AN ABSTRACT OF THE DISSERTATION OF
Tun-Min (Catherine) Jai for the degree of Doctor of Philosophy in Design and Human
Environment presented on June 4, 2010.
Title: The Impact of Unsolicited Behavioral Tracking Practices on Consumers’ Shopping
Evaluations and Attitudes toward Trusted Online Retailers
Abstract approved:
Leslie D. Burns
The purpose of the present study is to examine consumers’ privacy concerns in the
online shopping context.
Drawing from Social Contract Theory, the present study
proposed a structure equation model to examine how consumers’ evaluations of online
shopping experiences (perceived benefit, risk and fairness) and attitudes (trust, moods, and
repurchase loyalty) toward trusted online retailers are impacted when exposed to
information about unsolicited behavioral tracking (sources of behavioral tracking and
level of disseminating the information collected from consumers). Furthermore, the
study examined if personal factors such as innovativeness, consumer commitment, and
general privacy concern moderate the relationships among unsolicited behavioral tracking,
consumers’ evaluations of online shopping experiences and attitudes toward trusted online
retailers.
A total of 532 college students aged 18 and older participated in this study.
Four
unsolicited behavioral tracking scenarios were developed to provide the information of
unsolicited behavioral tracking to participants.
A between-subject experiment was
conducted in which data were collected using an online survey questionnaire.
The
results of structural equation model indicate that the level of disseminating consumers’
information has a significantly positive relationship with perceived risk (β=.46, p <.001),
hence decreasing consumers’ perceived fairness.
However, contrary to predictions,
third-party behavioral tracking does not significantly influence consumers’ perceived
benefit and perceived risk.
Consistent with the findings of the literature, consumers’
perceived fairness significantly predicts their attitudes toward trusted online retailer (trust,
pleasure, dominance, arousal and repurchase loyalty).
The result of multiple-group
comparison suggests that consumers’ personal traits such as innovativeness and
commitment moderate the relationships among the proposed model, while privacy
segment does not.
The findings of present study suggests there is a discrepancy between online
shoppers and their trusted online retailers regarding the information collected from online
shoppers since, currently, sharing of information collected from customers within
affiliates is a fairly common practice in the marketing field.
The findings do suggest that
online retailers should be cautious about their information practices since they may lose
consumers’ trust if consumers perceived it is unfair to them.
© Copyright by Tun-Min (Catherine) Jai
June 4, 2010
All Rights Reserved
The Impact of Unsolicited Behavioral Tracking Practices on Consumers’ Shopping
Evaluations and Attitudes toward Trusted Online Retailers
by
Tun-Min (Catherine) Jai
A DISSERTATION
Submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Doctor of Philosophy
Presented June 4, 2010
Commencement June 2011
Doctor of Philosophy dissertation of Tun-Min (Catherine) Jai
presented on June 4, 2010.
APPROVED:
_______________________________________________________________________
Major Professor, representing Design and Human Environment
________________________________________________________________________
Chair of the Department of Design and Human Environment
________________________________________________________________________
Dean of the Graduate School
I understand that my dissertation will become part of the permanent collection of Oregon
State University libraries. My signature below authorizes release of my dissertation to
any reader upon request.
________________________________________________________________________
Tun-Min (Catherine) Jai, Author
ACKNOWLEDGEMENTS
Though only my name appears on the cover of this dissertation, a great many people
have contributed to its production. I owe my sincere gratitude to all those people who
have made this dissertation possible and because of whom my doctoral education has
been one that I will treasure forever.
First of all, I thank my advisor, Dr. Leslie D. Burns, for giving me the opportunity to
work in a very an engaging and field of research and for her tremendous support and
encouragment throughout my graduate study.
I am grateful to the members of my committee for their invaluable direction,
assistance, and guidance. Dr. Nancy King (College of Business), whose researches
inspired me to work on the consumer privacy issue in the online retailing environment,
served on my comittee as a minor professor. Dr. Hsiou-Lien Chen, who has always been
there to listen and give me advice, Dr. Minjeong Kim, with her encouragement and
practical advice, and Dr. Urszula Iwaniec, thank you for being so nice and helpful all
along.
I am deeply grateful to Dr. Hal Koenig, Dr. Jimmy Young, Dr. Kathy Greaves, Dr.
Marilyn Read, Mary Pedersen, Carol Caughey and my dear DHE graduate student peers
for helping me in collecting data. Special thanks should be given to Dr. Alan Acock for
the long discussions that helped me sort out the technical details of statistical analysis.
I also have to give thanks to Dr. Brigitte Cluver, for her guiding and support over
these years, our department coordinator, Lavon Reese, for being so helpful, and my editor,
Rachael Cate, for copyediting my works and giving valuable suggestions on my writing.
Finally, words alone cannot express my appreciation to my family members for their
love and support. My husband, Stephen Shih, and my son, Leo, have been so lovely and
supportive in accompanying me in this adventure.
My friends in Corvallis, thank you for adding other dimensions to my life; I will miss you.
TABLE OF CONTENTS
Page
Chapter 1 Introduction .................................................................................. 1
Online Retail Market ............................................................................... 4
Statement of Problem .............................................................................. 6
Research Purpose .................................................................................... 6
Research Questions ................................................................................. 7
Research Hypotheses ............................................................................... 8
Assumptions ............................................................................................ 9
Definition of Terms ............................................................................... 10
Chapter 2 Literature Review........................................................................ 14
Online Behavioral Targeting .................................................................. 14
The U.S. Legal Environment ................................................................. 19
Fair Information Practice Principles ............................................... 21
Consumers’ Personal Information .......................................................... 24
Consumers’ Information Privacy ........................................................... 26
Consumers’ Evaluation of Online Transaction ....................................... 27
Perceived Fairness ......................................................................... 28
Consumers’ Attitudes toward Online Retailer ........................................ 30
TABLE OF CONTENTS (Continued)
Page
Trust .............................................................................................. 31
Moods............................................................................................ 32
Repurchase Loyalty ....................................................................... 33
Consumers’ Personal Traits ................................................................... 34
Innovativeness ............................................................................... 35
Consumer Commitment ................................................................. 36
General Information Privacy Concerns........................................... 37
Summary ............................................................................................... 40
Chapter 3 Method.......................................................................................... 42
Sample .................................................................................................. 43
Characteristics of Respondents....................................................... 44
Respondents’ Online Shopping Preferences. .................................. 48
Scenario Designs ................................................................................... 50
Measuring Instruments .......................................................................... 51
Data Collection ...................................................................................... 58
Data Analysis ........................................................................................ 59
Chapter 4 Results ........................................................................................ 62
Preliminary Analysis ............................................................................. 63
Structural Equation Modeling ................................................................ 68
Measurement Model .............................................................................. 69
TABLE OF CONTENTS (Continued)
Page
Structural Model .................................................................................... 73
Direct Effects ................................................................................. 74
Indirect Effects .............................................................................. 76
Test of Moderation Effects .................................................................... 78
Moderating effect of innovativeness............................................... 80
Moderating effect of commitment toward trusted online retailer..... 83
Summary ............................................................................................... 86
Chapter 5 Discussion and Conclusion ............................................................ 89
Theoretical Implications ........................................................................ 90
Practical Implications ............................................................................ 93
Limitations of the Study ........................................................................ 95
Suggestions for Future Research ............................................................ 96
Bibliography ......................................................................................................98
Appendices ................................................................................................. 117
Appendix 1 The 3rd Party Cookies Placement Among the Top 30 Apparel/
Accessory Websites .....................................................................118
Appendix 2 IRB Applications .........................................................................123
Appendix 3 Survey Questionnaires .................................................................134
Appendix 4 Names of the Websites Provide by Respondents that They Most
Frequently Shop ....................................................................... 181
Appendix 5 Means, Standard Deviations and Intercorrelations among
Indicators .....................................................................................185
LIST OF FIGURES
Figure
Page
1. 1 Proposed model ........................................................................................ 7
4. 1 Scatter matrix of endogenous variables ................................................... 67
4. 2 Eight-factor measurement model of the present study. ............................ 70
4. 3 Proposed causal model ........................................................................... 73
4. 4 Structual equation model showing relationships between sources of
unsolicited behavrioal tracking, level of disseminating consumer
informaiton, consumers’ evaluation of shopping experience
(perceived benefit, risk and fairness) and attitude toward trusted
online retailer (trust, pleasure, dominance, arousal, and
repurchase intention). .................................................................. 75
4. 5 Unstandarized coefficients between low / high innovativeness groups .... 82
4. 6 Unstandarized coefficients between low / high commitment groups
................................................................................................... 85
LIST OF TABLES
Table
Page
2. 1 U.S. Federal Regulation on Privacy ...................................................... 20
3. 1 Characteristics of Respondents (N=532)............................................... 46
3. 2 Frequencies and Percentage of Most-Shopped Product Categories
............................................................................................................. 49
3. 3 Scale Items and Factor Analysis Results of Personal Trait Variables .... 54
3. 4 Scale Items and Factor Analysis Results for Model Constructs,
Measured in 7-point Likert Scale .......................................................... 56
4. 1 Mean, Standard Deviation, Skewness, Kurtosis and Cronbach’s Alpha
of Indicators. ........................................................................................ 64
4. 2 Means, Standard Deviation, and Construct Inter-Correlations............... 65
4. 3 Maximum Likelihood Parameter Estimates for Measurement Model .... 71
4. 4 Error-correlations of Measurement Construct ....................................... 72
4. 5 Unstandardized Coefficients, Estimated Standard Errors, and
Standardized Coefficients of Direct Effects .......................................... 76
4. 6 Unstandardized Coefficients, Estimated Standard Error, and
Standardized Coefficients of Indirect Effects ........................................ 77
4. 7 Structural Equations Results for Moderating Effect Models .................. 79
4. 8 Structural Equations Results for Hypotheses 5a.................................... 81
4. 9 Structural Equations Results for Hypotheses 5b ................................... 84
The Impact of Unsolicited Behavioral Tracking Practices on
Consumers’ Shopping Evaluations and
Attitudes toward Trusted Online Apparel Retailers
Chapter 1
Introduction
The Internet has become an essential part of life for many people in the United States.
According to Internet World Stats (2009), there are over 227 million Internet users in the
United States; this figure translates to a seventy-four-percent penetration rate (the number
of Internet users divided by the total United States population).
The Internet provides
opportunities for social networking and information search, as well as serves as a medium
for both commercial and financial activities. However, the potentially negative issues
related to online privacy may not be so obvious to consumers.
For many online shoppers,
it is not odd to have the experience of being asked to provide personal information to
websites in exchange for “free” services or to be allowed to complete a transaction. It is
also a common experience for online shoppers to be recognized immediately by a website
when they patronize a website a second time. They may even be presented with a list of
2
suggested products that they may be interested in. This may seem harmless to consumers.
However, consumers may not be completely aware of how their information is being
obtained and used.
Behavioral targeting is a marketing practice of collecting and compiling a record of
individual consumers' online activities, interests, preferences, and/or communications over
time (Givens, 2009). Online retailers and third party advertisers are using technology to
track consumers’ online behaviors without obtaining affirmative consent. Most online
marketers and third-party advertisers put a small text file called “cookies” into the Internet
browsers within consumers’ computer drives. When installed in a consumers computer
drive, cookies allows the online marketer and third-party advertiser to track consumer
browsing behaviors across websites and enables them to provide personalized advertising
based upon their browsing behaviors (Bayan, 2001; Cranor, 1999; FTC, 2000; Miyazaki,
2008).
According to an online personalized ad-serving company, exposure to
personalized advertising can increase a consumer’s click rate by 44 percent when
compared to the click rate from exposure to standard non-personalized ads, with a 46
percent higher conversion rate off of those clicks (Internet Retailerc, 2009).
3
However, unsolicited behavioral tracking where marketers collect information from
consumers without their awareness is considered by many researchers to be a breach of
an implied social contract and may harm consumer trust and patronage (Culnan, 1995;
Milne & Gordaon, 1993; Miyazaki, 2008; Poddar, Mosteller & Ellen, 2009).
As the
result, behavioral targeting under nonconsensual tracking practice has rapidly become one
of the most effective, yet also controversial techniques to reach consumers.
Currently, U.S. self-regulation approach puts the burden of personal information
protection on consumers.
However, consumers have little knowledge about the online
behavioral tracking and the technologic mechanism to protect their personal information
(Dommeyer & Gross, 2003; Miyazaki, 2008; Turow, King, Hoofnagle, Bleakley &
Hennessy, 2009).
Besides that, research findings suggest that U.S. consumers
overestimated their ability to protect their information privacy online.
In their research,
Jensen, Potts & Jensen (2005) found that although a vast majority (90.3%) of the
experienced Internet user sample claimed to have knowledge of cookies, only 15.5% of
those making that claim demonstrated simple cookie knowledge.
Consumer Policy
Solutions (2008) found that almost 70 percent of Internet users said they were very or fairly
knowledgeable about how to protect their personal privacy online while 42 percent of
4
participants were unsure whether their online activity is tracked and recorded by
companies for commercial purposes. A recent national telephone survey also found that
over half of the subjects did not know whether a company had the right to sell or share their
information (Turow et al., 2009).
Online Retail Market
In 2008, the annual sales of the top 500 online retailers within the United States
increased 11.5 percent to 115.85 billion U.S. dollars (Internet Retailerb, 2009). Using
apprel/accessories category as an example, it was the second largest product category and
was responsible for nearly 14 billion dollars in web sales (Internet Retailer, 2009).
Because of the lack of possibility for physical evaluation before placing a purchase,
consumers tend to patronize online stores offering brands which they are already familiar
with.
Through my preliminary research, I found it is common for online apparel retailers
to allow other third-party marketers to place cookies for tracking consumers’ browser
behaviors across websites (Appendix 1).
For example, I found that Victoria’s Secret,
5
the top ranking company in the online apparel/accessory category presented by the
Internet Retailer (2009b), allowed seven third-party cookies to be placed into consumers’
hard drive without consumers’ affirmative consent.
Among the top 30 online
apparel/accessory retailers, 80 percent of them allowed third-party cookie placement on
their websites.
The websites having the most third-party cookies are Ann Taylor Stores
and Fingerhut Direct Marketing, which have 14 third-party cookies on their website
homepages.
The Neiman Marcus Group Inc., an upscale retailer, allowed 9 third-party
cookies on their websites.
Although researchers in the public policy and marketing fields have conducted
studies about consumers’ general online privacy concerns (Malhotra, Kim & Agarwal,
2004), consumers’ privacy attitudes and coping behaviors (Norberg & Horne, 2007; Son
& Kim, 2008; Lwin & Williams, 2003), and privacy concerns versus personalization
marketing (Chellappa &Sin, 2005), there are no empirical studies that examine the impact
of unsolicited behavioral tracking on consumers’ privacy concerns and attitude changes in
the context of trusted retailers. Prior researchers also suggested that consumers’ privacy
concern varied depending upon different contexts (FTC, 2009; Milne, 2004; Phelps,
Nowak & Ferrell, 2000). The empirical research of identifying the market privacy
6
practices and consumers’ privacy concerns in the trusted online shopping context is
warranted.
Statement of Problem
Online shoppers are being tracked via cookies placed by retailers and third party
advertisers. Prior research has shown that many consumers are not fully aware of the
behavioral tracking practices and suggests that consumers do not want private information
used for other secondary purposes. Given that prior research on this subject were not
context specific, there is a need to focus on the impact of unsolicited behavioral tracking
on consumers’ relationship with trusted retailers.
Research Purpose
The purpose of the present study is to examine consumers’ privacy concerns in the
online shopping context.
Specifically, the present study will examine how consumers’
evaluations of online shopping experiences (perceived benefit, risk and fairness) and
attitudes (trust, moods, and repurchase loyalty) toward trusted online retailers are impacted
when exposed to information about unsolicited behavioral tracking (retailer or third-party
7
advertiser). Moreover, the study will examine if personal factors such as innovativeness,
consumer commitment, and general privacy concern moderate the relationships among
unsolicited behavioral tracking, consumers’ evaluations of online shopping experiences
and attitudes toward trusted online retailers.
Sources of Unsolicited
Behavioral Tracking
Perceived
Benefit
Perceived
Fairness
Level of Disseminating
Consumer Information
Attitudes
toward Retailer
Perceived Risk
Moderator: Consumer Innovativeness, Consumer Commitment and General Privacy Concern
Figure 1. 1 Proposed model
Research Questions
1. Do the sources of unsolicited behavioral tracking (retailer and third-party advertiser)
have different influences on consumers’ evaluations of their online shopping
experiences (perceived benefit, risk and fairness)?
2. Does the level of disseminating consumer information influence consumers’
evaluations of their online shopping experiences (perceived benefit, risk and
fairness)?
3. Does the perceived fairness influence consumers’ attitudes toward trusted online
8
retailers?
4. Do consumers’ personal factors (fashion innovativeness, brand commitment, and
general privacy concern) moderate the relationships among unsolicited behavioral
tracking, consumers’ evaluations of online shopping experiences and their attitudes
toward trusted online retailers?
