural equation modeling, a correlation analysis with
all the variables described in Chapter IV was conducted. From the correlation
analysis, it was found that the variables of computer self-efficacy and Internet self-
efficacy are highly correlated (r = .858, p < .001). It was initially expected that the
two variables would be quite different because confidence in using the Internet
would not necessarily guarantee confidence in using computers including hardware
and software. However, based on the correlation analysis, it was decided that only
Internet self-efficacy would be used for statistical analyses, given that Internet self-
efficacy could be more relevant to the current study of computer-based VoIP phone
service which can be used with an Internet connection.
The correlation matrix of all variables used to test the hypothesized model
developed in Chapter III except for computer self-efficacy is shown in Table 5-3. In
addition, the variables’ means and standard deviations are presented in Table 5-4. All
pairwise associations were positively correlated with one another except for two
associations with technology cluster (i.e., technology cluster and motivation for
communication / technology cluster and system functions) and one association
between innovative attitude and perceived cost effectiveness. None of these
associations, however, was statistically significant. The correlation coefficients
among these variables were less than .60, except for four associations. These
associations include: 1) motivation for communication and attitude toward using the
76
technology (r = .63, p < .01); 2) motivation for entertainment and media richness (r
= .60, p < .01); 3) perceived ease of use and perceived usefulness (r = .64, p < .01);
and 4) perceived usefulness and attitude toward using the technology (r = .61, p
< .01). Among the relatively high correlations between these variables, the
association between perceived ease of use and perceived usefulness has been found
in past studies that used the TAM. Overall, these relationships were not extremely
high in their associations, suggesting that they do not exhibit significant
multicollinearity problems.
Finally, the variable of actual system use showed high degrees of skewness
and kurtosis (skewness: 4.49, kurtosis: 25.07), indicating that a transformation of the
variable is necessary for further statistical analyses. Thus, the common logarithm
(the logarithm having base 10) of the original data was computed in order to achieve
normality.
77
Table 5-3
Zero-Order Correlations (N = 309)
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1. Internet
self-efficacy
1 .23** .59** .27** .21** .15** .14* .14* .20** .28** .30** .28** .29** .24** .14**
2. Technology
cluster
1 .31** .14** -.05 .15** .20** .01 .05 -.01 .19** .02 .06 .11* .10
3. Innovative
attitude
1 .40** .11* .17** .15** -.01 .09 .20** .25** .13* .23** .23** .08
4. Communication
needs
1 .35** .31** .14* .04 .12* .18** .35** .13* .26** .22** .17**
5. Motivation for
communication
1 .47** .28** .49** .41** .37** .46** .49** .59** .63** .28**
6. Motivation for
entertainment
1 .56** .12* .31** .21** .60** .10 .38** .45** .26**
7. Motivation for
instrument use
1 .22** .33** .11* .37** .07 .30** .52** .35**
8. Perceived
cost
1 .34** .40** .18** .44** .42** .49** .30**
9. Perceived
quality
1 .25** .35** .49** .49** .53** .25**
10. System
functions
1 .52** .40** .46** .33** .16**
11. Media
richness
1 .33** .52** .49** .23**
12. Perceived
ease of use
1 64** .45** .12**
13. Perceived
usefulness
1 .61** .31**
14. Attitude
toward using
1 .41**
15. Actual
system use
1
Note. *p < .05, **p < .01 (2-tailed).
78
Table 5-4
Means and Standard Deviations (N = 309)
Variable M SD
Internet self-efficacy 5.44 1.03
Technology cluster 6.95 1.69
Innovative attitude 5.48 1.01
Communication needs 5.39 1.01
Motivation for communication 5.15 1.17
Motivation for entertainment 3.39 1.28
Motivation for instrumental use 3.33 1.67
Perceived cost effectiveness 5.46 1.24
Perceived quality 4.45 1.26
System functions 5.53 .82
Media richness 4.61 1.00
Perceived ease of use 5.77 .99
Perceived usefulness 5.23 1.09
Attitude toward using 4.55 1.55
Actual system use 2.09 .59
Tests of the Overall Model
Maximum likelihood estimation was employed to estimate the hypothesized
research model. The chi-square statistic was significant for the hypothesized model,

