A Model for Building Trustworthiness in Online Stores
Except where reference is made to the work of others, the work described in this
dissertation is my own or was done in collaboration with my advisory committee. This
dissertation does not include proprietary or classified information.
Patricia Lanford
Certificate of Approval:
Juan E. Gilbert
Associate Professor
Computer Science and Software Engi-
neering
Richard O. Chapman, Chair
Associate Professor
Computer Science and Software Engi-
neering
Cheryl D. Seals
Assistant Professor
Computer Science and Software Engi-
neering
Joe F. Pittman
Interim Dean
Graduate School
A Model for Building Trustworthiness in Online Stores
Patricia Lanford
A Dissertation
Submitted to
the Graduate Faculty of
Auburn University
in Partial Fulfillment of the
Requirements for the
Degree of
Doctor of Philosophy
Auburn, Alabama
August 4, 2007
A Model for Building Trustworthiness in Online Stores
Patricia Lanford
Permission is granted to Auburn University to make copies of this dissertation at its
discretion, upon the request of individuals or institutions and at
their expense. The author reserves all publication rights.
Signature of Author
Date of Graduation
iii
Dissertation Abstract
A Model for Building Trustworthiness in Online Stores
Patricia Lanford
Doctor of Philosophy, August 4, 2007
(B.S. Computer Science, Auburn University, 2000)
(M.S. Software Engineering, Auburn University, 2004)
342 Typed Pages
Directed by Richard O. Chapman
More and more research is being done everyday in the world of e-commerce as con-
sumers and merchants alike realize how powerful a selling tool the internet has become.
Research shows that trust is key to the success of electronic commerce [14] [21] [87] [35].
However, the question of how trust is obtained and sustained online has yet to be answered.
What is it that makes an online store trustworthy to consumers? A conceptual model for
trustworthiness in online stores was developed from the current literature and then enhanced
by an observational study of consumers making actual purchases. The conceptual model
identified the situation needed for trustworthiness to be of issue when shopping online, the
factors that affect the trustworthiness of an online store, and indicators or outcomes of
consumers perceiving an online store to be trustworthy. A questionnaire was conducted
and validated the conceptual model. The questionnaire focused on the trustor and trustee
characteristics of the model, their relationships with each other, and the relative importance
of trustee characteristics. This combination of both qualitative and quantitative data has
provided insight into the online shopping experience, which can be built upon to create
guidelines.
iv
Acknowledgments
First, I would like to thank Dr. Richard Chapman, my dissertation chair, for I am
extremely grateful for all of his advise, understanding, and willingness to work with me
long-distance. Many thanks also to my committee members, Dr. Juan Gilbert and Dr.
Cheryl Seals, and my outside reader, Dr. Thomas Marshall.
I am also very appreciative of the love and support given to me by my family and
friends. Without them, I would have never been able to complete this dissertation.
v
Style manual or journal used Journal of Approximation Theory (together with the style
known as ?auphd?). Bibliograpy follows van Leunen?s A Handbook for Scholars.
Computer software used The document preparation package TEX (specifically LATEX)
together with the departmental style-file auphd.sty.
vi
Table of Contents
List of Tables x
List of Figures xi
1 Introduction 1
1.1 Work Done . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 General Area of Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 The Need for Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 Approach Used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
2 Literature Review 4
2.1 Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 Definition of Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 Intentions and Competence . . . . . . . . . . . . . . . . . . . . . . . 6
2.1.3 Cooperation, Expectations, and Confidence . . . . . . . . . . . . . . 7
2.1.4 Uncertainty, Risk, and Vulnerability . . . . . . . . . . . . . . . . . . 8
2.1.5 Balance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.1.6 Security and Privacy . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.7 Context . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.8 Length of Relationship . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.9 Credibility, Brands, and Reputation . . . . . . . . . . . . . . . . . . 11
2.1.10 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.11 Trustmarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1.12 User Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 How My Research is Different . . . . . . . . . . . . . . . . . . . . . . . . . . 17
3 Statement of the Problem 19
4 General Trust Model 20
4.1 Situation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 Factors Affecting Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.3 Need . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.4 Indicators/Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
5 Observational Study 24
5.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5.2 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5.3 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
vii
5.4 Pilot Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
5.5 Participant Shopping Experiences . . . . . . . . . . . . . . . . . . . . . . . . 27
5.5.1 Participant 1 - Bob . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
5.5.2 Participant 2 - Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
5.5.3 Participant 3 - Jan . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
5.5.4 Participant 4 - Marsha . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.5.5 Participant 5 - Chuck . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.5.6 Participant 6 - Cindy . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5.5.7 Participant 7 - Sue . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.5.8 Participant 8 - Tina . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.5.9 Participant 9 - Greg . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
5.6 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.7 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
5.8 The Importance of Observation . . . . . . . . . . . . . . . . . . . . . . . . . 40
6 A Model of Trustworthiness Online 42
7 Questionnaire 48
7.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
7.2 Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
7.3 Data Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
7.4 Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
7.5 Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
7.5.1 Consumer Characteristics . . . . . . . . . . . . . . . . . . . . . . . . 57
7.5.2 Consumer Characteristics and Online Shopping Experience . . . . . 58
7.5.3 Consumer Characteristics and Elements of Online Shopping . . . . . 60
7.5.4 Relative Importance of Elements of Online Shopping . . . . . . . . . 65
8 Conceptual Model of Trustworthiness Online Revisited 68
9 Conclusions and Future Work 72
Bibliography 73
A Table Statistics 80
A.1 Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
A.2 Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
A.3 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
A.4 Income . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
A.5 Trust . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
A.6 Freq. Web . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
A.7 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
A.8 Browse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
viii
A.9 Purchase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
A.10 Expensive . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
A.11 Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290
A.12 Contingency Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
ix
List of Tables
4.1 General Trust Model - References to Literature . . . . . . . . . . . . . . . . 23
5.1 Participant Shopping Experience . . . . . . . . . . . . . . . . . . . . . . . . 27
6.1 Elements of E-Commerce Trust Model . . . . . . . . . . . . . . . . . . . . . 47
7.1 Q5 - Q12L Contingency Table . . . . . . . . . . . . . . . . . . . . . . . . . . 53
x
List of Figures
4.1 General Trust Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
6.1 General Trust Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
8.1 Conceptual Model of Trustworthiness Online . . . . . . . . . . . . . . . . . 68
8.2 Elements of Trustworthiness Online . . . . . . . . . . . . . . . . . . . . . . . 71
xi
Chapter 1
Introduction
Research shows that trust is key to the success of electronic commerce [14] [21] [87]
[35]. A study conducted by Consumer WebWatch [14] between May 2005 and June of 2005
found that over 20 percent of internet users did not trust online stores and 25 percent
stopped shopping online altogether. This lack of trust has been identified as a key element
of consumers hesitating in making online transactions [2] [41]. As Ang et al. [1] report,
many e-commerce sites are indeed not trustworthy, i.e., it is not just a perception problem.
This research aims to answer the question of what makes online stores trustworthy to
consumers and how can this trustworthiness be obtained and sustained? Understanding
the nature of trust seems like a logical first step. Too often, this step is not taken seriously
enough, resulting in naive and faulty notions of trust. Understanding the concept of trust
in other areas, such as psychology and sociology, will give insight into understanding what
facilitates trustworthiness online. Applying this understanding to e-commerce will help in
developing a model for building trustworthiness in online stores.
1.1 Work Done
A literature review was conducted of trustworthiness in an online setting as well as trust
in other areas such as psychology, sociology, and marketing. An observational study was
conducted along with a questionnaire regarding trustworthiness and its role when shopping
online. Using the data obtained from both the study and the questionnaire, a model for
building trustworthiness online has been developed.
1
1.2 General Area of Research
More and more research is being done everyday in the world of e-commerce as con-
sumers and merchants alike realize how powerful of a selling tool the internet has become.
E-commerce has become a research area in itself. However, my research also deals with
Human-Computer Interaction as well as cognitive science with regards to understanding
the decision-making process of consumers shopping online. Designing interfaces with trust
in mind is a concern for HCI [71].
1.3 The Need for Research
Despite the increase in research, the online shopping experience is still lacking; at times
creating a scary and frustrating experience for consumers. Both personal experience as well
as formal studies show the need for improvement [14] [78]. The study of trust online is
lacking [46] [92] [2] [3] and of the work that has been done, there is little agreement [17]
on how trust is created, sustained and lost online. Egger points out that ?the discipline of
HCI currently lacks substantive knowledge about how trust is formed, maintained and lost
in the electronically-mediated buyer-seller relationship? [20]. What authors have agreed on
is that trust is important and research now needs to focus more on how it can be developed
online [79]. It is evident that there is still room for improvement in e-commerce.
1.4 Approach Used
An observational study was conducted involving participants shopping online. The key
value of this study is that the participants made actual purchases online: they spent their
own money. Unlike a mock purchase study [76] [53] [22], where participants are asked to
2
either pretend to shop at a fake or dummy store or asked to say what they would buy or
how they would feel if they were to make a purchase, this study was of the real thing and
provided more insight. The observational study provided valuable qualitative data, aiding
in understanding not only the process of how consumers shop online but the role that trust
and trustworthiness play in that process.
After completing the observational study, a questionnaire was developed. This ques-
tionnaire contained questions created from the data found in the observational study as well
as knowledge obtained from the literature review. Because of the amount of time involved
in observations, interviews, and transcription, a large number of participants would not
have been feasible in the observational study. However, the questionnaire was short and
concise, and as such, was given to well over 200 participants. Many past questionnaires are
not throughly thought out [77] [75] [14] and it was a goal to create a questionnaire that
provided solid and informative quantitative data.
Reviewing both the qualitative data from the observational study and quantitative data
from the questionnaire, a conceptual model was created for building trustworthiness online.
This conceptual model expresses the main factors of shopping online and their relationships
with respect to their impact of trustworthiness in an online store. This conceptual model
could be further utilized to develop guidelines for trustworthiness in e-commerce.
3
Chapter 2
Literature Review
Recently, more and more research is being focused on the role of trustworthiness online.
From reviewing the current literature of trustworthiness online, it is seen that understanding
how trust is developed and maintained in everyday relationships is a step that is often
overlooked. This literature review explores not only work regarding trustworthiness online
in relation to e-commerce, but research of trust in itself, as in other areas such as psychology
and sociology.
2.1 Trust
Trust is an important issue in personal relationships [10] [58] and in (o?ine) commerce
[81]. However, the issue of trust online is also important[54] [31] [73] [69] [87] [36] [29].
Trust has been characterized as not only the ?foundation? of commerce [88] but that trust
is ?essential? for commerce [81] as well. Salam et al. [75] state that trust ?...plays a key
role in many such transactions that occur over the Internet? and Jones et al. [42] state
that trust in technology is ?an increasingly important issue?. Many authors point out how
critical trust is to e-commerce [68] [3] [15] [9] [92]. Others look at the idea of distrust, rather
than just a lack of trust, as being a barrier online [13] [55]. Often, however, the focus of
e-commerce generally tends to be on technology [40]. Trust online is a more important issue
for e-commerce than technology [43] [44]. Many feel that the more trustworthy an online
store, the more successful it will be [83] [31] [12] [74].
4
It seems clear that it is in agreement that trust is important, but what exactly is trust?
Unfortunately, the popular literature seems to assume that everyone knows what trust
means and therefore, there is no need to provide some kind of definition. From reviewing
the research literature it has been seen that on the occasion when trust is defined, most
authors do not agree on one and the same definition.
2.1.1 Definition of Trust
In the majority of literature dealing with trust, whether it be o?ine or online, there is
no consensus on the true definition of trust [15]. The lack of an agreement on one definition
could stem from the idea that trust is a multifaceted concept [79] [15].
Authors do agree that trust is a difficult concept to define [33] [37] [35]. This difficulty
is due in part to our daily vernacular, interchanging terms like trustworthiness and trust,
or entrusting and trusting. Barber states that ?in both serious social thought and everyday
discourse, it is assumed that the meaning of trust, and of its many apparent synonyms, is so
well known that it can be left undefined or to contextual implications? and that ?vagueness
is apparent also in the multiple meanings given to trust? [5]. Hardin agrees that ?we often
tend to suppose that our quick, even sloppy intuitions or insights are foundational, not
merely casual? [37].
Some believe trust deals with behaviors [9] [61]. Nielsen states that ?true trust comes
from a company?s actual behavior towards customers...? [62]. Olson states that ?people
learn to trust others by noting their behaviors? [63]. Others feel trust is a cognitive choice
[51] [71]. Lewis et al. state that ?we cognitively choose whom we will trust in which
5
respects and under which circumstances, and we base the choice on what we take to be
?good reasons,? constituting evidence of trustworthiness? [51].
Trust evolves over time, but exactly how is not so clear. The literature has conflicting
views on whether trust is hard or slow to build over time [88] [62] or whether trust is built
quickly in the beginning [6]. However, it is in agreement that trust in a merchant is a good
thing [90] [2], but as to exactly how this trust works is not yet completely understood [90].
2.1.2 Intentions and Competence
We have expectations when we place trust in someone. Govier states that expectations
of trust relationships have two dimensions: motivation and competence [33]. One can be
motivated to be trustworthy by self-interest, by what he or she gets out of being trustworthy.
Or, one can be motivated by the interests of the person who is placing the trust. Hardin
claims that trust is an issue only when the trusted party has concern for fulfilling the other
party?s interest and not his own [37]. Govier states that ?to trust people is to expect
that they will act well, that they will take our interests into account and not harm us?
[33] and similarly, Barber describes a trustworthy person as someone who places ?others
interests before their own? [5]. The intentions of a trusted party affect his or her level of
trustworthiness [79] [61] [19] [74].
Not only do we want a trusted party to be concerned about our interests, we want him
to be competent as well [56] [74] [67]. ?Technical competence? is an important facet of trust
[5]. If a person feels someone lacks ability necessary for the relationship, this person will
not place trust in that someone. Basso et al. [6] state that trust ?...can be based upon the
rational appraisal of a partner?s reliability and competence.?
6
2.1.3 Cooperation, Expectations, and Confidence
When attempting to define trust authors mention trust with respect to cooperation,
expectations, and confidence. Trust promotes or causes cooperative behavior [78] [28] [10]
as Friedman states that ?a climate of trust eases cooperation among people...? [27]. One
may assume that two people who cooperate must trust each other to a certain degree.
This is Govier?s view who makes a direct association between interaction and trust [33].
However, Hardin [37] points out that this is not necessarily the case. A person can engage
in cooperation not because she trusts someone but because she has no alternatives.
Also, a person may trust someone but never have the opportunity to act on that trust.
Therefore, it is important to draw a clear distinction between trust and action. According
to Hardin [37], ?trust is thus inherently a matter of knowledge or belief? and it is important
to note that there is no risk in trusting alone, the risk is in acting on trust.
Many feel trust is about expectations [31] [9] [79] [92] [39], expectations about the
honesty [28] [31] [56], reliability [3] [15] [46] [30] [2] [39] [93], dependability [26] [56] [79],
predictability [15] [7] [74], availability [39] and credibility [10] [9] [19] of another. However,
Friedman makes a distinction between relying on and trusting [27].
Many believe that having confidence in someone indicates trust [26] [49] [7] [30] [61].
Ferraro defines trust as ?...one in which confidence is place? [24]. Cassell et al. states agree
stating that ?trust among humans depends on ...confidence in one another?s judgment...?
[10].
7
2.1.4 Uncertainty, Risk, and Vulnerability
Trust is also thought as one dealing with overcoming risk [75] [42] [86] [35], vulnerability
[27] [63] [11] [31] [15], and uncertainty [34] [65]. Bickmore et al. state that ?trust is a
prerequisite for actions involving another agent in which one may suffer physical, financial,
or psychological harm...? [9].
Trust is only an issue if there is some amount of uncertainty involved. Moorman et al.
state that trust involves ?vulnerability and uncertainty on the part of the trustor? [61]. One
must have enough confidence in someone to overcome this uncertainty. Trusting someone
means taking a risk or, as Govier puts it ?trust is risky? [33]. As discussed in the previous
section, Hardin would likely feel that she should have said instead that acting on trust is
risky [37].
Trust involves choice, i.e., the concept of trust is meaningless in a deterministic world
[37]. The concept of trust is one that is used to ?decrease complexity? [15]. Rieglsberger et
al. agrees stating that trust ?helps to reduce...complexity - it is a shortcut for a detailed,
laborious evaluation of the relevant risks and benefits? [71]. This idea may be equivalent to
the statement that ?E-Commerce trust begins in chaos and ends in trustworthiness? [12] in
that trust reduces the complexity and makes order out of something chaotic.
2.1.5 Balance
As mentioned previously, shopping online can be risky for consumers and can put the
consumer in a vulnerable position. In order for trustworthiness to be obtained online, a
balance must be reached between the needs of the consumer and the needs of the online
merchant as Egger states, ?for users to adopt Business-to-Consumer (B2C) e-commerce, it
8
is imperative that the benefits of using this new commercial medium significantly outweigh
the potential risks and inconveniences? [20].
If the balance of power is shifted from the online merchant towards the consumer, the
consumer will feel more in control and more likely to trust the site [18] [38]. The lack of
control consumers can feel is a hurdle for creating trustworthiness online [38].
Tan et al. takes on a different view stating that ?...the more there is of trust, the less
there is of control and vice versa? [87], meaning the more trust a consumer holds, the less
the need for outside control mechanisms.
2.1.6 Security and Privacy
Many discuss the issues of security and privacy when speaking of trustworthiness online
[21] [50] [16] [57] [67] [93] [29]. Security concerns can be a major barrier in getting consumers
to shop online [64] [47] as well as a concern of privacy [24] [86] [39]. Araujo et al. state
?the lack of faith on the security and privacy of transactions accomplished on the Internet
is a significant obstacle for an extensive use of electronic commerce among Internet users?
[3]. Yoon states that sites will have to demonstrate ?their trustworthiness through the
state-of-the-art technology? [92].
Even though security is an important issue for trust, having a secure online store is not
enough. Even if there were a ?perfect system? for completely secure transactions, consumers
will not necessarily shop online [23]. Salam et al. agree saying, ?...we believe that secure
technological infrastructure is only a necessary foundation and by itself not sufficient for
creating the level of trust needed for spontaneous electronic transactions over the Internet?
[75].
9
Much of the literature states that privacy issues are more of a concern than security
issues [11] [8]. That is, consumers are more worried about how a company will handle their
personal information such as email addresses and phone numbers, etc., than what type of
encryption is being used for transactions, etc. Petre et al. state that consumers use privacy
policies as a cue to a online store?s trustworthiness [66].
2.1.7 Context
Context is important when discussing trust [5] [33] [37] [67]. Rarely do we trust a
person with everything, rather we trust people in a specific context only. Trust is different
in different contexts or situations. Davenport states the ? ?locus of trust? is likely to be
diverse in any given situation? [17]. This can imply that trustworthiness with regards to
shopping online is different than trustworthiness in shopping in brick-and-mortar due to the
different context of online or o?ine.
Often context is not discussed but implicitly assumed [33] [37]. This leads to an obvious
problem: the meaning of trust differs from author to author and people less aware of this
problem will simply ignore the context altogether. Hardin states that this ?...is an inherent
problem with the use of ordinary notions in such discussions. It often requires deliberate
effort to avoid falling into vernacular usage and, hence, into drawing the wrong implications?
[37]. Based on Govier?s insights [33], we may feel fine having a certain person fix our
computer but would be uncomfortable relying on the same person delivering an important
parcel. Therefore, behavioral measures, to be meaningful and generalizable, have to be
associated with a particular context [37].
10
Marsh et al. state that ?...it is clear that in fact trust is a situational phenomenon
- the trusting decisions we make are based on the situation we find ourselves in, and the
context we derive that from? [54]. Grabner-Kraeuter believe that noting context is ?critical
to the understanding of trust? [34].
Context can also apply to different types of products being sold online [35]. Certain
products sell more easily online than others. Ang et al. report that ?it is worth noting that
the experience to date clearly suggests that certain product categories are more amenable
to Internet transactions. For example, CDs, software and books are the three most popular
products bought on the Internet? [2]. The authors suggest that the reasoning behind this
fact is the ability to easily provide more precise and accurate descriptions of these products.
2.1.8 Length of Relationship
The longer the relationship, the more trustworthy parties become [33] [37]. If trust had
declined over time, the relationship would have been discontinued. Thus, a long relationship
generally implies strong trust that extends into the future [33]. Hardin states that ?it is
primarily those with whom we have ongoing relationships that we trust. And the richer the
ongoing relationship and the more valuable it is to us, the more trusting and trustworthy
we are likely to be? [37].
2.1.9 Credibility, Brands, and Reputation
Trustworthiness is a key component to credibility [26]. A positive reputation is also
a result of trustworthy behavior [34] [47]. A merchant?s reputation can have an effect on
a consumer?s view of trust of the merchant [56] [39] [93] and affect how willing the con-
sumer is to make a purchase [34]. Hardin describes reputation as perceived trustworthiness
11
[37]. Reputation can be created via word-of-mouth, upon which consumers tend to rely
heavily [21]. New relationships with other people and organizations are often based on
recommendations from other sources.
Brands are associated with reputation and credibility. Fang et al. state, ?Brand
name is one of the major factors, probably the most important one, that has an impact on
shopper?s trust in an e-commerce Web site? [23]. Cheskin Research state ?...one key aspect
of establishing trust with consumers is the reputation of a brand...? [12]. The popularity
of a brand name can be ?considered as an essential ingredient for garnering trust toward
online web sites? [92]. Ang et al. have termed how consumers are more likely to buy from
popular brands as the ?brand equity effect? [2].
2.1.10 Design
Many authors feel that the design of the interface (in this case the website) can influence
trustworthiness of an online store [23] [82] [29]. The manipulation of visual elements in the
interface can produce feelings of trustworthiness [45] [15] [20] [85]. The quality of the
website, whether the site has typos, grammatical errors, boken links, etc., has an effect on
trustworthiness [23] [21] [93].
Consumers draw on cues from the interface to determine their vulnerabilities as well
as the store?s intentions [27] [71]. Olson et al. state that ?the design of the interface needs
to recognize the kind of experience and social cues people need to be able to feel trust...?
[63].
Having an interface that exudes trust will aid in the success of E-commerce. Marsh
states ?...designing interfaces which take trust into account and reason using trust will
12
result in more effective, comfortable interactions for the user? [54]; while Lee et al. state that
?one of the critical requirements for the success of electronic commerce is the appropriate
customer interface...? [49]. The importance of a trustworthy interface to an online store
is a point made by Bauer who states ?customers apparently take a critical view towards
information presented to them via the Internet? [7].
The relative ease of use is an important determinate of trust online [21] [41] [47] [67]
[39] [93]. Ease of use online can make consumers feel more secure [18] which intern could
promote trustworthiness.
It is important to design the interface around good content [70] and for it to have strong
navigation and effective navigation [14]. The eCommerce Trust Study conducted by Cheskin
Research states that ?effective navigation is generally a precondition to communicating e-
commerce trust and the perception that sites meet customer needs...? [12].
Marsh et al. state, ?...designing interfaces which take trust into account and reason
using trust will result in more effective, comfortable interactions for the user? [54]. Under-
standing trust will allow us to create better interfaces to online stores. D?Hertefelt states
that ?only from an understanding of the causes of trust on the internet can we derive design
guidelines that will allow us to build websites where people feel safe? [18].
2.1.11 Trustmarks
There are various third-party trustmarks available today, such as TRUSTe, VeriSign
and BBBOnline. These trustmarks are ?meant to instill trust in the online consumer by
verifying the Web site has a policy about its collection and use of personally identifiable
information? [60].
13
Current literature investigates the effectiveness of these trustmarks on their ability
to enable online stores to give the impression of trustworthiness. Tang et al. state that
trustmarks ?appear to enhance confidence for online transactions? [88]. Benassi suggest
that trustmarks improve trust online stating that TRUSTe is ?accelerating the growth
of the Internet? [8]. Rieglsberger states that trustmarks show that the merchant shows
?rational interest - and also the ability - to act as promised? [71]. Cheskin Research reported
that ?web-based seals of approval matter more than credit card brands in communicating
trustworthiness ...? [12]. Petre et al. state that trustmarks should be used as a ?...cues
to enhance trustworthiness? [66].
However, McKnight et al. offer a different take on trustmarks stating ?there is little
empirical evidence that [trustmarks] do, in fact, increase consumer trust? [56]. Consumer
WebWatch found that trustmarks seals of approvals are not that important for consumers
[14]. Many consumers do not recognize trustmarks and are unaware of what an online store
must to do obtain a trustmark [59]. Sisson et al. make the important point of explicitly
saying one is trustworthy is not usually needed for a trustworthy individual or organization.
Sisson states, ?ecommerce sites seem to shout the message that they are trustworthy, that
users need have no trepidation over purchasing from these sites, but trust dervies not from
assertions but rather from experience and judgment? [80].
Atif takes the idea of trustmarks even further by suggesting trust can be built online
with the use of a third party referred to as a ?trust service provider (TSP)? [4]. The
TSP acts as an ?...Internet-based intermediary that assumes responsibility for a smooth
transaction? [4]. One obvious drawback to this type of solution is how one promotes trust
in the trusted service provider.
14
2.1.12 User Characteristics
All consumers are different. Many authors point out how these differences can affect a
consumer?s trust online [30] [52] [35] [29]. Friedman et al. note that ?...people can engage in
virtually identical online interactions, yet reach widely disparate judgments about whether
the interactions are trustworthy? [27]. Trust is an issue that is of different importance to
different people [83]. We all possess individual characteristics that affect our decision to
trust [34][56] and these characteristics can include the age, experience, occupation, and
disposition to trust of the consumer [82] [93], as well as gender [84]. Sisson states that
?Trust is a subjective judgment that must be made by every user for any site, because
individual goals vary and definitions of trust are unlikely to be consistent? [80]. Tan et al.
agree stating, ?Just as we said the level of trust considered sufficient is different for each
individual, the level of trust a person has in a certain situation is different for each person?
[87].