Research Hypotheses
H1: Compared to online retailer’s unsolicited behavioral tracking, the third-party
advertiser tracking will (a) decrease more perceived benefit and (b) increase more
perceived risk.
H2: The level of disseminating consumer information has (a) a negative relationship
with perceived benefit and (b) a positive relationship with perceived risk.
H3: The level of consumers’ perceived fairness has (a) a positive relationship with
perceived benefit and (b) a negative relationship with perceived risk.
H4: Higher level of perceived fairness has:
(a) a positive relationship with consumers’ trust toward trusted online retailers,
9
(b) a positive relationship with consumers’ pleasure,
(c) a negative relationship with consumers’ dominance,
(d) a positive relationship with consumers’ arousal, and,
(e) a positive relationship with consumers’ repurchase loyalty.
H5: Consumers’ personal factors (a. fashion innovativeness, b. brand commitment, and
c. general privacy concern) moderate the relationships among unsolicited
behavioral tracking, consumers’ evaluations of online shopping experiences and
their attitudes toward online retailers.
Assumptions
1. Online retailers have ethical reasons to maintain a positive relationship with
customers.
2. When consumers evaluate their relationships with online retailers, they tend to make
rational decisions.
3. The questionnaires used in this study will be completed by respondents in a truthful
manner.
10
Definition of Terms
Consumers’ Information Privacy
Consumers’ ability to control with, whom, how, and to what extent their personal
information is to be transmitted to others (Goodwin, 1991; Lanier & Saini, 2008; Milne
& Culnan, 2004; Phelps, Nowak & Ferrell, 2000; Westin, 1967; Youn, 2009)
Online Behavioral Advertising
“Online behavioral advertising means the tracking of a consumer’s online activities
over time – including the searches the consumer has conducted, the web pages visited,
and the content viewed – in order to deliver advertising targeted to the individual
consumer’s interests” (FTC, 2009, p. 2).
Unsolicited Behavioral Tracking
Consumers’ online browsing behaviors are tracked by online retailers and
third-party advertisers without consumers’ affirmative consents.
Cookies
“A cookie is a small text file that a website’s server places on a computer’s web
browser.
The cookie transmits information back to the website’s server about the
11
browsing activities of the computer user on the site.
This includes information such as
pages and content viewed, the time and duration of visits, search queries entered into
search engines, and whether a computer user clicked on an advertisement.
Cookies also
can be used to maintain data related to a particular individual, including passwords or
items in an online shopping cart. In some contexts, such as where a number of separate
websites participate in a network, cookies can be used to track a computer user across
different sites. In addition to cookies, there are other devices for tracking online activities,
including “web bugs,” “web beacons,” and “Flash cookies” (FTC, 2009, p.8)
Third Party Advertiser
“An entity that is a third Party to the extent that it engages in online behavioral
advertising on a non-Affiliate’s Web site” ( American Association of Advertising
Agencies, Association of National Advertisers, Council of Better Business Bureaus,
Direct Marketing Association & Interactive Advertising Bureau, 2009, p.11).
Perceived Fairness
Drawing from Social Contract Theory (SCT), consumers’ perceived fairness is a
function of benefit-cost evaluations when they conduct transactions online (Culnan &
Bies, 2003; Caudill & Murphy, 2000; Malhora, Kim & Agarwal, 2004)
12
Attitudes
Consumer attitudes are a composite of three dimensions: cognitive (beliefs), affective
(feelings) and behavioral (response tendencies) toward some object (Hawkins,
Mothersbaugh & Best, 2007).
The present study measures consumers’ trust as cognitive
attitude, moods (pleasure, arousal and dominance) as affective attitudes and repurchase
loyalty as consumers’ behavior intention.
Trust
Consumers’ trust is defined as the willingness to be vulnerable to the actions of online
retailer based on optimistic expectations that the company will protect their rights of all
involved (Hosmer, 1995; Mayer, Davis & Schoorman, 1995)
Moods
Moods (emotions) are strong, relatively uncontrolled personal feelings that affect
one’s behavior (Hawkins, Mothersbaugh & Best, 2007). The present study adopts
Mehrabian and Russell’s (1974) Pleasure-Arousal-Dominance (PAD) model to measure
consumers’ moods.
Behavioral Intention
13
Behavioral intention is one’s estimated expression of their future behaviors (Hawkins, et
al, 2007).
Repurchase loyalty is measured to indicate consumers’ behavioral intention
in the present study.
Innovativeness
Rogers (1995) defines innovativeness as “the degree to which an individual is
relatively earlier in adopting new ideas than other members of his/her social system”
(p.22).
In the present study, innovativeness is defined as the degree to which an
individual tends to try or buy new products (Raju, 1980; Roehrich, 2004).
Brand Commitment
Consumers’ attitude which involves one’s beliefs and acceptance of the brand’s goals
and values, expression of authentic interest in the company’s interests, expenditure of
considerable effort on its behalf, and desire to remain a consumer (Huang, 2001; Kelley
and Davis, 1994).
General Privacy Concern
Consumers’ general privacy concern refers to one’s privacy need of control one’s
personal information. The present study used Westin’s (1997) Privacy Segmentation
Indexes (PSI) to classify consumers according to their general privacy concerns.
14
Chapter 2
Literature Review
Consumers’ information privacy concern regarding behavioral marketing practices is
a controversial issue which surrounded by three major factors: the government legislative
agency, marketers and consumers.
In this chapter, I will first discuss marketers’
practices of online behavioral targeting and the U.S. legal environment including the Fair
Information Practice Principles, which guard consumers’ personal information in the
market place.
Then, I will discuss the concept of consumers’ information privacy and
the variables involved in the present research.
I will also discuss the theories that have
been applied in the present research for explaining consumers’ responses toward the
unsolicited behavioral tracking and their attitudes toward online retailers.
Online Behavioral Targeting
Online behavioral targeting is a marketing practice of collecting and compiling a
record of individual consumers' online activities, interests, preferences, and/or
15
communications over time and across websites in order to deliver personalized
advertising (FTC, 2009). It involves two types of activities: (1) tracking online users’
actions and (2) tailoring advertisements or service contents for the users based on those
actions (Givens, 2009; Turow et al. 2009). Providing personalized advertising is one of
the hottest trends in online retailing.
To be able to conduct personalized marketing,
consumers’ personal data (name, geographic location, income, family size, brand
preference, shopping history) is a crucial asset for marketers.
Thus, the collection of
consumer data is an almost universal practice of commercial websites, but the methods of
collection, as well as the scope and manner of the use of collected information, varies from
business to business (Hoy& Phelps, 2009; Miyazaki, 2008; Nakashima, 2008; Schwaig,
Kane & Storey, 2006).
There are two widely-used methods to collect consumer’s information-- direct and
indirect methods. An online retailer collects consumer’s information directly when they,
for instance, require a shopper to disclose personal information in order to complete a
transaction. In this case, consumers are aware that they are providing personal
information and have control over the personal information that they provide.
On the
16
other hand, an online retailer can also collect consumers’ information indirectly by using
technology to track consumers’ browsing behavior within and across websites.
The strategy that many websites are using for the indirect data collection is to place
small programs (e.g. cookies) onto online users’ computer drives. In this way, a
consumer’s surfing behaviors such as the pages which he/she visited or the searches which
he/she made can be reported to marketers. The behavioral information can be used on its
own or in conjunction with personal identifiable data (FTC, 2009).
However, such
unsolicited behavioral tracking where marketers collect information from consumers
without their awareness is consider by many researchers to be a breach of an implied
social contract and may harm consumer trust and patronage (Culnan, 1995; Milne &
Gordon, 1993; Miyazaki, 2008; Poddar, Mosteller & Ellen, 2009).
As the result,
behavioral targeting under nonconsensual tracking practice has rapidly become one of the
most effective, yet also controversial techniques to reach consumers.
There are two types of corporate involved in current online behavioral targeting:
websites and third-party advertising networks (FTC, 2009). The first, websites,
intimately follow online browser’s motions and observe, for instance, what news they read,
what ads they clicked, and what terms they searched. Then the website can serve up ads
17
or coupons to the browser based on a selected topic—for example, a suggested blouse if
the consumer is viewing a pair of paints. This is also called contextual marketing (FTC,
2009).
Similar to websites, third-party network advertisers also track online users and store
information about the users’ online behaviors; usually consumers are not aware of such
practices (Nakashima, 2008). These advertisers’ networks may include thousands, even
tens of thousands, of websites that accept ads from those firms and share in the revenues
(Network Advertising Initiative, 2009). According to letters released by the House
Energy and Commerce Committee, in 2008, Microsoft and Yahoo disclosed that they
engaged in some forms of behavioral targeting (Nakashima, 2008). Google, the leading
online third-party advertiser, launched its behavior targeting advertising program in March
2009, which enabled it to more precisely follow web-surfing behavior across affiliated
sites, like Google Search (search engine), You Tube (publisher), and Gmail (email
service).
Through preliminary research, the present research found it is common that online
apparel retailers allow other third-party marketers to place cookies for tracking
consumers’ browser behaviors across websites (Appendix 1).
Among the top 30 online
18
apparel/accessory retailers, 80 percent of them allowed third-party cookie placement on
their websites.
Victoria’s Secret, the top ranking company in the online
apparel/accessory category presented by the Internet Retailer (2009b), allowed seven
third-party cookies to be placed into consumers’ hard drive without consumers’
affirmative consent. American Eagle Outfitter, one of the favorite tween brands
(Eisenberg, 2009), has 13 third-party cookies on its website. The websites having the
most third-party cookies are Ann Taylor Stores and Fingerhut Direct Marketing, which
have 14 third-party cookies on their website homepages.
The Neiman Marcus Group
Inc., an upscale retailer, allowed 9 third-party cookies on their website.
With the emergence of real-time person-location technologies and biometric
identifiers, combined with mobile marketing, the issue of unsolicited behavioral tracking
will continue to play a major role in debates of consumer privacy in the age of information
economy. (Clarke, 1999; Huang, 2001; King, 2008; Milne, 2000; Miyazaki, 2008; Wirtz,
Lwin & Williams, 2007)
19
The U.S. Legal Environment
Citizens of nearly all developed countries throughout the world enjoy rights to
privacy through laws that are called “data protection acts” (Givens, 2009). In those
countries, comprehensive data protection laws govern how personal information can be
used by government agencies as well as commercial entities. The use of personal
information is usually an “opt in” under such laws. That means, an individual’s personal
information cannot be used for marketing unless that person gives affirmative consent.
The U.S. currently has no such law. Instead, there are only so-called sectoral privacy
laws. Examples are the Telephone Consumer Protection Act (regarding telemarketing),
the Fair Credit Reporting Act (regarding credit reports and employment background
checks), the FACT Act (regarding financial privacy), and Health Insurance Portability and
Accountability Act (HIPPA, regarding medical records privacy). Table 2.1 lists the U.S.
federal regulation on privacy. However, this sectoral approach leaves many uses of
personal information unprotected. For example, our online shopping history and website
preference is not covered by a specific law. Compared to the European government, the
U.S legislative institution chooses the “self-regulation” approach to facilitate its online
20
Table 2. 1
U.S. Federal Regulation on Privacy
Act
Year
Description
Fair Credit Reporting Act
1970
Allows consumers to correct errors in their credit reports.
Privacy Act
1974
Government officials may not maintain secret files or gather information
about people irrelevant to a lawful purpose.
Right to Financial Privacy Act
1978
Government officials need a warrant to obtain a bank's copies of checks.
Electronic Transfer Funds Act
1980
Banks must notify customers when disclosing records to third parties.
Privacy Protection Act
1980
Government officials are restricted in their ability to seize records of the
print media.
Cable Communications Act
1984
Cable companies may not disclose choices customers make or other
personal information without consent.
Family Education and Privacy
1984
Right Act
Computer Security Act
Government officials are restricted in their ability to reveal to third
parties information gathered by agencies or educational institutions.
1987
All government agencies develop safeguards for protecting sensitive data
stored in their computers.
Electronic Communications
1988
Privacy Act
Prohibits telephone, telegraph, and other communications services from
releasing the contents of messages they transmit (only the recipient of the
message can be identified).
Video Privacy Protection Act
1988
Video rental companies may not disclose choices customers make or
other personal information without consent.
Computer Matching and Privacy
1988
Protection Act
Telephone Consumer Protection
gather if the safeguards against information disclosure also increase.
1991
Act
Drivers' Privacy Protection Act
Allows governmental officials to increase the amount of information they
Prohibits telemarketers from using automatically dialing telephone calls
or facsimile machines to sell a product without obtaining consent first.
1993
Places restrictions on state government agencies and their ability to sell
driver's license records.
Children's Online Privacy
1998
Sets rules for online collection of information from children.
Protection Act
(Source: Caudill & Murphy, 2000, p.9)
21
business. However, research has shown that consumers had little knowledge about it.
In their recent research, Turow et al. (2009) found that most Americans “mistakenly
believe that current government laws restrict companies from selling wide-ranging data
about them” (p. 4). The increasingly complex data collection methods have raised
concerns about consumer’s information privacy, consumer advocacy organizations have
urged the Congress and FTC to develop a comprehensive online and offline privacy bill to
offer the ability to specifically regulate the marketing practices of behavioral targeting
(FTC, 2000, 2009; Harbour, 2009; Kafka, 2009; Turow et. al, 2009; The Center for
Democracy & Technology, 2009).
Fair Information Practice Principles
In the United States, the Federal Trade Commission (FTC) is in charge of developing
standards of companies marketing practices on the Internet.
The government agencies in
the United States have studied “the manner in which entities collect and use personal
information (their information practices) and what kinds of safeguards required to assure
those practices are fair and provide adequate privacy protection” (FTC, 2007, p.1).
22
Currently, all the self-regulation guidelines are in light of five core principles of Fair
Information Practice: (1) Notice/Awareness; (2) Choice/Consent; (3) Access/Participation;
(4) Integrity/Security; and (5) Enforcement/Redress. FTC states that notice/awareness is
the most fundamental principle, because “Without notice, a consumer cannot make an
informed decision as to whether and to what extent to disclose personal information.”
(FTC, 2007, p.1). The other principles such as choice, access and enforcement are all
based on when a consumer has an awareness of an entity's policies. FTC clearly states
that an online entity’s privacy notice should be “clear and conspicuous, posted in a
prominent location” (FTC, 2007, p.1) and the content should include,
“identification of the entity collecting the data;
identification of the uses to which the data will be put;
identification of any potential recipients of the data;
the nature of the data collected and the means by which it is collected if
not obvious (passively, by means of electronic monitoring, or actively,
by asking the consumer to provide the information);
whether the provision of the requested data is voluntary or required, and
the consequences of a refusal to provide the requested information; and
the steps taken by the data collector to ensure the confidentiality,
integrity and quality of the data.” (excerpt from FTC, Fair information
practice principles, 2007)
The second principle of fair information practice is consumer’s choice/consent.
online entity should give consumers options of the way the personal information
An
23
collected from them may be used secondarily, including the internal and external usage.
An internal usage example may be sharing the collected personal information with
affiliations.
For external usage, it could be sharing consumers’ information with a third
party entity.
Under this principle, consumers should be provided at least either opt-in or
opt-out choice to exercise their right of choice/consent.
The third principle is access/participation.
It refers to consumers’ abilities to
exercise control over their personal information stored in an entities database.
principle is integrity.
data integrity.
The forth
FTC requires data collectors to take reasonable steps to assure
The fifth principle is enforcement/redress.
There should be a
mechanism in place to ensure companies’ fair information practices.
However, it has
been shown that many online websites do not exactly follow the Fair Information
Practice Principles in their privacy related practices (FTC, 2000; Earp, Anton,
Aiman-Smith & Stufflebeam, 2005; The Center for Democracy & Technology, 2009).
24
Consumers’ Personal Information
In the age of an information economy, the advances in computer technology
facilitate companies’ abilities to collect, store and merge online users’ personal
information.
However, the range and sensitivity of consumers’ personal information
may vary from country to country, industry to industry, company to company and even
individual to individual. Generally, the collected personal information can be classified
according to the identifiability and sensitivity of the data as personal identifiable
information (PII) and non-personal identifiable information (non-PII). Some information
(no matter it is PII or non-PII) is more or less sensitive.
The Safe Harbor Privacy
Principles, for example, which guide US companies through a process to meet the terms of
the EU Directive 95/46/EC on the protection of personal data, the personal data are defined
as the data about an identified or identifiable individual that is recorded in any form (US
Department of Commerce, 2000). According to the Network Advertising Initiative (NAI),
a predominant industry self-regulatory organization, personal identifiable information (PII)
includes name, address, telephone number, email address, financial account number,
government-issued identifier, and any other data used or intended to be used to identify,
25
contact or precisely locate a person (Network Advertising Initiatives, 2008). Google
argued that Internet protocol (IP) addresses are not PII information (Hansell, 2008), while
Amazon, the biggest online retailer in the United State, includes the information they
automatically collect from consumers such as IP address, browsing history, the full
Uniform Resource Locator (URL) clickstream, etc as personal information (Amazon,
2010). As new technologies are developing, using identifiability to classify consumer
information may not be an effective method, since the non-PII may still become
identifiable after merging with other identifiable information. Thus, both government
agency (FTC, 2009) and privacy advocate (The Center of Democracy and Technology,
2009) suggest that categorization of information as either non-PII or PII has become
becoming less and less meaningful. Furthermore, the PII/non PII categorization should
not, by itself, determine the protections provided for the information collected from
consumers.