2
(26, N = 309) = 250.74, p = .00, and the ratio of chi-square to degrees of freedom
was not acceptable at 9.64 (250.74/26). For other indices, the goodness-of-fit index
(GFI) was .90, while the adjusted goodness-of-fit index (AGFI) was .55. The
Bentler-Bonett Normed Fit Index (NFI) was .90, while the Comparative Fit Index
(CFI) was .90. In addition, the root mean square error of approximation (RMSEA)
was .17. Overall, these summary statistics indicate that the proposed model does not
represent a good fit of the set of hypotheses to the data.
79
With respect to the chi-square difference test, the hypothesized model’s chi-
square statistic was significantly better than that of the null model, which represents
that all variables have no relationship at all. For this model, the chi-square of the null
was 3432.23 at the degrees of freedom of 105. Thus, the chi-square difference was
3181.49 (3432.23 – 250.74), while the difference in the degrees of freedom was 79
(105 – 26), which is significant at both 95% and 99% significance levels, meaning
that the proposed model is significantly better than the null model. However, the
summary statistics described above indicate that a model revision is necessary.
Tests of Hypotheses
Figure 5-1 presents the results for the LISREL analysis of the combined
hypotheses. The first two hypotheses proposed that perceived ease of use would
predict perceived usefulness of computer-based VoIP phone service (Hypothesis 1a)
and attitude toward using the technology (Hypothesis 1b), both with positive signs.
These proposed paths were significant in the hypothesized direction ( = .40, t =
10.53 for Hypothesis 1a; = .11, t = 2.08 for Hypothesis 1b); both Hypothesis 1a
and 1b were supported.
80
Figure 5-1. LISREL Results for the Hypothesized Model.
Note. +p < .10, *p < .05, **p < .01, ***p < .001.
Comm
needs
Motivation
for comm
Motivation
for entertain
Motivation
for inst. use
Perceived
quality
System
functions
Perceived
ease of use
Perceived
usefulness
Actual
system use
.31**
-.04
-.04
-.06
.02
.11+
-.07
.18**
.03
.12*
.19**
.08+
.13**
.40***
.11*
.54***
.09
.14*
-.04
Internet
self-efficacy
Technology
cluster
Innovative
attitude
Perceived
cost
effectiveness
.00
.08+
.10*
.03
Attitude
toward
using
.23**
Media
richness
81
The second two hypotheses proposed that perceived usefulness would be a
positive predictor of attitude toward using computer-based VoIP phone service
(Hypothesis 2a) and actual use of the technology (Hypothesis 2b). While perceived
usefulness was a significant predictor of attitude toward using with the hypothesized
direction ( = .54, t = 9.39), the impact of perceived usefulness was not channeled
into actual use of technology ( = .09, t = 1.17). Thus, Hypothesis 2a was supported,
whereas Hypothesis 2b was not.
The third hypothesis predicted that attitude toward using computer-based
VoIP phone service would be a positive predictor on actual use of the technology.
This hypothesis was supported as proposed ( = .23, t = 3.62).
The fourth hypothesis proposed that Internet self-efficacy would have a
positive effect on perceived ease of use of computer-based VoIP phone service. The
proposed path was significant in the hypothesized direction ( = .31, t = 4.51),
confirming the hypothesis.
The fifth set of hypotheses proposed that technology cluster would be a
positive predictor of perceived ease of use of computer-based VoIP phone service
(Hypothesis 5a) and perceived usefulness of the technology (Hypothesis 5b). None
of these hypotheses was supported ( = -.04, t = -0.66 for Hypothesis 5a; = .00, t =
-0.12 for Hypothesis 5b).
The sixth hypotheses suggested that users’ innovative attitude would be a
positive predictor of perceived ease of use of computer-based VoIP phone service
82
(Hypothesis 6a), perceived usefulness (Hypothesis 6b), and actual use of the
technology (Hypothesis 6c). Only Hypothesis 6b was marginally supported ( = .08,
t = 1.83), whereas neither the path to perceived ease of use nor the path to actual use
of the technology was significant ( = -.04, t = -.54 for Hypothesis 6a; = -.06, t = -
0.97 for Hypothesis 6c).
Hypothesis 7a, which predicted the impact of communication needs on
perceived usefulness of computer-based VoIP phone service, was not supported (
= .02, t = .52), whereas Hypothesis 7b, which suggested the impact of
communication needs on actual use of the technology, was marginally supported (
= .11, t = 1.86).
The eighth hypotheses proposed that perceived cost effectiveness would
predict perceived usefulness of computer-based VoIP phone service (Hypothesis 8a)
and actual use of the technology (Hypothesis 8b), all with positive signs. However,
only the impact on actual use of the technology was supported ( = .03, t = .67 for
Hypothesis 8a; = .14, t = 2.22 for Hypothesis 8b).
Hypothesis 9, which predicted the impact of perceived quality of computer-
based VoIP phone service on perceived usefulness of the technology, was supported
( = .10, t = 2.29). In a similar fashion, Hypothesis 10, which suggested that system
functions influence perceived usefulness, was also supported ( = .13, t = 3.09),
indicating that both perceived quality and system functions are positive predictors of
perceived usefulness of the technology.
83
In Chapter III, a research question that explores the impact of media richness
on actual system use was proposed. The analysis from structural equation modeling
indicates that media richness is not a significant predictor of actual use of computer-
based VoIP phone service ( = -.04, t = -.52).
After the exploratory factor analysis with the items for motivations, it was
hypothesized that the three motivations in the use of computer-based VoIP phone
service (motivations for communication, entertainment, and instrumental use) would
be positive predictors of both perceived usefulness and actual use of the technology.
It was found that both the motivations for communication and entertainment were
positive predictors of perceived usefulness only ( = .18, t = 3.43 for the motivation
for communication; = .12, t = 2.35 for the motivation for entertainment), while the
motivation for instrumental use was a positive predictor of both perceived usefulness
with a marginal significance ( = .08, t = 1.74) and actual system use ( = .19, t =
2.93).
Model Revision
As illustrated above, the poor summary statistics and the nonsignificant paths
of the hypothesized research model suggest that it is necessary to revise the model.
The ultimate objective of model revision in structural equation modeling is “to find a
model that is both substantially meaningful and statistically well fitting” (Byrne,
1998, p. 8). In other words, the approach is model generating, rather than model
84
testing (Jöreskog, 1993). The improvement processes were conducted based both on
theoretical grounds and on statistical indicators helped by LISREL output. The
specific improvement processes are as follows.
First Revision: Deleting Non-Significant Paths
First, all nonsignificant paths were deleted in order to have a meaningful and
parsimonious model. When those nonsignificant paths were deleted, the indices of
the model were as follows.
The chi-square statistic was still significant for this revised model,
2
(37, N =
309) = 257.67, p = .00, and the ratio of chi-square to degrees of freedom was not
acceptable at 6.96 (257.67/37). For other indices, the goodness-of-fit index (GFI)
was .90, while the adjusted goodness-of-fit index (AGFI) was .67. The Bentler-
Bonett Normed Fit Index (NFI) was .90, while the Comparative Fit Index (CFI)
was .91. In addition, the root mean square error of approximation (RMSEA) was .14.
When the chi-square difference test was conducted between the revised model and
the initial hypothesized model, the revised model was not significantly better than
the initial model. Specifically, the chi-square of the hypothesized model was 250.74
at the degrees of freedom of 26. Thus, the chi-square difference was 6.93 (257.67 –
250.74), while the difference in the degrees of freedom was 11 (37 – 26), which
means that the revised model is not a significant improvement from the hypothesized
model. Overall, these summary statistics indicate that the revised model does not
85
represent a good fit evidenced by various indices, except that there is no
nonsignificant path. This led to a second revision for the model.
Second Revision: Adding Relevant Paths
The second revision was driven by modification indices (MIs) from the
LISREL output that capture evidence of poor fit (Byrne, 1998). In this process,
possible paths that had not been suggested in the original model were added.
However, this improvement process for model fit was accompanied by a theoretical
rationale.