Authors tend to point out two major determinants of user characteristics: consumer
disposition or propensity to trust [20] [56][14] [93] and a consumer?s experience [93]. Some
people and some cultures tend to be more trusting than others [63]. Some feel trust is
learned during childhood and that we learn trust from our parents [90]. Grabner-Kraeuter
state ?The effect of the measures to develop and maintain trust in e-commerce is increased
or decreased by several other - person-specific and situational - factors that cannot be
controlled by the online retailer? [34] while McKnight et al. tend to disagree stating, ?We
posit that when consumers have experienced a web site, individual disposition to trust, while
still an important influence, will not directly affect trusting beliefs or trusting intention.
15
Rather the impact of this variable will be full mediated through institution-based trust and
perceived site-quality? [56].
Experience online and in previous trusting situations can affect a consumer?s propensity
to trust online [41] [25]. The more informed a consumer is the higher the expectations that
consumer has about the online shopping experience [78]. Fogg et al. point out how the level
of education obtained by a consumer can even affect his or her judgment of trustworthiness
online [26]. Jarvenpaa et al. state that the more experience a consumer has online, the
less likely they are to trust an online merchant. Hoffman et al. state that, ?In essence, the
more experience one acquires online, the less important are the functional barriers to online
shopping and the more important are concerns of control over personal information? [38].
Egger agrees pointing out that as users become more experienced they are less concerned
about IT difficulties and more concerned about company policies [21]. Moorman et al.
state that, ?Users with lower levels of experience are expected to be more willing to trust
researchers because of their lack of company, marketing, or research knowledge. Experienced
users, in contrast, are likely to have more knowledge and confidence in their own ability
to use research and to manage relationships? [61]. While the Consumer WebWatch group
found the contrary, ?the most experienced Internet users generally trust people more than
novice users? [14].
Authors tend to categorize consumers into different groups. Strader et al. grouped
consumers as ?price-sensitive? and ?trust-sensitive? individuals [83]. Lee et al. stated,
?Visitors to a web site can be classified into two broad categories, low involvement surfers
and high-involvement surfers? [49]. Sisson states that consumers have different ways of
evaluating levels of trust; they either have ?strict measures? or ?rely on a more subjective
16
?feel? for determining whether to trust somebody? [80]. He goes on to state, ?The path
people take to a level of trust can vary greatly, because some people work from the premise
that trust must be earned, and some from the premise that trust is assumed be can be lost?
[80]. Uslaner states that, ?Going online does not make people either more or less trusting,
though trust shapes how people interact with each other? [90] while the Consumer Web
Watch group on the contrary claim that one is more likely to be a ?trusting person? if he
or she shopped online [14].
2.2 How My Research is Different
My research is different due to my concentration on first reviewing trust literature,
and then applying this knowledge to an online setting. Understanding the concept of trust
in relationships outside of commerce can provide valuable insight to trust online. More
importantly, my research is different in that I conducted a unique study of actual purchases,
which provided insight that no mock purchase study can provide. What people say they do
or will do rarely is that same as what they actually do. Many studies have been conducted
using interviews and questionnaires and observations based on mock purchases [23] [6] [11]
[31] [92] [22] [91]. It is important to observe actual purchases because consumers can not
be expected to give accurate responses regarding actual shopping experiences while in a
virtual or pretend setting. Sisson agrees, stating that consumers pick up on ?implicit cues,
often without realizing it, and it is to these implicit messages that commerce sites should
pay particular attention? [80]. Grabner-Kraeuter also agree, commenting on the intricate
nature of trust stating ?...trust is a complex and dynamic phenomenon that can not simply
17
be ?produced? by applying adequate instruments. Expectations and actions based on trust
result from a delicate, situational interplay of different factors? [34].
18
Chapter 3
Statement of the Problem
Trust continues to be a challenge online [63]. The lack of trust online has been cited as
an ?impediment? to the growth of e-commerce [88] as well as a ?major inhibitor of online
transactions? [92]. With sites receiving low trust ratings [14], online shoppers are still feeling
insecure [88] and there is little agreement of how trust works online [17]. It is evident that
the perceived trustworthiness of online stores needs improvement [72].
Research discussing the relationship between trustworthiness of an online store and
online shopping characteristics (such as context, store design, company policies, etc.) as
well as people characteristics (such as one?s propensity to trust, experience shopping online,
etc.) is lacking. A validated concrete conceptual model for developing trustworthiness
online has yet to be developed. Being able to model this relationship will allow guidelines
to be drawn. My research aims to solidify the relationship of trustworthiness and online
shopping.
I will propose answers to the following questions of ?How is trustworthiness online
developed??, ?How do the issues of user characteristics, design of the online store, and
company policies affect the online store?s trustworthiness??, and ?Once trustworthiness is
developed online, how can it be sustained??. Finding the answers to these questions involves
understanding the process by which people make a purchase online. The answers to these
questions will allow online merchants to improve trustworthiness in their online stores.
19
Chapter 4
General Trust Model
Based on the literature reviewed, the following model of trust has been developed.
Figure 4.1: General Trust Model
4.1 Situation
The left section of the model entitled ?Situation? contains the items necessary for trust.
There should be a choice of whom to trust. In other words, there should be more than one
possible trustee. As Hardin states, ?...trust has no meaning in a fully deterministic setting?
[37]. If there were only one option or trustee then the trustor would be forced to use the
trustee whenever the need arose.
20
Secondly, there needs to be some risk involved for the trustor [75] [42]. If there is no
risk involved then trust is not an issue. Trust is a way of handling or overcoming risk.
4.2 Factors Affecting Trust
The next section of the model contains items that affect trust. These are the factors
that will determine whether an individual will trust another. This section contains three
main items: context, trustor characteristics, and trustee characteristics.
Context is an important factor that can affect trust [5] [33] [37]. We trust people in a
specific context, rather than trust someone in all situations. For example, we may have a
trusted car mechanic but would not trust that same individual to babysit.
Trustor characteristics refer to individual characteristics of a person placing her trust
in another. Trustor characteristics include the trustor?s disposition to trust [20] [56][14] and
past experience [41].
Trustee characteristics refer to individual characteristics of one whom trust is being
placed upon. An ideal trustworthy individual has good intentions, is competent, has a good
reputation, is predictable, honest, credible, reliable, and dependable.
4.3 Need
In order for an individual to act on trust, there has to be a need. Trust is a matter
of knowledge or belief and is a separate entity from action. It is entirely possible to place
trust in many different individuals but never have the occasion to act on that trust.
21
4.4 Indicators/Outcomes
Indicators or outcomes from acting on trust are shown on the right hand side of the
model and are cooperation and confidence. It should be noted that cooperation does not
always imply trust. It is possible to cooperate because of no other alternatives. But in the
case of the model, choice is a requirement in the ?Situation? section. Considering there is
a choice, cooperation is an outcome of trust.
The following table summarizes the model giving references to the literature review.
22
Table 4.1: General Trust Model - References to Literature
23
Chapter 5
Observational Study
5.1 Methodology
The observational study was designed in two parts. The first part consisted of the
observation of participants shopping online. The second part consisted of an interview con-
taining open-ended questions, with a portion of the questions arising from the observation in
part one. Using methodological triangulation by reviewing the observations and interviews,
codes and themes were generated.
5.2 Participants
Before the study was conducted, a consent form was obtained from Auburn University?s
institutional review board, human subjects office. The consent form assured participants
that all information obtained from them in connection with this study would remain anony-
mous with the use of pseudonyms.
A total of nine participants participated in the study. Because of the amount of time
involved in observing, interviewing, and transcribing, a very large number of participants
would not have been feasible. However, this study is followed by a questionnaire given with
a large number of participants. The participants had varying computer backgrounds, but
all had had at least one previous experience shopping online. All participants were over the
age of nineteen and consisted of five females and four males.
24
5.3 Data Collection
Convenience and snowball sampling were used to obtain participants. An email was sent
out to the Computer Science and Software Engineering department asking for volunteers.
It was also hoped that participants would refer others to volunteer.
The participants were not asked to perform a specific task, such as ?find the best deal for
...at your choice of these sites? or ?here is a fake credit card number, pretend to buy at the
following sites?. These types of scenarios were contemplated, but it was realized that these
types of tasks would yield less authentic data. This observational study examines a thought
process, and the role of trust within that thought process. To understand this process
of consumers? making purchases online, observations and studies should be conducted of
consumers actually doing so. In order to achieve more useful data, the participants were
asked to participate only if they were already planning on making a purchase online.
Participants were observed and recorded shopping online using the software program
?SnagIt? (http://www.techsmith.com). The software recorded all views of the monitor
and voice of the participants. The observations were started by explaining the purpose
of the study and then asking participants to use the ?think-aloud? protocol, which had
the participants speak their thoughts as they were shopping online. At times, questions
were asked during the observation if clarification was needed from the participant, or if the
participant remained quiet for an extended period of time. All participants were observed
shopping online at the same machine, at the same location, with the same connection speed.
After the observation of each participant, a semi-structured interview containing open-
ended questions was conducted. The interview consisted of predetermined questions re-
garding their experience of online shopping in general, this particular shopping experience,
25
and questions that arose from the observation. The length of time for each participant?s
observation/interview varied, depending on the participant?s task, with ranges from under
ten minutes to over a half-hour.
5.4 Pilot Study
A pilot study was previously conducted testing the methodology presented above [48].
The study addressed the issue of shopping cart abandonment - consumers adding products
to their online shopping cart yet not following through with a purchase. The study consisted
of three subjects, two male and one female, and was conducted during the summer of 2001.
The pilot study found the following results:
? Having to log-on to sites frustrates consumers.
? Online forms need improvement.
? Consumers shop online more with the intent of purchasing a particular product than
browsing.
? Consumers are quick in shopping online.
? Reputation and Need are major factors for consumers purchasing online.
? Consumers want upfront pricing information.
? Consumers are driven by price.
? Some products are easier to buy online than others.
? Experienced online consumer?s concentrate less on site design and more on product,
price, and security, and policies.
The study provided a better understanding of the process by which people make a decision
to buy online. The study showed that it is trust that in the end gives consumers the
confidence to go through with a purchase.
26
5.5 Participant Shopping Experiences
The following is a brief description of each of the participant?s experiences during
the observation, followed by a discussion of common findings found from the study. A
breakdown of the participants? shopping experience is shown in the following table.
Table 5.1: Participant Shopping Experience
5.5.1 Participant 1 - Bob
Bob is a graduate student in the Computer Science and Software Engineering depart-
ment and was shopping for a JVC brand microphone for his JVC digital camera. The
JVC list price for this microphone was $149, a relatively expensive item. Bob previously
researched various microphones and decided on purchasing this particular JVC microphone.
27
Bob was a comparison shopper and was driven by price for the majority of his shopping
experience. He knew he could purchase the microphone directly from JVC but felt he could
get the same product elsewhere for a cheaper price.
At first things went smoothly for Bob. He looked up the model number from the JVC
website and then searched for it in two different search engines, each giving what seemed
like promising results. It took Bob less than a minute after searching for the microphone
to find it for $20 cheaper at a site for the company B & H Photo.
However, for numerous reasons, including lack of product details, reputation, and poor
navigation at various sites, Bob did not make a purchase.
5.5.2 Participant 2 - Jack
Jack is a graduate student in the Computer Science and Software Engineering depart-
ment. He shopped for two Christmas presents - a Nintendo joystick for his brother and a
set of Dean Martin Variety Show DVDs for his father.
Jack?s shopping experience was challenging due to the fact that the Nintendo joystick
was sold out at every site he visited, making him unable to follow through with the purchase.
Jack also ended up not making the Dean Martin DVD purchase as well. Jack wanted to buy
the set of DVDs but the site he found was a subscription based site where the first DVD is
purchased and the subsequent DVDs are then mailed periodically for purchase. Jack was
unaware of this and did not want to do a subscription.
Jack did try eBay for both gifts when he could not find them at non-auction sites.
eBay did have a result for the set of DVDs, but they were too expensive for Jack.
28
Jack was determined to find both products. When they were unavailable, he did try
to think of alternative gifts ideas but the sites he visited did not make any suggestions to
him for similar items. In the end, Jack gave up his search for both items.
5.5.3 Participant 3 - Jan
Jan is a graduate student of the Computer Science and Software Engineering depart-
ment. She shopped for a Christmas present for her boyfriend, a hunting dog tracking collar.
The site Jan had intended to purchase from, Johnson?s Telemetry, was down. Jan
did a Google search and clicked on a link taking her to a site that looked very amateurish
and unprofessional. Jan was focused on getting this Christmas present off her list and was
willing to make a purchase from this site until the site needed her to either phone, fax, or
email her credit card information.
Jan did not feel comfortable emailing her credit card information and then remem-
bered another site she was familiar with, WICK Outdoor Works. However, Jan did not
remember the URL and it took her several minutes and several searches to finally find the
site. Unfortunately, WICK Outdoor Works also needed her to phone in her order for the
dog collar. Jan did not want to do that.
After searching Google again, Jan finally found a site that would let her complete her
order all online. The site had a similar product with a different brand. This site, Vetvax.com
(Discount Pet Supply Plus Dog Supply Vet-Vax, Inc.) was also very poorly designed. Jan
did not seem to mind and made her purchase here for almost $160.
29
She did not have too many issues during checkout except she was confused by the
?order instructions? box and she also hit the ?Continue Shopping? button instead of the
?Checkout? button.
Overall, Jan did not care about the site design at all, as long as she could complete her
order online. Jan?s shopping experience was driven by her need for a Christmas gift. She
was determined to make the purchase regardless of price or site design.
5.5.4 Participant 4 - Marsha
Marsha is an undergraduate student in the English department. She was shopping
for a Christmas present for her boyfriend?s younger sister. During her shopping experience
she stated this was her first purchase from an online store. Her only previous shopping
experience was a few times with eBay, buying CDs and a jacket.
Marsha did not have a product in mind and only visited sites, Delias.com and eBay.com.
She went to Delia?s first and had no problem navigating the site viewing different products.
To say her shopping experience was challenging would be an understatment. One of her
main struggles while shopping was she was unsure of a suitable present for a pre-teen girl.
At Delia?s, she found a couple of items, a purse and a pair of slippers, and added them
to her cart. She then went to eBay, hoping maybe to find a small jewelry box. However,
she simply searched for jewelry and thousands of auctions were displayed making it difficult
for her to find what she was looking for. She never thought to narrow her search.
30
After consulting her boyfriend she decided to purchase the slippers at Delia?s. Checking
out was extremely difficult and frustrating for her. This being her first online store shop-
ping experience, she simply did not know how to check out and called upon her boyfriend
repeatedly for help.
On her own she was not able to change the size of the slippers once they were in her
cart, in which she ended up with two pairs. When she corrected this (which was actually
the only task she was able to do on her own - remove item) she was disappointed to find
that the size slippers she wanted were out of stock.
After a discussion with her boyfriend she decided to go with the delayed delivery and
purchase the slippers anyways. The checkout form was difficult for her to fill out. It did
not state which fields were required, causing her to get angry after she submitted the form
and was told in red she was required to fill out certain fields. One of the fields she did not
understand was why she needed to supply an email address. I assumed this was so the site
could send her an order confirmation email, but the site did not tell her this.
Marsha also did not understand the billing process. She did not realize that the billing
address on her credit card had to match the address she was inputting into the form. The
site should have explained this to her. All the checkout pages were overwhelmed with
unnecessary information, making it challenging for Marsha to check and see if her order
was correct.
It seems Marsha was competent in navigating sites to look for products, but when it
came to follow through with the purchase, she just did not know how to check out.
31
5.5.5 Participant 5 - Chuck
Chuck is an undergraduate student in the Computer Science and Software Engineering
department. Chuck was purchasing a magazine subscription to Gourmet Magazine for his
father. He chose to do so at Amazon.com. Chuck is a big fan of Amazon and overall his
shopping experience went smoothly.
The only problem he encountered was in the beginning he wanted to log in and there
was not a place for him to do so. Chuck had no problems searching for the magazine, adding
it to his cart, and checking out with a purchase price of $15.
Chuck was very price oriented, constantly reading the promotional offers displayed.
Even though Chuck was a loyal customer to Amazon.com, when it came time for him to
follow through with the purchase he was very hesitant and took extra time reviewing all
the information for his order.
5.5.6 Participant 6 - Cindy
Cindy is a graduate student in the Computer Science and Software Engineering de-
partment. Cindy needed to purchase tall-sized jeans. Normally she cannot find jeans long
enough to fit her in the stores around town. Cindy visited one of her favorite sites, Long
Elegant Legs, where she had shopped numerous times before. Cindy quickly found two
pairs of jeans and decided to make a purchase for a total price of $104.
When it came time to checkout Cindy could not find a way to log in so she would not
have to reenter all of her personal information. Cindy ended up reentering her information
and checked out. At the end of the checkout the page prompted her to save her information
32
for checking out in the future, which frustrated Cindy even more since she could not log in
to the site to begin with.
After her quick purchase, Cindy shopped around at the current site as well as another
clothing site, Newport News, to see if there was anything else she might want. However,
due to poor site structure and product description, Cindy was not compelled to make any
unplanned purchases.
5.5.7 Participant 7 - Sue
Sue is an employee of Auburn University and shopped for a jewelry box. Sue?s shopping
experience was the worst of the study. She had a particular jewelry box in mind and searched
a few sites for the cheapest price.
She found a great deal on the jewelry box for under $40 at a site called Dakmart, but
when she went to check out a security warning popped up and scared her away. She found
the next cheapest for under $50 at another site, Catalog City, and proceeded to check out.
When she started to check out the form asked her to register at the site which she did not
want to do and proceeded to check out without registering. She entered in her information
and submitted the form.
Unfortunately, something went wrong. The site loaded a standard page - no confir-
mation number, no end of purchase page. Neither Sue nor myself knew exactly what went
wrong. Sue was frantic. She had no idea if the order went through or not. There was
no phone number to call and the only way she could contact them was through a contact
form. She kept checking her email for a confirmation notice, but nothing arrived. Sue was
33
very upset not knowing if she would be charged for the jewelry box and ended her shopping
experience. Days later I spoke with Sue and found out luckily the order did not go though.
5.5.8 Participant 8 - Tina
Tina is a graduate student in the Computer Science and Software Engineering de-
partment. She shopped for an international phone card to Asia. She shopped at the site
First Phone Card, where she has been ordering phone cards from for three years. A friend
introduced her to the site.
She had specific criteria for her phone card. She needed one that expired no sooner
than 180 days, charged about two cents a minute, and cost twenty dollars. She browsed
the site looking at various cards and after about five minutes found a card that met her
criteria. She mentioned this site offered discounts for return customers and logged in.
The checkout procedure was very basic and had an amateur look to it - bright blue
background with table formatting and a flashing image touting the security of the form.
Tina logged in as a returning customer and received a 4.5% discount on her purchase. Tina
did not mind the look of the site and was happy with her purchase.
5.5.9 Participant 9 - Greg
Greg is a graduate student in the Computer Science and Software Engineering depart-
ment. He shopped for an Audiovox cell phone cable. Greg was driven by need more than
price. He needed the cable soon, so he was willing to pay a little more at a more reliable
site.
His main requirement was that he had to have a driver come with the cable. At all the
sites he visited it was difficult for him to tell if the cable came with the driver or not. The
34
product description was not clear. In the end, based on his need to have the cable, Greg
took a chance and purchased the cable at Cell Phone Mall for $35, still unsure if the driver
software was included.
5.6 Data Analysis
Both the observations and interviews were transcribed. The transcriptions were read
and re-read several times. Themes and codes were generated by analyzing the transcriptions
with Glaser and Strauss? (1967) [32] grounded theory for qualitative data.
5.7 Findings
Trust is an important factor in online shopping.
For many of the participants, trust played a big role in the decision process of whether
or not to make a purchase at a store. Greg found the cheapest price for the Audiovox phone
cable shopping at an eBay store. However, Greg did not trust the eBay store enough to
follow through and decided to pay more elsewhere. ?$13.95, buy it now! ...This looks
good. I don?t know. I?ve never bought anything from an eBay store. I don?t know what
its like compared to buying from an eBay bid. And I?m not interested in trying that out
right now because I definitely need whatever I do tonight to be reliable because it is for my
business.?
Sue found the jewelry box she was looking for at a great price. She had never heard of
the site before and was hesitant, but decided to buy it anyway. When she went to checkout,
a security warning popped up and she abandoned the site stating, ?...There is a problem
with the security certificate? Oh no! I don?t think I?m going buy it from here. Since there
35
is a security alert, you know? Yeah, its a good price, but not worth...getting in trouble.?
The more product information, the more trustworthy the online store will be
perceived.
Searching for a good deal on a JVC microphone for his video camera, Bob comparison-
shopped and found the product for $20 cheaper than the JVC list price at an online store
he had never visited before. This particular online store, B & H Photo, had a professional
layout, a 1-800 contact number, a live help link, and touted itself as the ?professional source?
for photo, audio, and visual equipment. However, Bob did not feel comfortable making a
purchase there. Why? Mainly due to lack of product information; the site only displayed the
model number, a picture, and a one-line description of the microphone. Bob had done prior
research and already knew all the product information about the microphone. When asked
why the store?s lack of information prevented him from making a purchase even though
he already knew the product information, Bob replied, ?Yeah, I knew the product details
already, but the fact that they don?t even know the details...they might just ship me any
old thing.?
Thorough product information gives the perception of competence and knowledge. The
more competent and knowledgeable the online store, the more trustworthy it is perceived
to be. This agrees with the current literature stating competence promotes trust. Bob also
stated that he did not feel comfortable spending a lot of money at B & H Photo. When
given the scenario of his microphone only costing $10 at the store, Bob stated, ?I still
wouldn?t get it from [B & H Photo].? Because of the lack of product details, Bob felt the
online store lacked the competence and knowledge to send him the correct microphone.
36
Greg shopped online for an Audiovox cell phone transfer cable. The majority of the
sites displayed a picture and model number for the cable, but Greg became frustrated due
to the sites he visited not explicitly stating whether his purchase included driver software.
Design and usability are not high trust factors online.
Literature has stressed the important of design and usability when it comes to the
trustworthiness and success of an online store. This study, on the contrary, found consumers
place less importance on site design and usability and more on other aspects of shopping
online, such as product details, contact information, and price.
As Tina stated regarding the site she purchased her international phone card, ?...this
website, I don?t like its layout, but ...I always use this one. I trust this one, so I don?t
care.? And as Sue stated, ?I think if it is something I need or want, it doesnt matter if the
page looks good. ...Of course, aesthetics make things look easier and better or whatever,
but if it is something I know I really want or need, I?m gonna buy it anyways...? When
asked how he felt usability affects a stores trustworthiness, Greg stated ?...I?m not sure if
I can decide whether or not to trust a site based on its usability at all.?
Of course, an online store has to be usable enough for consumers to be able to make a
purchase. Jan purchased her dog-tracking collar at a site with extremely poor site design
having a very dated and unattractive look. However, Jan did not seem to mind. The site
had what she was looking for and was usable just enough for her to follow through with
the purchase. When asked if she trusted the site she purchased from, Jan replied, ?Yeah,
more so than some of the other ones...because they are pretty much ?ma and pa? shops.
37
Typically, the type of people that have [dog tracking collars]...are not the type that I think
either have the ability to or would try to take advantage of the situation.?
It is possible for poor usability to have a negative affect on trustworthiness if the con-
sumer cannot figure out all the details of their purchase. Jack stated, ?If I can?t find out
shipping really easily, that would concern me because if something would go wrong I imag-
ine I would get the runaround if I tried to phone them. If I could even find their number
on the website.? As long as the consumer can do what he/she wants to do, anything more
than that seems like ?icing on the cake?. For example, its unlikely that a consumer really
cares if it takes five clicks versus two clicks to find a product.
First impressions last.
If an online store makes consumers happy the first time around, the consumers are likely
to come back. Even if when they do come back they have a bad experience, consumers are
likely to be more forgiving than of a store they are experiencing for the first time.
During Bob?s product search for a JVC microphone, he visited a preferred site J R
Music World. He had been to the physical store and also made a purchase from online.
Bob went on and on at how great the customer service was at the store and how they
have all kinds of brands of electronics. However, Bob could not find the microphone on
the site. The site had changed since he last visited and Bob was unable to navigate the
store. Trying the sites search function yielded no results either. Bob spent several minutes
of frustration trying to find the microphone on the site. When asked in the interview about
his experience at his preferred site, Bob stated, ?...I know there was a section where you
could list products by brand stores, I think they have JVC, Sony, etc., but I couldnt find
38
it. But I have no idea if they are no longer doing that thing anymore or if they were. But
I already bought something from them, so its okay.?
Cindy shopped at her preferred site for jeans for tall women. Her site frustrated her
during navigation and checkout. She wanted to be able to log in and have the site already
have her information from her previous purchases. She could not find the link and had
to re-enter all of her information. Cindy did not mind too much though because she had
shopped there before and was satisfied with their service and products. This study?s find-
ings give the impression that trust can be built quickly and is easily sustained in the future
if the consumer has a positive first time shopping experience.
Context matters.
The study was consistent with the literature regarding context and trust. Some prod-
ucts are simply easier to buy online than others. The quickest and easiest shopping expe-
rience was Chuck?s. He purchased a magazine subscription at a popular online bookstore
that he had previous positive experience with. His product was the cheapest of all of the
participants and had an extremely low risk factor.
Consumer characteristics impact the consumers view of a store?s trustworthi-
ness.
Consumer characteristics affect consumers? view of a store?s trustworthiness. Jan, who
purchased a $150 dog-tracking collar at a small online store, characterized herself as a
trusting person. Marsha, however, was the opposite. Her shopping experience was full
of hesitations regarding how to check out, if her credit card information was safe, if the
39
shipping price and dates were feasible. Marsha?s previous online shopping experience only
consisted of a few eBay purchases. Marsha said the main reason she has not shopped online
much in the past was because she is a suspicious person by nature.