Using data sensitivity to classified consumers’ personal information is another
approach.
NAI (2008) defined “social security numbers or other government-issued
identifiers, insurance plan numbers, financial account numbers, and information that
describes the precise real-time geographic location through global-positioning-system-
26
enabled (GPS) devices as sensitive consumer information”, as well as “precise information
about health or medical conditions or treatments, including genetic, genomic and family
medical history” (p.6). However, using sensitivity of personal information to determine
privacy protection provided to consumer needs more clarification.
In their latest draft of
behavioral targeting guideline, NAI proposed a list of a few conditions, like AIDS, cancer
and psychiatric ailments, about which its members would not be allowed to collect data
to use in targeting ads (Hansell, 2010).
However, other heath related information would
be subject to the discretion of the advertising company.
Consumers’ Information Privacy
From the 1990s, consumer privacy issues moved to the front position of consumer
affairs and public policy research.
According to the American Marketing Association’s
web site, the top five most-cited articles in the last ten years for the Journal of Public
Policy & Marketing all deal with privacy issues (Langenderfer & Miyazaki, 2009).
Consumer information privacy has been defined as "the consumer's ability to control
(a) the presence of other people in the environment during a market transaction or
27
consumption behavior and (b) the dissemination of information related to or provided
during such transactions or behaviors to those who were not present" (Goodwin 1991, p.
152).
Some researchers suggest consumer privacy is a continuum, depending on
consumers’ personal factors, such as individual experience and knowledge (Culnan, 1995;
Dommeyer & Gross 2003; Foxman & Kilcoyne, 1993; Milne & Culnan, 2004; Nowak &
Phelps, 1992, 1995).
Milne & Rohm (2000) argued that consumer privacy exist only
when consumers are aware of their information being collected and they can remove their
names from undesirable lists (exercise control) if they wish.
In the present study, consumers’ information privacy refers to consumers’ ability to
control with, how, and to what extent their personal information is to be transmitted to
others (Goodwin, 1991; Lanier & Saini, 2008; Milne & Culnan, 2004; Phelps, Nowak &
Ferrell, 2000; Westin, 1967; Youn, 2009).
Consumers’ Evaluation of Online Transaction
Consumers continue to visit a particular business based on their perceptions of trust
(Caudill &Murphy, 2000). However, unsolicited behavioral tracking where marketers
28
collect information from consumers without their awareness is consider by many
researchers to be a breach of an implied social contract and may harm consumer trust and
patronage (Culnan, 1995; Milne & Gordon, 1993; Miyazaki, 2008; Poddar, Mosteller &
Ellen, 2009).
In the following section, I will review the variables involved in the present
research and the related theories used. They are consumers’ perceived fairness, trust
toward the retailer, moods and behavioral intention.
Perceived Fairness
Applying Social Contract Theory (SCT) in to their researches, researchers found
consumers performed benefit-cost evaluations (or “trade-off”), when they engaged in
online information exchange (Culnan & Bies, 2003; Caudill & Murphy, 2000; Malhora,
Kim & Agarwal, 2004). This tradeoff has been studied offline as “privacy calculus,”
which measures the usage of personal information against the potential negative
consequences of disseminating personal information (Laufer & Wolfe, 1977; Milne &
Gordon, 1993; Stone & Stone, 1990). In the online privacy context, consumer’s
willingness to share their personal information online involves evaluating the benefits and
the risk of online behavioral tracking and the release of personal information (Awad &
29
Krishnan, 2006; Caudill & Murphy, 2000). The perceived benefits may derive through
the degree of convenience received or monetary remedy (such as coupon or rebate) and the
cost might be a function of consumer privacy concerns, previous privacy invasion
experience, and consumer-rated importance of information transparency (Awad &
Krishnan, 2006; Poddar, Mosteller & Ellen, 2009; Yu & Cude, 2009). Consumers,
instead of following an absolute philosophy as “I want to be left alone”, might just want
the protection against unwarranted uses of personal information with minimal damage
(Dolnicar & Jordaan, 2007; Norberg, & Horne, 2007; Rotfeld, 2009). Previous
researches have shown us that consumers disclose their personal information to obtain
“free” information, personalized content (Pastore, 1999), prizes, loyalty program
memberships (Earp & Baumer, 2003), discounts (White, 2004) or some other form of “fair”
exchange (Culnan & Bies, 2003).
Moreover, consumer developed their coping strategies
such as creating multiple email addresses or giving false information to exchange the
desired benefits (Poddar et al., 2009).
In an online shopping context, consumers’ perceived risk of behavioral tracking
reflects their concerns of potential privacy invasion associated with retailers’ online
information practices.
Concerns for privacy are raised when consumers feel uninformed
30
by marketers about who is collecting their personal information, how their information is
collected and for what purpose their information is used (Lanier & Saini, 2008; Nowak &
Phelps, 1995; Youn, 2009).
In the present study, when informed that they have been
subject to unsolicited behavioral tracking, a consumer may feel uninformed and increase
his/her perceived risk of interacting with the retailer online.
Rifon, LaRose & Choi
(2005) suggest that “concern of privacy is a function of specific information practices
associated with privacy invasion or violations” (p.344).
As a result, in the context of
online shopping, it is expected that when consumers know about the unsolicited tracking
practices, their perceived fairness of transactions will change, and hence, consumers’
attitudes toward the online retailers will also change.
Consumers’ Attitudes toward Online Retailer
Attitude is composed of three dimensions: cognitive (beliefs), affective (feelings)
and behavioral (response tendencies) (Hawkins, Mothersbaugh & Best, 2007).
Prior
researches suggested that consumers’ attitudes have significant relationships with related
behaviors (Hawkins et al., 2007).
The present study measures consumers’ trust as
31
cognitive attitude, mood (pleasure, arousal and dominance) as affective attitude and
repurchase loyalty as consumers’ behavior intention.
Trust
Trust is a very important factor in many social and business relationships.
Trust is
defined as the willingness to be vulnerable to the actions of another person or company
(Mayer, Davis & Schoorman, 1995) based on optimistic expectations that the other person
or company will protect the rights of all involved (Hosmer, 1995). Pavlou (2003) defined
trust in online retailing field as “the belief that allows consumers to willingly become
vulnerable to Web retailers after having taken the retailers’ characteristics into
consideration” (p.106).
It is also a significant factor leading to anticipated purchases
(Doney & Cannon, 1997), and creates the atmosphere where people are more willing to
provide sensitive information (Ramaswani, Srinivasan & Gorton, 1997). Consumers’
trust toward an online retailer can be considered as a mirror of concern and is based on
the likelihood that their information would not be abused (Rifon, et al, 2005).
Prior research has shown when consumer had prior experience with a company, they
tend to keep their trust in that company and their website (Chellappa & Sin, 2005; Milne
32
& Culnan, 2004; Poddar, et al., 2009). In their study, the participants stated: “I only buy
from trusted Web sites—stores I’ve already experienced offline, so just assume I’m
protected” and “I generally do Internet business with the same companies and have grown
to trust them” (Milne & Culnan, 2004, p.23).
From the above review, consumers’ trust is
suggested to be a critical factor to determine how consumer interacts with online retailers
and whether a business interaction will even occur.
Moods
Moods (emotions) are strong, relatively uncontrolled personal feelings that affect
one’s behavior (Hawkins, Mothersbaugh & Best, 2007).
According to Bagozzi,
Gopinath, and Nyer (1999), emotion can be defined as a psychological state of
preparation that arises from cognitive appraisals of events or thoughts.
Mehrabian and
Russell (1974) suggested the Pleasure-Arousal-Dominance (PAD) model to measure
consumers’ moods.
PAD model has been used by many marketing and advertising
researchers (Baker, Levy & Grewal, 1992; Donovan & Rossiter, 1982; Holbrook &
Gardner, 1998; Li, Kim & Lee, 2009; Machleit & Eroglu, 2000; Menon & Kahn, 2002;
Poels & Dewitte, 2008; Lehto, Douglas & Park, 2007; Yani-de-Soriano & Foxall, 2006).
The present research adopts the measuring items from Holbrook & Batra’s research
33
(1987) to measure consumers’ emotional responses.
In the dimension of pleasure, joy
(joyful, happy, delighted) and affection (loving, affectionate, friendly) are measured.
In
the dimension of arousal, the following are measured: attentive, curious, aroused, and
excited.
Last, in the dimension of dominance, the following are measured:
anxious, frustrated, conflictful, irritated, and mad.
fearful,
It is expected that consumers’
fairness perception would have a positive relationship toward consumers’ positive
moods.
Repurchase Loyalty
The behavioral component of attitude is “ones’ tendency to respond in a certain
manner toward an object or activity” (Hawkins wt al., 2007).
Consumers’ behavioral
tendencies are most often measured by relatively direct questions.
loyalty is measured to indicate consumers’ behavioral intention.
Thus, repurchase
Modified from past
research (Chaudhuri & Ligas, 2009), a four-item scale was used to assess repurchase
loyalty. The specific items were (1) I intend to return to shop at MyFavoriteStore.com, (2)
I will use this store the next time I want to make a purchase., (3) I probably won't switch to
another website to make purchases.and (4) I would recommend this store to my friends.
34
Consumers’ Personal Traits
Social cognitive theory suggests human behavior as a triadic, dynamic, and reciprocal
interaction among personal factors, behavior, and the environment (Bandura, 1986, 1989,
1991, 1995, 2001). Personal factors are expected have influence on individuals’
responses to their surrounding environments. In an online environment, personal
determinants such as gender, age, privacy knowledge, and Internet experience has been
found to have significant relationships with one’s general privacy concerns and privacy
protection behaviors (Dommeyer & Gross, 2003; Milne & Culnan, 2004; Milne, Rohm &
Bahl, 2004; Miyazaki & Krishnamurthy, 2002; Schoenbachler & Gordon, 2002; Youn,
2009). Since the present research is set within the context of the online shopping field, it
is warranted to examine how consumers’ personal factors such as innovativeness,
consumer commitment, and general information privacy concerns influence the
relationships among the impact of unsolicited behavioral tracking and consumers attitude
changes toward trusted online retailers.
35
Innovativeness
Rogers (1995) defines innovativeness as “the degree to which an individual is
relatively earlier in adopting new ideas than other members of his/her social system”
(p.22).
Consumer innovators reflect “more favorable new product attitudes and are
more swayed by newness appeals than later buyers” (Robertson, 1971, p.15).
Prior
researches suggest consumer innovativeness is positively associated with opinion
leadership (Goldsmith, Moore & Beaudion, 1996; Jordaan & Simpson, 2006).
According to Feick and Price (1987), opinion leaders are persons who act as information
communicators between mass media sources and the opinions and choices of the
population.
They often have significant effects on the diffusion of new merchandise in
a specific market through their interpersonal communication.
Opinion leaders appear to be more knowledgeable about, and involved in a specific
product class.
In the online shopping context, since fashion related information are
important for fashion leader, it is expected that they will perceived more benefits from
retailers’ behavioral targeting practices such as personalized advertising and product
36
information, which in turns to reduce their unfairness perception of unsolicited behavioral
tracking.
Consumer Commitment
Consumer commitment is an attitude which involves one’s beliefs and acceptance of
the origination’s goals and values, expression of authentic interest in the company’s
interests, expenditure of considerable effort on its behalf, and desire to remain a consumer
(Huang, 2001; Kelley & Davis, 1994). Huang (2001) suggested that the unethical
behaviors of websites would negatively affect consumers’ commitment toward the
websites.
Meanwhile, it was found that the consumers with a higher level of brand
commitment instinctively refuse to accept the negative information about the brand
(Ahluwalia, Burnkrant & Unnava, 2000).
Due to their defensive responses, the effects
of negative publicity toward a brand would be mitigated.
Thus, a consumer with
high-commitment toward an online retailer would have less attitude degradation after
expose to the negative information about the online retailer.
In the present study, the
information of online retailers’ unsolicited behavioral tracking practices is expected to
work as a negative publicity to consumers.
As the result, it is expected that the level of
37
consumers’ brand commitment would moderate the effects of negative information such
as unsolicited behavioral tracking about a well-liked online retailer.
The measuring
construct has been previously examined in the previous literature (Ingram, Skinner &
Taylor, 2005), and has been modified for the setting of this study. The six-item scale
included the items like “I am a loyal patron of this website”, “I believe that my values are in
line with the values of the website.”, and “I care about the fate of the website (i.e., stays in
business).”
General Information Privacy Concerns
Privacy is a complicated concept and the degree of privacy concerns may vary from
individual to individual (Foxman & Kilcoyne, 1993; Larose & Rifon, 2007; Milne &
Rohm, 2000).
In order to better understand the relationships between consumers’
privacy preferences and their privacy related behaviors, from 1978 to 2004, Dr. Alan
Westin created Privacy Segmentation Indexes (PSI) to classify consumers according to
their privacy concerns into three groups: privacy fundamentalists, privacy pragmatists
and privacy unconcerned groups (Kumaraguru & Cranor, 2005).
classify the public in his studies from 1995 to 1999.
He used three items to
These items include “(1)
38
consumers have lost all control over how personal information is collected and used by
companies, (2) most businesses handle the personal information they collect about
consumers in a proper and confidential way, and (3) existing laws and organizational
practices provide a reasonable level of protection for consumer privacy today”
(Kumaraguru & Cranor, 2005, p. 13).
“[T]he respondents who agreed (strongly or
somewhat) with the first statement and disagreed (strongly or somewhat) with the second
and third statements were classified as Privacy Fundamentalists… [T]he respondents who
disagreed (strongly or somewhat) with the first statement and agreed (strongly or
somewhat) with the second and third statements were classified as Privacy Unconcerned.
Privacy Pragmatists are all other respondents” (Harris Interactive, 2002, p. 20).
The descriptions of these three groups follow:
Privacy Fundamentalists (about 25% of the national public). “This group
sees privacy as an especially high value, rejects the claims of many
organizations to need or be entitled to get personal information for their
business or governmental programs, thinks more individuals should simply
refuse to give out information they are asked for, and favors enactment of
strong federal and state laws to secure privacy rights and control
organizational discretion”(excerpt from Harris Interactive, 2002, p. 20) .
Privacy Pragmatists (about 55% of the national public): “This group
weighs the value to them and society of various business or government
programs calling for personal information, examines the relevance and
39
social propriety of the information sought, wants to know the potential risks
to the privacy or security of their information, looks to see whether fair
information practices are being widely enough observed, and then decides
whether they will agree or disagree with specific information activities-with their trust in the particular industry or company involved a critical
decisional factor. The Pragmatists favor voluntary standards and consumer
choice over legislation and government enforcement. But they will back
legislation when they think not enough is being done-- or meaningfully done
¾ by voluntary means” (excerpt from Harris Interactive, 2002, p. 20-21).
Privacy Unconcerned (about 20% of the national public): “This group
doesn't know what the “privacy fuss” is all about, supports the benefits of
most organizational programs over warnings about privacy abuse, has little
problem with supplying their personal information to government
authorities or businesses, and sees no need for creating another government
bureaucracy (a “Federal Big Brother”) to protect someone's privacy”
(excerpt from Harris Interactive, 2002, p. 21).
Many privacy researchers have used these privacy indexes as benchmarks to
compare their own survey results (Acquist & Grossklags, 2005; Cranor, Reagle &
Ackerman, 2004; Dolnicar & Jordaan, 2007; Turow et al, 2009).
Prior research found
that privacy fundamentalists were twice as likely as other consumers to report having
been a victim of an invasion of privacy on the Internet (Cranor, 1999).
Since consumers’
general privacy concern is an important personal factor that influences consumers’ online
privacy protection behaviors, the researcher expects that consumers in different PSI
40
categories will react differently to when they are made aware of unsolicited online
behavior tracking.
Summary
Online behavioral targeting is a marketing practice of collecting and compiling a
record of individual consumers' online activities, interests, preferences, and/or
communications over time and across websites in order to deliver personalized
advertising (FTC, 2009). Consumers’ information privacy concerns regarding behavioral
marketing practices are a controversial issue which is surrounded by three major factors:
the government legislative agency, marketers and consumers. In the United States, the
Federal Trade Commission (FTC) is in charge of developing standards regarding
companies’ marketing practices on the Internet. Instead of have a comprehensive online
and offline privacy law to regulate the marketing practices of behavioral targeting,
currently, the United States adopts a self-regulatory approach. However, it has been
shown that many online websites do not exactly follow the Fair Information Practice
Principles in their privacy related practices (Earp, et al, 2005; FTC, 2000; The Center for
41
Democracy & Technology, 2009). Consumers’ concerns of privacy are raised when
they feel uninformed by marketers about who is collecting their personal information,
how their information is collected and for what purpose their information is used (Lanier
& Saini, 2008; Nowak & Phelps, 1995; Youn, 2009). As a result, in the context of online
shopping, it is expected that when consumers know about the unsolicited tracking
practices, their perceived fairness of transactions will change, and hence, consumers’
attitudes towards the trusted online retailers will change as well.