The modification indices suggested that 1) the motivation variables
(motivations for communication, entertainment, and instrumental use) might be
predictors for both perceived ease of use and attitude toward using computer-based
VoIP phone service, and 2) the variables of system characteristics (perceived cost
effectiveness, perceived quality, system functions, and media richness) might be
predictors for both perceived ease of use and attitude toward using the technology.
Given that, from the uses and gratifications approach, people select and use a
technology to satisfy their felt needs or desires, and their motivations guide, filter, or
mediate their communication behavior, the indication from the LISREL results that
the motivation variables could be positive predictors for attitude toward using the
technology is not inconsistent with the theoretical propositions. What is not
theoretically clear from the modification indices is that the motivations might be a
86
positive predictor for perceived ease of use of computer-based VoIP phone service. It
may be necessary to explain the relationship between the motivations and perceived
ease of use, if the paths are significant when added.
It is also theoretically sound that the variables of system characteristics would
be positive predictors for both perceived ease of use and attitude toward using
computer-based VoIP phone service. According to the TAM, external factors that
affect perceived ease of use and perceived usefulness include system design
characteristics, user characteristics, and so on. In addition, the TAM explains that
such external factors influence attitude toward using a technology through perceived
ease of use and perceived usefulness (see Figure 2-1). Thus, the direct effects of
system characteristics on attitude toward using computer-based VoIP phone service
are congruent with the theoretical propositions of the TAM, even if the variables of
system characteristics are not channeled through perceived ease of use and perceived
usefulness.
The addition of a path from people’s innovative attitude to attitude toward
using computer-based VoIP phone service can be clearly supported by the diffusion
literature. It has been found that individuals with strong innovative attitudes are more
willing to learn new ideas, more willing to explore new technologies, and keep up
with new technologies (Lin, 1998). Therefore, it is obvious that innovative attitude
can be a positive predictor for attitude toward using computer-based VoIP phone
service.
87
After this process of adding relevant paths, a second revised model was
obtained and its indices were as follows. The chi-square statistic was not significant
for the second revised model,
2
(21, N = 309) = 22.37, p = .38, and the ratio of chi-
square to degrees of freedom was now acceptable at 1.07 (22.37/21). For other
indices, the goodness-of-fit index (GFI) was .99, while the adjusted goodness-of-fit
index (AGFI) was .95. The Bentler-Bonett Normed Fit Index (NFI) was .99, and the
Comparative Fit Index (CFI) was 1.00. In addition, the root mean square error of
approximation (RMSEA) was .015.
When the chi-square difference test was conducted between the second
revised model and the first revised model examined above, it was found that the
second revised model was significantly better than the first revised model.
Specifically, the chi-square difference between the second revised model and the
first revised model was 235.30 (257.67 – 22.37), while the difference in the degrees
of freedom was 16 (37 – 21), which is statistically significant at both 95% and 99%
significance levels, indicating that the second revised model is significantly
improved from the first revised model. Interestingly, however, it was found that the
motivation for entertainment was a negative predictor for perceived ease of use ( = -
.22, t = -3.53), which needs to be explained with plausible reasons in the next chapter.
Nevertheless, overall summary statistics indicate that the second revised model
represents an excellent fit with various indices.
88
It should be noted, however, that there were some changes in the significance
of the paths from the initially hypothesized model, and there existed some
nonsigificant paths when the relevant paths discussed above were added.
The paths that were no longer significant were: 1) the path from perceived
ease of use to attitude toward using; 2) the path from innovative attitude to actual use;
3) the path from communication needs to perceived usefulness; and 4) the path from
motivation for entertainment to perceived usefulness. However, 14 paths obtained
significance through the model improvement process (see Table 5-5 for a summary
of the paths added).
Table 5-5
The Paths Added through the Model Revision Process
Variable Path added
Innovative attitude
Motivation for communication
Motivation for entertainment
Motivation for instrumental use
Perceived cost effectiveness
Perceived quality
System functions
Media richness
Innovative attitude Perceived usefulness
Innovative attitude Attitude toward using
Motivation for comm. Perceived ease of use
Motivation for comm. Attitude toward using
Motivation for entertainment Perceived ease of use
Motivation for inst. use Attitude toward using
Perceived cost effectiveness Perceived ease of use
Perceived cost effectiveness Attitude toward using
Perceived quality Perceived ease of use
Perceived quality Attitude toward using
System functions Perceived ease of use
System functions Perceived usefulness
Media richness Perceived ease of use
Media richness Perceived usefulness
89
Although there were some paths that were no longer statistically significant,
the second revised model was significantly improved from the first revised model
with a much better model fit and more significant paths added. As the final process
of model generating, this study conducted one more revision deleting nonsignficant
paths from the second revised model in order to make the model parsimonious.
Third Revision: Making the Model Parsimonious
After all these processes, the indices of the third revised model were as
follows. The chi-square statistic was not significant for the revised model,
2
(19, N =
309) = 21.32, p = .32, and the ratio of chi-square to degrees of freedom was
acceptable at 1.12 (21.32/19). For other indices, the goodness-of-fit index (GFI)
was .99, while the adjusted goodness-of-fit index (AGFI) was .95. The Bentler-
Bonett Normed Fit Index (NFI) was .99, and the Comparative Fit Index (CFI) was
1.00. In addition, the root mean square error of approximation (RMSEA) was .020.
Overall, summary statistics indicate that the third revised model also represents an
excellent fit with various indices.
When the chi-square difference test was conducted between the second
revised model and the third revised model, it was found that the third revised model
was not significantly better than the second revised model. Specifically, the chi-
square difference between the second revised model and the third revised model was
90
1.05 (22.37 – 21.32), while the difference in the degrees of freedom was 2 (21 – 19),
which is not statistically significant at either 95% or 99% significance level.
In sum, the third revised model is not a significant improvement from the
previous model, given that all indices of the second revised model are slightly,
though not significantly, better than those of the third revised model in addition to no
significance in the chi-square difference test. More importantly, however, the third
revised model is better than the second revised model in terms of parsimony, thanks
to exclusion of the nonsignificant paths, and therefore, this study concludes that the
third revised model is the final model. The final model is presented in Figure 5-2,
and a comparison of the initial hypothesized model and the revised models is
presented in Table 5-6.
91
Figure 5-2. LISREL Results for the Final Model.
Note. +p < .10, *p < .05, **p < .01, ***p < .001.
Motivation
for comm
Motivation
for inst. use
Media
richness
System
functions
Perceived
cost
effectiveness
Perceived
quality
Perceived
ease of use
Perceived
usefulness
Attitude
toward using
Actual system
use
.10*
.10**
-.28**
.31**
.28**
.21**
.15**
.20**
.17**
.12+
.13**
.09*
.15**
.38***
.10**
.18**
.13*
.10*
Internet
self-efficacy
Innovative
attitude
Motivation
for
entertainment
.24**
.07+
.29**
.12*
.31**
92
Table 5-6
Comparison of Hypothesized and Revised Models
Hypothesized Model First Revision
(No nonsignificant
path from the
hypothesized
model)
Second Revision
(Add motivations,
system characteristics,
innovative attitude
perceived ease of use,
attitude toward using)
Third Revision
Final Model
(No nonsignificant
path from the
second revised
model)