Another consumer characteristic aspect of the study was participants were either very
price-oriented or need-oriented. The price factor correlates with the literature involving risk
and trust. The less the product costs, the less risk the consumer is taking. Participants
tried to minimize their risk by shopping for the product with the cheapest price.
When participants were also driven by need, they seem to do whatever it took to
make the purchase. This study was conducted in November and December and many
participants were buying holiday gifts. Because of their need of a gift, many were willing to
place a purchase even if they did not trust the site. This verifies the literature that states
cooperation does not necessarily imply trust. Conversely, during the interview, participants
were asked if they could think of an online store they trusted, but could never see themselves
making a purchase from. Many could, which is consistent with the literature regarding the
distinction between knowledge and action. An online store could be extremely trustworthy,
but this does not necessarily mean it will be successful.
5.8 The Importance of Observation
?The obvious isn?t always apparent? - Paco Underhill [89]. Many times during this
study participants did one thing and then said another. It is extremely important to observe
participants in a natural setting as opposed to simply asking them what they would do or
think in a mock situation. Some of the participants were graduate students in the Computer
Science and Software Engineering department and as such, responded with what they might
40
have felt were the ?correct? answers during their interviews, reciting what they have learned
in their courses of Human-Computer Interaction.
For example, during Bob?s interview he expressed the importance of third-party en-
dorsements of the Better Business Bureau on online stores, yet observing him shop, he
did not seem to notice any third-party endorsements. Bob stated he did not trust online
stores that change formats which would cause him difficulty in finding products. Yet at his
preferred online store, J & R Music World, the site had changed, making it impossible for
him to find the JVC microphone. Also, earlier in the interview, Bob contradicted himself
by stating that he would not trust a store if ?over time the site looks the same for example,
that gets me, I mean are they even changing inventory or anything?? When Tina checked
out at her favorite phone card site, there was a flashing animation at the top of the screen
touting the site?s security. During Tina?s interview, however, Tina stated that a website
that had animations would not be trustworthy to her.
In Paco Underhill?s book Why We Buy, he states, ?There are surveys that do ask
customers for information about what they saw and did inside a store, but the answers are
often suspect. Sometimes people just don?t remember every little thing they saw or did in
a store - they weren?t shopping with the thought that they?d have to recall it all later? [89].
If I went by interviews or questionnaires alone, I would have missed out on vital clues into
the real online shopping experience.
41
Chapter 6
A Model of Trustworthiness Online
Using the qualitative data from the observational study, the general trust model pre-
sented in Chapter 4, shown below, can now be applied and modified for business-to-consumer
e-commerce.
Figure 6.1: General Trust Model
The situation for trust is present in online shopping. Regarding choice, there are
millions of online stores on the web consumers can choose from. Along with numerous
choices of online stores, there are also several risks associated with buying online. Some of
the risks include late arrival of an item, not receiving the item purchased at all, inaccurate
42
product description, being overcharged for an item, as well as having personal information
and credit card information compromised.
The observational study has shown that context matters when shopping online. Based
on the type of item being purchased, the issue of trust varied amongst the participants.
Trust was more of an issue with Bob purchasing an expensive JVC microphone than with
Chuck who purchased a $15 magazine subscription.
Trustor characteristics, disposition to trust and past experience, were shown to play
a part in shopping online. As expected, consumers with higher dispositions towards trust
were more trusting online. If a consumer has previous experience at a particular online
store this will affect his or her decision to return to the store. Past experience shopping
online in general can affect trust. Lack of experience can lead to more hesitation and
more surprises which can have a negative impact on the perceived trustworthiness of an
online merchant. Jan described herself as a trusting person, had substantial previous online
shopping experience, and stated that she had not had a bad experience buying online. On
the other hand, Marsha had a less disposition to trust and and little experience shopping
online. Marsha?s online shopping experience was full of hesitations and questions, while
Jan seemed largely focused on just finding her product. It took Marsha over 30 minutes
to purchase a $24 item at a larger, well-known store, while it only took Jan just over 11
minutes to purchase a $155 item at small unknown store.
Trustee characteristics are correlated to characteristics of an online merchant. The
observational study can equate the items in the original model to elements of the online
shopping experience.
43
The intentions of an online merchant can be seen through the prices of products dis-
played. If the merchant?s prices are unusually high, then consumers are likely to feel that
the merchant is concerned more about his own intentions, rather than the consumers?.
Also, displaying upfront shipping costs, having specials or deals, and providing savings or
discounts for return customers show the merchant is concerned about the consumer which
can have a positive impact on the merchant?s perceived trustworthiness. One of Tina?s
comments regarding her favorite site for purchasing phone cards was that the site had good
prices and gave returning customers discounts. Chuck stated he trusted Amazon and raved
about all the deals and promotions they offer. Price was a major factor for almost all the
participants in the observational study.
Having accurate and substantial product information is an indicator of competence
of an online merchant. This observational study has shown that even if the consumer is
already familiar with the product he or she still wants to see the product information to
verify the product is indeed the product in question. Detailed product information shows
the merchant is familiar with the product. Bob did not trust B & H Photo due to their lack
of product information for a JVC microphone, and as such, Bob refused to make a purchase
there.
As one would expect, a positive reputation has a positive effect on a merchant?s per-
ceived trustworthiness. Marsha?s main reason for trusting the online store she purchased was
because of it?s reputation, ?...they are a big national chain, everybody?s heard of them...they
have too much exposure to be doing something underhanded?. However, lack of a repu-
tation was not detrimental as in preventing an online merchant from being perceived as
44
trustworthy. Jan purchased a dog-tracking collar at a store she had never heard of, but the
store carried the product she was looking for and was in her price-range.
Predictability, reliability, and dependability are all related and can be correlated to
online shopping as matching the expectations of the consumer with the actions of the
online merchant. This can mean product follow-through as well as clicking a button and
having the website display what is expected. This can be related to usability of a website.
Credibility can be correlated to the professional look of a website, i.e., the design of
the site. Jack stated stores that looked ?professional? and ?like they sell stuff all the time?
were perceived as trustworthy.
Honesty can be projected from the site by having high visibility of contact information
including a physical address and phone number. Accurate product information and unbiased
customer reviews can also be an indicator of an honest merchant.
Many consumers will and have the need to purchase an item or service. As seen in
the observation, at times this need was so heavy that not much else mattered. All of the
participants stated that there were online stores they trusted but never needed to make a
purchase at. While it is possible to have trust in an individual and never need to the act
on that trust, the converse can be said as well. It is possible that a need is so great that
cooperation, in this case, an online transaction, can take place even if the consumer does not
trust the online merchant. During Greg?s search for an Audiovox cell phone cable, he was
frustrated not being able to find an online store that gave him enough product information.
When asked if he trusted the online store he finally made a purchase from (still not sure if
the product was exactly what he was looking for) Greg replied, ?I trust it enough.? Greg
needed the cable and took a chance.
45
The cooperation element of the general trust model is correlated to the actual transac-
tion taking place online. Once the transaction is complete, a level of confidence is created.
As seen in the observational study, if a first time transaction goes well, this will be a lasting
first impression on the consumer. If the transaction goes well, then the consumer will likely
have an increased amount of confidence in the merchant and vice versa.
The following table summarizes the elements of the trust model applied to e-commerce.
46
Table 6.1: Elements of E-Commerce Trust Model
47
Chapter 7
Questionnaire
The conceptual model for trustworthiness in online stores identified trustor and trustee
characteristics as factors affecting trust. A questionnaire was developed to identify the
relationships, if any, between these elements of the trustor (the online consumer), and the
trustee (the online store). Do certain elements of the conceptual model have more impact on
the trustworthiness of an online store than others? How do consumer characteristics have
an effect on what elements of a online store are important in determining trustworthiness?
Answers to these questions will aid in enhancing the conceptual model.
7.1 Methodology
The questionnaire was designed in a way to make it as short and as concise as possible.
Long questionnaires yield less accurate data. Participants are likely to rush in answering
the questions of a questionnaire several pages long in order to save time. The question-
naire in this study consisted of 3 pages containing 32 multiple-choice questions and took
approximately 3-5 minutes to fill out. The questionnaire contained demographic questions,
questions pertaining to the participant?s disposition towards trust, and questions regarding
online use and shopping experiences. Question 5, which asked participants if most people
could be trusted was obtained from the questionnaire created by the Consumer Reports
Web Watch group in October of 2005 [14]. The questionnaire also contained questions that
gave the choice between two trustworthiness elements in the conceptual model and had the
participant select which was more important.
48
7.2 Participants
Before the questionnaire was conducted, consent was obtained from Auburn Univer-
sity?s Institutional Review Board, Human Subjects Office. Participants were assured that
all information obtained from them in connection to the study would remain anonymous.
All participants were 19 years of age or older. A total of 229 questionnaires were obtained
with 2 incomplete questionnaires thrown out.
7.3 Data Collection
Participants included both students and employees of Auburn University, as well as
persons not directly affiliated with the university. Participants were wanted with varying
backgrounds, differing in age, education, and computer experience. Participants were ob-
tained by using convenience and snowball sampling. When on Auburn University?s campus,
the questionnaire was conducted during daylight hours. Individuals were approached asking
if they would like to participate in the study by filling out a short questionnaire. If they
agreed, participants were given a information letter describing the purpose of the study.
Participants were not compensated for their participation in the study. Participants filled
out the questionnaire on paper, rather than online. This was done to eliminate a possible
bias towards a participant?s computer use.
7.4 Data Analysis
The following displays the questionnaire in its entirety along with the raw data given
by the participants. For questions not totaling to 227, not all of participants answered those
questions.
49
50
51
Because the data obtained in the questionnaire was categorical, rather than numerical,
the chi-square statistic was used in data analysis. The chi-square statistic is a probability
distribution used to test the independence of two nominal variables. The chi square statistic
compares the counts of categorical responses between two or more independent groups
and with the use of contingency tables and the chi-square goodness-of-fit test it can be
determined if results are statistically significant.
52
This questionnaire was used to investigate the relationship between consumer charac-
teristics and preferences of one element of shopping online in determining a store?s trustwor-
thiness over another. Contingency tables were generated for each question 1-11 (consumer
characteristics) with questions 12 and 13 (element preference).
For example, question 5 asked participants if they felt, generally speaking, people
could be trusted. One hundred six participants felt most people can be trusted, while 121
participants felt you can?t be too careful. Question 12L asked participants which was more
important when determining the trustworthiness of an online store, the price of products for
sale or the professional look of the store. A contingency table was created to help determine
if there is any association between being a trusting person and a preference between price
and professional look. The following shows the 2 x 2 contingency table for question 5 with
question 12L.
Q5 - Q12L Price Professional Look Totals
Trust 70 35 105
No Trust 96 22 118
Totals 166 57 223
Table 7.1: Q5 - Q12L Contingency Table
Of the 223 people in the study who answered both questions 5 and 12L, 166 participants,
or 74.44%, prefer price over professional look and 57, or 25.56%, prefer professional look over
price. The null hypothesis is that the categories or trust and of price versus professional look
are independent from one another. If the null hypothesis is rejected, there is a relationship
between the two categories. For questions 5 and 12L, if the null hypothesis were true,
53
74.44% of the 105 trusting people, or 78.16 people, should prefer price over professional
look. Similarly, 25.56% of 105, or 26.84 people, should prefer professional look over price.
The same proportions should hold true for non-trusting participants. Thus, 74.44%
of the 118 non-trusting participants, or 87.84 people, should prefer price over professional
look and 25.56% of 118, or 30.16, should prefer professional look over price. These are the
expected counts if the null hypothesis were true.
The chi-square test was used to determine whether the differences between the observed
counts and the expected counts are statistically significant; in other words, not due to
chance. The chi-square statistic is:
?2 =summationtext(Observed?Expected)2Expected
For the data obtained for questions 5 and 12L,
?2 = (70?78.16)278.16 + (35?26.84)226.84 + (96?87.84)287.84 + (22?30.16)230.16 = 6.301
The number of degrees of freedom is computed by the number of columns in the con-
tingency table minus one times the number of rows in the contingency table minus one. For
questions 5 and 12L, this gives (2-1) x (2-1) = 1.
Using the chi-square distribution table with 1 df, the ?2 value of 6.301 lies between
5.41 and 6.63. The corresponding probability falls between 0.01 and 0.02. This is above
the significance level of 0.05 or 5%, so the null hypothesis is rejected. The following table
displays the values calculated by Minitab.
54
Table Statistics - Trust and Q12l
Observed Counts Price Prof. Look
Trust 70 35
No Trust 96 22
Expected Counts Price Prof. Look
Trust 78.16 26.84
No Trust 87.84 30.16
Test Statistics Value df p-value
Pearson Chi-Square 6.301 1 0.012
Likelihood Ratio Chi-Square 6.322 1 0.012
Null Hypothesis (Ho) : No Trust difference for Q12l.
The p-value is less than 0.05. Therefore REJECT the Ho.
The exact p value is 0.012 which is less than 0.05. Therefore, there is strong evidence
that the distribution of preference of price over professional look among trusting people is
different from that among non-trusting people.
For questions 12 and 13, which asked the participant to select a preference of one
element of online shopping over another, the chi-squre goodness-of-fit test was used. The
goodness-of-fit test states whether the results for each question were statistically significant.
For example, question 12G asked participants which was more important when deter-
mining the trustworthiness of an online store, the price of products for sale, or the visibility
of contact information, such as phone, email, physical address. One hundred two of the
55
227 participants, or 44.93%, selected price and 125 of the 227, or 55.07%, selected contact
information. If the probability of selecting one element over another followed the binomial
distribution, the probability would be 0.5. The expected number for both price and contact
information would be half of 227 or 113.5 participants.
Once again the chi-square statistic is
?2 =summationtext(Observed?Expected)2Expected
For question 12G, this gives a chi-square value of 2.33. Looking at the chi-square
distribution table, for 1 df, 2.33 lies between 0.10 and 0.15 which is less than the chi-square
of 3.84 for 0.5. Therefore, the null hypothesis cannot be rejected. There is no statistical
difference between the preference of contact information over price. The following table
summarizes the goodness-of-fit test for question 12G.
56
Price Contact Info Total
Observed (O) 102 125 227
Expected (E) 113.5 113.5 227
(O - E) -11.5 11.5
(O - E)2 132.250 132.250
(O - E)2 / E 1.165 1.165
Chi Squared Calculated 2.33
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Price and Contact Info
Contingency tables and chi-square statistics for all questions can be found in the Ap-
pendix.
7.5 Findings
7.5.1 Consumer Characteristics
The gender of participants was almost split with 107 (47%) of the participants being
male and 120 (53%) female. The majority of participants were under the age of 50 (93
participants or 41% were between the ages of 19 and 29; 89 participants or 39% were
between the ages of 30 and 49).
57
All participants had at least graduated from high school with the majority, 196 (86%)
having at least some college education. Participants had varying income levels. One hundred
nine participants, 48%, made $50,000 or less per year. The income question was the question
most omitted. Fifty-one participants (22%) did not feel comfortable stating their income.
About half of the participants had a propensity towards trust. One hundred six (47%)
of the participants stated most people can be trusted and 121 (53%) stated you can?t be
too careful. Over half of the participants (120 or 53%) access the internet several times a
day, with 20 (9%) accessing the internet once a day, 47 (21%) several times a week and 40
(17%) accessing the internet less. The majority of participants, 137 (or 60%), have been
accessing the internet for over 5 years.
One hundred thirty-one participants (58%) browse online stores at least once a week or
more. The majority of participants, 141 (62%), make a purchase at an online store about
once a month. For 130 participants (57%), the most expensive single item purchased online
was $100 or less. One hundred thirty participants (57%) felt their overall online shopping
experience had been a positive one.
7.5.2 Consumer Characteristics and Online Shopping Experience
The following table shows the percentage of participants who have made a purchase
online, made a purchase of $100 or more online, and have had a positive online shopping
experience with varying categories of the participants? age, income, online experience, and
propensity towards trust.
58
For participants aging 30 to 49, almost all (90%) had made at least one purchase online.
The older a participant, the more likely to make a purchase over $100 and have a positive
online shopping experience.
Participants with a higher yearly income were more likely to make a purchase online,
more likely to spend at least $100, and more likely to have a positive online shopping
experience. The same holds true for the more online experience a participant had.
The more trusting the participant, the more likely was the participant to make a
purchase and have a positive experience online shopping experience. Interesting to note that
more non-trusting participants made more expensive purchases than trusting participants.
59
7.5.3 Consumer Characteristics and Elements of Online Shopping
Data analysis identified relationships between consumer characteristics, questions 2 -
11, and the preference of one trustworthiness element of an online store over another, ques-
tions 12e, 12f, and 12h through 12n; as well as the preference of need or an online element,
questions 13a through 13f. These identified relationships are displayed below.
60
There was no statistical difference in the answers to questions 12 and 13 (preference
of elements of online shopping) in relationship to gender (question 1). Also, the ?No Con-
sumer Char. Relationship? table above identifies questions 12 and 13 that did not have a
relationship with any of the questions 2-11 (consumer characteristics).
Age
The results showed that there was a relationship between age (if 60 and older was
excluded) and the choice of professional look versus visibility of contact information (12n).
In all age groups, more participants preferred contact information over professional look.
However, for participants in the 30-49 age group, more than expected (if there was no rela-
tionship between age and question 12n) preferred professional look over contact information.
Education
Question 3, which asked participants their level of education, was found to be related
to the way 7 questions were answered, questions 12f, 12h, 12k, and 13b through 13e. For
question 12f, those with some college education were unlike the rest of the participants with
either less or more education. More participants with some college education than expected
preferred contact information over reputation.
In all education categories, more participants preferred reputation over professional look
(question 12h). However, only in the some college education category did more participants
than expected prefer professional look over reputation.
Overall, in question 12k, participants with at least some college education preferred
ease of use over professional look. But those who did not have a college degree preferred
professional look more than expected.
61
All education categories preferred need over ease of use (question 13b). Those with
some college education and those with a college degree preferred ease of use more than
expected. While high school graduates and post graduates answered very similarly in their
majority preference of need.
For question 13c, all education groups preferred reputation over need. Those without
a college degree preferred need over reputation more than expected. For question 13d,
all groups preferred need over professional look. Those without a college degree preferred
professional look more than expected.
Those participants without a college degree preferred contact information over need
(question 13e) more than expected. While those participants with a degree preferred need
more than expected.
Income
Income only showed a relationship in the way question 13e was answered by the par-
ticipants. All income groups, except the $75,000 or less and over $100,000 preferred contact
information over need.
Trust
For both trusting and non-trusting participants, the majority selected price of products
over the professional look of an online store (question 12l). However, more than expected
trusting participants preferred professional look, while more than expected non-trusting
participants preferred price.
Both trusting and non-trusting participants preferred contact information over profes-
sional look (question 12n). However, more trusting participants than expected preferred
62
professional look and more non-trusting participants than expected preferred contact infor-
mation.
Both trusting and non-trusting participants preferred reputation over need (question
13c). But, more trusting participants than expected preferred need while more non-trusting
participants than expected preferred reputation.
Frequency Online
Data analysis identified relationships between how often a participant gets online to how
questions 12m and 13b through 13e were answered. For question 12m, those participants
who accessed the internet several times a week or more preferred product information over
ease of use.
For those participants who accessed the internet at least once a day, more than expected
preferred need over ease of use (question 13b), reputation (question 13c), and professional
look (question 13d).
Only those participants who accessed the web several times a day preferred need over
contact info more than expected (question 13e).
Online History
When looking at how long participants have been using the internet, there was a clear
division between participants who had been online for 5 years or less and those online for
over 5 years. For those participants who have been accessing the internet for over 5 years,
more than expected preferred reputation over contact info (question 12f).
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For questions 13c through 13f, those participants who have been accessing the internet
for over 5 years, selected need more than expected over reputation, professional look, contact
information and product information.
Browsing Online
Question 12i asked participants which element of online shopping was more important
in determining the trustworthiness of an online store: price of products or reputation of the
online store. For participants who browsed online several times a week or more, more than
expected preferred price over reputation.
Buying Online
For those who bought products online about once a week, more than expected preferred
professional look over ease of use (question 12k). For those who bought about once a month,
more than expected preferred ease of use.
Most Expensive Online Purchase
Those participants whose most expensive item was over $100, more than expected
preferred ease of use over contact information (question 12j). Also, those same participants
whose most expensive item was over $100, more than expected preferred need over contact
information (question 13e).
Online Experience
For those participants who had a positive online shopping experience, more than ex-
pected preferred professional look over product information (question 12e) and more than
64
expected preferred need over price (question 13a). While those who did not, more than
expected preferred both product information over professional look and price over need.
For all participants, more preferred ease of use over professional look. For those who
stated somewhat, more than expected preferred professional look over ease of use. For the
rest of the participants, more than expected preferred ease of use (question 12k). Also,
those participants who answered somewhat, more than expected preferred ease of use over
product information. While the rest of the participants, more than expected preferred
product information (question 12m).
7.5.4 Relative Importance of Elements of Online Shopping
From the chi-square goodness-of-fit tests done on questions 12a-12o, the null hypothesis
that there was no difference between the two choices was rejected for all questions except
12d, 12g, and 12j. There was no statistical difference between ease of use and price (12d),
between price and contact information (12g), and between contact information and ease of
use (12j).
Also, from the chi-square goodness-of-fit tests done on questions 13a-13f, the null hy-
pothesis that there was no difference between the two choices was rejected for all questions
except 13a, 13e, and 13f. There was no statistical difference between need and price (13a),
between contact information and need (13e), and between product information and need
(13f).
Question 13 was created based on the observational study, where it was seen if a
participant needed an item online, not much else mattered. It was expected that the
majority of questionnaire participants would select need over the other elements of online
65
shopping. Even though this was not the case for all parts of question 13, results from data
analysis already presented have shown consumer characteristics affect how question 13 was
answered. It may be that the participants? characteristics in the observational study were
those where need was more important.
The professional look of an online store was the least important element of determining
the trustworthiness of an online store when compared to all the other elements. Ease of use
was more important than professional look and not as important as product information
and store reputation. This is consistent with what was seen in the observational study.
Detailed product information was more important than the professional look and ease
of use of an online store. Detailed product information was less important in determining
the trustworthiness of an online store than price, contact information, and reputation.
Reputation was the most important element in determining the trustworthiness of an online
store followed by contact information. There was no statistical difference between price and
ease of use, price and contact information, and contact information and ease of use.
Need of a product was more important than ease of use and professional look of an
online store, but not as important as the reputation of an online store. There was no
statistical difference between need and price, need and contact information, and need and
product information.
The questionnaire has shown that consumer characteristics play a large part in what
elements of an online store are important in determining its trustworthiness. Some of the
results of the questionnaire were in conflict with what was observed in the observational
study. This is likely due to the observational study?s participants? characteristics.
66
The results of the questionnaire have also helped order the general importance of online
shopping elements of trustworthiness. This ordering will enhance the conceptual model.
67
Chapter 8
Conceptual Model of Trustworthiness Online Revisited
The conceptual model of trustworthiness online was developed from the current lit-
erature and then enhanced by the observational study. The conceptual model identified
the situation needed for trustworthiness to be of issue when shopping online, the factors
that affect the trustworthiness of an online store, and indicators or outcomes of consumers
perceiving an online store to be trustworthy.
Figure 8.1: Conceptual Model of Trustworthiness Online
The questionnaire conducted validated the conceptual model. It focused on the trustor
and trustee characteristics of the model, their relationships with each other, and the relative
importance of trustee characteristics.
68
The questionnaire proved that trustor characteristics affect the perceived trustworthi-
ness of an online store. Based on what type of consumer an online store is targeting, different
elements of the online store will be more important in instilling a sense of trustworthiness.
Age, education, income, and online experience were trustor (consumer) characteristics that
affect an online store?s perceived trustworthiness.
Past online experience can be broken down into how often a consumer is online, how
long the consumer has been using the internet, how often the consumer browses online, how
often the consumer makes a purchase online, the most expensive item a consumer has pur-
chased online, and overall past online experience. This emphasizes to online merchants how
important it is to know their customers. Age, education, and income may be the easiest to
gage of consumers purchasing a particular type of product, while the other elements may be
difficult to learn. One way is to have customers fill out a demographic survey. Knowing what
type of consumer the online merchant wants to target can help the merchant in tailoring
his online store. Even if a merchant does not have a specific target audience of consumers,
just knowing that these characteristics have a relationship to perceived trustworthiness of
an online store is important.
The questionnaire identified the relative importance of different trustee or online mer-
chant characteristics. The most important element of trustworthiness is the reputation of
an online store. The second most important element was visibility of contact information
on the online store?s website. Honesty of an online merchant can be shown through the
ability to contact and converse with the merchant, be it via email, phone, or at a physical
location.
69
The least important element was the professional look of the online store. While this is
not to say that a professional look is not important, having the most aesthetically pleasing
website is the least effective way to exude trustworthiness to consumers. Ease of use was
the second least important element. Consumers definitely need to be able to navigate an
online store, search and find products, and be able to checkout. As long as the website is
functional, anything else extra usability-wise is just that, extra.
Price and product info are also very important and fell somewhere between contact in-
formation and usability. Although, the observational study found that product information
was more important than price.
The questionnaire also looked at the need element of the conceptual model. The
questionnaire identified an additional relationship between trustor characteristics and the
need of a product. Based on consumer characteristics, it is possible that the need of an
item is so great that none of the trustee characteristics are as important.
The following table summarizes the elements of the conceptual model for trustworthi-
ness in online stores.
70
Figure 8.2: Elements of Trustworthiness Online
71
Chapter 9
Conclusions and Future Work
This research defined a conceptual model for trustworthiness in online stores. This
conceptual model was developed from the current literature and validated by both an ob-
servational study and a questionnaire. The combination of both qualitative and quantitative
data provided insight into the online shopping experience, identifying relationships between
consumers and elements of online shopping.
With the use of the observational study, for the first time, real consumers were observed
making real purchases online. This new methodology can be used in future research of e-
commerce.