42
Chapter 3
Method
The purpose of the present study is to examine the impact of unsolicited behavioral
tracking (retailer or third-party advertiser) on consumers’ evaluations of online shopping
experiences (perceived benefit, risk and fairness) and attitudes (trust, mood, and
repurchase loyalty) toward a trusted online retailer.
Moreover, the study examines if
personal factors such as innovativeness, store commitment, and general privacy concern
moderate the relationships within the proposed model.
Below are descriptions of the sample, scenario designs, measuring instrument, and
data collection process.
Before collecting data, the present study was approved by the
Institutional Review Board (IRB) of Oregon State University. IRB application documents
are presented in Appendix 2.
43
Sample
A purposive convenience non-probability sample was used in the present study. The
sample consisted of college students because college students not only represent a
vulnerable and significant Internet user group, but they are also an important cohort,
Generation Y, to online retailers (Internet Retailera, 2009; National Retail Federation,
2007).
They have the highest Internet usage of any other cohort and their online buying
and purchasing behavior is representative of a wide range of users (Fox & Madden, 2005;
LaRose & Rifon, 2007).
According to the FTC (2005), young adults (the 18- to
29-year-old segment) experienced the greatest risk of privacy violations such as identity
theft and Internet fraud.
The questionnaire included a variety of questions designed to elicit information
necessary to describe the sample.
First, respondents were asked to provide the
following demographic information:
“What is your gender?”; “Age”; “What college
you are attending?”; “What is your class standing?” and “What is your ethnicity
background?” Furthermore, respondents were provided with a list of possible online
privacy invasion experiences and asked to indicate which they had personally
44
experienced.
Second, respondents were asked to provide behavioral information
regarding online shopping, including the name of the website at which they shop most
frequently, which product category best describes their shopping choices at the website,
their patronage frequency of the website, and whether they have made purchase on the
website before.
Characteristics of Respondents
A total of 532 college students aged 18 and older from Oregon State University
(OSU) participated in this study.
Some participants were recruited via email using the
listserve (an electronic mailing lists system used at OSU) such as “Milam Hall”.
Other
participants enrolled in specific College of Business and College of Health and Human
Sciences courses were recruited via emails that were sent by their courses instructors; in
some cases, instructors offered extra credit to students for their participation.
Regarding the characteristics of respondents, seventy-one percent of respondents
were female (n=373; 70.91%), and most ranged from 18 to25 years in age (91.20%).
The major ethnicity backgrounds of respondents include: White/ Non-Hispanic (n=398,
76.25%), Asian (n=65, 12.45%), and Hispanic/Latino (n=28, 5.36%).
Primarily,
45
respondents were undergraduate students (n=490, 93.16%) from either the College of
Health and Human Science (n=273, 52.40%) or the College of Business (n=199, 38.20%).
More detailed demographic characteristics of respondents are displayed in Table 3.1.
Because the present study addresses online privacy, it is important to understand
respondents’ personal experiences with the topic.
some experience with online privacy invasion.
Most respondents indicated they had
“Spam/junk email experience” was the
most common experience among respondents (93.42%), followed “Computer virus attack
experience” (59.59%), “Others learning your personal info from online activities”
(34.02%), and “e-mail read by someone other than recipient” (13.72%).
Some
respondents also reported that they had experienced severe privacy invasions such as
credit card fraud (11.28%) and ID theft (6.95%).
Only three percent of respondent
reported that they had not experience any of the above mentioned privacy-related issues.
46
Table 3. 1
Characteristics of Respondents (N=532)
What is your gender?
Male
Female
No answer, missing
Age
18-25
26-35
36-45
46 above
What college you are attending?
1. Agricultural Sciences
2. Business
3. Education
4. Engineering
5. Forestry
6. Health & Human Sci.
7. Liberal Arts
9. Pharmacy
10. Science
What is your class standing?
1. Freshman
2. Sophomore
3. Junior
4. Senior
5. Post Bac.
6. Grad - Masters
7. Grad - Phd.
Frequency
Percentage
Cumulative P.
145
373
8
27.57
70.91
1.52
27.57
98.48
100
477
37
5
4
91.2
7.07
0.96
0.76
91.2
98.28
99.24
100
4
199
2
10
1
273
12
4
16
0.77
38.20
0.38
1.92
0.19
52.40
2.30
0.77
3.07
0.77
38.96
39.35
41.27
41.46
93.86
96.16
96.93
100.00
79
78
155
178
6
20
10
15.02
14.83
29.47
33.84
1.14
3.8
1.9
15.02
29.85
59.32
93.16
94.3
98.1
100
398
65
28
4
5
8
14
76.25
12.45
5.36
0.77
0.96
1.53
2.68
76.25
88.7
94.06
94.83
95.79
97.32
100
111
118
177
63
57
21.10
22.43
33.65
11.98
10.84
21.10
43.54
77.19
89.16
100.00
What is your ethnicity background?
1. White, non-Hispanic
2. Asian
3. Hispanic/Latino
4. American Indian or Alaskan Native
5. Black or African American
6. Native Hawaiian or Pacific Islander
7. Other
Shopping frequency on the website
1. More than once a week
2. Once a week
3. 2-3 times a month
4. Once a month
5. Less than once a month
47
With regards to respondents’ behavior and knowledge of the “cookie” computer
program, 72.69% of respondents reported that they had deleted “cookies” from their hard
drives.
Sixty percent of respondents reported they somewhat agree to strongly agree
with the statement “I know a cookie is a small text file that a website’s server places on
my computer’s web browser.”
Forty-nine percent of respondent reported they
somewhat agree to strongly agree with the statement “I know the cookie transmits
information back to the website’s server about my browsing activities on the site, such as
pages and content viewed, the time and duration of visits, search queries entered into
search engines, and whether a computer user clicked on an advertisement.”
Forty-four
percent of respondents reported they somewhat agree to strongly agree with the statement
“I know cookies also can be used to maintain data related to a particular individual,
including passwords or items in an online shopping cart”.
Lastly, 37% percent of
respondent reported they somewhat agree to strongly agree with the statement “I know
some websites allow other third-party companies to place cookies into customers' hard
drives to track shopping behaviors”.
Because the present study investigates online privacy issues in the context of the
respondent-defined retail environment, it is important to understand the respondents’
48
histories with the online retailers they reference throughout the study.
were asked to identify a retailer they frequently patronized online.
First, respondents
In the present study,
89.16% of respondents reported that they shopped at least once a month on the website
which they identified and 85.82% of respondents reported that they made purchases on
the website before.
The behaviors of making purchases on a specific website and
continually visiting the specific website suggests that an individual has developed a
certain level of trust toward the online retailer; the level of trust towards the online
retailer is an important component of this study.
Respondents’ Online Shopping Preferences.
“Clothing/shoes/accessories” is the biggest reported product category (70.17%).
Top reported product categories also include “Books/magazines” (22.89%),
“Entertainment” such as compact disks, videos, and concert tickets (14.26%), “Sporting /
Hobby goods” (13.88%), and “Consumer electronics” such as TV, VCR, stereo, and
cellular phones (12.01%) (Table 3.2).
49
Table 3. 2
Frequencies and Percentage of Most-Shopped Product Categories
Product Category
Freq. Percentage
1 Clothing/shoes/accessories
2 Books/magazines
374 70.17%
122 22.89%
3 Entertainment (compact disks, videos, concert tickets)
76
4 Sporting / Hobby goods
74
5 Consumer electronics (TV, VCR, stereo, cellular phones) 64
14.26%
13.88%
12.01%
6 Computer hardware or software
7 Other
50
33
9.38%
6.19%
8 Health and medical
9 Travel
10 Food/beverage/grocery
11 Financial services
16
14
8
2
3.00%
2.63%
1.50%
0.38%
For each product category, respondents indicated which websites they most
frequently shopped.
Under the category of “Clothing/shoes/accessories”, a total of 67
websites were reported.
Nordstrom.com (17.65%), Forever 21.com (13.37%) and
Victoria’s Secret.com (9.89%) were the top three most frequently shopped websites.
Under the category of “Book/Magazine”, a total of 13 websites were reported.
Amazon.com (74.59%), Ebay.com (12.30%) and Barns and Noble.com (4.10%) were the
top three most frequently shopped websites.
In addition, Amazon and EBay were also
reported as the top two websites in other categories, such as the categories of
“Entertainment” (Amazon, 48.68%; EBay, 27.63%), “Consumer Electronic” (Amazon,
50
43.75%; EBay, 31.25%) and “Computer Hardware or Software” (Amazon, 42.00%;
EBay, 22.00%). Tables displaying all “most frequently shopped” retailers mentioned by
respondents is provided in Appendix 4.
Scenario Designs
A between-subject experiment was conducted in which data were collected using an
online survey questionnaire.
In total, five versions of the online survey questionnaire
were developed (see Appendix 3).
treatments.
Each subject was randomly assigned to one of five
One treatment served as a control and did not include subject exposure to an
unsolicited behavioral tracking scenario.
The remaining four treatments included
subject exposure to an unsolicited behavioral tracking scenario.
The researchers developed four unsolicited behavioral tracking scenarios: (1) online
retailer does not have third-party cookie on its website and shares consumers’ personal
information only with affiliations, (2) online retailer does not have third-party cookie on
its website but shares consumers’ personal information with affiliates and other
third-party companies, (3) online retailer allows one third-party cookies on its website
51
and shares consumers’ personal information with affiliates and other third-party
companies, (4) online retailer allows fourteen third-party cookies on its website and
shares consumers’ personal information with affiliates and other third-party companies.
In order to ensure the manipulations were effective, the researchers presented the scenarios
to eight Oregon State University graduate students and asked them to evaluate how risky
they felt it was to patronize a specific retailer after they read the scenarios and were
provided with a description of cookie programs. Most of them (n=7) reported that they
sensed more risk when consumer information was shared with third-party companies and
when there were 14 third-party cookies (as opposed to 1 or zero third-party cookies)
inserted on their hard drives when they patronized the website.
These results provide
support for the effectiveness of the manipulation.
Measuring Instruments
The questionnaire consists of five sections.
In the first section, respondents were
asked questions about respondents’ online shopping behaviors with a trusted online
retailer.
Specifically, they were asked the name of the website at which they shop most
52
frequently, which product category best describes their shopping choices at the website,
their patronage frequency of the website, and whether they have made purchase on the
website before.
In the second section, respondents’ personal traits, including innovativeness,
commitment toward the website, and general privacy concerns, were measured.
items are shown in Table 3.3.
Scale
Seven-point Likert scales were used for measuring
consumers’ personal traits including innovativeness, commitment and general privacy
concern.
All were seven-point Likert scales anchored with “1 Strongly Disagree” and
“7 Strongly Agree.” The innovativeness scale, which contained five items, was adapted
from Raju’s (1991) consumer innovativeness scale.
After dropping the first item and
reverse coding the second to fifth item, the scale had good internal reliability (α=0.70)
and good convergent validity (factor loadings ranged from .50 to .78).
The consumer
commitment scale, which contained six items, was adapted from prior research (Ingram,
Skinner & Taylor, 2005).
The fourth item in the commitment scale was dropped for
analysis due to the low internal reliability.
This step resulted in the commitment scale
having excellent internal reliability (α=.83) and good convergent validity (factor
loadings ranged from .52 to .85).
The Privacy Segmentation Index (PSI) is a three-item
53
scale developed by Westin (1997).
It was used to group respondents to three segments
(privacy fundamentalist, privacy pragmatist and privacy unconcerned) according to how
respondents rated the three scale items.
Subjects who were not assigned to the control group were exposed to a third section.
In this section, each respondent was exposed to one of the four unsolicited behavioral
tracking scenarios presented earlier in this chapter.
The fourth section included questions measuring perceived benefit, risk and fairness
regarding shopping on the focal website.
All questions were measured using
seven-point Likert scales anchored with “1 Strongly Disagree” and “7 Strongly Agree.”
Similar to scales in section two, the scales in section four were examined with respects to
their internal consistency and convergent validity by using Cronbach’s alpha test and
exploratory factor analysis (EFA).
The results suggest that the measurement scales of
the present study had good internal reliability (αranged from .73 to .96) and good
convergent validity (all factor loading > .59) (Table 3.4).
Based upon the results of EFA,
three indicators with highest factor loadings from each scale were selected to perform the
structural equation model (SEM) for hypotheses testing.
Table 3. 3
Scale Items and Factor Analysis Results of Personal Trait Variables
Variable/ Source
Code
Consumer Commitment
comm1
(Ingram, Skinner & Taylor, comm2
2005)
comm3
comm4_r
comm5
comm6
Consumer Innovativeness
(Raju, 1991)
inno1*
inno2_r
inno3_r
inno4_r
inno5_r
Privacy Segmentation Index psi1
(Westin,1997)
psi2
psi3
Items
Factor % of variance
Loading explained
0.85
59.90
0.74
I am a loyal patron of this website.
I believe that my values are in line with the values of the
website.
I care about the fate of the website (i.e., stays in business). 0.70
I felt very little loyalty to the website.
*drop
I introduce/recommend this website to my friends.
0.52
I spend a lot of time on this website searching for or
0.71
purchasing products.
When I see a new or different brand on a shelf, I often pick *drop
it up just to see what it is like.
A new store or restaurant is not something I would be
0.50
eager to find out about.
I am very cautious in trying new/different products.
0.63
I would rather wait for others to try a new store or
0.78
restaurant than try it myself.
Investigating new brands of grocery and other similar
0.50
products is generally a waste of time.
Consumers have lost all control over how personal
NA
information is collected and used by companies.
Most businesses handle the personal information they
NA
collect about consumers in a proper and confidential way.
Existing laws and organizational practices provide a
NA
reasonable level of protection for consumer privacy today.
Cronbach’s
Alpha (α)
.83
52.48
.70
_
_
54
55
Section five included questions measuring attitudes toward the online retailer,
Specifically trust, pleasure-arousal-dominance moods and behavioral intentions.
All
questions were measured using seven-point Likert scales anchored with “1 Strongly
Disagree” and “7 Strongly Agree.” Scale items are displayed in Table 3.4.
The results suggest that the measurement scales of the present study had good
internal reliability (αranged from .73 to .96) and good convergent validity (all factor
loading > .59) (Table 3.4) Based upon the results of EFA, three indicators with highest
factor loadings from each scale were selected to perform the structural equation model
(SEM) for hypotheses testing.
Section six of the survey questionnaire included questions asking about
demographic characteristics of the respondent and their prior privacy invasion
experiences (see Appendix 3 Questionnaire).
Specifically, they were asked to indicate,
“What is your gender?”; “Age”; “What college you are attending?”; “What is your class
standing?”; and “What is your ethnicity background?”.
Furthermore, respondents were
provided with a list of possible online privacy invasion experiences and asked to indicate
which they had personally experienced.
Table 3. 4
Scale Items and Factor Analysis Results for Model Constructs, Measured in 7-point Likert Scale (1_Strongly Disagree/ 7_Strongly
Agree), r = Reversed Item
Factor
Variable/ Source
Perceived Risk (Pan
&Zinkhan, 2006)
Code
prisk1
prisk2
prisk3
Perceived Benefit about
pbenf1
Personalized Service &
Personalized Advertising,
(Revised from Yu & Cude, pbenf2
2009)
pbenf3
pbenf4a
pbenf5a
pbenf6a
Perceived Fairness (Oliver pfair1_r
& Swan, 1989)
pfair2_r
pfair3_r
Items
I think that buying a product from MyFavoriteStore.com would be
risky because of the possibility of unauthorized access to my
personal information.
I think that buying a product from MyFavoriteStore.com would be
risky because my personal information may be released to other
third-party.
I feel I don't have control over my personal information when I shop
at MyFavoriteStore.com.
I am pleased when I receive personalized advertising that has my
name on the title from an advertiser (company or brand) where I
never shopped before.
I am pleased when I receive personalized advertising that has my
name on the title from stores I have shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising tailored to my interests when I
surfing online.
I am pleased to see the advertisements of the brands I shopped when
I use my social network website (e.g., facebook, myspace).
I am pleased to see the personalized advertisements when when I go
to a news website (e.g., msn news, New York Times).
I am pleased to see the advertisements of the brands I shopped when
I use online email services (e.g., Gmail, hotmail, yahoo! mail).
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an unfair deal.