2
(p-value)

2
d
/df
d
(p-value)

2
/df
GFI
AGFI
NFI
CFI
RMSEA
250.74 (p = .00)
3181.49/79 (p < .01)
a
9.64
.90
.55
.90
.90
.17
257.67 (p = .00)
6.93/11 (p = n.s.)
b
6.96
.90
.67
.90
.91
.14
22.37 (p = .38)
235.30/16 (p < .01)
b
1.07
.99
.95
.99
1.00
.015
21.32 (p = .32)
1.05/2 (p = n.s.)
b
1.12
.99
.95
.99
1.00
.020
Note. a. The chi-square difference test with the null model.
b. The chi-square difference test with the previous model.
GFI = the Goodness-of-Fit Index, AGFI = the Adjusted Goodness-of-Fit Index
NFI = the Bentler-Bonett Normed Fit Index, CFI = Comparative Fit Index
RMSEA = the root mean square error of approximation.
93
Direct and Indirect Effects
Examination of total effects is shown in Table 5-7. It was found that Internet
self-efficacy had effects on all endogenous (dependent) variables, except for actual
use of computer-based VoIP phone service, either directly or indirectly. The variable
had a direct effect on perceived ease of use (.10), while it had indirect effects on both
perceived usefulness (.04) and attitude toward using (.01).
Similarly, innovative attitude had substantial direct effects on both perceived
usefulness (.07) and attitude toward using (.11). The variable also had an indirect
effect on actual use of computer-based VoIP phone service (.03).
The motivation for communication played a significant role in the final
model. The variable had substantial direct effects on perceived ease of use (.31),
perceived usefulness (.21), and attitude toward using (.35) with the strongest impacts
among all exogenous variables. It also had an indirect effect on actual use of
computer-based VoIP phone service (.09).
Contrary to expectation, the motivation for entertainment had negative
impacts on endogenous variables. It had a direct effect on perceived ease of use (-.28)
along with indirect effects on perceived usefulness (-.10) and attitude toward using (-
.02).
The motivation for instrumental use was another important variable to
explain the adoption and use of computer-based VoIP phone service. Although the
variable did not have a significant impact on perceived ease of use, its direct effects
94
on perceived usefulness (.10), attitude toward using (.27), and actual system use (.20)
were substantial.
All system characteristics variables (perceived cost effectiveness, perceived
quality, system functions, and media richness) had impacts on all endogenous
variables either directly or indirectly, indicating that these variables are also
important determinants of the adoption and use of computer-based VoIP phone
service.
As the TAM suggests, perceived ease of use had a strong impact on
perceived usefulness directly (.38), while it had indirect effects on attitude toward
using (.07) and actual system use (.02). In addition, perceived usefulness also had a
substantial direct effect on attitude toward using (.18) together with an indirect effect
on actual system use (.04). Finally, attitude toward using had a strong direct effect on
actual system use (.24), confirming the theoretical prediction of the TAM.
95
Table 5-7
Direct and Indirect Effects
Effects on
a
Perceived ease of use Perceived usefulness Attitude toward using Actual system use
Variable
Direct Indirect Total Direct Indirect Total Direct Indirect Total Direct Indirect Total
Internet
self-efficacy
.10 -- .10 -- .04
(.02)
.04 -- .01
(.00)
.01
b
Innovative
attitude
Motivation
for comm.
Motivation
for entertain
.31
-.28
--
--
.31
-.28
.07
.21
--
--
.12
(.03)
-.10
(.03)
.07
b
.33
-.10
.11
.29
--
.01
(.01)
.06
(.02)
-.02
(.01)
.12
.35
-.02
--
--
.03
(.01)
.09
(.03)
.03
.09
Motivation
for inst. use
Perceived cost
effectiveness
.12 -- .12
.10
--
--
.05
(.02)
.10
.05
.27
.15
.02
(.01)
.01
(.00)
.29
.16
.20
.13
.07
(.02)
.04
(.01)
.27
.17
Perceived
quality
.31 -- .31 .10 .12
(.02)
.22 .17 .04
(.01)
.21 -- .05
(.02)
.05
System
functions
.13 -- .13 .09 .05
(.02)
.14 -- .03
(.01)
.03 -- .01
(.00)
.01
b
Media
richness
Perceived
ease of use
Perceived
usefulness
.12 -- .12
b
.15
.38
.05
(.02)
--
.20
.38
--
--
.18
.04
(.01)
.07
(.02)
--
.04
.07
.18
--
--
--
.01
(.00)
.02
(.01)
.04
(.02)
.01
.02
.04
Attitude .24 -- .24
Note. a. All p < .05, b. p < .10. Standard errors in parentheses.
96
Multiple Regression Analysis for Non-Users
Thus far, this study has investigated the factors that affect users’ acceptance
and use of computer-based VoIP phone service. The study now discusses the factors
that affect non-users’ behavioral intention to use the technology in the future. The
possible factors were selected from diffusion theory as explained in Chapter III.
Table 5-8 provides the relative influence of each variable in predicting
behavioral intention to use computer-based VoIP phone service among non-users (N
= 1,329). The regression model estimate yielded five significant predictors for
behavioral intention to use: income ( = -.06, t = -1.80), Internet self-efficacy (
= .10, t = 2.62), technology cluster ( = .06, t = 1.93), innovative attitude ( = .18, t =
4.40), and communication needs ( = .07, t = 2.23). With these significant predictors,
a total of 10.1% of the variance was accounted for after all of the predictor variables
were entered into the regression equation, F(7, 1321) = 20.74, p < .001. With respect
to the hypotheses for non-users proposed in Chapter III, all hypotheses except for
Hypotheses 11a and 11b, which were about the effects of age and education on
behavioral intention to use the technology, were supported.
97
Table 5-8
Multiple Regression: Predictors of Behavioral Intention
Predictors R
2
F
Age
Education
Income
Internet self-efficacy
Technology cluster
Innovative attitude
Communication needs
-.01
-.02
-.06
+
.10**
.06
+
.18***
.07*
.101 20.74
+
p < .10, * p < .05, ** p < .01, *** p < .001.
98
CHAPTER VI
CONCLUSION AND DISCUSSION
This chapter summarizes the results of the hypothesis testing and model
building with respect to the contribution of each variable to the adoption and use of
computer-based VoIP phone service. Based upon the findings, theoretical
implications are discussed together with limitations of the current study and
suggestions for future research.
Summary of Findings and Discussion
The first goal of the current study was to identify the factors that affect users’
acceptance of computer-based VoIP phone service through the framework of the
Technology Acceptance Model developed by Davis (1986). The findings generally
supported hypotheses derived from the model along with other theoretical
perspectives including the uses and gratifications approach, diffusion theory, and the
theory of media richness.
First of all, this study confirmed that perceived ease of use had a significant
impact on perceived usefulness as the TAM suggested. However, it could not
confirm the direct effect of perceived ease of use on attitude toward using as the
TAM proposed (see Figure 5-2). Although the direct effect was initially supported
with the hypothesized research model (see Figure 5-1), the variable lost its
99
significance during the model revision process. Nevertheless, given the significant
indirect effect of perceived ease of use on attitude toward using (.07), it does not
mean that perceived ease of use does not affect attitude toward using. It can be
interpreted that in the context of computer-based VoIP phone service, people’s
perception of ease of use may not be necessarily channeled into favorable attitudes
toward using the technology because a variety of other similar technology options
such as cellular phones or BlackBerry are available. It means that people reveal
positive attitudes toward using the technology only when they perceive the
technology as useful.
Additionally, this study could not find a direct effect of perceived ease of use
on actual system use. It should be noted that there has been a controversy with
respect to the role of perceived ease of use on actual system use. As discussed earlier
in Chapter II, although the original TAM suggested that “perceived ease of use
operates through perceived usefulness” (Davis, 1989, p. 332), some studies have
questioned the variable’s direct effect on actual use (e.g., Keil, Beranek, &
Konsynski, 1995), and in fact some of the studies have proved that perceived ease of
use could have a direct effect on actual system use (e.g., Gefen & Straub, 2000).
However, the current study could not find a direct effect of perceived ease of use on
actual system use like many other studies that used the TAM.
With respect to the role of perceived usefulness, the current study confirmed
its effect on attitude toward using computer-based VoIP phone service as the TAM
100
proposed, yet could not support its direct impact on actual use of the technology,
contrary to expectation. Although many studies that employed the TAM tested
whether perceived usefulness has an effect on behavioral intention to use rather than
actual system use, as mentioned in Chapter III, it is somewhat disappointing that the
variable does not have a direct effect on actual use of computer-based VoIP phone
service. One possible explanation to the lack of the direct effect would be that
people’s perception of computer-based VoIP phone service’s usefulness might not be
transformed into actual use when there are many other competing technologies.
However, attitude toward using, which received a direct effect from perceived
usefulness, contained a substantial direct effect on actual system use, indicating that
perceived usefulness still had an impact on actual system use indirectly.
As discussed earlier, since the TAM is a general and parsimonious model, the
current study employed various antecedent variables to enrich the explanation of
adoption and use of computer-based VoIP phone service. Among the individual
difference variables, only Internet self-efficacy and innovative attitude had
significant effects on either perceived ease of use or perceived usefulness.
Specifically, Internet self-efficacy had a direct effect on perceived ease of use and
indirect effects on perceived usefulness and attitude toward using. Given that
computer-based VoIP phone service is another new Internet application, it is not a
surprise that confidence in using the Internet facilitated perceived ease of use of the
technology.
101
It is accountable that people’s innovative attitude positively affected
perceived usefulness, attitude toward using, and actual system use, either directly or
indirectly, considering that, for the users who possess innovative attitudes, computer-
based VoIP is an attractive new innovation which combines the Internet and the
telephone.
It is interesting to see, however, that neither technology cluster nor
communication needs had significant effects on the dependent variables in this study,
contrary to the propositions of diffusion theory. A closer examination of technology
cluster provides an explanation for the null effect of the variable. Since most users of
computer-based VoIP phone service (93.2%) owned or subscribed to more than five
technology products out of ten products included in the current study, and about
three quarters of users (74.5%) owned or subscribed to more than six technology
products (M = 6.95, SD = 1.69), the distinctive value of technology cluster almost
disappeared. In the case of communication needs, it had a marginally significant
effect on perceived usefulness at the initial hypothesis testing, yet the variable lost its
significance during the revision process. A plausible reason is that both the
motivation for communication and communication needs might capture a similar
construct, yet the motivation for communication might be a better predictor to
explain the adoption and use of computer-based VoIP phone service than