A large amount of data was obtained during both the observational and questionnaire
study. Future work can include taking a deeper look at interface elements of each online store
visited during the observational study. Also, a ?where are they now? look can take the design
of the online stores visited during the observational study and comparing and contrasting it
to the current design of stores today. The study could be run looking at the online shopping
experience in general and results could be used to make online shopping more enjoyable and
make online shopping easier for consumers. In retrospect, when conducted again, the study
should keep in contact with the observational study participants and interview them after
their item arrives, giving a full and complete view of the purchase experience from start
to finish. Finally, using the conceptual model presented here, guidelines can be created for
merchants in creating online stores perceived trustworthy by consumers.
72
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Appendix A
Table Statistics
A.1 Gender
Gender and Q12a
Observed Counts Reputation Product Info
Male 68 39
Female 83 37
Expected Counts Reputation Product Info
Male 71.18 35.82
Female 79.82 40.18
Test Statistics Value df p-value
Pearson Chi-Square 0.801 1 0.371
Likelihood Ratio Chi-Square 0.800 1 0.371
Null Hypothesis (Ho) : No Gender difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
80
Gender and Q12b
Observed Counts Product Info Contact Info
Male 39 68
Female 52 68
Expected Counts Product Info Contact Info
Male 42.89 64.11
Female 48.11 71.89
Test Statistics Value df p-value
Pearson Chi-Square 1.116 1 0.291
Likelihood Ratio Chi-Square 1.119 1 0.290
Null Hypothesis (Ho) : No Gender difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
81
Gender and Q12c
Observed Counts Price Product Info
Male 61 44
Female 75 45
Expected Counts Price Product Info
Male 63.47 41.53
Female 72.53 47.47
Test Statistics Value df p-value
Pearson Chi-Square 0.454 1 0.500
Likelihood Ratio Chi-Square 0.454 1 0.500
Null Hypothesis (Ho) : No Gender difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
82
Gender and Q12d
Observed Counts Ease of Use Price
Male 54 53
Female 62 58
Expected Counts Ease of Use Price
Male 54.68 52.32
Female 61.32 58.68
Test Statistics Value df p-value
Pearson Chi-Square 0.033 1 0.857
Likelihood Ratio Chi-Square 0.033 1 0.857
Null Hypothesis (Ho) : No Gender difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
83
Gender and Q12e
Observed Counts Prof. Look Product Info
Male 44 62
Female 41 79
Expected Counts Prof. Look Product Info
Male 39.87 66.13
Female 45.13 74.87
Test Statistics Value df p-value
Pearson Chi-Square 1.293 1 0.255
Likelihood Ratio Chi-Square 1.293 1 0.256
Null Hypothesis (Ho) : No Gender difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
84
Gender and Q12f
Observed Counts Contact Info Reputation
Male 39 68
Female 49 70
Expected Counts Contact Info Reputation
Male 41.66 65.34
Female 46.34 72.66
Test Statistics Value df p-value
Pearson Chi-Square 0.530 1 0.467
Likelihood Ratio Chi-Square 0.530 1 0.466
Null Hypothesis (Ho) : No Gender difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
85
Gender and Q12g
Observed Counts Price Contact Info
Male 45 62
Female 57 63
Expected Counts Price Contact Info
Male 48.08 58.92
Female 53.92 66.08
Test Statistics Value df p-value
Pearson Chi-Square 0.677 1 0.410
Likelihood Ratio Chi-Square 0.678 1 0.410
Null Hypothesis (Ho) : No Gender difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
86
Gender and Q12h
Observed Counts Prof. Look Reputation
Male 24 83
Female 24 96
Expected Counts Prof. Look Reputation
Male 22.63 84.37
Female 25.37 94.63
Test Statistics Value df p-value
Pearson Chi-Square 0.200 1 0.654
Likelihood Ratio Chi-Square 0.200 1 0.655
Null Hypothesis (Ho) : No Gender difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
87
Gender and Q12i
Observed Counts Reputation Price
Male 62 45
Female 68 52
Expected Counts Reputation Price
Male 61.28 45.72
Female 68.72 51.28
Test Statistics Value df p-value
Pearson Chi-Square 0.038 1 0.846
Likelihood Ratio Chi-Square 0.038 1 0.846
Null Hypothesis (Ho) : No Gender difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
88
Gender and Q12j
Observed Counts Contact Info Ease of Use
Male 58 49
Female 62 58
Expected Counts Contact Info Ease of Use
Male 56.56 50.44
Female 63.44 56.56
Test Statistics Value df p-value
Pearson Chi-Square 0.146 1 0.702
Likelihood Ratio Chi-Square 0.146 1 0.702
Null Hypothesis (Ho) : No Gender difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
89
Gender and Q12k
Observed Counts Ease of Use Prof. Look
Male 69 38
Female 82 38
Expected Counts Ease of Use Prof. Look
Male 71.18 35.82
Female 79.82 40.18
Test Statistics Value df p-value
Pearson Chi-Square 0.376 1 0.540
Likelihood Ratio Chi-Square 0.376 1 0.540
Null Hypothesis (Ho) : No Gender difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
90
Gender and Q12l
Observed Counts Price Prof. Look
Male 76 30
Female 91 27
Expected Counts Price Prof. Look
Male 79.03 26.97
Female 87.97 30.03
Test Statistics Value df p-value
Pearson Chi-Square 0.865 1 0.352
Likelihood Ratio Chi-Square 0.864 1 0.353
Null Hypothesis (Ho) : No Gender difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
91
Gender and Q12m
Observed Counts Product Info Ease of Use
Male 68 39
Female 72 48
Expected Counts Product Info Ease of Use
Male 65.99 41.01
Female 74.01 45.99
Test Statistics Value df p-value
Pearson Chi-Square 0.302 1 0.583
Likelihood Ratio Chi-Square 0.302 1 0.583
Null Hypothesis (Ho) : No Gender difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
92
Gender and Q12n
Observed Counts Prof. Look Contact Info
Male 40 67
Female 35 85
Expected Counts Prof. Look Contact Info
Male 35.35 71.65
Female 39.65 80.35
Test Statistics Value df p-value
Pearson Chi-Square 1.726 1 0.189
Likelihood Ratio Chi-Square 1.725 1 0.189
Null Hypothesis (Ho) : No Gender difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
93
Gender and Q12o
Observed Counts Ease of Use Reputation
Male 29 78
Female 38 82
Expected Counts Ease of Use Reputation
Male 31.58 75.42
Female 35.42 84.58
Test Statistics Value df p-value
Pearson Chi-Square 0.566 1 0.452
Likelihood Ratio Chi-Square 0.568 1 0.452
Null Hypothesis (Ho) : No Gender difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
94
Gender and Q13a
Observed Counts Need Price
Male 47 60
Female 57 63
Expected Counts Need Price
Male 49.02 57.98
Female 54.98 65.02
Test Statistics Value df p-value
Pearson Chi-Square 0.291 1 0.589
Likelihood Ratio Chi-Square 0.291 1 0.589
Null Hypothesis (Ho) : No Gender difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
95
Gender and Q13b
Observed Counts Ease of Use Need
Male 42 65
Female 49 70
Expected Counts Ease of Use Need
Male 43.08 63.92
Female 47.92 71.08
Test Statistics Value df p-value
Pearson Chi-Square 0.087 1 0.768
Likelihood Ratio Chi-Square 0.087 1 0.768
Null Hypothesis (Ho) : No Gender difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
96
Gender and Q13c
Observed Counts Need Reputation
Male 40 67
Female 46 74
Expected Counts Need Reputation
Male 40.54 66.46
Female 45.46 74.54
Test Statistics Value df p-value
Pearson Chi-Square 0.022 1 0.883
Likelihood Ratio Chi-Square 0.022 1 0.883
Null Hypothesis (Ho) : No Gender difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
97
Gender and Q13d
Observed Counts Prof. Look Need
Male 38 69
Female 39 81
Expected Counts Prof. Look Need
Male 36.30 70.70
Female 40.70 79.30
Test Statistics Value df p-value
Pearson Chi-Square 0.229 1 0.632
Likelihood Ratio Chi-Square 0.229 1 0.632
Null Hypothesis (Ho) : No Gender difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
98
Gender and Q13e
Observed Counts Contact Info Need
Male 59 48
Female 65 55
Expected Counts Contact Info Need
Male 58.45 48.55
Female 65.55 54.45
Test Statistics Value df p-value
Pearson Chi-Square 0.022 1 0.883
Likelihood Ratio Chi-Square 0.022 1 0.883
Null Hypothesis (Ho) : No Gender difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
99
Gender and Q13f
Observed Counts Product Info Need
Male 65 42
Female 59 61
Expected Counts Product Info Need
Male 58.45 48.55
Female 65.55 54.45
Test Statistics Value df p-value
Pearson Chi-Square 3.061 1 0.080
Likelihood Ratio Chi-Square 3.071 1 0.080
Null Hypothesis (Ho) : No Gender difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
100
A.2 Age
Age and Q12a
Observed Counts Reputation Product Info
19-29 56 37
30-49 60 29
50-59 30 8
Expected Counts Reputation Product Info
19-29 61.72 31.28
30-49 59.06 29.94
50-59 25.22 12.78
Test Statistics Value df p-value
Pearson Chi-Square 4.315 2 0.116
Likelihood Ratio Chi-Square 4.499 2 0.105
Null Hypothesis (Ho) : No Age difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
101
Age and Q12b
Observed Counts Product Info Contact Info
19-29 37 56
30-49 37 52
50-59 13 25
Expected Counts Product Info Contact Info
19-29 36.78 56.22
30-49 35.20 53.80
50-59 15.03 22.97
Test Statistics Value df p-value
Pearson Chi-Square 0.608 2 0.738
Likelihood Ratio Chi-Square 0.615 2 0.735
Null Hypothesis (Ho) : No Age difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
102
Age and Q12c
Observed Counts Price Product Info
19-29 57 35
30-49 51 38
50-59 24 13
Expected Counts Price Product Info
19-29 55.71 36.29
30-49 53.89 35.11
50-59 22.40 14.60
Test Statistics Value df p-value
Pearson Chi-Square 0.757 2 0.685
Likelihood Ratio Chi-Square 0.758 2 0.684
Null Hypothesis (Ho) : No Age difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
103
Age and Q12d
Observed Counts Ease of Use Price
19-29 45 48
30-49 50 39
50-59 17 21
Expected Counts Ease of Use Price
19-29 47.35 45.65
30-49 45.31 43.69
50-59 19.35 18.65
Test Statistics Value df p-value
Pearson Chi-Square 1.805 2 0.406
Likelihood Ratio Chi-Square 1.809 2 0.405
Null Hypothesis (Ho) : No Age difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
104
Age and Q12e
Observed Counts Prof. Look Product Info
19-29 37 56
30-49 35 53
50-59 11 27
Expected Counts Prof. Look Product Info
19-29 35.25 57.75
30-49 33.35 54.65
50-59 14.40 23.60
Test Statistics Value df p-value
Pearson Chi-Square 1.566 2 0.457
Likelihood Ratio Chi-Square 1.614 2 0.446
Null Hypothesis (Ho) : No Age difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
105
Age and Q12f
Observed Counts Contact Info Reputation
19-29 35 57
30-49 36 53
50-59 14 24
Expected Counts Contact Info Reputation
19-29 35.71 56.29
30-49 34.54 54.46
50-59 14.75 23.25
Test Statistics Value df p-value
Pearson Chi-Square 0.185 2 0.911
Likelihood Ratio Chi-Square 0.185 2 0.911
Null Hypothesis (Ho) : No Age difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
106
Age and Q12g
Observed Counts Price Contact Info
19-29 36 57
30-49 43 46
50-59 19 19
Expected Counts Price Contact Info
19-29 41.43 51.57
30-49 39.65 49.35
50-59 16.93 21.07
Test Statistics Value df p-value
Pearson Chi-Square 2.252 2 0.324
Likelihood Ratio Chi-Square 2.261 2 0.323
Null Hypothesis (Ho) : No Age difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
107
Age and Q12h
Observed Counts Prof. Look Reputation
19-29 22 71
30-49 18 71
50-59 7 31
Expected Counts Prof. Look Reputation
19-29 19.87 73.13
30-49 19.01 69.99
50-59 8.12 29.88
Test Statistics Value df p-value
Pearson Chi-Square 0.555 2 0.758
Likelihood Ratio Chi-Square 0.556 2 0.757
Null Hypothesis (Ho) : No Age difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
108
Age and Q12i
Observed Counts Reputation Price
19-29 51 42
30-49 55 34
50-59 19 19
Expected Counts Reputation Price
19-29 52.84 40.16
30-49 50.57 38.43
50-59 21.59 16.41
Test Statistics Value df p-value
Pearson Chi-Square 1.768 2 0.413
Likelihood Ratio Chi-Square 1.771 2 0.413
Null Hypothesis (Ho) : No Age difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
109
Age and Q12j
Observed Counts Contact Info Price
19-29 57 36
30-49 43 46
50-59 17 21
Expected Counts Contact Info Price
19-29 49.46 43.54
30-49 47.33 41.67
50-59 20.21 17.79
Test Statistics Value df p-value
Pearson Chi-Square 4.391 2 0.111
Likelihood Ratio Chi-Square 4.415 2 0.110
Null Hypothesis (Ho) : No Age difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
110
Age and Q12k
Observed Counts Ease of Use Prof. Look
19-29 54 39
30-49 63 26
50-59 28 10
Expected Counts Ease of Use Prof. Look
19-29 61.30 31.70
30-49 58.66 30.34
50-59 25.05 12.95
Test Statistics Value df p-value
Pearson Chi-Square 4.512 2 0.105
Likelihood Ratio Chi-Square 4.502 2 0.105
Null Hypothesis (Ho) : No Age difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
111
Age and Q12l
Observed Counts Price Prof. Look
19-29 69 22
30-49 62 26
50-59 31 7
Expected Counts Price Prof. Look
19-29 67.94 23.06
30-49 65.70 22.30
50-59 28.37 9.63
Test Statistics Value df p-value
Pearson Chi-Square 1.849 2 0.397
Likelihood Ratio Chi-Square 1.892 2 0.388
Null Hypothesis (Ho) : No Age difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
112
Age and Q12m
Observed Counts Product Info Ease of Use
19-29 58 35
30-49 58 31
50-59 20 18
Expected Counts Product Info Ease of Use
19-29 57.49 35.51
30-49 55.02 33.98
50-59 23.49 14.51
Test Statistics Value df p-value
Pearson Chi-Square 1.794 2 0.408
Likelihood Ratio Chi-Square 1.766 2 0.413
Null Hypothesis (Ho) : No Age difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
113
Age and Q12n
Observed Counts Prof. Look Contact Info
19-29 28 65
30-49 36 53
50-59 7 31
Expected Counts Prof. Look Contact Info
19-29 30.01 62.99
30-49 28.72 60.28
50-59 12.26 25.74
Test Statistics Value df p-value
Pearson Chi-Square 6.258 2 0.044
Likelihood Ratio Chi-Square 6.510 2 0.039
Null Hypothesis (Ho) : No Age difference for Q12n.
The p-value is less than 0.05. Therefore REJECT the Ho.
114
Age and Q12o
Observed Counts Ease of Use Reputation
19-29 27 66
30-49 28 61
50-59 11 27
Expected Counts Ease of Use Reputation
19-29 27.90 65.10
30-49 26.70 62.30
50-59 11.40 26.60
Test Statistics Value df p-value
Pearson Chi-Square 0.152 2 0.927
Likelihood Ratio Chi-Square 0.152 2 0.927
Null Hypothesis (Ho) : No Age difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
115
Age and Q13a
Observed Counts Need Price
19-29 43 50
30-49 40 49
50-59 19 19
Expected Counts Need Price
19-29 43.12 49.88
30-49 41.26 47.74
50-59 17.62 20.38
Test Statistics Value df p-value
Pearson Chi-Square 0.275 2 0.872
Likelihood Ratio Chi-Square 0.274 2 0.872
Null Hypothesis (Ho) : No Age difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
116
Age and Q13b
Observed Counts Ease of Use Need
19-29 31 61
30-49 44 45
50-59 13 25
Expected Counts Ease of Use Need
19-29 36.97 55.03
30-49 35.76 53.24
50-59 15.27 22.73
Test Statistics Value df p-value
Pearson Chi-Square 5.347 2 0.069
Likelihood Ratio Chi-Square 5.332 2 0.070
Null Hypothesis (Ho) : No Age difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
117
Age and Q13c
Observed Counts Need Reputation
19-29 34 59
30-49 35 54
50-59 16 22
Expected Counts Need Reputation
19-29 35.93 57.07
30-49 34.39 54.61
50-59 14.68 23.32
Test Statistics Value df p-value
Pearson Chi-Square 0.380 2 0.827
Likelihood Ratio Chi-Square 0.379 2 0.827
Null Hypothesis (Ho) : No Age difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
118
Age and Q13d
Observed Counts Prof. Look Need
19-29 33 60
30-49 30 59
50-59 9 29
Expected Counts Prof. Look Need
19-29 30.44 62.56
30-49 29.13 59.87
50-59 12.44 25.56
Test Statistics Value df p-value
Pearson Chi-Square 1.771 2 0.412
Likelihood Ratio Chi-Square 1.849 2 0.397
Null Hypothesis (Ho) : No Age difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
119
Age and Q13e
Observed Counts Contact Info Need
19-29 53 40
30-49 46 43
50-59 20 18
Expected Counts Contact Info Need
19-29 50.30 42.70
30-49 48.14 40.86
50-59 20.55 17.45
Test Statistics Value df p-value
Pearson Chi-Square 0.555 2 0.758
Likelihood Ratio Chi-Square 0.555 2 0.758
Null Hypothesis (Ho) : No Age difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
120
Age and Q13f
Observed Counts Product Info Need
19-29 55 38
30-49 46 43
50-59 17 21
Expected Counts Product Info Need
19-29 49.88 43.12
30-49 47.74 41.26
50-59 20.38 17.62
Test Statistics Value df p-value
Pearson Chi-Square 2.479 2 0.290
Likelihood Ratio Chi-Square 2.483 2 0.289
Null Hypothesis (Ho) : No Age difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
121
A.3 Education
Education and Q12a
Observed Counts Reputation Product Info
High School Graduate 18 11
Some College 44 29
Post College 65 28
Post Graduate 22 8
Expected Counts Reputation Product Info
High School Graduate 19.20 9.80
Some College 48.34 24.66
Post College 61.59 31.41
Post Graduate 19.87 10.13
Test Statistics Value df p-value
Pearson Chi-Square 2.617 3 0.455
Likelihood Ratio Chi-Square 2.622 3 0.454
Null Hypothesis (Ho) : No Education difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
122
Education and Q12b
Observed Counts Product Info Contact Info
High School Graduate 12 17
Some College 26 47
Post College 42 51
Post Graduate 10 20
Expected Counts Product Info Contact Info
High School Graduate 11.60 17.40
Some College 29.20 43.80
Post College 37.20 55.80
Post Graduate 12.00 18.00
Test Statistics Value df p-value
Pearson Chi-Square 2.195 3 0.533
Likelihood Ratio Chi-Square 2.203 3 0.531
Null Hypothesis (Ho) : No Education difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
123
Education and Q12c
Observed Counts Price Product Info
High School Graduate 16 13
Some College 42 30
Post College 59 33
Post Graduate 18 12
Expected Counts Price Product Info
High School Graduate 17.56 11.44
Some College 43.59 28.41
Post College 55.70 36.30
Post Graduate 18.16 11.84
Test Statistics Value df p-value
Pearson Chi-Square 0.997 3 0.802
Likelihood Ratio Chi-Square 0.997 3 0.802
Null Hypothesis (Ho) : No Education difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
124
Education and Q12d
Observed Counts Ease of Use Price
High School Graduate 11 18
Some College 41 32
Post College 48 45
Post Graduate 15 15
Expected Counts Ease of Use Price
High School Graduate 14.82 14.18
Some College 37.31 35.69
Post College 47.53 45.47
Post Graduate 15.33 14.67
Test Statistics Value df p-value
Pearson Chi-Square 2.786 3 0.426
Likelihood Ratio Chi-Square 2.805 3 0.423
Null Hypothesis (Ho) : No Education difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
125
Education and Q12e
Observed Counts Prof. Look Product Info
High School Graduate 7 22
Some College 32 40
Post College 33 60
Post Graduate 11 19
Expected Counts Prof. Look Product Info
High School Graduate 10.75 18.25
Some College 26.68 45.32
Post College 34.46 58.24
Post Graduate 11.12 18.88
Test Statistics Value df p-value
Pearson Chi-Square 3.861 3 0.277
Likelihood Ratio Chi-Square 3.960 3 0.266
Null Hypothesis (Ho) : No Education difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
126
Education and Q12f
Observed Counts Contact Info Reputation
High School Graduate 11 18
Some College 39 34
Post College 30 62
Post Graduate 7 23
Expected Counts Contact Info Reputation
High School Graduate 11.26 17.74
Some College 28.35 44.65
Post College 35.73 56.27
Post Graduate 11.65 18.35
Test Statistics Value df p-value
Pearson Chi-Square 11.088 3 0.011
Likelihood Ratio Chi-Square 11.153 3 0.011
Null Hypothesis (Ho) : No Education difference for Q12f.
The p-value is less than 0.05. Therefore REJECT the Ho.
127
Education and Q12g
Observed Counts Price Contact Info
High School Graduate 12 17
Some College 31 42
Post College 44 49
Post Graduate 14 16
Expected Counts Price Contact Info
High School Graduate 13.02 15.98
Some College 32.77 40.23
Post College 41.75 51.25
Post Graduate 13.47 16.53
Test Statistics Value df p-value
Pearson Chi-Square 0.577 3 0.902
Likelihood Ratio Chi-Square 0.577 3 0.902
Null Hypothesis (Ho) : No Education difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
128
Education and Q12h
Observed Counts Prof. Look Reputation
High School Graduate 6 23
Some College 23 50
Post College 17 76
Post Graduate 2 28
Expected Counts Prof. Look Reputation
High School Graduate 6.19 22.81
Some College 15.57 57.43
Post College 19.84 73.16
Post Graduate 6.40 23.60
Test Statistics Value df p-value
Pearson Chi-Square 8.871 3 0.031
Likelihood Ratio Chi-Square 9.553 3 0.023
Null Hypothesis (Ho) : No Education difference for Q12h.
The p-value is less than 0.05. Therefore REJECT the Ho.
129
Education and Q12i
Observed Counts Reputation Price
High School Graduate 16 13
Some College 40 33
Post College 52 41
Post Graduate 21 9
Expected Counts Reputation Price
High School Graduate 16.63 12.37
Some College 41.85 31.15
Post College 53.32 39.68
Post Graduate 17.20 12.80
Test Statistics Value df p-value
Pearson Chi-Square 2.292 3 0.514
Likelihood Ratio Chi-Square 2.367 3 0.500
Null Hypothesis (Ho) : No Education difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
130
Education and Q12j
Observed Counts Contact Info Price
High School Graduate 18 11
Some College 40 33
Post College 46 47
Post Graduate 15 15
Expected Counts Contact Info Price
High School Graduate 15.34 13.66
Some College 38.61 34.39
Post College 49.19 43.81
Post Graduate 15.87 14.13
Test Statistics Value df p-value
Pearson Chi-Square 1.626 3 0.654
Likelihood Ratio Chi-Square 1.638 3 0.651
Null Hypothesis (Ho) : No Education difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
131
Education and Q12k
Observed Counts Ease of Use Prof. Look
High School Graduate 14 15
Some College 44 29
Post College 68 25
Post Graduate 24 6
Expected Counts Ease of Use Prof. Look
High School Graduate 19.33 9.67
Some College 48.67 24.33
Post College 62.00 31.00
Post Graduate 20.00 10.00
Test Statistics Value df p-value
Pearson Chi-Square 9.898 3 0.019
Likelihood Ratio Chi-Square 9.877 3 0.020
Null Hypothesis (Ho) : No Education difference for Q12k.
The p-value is less than 0.05. Therefore REJECT the Ho.
132
Education and Q12l
Observed Counts Price Prof. Look
High School Graduate 20 8
Some College 53 19
Post College 70 22
Post Graduate 23 7
Expected Counts Price Prof. Look
High School Graduate 20.94 7.06
Some College 53.84 18.16
Post College 68.79 23.21
Post Graduate 22.43 7.57
Test Statistics Value df p-value
Pearson Chi-Square 0.359 3 0.949
Likelihood Ratio Chi-Square 0.356 3 0.949
Null Hypothesis (Ho) : No Education difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
133
Education and Q12m
Observed Counts Product Info Ease of Use
High School Graduate 20 9
Some College 40 33
Post College 60 33
Post Graduate 20 10
Expected Counts Product Info Ease of Use
High School Graduate 18.04 10.96
Some College 45.42 27.58
Post College 57.87 35.13
Post Graduate 18.67 11.33
Test Statistics Value df p-value
Pearson Chi-Square 2.735 3 0.434
Likelihood Ratio Chi-Square 2.720 3 0.437
Null Hypothesis (Ho) : No Education difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
134
Education and Q12n
Observed Counts Prof. Look Contact Info
High School Graduate 8 21
Some College 22 51
Post College 37 56
Post Graduate 6 24
Expected Counts Prof. Look Contact Info
High School Graduate 9.41 19.59
Some College 23.68 49.32
Post College 30.17 62.83
Post Graduate 9.73 20.27
Test Statistics Value df p-value
Pearson Chi-Square 4.896 3 0.180
Likelihood Ratio Chi-Square 5.021 3 0.170
Null Hypothesis (Ho) : No Education difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
135
Education and Q12o
Observed Counts Ease of Use Reputation
High School Graduate 7 22
Some College 24 49
Post College 29 64
Post Graduate 7 23
Expected Counts Ease of Use Reputation
High School Graduate 8.64 20.36
Some College 21.74 51.26
Post College 27.69 65.31
Post Graduate 8.93 21.07
Test Statistics Value df p-value
Pearson Chi-Square 1.460 3 0.692
Likelihood Ratio Chi-Square 1.500 3 0.682
Null Hypothesis (Ho) : No Education difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
136
Education and Q13a
Observed Counts Need Price
High School Graduate 10 19
Some College 30 43
Post College 47 46
Post Graduate 16 14
Expected Counts Need Price
High School Graduate 13.28 15.72
Some College 33.42 39.58
Post College 42.57 50.43
Post Graduate 13.73 16.27
Test Statistics Value df p-value
Pearson Chi-Square 3.674 3 0.299
Likelihood Ratio Chi-Square 3.705 3 0.295
Null Hypothesis (Ho) : No Education difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
137
Education and 13b
Observed Counts Ease of Use Need
High School Graduate 6 23
Some College 32 40
Post College 44 49
Post Graduate 7 23
Expected Counts Ease of Use Need
High School Graduate 11.52 17.48
Some College 28.61 43.39
Post College 36.95 56.05
Post Graduate 11.92 18.08
Test Statistics Value df p-value
Pearson Chi-Square 10.660 3 0.014
Likelihood Ratio Chi-Square 11.271 3 0.010
Null Hypothesis (Ho) : No Education difference for Q13b.