% of variance Cronbach’s Alpha
Loading
explained
(α)
0.91
83.67
.90
66.42
.90
88.97
.94
0.91
0.79
0.59
0.60
0.75
0.86
0.91
0.89
0.88
0.94
0.92
56
Factor
Variable/ Source
Trust (Pan & Zinkhan,
2006; Gefen, 2002)
Code
ptrst1
ptrst2
ptrst3a
ptrst4a
ptrst5a
ptrst6
ptrst7
ptrst8
Mood-Pleasure
mpreas1a
(Holbrook & Batra, 1987) mpreas2a
mpreas3a
mpreas4
mpreas5
mpreas6
Mood-Dominance
mdom1
(Holbrook & Batra, 1987) mdom2
mdom3a
mdom4a
mdom5a
mdom6
Mood-Arousal
marous1a
(Holbrook & Batra, 1987) marous2a
marous3
marous4
Repurchase Loyalty
loyal1a
(Chaudhuri and Ligas,2009) loyal2a
loyal3
loyal4a
Items
I can count on Myfavoritestore.com to protect my privacy.
Myfavoritestore.com is a trustworthy store.
I can count on Myfavoritestore.com to protect customers’ personal
information from unauthorized use.
Myfavoritestore.com can be relied on to keep its promise.
Promises made by Myfavoritestore.com are likely to be reliable.
I do not doubt the honesty of Myfavoritestore. Com
I expect that Myfavoritestore.com will keep promises they make.
I expect that Myfavoritestore.com has good intentions toward me.
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Attentive
Curious
Aroused
Excited
I intend to return to shop at MyFavoriteStore.com.
I will use this store the next time I want to make a purchase.
I probably won't switch to another website to make purchases.
I would recommend this store to my friends.
% of variance Cronbach’s Alpha
Loading
explained
(α)
0.85
0.88
0.89
79.39
.96
84.75
.96
77.92
.94
55.78
.73
80.13
.92
0.91
0.90
0.85
0.88
0.83
0.96
0.98
0.95
0.82
0.80
0.84
0.83
0.76
0.91
0.87
0.91
0.86
0.71
0.67
0.57
0.61
0.93
0.91
0.70
0.89
Note: a Selected items to perform the structural equation model analysis.
57
58
Data Collection
The present study consisted of an online between-subject survey.
The participants
were recruited either through selected class instructors in the Department of Design and
Human Environment, College of Business, and Department of Human Development and
Family Science or through OSU listserv email.
The survey URLs were distributed
through the instructors of selected classes via Blackboard and email in Oregon State
University (OSU) or through the managers of OSU email listserv.
during a three-week period from March 31, 2010 to April 19, 2010.
Data were collected
Once prospective
respondents clicked on the provided URL, they were directed to the online survey
questionnaire located on SurveyMonkey. Com.
Before the Web survey begins, informed consent forms were displayed, and the
purpose of the study was explained along with their roles and rights as a participant. After
each respondent indicated agreement with the informed consent, he/she was given access
the survey webpage. The first question of the survey (“If you are a student of Oregon
State University, please click on the top choice shown below.”) was designed to ensure
59
random assignment of each respondent to one of the five conditions by using randomized
choices function of the online-survey website.
The survey took respondents approximately 8-15 minutes to complete. The actual data
file that the researchers used for analysis did not have any personal identifiable
information of participants. After completing the survey, the respondents who would
received extra-credit points as incentives were directed to another survey URL for
providing their OSU Onid accounts (for the reason of separating personal identifiable data
from their responses); otherwise, a thank-you-for-your-participation page was be presented.
After the data collection finished, the collected data-sets were download from the survey
website in spreadsheet format and merged in the one data file for following analyses.
Data Analysis
In the present study, source of unsolicited behavioral tracking and level of
disseminating consumer information are exogenous variables. A dummy variable was
generated for the source of unsolicited behavioral tracking based on if there was a
description of identifying third-party cookie(s) usage in the designed scenarios.
A
60
categorical variable was generated for the level of disseminating consumer information
based on the description of how consumer information was shared, either internally or
externally, in the designed scenarios.
Perceived benefit of personalized advertisement,
perceived risk, perceived fairness, trust, pleasure, dominance, arousal and repurchase
loyalty are continuous variables.
The variables of personal traits (innovativeness,
commitment, and general privacy concern) were used to categorize respondents into
groups for moderation effect testing.
I used median-split to categorize the consumer
innovativeness (median=5) and commitment (median=4.8) as high and low group for
multiple group comparison.
In the aspect of general privacy concern, Westin’s (1997)
privacy segmentation index was used to categorize respondents into three groups:
privacy fundamentalist (PF), privacy pragmatist (PP), and privacy unconcerned (PU).
The respondents were categorized as Privacy Fundamentalists if they agreed
(strongly or somewhat, score above or equal 5 in a 7-point Likert scale) with the scale
item psi1 and disagreed (strongly or somewhat, score below or equal 3 in a 7-point Likert
scale) with scale item psi2 and psi3.
The respondents who disagreed (strongly or
somewhat) with the scale item psi1 and agreed (strongly or somewhat) with scale item
psi2 and psi3 were classified as Privacy Unconcerned.
Privacy Pragmatists are all other
61
respondents.
Thus, a categorical variable of different privacy segmentations were
generated for following analysis.
Descriptive statistics were used to summarize
demographic data and to examine if the data fulfill the assumptions of the statistic
methods used in the present study.
To assess the validity of measuring instruments, exploratory factor analysis (EFA)
was used.
To be considered as evidence of construct validity, factor loading should be
above.55 on one factor and not load higher than .30 on other factor (Brown, 2006).
Structural equation model was used to analyze the effects of unsolicited behavioral
tracking on consumers’ evaluations of online shopping experiences (perceived benefit,
risk and fairness) and attitudes (trust, pleasure, dominance, arousal, and repurchase
loyalty) toward trusted online retailer.
Multiple group comparison was used to test the
moderating effects of personal traits (innovativeness, commitment and general privacy
concern).
62
Chapter 4
Results
The first purpose of the present study was to investigate the impact of unsolicited
behavioral tracking on consumers’ evaluations of online shopping experiences (perceived
benefit, risk and fairness) and their attitudes toward trusted retailers (trust, moods and
repurchase loyalty). The second purpose of the present study was to examine the
moderating effects of personal traits (innovativeness, commitment toward the website, and
privacy segment) on the relationships among unsolicited behavioral tracking scenarios,
consumers’ evaluations of online shopping experiences, and attitudes toward online
retailers. In this chapter, results will be presented to test a model that addresses the two
research purposes. First, a preliminary analysis is presented.
Second, results of
confirmative factor analysis (CFA) are presented to ensure the measurement construct.
Third, structural equation model (SEM) results are presented.
moderation effect tests are presented.
Fourth, results from
Last, a summary of results is provided.
The
Descriptive statistic analysis was performed using the Stata 11 statistical package. The
63
CFA and SEM models were run using the Mplus version 5.21 statistical package (Muthen
& Muthen, 1998-2010).
Preliminary Analysis
Before testing the measurement construct and structural model, assumptions for
multivariate analysis, including multivariate normality and homocedasticity were
examined.
Kline (2005) suggests that there is a problem of multivariate normality when
a Kurtosis value is greater than ten. The Kurtosis values in this is study ranged from 1.95
to 2.55 (Table 4.1), which suggested that the data did not have serious problems
regarding the data normality.
Meanwhile, the skewness values (using a cut-off range
from +1 to -1) also confirmed the normality of the data.
Brown (2006) recommends a
sample size of ten observations for every one parameter estimated. The present study
estimated 57 parameters, which suggests a sample size of 570; therefore the sample size of
this study (n=532) is acceptable.
64
Table 4. 1
Mean, Standard Deviation, Skewness, Kurtosis and Cronbach’s Alpha of Indicators.
Construct Name
Indicators
Mean
S.D.
Skewness
Kurtosis
Alpha
Perceived Risk
PRISK1
PRISK2
4.04
4.27
1.69
1.64
.05
-.09
2.02
2.14
.90
PRISK3
4.33
1.71
-.16
2.11
Perceived
Benefit
PBENF4
PBENF5
PBENF6
3.30
3.08
3.03
1.60
1.59
1.57
.14
.30
.31
2.28
2.27
2.27
.92
Perceived
Fairness
PFAIR1_r
PFAIR2_r
PFAIR3_r
4.51
4.65
4.77
1.62
1.65
1.60
-.17
-.28
-.32
2.32
2.3
2.36
.94
Trust
PTRST3
PTRST4
PTRST5
3.94
4.11
4.18
1.56
1.46
1.47
.04
.03
-.09
2.40
2.55
2.52
.93
Pleasure
MPREAS1
MPREAS2
3.13
3.19
1.73
1.78
.44
.40
2.19
2.11
.97
MPREAS3
3.11
1.75
.45
2.20
MDOM3
MDOM4
3.64
3.59
1.76
1.76
.06
.12
1.99
2.03
MDOM5
3.63
1.79
.09
1.95
Arousal
MAROUS1
MAROUS2
3.98
4.35
1.75
1.62
-.18
-.41
2.09
2.50
.73
Repurchase
Loyalty
LOYAL1
LOYAL2
LOYAL4
4.74
4.44
4.50
1.76
1.72
1.84
-.36
-.15
-.27
2.16
2.18
2.07
.93
Dominance
Note: The scale items of indicators are shown in Table3.4
.93
65
To predict the relationship among the variables in the proposed model, I ran a
construct inter-correlation test (Table 4. 2).
The results suggest that perceived risk and
fairness are highly correlated to trust, pleasure, dominance, arousal and repurchase
loyalty.
Meanwhile, perceived benefit is highly correlated to trust, pleasure, arousal and
repurchase loyalty.
Table 4. 2
Means, Standard Deviation, and Construct Inter-Correlations
Mean S.D. Mpbenf Mprisk Mpfair_r Mptrst
Mmdom Mmpreas Mmarous Mloyal
Mpbenf 3.21 1.53 1.00
Mprisk
4.22 1.32 0.01
1.00
Mpfair
4.64 1.53 0.06
-0.61*** 1.00
Mptrst
4.10 1.34 0.17*** -0.49*** 0.49*** 1.00
Mmdom 3.45 1.52 -0.05
0.65*** -0.69*** -0.49*** 1.00
Mmpreas 2.90 1.53 0.23*** -0.41*** 0.40*** 0.42*** -0.49*** 1.00
Mmarous 3.45 1.28 0.24*** -0.21*** 0.24*** 0.28*** -0.26*** 0.70*** 1.00
Mloyal
4.49 1.58 0.11** -0.48*** 0.46*** 0.65*** -0.54*** 0.37*** 0.27*** 1.00
Note: N=532, Mpbenf= Perceived Benefit Scale; Mprisk=Perceived Risk Scale; Mpfair= Perceived
Fairness Scale; Mptrust=Trust Scale; mdom=Mood_Donminance Scale; Mmpreas=Mood_Preasure
Scale; Mmarous=Mood_Arousal Scale; Mloyal=Repurchase Loyalty Scale. * p<.05, **<.01, ***<.00
A scatter plot matrix was performed to ensure that linear relationships exist among the
variables (Figure 4. 1).
It provides an assessment of the linear relationships between
predicting the relationships between variables in the proposed model.
Figure 4. 1
66
indicates there are linear relationships between consumers’ evaluation of online shopping
(perceived risk, benefit and fairness) and their attitudes toward online retailers (trust,
pleasure, dominance, arousal and repurchase loyalty).
Specifically, perceived risk has
negative relationships with perceived fairness, trust, pleasure and loyalty. Meanwhile,
perceived fairness has positive relationships with trust, pleasure, arousal and repurchase
loyalty and a negative relationship with dominance.
Perceived
Risk
10
Perceived
Benefit
5
0
10
Perceived
Fa irness
5
0
10
5
Trust
0
10
Pleasure
5
0
10
Dom inance
5
0
10
Arousal
5
0
10
Repurchase
Lo yalty
5
0
0
5
100
5
100
5
100
5
100
5
1 00
5
100
5
10
Figure 4. 1 Scatter matrix of endogenous variables
67
68
Structural Equation Modeling
The proposed causal model was analyzed using structural equation modeling (SEM).
Kline (2005) suggests a two-step model building approach including two conceptually
distinct models: measurement model and path model.
Mplus version 5.21 (Muthen &
Muthen, 1998-2010) was used to analyze variance-covariance matrices.
Missing data
were estimated using Maximum Likelihood estimation, making it possible to use all
available information in the dataset.
Several model-fit indexes were used to assess
confirmatory factor analysis (CFA) and structural equation model fit (SEM).
Suggested
by Hu & Bentler (1999), the Comparative Fit Index (CFI) ≥ .95, Non-Normed Fit Index
(NNFI, also known as TLI) ≥ .95, root mean square error of approximation (RMSEA)
≤ .06, and Standardized root mean square residual (SRMR) ≤ 0.08) were used to as
cut-off lines in this study.
models.
χ2 difference test was used to compare the model fit among
The means, standard deviations and inter-correlations among indicators are
provided in Appendix 5.
69
Measurement Model
The measurement model consisted of eight latent constructs; there were three
indicators to estimate each latent construct, except the latent construct of arousal.
There
were two indicators selected to estimate arousal according to the EFA results presented in
Chapter 3.
The measurement model was estimated using the maximum-likelihood
method in the Mplus program.
A CFA was conducted and the one factor solution
provided a moderate fit, χ2 (202) = 398.49, p <0.01, CFI=.98, TLI=.98, RMSEA=.04,
SRMR= .03, which indicated a good fit between the model and the observed data.
Standardized parameter estimates shown in Figure 4. 2 suggested the latent variables
have been effectively measured by their respective indicators (factor loadings＞.71).
Un-standardized parameter estimates are provided in Table 4.3.
In addition, the
standardized estimated error correlations between latent factors were checked.
Brown
(2006) suggested that an error-correlation of latent factor that equals or exceeds .85 is
often used as the cutoff criterion for problematic discriminant validity.
As described in
Table 4.4, each error-correlation between latent factors did not exceed .85, which
indicates that the measurement construct has good discriminant validity.
70
.86***
eb
Perceived
Benefit
Perceived
Risk
ef
Perceived
Fairness
et
pbenf5
eb5
.89***
pbenf6
eb6
.90***
.80***
.88***
.93***
.93***
prisk1
er1
prisk2
er2
prisk3
er3
pfair1_r
ef1
pfair2_r
ef2
pfair3_r
ef3
ptrst3
et3
ptrst4
et4
ptrst5
et5
.86***
Trust
ep
Pleasure
ed
Dominance
ea
.93***
.91***
mpreas1
ep1
.96***
.99*** mpreas2
.94***
ep2
mpreas3
ep3
mdom3
ed3
.91***
.85*** mdom4
.93***
ed4
mdom5
ed5
marous1
ea1
marous2
ea2
.81***
Arousal
el
eb4
.91***
.91***
er
pbenf4
Repurchase
Loyalty
.71***
loyal1
el1
.93***
.89*** loyal2
.91***
el2
loyal4
el4
Figure 4. 2 Eight-factor measurement model of the present study.
Note: χ2 (202) = 398.49, p < .001; CFI = .98, TLI=.98, RMSEA = .04; SRMR= 0.03;
Standardized coefficients are shown. *p<.05, **p<.01, ***p<.001 (two-tailed)
71
Table 4. 3
Maximum Likelihood Parameter Estimates for Measurement Model
Parameter
Unstandardized
S.E.
Standardized
Perceived Risk prisk 1
Factor Loadings
1 na
-
0.91 ***
0.957 ***
0.885 ***
1 na
1.06 ***
1.03 ***
1 na
1.07 ***
0.03
0.04
0.04
0.04
0.03
0.90 ***
0.80 ***
0.86 ***
0.91 ***
0.89 ***
0.88 ***
0.93 ***
Fairness pfair3_r
Trust ptrst 3
Trust ptrst 4
Trust ptrst 5
1.04 ***
1 na
1.02 ***
1.00 ***
0.03
0.03
0.04
0.93 ***
0.86 ***
0.93 ***
0.91 ***
Dominance mdom 3
Dominance mdom 4
Dominance mdom 5
1.00 na
0.93 ***
1.03 ***
0.03
0.03
0.91 ***
0.85 ***
0.93 ***
Pleasure preas 1
Pleasure preas 2
Pleasure preas 3
Arousal marous1
Arousal marous 2
1.00 na
1.06 ***
0.99 ***
1.00 na
0.81 ***
0.02
0.02
0.09
0.96 ***
0.99 ***
0.94 ***
0.81 ***
0.71 ***
Loyalty loyal 1
Loyalty loyal 2
Loyalty loyal 4
1.00 na
0.94 ***
1.02 ***
0.03
0.03
0.93 ***
0.89 ***
0.91 ***
Perceived Risk prisk 2
Perceived Risk prisk 3
Perceived Benefit pbenf 4
Perceived Benefit pbenf 5
Perceived Benefit pbenf 6
Fairness pfair1_r
Fairness pfair2_r
Note: Prisk1-3 are the item codes of perceived risk scale, pbenf 4-6 are the item codes of
perceived benefit scale, pfair1_r-pfair3_r are the item codes of perceived fairness scale,
ptrst3-5 are the item codes of trust scale, mdom3-5 are the item codes of dominance scale,
preas1-3 are the item codes of pleasure scale, marous1-2 are the item codes of arousal
scale, loyal1,2,4 are the item codes of repurchase loyalty scale. Scale items are shown in
Table 3.4. *p<.05, **p<.01, ***p<.001 (two-tailed)
72
Table 4. 4
Error-correlations of Measurement Construct
Error-correlation
Unstandardized
S.E.