communication needs in that the former is more specific and clearer than the latter in
102
terms of identification of users’ felt needs or desires (see the survey question items
for the two variables in Appendix section 12 and section 14 [questions 5 to 7]).
System characteristics generally played an important role in the adoption and
use of computer-based VoIP phones service. Most importantly, perceived cost
effectiveness affected all dependent variables either directly or indirectly. The
variable significantly influenced attitude toward using and actual use of computer-
based VoIP phone service. This is not a surprise given that cost reduction is the
greatest attraction of VoIP in general. An interesting finding about perceived cost
effectiveness is that the variable had a direct effect on perceived ease of use, but an
indirect effect on perceived usefulness. It means that cost reduction made users even
feel that computer-based VoIP phone service is easy to use. In other words, users are
likely to perceive that the technology is easy to use as long as it seems to be
beneficial for their communication and other uses. This does not seem implausible,
but does seem somewhat unreasonable. Thus, an elaborated psychological
explanation is called for to make sense of this finding in future research.
Supporting the findings from past research with the TAM, other system
characteristics variables such as perceived quality and system functions were
positive predictors of perceived ease of use, perceived usefulness, attitude toward
using, and actual use of computer-based VoIP phone service, either directly or
indirectly.
103
It was found that the variable of media richness affected perceived ease of
use and perceived usefulness, although it did not have a significant direct effect on
actual system use. Given that media richness is mostly about the ability of a medium
to transmit multiple cues, immediacy of feedback, language variety, or personal
focus of a medium (Daft & Lengel, 1984), computer-based VoIP phone service can
be considered as a rich medium. That is, computer-based VoIP phone service
provides not only multiple cues including voice and nonverbal cues through video
conversation or conference calling but also immediate feedback thanks to
widespread broadband Internet access services in recent years. Thus, media richness
as a key characteristic of computer-based VoIP phone service contributed to
enhancing perceived ease of use and perceived usefulness.
The variables of motivation were crucial in the explanation of adoption and
use of computer-based VoIP phone service. The motivation for communication in
particular played an essential role in influencing all dependent variables with the
strongest substantial effects among all independent variables. It had direct effects on
perceived ease of use (.31), perceived usefulness (.21), and attitude toward using
(.29), and an indirect effect on actual use of the technology (.09). These effects of the
motivation for communication indicate that it is the most important variable in
explaining the adoption and use of computer-based VoIP phone service. In addition,
it is also interesting that users’ strong motivation for communication led to even
higher perceived ease of use. It means that, compared with those who have a weak
104
motivation for communication, users with a strong motivation for communication are
more likely to perceive ease of use and usefulness of the technology and to exhibit
favorable attitudes toward using, which in turn, facilitate actual use of the technology.
Similar to the effects of the motivation for communication, the motivation for
instrumental use was also an essential component in the use of computer-based VoIP
phone service. The difference between the motivation for communication and the
motivation for instrumental use was that the former affected perceived ease of use,
while the latter had a direct effect on actual use of the technology. It is plausible that,
for those who have practical purposes for telephone use as opposed to social or
relational purposes, whether or not computer-based VoIP phone service is easy to
use does not matter much; rather they are simply inclined to use the technology
perceiving it as useful.
After all, although the motivation variables were categorized separately from
the individual difference variables in the current study, these findings about the role
played by the motivations are consistent with the TAM’s original proposition that
emphasizes the effects of individual differences on perceived ease of use and
perceived usefulness.
One thing that remains unanswered is why the motivation for entertainment
had a negative effect on perceived ease of use along with indirect negative effects on
perceived usefulness and attitude toward using computer-based VoIP phone service.
That is, the more an individual likes to entertain with the technology, the more he or
105
she thinks it hard to use. This finding is somewhat astounding, given that another
motivation, the motivation for communication, increased perceived ease of use as
examined above. One possible reason for this unexpected finding might be that
computer-based VoIP phone service thus far has not reached the level of
sophistication at which users with a high motivation to entertain can be satisfied, and
thus, it affected the dependent variables negatively. This finding, however, calls for
further investigation of the role of the motivation for entertainment in future research.
To sum up, the current study found that all independent variables, especially
the motivation variables, significantly contributed to the explanation of adoption and
use of computer-based VoIP phone service, generally supporting the propositions
from the theoretical perspectives employed in this study.
Another goal of the current study was to compare users and non-users of
computer-based VoIP phone service with regard to the factors that facilitate (or
hinder) their use of the technology. It was found that there exist many differences
between the two groups in various fronts.
First, the current study’s findings partially supported diffusion theory’s claim
that early adopters would be younger, better educated, and of higher income than
later adopters or non-adopters (Rogers, 1983, 1995, 2003). It was found that users of
computer-based VoIP phone service in this study were younger than non-users, but
there was no difference between the two groups in terms of education and income.
106
Because computer-based VoIP phone service is almost free or can be provided at a
much lower price than other phone services, education and income, which are highly
correlated with each other, did not affect the adoption and use of the technology.
In addition, there was a significant difference between users and non-users of
computer-based VoIP phone service in terms of the time spent on using the Internet
per day: users spent more time on the Internet (M = 4.90, SD = 3.27) than non-users
(M = 4.15, SD = 2.91).
The current study found significant differences in the individual difference
variables as well. Users of computer-based VoIP phone service exhibited higher
computer and Internet self-efficacies, owned more communication technology
devices or products, showed greater innovative attitude, and possessed greater
communication needs than non-users of the technology. This finding indirectly
supports that most of these individual differences accounted for the adoption and use
of computer-based VoIP phone service, as explained above.
Finally, with respect to the factors that affect non-users’ behavioral intention
to use computer-based VoIP phone service in the future, the current study found that
all individual difference variables (Internet self-efficacy, technology cluster,
innovative attitude, and communication needs) positively affected non-users’
intention to use. It was revealed, however, that income had a negative effect, though
marginally significant, on future intention to use the technology, indicating that
107
relatively poor people are more likely to adopt the technology in the future. This may
be partly because computer-based VoIP phone service is free or very affordable. It
can be also interpreted that if an individual is rich enough to use other competing
technologies, and if he or she is currently not using computer-based VoIP phone
service, he or she may be satisfied with other technologies and will be unlikely to
spend time on trying to use computer-based VoIP phone service.
Research Implications
Results of this study offer some important theoretical insights and
implications. First, as the current study uncovered, the TAM is a useful framework to
explain the factors that affect people’s actual use of computer-based VoIP phone
service. The current study suggests, however, that other possible factors should be
employed to make the theory building process of technology use more fruitful, as
previous research recommends. In addition to the constructs that were found in this
study, efforts to search for other relevant constructs are also encouraged.
Second, the current study proposed an integration of the TAM and the uses
and gratifications approach by incorporating motivations as critical constructs that
facilitate perceived ease of use and perceived usefulness. Thus far, the TAM has
been widely used in studies of information systems, while the uses and gratifications
approach has been heavily utilized in media effects research. Given that there have
been few efforts to connect the two approaches despite the fact that both are trying to
108
explain the underlying personal factors that influence people’s use of information
and communication technologies, this study contributes to an exploration of how the
TAM and the uses and gratifications approach can be integrated. It is necessary to
further elaborate on the integration of the two approaches in future studies.
Third, as a practical implication, this study suggests that the vendors of
computer-based VoIP phone service need to equally emphasize the technology’s
functions and quality. The findings of this study indicate that perceived cost
effectiveness has a direct effect on actual use of the technology, but other system
characteristics variables such as system functions or perceived quality do not. Until
today, computer-based VoIP phone service has been successful in attracting people
who are willing to use the technology, focusing on its free service or at least very
low costs. However, as many players enter the fray, competition between the vendors
will be intensified, and thus, each market player needs to develop its own unique
features and functions beyond the cost advantage of the technology.
Limitations and Suggestions for Future Research
This study has some limitations to be mentioned. First, it should be pointed
out that this study has a limited external validity due to the nature of online surveys.
As mentioned earlier, it is hard to obtain a sampling frame in which every subject in
the population has an equal chance of being selected for participation in online
surveys. Although this study used an online panel from an established academic
109
institution, it is hard to believe that the problem of representativeness from a
population of general Internet users was completely solved. For instance,
participants’ median ages in the current study were higher (40 for users, 42.65 for
non-users) than that of the U.S. population in 2005 (36.4) (United States Fact Sheet,
2005). In addition, members of racial minorities were not properly represented in the
current study. This study had a sample of users in which “African American, not of