The p-value is less than 0.05. Therefore REJECT the Ho.
138
Education and Q13c
Observed Counts Need Reputation
High School Graduate 8 21
Some College 22 51
Post College 37 56
Post Graduate 18 12
Expected Counts Need Reputation
High School Graduate 10.96 18.04
Some College 27.58 45.42
Post College 35.13 57.87
Post Graduate 11.33 18.67
Test Statistics Value df p-value
Pearson Chi-Square 9.556 3 0.023
Likelihood Ratio Chi-Square 9.421 3 0.024
Null Hypothesis (Ho) : No Education difference for Q13c.
The p-value is less than 0.05. Therefore REJECT the Ho.
139
Education and Q13d
Observed Counts Prof. Look Need
High School Graduate 10 19
Some College 33 40
Post College 29 64
Post Graduate 4 26
Expected Counts Prof. Look Need
High School Graduate 9.80 19.20
Some College 24.66 48.34
Post College 31.41 61.59
Post Graduate 10.13 19.87
Test Statistics Value df p-value
Pearson Chi-Square 10.154 3 0.017
Likelihood Ratio Chi-Square 10.924 3 0.012
Null Hypothesis (Ho) : No Education difference for Q13d.
The p-value is less than 0.05. Therefore REJECT the Ho.
140
Education and 13e
Observed Counts Contact Info Need
High School Graduate 18 11
Some College 48 25
Post College 45 48
Post Graduate 12 18
Expected Counts Contact Info Need
High School Graduate 15.85 13.15
Some College 39.91 33.09
Post College 50.84 42.16
Post Graduate 16.40 13.60
Test Statistics Value df p-value
Pearson Chi-Square 8.346 3 0.039
Likelihood Ratio Chi-Square 8.420 3 0.038
Null Hypothesis (Ho) : No Education difference for Q13e.
The p-value is less than 0.05. Therefore REJECT the Ho.
141
Education and Q13f
Observed Counts Product Info Need
High School Graduate 19 10
Some College 44 29
Post College 46 47
Post Graduate 13 17
Expected Counts Product Info Need
High School Graduate 15.72 13.28
Some College 39.58 33.42
Post College 50.43 42.57
Post Graduate 16.27 13.73
Test Statistics Value df p-value
Pearson Chi-Square 4.850 3 0.183
Likelihood Ratio Chi-Square 4.883 3 0.181
Null Hypothesis (Ho) : No Education difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
142
A.4 Income
Income and Q12a
Observed Counts Reputation Product Info
$10,000 or less 24 12
$25,000 or less 14 12
$50,000 or less 26 21
$75,000 or less 18 9
$100,000 or less 10 5
More than $100,000 19 6
Expected Counts Reputation Product Info
$10,000 or less 22.70 13.30
$25,000 or less 16.40 9.60
$50,000 or less 29.64 17.36
$75,000 or less 17.03 9.97
$100,000 or less 9.46 5.54
More than $100,000 15.77 9.23
Test Statistics Value df p-value
Pearson Chi-Square 4.390 5 0.495
Likelihood Ratio Chi-Square 4.462 5 0.485
Null Hypothesis (Ho) : No Income difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
143
Income and Q12b
Observed Counts Product Info Contact Info
$10,000 or less 11 25
$25,000 or less 10 16
$50,000 or less 21 26
$75,000 or less 10 17
$100,000 or less 6 9
More than $100,000 15 10
Expected Counts Product Info Contact Info
$10,000 or less 14.93 21.07
$25,000 or less 10.78 15.22
$50,000 or less 19.49 27.51
$75,000 or less 11.20 15.80
$100,000 or less 6.22 8.78
More than $100,000 10.37 14.63
Test Statistics Value df p-value
Pearson Chi-Square 5.832 5 0.323
Likelihood Ratio Chi-Square 5.829 5 0.323
Null Hypothesis (Ho) : No Income difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
144
Income and Q12c
Observed Counts Price Product Info
$10,000 or less 20 15
$25,000 or less 16 10
$50,000 or less 23 24
$75,000 or less 22 5
$100,000 or less 8 7
More than $100,000 13 12
Expected Counts Price Product Info
$10,000 or less 20.40 14.60
$25,000 or less 15.15 10.85
$50,000 or less 27.39 19.61
$75,000 or less 15.74 11.26
$100,000 or less 8.74 6.26
More than $100,000 14.57 10.43
Test Statistics Value df p-value
Pearson Chi-Square 8.354 5 0.138
Likelihood Ratio Chi-Square 8.969 5 0.110
Null Hypothesis (Ho) : No Income difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
145
Income and Q12d
Observed Counts Ease of Use Price
$10,000 or less 19 17
$25,000 or less 12 14
$50,000 or less 27 20
$75,000 or less 14 13
$100,000 or less 6 9
More than $100,000 9 16
Expected Counts Ease of Use Price
$10,000 or less 17.80 18.20
$25,000 or less 12.85 13.15
$50,000 or less 23.23 23.77
$75,000 or less 13.35 13.65
$100,000 or less 7.41 7.59
More than $100,000 12.36 12.64
Test Statistics Value df p-value
Pearson Chi-Square 3.882 5 0.566
Likelihood Ratio Chi-Square 3.916 5 0.562
Null Hypothesis (Ho) : No Income difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
146
Income and Q12e
Observed Counts Prof. Look Product Info
$10,000 or less 16 20
$25,000 or less 7 19
$50,000 or less 16 31
$75,000 or less 11 16
$100,000 or less 6 9
More than $100,000 9 15
Expected Counts Prof. Look Product Info
$10,000 or less 13.37 22.63
$25,000 or less 9.66 16.34
$50,000 or less 17.46 29.54
$75,000 or less 10.03 16.97
$100,000 or less 5.57 9.43
More than $100,000 8.91 15.09
Test Statistics Value df p-value
Pearson Chi-Square 2.382 5 0.794
Likelihood Ratio Chi-Square 2.420 5 0.788
Null Hypothesis (Ho) : No Income difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
147
Income and Q12f
Observed Counts Contact Info Reputation
$10,000 or less 16 20
$25,000 or less 11 15
$50,000 or less 24 22
$75,000 or less 9 18
$100,000 or less 3 12
More than $100,000 7 18
Expected Counts Contact Info Reputation
$10,000 or less 14.40 21.60
$25,000 or less 10.40 15.60
$50,000 or less 18.40 27.60
$75,000 or less 10.80 16.20
$100,000 or less 6.00 9.00
More than $100,000 10.00 15.00
Test Statistics Value df p-value
Pearson Chi-Square 7.695 5 0.174
Likelihood Ratio Chi-Square 7.953 5 0.159
Null Hypothesis (Ho) : No Income difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
148
Income and Q12g
Observed Counts Price Contact Info
$10,000 or less 14 22
$25,000 or less 11 15
$50,000 or less 23 24
$75,000 or less 15 12
$100,000 or less 7 8
More than $100,000 12 13
Expected Counts Price Contact Info
$10,000 or less 16.77 19.23
$25,000 or less 12.11 13.89
$50,000 or less 21.90 25.10
$75,000 or less 12.58 14.42
$100,000 or less 6.99 8.01
More than $100,000 11.65 13.35
Test Statistics Value df p-value
Pearson Chi-Square 2.046 5 0.843
Likelihood Ratio Chi-Square 2.054 5 0.842
Null Hypothesis (Ho) : No Income difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
149
Income and Q12h
Observed Counts Prof. Look Reputation
$10,000 or less 8 28
$25,000 or less 3 23
$50,000 or less 13 34
$75,000 or less 8 19
$100,000 or less 2 13
More than $100,000 5 20
Expected Counts Prof. Look Reputation
$10,000 or less 7.98 28.02
$25,000 or less 5.76 20.24
$50,000 or less 10.41 36.59
$75,000 or less 5.98 21.02
$100,000 or less 3.32 11.68
More than $100,000 5.54 19.46
Test Statistics Value df p-value
Pearson Chi-Square 4.143 5 0.529
Likelihood Ratio Chi-Square 4.394 5 0.494
Null Hypothesis (Ho) : No Income difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
150
Income and Q12i
Observed Counts Reputation Price
$10,000 or less 21 15
$25,000 or less 10 16
$50,000 or less 28 19
$75,000 or less 13 14
$100,000 or less 8 7
More than $100,000 17 8
Expected Counts Reputation Price
$10,000 or less 19.84 16.16
$25,000 or less 14.33 11.67
$50,000 or less 25.90 21.10
$75,000 or less 14.88 12.12
$100,000 or less 8.27 6.73
More than $100,000 13.78 11.22
Test Statistics Value df p-value
Pearson Chi-Square 5.670 5 0.340
Likelihood Ratio Chi-Square 5.709 5 0.336
Null Hypothesis (Ho) : No Income difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
151
Income and Q12j
Observed Counts Contact Info Ease of Use
$10,000 or less 25 11
$25,000 or less 14 12
$50,000 or less 27 20
$75,000 or less 14 13
$100,000 or less 5 10
More than $100,000 12 13
Expected Counts Contact Info Ease of Use
$10,000 or less 19.84 16.16
$25,000 or less 14.33 11.67
$50,000 or less 25.90 21.10
$75,000 or less 14.88 12.12
$100,000 or less 8.27 6.73
More than $100,000 13.78 11.22
Test Statistics Value df p-value
Pearson Chi-Square 6.613 5 0.251
Likelihood Ratio Chi-Square 6.723 5 0.242
Null Hypothesis (Ho) : No Income difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
152
Income and Q12k
Observed Counts Ease of Use Prof. Look
$10,000 or less 19 17
$25,000 or less 12 14
$50,000 or less 29 18
$75,000 or less 21 6
$100,000 or less 10 5
More than $100,000 17 8
Expected Counts Ease of Use Prof. Look
$10,000 or less 22.06 13.91
$25,000 or less 15.95 10.05
$50,000 or less 28.84 18.16
$75,000 or less 16.57 10.43
$100,000 or less 9.20 5.80
More than $100,000 15.34 9.66
Test Statistics Value df p-value
Pearson Chi-Square 7.369 5 0.195
Likelihood Ratio Chi-Square 7.532 5 0.184
Null Hypothesis (Ho) : No Income difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
153
Income and Q12l
Observed Counts Price Prof. Look
$10,000 or less 26 10
$25,000 or less 16 10
$50,000 or less 34 10
$75,000 or less 23 4
$100,000 or less 8 7
More than $100,000 17 8
Expected Counts Price Prof. Look
$10,000 or less 25.80 10.20
$25,000 or less 18.64 7.36
$50,000 or less 31.54 12.46
$75,000 or less 19.35 7.65
$100,000 or less 10.75 4.25
More than $100,000 17.92 7.08
Test Statistics Value df p-value
Pearson Chi-Square 7.080 5 0.215
Likelihood Ratio Chi-Square 7.136 5 0.211
Null Hypothesis (Ho) : No Income difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
154
Income and Q12m
Observed Counts Product Info Ease of Use
$10,000 or less 26 10
$25,000 or less 11 15
$50,000 or less 30 17
$75,000 or less 16 11
$100,000 or less 6 9
More than $100,000 17 8
Expected Counts Product Info Ease of Use
$10,000 or less 21.68 14.32
$25,000 or less 15.66 10.34
$50,000 or less 28.31 18.69
$75,000 or less 16.26 10.74
$100,000 or less 9.03 5.97
More than $100,000 15.06 9.94
Test Statistics Value df p-value
Pearson Chi-Square 9.105 5 0.105
Likelihood Ratio Chi-Square 9.060 5 0.107
Null Hypothesis (Ho) : No Income difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
155
Income and Q12n
Observed Counts Prof. Look Contact Info
$10,000 or less 11 25
$25,000 or less 8 18
$50,000 or less 21 26
$75,000 or less 9 18
$100,000 or less 5 10
More than $100,000 10 15
Expected Counts Prof. Look Contact Info
$10,000 or less 13.09 22.91
$25,000 or less 9.45 16.55
$50,000 or less 17.09 29.91
$75,000 or less 9.82 17.18
$100,000 or less 5.45 9.55
More than $100,000 9.09 15.91
Test Statistics Value df p-value
Pearson Chi-Square 2.591 5 0.763
Likelihood Ratio Chi-Square 2.576 5 0.765
Null Hypothesis (Ho) : No Income difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
156
Income and Q12o
Observed Counts Ease of Use Reputation
$10,000 or less 9 27
$25,000 or less 6 20
$50,000 or less 16 31
$75,000 or less 11 16
$100,000 or less 2 13
More than $100,000 10 16
Expected Counts Ease of Use Reputation
$10,000 or less 11.05 24.95
$25,000 or less 7.98 18.02
$50,000 or less 14.42 32.58
$75,000 or less 8.28 18.72
$100,000 or less 4.60 10.40
More than $100,000 7.67 17.33
Test Statistics Value df p-value
Pearson Chi-Square 5.931 5 0.313
Likelihood Ratio Chi-Square 6.227 5 0.285
Null Hypothesis (Ho) : No Income difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
157
Income and Q13a
Observed Counts Need Price
$10,000 or less 14 22
$25,000 or less 8 18
$50,000 or less 18 29
$75,000 or less 13 14
$100,000 or less 5 10
More than $100,000 16 9
Expected Counts Need Price
$10,000 or less 15.14 20.86
$25,000 or less 10.93 15.07
$50,000 or less 19.76 27.24
$75,000 or less 11.35 15.65
$100,000 or less 6.31 8.69
More than $100,000 10.51 14.49
Test Statistics Value df p-value
Pearson Chi-Square 7.600 5 0.180
Likelihood Ratio Chi-Square 7.587 5 0.180
Null Hypothesis (Ho) : No Income difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
158
Income and Q13b
Observed Counts Ease of Use Need
$10,000 or less 14 22
$25,000 or less 10 16
$50,000 or less 23 23
$75,000 or less 12 15
$100,000 or less 4 11
More than $100,000 5 20
Expected Counts Ease of use Need
$10,000 or less 13.99 22.01
$25,000 or less 10.10 15.90
$50,000 or less 17.87 28.13
$75,000 or less 10.49 16.51
$100,000 or less 5.83 9.17
More than $100,000 9.71 15.29
Test Statistics Value df p-value
Pearson Chi-Square 7.440 5 0.190
Likelihood Ratio Chi-Square 7.793 5 0.168
Null Hypothesis (Ho) : No Income difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
159
Income and Q13c
Observed Counts Need Reputation
$10,000 or less 12 24
$25,000 or less 5 21
$50,000 or less 18 29
$75,000 or less 10 17
$100,000 or less 4 11
More than $100,000 15 10
Expected Counts Need Reputation
$10,000 or less 13.09 22.91
$25,000 or less 9.45 16.55
$50,000 or less 17.09 29.91
$75,000 or less 9.82 17.18
$100,000 or less 5.45 9.55
More than $100,000 9.09 15.91
Test Statistics Value df p-value
Pearson Chi-Square 10.167 5 0.071
Likelihood Ratio Chi-Square 10.244 5 0.069
Null Hypothesis (Ho) : No Income difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
160
Income and Q13d
Observed Counts Prof. Look Need
$10,000 or less 12 24
$25,000 or less 12 14
$50,000 or less 19 28
$75,000 or less 12 15
$100,000 or less 8 7
More than $100,000 5 20
Expected Counts Prof. Look Need
$10,000 or less 13.91 22.09
$25,000 or less 10.05 15.95
$50,000 or less 18.16 28.84
$75,000 or less 10.43 16.57
$100,000 or less 5.80 9.20
More than $100,000 9.66 15.34
Test Statistics Value df p-value
Pearson Chi-Square 6.523 5 0.259
Likelihood Ratio Chi-Square 6.833 5 0.233
Null Hypothesis (Ho) : No Income difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
161
Income and Q13e
Observed Counts Contact Info Need
$10,000 or less 25 11
$25,000 or less 18 8
$50,000 or less 28 19
$75,000 or less 13 14
$100,000 or less 9 6
More than $100,000 8 17
Expected Counts Contact Info Need
$10,000 or less 20.66 15.34
$25,000 or less 14.92 11.08
$50,000 or less 26.97 20.03
$75,000 or less 15.49 11.51
$100,000 or less 8.61 6.39
More than $100,000 14.35 10.65
Test Statistics Value df p-value
Pearson Chi-Square 11.297 5 0.046
Likelihood Ratio Chi-Square 11.372 5 0.044
Null Hypothesis (Ho) : No Income difference for Q13e.
The p-value is less than 0.05. Therefore REJECT the Ho.
162
Income and Q13f
Observed Counts Product Info Need
$10,000 or less 23 13
$25,000 or less 16 10
$50,000 or less 28 19
$75,000 or less 10 17
$100,000 or less 9 6
More than $100,000 13 12
Expected Counts Product Info Need
$10,000 or less 20.25 15.75
$25,000 or less 14.63 11.38
$50,000 or less 26.44 20.56
$75,000 or less 15.19 11.81
$100,000 or less 8.44 6.56
More than $100,000 14.06 10.94
Test Statistics Value df p-value
Pearson Chi-Square 5.679 5 0.339
Likelihood Ratio Chi-Square 5.669 5 0.340
Null Hypothesis (Ho) : No Income difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
163
A.5 Trust
Trust and Q12a
Observed Counts Reputation Product Info
Trust 69 37
No Trust 82 38
Expected Counts Reputation Product Info
Trust 70.82 35.18
No Trust 80.18 39.82
Test Statistics Value df p-value
Pearson Chi-Square 0.266 1 0.606
Likelihood Ratio Chi-Square 0.266 1 0.606
Null Hypothesis (Ho) : No Trust difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
164
Trust and Q12b
Observed Counts Product Info Contact Info
Trust 42 64
No Trust 48 72
Expected Counts Product Info Contact Info
Trust 42.21 63.79
No Trust 47.79 72.21
Test Statistics Value df p-value
Pearson Chi-Square 0.003 1 0.954
Likelihood Ratio Chi-Square 0.003 1 0.954
Null Hypothesis (Ho) : No Trust difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
165
Trust and Q12c
Observed Counts Price Product Info
Trust 60 45
No Trust 76 43
Expected Counts Price Product Info
Trust 63.75 41.25
No Trust 72.25 46.75
Test Statistics Value df p-value
Pearson Chi-Square 1.057 1 0.304
Likelihood Ratio Chi-Square 1.057 1 0.304
Null Hypothesis (Ho) : No Trust difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
166
Trust and Q12d
Observed Counts Ease of Use Price
Trust 58 48
No Trust 58 62
Expected Counts Ease of Use Price
Trust 54.41 51.59
No Trust 61.59 58.41
Test Statistics Value df p-value
Pearson Chi-Square 0.918 1 0.338
Likelihood Ratio Chi-Square 0.919 1 0.338
Null Hypothesis (Ho) : No Trust difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
167
Trust and Q12e
Observed Counts Prof. Look Product Info
Trust 47 59
No Trust 38 81
Expected Counts Prof. Look Product Info
Trust 40.04 65.96
No Trust 44.96 74.04
Test Statistics Value df p-value
Pearson Chi-Square 3.671 1 0.055
Likelihood Ratio Chi-Square 1 0.055
Null Hypothesis (Ho) : No Trust difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
168
Trust and Q12f
Observed Counts Contact Info Reputation
Trust 42 63
No Trust 45 75
Expected Counts Contact Info Reputation
Trust 40.60 64.40
No Trust 46.40 73.60
Test Statistics Value df p-value
Pearson Chi-Square 0.148 1 0.701
Likelihood Ratio Chi-Square 0.148 1 0.701
Null Hypothesis (Ho) : No Trust difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
169
Trust and Q12g
Observed Counts Price Contact Info
Trust 53 53
No Trust 48 72
Expected Counts Price Contact Info
Trust 47.37 58.63
No Trust 53.63 66.37
Test Statistics Value df p-value
Pearson Chi-Square 2.277 1 0.131
Likelihood Ratio Chi-Square 2.279 1 0.131
Null Hypothesis (Ho) : No Trust difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
170
Trust and Q12h
Observed Counts Prof. Look Reputation
Trust 22 84
No Trust 26 94
Expected Counts Prof. Look Reputation
Trust 22.51 83.49
No Trust 25.49 94.51
Test Statistics Value df p-value
Pearson Chi-Square 0.028 1 0.867
Likelihood Ratio Chi-Square 0.028 1 0.867
Null Hypothesis (Ho) : No Trust difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
171
Trust and Q12i
Observed Counts Reputation Price
Trust 59 47
No Trust 71 49
Expected Counts Reputation Price
Trust 60.97 45.03
No Trust 69.03 50.97
Test Statistics Value df p-value
Pearson Chi-Square 0.283 1 0.595
Likelihood Ratio Chi-Square 0.283 1 0.595
Null Hypothesis (Ho) : No Trust difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
172
Trust and Q12j
Observed Counts Contact Info Ease of Use
Trust 59 47
No Trust 60 60
Expected Counts Contact Info Ease of Use
Trust 55.81 50.19
No Trust 63.19 56.81
Test Statistics Value df p-value
Pearson Chi-Square 0.723 1 0.395
Likelihood Ratio Chi-Square 0.724 1 0.395
Null Hypothesis (Ho) : No Trust difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
173
Trust and Q12k
Observed Counts Ease of Use Prof. Look
Trust 67 39
No Trust 83 37
Expected Counts
Trust 70.35 35.65
No Trust 79.65 40.35
Test Statistics Value df p-value
Pearson Chi-Square 0.895 1 0.344
Likelihood Ratio Chi-Square 0.895 1 0.344
Null Hypothesis (Ho) : No Trust difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
174
Trust and Q12l
Observed Counts Price Prof. Look
Trust 70 35
No Trust 96 22
Expected Counts Price Prof. Look
Trust 78.16 26.84
No Trust 87.84 30.16
Test Statistics Value df p-value
Pearson Chi-Square 6.301 1 0.012
Likelihood Ratio Chi-Square 6.322 1 0.012
Null Hypothesis (Ho) : No Trust difference for Q12l.
The p-value is less than 0.05. Therefore REJECT the Ho.
175
Trust and Q12m
Observed Counts Product Info Ease of Use
Trust 66 40
No Trust 73 47
Expected Counts Product Info Ease of Use
Trust 65.19 40.81
No Trust 73.81 46.19
Test Statistics Value df p-value
Pearson Chi-Square 0.049 1 0.825
Likelihood Ratio Chi-Square 0.049 1 0.825
Null Hypothesis (Ho) : No Trust difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
176
Trust and Q12n
Observed Counts Prof. Look Contact Info
Trust 43 63
No Trust 32 88
Expected Counts Prof. Look Contact Info
Trust 35.18 70.82
No Trust 39.82 80.18
Test Statistics Value df p-value
Pearson Chi-Square 4.904 1 0.027
Likelihood Ratio Chi-Square 4.904 1 0.027
Null Hypothesis (Ho) : No Trust difference for Q12n.
The p-value is less than 0.05. Therefore REJECT the Ho.
177
Trust and Q12o
Observed Counts Ease of Use Reputation
Trust 35 71
No Trust 32 88
Expected Counts Ease of Use Reputation
Trust 31.42 74.58
No Trust 35.58 84.42
Test Statistics Value df p-value
Pearson Chi-Square 1.089 1 0.297
Likelihood Ratio Chi-Square 1.088 1 0.297
Null Hypothesis (Ho) : No Trust difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
178
Trust and Q13a
Observed Counts Need Price
Trust 51 55
No Trust 53 67
Expected Counts Need Price
Trust 48.78 57.22
No Trust 55.22 64.78
Test Statistics Value df p-value
Pearson Chi-Square 0.353 1 0.552
Likelihood Ratio Chi-Square 0.353 1 0.552
Null Hypothesis (Ho) : No Trust difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
179
Trust and Q13b
Observed Counts Ease of Use Need
Trust 45 61
No Trust 46 73
Expected Counts Ease of Use Need
Trust 42.87 63.13
No Trust 48.13 70.87
Test Statistics Value df p-value
Pearson Chi-Square 0.336 1 0.562
Likelihood Ratio Chi-Square 0.336 1 0.562
Null Hypothesis (Ho) : No Trust difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
180
Trust and Q13c
Observed Counts Need Reputation
Trust 47 59
No Trust 38 82
Expected Counts Need Reputation
Trust 39.87 66.13
No Trust 45.13 74.87
Test Statistics Value df p-value
Pearson Chi-Square 3.852 1 0.050
Likelihood Ratio Chi-Square 3.856 1 0.050
Null Hypothesis (Ho) : No Trust difference for Q13c.
The p-value is equal to 0.05. Therefore REJECT the Ho.