Standardized
ns
PBENF WITH PRISK
PFAIR WITH PRISK
<.01
-1.42 ***
0.10
0.13
<.01 ns
-0.65 ***
PFAIR WITH PBENF
PTRST WITH PRISK
PTRST WITH PBENF
PTRST WITH PFAIR
MDOM WITH PRISK
MDOM WITH PBENF
MDOM WITH PFAIR
0.14 ns
-1.00 ***
0.31 ***
0.96 ***
1.65 ***
-0.22 *
-1.68 ***
0.09
0.11
0.09
0.10
0.14
0.11
0.14
0.07 ns
-0.49 ***
0.17 ***
0.50 ***
0.67 ***
-0.10 *
-0.74 ***
MDOM WITH PTRST
MPREAS WITH PRISK
MPREAS WITH PBENF
MPREAS WITH PFAIR
-1.00 ***
-1.15 ***
0.51 ***
1.12 ***
0.12
0.13
0.11
0.12
-0.46 ***
-0.45 ***
0.22 ***
0.47 ***
MPREAS WITH PTRST
MPREAS WITH MDOM
MAROUS WITH PRISK
0.98 ***
-1.55 ***
-0.16 ns
0.11
0.14
0.12
0.44 ***
-0.58 ***
-0.08 ns
MAROUS WITH PBENF
MAROUS WITH PFAIR
MAROUS WITH PTRST
MAROUS WITH MDOM
MAROUS WITH MPREAS
0.44 ***
0.21 *
0.42 ***
-0.32 **
1.06 ***
0.11
0.11
0.11
0.13
0.14
0.23 ***
0.10 *
0.22 ***
-0.14 **
0.45 ***
LOYAL WITH PRISK
LOYAL WITH PBENF
LOYAL WITH PFAIR
-1.42 ***
0.26 *
1.26 ***
0.14
0.11
0.13
-0.56 ***
0.12 *
0.54 ***
LOYAL WITH PTRST
LOYAL WITH MDOM
LOYAL WITH MPREAS
LOYAL WITH MAROUS
1.46 ***
-1.55 ***
1.19 ***
0.55 ***
0.13
0.15
0.14
0.13
0.67 ***
-0.59 ***
0.44 ***
0.24 ***
Note: PBENF= perceived benefit, PRISK= perceived risk, PFAIR= perceived fairness,
PTRST=trust, MPREAS= pleasure, MDOM=dominance, MAROUS=arousal,
LOYAL=repurchase loyalty,*p<.05, **p<.01, ***p<.001 (two-tailed)
73
Structural Model
The proposed structural model (Figure 4. 3) specifies relationships among
unsolicited behavioral tracking, consumers’ evaluations of online shopping experiences
(perceived benefit, risk and fairness) and their attitudes toward trusted retailers (trust,
pleasure, dominance, arousal and repurchase loyalty).
Following the CFA, the
variance-covariance matrices were used to estimate the hypothesized structural model in
Mplus verion 5.21 (Muthen & Muthen, 1998-2010) with Maximum Likelihood
estimation.
Trust
Sources of Unsolicited
Behavioral Tracking
Perceived
Benefit
Perceived
Fairness
Level of Disseminating
Consumer Information
Pleasure
Perceived Risk
Dominance
Arousal
Repurchase
Loyalty
Figure 4. 3 Proposed causal model
The results of SEM model suggested a good model fit, χ2 (255) = 648.82, p<.01, CFI
= 0.97, TLI = .96, RMSEA = 0.05, SRMR = 0.07. No modification indices were used to
74
respecify the model as the model had a good fit. Standardized parameter estimates (β)
are shown in Figure 4.4; unstandardized parameter estimates (B) are provided in Table 4.5.
Direct Effects
Structural model results suggest that most model paths yield significant parameter
estimates.
However, in the context of the effects of unsolicited behavioral tracking (e.g.,
sources of unsolicited behavioral tracking and disseminating level of consumer
information) on perceived risk and benefit, only disseminating level of consumer
information has a significant effect on perceived risk (β=.46, p < .001).
These results
provide empirical support for Hypothesis 2b, but not for hypotheses 1a, 1b and 2a.
The results shown in Figure 4.4 suggest that perceived fairness has a significant
positive relationship with perceived benefit (β=.08, p < .05) and a significant negative
relationship with perceived risk (β=-.68, p < .001).
Thus, H3a and H3b are supported.
The paths from perceived fairness to consumers’ attitudes (trust, pleasure, dominance,
arousal, and repurchase loyalty) all received significant support. Thus, H4a to H4e were
supported.
A summary of direct effects can be found in Table 4.5.
ptrst3
R2=.26
.86***
Trust
pbenf4
pbenf5
pbenf6
pfair1_r
R =.004
Sources of Unsolicited
Behavioral Tracking
Perceived
Benefit
ns
pfair2_r
R2=.23
pfair3_r
.51***
Level of Disseminating
Consumer Information
R2=.17
.46***
-.68***
mpreas1
.96***
.99*** mpreas2
.94***
mpreas3
.48***
Perceived
Fairness
ns
Pleasure
.88*** .92*** .93***
.08*
ns
ptrst4
ptrst5
.86*** .91*** .89***
2
.93***
.91***
-.75***
R2=.56
2
R =.47
Dominance
Perceived Risk
.10*
mdom3
.91***
.85*** mdom4
.93***
mdom5
.56***
.91*** .90*** .80***
prisk1
prisk2
prisk3
marous1
R2=.01
.79***
Arousal
.73***
marous2
R2=.31
Repurchase
Loyalty
loyal1
.93***
.89*** loyal2
.90***
loyal4
Figure 4. 4 Structual Equation Model showing relationships between sources of unsolicited behavrioal tracking, level of disseminating consumer informaiton,
consumers’ evaluation of shopping experience (perceived benefit, risk and fairness) and attitude toward trusted online retailer (trust, pleasure, dominance, arousal,
and repurchase intention).
Note: χ2 (255) = 648.82, p<.01, CFI = .97, TLI = .96, RMSEA = .05, SRMR = .07. Standardized coefficients are shown. *p<.05, **p<.01, ***p<.001 (two-tailed).
The scale items are shown in Table 3.4.
75
76
Table 4. 5
Unstandardized Coefficients, Estimated Standard Errors, and Standardized Coefficients of
Direct Effects
Hypothesis Direct Effect Path
B
SE
Beta
H1a
COKIE3RD PBENF
0.12
0.17
0.04
H1b
H2a
H2b
H3a
H3b
H4a
H4b
COKIE3RDPRISK
SHARE_G PBENF
SHARE_GPRISK
PBENF PFAIR
PRISK PFAIR
PFAIR PTRST
PFAIR MPREAS
-0.27
0.05
0.96***
0.08*
-0.63***
0.48***
0.57***
0.17
0.11
0.12
0.04
0.04
0.04
0.05
-0.09
0.03
0.46
0.08
-0.68
0.51
0.48
H4c
H4d
H4e
PFAIR MDOM
PFAIR MAROUS
PFAIRLOYAL
-0.85***
0.10*
0.64***
0.05
0.05
0.05
-0.75
0.11
0.56
Note: COKIE3RD = third-party cookie tracking (source of uncolicited behavioral tracking),
SHARE_G = level of disseminating consumer information, PRISK= perceived risk, PBENF=
perceived benefit, PFAIR= perceived fairness, PTRST=trust, MPREAS= pleasure,
MDOM=dominance, MAROUS=arousal, LOYAL=repurchase loyalty, *p<.05, **p<.01,
***p<.001 (two-tailed)
Indirect Effects
It was hypothesized that consumers’ evaluation of shopping experience (perceived
benefit, risk and fairness) mediate the relationship between unsolicited behavioral tracking
and consumer attitudes (trust, pleasure, dominance, arousal and repurchase loyalty).
Third-party cookie tracking was not found to have indirect effect on consumers’ attitudes
toward the trusted retailer.
However, the level of disseminating consumer information
77
had a statistically significant indirect effect on consumers’ attitudes toward the trusted
retailer, including trust, pleasure, dominance, and their repurchase loyalty.
It is found
that the indirect effect of disseminating consumer information was mediated by perceived
risk and perceived fairness but not perceived benefit.
Table 4. 6
Unstandardized Coefficients(B), Estimated Standard Error(S.E.), and Standardized
Coefficients(β) of Indirect Effects
Parameters
B
S.E.
β
SHAREPRISKPFAIRPTRST
-0.29***
0.05
-0.16***
SHAREPBENFPFAIRPTRST
0.00
0.00
0.00
SHARE PRISKPFAIRMPREAS
-0.34***
0.05
-0.15***
SHARE PBENFPFAIRMPREAS
0.00
0.01
0.00
SHAREPRISKPFAIRMDOM
0.51***
0.07
0.23***
SHAREPBNFPFAIRMDOM
0.00
0.01
0.00
SHAREPRISKPFAIRMAROUS
-0.06
0.03
-0.03
SHAREPBENFPFAIRMAROUS
0.00
0.00
0.00
SHAREPRISKPFAIRLOYAL
-0.39***
0.06
-0.18***
SHAREPBENFPFAIR LOYAL
0.00
0.01
0.00
COKIE3RDPRISKPFAIRPTRST
0.08
0.05
0.03
COKIE3RDPBENFPFAIRPTRST
0.01
0.01
0.00
COKIE3RD PRISKPFAIRMPREAS
0.10
0.06
0.03
COKIE3RD PBENFPFAIRMPREAS
0.01
0.01
0.00
COKIE3RDPRISKPFAIRMDOM
-0.14
0.09
-0.04
COKIE3RDPBNFPFAIRMDOM
-0.01
0.01
0.00
COKIE3RDPRISKPFAIRMAROUS
0.02
0.01
0.01
Indirect Effect Paths
Level of disseminating consumer information (SHARE)
Source of unsolicited behaviroal tracking (COKIE3RD)
78
Parameters
B
S.E.
β
COKIE3RDPBENFPFAIRMAROUS
0.00
0.00
0.00
COKIE3RDPRISKPFAIRLOYAL
0.11
0.07
0.03
COKIE3RDPBENFPFAIR LOYAL
0.01
0.01
0.00
Indirect Effect Paths
Note: PRISK= perceived risk, PBENF= perceived benefit, PFAIR= perceived fairness,
PTRST=trust, MPREAS= pleasure, MDOM=dominance, MAROUS=arousal,
LOYAL=repurchase loyalty. *p<.05, **p<.01, ***p<.001 (two-tailed)
Test of Moderation Effects
In order to investigate moderating effects of personal trait factors such as
innovativeness, commitment toward the trusted retailer and privacy segment, the current
study used the multiple-group comparison to test the moderation effect by following the
steps for examination of moderators as suggested by Muthén and Muthén (2009).
The
total sample was divided into high and low groups according to the medians of individual
trait factors (the median of innovativeness was 5 and the median of commitment was 4.8).
First, I estimated high-group and low-group (three groups for privacy segment)
simultaneously without measurement invariance (freely estimated loadings and intercepts)
and called it Model A.
Second, I ran a Model B for constraining the factor loadings but
freely estimated the intercepts.
Third, I constrained both factor loadings and intercepts
79
and called it Model C.
According to Table 4.7, the results of χ2 difference comparisons
between pairs of given models provided evidence that there is significant difference
between Model A and Model B for innovativeness groups and between Model B and
Model C for commitment groups.
The significant results validate the moderator effects
of innovativeness and commitment toward online retailer on the proposed model,
however, no significant results to support privacy segment as a moderator in the proposed
model.
Thus, H5a and H5b were suppported but H5c was not.
Table 4. 7
Structural Equations Results for Moderating Effect Models
Moderator
Variable
Δχ2
Model
χ2
df
CFI
RMSEA SRMR
(df)
p
<.01
Innovativeness
A
B
998.12
1029.39
510 .96
525 .96
.06
.06
.08
.08
31.3(15)
Commitment
B
C
981.60
1053.57
525 .96
548 .96
.06
.06
.08
.09
71.98(23) <.01
Privacy Segment
B
C
1362.788 795 .95
1391.736 825 .95
.06
.06
.08
.08
28.95(30) ns
80
Moderating effect of innovativeness
Figure 4.5 and Table 4.8 indicate that the effect of level of disseminating consumer
information had a relatively stronger relationship with perceived risk (Bhigh-inno=.98, S.E.
=.16; Blow-inno=.93, S.E.=.17) and perceived risk had a relatively stronger negative
relationship with perceived fairness (Bhigh-inno=-.68, S.E. =.06; Blow-inno=-.55, S.E.=.05) in
the higher-inno group.
This means that the higher-inno group would perceive more risk
and less fairness than the lower-inno group when they find out the online retailer is
disseminating their information to others.
Meanwhile, the perceived fairness also
influences higher-inno/lower-inno groups’ attitudes differently.
The present study
includes the three dimensions of attitude: cognitive (trust), affective (pleasure, dominance,
arousal) and behavioral (repurchase loyalty).
Perceived fairness has a relatively
stronger relationship with trust (cognitive attitude) in the higher-inno group (Bhigh-inno=.51,
S.E. =.06; Blow-inno=.47, S.E.=.06) and a relatively stronger relationship with affective
attitudes-- pleasure (Bhigh-inno=.51, S.E. =.07; Blow-inno=.65, S.E.=.08), dominance
(Bhigh-inno=-.82, S.E. =.06; Blow-inno=-.87, S.E.=.07) and arousal (Bhigh-inno=.02, S.E. =.07;
81
Blow-inno=.20, S.E.=.08) and with repurchase loyalty (behavioral intention) in the
lower-inno group.
Table 4. 8
Structural Equations Results for Hypotheses 5a
Baseline Model
Moderating Model_Innovativeness
Low
Path
B
S.E.
B
High
S.E.
B
S.E.
COKIE3RD PBENF
0.12
0.17
0.09
0.21
0.16
0.26
COKIE3RDPRISK
-0.27
0.17
-0.20
0.24
-0.34
0.25
SHARE_G PBENF
0.05
0.11
0.05
0.14
0.05
0.17
0.96***
0.12
0.93***
0.17
0.98***
0.16
PBENF PFAIR
0.08*
0.04
0.08
0.05
0.10
0.05
PRISK PFAIR
-0.63***
0.04
-0.55***
0.05
-0.68***
0.06
PFAIR PTRST
0.48***
0.04
0.47***
0.06
0.51***
0.06
PFAIR MPREAS
0.57***
0.05
0.65***
0.08
0.51***
0.07
-0.85***
0.05
-0.87***
0.07
-0.82***
0.06
0.10*
0.05
0.20*
0.08
0.02
0.07
0.12
0.17
0.67***
0.07
0.63***
0.07
SHARE_GPRISK
PFAIR MDOM
PFAIR MAROUS
PFAIRLOYAL
Note: COKIE3RD = third-party cookie tracking (source of uncolicited behavioral tracking),
SHARE_G = level of disseminating consumer information, PRISK= perceived risk, PBENF=
perceived benefit, PFAIR= perceived fairness, PTRST=trust, MPREAS= pleasure,
MDOM=dominance, MAROUS=arousal, LOYAL=repurchase loyalty. *p<.05, **p<.01,
***p<.001 (two-tailed)
82
Lower_Inno
Trust
Sources of Unsolicited
Behavioral Tracking
ns
ns
Level of Disseminating
Consumer Information
Perceived
Benefit
.47***
ns
Perceived
Fairness
ns
.93***
Perceived Risk
.65***
Pleasure
-.87***
-.55***
.20*
Dominance
.67***
Arousal
Repurchase
Loyalty
Trust
Sources of Unsolicited
Behavioral Tracking
ns
ns
Perceived
Benefit
.51***
ns
Perceived
Fairness
ns
Level of Disseminating
Consumer Information
.98***
Perceived Risk
-.68***
.51***
Pleasure
-.82***
ns
Dominance
.63***
Higher_Inno
Arousal
Repurchase
Loyalty
Figure 4. 5 Unstandarized coefficients between low / high innovativeness groups
Note: (1) Lower-inno group: χ2 (255) = 534.854, p < .001; CFI = .95; RMSEA = .06; (2)
Higher-inno group: χ2(255) = 463.26, p < .001; CFI = .95; RMSEA = .06; (3)*p<.05,
**p<.01, ***p<.001 (two-tailed)
83
Moderating effect of commitment toward trusted online retailer
Figure 4.6 and Table 4.9 indicate that the effect of level of disseminating consumer
information had a relatively stronger relationship with perceived risk (Bhigh-comm=.93, S.E.