Hispanic origin” was 2.9%, “Hispanic” was 5.2%, and “Asian or Pacific Islander”
was 13.9%. However, the proportions of these ethnic groups in the U.S. population
are 12.1%, 14.5%, and 4.4%, respectively. This might affect the results of the current
study, calling its generalizability into question. Future studies are encouraged to use
a more representative sample in order to replicate and corroborate the findings and
the research model suggested in the current study.
Another methodological problem of the present study is that it is a cross-
sectional study, meaning that it is hard to demonstrate causes and effects directly
from a one-time survey study. Longitudinal studies are highly desired to prove the
effects of antecedent variables on the use of computer-based VoIP phone service
discovered in the current study.
Finally, this study could not explain why the motivation for entertainment
negatively affected perceived ease of use. There may be some psychological reasons
this study could not capture or there may be some problems in measurement of the
variables. In addition, it is necessary to account for why no or reduced cost of
110
computer-based VoIP phone service made users feel that the technology is easy to
use. Future studies are strongly encouraged to address these issues and validate the
findings of the current study.
111
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APPENDIX
SURVEY QUESTIONNAIRE
1. INSTRUCTIONS
Hello, my name is Namkee Park, a Ph.D. candidate at the Annenberg School for
Communication, University of Southern California. Together with Professor
Margaret McLaughlin of the Annenberg School, I am conducting a research study
about the use of computer-based VoIP (Voice over Internet Protocol) phone service
such as Skype.
VoIP phone service is also called Internet Telephony, and it refers to the digital form
of voice transferring via the Internet: your voice is transformed into data and carried
through the Internet to reach the person you talk to. Vonage is a popular example of
VoIP phone service. Computer-based VoIP phone service is slightly different. It
requires a computer or PDA with microphone and speaker for you to make calls.
Thus, without a phone set or device, you can make calls by simply using a computer
with an Internet connection. Currently, the most popular computer-based VoIP
phone service in the market is Skype.
The following survey contains questions on computer-based VoIP phone service. It
will take approximately 20 minutes to complete. Please answer all questions unless
otherwise informed. If you would like any additional information about the study or
the questions, please feel free to contact me at npark@usc.edu. The information you
provide will be kept completely confidential and used for research purposes only.
Completion of the questions and submission of the questionnaire will constitute
consent to participate in this research project.
There are no psychological or physical risks for participation in this study. Any
questions that cause discomfort may be skipped. There are no direct benefits for your
participation. Results of this study, however, may lead to social benefits. This study
has been approved by USC Institutional Review Board (IRB # UP-07-00021).
You will have a chance to win a cash prize by participating in this study, and your
participation will be much appreciated. Thank you for your time.
129
2. INFORMATION STATEMENT
CONFIDENTIALITY
Any information that is obtained in connection with this study and that can be
identified with you will remain confidential and will be disclosed only with your
permission or as required by law. Data will be stored for three years after completion
of study as required by Federal Regulations but will then be destroyed. Data will be
password protected and only researchers will have access to it. When the results of
the research are published or discussed in conferences, no information will be
included that will reveal your identity.
PARTICIPATION
You can choose whether to be in this study or not. If you volunteer to be in this
study, you may withdraw at any time without consequences of any kind. You may
also refuse to answer any questions you don’t want to answer and still remain in the
study. The investigators may withdraw you from this research if circumstances arise
which warrant doing so.
QUESTIONS
If you have any questions, please feel free to contact Namkee Park at
npark@usc.edu.
RIGHTS OF RESEARCH SUBJECTS
You may withdraw your consent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have questions, contact University Park
IRB, Office of the Vice Provost for Research, Grace Ford Salvatori Building, Room
306, Los Angeles, CA 90089-1695, (213) 821-5272 or upirb@usc.edu.
130
3. INSTRUCTIONS: Please read carefully the following description and then
answer the question below.
The question below is about computer-based VoIP (Voice over Internet Protocol)
phone service. VoIP phone service is also called Internet Telephony, and it refers to
the digital form of voice transferring via the Internet: your voice is transformed into
data and carried through the Internet to reach the person you talk to. Vonage is a
popular example of VoIP phone service. Computer-based VoIP phone service is
slightly different. It requires a computer or PDA with microphone and speaker for
you to make calls. Thus, without a phone set or device, you can make calls by simply
using a computer with an Internet connection. Currently, the most popular computer-
based VoIP phone service in the market is Skype.
1. Do you use a computer-based VoIP phone service (e.g., Skype, phone call with
Google Talk, etc.)?
_____ Yes _____ No (Go to section # 12)
4. INSTRUCTIONS: For each question below, please fill in the blanks or check
the appropriate answer.
1. If you are currently using a computer-based VoIP phone service such as Skype,
approximately how many times do you use the service in a typical week?
__________ times / week
2. If you are currently using a computer-based VoIP phone service such as Skype,
approximately how many hours do you use the service in a typical week?
__________ hours __________ minutes / week
3. If you are currently using a computer-based VoIP phone service such as Skype,
what is the average number of minutes you spend on each call?
__________ minutes / call
4. How long have you been a user of a computer-based VoIP phone service such as
Skype?
_____ Less than 3 months
_____ from 6 months to 1 year
_____ from 1 year to 1 and half year
_____ from 1 and half year to 2 years
_____ from 2 years to 2 and half years
_____ from 2 and half years to 3 years
_____ more than 3 years
131
5. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. It is easy to have an account and phone number from a computer-based VoIP
phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. Using a computer-based VoIP phone service does not require a lot of effort.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I find computer-based VoIP phone service easy to use.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. I find it easy to get computer-based phone service to do what I want it to do.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. Using computer-based VoIP phone service is a convenient way to make phone
calls.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. I find computer-based VoIP phone service to be useful for my personal
communication with others.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. Using computer-based VoIP phone service improves my personal communication
with others.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
132
8. Computer-based VoIP phone service is not as useful as traditional phone services.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
9. Using computer-based VoIP phone service increases my productivity.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
10. Using computer-based VoIP phone service enables me to make my calls more
effectively.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. I like to make or receive calls with computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. I would recommend that my friends use computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I have been satisfied with computer-based VoIP phone service since I began to use
it.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. I use computer-based VoIP phone service as much as possible.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. I use computer-based VoIP phone service whenever it is available.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
133
6. Computer-based VoIP phone service is my first choice when I want to make a call.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. I do not use computer-based VoIP phone service as long as other traditional phone
services are available.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. I use computer-based VoIP phone service in order to communicate with friends
and family.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. I use computer-based VoIP phone service in order to let others know I care for
them.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I use computer-based VoIP phone service in order to stay in touch with people I
do not see very often.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. I use computer-based VoIP phone service in order to feel involved with what is
going on with other people.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. I use computer-based VoIP phone service in order to keep up-to-date on people
and events.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
134
6. I use computer-based VoIP phone service because using it relaxes me.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. I use computer-based VoIP phone service in order to kill the time.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
8. I use computer-based VoIP phone service because it is entertaining.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
9. I use computer-based VoIP phone service because sometimes I just like to talk.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
10. I use computer-based VoIP phone service in order to enjoy the pleasure of
talking to people.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
11. I use computer-based VoIP phone service in order to gossip or chat.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
12. I use computer-based VoIP phone service in order to relieve boredom by calling
people.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
13. I use computer-based VoIP phone service in order to buy tickets for travel or
special events.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
135
14. I use computer-based VoIP phone service in order to get information about
products and services.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
15. I use computer-based VoIP phone service in order to order products.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
16. I use computer-based VoIP phone service in order to schedule appointments.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
17. I use computer-based VoIP phone service in order to avoid looking old-fashioned.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
18. I use computer-based VoIP phone service in order to look cool.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
19. I use computer-based VoIP phone service in order to have it as a status symbol.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
8. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. It is cheaper to use computer-based VoIP phone service compared to traditional