181
Trust and Q13d
Observed Counts Prof. Look Need
Trust 38 68
No Trust 39 81
Expected Counts Prof. Look Need
Trust 36.12 69.88
No Trust 40.88 79.12
Test Statistics Value df p-value
Pearson Chi-Square 0.281 1 0.596
Likelihood Ratio Chi-Square 0.281 1 0.596
Null Hypothesis (Ho) : No Trust difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
182
Trust and Q13e
Observed Counts Contact Info Need
Trust 60 46
No Trust 64 56
Expected Counts Contact Info Need
Trust 58.16 47.84
No Trust 65.84 54.16
Test Statistics Value df p-value
Pearson Chi-Square 0.243 1 0.622
Likelihood Ratio Chi-Square 0.243 1 0.622
Null Hypothesis (Ho) : No Trust difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
183
Trust and Q13f
Observed Counts Product Info Need
Trust 57 49
No Trust 67 53
Expected Counts Product Info Need
Trust 58.16 47.84
No Trust 65.84 54.16
Test Statistics Value df p-value
Pearson Chi-Square 0.096 1 0.756
Likelihood Ratio Chi-Square 0.096 1 0.756
Null Hypothesis (Ho) : No Trust difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
184
A.6 Freq. Web
Freq. Web and Q12a
Observed Counts Reputation Product Info
Once a month 15 5
Once a week 16 3
Several times a week 29 18
Once a day 9 11
Several times a day 82 38
Expected Counts Reputation Product Info
Once a month 13.36 6.64
Once a week 12.69 6.31
Several times a week 31.40 15.60
Once a day 13.36 6.64
Several times a day 80.18 39.82
Test Statistics Value df p-value
Pearson Chi-Square 8.169 4 0.086
Likelihood Ratio Chi-Square 8.250 4 0.083
Null Hypothesis (Ho) : No Freq. Web difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
185
Freq. Web and Q12b
Observed Counts Product Info Contact Info
Once a month 6 14
Once a week 11 8
Several times a week 18 29
Once a day 8 12
Several times a day 47 73
Expected Counts Product Info Contact Info
Once a month 7.96 12.04
Once a week 7.57 11.43
Several times a week 18.72 28.28
Once a day 7.96 12.04
Several times a day 47.79 72.21
Test Statistics Value df p-value
Pearson Chi-Square 3.462 4 0.484
Likelihood Ratio Chi-Square 3.421 4 0.490
Null Hypothesis (Ho) : No Freq. Web difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
186
Freq. Web and Q12c
Observed Counts Price Product Info
Once a month 12 7
Once a week 10 9
Several times a week 24 22
Once a day 13 7
Several times a day 76 44
Expected Counts Price Product Info
Once a month 11.45 7.55
Once a week 11.45 7.55
Several times a week 27.72 18.28
Once a day 12.05 7.95
Several times a day 72.32 47.68
Test Statistics Value df p-value
Pearson Chi-Square 2.445 4 0.654
Likelihood Ratio Chi-Square 2.423 4 0.659
Null Hypothesis (Ho) : No Freq. Web difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
187
Freq. Web and Q12d
Observed Counts Ease of Use Price
Once a month 11 9
Once a week 11 8
Several times a week 24 23
Once a day 9 11
Several times a day 61 59
Expected Counts Ease of Use Price
Once a month 10.27 9.73
Once a week 9.75 9.25
Several times a week 24.12 22.88
Once a day 10.27 9.73
Several times a day 61.59 58.41
Test Statistics Value df p-value
Pearson Chi-Square 0.770 4 0.942
Likelihood Ratio Chi-Square 0.772 4 0.942
Null Hypothesis (Ho) : No Freq. Web difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
188
Freq. Web and Q12e
Observed Counts Prof. Look Product Info
Once a month 10 10
Once a week 8 11
Several times a week 18 28
Once a day 6 14
Several times a day 43 77
Expected Counts Prof. Look Product Info
Once a month 7.56 12.44
Once a week 7.18 11.82
Several times a week 17.38 28.62
Once a day 7.56 12.44
Several times a day 45.33 74.67
Test Statistics Value df p-value
Pearson Chi-Square 2.166 4 0.705
Likelihood Ratio Chi-Square 2.143 4 0.709
Null Hypothesis (Ho) : No Freq. Web difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
189
Freq. Web and Q12f
Observed Counts Contact Info Reputation
Once a month 10 10
Once a week 11 8
Several times a week 15 32
Once a day 8 12
Several times a day 44 75
Expected Counts Contact Info Reputation
Once a month 7.82 12.18
Once a week 7.43 11.57
Several times a week 18.38 28.62
Once a day 7.82 12.18
Several times a day 46.54 72.46
Test Statistics Value df p-value
Pearson Chi-Square 5.067 4 0.280
Likelihood Ratio Chi-Square 4.984 4 0.289
Null Hypothesis (Ho) : No Freq. Web difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
190
Freq. Web and Q12g
Observed Counts Price Contact Info
Once a month 10 10
Once a week 6 13
Several times a week 17 30
Once a day 7 13
Several times a day 61 59
Expected Counts Price Contact Info
Once a month 8.94 11.06
Once a week 8.49 10.51
Several times a week 21.00 26.00
Once a day 8.94 11.06
Several times a day 53.63 66.37
Test Statistics Value df p-value
Pearson Chi-Square 5.522 4 0.238
Likelihood Ratio Chi-Square 5.592 4 0.232
Null Hypothesis (Ho) : No Freq. Web difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
191
Freq. Web and Q12h
Observed Counts Prof. Look Reputation
Once a month 7 13
Once a week 3 16
Several times a week 12 35
Once a day 7 13
Several times a day 19 101
Expected Counts Prof. Look Reputation
Once a month 4.25 15.75
Once a week 4.04 14.96
Several times a week 9.98 37.02
Once a day 4.25 15.75
Several times a day 25.49 94.51
Test Statistics Value df p-value
Pearson Chi-Square 7.479 4 0.113
Likelihood Ratio Chi-Square 7.105 4 0.130
Null Hypothesis (Ho) : No Freq. Web difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
192
Freq. Web and Q12i
Observed Counts Reputation Price
Once a month 12 8
Once a week 10 9
Several times a week 26 21
Once a day 12 8
Several times a day 70 50
Expected Counts Reputation Price
Once a month 11.50 8.50
Once a week 10.93 8.07
Several times a week 27.04 19.96
Once a day 11.50 8.50
Several times a day 69.03 50.97
Test Statistics Value df p-value
Pearson Chi-Square 0.412 4 0.981
Likelihood Ratio Chi-Square 0.411 4 0.982
Null Hypothesis (Ho) : No Freq. Web difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
193
Freq. Web and Q12j
Observed Counts Contact Info Ease of Use
Once a month 12 8
Once a week 8 11
Several times a week 32 15
Once a day 9 11
Several times a day 59 61
Expected Counts Contact Info Ease of Use
Once a month 10.62 9.38
Once a week 10.09 8.91
Several times a week 24.96 22.04
Once a day 10.62 9.38
Several times a day 63.72 56.28
Test Statistics Value df p-value
Pearson Chi-Square 6.815 4 0.146
Likelihood Ratio Chi-Square 6.938 4 0.139
Null Hypothesis (Ho) : No Freq. Web difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
194
Freq. Web and Q12k
Observed Counts Ease of Use Prof. Look
Once a month 11 9
Once a week 12 7
Several times a week 25 22
Once a day 13 7
Several times a day 89 31
Expected Counts Ease of Use Prof. Look
Once a month 13.27 6.73
Once a week 12.61 6.39
Several times a week 31.19 15.81
Once a day 13.27 6.73
Several times a day 79.65 40.35
Test Statistics Value df p-value
Pearson Chi-Square 8.188 4 0.085
Likelihood Ratio Chi-Square 8.110 4 0.088
Null Hypothesis (Ho) : No Freq. Web difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
195
Freq. Web and Q12l
Observed Counts Price Prof. Look
Once a month 15 5
Once a week 13 5
Several times a week 29 17
Once a day 14 6
Several times a day 95 24
Expected Counts Price Prof. Look
Once a month 14.89 5.11
Once a week 13.40 4.60
Several times a week 34.24 11.76
Once a day 14.89 5.11
Several times a day 88.58 30.42
Test Statistics Value df p-value
Pearson Chi-Square 5.215 4 0.266
Likelihood Ratio Chi-Square 5.062 4 0.281
Null Hypothesis (Ho) : No Freq. Web difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
196
Freq. Web and Q12m
Observed Counts Product Info Ease of Use
Once a month 10 10
Once a week 5 14
Several times a week 35 12
Once a day 11 9
Several times a day 79 41
Expected Counts Product Info Ease of Use
Once a month 12.39 7.61
Once a week 11.77 7.23
Several times a week 29.12 17.88
Once a day 12.39 7.61
Several times a day 74.34 45.66
Test Statistics Value df p-value
Pearson Chi-Square 15.748 4 0.003
Likelihood Ratio Chi-Square 15.608 4 0.004
Null Hypothesis (Ho) : No Freq. Web difference for Q12m.
The p-value is less than 0.05. Therefore REJECT the Ho.
197
Freq. Web and Q12n
Observed Counts Prof. Look Contact Info
Once a month 9 11
Once a week 8 11
Several times a week 16 31
Once a day 6 14
Several times a day 36 84
Expected Counts Prof. Look Contact Info
Once a month 6.64 13.36
Once a week 6.31 12.69
Several times a week 15.60 31.40
Once a day 6.64 13.36
Several times a day 39.82 80.18
Test Statistics Value df p-value
Pearson Chi-Square 2.597 4 0.627
Likelihood Ratio Chi-Square 2.525 4 0.640
Null Hypothesis (Ho) : No Freq. Web difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
198
Freq. Web and Q12o
Observed Counts Ease of Use Reputation
Once a month 7 13
Once a week 4 15
Several times a week 15 32
Once a day 8 12
Several times a day 33 87
Expected Counts Ease of Use Reputation
Once a month 5.93 14.07
Once a week 5.63 13.37
Several times a week 13.93 33.07
Once a day 5.93 14.07
Several times a day 35.58 84.42
Test Statistics Value df p-value
Pearson Chi-Square 2.357 4 0.670
Likelihood Ratio Chi-Square 2.341 4 0.673
Null Hypothesis (Ho) : No Freq. Web difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
199
Freq. Web and Q13a
Observed Counts Need Price
Once a month 9 11
Once a week 7 12
Several times a week 20 27
Once a day 14 6
Several times a day 54 66
Expected Counts Need Price
Once a month 9.20 10.80
Once a week 8.74 10.26
Several times a week 21.63 25.37
Once a day 9.20 10.80
Several times a day 55.22 64.78
Test Statistics Value df p-value
Pearson Chi-Square 5.560 4 0.235
Likelihood Ratio Chi-Square 5.636 4 0.228
Null Hypothesis (Ho) : No Freq. Web difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
200
Freq. Web and Q13b
Observed Counts Ease of Use Need
Once a month 12 8
Once a week 8 11
Several times a week 28 18
Once a day 6 14
Several times a day 37 83
Expected Counts Ease of Use Need
Once a month 8.09 11.91
Once a week 7.68 11.32
Several times a week 18.60 27.40
Once a day 8.09 11.91
Several times a day 48.53 71.47
Test Statistics Value df p-value
Pearson Chi-Square 16.672 4 0.002
Likelihood Ratio Chi-Square 16.588 4 0.002
Null Hypothesis (Ho) : No Freq. Web difference for Q13b.
The p-value is less than 0.05. Therefore REJECT the Ho.
201
Freq. Web and Q13c
Observed Counts Need Reputation
Once a month 5 15
Once a week 3 16
Several times a week 11 36
Once a day 10 10
Several times a day 57 63
Expected Counts Need Reputation
Once a month 7.61 12.39
Once a week 7.23 11.77
Several times a week 17.88 29.12
Once a day 7.61 12.39
Several times a day 45.66 74.34
Test Statistics Value df p-value
Pearson Chi-Square 15.473 4 0.004
Likelihood Ratio Chi-Square 16.279 4 0.003
Null Hypothesis (Ho) : No Freq. Web difference for Q13c.
The p-value is less than 0.05. Therefore REJECT the Ho.
202
Freq. Web and Q13d
Observed Counts Prof. Look Need
Once a month 11 9
Once a week 7 12
Several times a week 28 19
Once a day 6 14
Several times a day 25 95
Expected Counts Prof. Look Need
Once a month 6.81 13.19
Once a week 6.47 12.53
Several times a week 16.01 30.99
Once a day 6.81 13.19
Several times a day 40.88 79.12
Test Statistics Value df p-value
Pearson Chi-Square 27.083 4 0.000
Likelihood Ratio Chi-Square 26.752 4 0.000
Null Hypothesis (Ho) : No Freq. Web difference for Q13d.
The p-value is less than 0.05. Therefore do REJECT the Ho.
203
Freq. Web and Q13e
Observed Counts Contact Info Need
Once a month 15 5
Once a week 13 6
Several times a week 33 14
Once a day 11 9
Several times a day 52 68
Expected Counts Contact Info Need
Once a month 10.97 9.03
Once a week 10.42 8.58
Several times a week 25.79 21.21
Once a day 10.97 9.03
Several times a day 65.84 54.16
Test Statistics Value df p-value
Pearson Chi-Square 15.599 4 0.004
Likelihood Ratio Chi-Square 15.973 4 0.003
Null Hypothesis (Ho) : No Freq. Web difference for Q13e.
The p-value is less than 0.05. Therefore REJECT the Ho.
204
Freq. Web and Q13f
Observed Counts Product Info Need
Once a month 14 6
Once a week 9 10
Several times a week 32 15
Once a day 9 11
Several times a day 60 60
Expected Counts Product Info Need
Once a month 10.97 9.03
Once a week 10.42 8.58
Several times a week 25.79 21.21
Once a day 10.97 9.03
Several times a day 65.84 54.16
Test Statistics Value df p-value
Pearson Chi-Square 7.531 4 0.110
Likelihood Ratio Chi-Square 7.690 4 0.104
Null Hypothesis (Ho) : No Freq. Web difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
205
A.7 History
History and Q12a
Observed Counts Reputation Product Info
A year or less 11 8
5 years or less 52 19
10 years or less 61 27
More than 10 years 27 22
Expected Counts Reputation Product Info
A year or less 12.64 6.36
5 years or less 47.23 23.77
10 years or less 58.54 29.46
More than 10 years 32.59 16.41
Test Statistics Value df p-value
Pearson Chi-Square 5.252 3 0.154
Likelihood Ratio Chi-Square 5.164 3 0.160
Null Hypothesis (Ho) : No History difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
206
History and Q12b
Observed Counts Product Info Contact Info
A year or less 9 10
5 years or less 26 45
10 years or less 37 51
More than 10 years 19 30
Expected Counts Product Info Contact Info
A year or less 7.62 11.38
5 years or less 28.46 42.54
10 years or less 35.28 52.72
More than 10 years 19.64 29.36
Test Statistics Value df p-value
Pearson Chi-Square 0.950 3 0.813
Likelihood Ratio Chi-Square 0.947 3 0.814
Null Hypothesis (Ho) : No History difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
207
History and Q12c
Observed Counts Price Product Info
A year or less 12 7
5 years or less 35 34
10 years or less 59 29
More than 10 years 30 19
Expected Counts Price Product Info
A year or less 11.48 7.52
5 years or less 41.71 27.29
10 years or less 53.19 34.81
More than 10 years 29.62 19.38
Test Statistics Value df p-value
Pearson Chi-Square 4.401 3 0.221
Likelihood Ratio Chi-Square 4.381 3 0.223
Null Hypothesis (Ho) : No History difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
208
History and Q12d
Observed Counts Ease of Use Price
A year or less 10 9
5 years or less 37 34
10 years or less 49 39
More than 10 years 20 29
Expected Counts Ease of Use Price
A year or less 9.71 9.29
5 years or less 36.28 34.72
10 years or less 44.67 43.03
More than 10 years 25.04 23.96
Test Statistics Value df p-value
Pearson Chi-Square 2.860 3 0.414
Likelihood Ratio Chi-Square 2.871 3 0.412
Null Hypothesis (Ho) : No History difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
209
History and Q12e
Observed Counts Prof. Look Product Info
A year or less 8 11
5 years or less 27 43
10 years or less 31 57
More than 10 years 19 30
Expected Counts Prof. Look Product Info
A year or less 7.15 11.85
5 years or less 26.33 43.67
10 years or less 33.10 54.90
More than 10 years 18.43 30.57
Test Statistics Value df p-value
Pearson Chi-Square 0.432 3 0.933
Likelihood Ratio Chi-Square 0.432 3 0.934
Null Hypothesis (Ho) : No History difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
210
History and Q12f
Observed Counts Contact Info Reputation
A year or less 8 11
5 years or less 37 33
10 years or less 25 63
More than 10 years 18 31
Expected Counts Contact Info Reputation
A year or less 7.40 11.60
5 years or less 27.26 42.74
10 years or less 34.27 53.73
More than 10 years 19.08 29.92
Test Statistics Value df p-value
Pearson Chi-Square 9.987 3 0.019
Likelihood Ratio Chi-Square 10.002 3 0.019
Null Hypothesis (Ho) : No History difference for Q12f.
The p-value is less than 0.05. Therefore REJECT the Ho.
211
History and Q12g
Observed Counts Price Contact Info
A year or less 7 12
5 years or less 26 45
10 years or less 41 47
More than 10 years 28 21
Expected Counts Price Contact Info
A year or less 8.54 10.46
5 years or less 31.90 39.10
10 years or less 39.54 48.46
More than 10 years 22.02 26.98
Test Statistics Value df p-value
Pearson Chi-Square 5.536 3 0.137
Likelihood Ratio Chi-Square 5.557 3 0.135
Null Hypothesis (Ho) : No History difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
212
History and Q12h
Observed Counts Prof. Look Reputation
A year or less 8 11
5 years or less 14 57
10 years or less 14 74
More than 10 years 12 37
Expected Counts Prof. Look Reputation
A year or less 4.02 14.98
5 years or less 15.01 55.99
10 years or less 18.61 69.39
More than 10 years 10.36 38.64
Test Statistics Value df p-value
Pearson Chi-Square 6.868 3 0.076
Likelihood Ratio Chi-Square 6.176 3 0.103
Null Hypothesis (Ho) : No History difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
213
History and Q12i
Observed Counts Reputation Price
A year or less 9 10
5 years or less 48 23
10 years or less 45 43
More than 10 years 28 21
Expected Counts Reputation Price
A year or less 10.88 8.12
5 years or less 40.66 30.34
10 years or less 50.40 37.60
More than 10 years 28.06 20.94
Test Statistics Value df p-value
Pearson Chi-Square 5.214 3 0.157
Likelihood Ratio Chi-Square 5.282 3 0.152
Null Hypothesis (Ho) : No History difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
214
History and Q12j
Observed Counts Contact Info Ease of Use
A year or less 12 7
5 years or less 37 34
10 years or less 49 39
More than 10 years 22 27
Expected Counts Contact Info Ease of Use
A year or less 10.04 8.96
5 years or less 37.53 33.47
10 years or less 46.52 41.48
More than 10 years 25.90 23.10
Test Statistics Value df p-value
Pearson Chi-Square 2.352 3 0.503
Likelihood Ratio Chi-Square 2.363 3 0.501
Null Hypothesis (Ho) : No History difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
215
History and Q12k
Observed Counts Ease of Use Prof. Look
A year or less 10 9
5 years or less 43 28
10 years or less 63 25
More than 10 years 35 14
Expected Counts Ease of Use Prof. Look
A year or less 12.64 6.36
5 years or less 47.23 23.77
10 years or less 58.54 29.46
More than 10 years 32.59 16.41
Test Statistics Value df p-value
Pearson Chi-Square 4.323 3 0.229
Likelihood Ratio Chi-Square 4.254 3 0.235
Null Hypothesis (Ho) : No History difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
216
History and Q12l
Observed Counts Price Prof. Look
A year or less 12 7
5 years or less 52 17
10 years or less 65 23
More than 10 years 38 10
Expected Counts Price Prof. Look
A year or less 14.17 4.83
5 years or less 51.44 17.56
10 years or less 65.61 22.39
More than 10 years 35.79 12.21
Test Statistics Value df p-value
Pearson Chi-Square 1.885 3 0.597
Likelihood Ratio Chi-Square 1.808 3 0.613
Null Hypothesis (Ho) : No History difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
217
History and Q12m
Observed Counts Product Info Ease of Use
A year or less 12 7
5 years or less 41 30
10 years or less 54 34
More than 10 years 33 16
Expected Counts Product Info Ease of Use
A year or less 11.72 7.28
5 years or less 43.79 27.21
10 years or less 54.27 33.73
More than 10 years 30.22 18.78
Test Statistics Value df p-value
Pearson Chi-Square 1.152 3 0.765
Likelihood Ratio Chi-Square 1.161 3 0.762
Null Hypothesis (Ho) : No History difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
218
History and Q12n
Observed Counts Prof. Look Contact Info
A year or less 9 10
5 years or less 25 46
10 years or less 21 67
More than 10 years 20 29
Expected Counts Prof. Look Contact Info
A year or less 6.28 12.72
5 years or less 23.46 47.54
10 years or less 29.07 28.93
More than 10 years 16.19 32.81
Test Statistics Value df p-value
Pearson Chi-Square 6.603 3 0.086
Likelihood Ratio Chi-Square 6.657 3 0.084
Null Hypothesis (Ho) : No History difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
219
History and Q12o
Observed Counts Ease of Use Reputation
A year or less 6 13
5 years or less 18 53
10 years or less 27 61
More than 10 years 16 33
Expected Counts Ease of Use Reputation
A year or less 5.61 13.39
5 years or less 20.96 50.04
10 years or less 25.97 62.03
More than 10 years 14.46 34.54
Test Statistics Value df p-value
Pearson Chi-Square 0.920 3 0.821
Likelihood Ratio Chi-Square 0.932 3 0.818
Null Hypothesis (Ho) : No History difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
220
History and Q13a
Observed Counts Need Price
A year or less 8 11
5 years or less 27 44
10 years or less 44 44
More than 10 years 25 24
Expected Counts Need Price
A year or less 8.70 10.30
5 years or less 32.53 38.47
10 years or less 40.32 47.68
More than 10 years 22.45 26.55
Test Statistics Value df p-value
Pearson Chi-Square 2.995 3 0.392
Likelihood Ratio Chi-Square 3.014 3 0.389
Null Hypothesis (Ho) : No History difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
221
History and Q13b
Observed Counts Ease of Use Need
A year or less 10 9
5 years or less 36 35
10 years or less 31 56
More than 10 years 14 35
Expected Counts Ease of Use Need
A year or less 7.65 11.35
5 years or less 28.59 42.41
10 years or less 35.03 51.97
More than 10 years 19.73 29.27
Test Statistics Value df p-value
Pearson Chi-Square 7.987 3 0.046
Likelihood Ratio Chi-Square 8.030 3 0.045
Null Hypothesis (Ho) : No History difference for Q13b.
The p-value is less than 0.05. Therefore do REJECT the Ho.
222
History and Q13c
Observed Counts Need Reputation
A year or less 6 13
5 years or less 20 51
10 years or less 34 54
More than 10 years 26 23
Expected Counts Need Reputation
A year or less 7.20 11.80
5 years or less 26.90 44.10
10 years or less 33.34 54.66
More than 10 years 18.56 30.44
Test Statistics Value df p-value
Pearson Chi-Square 7.986 3 0.046
Likelihood Ratio Chi-Square 7.952 3 0.047
Null Hypothesis (Ho) : No History difference for Q13c.
The p-value is less than 0.05. Therefore REJECT the Ho.
223
History and Q13d
Observed Counts Prof. Look Need
A year or less 9 10
5 years or less 32 39
10 years or less 27 61
More than 10 years 9 40
Expected Counts Prof. Look Need
A year or less 6.44 12.56
5 years or less 24.08 46.92
10 years or less 29.85 58.15
More than 10 years 16.62 32.38
Test Statistics Value df p-value
Pearson Chi-Square 11.171 3 0.011
Likelihood Ratio Chi-Square 11.521 3 0.009
Null Hypothesis (Ho) : No History difference for Q13d.
The p-value is less than 0.05. Therefore REJECT the Ho.
224
History and Q13e
Observed Counts Contact Info Need
A year or less 14 5
5 years or less 46 25
10 years or less 47 41
More than 10 years 17 32
Expected Counts Contact Info Need
A year or less 10.38 8.62
5 years or less 38.78 32.22
10 years or less 48.07 39.93
More than 10 years 26.77 22.23
Test Statistics Value df p-value
Pearson Chi-Square 13.649 3 0.003
Likelihood Ratio Chi-Square 13.874 3 0.003
Null Hypothesis (Ho) : No History difference for Q13e.
The p-value is less than 0.05. Therefore do REJECT the Ho.
225
History and Q13f
Observed Counts Product Info Need
A year or less 12 7
5 years or less 48 23
10 years or less 45 43
More than 10 years 19 30
Expected Counts Product Info Need
A year or less 10.38 8.62
5 years or less 38.78 32.22
10 years or less 48.07 39.93
More than 10 years 26.77 22.23
Test Statistics Value df p-value
Pearson Chi-Square 10.783 3 0.013
Likelihood Ratio Chi-Square 10.916 3 0.012
Null Hypothesis (Ho) : No History difference for Q13f.
The p-value is less than 0.05. Therefore do REJECT the Ho.