=.14; Blow-comm=1.05, S.E.=.13) and perceived risk has a relatively stronger negative
relationship with perceived fairness (Bhigh-comm=-.61, S.E. =.04; Blow-comm=-.67, S.E.=.05)
in the lower-commitment group.
Which means the lower-commitment group would feel
more risky and unfair than higherer-commitment group when they find out online retailer
dissemianting their information to others.
Meanwhile, the perceived fairness also
influence higher-commitment / lower-commitment groups’ attitudes differently.
Table
4.9 indicates that perceived fairness has relatively stronger relationship with trust in
lower-commitment group (Bhigh-comm=.42, S.E. =.06; Blow-comm=.53, S.E.=.05) and
relatively stronger relationship with pleasure (Bhigh-comm=.63, S.E. =.07; Blow-comm=.50,
S.E.=.06) and dominance (Bhigh-comm=-.90, S.E. =.06; Blow-comm=-.79, S.E.=.05) in the
higher-commitment group.
It is found that perceived fairness had a relatively stronger
relationship with repurchase loyalty (behavioral intention) in the lower-commitment
group.
84
Table 4. 9 Structural Equations Results for Hypotheses 5b
Baseline Model
Moderating Model_Commitment
Low
Path
B
S.E.
B
High
S.E.
B
S.E.
COKIE3RD PBENF
0.12
0.17
0.02
0.22
0.20
0.25
COKIE3RDPRISK
-0.27
0.17
-0.32
0.22
-0.22
0.26
SHARE_G PBENF
0.05
0.11
0.00
0.12
0.11
0.13
SHARE_GPRISK
0.96***
0.12
1.05***
0.13
0.93***
0.14
PBENF PFAIR
0.08*
0.04
0.07
0.06
0.09
0.05
PRISK PFAIR
-0.63***
0.04
-0.67***
0.05
-0.61***
0.04
PFAIR PTRST
0.48***
0.04
0.53***
0.05
0.42***
0.06
PFAIR MPREAS
0.57***
0.05
0.50***
0.06
0.63***
0.07
PFAIR MDOM
-0.85***
0.05
-0.79***
0.05
-0.90***
0.06
PFAIR MAROUS
0.10*
0.05
0.14*
0.07
0.07
0.07
PFAIRLOYAL
0.12
0.17
0.67***
0.06
0.62***
0.07
Note: COKIE3RD = third-party cookie tracking (source of uncolicited behavioral tracking),
SHARE_G = level of disseminating consumer information, PRISK= perceived risk, PBENF=
perceived benefit, PFAIR= perceived fairness, PTRST=trust, MPREAS= pleasure,
MDOM=dominance, MAROUS=arousal, LOYAL=repurchase loyalty. *p<.05, **p<.01,
***p<.001 (two-tailed)
85
Trust
Sources of Unsolicited
Behavioral Tracking
ns
Perceived
Benefit
.53***
ns
ns
Perceived
Fairness
ns
Level of Disseminating
Consumer Information
1.048***
Perceived Risk
.49***
Pleasure
-.79***
-.67***
.14*
Lower_COMM
.67***
Dominance
Arousal
Repurchase
Loyalty
Trust
Sources of Unsolicited
Behavioral Tracking
ns
ns
Level of Disseminating
Consumer Information
Perceived
Benefit
Perceived
Fairness
ns
.93***
.42***
ns
Perceived Risk
-.61***
Higher_COMM
.63***
Pleasure
-.90***
ns
Dominance
.62***
Arousal
Repurchase
Loyalty
Figure 4. 6 Unstandarized coefficients between low /high commitment groups
Note: (1) lower-commitment group:χ2 (255) = 508.13, p < .001; CFI = .95; RMSEA
= .06; (2) higherer-commitment group: χ2 (255) = 454.901, p < .001; CFI = .97; RMSEA
= .06; (3) *p<.05, **p<.01, ***p<.001 (two-tailed)
86
Summary
The first hypothesis predicted that the presence of third-party behavioral tracking
will decrease consumers’ perceived benefit and increase perceived risk.
Contrary to
expectations, third-party behavioral tracking does not significantly influence consumers’
perceived benefit and perceived risk.
Thus, hypothesis 1 is not supported.
The results of structural equation model indicate that the level of disseminating
consumer’s information has a significantly positive relationship with perceived risk (β
=.46, p <.001).
However a significantly negative relationship with perceived benefit
was not found. Thus, only hypothesis 2b is supported.
Meanwhile it was found that
perceived benefit and risk significantly predict perceived fairness (β=.08, p <.05; β
=-.68, p <.001), thus hypothesis 3a and 3b are also supported.
With regard to the influence of perceived fairness on consumers’ attidues toward
trusted retailers, the results of SEM suggested that a higher level of perceived fairness has
a positive relationship with (a) trust (β=.51, p <.001), (b) pleasure (β=.48, p <.001), (d)
arousal (β=.10, p <.05) (e) repurchase loyalty (β=.56, p <.001) and a negative
87
relationship with (c) dominance (β=-.75, p <.001).
Thus, hypothesis 4a to 4e are
supported.
The current study aimed to test if consumers’ personal traits (innovativeness and
commitment toward online retailer) would moderate the relationships among unsolicited
behavioral tracking, consumers’ evaluations of online shopping experience, and their
attitudes toward their trusted online retailers.
The present study followed the steps of
multiple-group comparison suggested by Muthen and Muthen (2009) and the results of
suggest that innovativeness and consumers’ commitment toward online retailers
moderates the relationships in the proposed model.
supported.
Thus, hypotheses 5a and 5b are
However, there is no significant evidence found to support privacy segment
as a moderator.
As a result, hypothesis 5c is not supported.
For the moderating effects
of innovativeness, it is found that the higher-inno group would perceive more risk and
less fairness than the lower-inno group when they find out the online retailer is
dissemianting their information to others.
Meanwhile, the perceived fairness also
influences higher-inno/lower-inno groups’ attitudes differently.
The present study
includes the three dimensions of attitude: cognitive (trust), affective (pleasure, dominance,
arousal) and behavioral (repurchase loyalty).
Perceived fairness has a relatively
88
stronger relationship with trust (cognitive attitude) in the higher-inno group and a
relatively stronger relationship with affective attitudes (pleasure, dominance and arousal)
and with repurchase loyalty (behavioral intention) in the lower-inno group.
For the moderating effects of commitment toward online retailer, it is found the
lower-commitment group would feel more risky and unfair than higherer-commitment
group when they find out online retailer dissemianting their information to others.
Meanwhile, the perceived fairness also influence higher-commitment /
lower-commitment groups’ attitudes differently.
The perceived fairness has relatively
stronger relationship with trust and repurchase loyalty in lower-commitment group and
relatively stronger relationship with pleasure and dominance in the higher-commitment
group.
89
Chapter 5
Discussion and Conclusion
Drawing from Social Contract Theory (SCT), the purpose of the present study is to
investigate the effects of unsolicited tracking on consumers’ evaluations of online
shopping (perceived benefit, risk and fairness) and their attitudes (trust, moods and
repurchase intention) toward trusted online retailers.
The effects of unsolicited
behavioral tracking were manipulated as (1) different sources (online retailer versus
third-party advertiser) and (2) different levels of disseminating consumers’ personal
information (internally versus externally) in the designed scenarios in this study.
The
main difference of the present study from the prior consumer privacy studies is the
present study investigates the influence of unsolicited behavioral tracking on consumers’
responses toward their “trusted” retailers.
That is, the study results may more closely
reflected the realities of online shopping situations that previous studies which did not
account for the established relationship between consumers and retailers.
In addition,
the study also aimed at investigating the roles of personal traits such as innovativeness,
commitment and general privacy concern as moderators.
This chapter describes the
90
theoretical and applied implications of the results and the contributions of this study.
Research limitations are also addressed, as well as suggestions for future research.
Theoretical Implications
The unsolicited behavioral tracking where marketers collect information from
consumers without their awareness is considered by many researchers to be a breach of
an implied social contract and may harm consumer trust and patronage (Culnan, 1995;
Milne & Gordaon, 1993; Miyazaki, 2008; Poddar, Mosteller & Ellen, 2009).
In an
online shopping context, consumers’ perceived risk of behavioral tracking reflects their
concerns of potential privacy invasion associated with retailers’ online information
practices (Ha, 2004; Malhotra, et al, 2004; Turow, et al, 2009; ).
The present study
provides evidence to support that the level of disseminating behavioral information
collected from consumers significantly increases consumers’ perceived risk, hence
reducing their perceived fairness on their evaluations of online shopping experiences.
Concurrent with prior research results, perceived risk is raised when consumers feel
uninformed by marketers about how their information is collected and used (Lanier &
91
Saini, 2008; Nowak & Phelps, 1995; Youn, 2009).
However, contrary to my prediction,
no significant result of the effects of third-party cookie tracking on consumers’
evaluations of shopping experiences was found.
Even though several questions in the
questionnaire included explainations as to what cookies are, many respondents still
seemed to not be able to link the third-party-cookie tracking with personalized
advertising. This is speculated form the result of the perceived benefit not being
influenced by the designed third-party-cookie tracking scenarios (see Figure 4.4).
Another possible reason to explain this may be due to the high cookie-deleting
experience among the respondents (72.69%).
It is speculated that respondents care less
about the third-party cookies tracking because they thought deleting cookies would
prevent their personal information from the potential privacy invasion.
As a result, the
need of interviewing consumers why they delete cookies and how they use different
techniques to prevent online unsolicited behavioral tracking is warranted in future
research.
As shown in Table 4.6, the significant indirect effects of the level of disseminating
consumer information on their attitudes toward trusted retailers suggest that consumers’
perceived risk and fairness mediated the relationship between the unsolicited behavioral
92
tracking and consumers’ attitudes toward retailers.
Furthermore, the applied SCT is
validated by consumers’ perceived fairness evaluations of their relationships with trusted
online retailers.
More specifically, the results demonstrated a positive relationship
between perceived fairness and consumers’ trust, pleasure, arousal and repurchase loyalty
and a negative relationship with dominance toward trusted online retailers.
This is
consistent with the findings of the literature, in that the influence of privacy concern on
consumers’ trust and behavioral intentions seems to be mediated by perceived fairness of
marketing strategies (Ashworth & Free, 2006; Bies, 1993; Caudill & Murphy, 2000;
Culnan & Armstrong, 1999; Son & Kim, 2008).
The result of multiple-group comparison suggests that cosumers’ personal traits such
as innovativeness and commitment moderate the relationships among the proposed model;
however, it is hard to draw a clear picture about how the groups are different by
comparing the co-efficient differences of the factor loadings, since they are fairly similar
(see Figure 4.5 and Figure 4.6).
One possible reason of this may be because the present
study used median-split method to divide respondents as high/low groups according their
scores of innovativeness and commitment scales.
Median-split method is known as a
convenient way to split respondents into two groups for moderating effects of testing.
93
However, the disadvantage of median split is that it also forces the despondences of
middle scores to fall into either the high or low group.
In the context of innovativeness
and commitment toward online retailers, considering another dividing method, such as
categorizing respondents as belonging to a high-innovative group (high-commitment
group) if their scores of innovativeness (commitment) are above the mean score one
standard deviation and categorizing respondents as low-innovative group
(low-commitment group) if their scores of innovativeness (commitment) are below the
mean score one standard deviation may be a better way to test the significance of
moderating effects.
Due to the limitation of big sample size of structure equation
modeling, the present study could not perform multiple group comparisons by using the
alternative dividing method.
Practical Implications
Scholars had suggested that trust in a marketer can significantly mitigate perceived
risk and ultimately a customer’s reluctance in releasing personal information (Luo, 2002;
Malhotra et al, 2004).
The findings of the present study suggest that consumers are
94
concerned about their privacy with respect to the level of disseminating their personal
information for secondary use even by their trusted retailers. Consistent with other
information privacy studies (Dommeyer & Gross, 2003; Earp, et al, 2005; Turow, et al,
2009), this finding suggests there is a discrepancy between online shoppers and online
retailers regarding the information collected from online shoppers since, currently,
sharing of information collected from customers within affiliates is a fairly common
practice in the marketing field.
The findings do suggest that online retailers should be
cautious about their information practices since they may lose consumers’ trust if
consumers perceived it is unfair to them.
The present study used scenarios to describe the information practices, however,
research showed that it is less likely that consumers will attend to, process, understand,
and remember cookie disclosures from long and hard-to-understand privacy policies,
which are prevalent within the current online retail environment (Milne, Culnan & Greene,
2006).
As more and more new techniques are developed to profile consumers for
secondary usages such as providing personalized advertisements and prodcuts, consumers
may not be able to protect their information privacy.
With regard to public policy
maker, the present research provides empirical results to address the young online
95
shoppers’ (college students’) need of preventing their information collected by trusted
online retailers from secondary usage.
Limitations of the Study
This study aimed to explore the effect of unsolicited behavioral tracking on
consumers’ evaluations of shopping experiences and their attitudes toward trusted online
retailers. As with any research, the study should be considered in light of its limitations.
First, the present study used manipulated scenarios as a forced exposure setting.
Forced exposure to the statements of unsolicited third-party tracking and the
dissemination practices of consumers’ information was used, while only few consumers
may actually notice this information when they shop online.
As a result, the present
approach may exaggerate the effect of unsolicited tracking practices since the
information of online behavioral tracking and related practices is not so salient to
consumers in the current online environment.
Second, due to the sample size, though significant moderating effects of personal
traits (innovativeness and commitment toward online retailer) were accounted for, the
96
study could not draw a definitive conclusion about implications regarding the moderator
effects of the personal traits.
Third, the convenience sample from Oregon State University used in this study may
constrain the generalizability of the results found in this study.
characteristics are described in Table 3.1.
The respondents’
Since the majority of respondents are female
(70.91%), 18-25 years old (91.2%), Caucasian (76.25%), shop for clothing/ shoes/
accessories online (70.17%), some results found in this study may be a function of gender,
age, ethnicity, product category and geographic area.
However, at the same time that it
suggests that consumers’ privacy concern is context specific (FTC, 2009; Phelps, et al,
2000), thus, the present results may better describe the consumers’ with these specific
characteristics.
Suggestions for Future Research
There are several suggestions I would make for the future research.
The majority
of respondents in the present study (72.69%) reported that they had the experiences of
deleting cookies from their Internet browser before.
As a result, the need of
97
interviewing consumers about why they delete cookies and how they use different
techniques to prevent online unsolicited behavioral tracking is warranted in future
research.
Second, a larger sample size is recommended for using multiple group
comparison in SEM to test the moderators.
Third, cookie usage has been a complicated
issue for online shoppers; consumers seem to be aware that allowing cookies from their
trusted websites enables to make purchases or perform transactions on the websites.
However, they may not want to do business with or release their browsing behaviors to
third-party companies.
It is suggested, in the future, that using explicit and
easily-understandable materials such as video clips to help respondents comprehend the
mechanism behind cookie usage and behavioral marketing before collecting their
responses.
Forth, the repeat-measure method is suggested (for example, over a period of
three months) to investigate if the significance of the effect of disseminating consumer
information will decrease or increase over time.
98
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APPENDICES
118
Appendix 1
The 3rd Party Cookies Placement Among the Top 30 Apparel/ Accessory Websites
No. of 3rd party
2009
Websites
Ranking
1
Involved Third Party
cookies
Victoria’s secret
7
Microsoft (Atlas Technology),
Google (DoubleClick)
MediaMath
Yahoo! Ad Network
Right Media (Yahoo!)
Google Analytics*
AppNexus*
2
L.L.Bean Inc.
0
NA
3
Gap Inc. Direct
0
NA
4
Zappos.com
2
Google (DoubleClick)
Google Analytics
5
Northstrom Inc.
0
NA
6
Redcast USA
1
Google Analytics
7
The Neiman Marcus
9
Channel Intelligence
Group Inc.
Google (DoubleClick)
[x+1]
Undertone Networks
24/7 Real Media
Rocket Fuel
Turn
Right Media (Yahoo!)
AppNexus
8
Saks Direct
4
Channel Intelligence
RichRelevance
Google (DoubleClick)
Right Media (Yahoo!)
9
Nike. com
1
Omniture
10
J Crew.com
1
Omniture
11
Footlocker.com
0
NA
119
No. of 3rd party
2009
Websites
Ranking
12
Involved Third Party
cookies
American Eagle
13
Outfitters (ae.com)
Google Analytics
aCerno (Akamai)
Google (DoubleClick)
Right Media (Yahoo!)
Adify (100+ networks)
Traffic Marketplace
Microsoft (Atlas Technology)
ValueClick (Fastclick)
ASDAQ (ContextWeb)
Undertone Networks
interCLICK
AdBrite
SpecificMEDIA
13
Urban Outfitters Inc
12
iPerceptions
Baynote
aCerno (Akamai)
Right Media (Yahoo!)