phone services.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
136
2. To use computer-based VoIP phone service is expensive considering that I need to
have other equipment such as personal computer, broadband Internet connection,
speaker, and headset.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I have saved a lot of money since I used computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. When talking through computer-based VoIP phone service, there is no delay in
hearing the voice from the other side.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. When talking through computer-based VoIP phone service, it is clear enough to
hear the voice from the other side.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. The quality of computer-based VoIP phone service is better than that of landline-
based phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. The quality of computer-based VoIP phone service is better than that of mobile
phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
8. The quality of calls via computer-based VoIP phone service is below my
expectation.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
137
9. I believe my privacy is protected when I use computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
10. My personal information is safe when I use computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
11. I believe the VoIP phone service company can protect my privacy including my
contact list or calling habit.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
12. It is not easy for others to overhear what I say through computer-based VoIP
phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
9. 1/2 Done
You are now about halfway done with this survey.
If you click the 'NEXT' button below, you will proceed to the latter part of this
survey.
Before clicking the 'NEXT' button, please make sure that you have answered all of
the questions above.
Thank you.
10. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. Video conversation with a webcam makes computer-based VoIP phone service
more valuable.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
138
2. Computer-based VoIP phone service is valuable because I can chat with one or
more persons during calls.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. Computer-based VoIP phone service is valuable because I can do other tasks on
the computer simultaneously even during conversation with other people.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. Computer-based VoIP phone service is valuable when I make long-distance calls.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. Computer-based VoIP phone service is valuable when I make international calls.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. Computer-based VoIP phone service is valuable because I can attach and send
files and photos.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
11. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. Computer-based VoIP phone service helps me communicate quickly with my
communication partner(s), giving and receiving timely feedback.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. I cannot easily communicate ideas to my communication partner(s) when I use
computer-based VoIP phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
139
3. Computer-based VoIP phone service helps me and my communication partner(s)
to better understand each other.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. Computer-based VoIP phone service slows down my communication with my
communication partner(s).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. With computer-based VoIP phone service, I can easily deliver a variety of
different cues beyond spoken messages.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. With computer-based VoIP phone service, I can easily customize messages to my
personal circumstances.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. I feel closer to the person I am talking to when I use computer-based VoIP phone
service than when I use traditional phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
8. I feel more casual when I use computer-based VoIP phone service than when I use
traditional phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
9. I am involved in less conflict during conversation when I use computer-based
VoIP phone service than when I use traditional phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
140
10. I tend to talk about less official things when I use computer-based VoIP phone
service than when I use traditional phone service.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
12. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. I feel confident using a user’s guide for computer software when help needed.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. I feel confident using a user’s guide for computer hardware when help needed.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I feel confident learning how to use a variety of technological features of computer
software.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. I feel confident understanding terms related to computer hardware.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. I feel confident understanding terms related to computer software.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. I feel confident troubleshooting computer problems.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. I feel confident getting software up and running.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
141
8. I feel confident learning to use new computer programs.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
9. I feel confident learning advanced skills related to programs (software).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
10. I feel confident describing the functions of computer hardware (e.g., keyboard,
monitors, disk drives, CPU, etc.).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
11. I feel confident understanding terms related to Internet hardware (e.g., cable
modem, wireless Internet router, etc.).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
12. I feel confident understanding terms related to Internet programs (e.g., web
browser, Java applications, etc.).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
13. I feel confident describing the functions of Internet hardware.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
14. I feel confident trouble-shooting Internet problems.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
15. I feel confident explaining why some functions do not work well on the Internet.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
142
16. I feel confident using the Internet to gather information.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
17. I feel confident learning advanced skills related to a specific Internet program
(e.g., Java, Flash, etc.).
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
13. INSTRUCTIONS: For each question below, please check the appropriate
answer.
1. Do you have a personal computer (desktop or laptop)?
_____ Yes _____ No
2. Do you have a broadband Internet access at home or at work?
_____ Yes _____ No
3. Do you have a PDA (Personal Data Assistant)?
_____ Yes _____ No
4. Do you have a cellphone?
_____ Yes _____ No
5. Do you have a video game player (e.g., PlayStation, Xbox, etc.)?
_____ Yes _____ No
6. Do you have a DVD player (including a computer-attached DVD player)?
_____ Yes _____ No
7. Do you have a digital camera (including a cellphone-attached camera)?
_____ Yes _____ No
8. Do you have a camcorder?
_____ Yes _____ No
9. Do you have a device for podcasting such as iPod?
_____ Yes _____ No
10. Do you or your family have a DVR (Digital Video Recorder such as TiVo)?
_____ Yes _____ No
143
14. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
1. On a scale of 1 to 7 where 1 means not technically progressive at all, or low tech,
and 7 means very technically progressive, or high tech, how would you rate yourself?
1 2 3 4 5 6 7
2. I enjoy trying out new technologies.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
3. I like to introduce new technologies to my friends or colleagues.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
4. I consider myself a modern person who is usually up-to-date on new technologies.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
5. I spend a lot of time talking with friends and associates about things I find
interesting, like hobbies, personal interests, or current issues.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
6. I often feel the need to express myself to others.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
7. If there is some way I can send a message to others, I will do it regularly.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
15. INSTRUCTIONS: For each question, please check the number that best
describes your answer.
Instructions: If you are currently using a computer-based VoIP phone service, please
skip the following two questions and go to the next page. Then, please answer the
144
subsequent questions. If you are currently NOT using a computer-based VoIP phone
service, please answer the questions in this page and then go to the next page. Then,
please answer the subsequent questions.
1. I will use computer-based VoIP phone service in the near future.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
2. I will not use computer-based VoIP phone service as long as regular phone
services (landline or mobile phone) are available.
1 2 3 4 5 6 7
Strongly Disagree Somewhat Neutral Somewhat Agree Strongly
disagree disagree agree agree
16. INSTRUCTIONS: For the questions below, please check the appropriate
answer or fill in the blanks. .
1. How long have you been a user of computers?
_____ Non-user
_____ Less than 1 year
_____ from 1 year to 2 years
_____ from 2 years to 4 years
_____ from 4 years to 6 years
_____ from 6 years to 8 years
_____ from 8 years to 10 years
_____ more than 10 years
2. How long have you been a user of the Internet?
_____ Non-user
_____ Less than 1 year
_____ from 1 year to 2 years
_____ from 2 years to 4 years
_____ from 4 years to 6 years
_____ from 6 years to 8 years
_____ from 8 years to 10 years
_____ more than 10 years
3. How much time do you spend using computers in a typical day?
__________ hours __________ minutes / day
4. How much time do you spend using the Internet in a typical day?
__________ hours __________ minutes / day
145
5. What is your age?
__________ years old
6. What is your gender?
_____ Female _____ Male
7. So that we may represent all people fairly, how do you describe your race?
______ White, not of Hispanic origin
______ African American, not of Hispanic origin
______ American Indian or Alaska Native
______ Hispanic
______ Asian / Pacific Islander
______ Other Please specify ______________________
8. Please indicate your income per year on average.
______ Less than $20,000
______ $20,001 --- $40,000
______ $40,001 --- $60,000
______ $60,001 --- $80,000
______ $80,001 --- $100,000
______ More than $100,001
9. What is the last year of education you completed?
______ None
______ Elementary
______ Junior high / Middle school
______ Some high school / Did not finish
______ High school graduate
______ Vocational / Trade school
______ Some college, no degree
______ Associate degree (2 year degree)
______ Bachelor’s degree (4 year degree)
______ Master’s degree
______ Professional degree / M.D. / LLD
______ Doctorate degree / Ph.D. / ED.D.
17. You are finished!
Now you have finished the study. Thank you for your time and participation!