226
A.8 Browse
Browse and Q12a
Observed Counts Reputation Product Info
Never 12 8
Once a month 52 24
Once a week 48 14
Several times a week 25 17
Once a day 6 6
Several times a day 8 7
Expected Counts Reputation Product Info
Never 13.30 6.70
Once a month 50.56 25.44
Once a week 41.24 20.76
Several times a week 27.94 14.06
Once a day 7.98 4.02
Several times a day 9.98 5.02
Test Statistics Value df p-value
Pearson Chi-Square 7.377 5 0.194
Likelihood Ratio Chi-Square 7.431 5 0.190
Null Hypothesis (Ho) : No Browse difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
227
Browse and Q12b
Observed Counts Product Info Contact Info
Never 9 11
Once a month 31 45
Once a week 20 42
Several times a week 20 22
Once a day 5 7
Several times a day 6 9
Expected Counts Product Info Contact Info
Never 8.02 11.98
Once a month 30.47 45.53
Once a week 24.85 37.15
Several times a week 16.84 25.16
Once a day 4.81 7.19
Several times a day 6.01 8.99
Test Statistics Value df p-value
Pearson Chi-Square 2.803 5 0.730
Likelihood Ratio Chi-Square 2.827 5 0.727
Null Hypothesis (Ho) : No Browse difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
228
Browse and Q12c
Observed Counts Price Product Info
Never 12 8
Once a month 46 29
Once a week 34 27
Several times a week 29 13
Once a day 7 5
Several times a day 8 7
Expected Counts Price Product Info
Never 12.09 7.91
Once a month 45.33 29.67
Once a week 36.87 24.13
Several times a week 25.39 16.61
Once a day 7.25 4.75
Several times a day 9.07 5.93
Test Statistics Value df p-value
Pearson Chi-Square 2.231 5 0.816
Likelihood Ratio Chi-Square 2.261 5 0.812
Null Hypothesis (Ho) : No Browse difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
229
Browse and Q12d
Observed Counts Ease of Use Price
Never 10 10
Once a month 42 34
Once a week 35 27
Several times a week 17 25
Once a day 6 6
Several times a day 6 9
Expected Counts Ease of Use Price
Never 10.22 9.78
Once a month 38.84 37.16
Once a week 31.68 30.32
Several times a week 21.46 20.54
Once a day 6.13 5.87
Several times a day 7.67 7.33
Test Statistics Value df p-value
Pearson Chi-Square 3.890 5 0.565
Likelihood Ratio Chi-Square 3.906 5 0.563
Null Hypothesis (Ho) : No Browse difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
230
Browse and Q12e
Observed Counts Prof. Look Product Info
Never 6 14
Once a month 27 49
Once a week 27 34
Several times a week 18 24
Once a day 2 10
Several times a day 5 10
Expected Counts Prof. Look Product Info
Never 7.52 12.48
Once a month 28.58 47.42
Once a week 22.94 38.06
Several times a week 15.80 26.20
Once a day 4.51 7.49
Several times a day 5.64 9.36
Test Statistics Value df p-value
Pearson Chi-Square 4.637 5 0.462
Likelihood Ratio Chi-Square 4.916 5 0.426
Null Hypothesis (Ho) : No Browse difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
231
Browse and Q12f
Observed Counts Contact Info Reputation
Never 8 12
Once a month 32 44
Once a week 18 44
Several times a week 17 25
Once a day 3 8
Several times a day 10 5
Expected Counts Contact Info Reputation
Never 7.79 12.21
Once a month 29.59 46.41
Once a week 24.14 37.86
Several times a week 16.35 25.65
Once a day 4.28 6.72
Several times a day 5.84 9.16
Test Statistics Value df p-value
Pearson Chi-Square 8.411 5 0.135
Likelihood Ratio Chi-Square 8.392 5 0.136
Null Hypothesis (Ho) : No Browse difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
232
Browse and Q12g
Observed Counts Price Contact Info
Never 7 13
Once a month 36 40
Once a week 24 38
Several times a week 23 19
Once a day 7 5
Several times a day 5 10
Expected Counts Price Contact Info
Never 8.99 11.01
Once a month 34.15 41.85
Once a week 27.86 34.14
Several times a week 18.87 23.13
Once a day 5.39 6.61
Several times a day 6.74 8.26
Test Statistics Value df p-value
Pearson Chi-Square 5.277 5 0.383
Likelihood Ratio Chi-Square 5.308 5 0.379
Null Hypothesis (Ho) : No Browse difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
233
Browse and Q12h
Observed Counts Prof. Look Reputation
Never 5 15
Once a month 18 58
Once a week 8 54
Several times a week 10 32
Once a day 4 8
Several times a day 3 12
Expected Counts Prof. Look Reputation
Never 4.23 15.77
Once a month 16.07 59.93
Once a week 13.11 48.89
Several times a week 8.88 33.12
Once a day 2.54 9.46
Several times a day 3.17 11.83
Test Statistics Value df p-value
Pearson Chi-Square 4.258 5 0.513
Likelihood Ratio Chi-Square 4.431 5 0.489
Null Hypothesis (Ho) : No Browse difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
234
Browse and 12i
Observed Counts Reputation Price
Never 12 8
Once a month 39 37
Once a week 45 17
Several times a week 24 18
Once a day 3 9
Several times a day 7 8
Expected Counts Reputation Price
Never 11.45 8.55
Once a month 43.52 32.48
Once a week 35.51 26.49
Several times a week 24.05 17.95
Once a day 6.87 5.13
Several times a day 8.59 6.41
Test Statistics Value df p-value
Pearson Chi-Square 12.897 5 0.024
Likelihood Ratio Chi-Square 13.224 5 0.021
Null Hypothesis (Ho) : No Browse difference for Q12i.
The p-value is less than 0.05. Therefore REJECT the Ho.
235
Browse and Q12j
Observed Counts Contact Info Price
Never 11 9
Once a month 43 33
Once a week 31 31
Several times a week 20 22
Once a day 5 7
Several times a day 10 5
Expected Counts Contact Info Price
Never 10.57 9.43
Once a month 40.18 35.82
Once a week 32.78 29.22
Several times a week 22.20 19.80
Once a day 6.34 5.66
Several times a day 7.93 7.07
Test Statistics Value df p-value
Pearson Chi-Square 2.876 5 0.719
Likelihood Ratio Chi-Square 2.904 5 0.715
Null Hypothesis (Ho) : No Browse difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
236
Browse and Q12k
Observed Counts Ease of Use Prof. Look
Never 11 9
Once a month 49 27
Once a week 47 15
Several times a week 30 12
Once a day 6 6
Several times a day 8 7
Expected Counts Ease of Use Prof. Look
Never 13.30 6.70
Once a month 50.56 25.44
Once a week 41.24 20.76
Several times a week 27.94 14.06
Once a day 7.98 4.02
Several times a day 9.98 5.02
Test Statistics Value df p-value
Pearson Chi-Square 6.832 5 0.233
Likelihood Ratio Chi-Square 6.787 5 0.237
Null Hypothesis (Ho) : No Browse difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
237
Browse and Q12l
Observed Counts Price Prof. Look
Never 16 4
Once a month 59 17
Once a week 39 21
Several times a week 35 7
Once a day 8 3
Several times a day 10 5
Expected Counts Price Prof. Look
Never 14.91 5.09
Once a month 55.66 19.34
Once a week 44.73 15.27
Several times a week 31.31 10.69
Once a day 8.20 2.80
Several times a day 11.18 3.82
Test Statistics Value df p-value
Pearson Chi-Square 5.797 5 0.327
Likelihood Ratio Chi-Square 5.764 5 0.330
Null Hypothesis (Ho) : No Browse difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
238
Browse and Q12m
Observed Counts Product Info Ease of Use
Never 11 9
Once a month 48 28
Once a week 35 27
Several times a week 27 15
Once a day 7 5
Several times a day 12 3
Expected Counts Product Info Ease of Use
Never 12.33 7.67
Once a month 46.87 29.13
Once a week 38.24 23.76
Several times a week 25.90 16.10
Once a day 7.40 4.60
Several times a day 9.25 5.75
Test Statistics Value df p-value
Pearson Chi-Square 3.472 5 0.628
Likelihood Ratio Chi-Square 3.666 5 0.598
Null Hypothesis (Ho) : No Browse difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
239
Browse and Q12n
Observed Counts Prof. Look Contact Info
Never 4 16
Once a month 21 55
Once a week 23 39
Several times a week 18 24
Once a day 5 7
Several times a day 4 11
Expected Counts Prof. Look Contact Info
Never 6.61 13.39
Once a month 25.11 50.89
Once a week 20.48 41.52
Several times a week 13.88 28.12
Once a day 3.96 8.04
Several times a day 4.96 10.04
Test Statistics Value df p-value
Pearson Chi-Square 5.512 5 0.357
Likelihood Ratio Chi-Square 5.597 5 0.347
Null Hypothesis (Ho) : No Browse difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
240
Browse and Q12o
Observed Counts Ease of Use Reputation
Never 5 15
Once a month 23 53
Once a week 14 48
Several times a week 15 27
Once a day 6 6
Several times a day 4 11
Expected Counts Ease of Use Reputation
Never 5.90 14.10
Once a month 22.43 53.57
Once a week 18.30 43.70
Several times a week 12.40 29.60
Once a day 3.54 8.46
Several times a day 4.43 10.57
Test Statistics Value df p-value
Pearson Chi-Square 4.904 5 0.428
Likelihood Ratio Chi-Square 4.745 5 0.448
Null Hypothesis (Ho) : No Browse difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
241
Browse and Q13a
Observed Counts Need Price
Never 7 13
Once a month 30 46
Once a week 29 33
Several times a week 25 17
Once a day 5 7
Several times a day 8 7
Expected Counts Need Price
Never 9.16 10.84
Once a month 34.82 41.18
Once a week 28.41 33.59
Several times a week 19.24 22.76
Once a day 5.50 6.50
Several times a day 6.87 8.13
Test Statistics Value df p-value
Pearson Chi-Square 5.801 5 0.326
Likelihood Ratio Chi-Square 5.823 5 0.324
Null Hypothesis (Ho) : No Browse difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
242
Browse and Q13b
Observed Counts Ease of Use Need
Never 7 13
Once a month 38 38
Once a week 25 37
Several times a week 14 28
Once a day 2 9
Several times a day 5 10
Expected Counts Ease of Use Need
Never 8.05 11.95
Once a month 30.60 45.40
Once a week 24.96 37.04
Several times a week 16.91 25.09
Once a day 4.43 6.57
Several times a day 6.04 8.96
Test Statistics Value df p-value
Pearson Chi-Square 6.594 5 0.253
Likelihood Ratio Chi-Square 6.818 5 0.235
Null Hypothesis (Ho) : No Browse difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
243
Browse and Q13c
Observed Counts Need Reputation
Never 6 14
Once a month 25 51
Once a week 21 41
Several times a week 23 19
Once a day 4 8
Several times a day 7 8
Expected Counts Need Reputation
Never 7.58 12.42
Once a month 28.79 47.21
Once a week 23.49 38.51
Several times a week 15.91 26.09
Once a day 4.55 7.45
Several times a day 5.68 9.32
Test Statistics Value df p-value
Pearson Chi-Square 7.438 5 0.190
Likelihood Ratio Chi-Square 7.285 5 0.200
Null Hypothesis (Ho) : No Browse difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
244
Browse and Q13d
Observed Counts Prof. Look Need
Never 7 13
Once a month 27 49
Once a week 21 41
Several times a week 13 29
Once a day 4 8
Several times a day 5 10
Expected Counts Prof. Look Need
Never 6.78 13.22
Once a month 25.78 50.22
Once a week 21.03 40.97
Several times a week 14.25 27.75
Once a day 4.07 7.93
Several times a day 5.09 9.91
Test Statistics Value df p-value
Pearson Chi-Square 0.267 5 0.998
Likelihood Ratio Chi-Square 0.269 5 0.998
Null Hypothesis (Ho) : No Browse difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
245
Browse and Q13e
Observed Counts Contact Info Need
Never 10 10
Once a month 50 26
Once a week 34 28
Several times a week 19 23
Once a day 6 6
Several times a day 5 10
Expected Counts Contact Info Need
Never 10.93 9.07
Once a month 41.52 34.48
Once a week 33.87 28.13
Several times a week 22.94 19.06
Once a day 6.56 5.44
Several times a day 8.19 6.81
Test Statistics Value df p-value
Pearson Chi-Square 8.336 5 0.139
Likelihood Ratio Chi-Square 8.427 5 0.134
Null Hypothesis (Ho) : No Browse difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
246
Browse and Q13f
Observed Counts Product Info Need
Never 13 7
Once a month 46 30
Once a week 34 28
Several times a week 23 19
Once a day 4 8
Several times a day 4 11
Expected Counts Product Info Need
Never 10.93 9.07
Once a month 41.52 34.48
Once a week 33.87 28.13
Several times a week 22.94 19.06
Once a day 6.56 5.44
Several times a day 8.19 6.81
Test Statistics Value df p-value
Pearson Chi-Square 8.863 5 0.115
Likelihood Ratio Chi-Square 8.996 5 0.109
Null Hypothesis (Ho) : No Browse difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
247
A.9 Purchase
Purchase and Q12a
Observed Counts Reputation Product Info
Never 36 21
Once a month 95 46
Once a week 17 6
Expected Counts Reputation Product Info
Never 38.17 18.83
Once a month 94.43 46.57
Once a week 15.40 7.60
Test Statistics Value df p-value
Pearson Chi-Square 0.886 2 0.642
Likelihood Ratio Chi-Square 0.900 2 0.637
Null Hypothesis (Ho) : No Purchase difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
248
Purchase and Q12b
Observed Counts Product Info Contact Info
Never 20 37
Once a month 58 83
Once a week 9 14
Expected Counts Product Info Contact Info
Never 22.44 34.56
Once a month 55.51 85.49
Once a week 9.05 13.95
Test Statistics Value df p-value
Pearson Chi-Square 0.622 2 0.733
Likelihood Ratio Chi-Square 0.628 2 0.731
Null Hypothesis (Ho) : No Purchase difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
249
Purchase and Q12c
Observed Counts Price Product Info
Never 39 18
Once a month 84 56
Once a week 12 10
Expected Counts Price Product Info
Never 35.14 21.86
Once a month 86.30 53.70
Once a week 13.56 8.44
Test Statistics Value df p-value
Pearson Chi-Square 1.736 2 0.420
Likelihood Ratio Chi-Square 1.756 2 0.416
Null Hypothesis (Ho) : No Purchase difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
250
Purchase and Q12d
Observed Counts Ease of Use Price
Never 28 29
Once a month 75 66
Once a week 8 15
Expected Counts Ease of Use Price
Never 28.63 28.37
Once a month 70.82 70.18
Once a week 11.55 11.45
Test Statistics Value df p-value
Pearson Chi-Square 2.718 2 0.257
Likelihood Ratio Chi-Square 2.752 2 0.253
Null Hypothesis (Ho) : No Purchase difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
251
Purchase and Q12e
Observed Counts Prof. Look Product Info
Never 16 41
Once a month 56 85
Once a week 10 12
Expected Counts Prof. Look Product Info
Never 21.25 35.75
Once a month 52.55 88.45
Once a week 8.20 13.80
Test Statistics Value df p-value
Pearson Chi-Square 3.055 2 0.217
Likelihood Ratio Chi-Square 3.123 2 0.210
Null Hypothesis (Ho) : No Purchase difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
252
Purchase and Q12f
Observed Counts Contact Info Reputation
Never 26 31
Once a month 48 92
Once a week 10 13
Expected Counts Contact Info Reputation
Never 21.76 35.24
Once a month 53.45 86.55
Once a week 8.78 14.22
Test Statistics Value df p-value
Pearson Chi-Square 2.508 2 0.285
Likelihood Ratio Chi-Square 2.489 2 0.288
Null Hypothesis (Ho) : No Purchase difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
253
Purchase and Q12g
Observed Counts Price Contact Info
Never 25 32
Once a month 65 76
Once a week 9 14
Expected Counts Price Contact Info
Never 25.53 31.47
Once a month 63.16 77.84
Once a week 10.30 12.70
Test Statistics Value df p-value
Pearson Chi-Square 0.416 2 0.812
Likelihood Ratio Chi-Square 0.419 2 0.811
Null Hypothesis (Ho) : No Purchase difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
254
Purchase and Q12h
Observed Counts Prof. Look Reputation
Never 13 44
Once a month 27 114
Once a week 4 19
Expected Counts Prof. Look Reputation
Never 11.35 45.65
Once a month 28.07 112.93
Once a week 4.58 18.42
Test Statistics Value df p-value
Pearson Chi-Square 0.443 2 0.801
Likelihood Ratio Chi-Square 0.436 2 0.804
Null Hypothesis (Ho) : No Purchase difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
255
Purchase and Q12i
Observed Counts Reputation Price
Never 28 29
Once a month 84 57
Once a week 15 8
Expected Counts Reputation Price
Never 32.76 24.24
Once a month 81.03 59.97
Once a week 13.22 9.78
Test Statistics Value df p-value
Pearson Chi-Square 2.445 2 0.294
Likelihood Ratio Chi-Square 2.438 2 0.295
Null Hypothesis (Ho) : No Purchase difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
256
Purchase and Q12j
Observed Counts Contact Info Ease of Use
Never 33 24
Once a month 73 68
Once a week 10 13
Expected Counts Contact Info Ease of Use
Never 29.92 27.08
Once a month 74.01 66.99
Once a week 12.07 10.93
Test Statistics Value df p-value
Pearson Chi-Square 1.446 2 0.485
Likelihood Ratio Chi-Square 1.449 2 0.485
Null Hypothesis (Ho) : No Purchase difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
257
Purchase and Q12k
Observed Counts Ease of Use Prof. Look
Never 31 26
Once a month 104 37
Once a week 11 12
Expected Counts Ease of Use Prof. Look
Never 37.66 19.34
Once a month 93.15 47.85
Once a week 15.19 7.81
Test Statistics Value df p-value
Pearson Chi-Square 10.603 2 0.005
Likelihood Ratio Chi-Square 10.422 2 0.005
Null Hypothesis (Ho) : No Purchase difference for Q12k.
The p-value is less than 0.05. Therefore REJECT the Ho.
258
Purchase and Q12l
Observed Counts Price Prof. Look
Never 45 11
Once a month 104 35
Once a week 13 10
Expected Counts Price Prof. Look
Never 41.61 14.39
Once a month 103.29 35.71
Once a week 17.09 5.91
Test Statistics Value df p-value
Pearson Chi-Square 4.904 2 0.086
Likelihood Ratio Chi-Square 4.656 2 0.102
Null Hypothesis (Ho) : No Purchase difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
259
Purchase and Q12m
Observed Counts Product Info Ease of Use
Never 29 28
Once a month 95 46
Once a week 13 10
Expected Counts Product Info Ease of Use
Never 35.33 21.67
Once a month 87.41 53.59
Once a week 14.26 8.74
Test Statistics Value df p-value
Pearson Chi-Square 5.015 2 0.081
Likelihood Ratio Chi-Square 4.964 2 0.084
Null Hypothesis (Ho) : No Purchase difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
260
Purchase and Q12n
Observed Counts Prof. Look Contact Info
Never 14 43
Once a month 46 95
Once a week 11 12
Expected Counts Prof. Look Contact Info
Never 18.31 38.69
Once a month 45.30 95.70
Once a week 7.39 15.61
Test Statistics Value df p-value
Pearson Chi-Square 4.112 2 0.128
Likelihood Ratio Chi-Square 4.026 2 0.134
Null Hypothesis (Ho) : No Purchase difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
261
Purchase and Q12o
Observed Counts Ease of Use Reputation
Never 18 39
Once a month 36 105
Once a week 7 16
Expected Counts Ease of Use Reputation
Never 15.73 41.27
Once a month 38.92 102.08
Once a week 6.35 16.65
Test Statistics Value df p-value
Pearson Chi-Square 0.846 2 0.655
Likelihood Ratio Chi-Square 0.837 2 0.658
Null Hypothesis (Ho) : No Purchase difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
262
Purchase and Q13a
Observed Counts Need Price
Never 23 34
Once a month 66 75
Once a week 12 11
Expected Counts Need Price
Never 26.05 30.95
Once a month 64.44 76.56
Once a week 10.51 12.49
Test Statistics Value df p-value
Pearson Chi-Square 1.116 2 0.572
Likelihood Ratio Chi-Square 1.119 2 0.571
Null Hypothesis (Ho) : No Purchase difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
263
Purchase and Q13b
Observed Counts Ease of Use Need
Never 19 38
Once a month 60 80
Once a week 9 14
Expected Counts Ease of Use Need
Never 22.80 34.20
Once a month 56.00 84.00
Once a week 9.20 13.80
Test Statistics Value df p-value
Pearson Chi-Square 1.539 2 0.463
Likelihood Ratio Chi-Square 1.559 2 0.459
Null Hypothesis (Ho) : No Purchase difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
264
Purchase and Q13c
Observed Counts Need Reputation
Never 18 39
Once a month 58 83
Once a week 9 14
Expected Counts
Never 21.92 35.08
Once a month 54.23 86.77
Once a week 8.85 14.15
Test Statistics Value df p-value
Pearson Chi-Square 1.571 2 0.456
Likelihood Ratio Chi-Square 1.598 2 0.450
Null Hypothesis (Ho) : No Purchase difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
265
Purchase and Q13d
Observed Counts Prof. Look Need
Never 22 35
Once a month 39 102
Once a week 11 12
Expected Counts Prof. Look Need
Never 18.57 38.43
Once a month 45.94 95.06
Once a week 7.49 15.51
Test Statistics Value df p-value
Pearson Chi-Square 4.927 2 0.085
Likelihood Ratio Chi-Square 4.805 2 0.090
Null Hypothesis (Ho) : No Purchase difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
266
Purchase and Q13e
Observed Counts Contact Info Need
Never 32 25
Once a month 75 66
Once a week 12 11
Expected Counts Contact Info Need
Never 30.69 26.31
Once a month 75.92 65.08
Once a week 12.38 10.62
Test Statistics Value df p-value
Pearson Chi-Square 0.171 2 0.918
Likelihood Ratio Chi-Square 0.1717 2 0.918
Null Hypothesis (Ho) : No Purchase difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
267
Purchase and Q13f
Observed Counts Product Info Need
Never 32 25
Once a month 78 63
Once a week 11 12
Expected Counts Product Info Need
Never 31.21 25.79
Once a month 77.20 63.80
Once a week 12.59 10.41
Test Statistics Value df p-value
Pearson Chi-Square 0.508 2 0.776
Likelihood Ratio Chi-Square 0.506 2 0.777
Null Hypothesis (Ho) : No Purchase difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
268
A.10 Expensive
Expensive and Q12a
Observed Counts Reputation Product Info
$10 or less 13 12
$50 or less 27 12
$100 or less 44 22
$500 or less 42 13
Over $500 25 17
Expected Counts Reputation Product Info
$10 or less 16.63 8.37
$50 or less 25.94 13.06
$100 or less 43.90 22.10
$500 or less 36.59 18.41
Over $500 27.94 14.06
Test Statistics Value df p-value
Pearson Chi-Square 5.812 4 0.214
Likelihood Ratio Chi-Square 5.810 4 0.214
Null Hypothesis (Ho) : No Expensive difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
269
Expensive and Q12b
Observed Counts Product Info Contact Info
$10 or less 9 16
$50 or less 15 24
$100 or less 24 42
$500 or less 24 31
Over $500 19 23
Expected Counts Product Info Contact Info
$10 or less 10.02 14.98
$50 or less 15.63 23.37
$100 or less 26.46 39.54
$500 or less 22.05 32.95
Over $500 16.84 25.16
Test Statistics Value df p-value
Pearson Chi-Square 1.350 4 0.853
Likelihood Ratio Chi-Square 1.349 4 0.853
Null Hypothesis (Ho) : No Expensive difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
270
Expensive and Q12c
Observed Counts Price Product Info
$10 or less 15 10
$50 or less 25 13
$100 or less 35 31
$500 or less 34 20
Over $500 27 15
Expected Counts Price Product Info
$10 or less 15.11 9.89
$50 or less 22.97 15.03
$100 or less 39.89 26.11
$500 or less 32.64 21.36
Over $500 25.39 16.61
Test Statistics Value df p-value
Pearson Chi-Square 2.376 4 0.667
Likelihood Ratio Chi-Square 2.362 4 0.669
Null Hypothesis (Ho) : No Expensive difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
271
Expensive and Q12d
Observed Counts Ease of Use Price
$10 or less 12 13
$50 or less 21 18
$100 or less 37 29
$500 or less 22 33
Over $500 24 18
Expected Counts Ease of Use Price
$10 or less 12.78 12.22
$50 or less 19.93 19.07
$100 or less 33.73 32.27
$500 or less 28.11 26.89
Over $500 21.46 20.54
Test Statistics Value df p-value
Pearson Chi-Square 4.190 4 0.381
Likelihood Ratio Chi-Square 4.208 4 0.379
Null Hypothesis (Ho) : No Expensive difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
272
Expensive and Q12e
Observed Counts Prof. Look Product Info
$10 or less 10 15
$50 or less 10 29
$100 or less 30 36
$500 or less 20 35
Over $500 15 26
Expected Counts Prof. Look Product Info
$10 or less 9.40 15.60
$50 or less 14.67 24.33
$100 or less 24.82 41.18
$500 or less 20.69 34.31
Over $500 15.42 25.58
Test Statistics Value df p-value
Pearson Chi-Square 4.227 4 0.376
Likelihood Ratio Chi-Square 4.325 4 0.364
Null Hypothesis (Ho) : No Expensive difference for Q12e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
273
Expensive and Q12f
Observed Counts Contact Info Reputation
$10 or less 13 12
$50 or less 16 23
$100 or less 26 40
$500 or less 19 35
Over $500 14 28
Expected Counts Contact Info Reputation
$10 or less 9.73 15.27
$50 or less 15.19 23.81
$100 or less 25.70 40.30
$500 or less 21.03 32.97
Over $500 16.35 25.65
Test Statistics Value df p-value
Pearson Chi-Square 2.746 4 0.601
Likelihood Ratio Chi-Square 2.711 4 0.607
Null Hypothesis (Ho) : No Expensive difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
274
Expensive and Q12g
Observed Counts Contact Info Reputation
$10 or less 10 15
$50 or less 20 19
$100 or less 30 36
$500 or less 23 32
Over $500 19 23
Expected Counts Contact Info Reputation
$10 or less 11.23 13.77
$50 or less 17.52 21.48
$100 or less 29.66 36.34
$500 or less 24.71 30.29
Over $500 18.87 23.13
Test Statistics Value df p-value
Pearson Chi-Square 1.106 4 0.893
Likelihood Ratio Chi-Square 1.105 4 0.893
Null Hypothesis (Ho) : No Expensive difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
275
Expensive and Q12h
Observed Counts Prof. Look Reputation
$10 or less 7 18
$50 or less 9 30
$100 or less 14 52
$500 or less 7 48
Over $500 11 31
Expected Counts Prof. Look Reputation
$10 or less 5.29 19.71
$50 or less 8.25 30.75
$100 or less 13.96 52.04
$500 or less 11.63 43.37
Over $500 8.88 33.12
Test Statistics Value df p-value
Pearson Chi-Square 3.771 4 0.438
Likelihood Ratio Chi-Square 3.981 4 0.409
Null Hypothesis (Ho) : No Expensive difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
276
Expensive and Q12i
Observed Counts Reputation Price
$10 or less 14 11
$50 or less 20 19
$100 or less 36 30
$500 or less 37 18
Over $500 23 19
Expected Counts Reputation Price
$10 or less 14.32 10.68
$50 or less 22.33 16.67
$100 or less 37.80 28.20
$500 or less 31.50 23.50
Over $500 24.05 17.95
Test Statistics Value df p-value
Pearson Chi-Square 3.145 4 0.534
Likelihood Ratio Chi-Square 3.201 4 0.525
Null Hypothesis (Ho) : No Expensive difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
277
Expensive and Q12j
Observed Counts Contact Info Price
$10 or less 19 6
$50 or less 23 16
$100 or less 36 30
$500 or less 23 32
Over $500 19 23
Expected Counts Contact Info Price
$10 or less 13.22 11.78
$50 or less 20.62 18.38
$100 or less 34.89 31.11
$500 or less 29.07 25.93
Over $500 22.20 19.80
Test Statistics Value df p-value
Pearson Chi-Square 9.703 4 0.046
Likelihood Ratio Chi-Square 10.029 4 0.040
Null Hypothesis (Ho) : No Expensive difference for Q12j.