Asset Metadata

Creator Park, Namkee (author)

Core Title User acceptance of computer-based VoIP phone service: an application of the technology acceptance model

School Annenberg School for Communication

Degree Doctor of Philosophy

Degree Program Communication

Publication Date 07/23/2007

Defense Date 06/01/2007

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

Tag computer-based VoIP phone service,diffusion theory,media richness,oai:digitallibrary.usc.edu:usctheses,OAI-PMH Harvest,technology acceptance model,uses and gratifications

Language English

Advisor McLaughlin, Margaret L. (committee chair), Lee, Kwan Min (committee member), Rizzo, Albert Skip (committee member)

Creator Email npark@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m640

Unique identifier UC1467101

Identifier etd-Park-20070723 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-519205 (legacy record id),usctheses-m640 (legacy record id)

Legacy Identifier etd-Park-20070723.pdf

Dmrecord 519205

Document Type Dissertation

Rights Park, Namkee

Type texts

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

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email uscdl@usc.edu

Abstract (if available)

Abstract The recent few years have witnessed remarkable growth in the use of computer-based VoIP phone service, which allows computer users to talk to other people at no or little cost via calls through an Internet connection. Employing a theoretical framework from the technology acceptance model (TAM), the uses and gratifications approach, diffusion theory, and the theory of media richness, this study aims to examine the process of adoption and use of computer-based VoIP phone service, and further derive the determinants of technology acceptance by looking at user characteristics.