The p-value is less than 0.05. Therefore do REJECT the Ho.
278
Expensive and Q12k
Observed Counts Ease of Use Prof. Look
$10 or less 12 13
$50 or less 23 16
$100 or less 45 21
$500 or less 42 13
Over $500 29 13
Expected Counts Ease of Use Prof. Look
$10 or less 16.63 8.37
$50 or less 25.94 13.06
$100 or less 43.90 22.10
$500 or less 36.59 18.41
Over $500 27.94 14.06
Test Statistics Value df p-value
Pearson Chi-Square 7.443 4 0.114
Likelihood Ratio Chi-Square 7.327 4 0.120
Null Hypothesis (Ho) : No Expensive difference for Q12k.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
279
Expensive and Q12l
Observed Counts Price Prof. Look
N$10 or less 21 3
$50 or less 28 11
$100 or less 43 23
$500 or less 45 8
Over $500 30 12
Expected Counts Price Prof. Look
$10 or less 17.89 6.11
$50 or less 29.08 9.92
$100 or less 49.21 16.79
$500 or less 39.51 13.49
Over $500 31.31 10.69
Test Statistics Value df p-value
Pearson Chi-Square 8.562 4 0.073
Likelihood Ratio Chi-Square 9.041 4 0.060
Null Hypothesis (Ho) : No Expensive difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
280
Expensive and Q12m
Observed Counts Product Info Ease of Use
$10 or less 18 7
$50 or less 22 17
$100 or less 38 28
$500 or less 33 22
Over $500 29 13
Expected Counts Product Info Ease of Use
$10 or less 15.42 9.58
$50 or less 24.05 14.95
$100 or less 40.70 25.30
$500 or less 33.92 21.08
Over $500 25.90 16.10
Test Statistics Value df p-value
Pearson Chi-Square 3.085 4 0.544
Likelihood Ratio Chi-Square 3.151 4 0.533
Null Hypothesis (Ho) : No Expensive difference for Q12m.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
281
Expensive and Q12n
Observed Counts Prof. Look Contact Info
$10 or less 3 22
$50 or less 14 25
$100 or less 23 43
$500 or less 17 38
Over $500 18 24
Expected Counts Prof. Look Contact Info
$10 or less 8.26 16.74
$50 or less 12.89 26.11
$100 or less 21.81 44.19
$500 or less 18.17 36.83
Over $500 13.88 28.12
Test Statistics Value df p-value
Pearson Chi-Square 7.186 4 0.126
Likelihood Ratio Chi-Square 8.054 4 0.090
Null Hypothesis (Ho) : No Expensive difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
282
Expensive and Q12o
Observed Counts Ease of Use Reputation
$10 or less 7 18
$50 or less 10 29
$100 or less 21 45
$500 or less 14 41
Over $500 15 27
Expected Counts Ease of Use Reputation
$10 or less 7.38 17.62
$50 or less 11.51 27.49
$100 or less 19.48 46.52
$500 or less 16.23 38.77
Over $500 12.40 29.60
Test Statistics Value df p-value
Pearson Chi-Square 1.689 4 0.793
Likelihood Ratio Chi-Square 1.680 4 0.794
Null Hypothesis (Ho) : No Expensive difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
283
Expensive and Q13a
Observed Counts Need Price
$10 or less 10 15
$50 or less 13 26
$100 or less 27 39
$500 or less 28 27
Over $500 26 16
Expected Counts Need Price
$10 or less 11.45 13.55
$50 or less 17.87 21.13
$100 or less 30.24 35.76
$500 or less 25.20 29.80
Over $500 19.24 22.76
Test Statistics Value df p-value
Pearson Chi-Square 8.383 4 0.079
Likelihood Ratio Chi-Square 8.448 4 0.076
Null Hypothesis (Ho) : No Expensive difference for Q13a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
284
Expensive and Q13b
Observed Counts Ease of Use Need
$10 or less 10 15
$50 or less 16 23
$100 or less 26 39
$500 or less 23 32
Over $500 16 26
Expected Counts Ease of Use Need
$10 or less 10.07 14.93
$50 or less 15.70 23.30
$100 or less 26.17 38.83
$500 or less 22.15 32.85
Over $500 16.91 25.09
Test Statistics Value df p-value
Pearson Chi-Square 0.149 4 0.997
Likelihood Ratio Chi-Square 0.150 4 0.997
Null Hypothesis (Ho) : No Expensive difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
285
Expensive and Q13c
Observed Counts Need Reputation
$10 or less 8 17
$50 or less 13 26
$100 or less 23 43
$500 or less 23 32
Over $500 19 23
Expected Counts Need Reputation
$10 or less 9.47 15.53
$50 or less 14.78 24.22
$100 or less 25.00 41.00
$500 or less 20.84 34.16
Over $500 15.91 26.09
Test Statistics Value df p-value
Pearson Chi-Square 2.296 4 0.681
Likelihood Ratio Chi-Square 2.290 4 0.683
Null Hypothesis (Ho) : No Expensive difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
286
Expensive and Q13d
Observed Counts Prof. Look Need
$10 or less 9 16
$50 or less 17 22
$100 or less 23 43
$500 or less 16 39
Over $500 12 30
Expected Counts Prof. Look Need
$10 or less 8.48 16.52
$50 or less 13.23 25.77
$100 or less 22.39 43.61
$500 or less 18.66 36.34
Over $500 14.25 27.75
Test Statistics Value df p-value
Pearson Chi-Square 2.809 4 0.590
Likelihood Ratio Chi-Square 2.778 4 0.596
Null Hypothesis (Ho) : No Expensive difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
287
Expensive and Q13e
Observed Counts Contact Info Need
$10 or less 14 11
$50 or less 29 10
$100 or less 37 29
$500 or less 28 27
Over $500 16 26
Expected Counts Contact Info Need
$10 or less 13.66 11.34
$50 or less 21.30 17.70
$100 or less 36.05 29.95
$500 or less 30.04 24.96
Over $500 22.94 19.06
Test Statistics Value df p-value
Pearson Chi-Square 11.138 4 0.025
Likelihood Ratio Chi-Square 11.472 4 0.022
Null Hypothesis (Ho) : No Expensive difference for Q13e.
The p-value is less than 0.05. Therefore REJECT the Ho.
288
Expensive and Q13f
Observed Counts Product Info Need
$10 or less 14 11
$50 or less 27 12
$100 or less 29 37
$500 or less 33 22
Over $500 21 21
Expected Counts Product Info Need
$10 or less 13.66 11.34
$50 or less 21.30 17.70
$100 or less 36.05 29.95
$500 or less 30.04 24.96
Over $500 22.94 19.06
Test Statistics Value df p-value
Pearson Chi-Square 7.420 4 0.115
Likelihood Ratio Chi-Square 7.523 4 0.111
Null Hypothesis (Ho) : No Expensive difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
289
A.11 Experience
Experience and Q12a
Observed Counts Reputation Product Info
Yes, definitely 91 39
Somewhat 45 30
No, not at all 6 6
Expected Counts Reputation Product Info
Yes, definitely 85.07 44.93
Somewhat 49.08 25.92
No, not at all 7.85 4.15
Test Statistics Value df p-value
Pearson Chi-Square 3.441 2 0.179
Likelihood Ratio Chi-Square 3.385 2 0.184
Null Hypothesis (Ho) : No Experience difference for Q12a.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
290
Experience and Q12b
Observed Counts Product Info Contact Info
Yes, definitely 48 82
Somewhat 34 41
No, not at all 6 6
Expected Counts Product Info Contact Info
Yes, definitely 52.72 77.28
Somewhat 30.41 44.59
No, not at all 4.87 7.13
Test Statistics Value df p-value
Pearson Chi-Square 1.866 2 0.393
Likelihood Ratio Chi-Square 1.858 2 0.395
Null Hypothesis (Ho) : No Experience difference for Q12b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
291
Experience and Q12c
Observed Counts Price Product Info
Yes, definitely 77 53
Somewhat 47 26
No, not at all 6 6
Expected Counts Price Product Info
Yes, definitely 78.60 51.40
Somewhat 44.14 28.86
No, not at all 7.26 4.74
Test Statistics Value df p-value
Pearson Chi-Square 1.102 2 0.577
Likelihood Ratio Chi-Square 1.095 2 0.578
Null Hypothesis (Ho) : No Experience difference for Q12c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
292
Experience and Q12d
Observed Counts Ease of Use Price
Yes, definitely 63 67
Somewhat 37 38
No, not at all 10 2
Expected Counts Ease of Use Price
Yes, definitely 65.90 64.10
Somewhat 38.02 36.98
No, not at all 6.08 5.92
Test Statistics Value df p-value
Pearson Chi-Square 5.429 2 0.066
Likelihood Ratio Chi-Square 5.917 2 0.052
Null Hypothesis (Ho) : No Experience difference for Q12d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
293
Experience and Q12e
Observed Counts Prof. Look Product Info
Yes, definitely 61 69
Somewhat 19 55
No, not at all 2 10
Expected Counts Prof. Look Product Info
Yes, definitely 49.35 80.65
Somewhat 28.09 45.91
No, not at all 4.56 7.44
Test Statistics Value df p-value
Pearson Chi-Square 11.486 2 0.003
Likelihood Ratio Chi-Square 11.952 2 0.003
Null Hypothesis (Ho) : No Experience difference for Q12e.
The p-value is less than 0.05. Therefore REJECT the Ho.
294
Experience and Q12f
Observed Counts Contact Info Reputation
Yes, definitely 48 82
Somewhat 29 45
No, not at all 8 4
Expected Counts Contact Info Reputation
Yes, definitely 51.16 78.84
Somewhat 29.12 44.88
No, not at all 4.72 7.28
Test Statistics Value df p-value
Pearson Chi-Square 4.074 2 0.130
Likelihood Ratio Chi-Square 3.971 2 0.137
Null Hypothesis (Ho) : No Experience difference for Q12f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
295
Experience and Q12g
Observed Counts Price Contact Info
Yes, definitely 61 69
Somewhat 36 39
No, not at all 3 9
Expected Counts Price Contact Info
Yes, definitely 59.91 70.09
Somewhat 34.56 40.44
No, not at all 5.53 6.47
Test Statistics Value df p-value
Pearson Chi-Square 2.295 2 0.317
Likelihood Ratio Chi-Square 2.419 2 0.298
Null Hypothesis (Ho) : No Experience difference for Q12g.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
296
Experience and Q12h
Observed Counts Prof. Look Reputation
Yes, definitely 29 101
Somewhat 14 61
No, not at all 4 8
Expected Counts Prof. Look Reputation
Yes, definitely 28.16 101.84
Somewhat 16.24 58.76
No, not at all 2.60 9.40
Test Statistics Value df p-value
Pearson Chi-Square 1.392 2 0.499
Likelihood Ratio Chi-Square 1.309 2 0.520
Null Hypothesis (Ho) : No Experience difference for Q12h.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
297
Experience and Q12i
Observed Counts Reputation Price
Yes, definitely 80 50
Somewhat 37 38
No, not at all 6 6
Expected Counts Reputation Price
Yes, definitely 73.69 56.31
Somewhat 42.51 32.49
No, not at all 6.80 5.20
Test Statistics Value df p-value
Pearson Chi-Square 3.116 2 0.211
Likelihood Ratio Chi-Square 3.112 2 0.211
Null Hypothesis (Ho) : No Experience difference for Q12i.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
298
Experience and Q12j
Observed Counts Contact Info Ease of Use
Yes, definitely 68 62
Somewhat 39 36
No, not at all 7 5
Expected Counts Contact Info Ease of Use
Yes, definitely 68.29 61.71
Somewhat 39.40 35.60
No, not at all 6.30 5.70
Test Statistics Value df p-value
Pearson Chi-Square 0.173 2 0.917
Likelihood Ratio Chi-Square 0.174 2 0.917
Null Hypothesis (Ho) : No Experience difference for Q12j.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
299
Experience and Q12k
Observed Counts Ease of Use Prof. Look
Yes, definitely 93 37
Somewhat 41 34
No, not at all 11 1
Expected Counts Ease of Use Prof. Look
Yes, definitely 86.87 43.13
Somewhat 50.12 24.88
No, not at all 8.02 3.98
Test Statistics Value df p-value
Pearson Chi-Square 9.463 2 0.008
Likelihood Ratio Chi-Square 10.293 2 0.006
Null Hypothesis (Ho) : No Experience difference for Q12k.
The p-value is less than 0.05. Therefore REJECT the Ho.
300
Experience and Q12l
Observed Counts Price Prof. Look
Yes, definitely 94 36
Somewhat 52 20
No, not at all 11 1
Expected Counts Price Prof. Look
Yes, definitely 95.37 34.63
Somewhat 52.82 19.18
No, not at all 8.80 3.20
Test Statistics Value df p-value
Pearson Chi-Square 2.179 2 0.336
Likelihood Ratio Chi-Square 2.697 2 0.260
Null Hypothesis (Ho) : No Experience difference for Q12l.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
301
Experience and Q12m
Observed Counts Product Info Ease of Use
Yes, definitely 88 42
Somewhat 36 39
No, not at all 8 4
Expected Counts Product Info Ease of Use
Yes, definitely 79.08 50.92
Somewhat 45.62 29.38
No, not at all 7.30 4.70
Test Statistics Value df p-value
Pearson Chi-Square 7.922 2 0.019
Likelihood Ratio Chi-Square 7.853 2 0.020
Null Hypothesis (Ho) : No Experience difference for Q12m.
The p-value is less than 0.05. Therefore do REJECT the Ho.
302
Experience and Q12n
Observed Counts Prof. Look Contact Info
Yes, definitely 47 83
Somewhat 26 49
No, not at all 1 11
Expected Counts Prof. Look Contact Info
Yes, definitely 44.33 85.67
Somewhat 25.58 49.42
No, not at all 4.09 7.91
Test Statistics Value df p-value
Pearson Chi-Square 3.800 2 0.150
Likelihood Ratio Chi-Square 4.695 2 0.096
Null Hypothesis (Ho) : No Experience difference for Q12n.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
303
Experience and Q12o
Observed Counts Ease of Use Reputation
Yes, definitely 36 94
Somewhat 27 48
No, not at all 3 9
Expected Counts Ease of Use Reputation
Yes, definitely 39.54 90.46
Somewhat 22.81 52.19
No, not at all 3.65 8.35
Test Statistics Value df p-value
Pearson Chi-Square 1.727 2 0.422
Likelihood Ratio Chi-Square 1.708 2 0.426
Null Hypothesis (Ho) : No Experience difference for Q12o.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
304
Experience and Q13a
Observed Counts Need Price
Yes, definitely 70 60
Somewhat 25 50
No, not at all 3 9
Expected Counts Need Price
Yes, definitely 58.71 71.29
Somewhat 33.87 41.13
No, not at all 5.42 6.58
Test Statistics Value df p-value
Pearson Chi-Square 10.166 2 0.006
Likelihood Ratio Chi-Square 10.369 2 0.006
Null Hypothesis (Ho) : No Experience difference for Q13a.
The p-value is less than 0.05. Therefore REJECT the Ho.
305
Experience and Q13b
Observed Counts Ease of Use Need
Yes, definitely 47 83
Somewhat 35 39
No, not at all 6 6
Expected Counts Ease of Use Need
Yes, definitely 52.96 77.04
Somewhat 30.15 43.85
No, not at all 4.89 7.11
Test Statistics Value df p-value
Pearson Chi-Square 2.877 2 0.237
Likelihood Ratio Chi-Square 2.867 2 0.239
Null Hypothesis (Ho) : No Experience difference for Q13b.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
306
Experience and Q13c
Observed Counts Need Reputation
Yes, definitely 54 76
Somewhat 26 49
No, not at all 4 8
Expected Counts Need Reputation
Yes, definitely 50.32 79.68
Somewhat 29.03 45.97
No, not at all 4.65 7.35
Test Statistics Value df p-value
Pearson Chi-Square 1.101 2 0.577
Likelihood Ratio Chi-Square 1.108 2 0.575
Null Hypothesis (Ho) : No Experience difference for Q13c.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
307
Experience and Q13d
Observed Counts Prof. Look Need
Yes, definitely 38 92
Somewhat 29 46
No, not at all 7 5
Expected Counts Prof. Look Need
Yes, definitely 44.33 85.67
Somewhat 25.58 49.42
No, not at all 4.09 7.91
Test Statistics Value df p-value
Pearson Chi-Square 5.203 2 0.074
Likelihood Ratio Chi-Square 5.021 2 0.081
Null Hypothesis (Ho) : No Experience difference for Q13d.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
308
Experience and Q13e
Observed Counts Contact Info Need
Yes, definitely 67 63
Somewhat 42 33
No, not at all 9 3
Expected Counts Contact Info Need
Yes, definitely 70.69 59.31
Somewhat 40.78 34.22
No, not at all 6.53 5.47
Test Statistics Value df p-value
Pearson Chi-Square 2.559 2 0.278
Likelihood Ratio Chi-Square 2.679 2 0.262
Null Hypothesis (Ho) : No Experience difference for Q13e.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
309
Experience and Q13f
Observed Counts Product Info Need
Yes, definitely 65 65
Somewhat 45 30
No, not at all 8 4
Expected Counts Product Info Need
Yes, definitely 70.69 59.31
Somewhat 40.78 34.22
No, not at all 6.53 5.47
Test Statistics Value df p-value
Pearson Chi-Square 2.690 2 0.260
Likelihood Ratio Chi-Square 2.714 2 0.257
Null Hypothesis (Ho) : No Experience difference for Q13f.
The p-value is greater than 0.05. Therefore do NOT reject the Ho.
310
A.12 Contingency Tables
Question 12a
Reputation Product Info Total
Observed (O) 151 76 227
Expected (E) 113.5 113.5 227
(O - E) 37.5 -37.5
(O - E)2 1406.250 1406.250
(O - E)2 / E 12.390 12.390
Chi Squared Calculated 24.78
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Reputation and Product Info
311
Question 12b
Product Info Contact Info Total
Observed (O) 91 136 227
Expected (E) 113.5 113.5 227
(O - E) -22.5 22.5
(O - E)2 506.250 506.250
(O - E)2 / E 4.460 4.460
Chi Squared Calculated 8.92
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Product Info and Contact Info
312
Question 12c
Price Product Info Total
Observed (O) 136 89 225
Expected (E) 112.5 112.5 225
(O - E) 23.5 -23.5
(O - E)2 552.250 552.250
(O - E)2 / E 4.909 4.909
Chi Squared Calculated 9.82
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Price and Product Info
313
Question 12d
Ease of Use Price Total
Observed (O) 116 111 227
Expected (E) 113.5 113.5
(O - E) 2.5 -2.5
(O - E)2 6.250 6.250
(O - E)2 / E 0.055 0.055
Chi Squared Calculated 0.11
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Ease of Use and Price
314
Question 12e
Prof. Look Product Info Total
Observed (O) 85 141 226
Expected (E) 113 113 226
(O - E) -28 28
(O - E)2 784.000 784.000
(O - E)2 / E 6.938 6.938
Chi Squared Calculated 13.88
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Prof. Look and Product Info
315
Question 12f
Contact Info Reputation Total
Observed (O) 88 138 226
Expected (E) 113 113 226
(O - E) -25 25
(O - E)2 625.000 625.000
(O - E)2 / E 5.531 5.531
Chi Squared Calculated 11.06
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Contact Info and Reputation
316
Question 12g
Price Contact Info Total
Observed (O) 102 125 227
Expected (E) 113.5 113.5 227
(O - E) -11.5 11.5
(O - E)2 132.250 132.250
(O - E)2 / E 1.165 1.165
Chi Squared Calculated 2.33
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Price and Contact Info
317
Question 12h
Prof. Look Reputation Total
Observed (O) 48 179 227
Expected (E) 113.5 113.5 227
(O - E) -65.5 65.5
(O - E)2 4290.250 4290.250
(O - E)2 / E 37.800 37.800
Chi Squared Calculated 75.60
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Prof. Look and Reputation
318
Question 12i
Reputation Price Total
Observed (O) 130 97 227
Expected (E) 113.5 113.5 227
(O - E) 16.5 -16.5
(O - E)2 272.250 272.250
(O - E)2 / E 2.399 2.399
Chi Squared Calculated 4.80
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Reputation and Price
319
Question 12j
Contact Info Ease of Use Total
Observed (O) 120 107 227
Expected (E) 113.5 113.5 227
(O - E) 6.5 -6.5
(O - E)2 42.250 42.250
(O - E)2 / E 0.372 0.372
Chi Squared Calculated 0.74
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Contact Info and Ease of Use
320
Question 12k
Ease of Use Prof. Look Total
Observed (O) 151 76 227
Expected (E) 113.5 113.5 227
(O - E) 37.5 -37.5
(O - E)2 1406.250 1406.250
(O - E)2 / E 12.390 12.390
Chi Squared Calculated 24.78
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Ease of Use and Prof. Look
321
Question 12l
Price Prof. Look Total
Observed (O) 167 57 224
Expected (E) 112 112
(O - E) 55 -55
(O - E)2 3025.000 3025.000
(O - E)2 / E 27.009 27.009
Chi Squared Calculated 54.02
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Price and Prof. Look
322
Question 12m
Product Info Ease of Use Total
Observed (O) 140 87 227
Expected (E) 113.5 113.5 227
(O - E) 26.5 -26.5
(O - E)2 702.250 702.250
(O - E)2 / E 6.187 6.187
Chi Squared Calculated 12.37
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Product Info and Ease of Use
323
Question 12n
Prof. Look Contact Info Total
Observed (O) 75 152 227
Expected (E) 113.5 113.5 227
(O - E) -38.5 38.5
(O - E)2 1482.250 1482.250
(O - E)2 / E 13.059 13.059
Chi Squared Calculated 26.12
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Prof. Look and Contact Info
324
Question 12o
Ease of Use Reputation Total
Observed (O) 67 160 227
Expected (E) 113.5 113.5 227
(O - E) -46.5 46.5
(O - E)2 2162.250 2162.250
(O - E)2 / E 19.051 19.051
Chi Squared Calculated 38.10
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Ease of Use and Reputation
325
Question 13a
Need Price Total
Observed (O) 104 123 227
Expected (E) 113.5 113.5 227
(O - E) -9.5 9.5
(O - E)2 90.250 90.250
(O - E)2 / E 0.795 0.795
Chi Squared Calculated 1.59
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Need and Price
326
Question 13b
Ease of Use Need Total
Observed (O) 91 135 226
Expected (E) 113 113 226
(O - E) -22 22
(O - E)2 484.000 484.000
(O - E)2 / E 4.283 4.283
Chi Squared Calculated 8.57
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Ease of Use and Need
327
Question 13c
Need Reputation Total
Observed (O) 86 141 227
Expected (E) 113.5 113.5 227
(O - E) -27.5 27.5
(O - E)2 756.250 756.250
(O - E)2 / E 6.663 6.663
Chi Squared Calculated 13.33
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Need and Reputation
328
Question 13d
Prof. Look Need Total
Observed (O) 77 150 227
Expected (E) 113.5 113.5 227
(O - E) -36.5 36.5
(O - E)2 1332.250 1332.250
(O - E)2 / E 11.738 11.738
Chi Squared Calculated 23.48
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is greater than 3.84
REJECT the Ho
There is a difference between Prof. Look and Need
329
Question 13e
Contact Info Need Total
Observed (O) 124 103 227
Expected (E) 113.5 113.5 227
(O - E) 10.5 -10.5
(O - E)2 110.250 110.250
(O - E)2 / E 0.971 0.971
Chi Squared Calculated 1.94
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Contact Info and Need
330
Question 13f
Product Info Need Total
Observed (O) 124 103 227
Expected (E) 113.5 113.5 227
(O - E) 10.5 -10.5
(O - E)2 110.250 110.250
(O - E)2 / E 0.971 0.971
Chi Squared Calculated 1.94
Degrees of Freedom 1
Chi Squared (0.05) 3.84
Since Chi Squared Calculated is less than 3.84
Do NOT reject the Ho
There is no difference between Product Info and Need
331