Adify (100+ networks)
Traffic Marketplace
Google (DoubleClick)
Microsoft (Atlas Technology)
ValueClick (Fastclick)
ASDAQ (ContextWeb)
Undertone Networks
interCLICK
14
Abercrombie
1
Google Analytics*
1
Google Analytics*
13
Google (DoubleClick)
& Fitch
15
Orchard Brands
Corp.
16
Spiegel
Brand Inc.
aCerno (Akamai)
120
No. of 3rd party
2009
Websites
Ranking
Involved Third Party
cookies
ValueClick (Fastclick)
Right Media (Yahoo!)
Traffic Marketplace
Undertone Networks
interCLICK
Adconion
AdBrite
Tribal Fusion
Adify (100+ networks)
Rubicon Project
Pubmatic
17
Coldwater Creek
1
Google Analytics
1
Google Analytics
Inc.
18
Sierra Trading Post
Inc.
19
Yoox Group
1
Google Analytics
20
Eddie Bauer
4
AddThis
CoreMetrics
Media6degrees
AdBrite
21
Ralph Lauren
2
Media LLC
22
Shoebuy.com Inc.
Microsoft (Atlas Technology)
Google Analytics*
7
Dotomi
Akamai
ValueClick (Fastclick)
Undertone Networks
Google (DoubleClick)
Adify (100+ networks)
Collective Media
23
eBags.com
1
Google Analytics
24
Fingerhut Direct
14
[x+1]
121
No. of 3rd party
2009
Websites
Ranking
Involved Third Party
cookies
Marketing Inc.
Google Analytics*
Right Media (Yahoo!)
Google (DoubleClick)
Rubicon Project
aCerno (Akamai)
CoreMetrics
Traffic Marketplace
ValueClick (Fastclick)
Undertone Networks
interCLICK
Adconion
AdBrite
Tribal Fusion (Exponential)
25
Charming
0
NA
6
Google (DoubleClick)
Shoppes.com
26
The Talbots Inc.
aCerno (Akamai)
Microsoft (Atlas Technology)
Advertising.com (AOL)
Right Media (Yahoo!)
Turn
27
Ann Taylor Stores
Corp.
14
Google Analytics
Microsoft (Atlas Technology)
Advertising.com (AOL)
Tribal Fusion (Exponential)
aCerno (Akamai)
Right Media (Yahoo!)
Traffic Marketplace
ValueClick (Fastclick)
Google (DoubleClick)
Undertone Networks
122
No. of 3rd party
2009
Websites
Ranking
Involved Third Party
cookies
interCLICK
Adconion
AdBrite
SpecificMEDIA
28
The Orvis Co. Inc.
7
Akamai
Dotomi
Undertone Networks
Google (DoubleClick)
Adify (100+ networks)
Collective Media
Rubicon Project
29
Bluefly Inc.
7
Google Analytics
Turn
Baynote
Akamai
Dotomi
Right Media (Yahoo!)
Google (DoubleClick)
30
Onlineshoes.com
0
NA
123
RESEARCH PROTOCOL
The effects of unsolicited behavioral tracking on consumers’ evaluation of their
online shopping experiences and attitudes toward trusted online retailers
Version.3, Apr. 6th, 2010
Principal Investigator:
Leslie D. Burns, Design and Human Environment
Co-Investigator:
TunMin (Catherine) Jai, Design and Human Environment
1.
Brief Description
The purpose of this research is to examine the effects of unsolicited behavioral
tracking on consumers’ evaluation of their online shopping experiences and attitudes
toward trusted online retailers. Nowadays, most online marketers and third-party
advertisers put a small text file called “cookies” into the internet browsers within
consumers’ computer drives for helping them distribute personalized advertising based
upon their browsing behaviors. However, such unsolicited behavioral tracking where
marketers collect information from consumers without their awareness is consider by
many researchers to be a breach of an implied social contract and may harm consumer trust
and patronage (Culnan, 1995; Milne & Gordaon, 1993; Miyazaki, 2008; Poddar, Mosteller
& Ellen, 2009). Drawing from social contract theory, the present study will examine how
consumers’ evaluations of online shopping experiences (perceived benefit, risk and
fairness) and attitudes (trust, mood, and repurchase loyalty) toward trusted online apparel
retailers are impacted when exposed to information about unsolicited behavioral tracking
(from retailer or third-party advertiser). To achieve the research goal, four unsolicited
behavioral tracking scenarios are created for between-subject experiments:
(1) online retailer allows zero third-party cookie placement on their website and shares
consumers’ personal information only with their corporate family,
(2) online retailer allows zero third-party cookie placement on their website and shares
consumers’ personal information with not only corporate family but other companies,
(3) online retailer allows one third party cookies on its website to collect consumers’
information and shares consumers’ personal information only with their corporate
family
124
(4) online retailer allows one third party cookies on its website to collect consumers’
information and shares consumers’ personal information with not only corporate family
but other companies (see Appendix 2).
The results from this research will be used to complete the dissertation requirement
and will be presented to the graduate committee. The findings of the research will
contribute by building on theory in consumer online shopping behavior field. Meanwhile,
the results will also provide empirical evidence to help legislators make informed policy
decisions since the U.S. congress is currently reviewing the needs to establish a law to
regulate online retailers’ behavioral marketing practices. It is intended that the findings of
this research will be submitted to peer-refereed academic journals for publication.
2.
Background and Significance
Behavioral targeting under nonconsensual tracking practice has rapidly become
one of the most effective, yet also controversial techniques to reach consumers. Through
my preliminary research, I found 80 percent of online apparel/accessory retailers allowed
third-party cookie placement on their websites. For instance, Ann Taylor Stores have 14
third-party cookies on their website homepage. The Neiman Marcus Group Inc., an
upscale retailer, allowed 9 third-party cookies. Although researchers in the public policy
and marketing fields have conducted studies about consumers’ general online privacy
concerns (Malhotra, Kim & Agarwal, 2004), consumers’ privacy attitudes and coping
behaviors (Norberg & Horne, 2007; Son & Kim, 2008; Lwin & Williams, 2003), and
privacy concerns versus personalization marketing (Chellappa &Sin, 2005; ), there are no
empirical studies that examine the impact of unsolicited behavioral tracking on
consumers’ attitude changes toward trusted online retailers. Hence, this study also
examines how personal factors such as innovativeness, general privacy concern and
commitment toward retailers will moderate the relationship among unsolicited behavioral
tracking, evaluation of shopping experience and attitudes toward online retailers.
3.
Method and Procedure
This research study will consist of a Web survey distributed through (1) selected
classes from the departments of Design and Human Environment (DHE), Human
Development and Family Science (HDFS), Psychology (PSY) and Business (BA) and (2)
listserv of OSU. No class under the researchers’ control will be used to recruit participants.
An example of the email that will be sent to instructors for permission to recruit students is
125
attached in Appendix Three. Once permission is granted to recruit students from the
selected DHE, HDFS, PSY and BA classes, either course Blackboard sites or emails will be
used to make announcement about the study. See the Appendix one for examples of
announcement. The announcement will explain the purpose of the web survey, the
approximation of how long the survey will take, and the URL link to the web survey. If
students are willing to participate, they can click the URL link. Once they click the link,
they will be randomly assigned to one of four treatments. Before the Web survey begins,
informed consent forms will be displayed, and the purpose of the study will again be
explained along with their roles and rights as a participant. After they agree with the
informed consent, they will be able to access the survey webpage. The survey will take
approximately 7-10 minutes. The actual data file that the researchers are going to use will
not have any personal identifiable information of participants.
4.
Risks/Benefit Assessment
(1). Risk: There are no foreseeable risks associated with participation in the study.
(2). Benefits: There is no benefit to individual paticipant directly. In some selected
DHE and Business classes, participants will receive extra credits from their
instructors for participating. Particiants do not have to complete this survey for
extra credits; the instructors will provide other opportunities for extra credits in lieu
of completing this survey. In the future, we hope that other people might benefit
from this study because the results will help online retailers learn how to adjust
their online behavioral marketing practices.
(3). Conclusion: Therefore, there are no foreseeable risks and no benefits to
participants, besides the extra credit participants from selected courses will receive.
5.
Participant Population
Close to 1200 participants will participate in the online survey. Students will be
recruited from (1) selected DHE, HDFS, PSY, and BA courses with prior permission from
instructors and (2) from listserv of OSU. College students not only represent a vulnerable
and significant internet user group but also represent an important cohort, Generation Y, to
online retailers (Internet Retailer, 2009; National Retail Federation, 2007). They have the
highest Internet usage of any other cohort and their online buying and purchasing behavior
is representative of a wide range of users (Fox and Madden, 2005; LaRose & Rifon, 2007).
126
According to FTC (2005), young adults (the 18- to 29-year-old segment) experienced the
greatest risk of privacy violations such as identity theft and Internet fraud. Thus this
population is deemed relevant for the current study.
6.
Subject Identification and Recruitment
Regardless of gender, university students, which are a representative population of
online shoppers in the U.S., will be recruited through (1) selected DHE, BA, PSY and
HDFS classes and (2) listserv of OSU. For the selected DHE, BA, PSY and HDFS classes,
instructors will be asked to announce this web survey in class and post the survey
information on the Blackboard course website. Students may also be contacted via emails
for recruitment (See Appendix One). For the participant recruitment from listserv of OSU,
student researcher will email the research announcement and survey link (no extra-credit)
to the managers of listserv.
Compensation
Participants in this study will receive no compensation for their participating,
besides some participants from selected courses (DHE245, 299, 445, 453, BA390 and
BA396) would receive extra credits.
7.
Informed Consent Process
Before the Web survey begins, informed consent forms will be displayed (see
attachment: IRB_4575_Burns_Informed_consent_noEC_03252010.docx). In the case of
DHE245, 299, 445, 453, BA390 and BA396 classes, participants will see the informed
consent with a statement about extra credits, see attachment:
IRB_4575_Burns_Informed_consent_EC_04062010.docx. The purpose of the study will
be explained along with their roles and rights as participants. Participants will also be able
to print off an informed consent form so that they have a copy of the informed consent to
keep for his/her records.
At the completion of the study, a summary and debriefing will be provided to the
instructor of each of the courses from which participants were recruited. The debriefing
will provide a description of the study and opportunities for participants to ask questions
(See Appendix Two).
Because this study involves a minimal risk, a signed Informed Consent Form will
not be collected. Students will indicate their consent by participating in the study.
127
8.
Anonymity or Confidentiality
Participants for the Web survey will be informed electronically in the letter of
informed consent displayed before the survey that the information they provide will be
kept completely confidential. The principal investigator and student researcher will be the
only ones to have access to the results of the web surveys, and the data will be stored in a
locked cabinet in the student researcher’s office which is not available to the public, and
also on the student researcher’s personal computer (private to the public).
When the researchers receive the Excel data from a website server, the data that the
researchers are going to use will not have any identifying information of participants. So
the researchers will not be able to identify individuals who participated and their responses.
In the case of DHE245, 299, 445, 453, BA390 and BA396 classes, student
participants will be led to another onid account collector in the end of the survey. In this
way, their responses to the survey would be separated from their personal identifiable
information (their onid accounts). After the data collecting is finished, I will provide the
instructors the accesses (individually) to download a list of their students’ onid accounts so
that no one will know who in their classes take this survey except the instructor his/herself.
If the results of this project are published, identities will not be published and
results will be presented in an aggregate form so individual responses are not given. Extra
caution will be taken to ensure confidentiality of participants’ responses.
128
INFORMED CONSENT DOCUMENT (no extra credit)
Project Title: The Effects of Unsolicited Behavioral Tracking on Consumers’ Evaluation
of Their Online Shopping Experiences and Attitudes Toward the Trusted Online Retailers.
Principal Investigator: Leslie D. Burns, Design and Human Environment
Co-Investigator: TunMin (Catherine) Jai, Design and Human Environment
WHAT IS THE PURPOSE OF THIS STUDY?
You are being invited to take part in this study of consumers' evaluations and attitudes of
online shopping. This study is intended for research by the student researcher. We are
specifically interested in how consumers respond to the different online behavioral
marketing practices. There is currently limited research on consumers' responses on online
retailers’ behavioral tracking practices. We are studying this because finding from this
study may be useful for developing marketing strategies for online retailing; the results will
also provide empirical evidence to help legislator to make informed policy since the U.S.
congress currently reviewing the needs to establish a law to regulate online retailers’
behavioral marketing practices, which may also benefit your future online shopping
experience.
WHAT IS THE PURPOSE OF THIS FORM?
This consent form gives you the information you will need to help you decide whether or
not to participate in the study. Please read the form carefully. You may ask any questions
via email or telephone call about the research, the possible risks and benefits, your rights as
a volunteer, and anything else that is not clear. When all of your questions have been
answered, you can decide if you want to participate in this study.
WHY AM I BEING INVITED TO TAKE PART IN THIS STUDY?
You are being invited to take part in this study because you are a college student and
18years of age or older. You must be 18 years of age or older as well as OSU student to
participate in this study. Your participation in this study is entirely voluntary and you
may refuse to answer any question or stop the survey at any time.
WHAT WILL HAPPEN DURING THIS STUDY AND HOW LONG WILL IT
129
TAKE?
If you choose to participate in this study, you will be asked some questions to evaluate your
online shopping experience. Then you will read a scenario which describes online retailer
behavioral marketing practice. After viewing the scenario, you will be asked to answer
second part of survey. This survey will present several questions about your evaluations of
your online shopping experience. If you agree to take part in this study, your participation
will take approximately 7-10 minutes.
WHAT ARE THE RISKS OF THIS STUDY?
There are no foreseeable risks associated with your participation in the study.
WHAT ARE THE BENEFITS OF THIS STUDY?
This study is not designed to benefit you directly. In the future, we hope that other people
might benefit from this study because the results will help online retailers learn how to
adjust their online behavioral marketing practices. In addition, we hope you find the study
interesting.
WILL I BE PAID FOR PARTICIPATING?
You will not be paid for participating.
WHO WILL SEE THE INFORMATION I GIVE?
The information you provide during this research study will be kept confidential to the
extent permitted by law. To help protect your confidentiality, nowhere on the survey asks
for any identifying information. Also, all information collected will be securely locked in a
filing cabinet and out of view to the public. Therefore, there is no ways to identify survey
information with any personal identifiable information. If the results of this project are
published, identities will not be published and results will be presented in an aggregate
form so individual responses are not given.
DO I HAVE A CHOICE TO BE IN THE STUDY?
Participation in this study is completely voluntary. You can stop at any time during the
study and still keep the benefits and rights you had before volunteering. You are free to skip
any question you prefer not to answer. Choosing not to participate or withdrawing will not
affect your grade in the course or your standing in the class or at the university. If you
130
choose to withdraw from this project before it ends, the researchers may keep information
collected from you and this information may be included in study reports.
WHAT IF I HAVE QUESTIONS?
If you have any questions about this research project, please contact: Tunmin (Catherine)
Jai at (541) 737-3797 or by email at jait@onid.orst.edu, as well as Dr. Leslie D. Burns, at
(541) 737-0983 or by email at Leslie.Burns@oregonstate.edu. If you have questions about
your rights as a participant, please contact the Oregon State University Institutional
Review Board (IRB) Human Protections Administrator, at (541) 737-8008 or by email
at IRB@oregonstate.edu.
Your consent to participate in this study is indicated by your completion of the online
questionnaire.
131
INFORMED CONSENT DOCUMENT (with extra credit)
Project Title: The Effects of Unsolicited Behavioral Tracking on Consumers’ Evaluation
of Their Online Shopping Experiences and Attitudes Toward the Trusted Online Retailers.
Principal Investigator: Leslie D. Burns, Design and Human Environment
Co-Investigator: TunMin (Catherine) Jai, Design and Human Environment
WHAT IS THE PURPOSE OF THIS STUDY?
You are being invited to take part in this study of consumers' evaluations and attitudes of
online shopping. This study is intended for research by the student researcher. We are
specifically interested in how consumers respond to the different online behavioral
marketing practices. There is currently limited research on consumers' responses on online
retailers’ behavioral tracking practices. We are studying this because finding from this
study may be useful for developing marketing strategies for online retailing; the results will
also provide empirical evidence to help legislator to make informed policy since the U.S.
congress currently reviewing the needs to establish a law to regulate online retailers’
behavioral marketing practices, which may also benefit your future online shopping
experience.
WHAT IS THE PURPOSE OF THIS FORM?
This consent form gives you the information you will need to help you decide whether or
not to participate in the study. Please read the form carefully. You may ask any questions
via email or telephone call about the research, the possible risks and benefits, your rights as
a volunteer, and anything else that is not clear. When all of your questions have been
answered, you can decide if you want to participate in this study.
WHY AM I BEING INVITED TO TAKE PART IN THIS STUDY?
You are being invited to take part in this study because you are a college student and
18years of age or older. You must be 18 years of age or older as well as OSU student to
participate in this study. Your participation in this study is entirely voluntary and you
may refuse to answer any question or stop the survey at any time.
132
WHAT WILL HAPPEN DURING THIS STUDY AND HOW LONG WILL IT
TAKE?
If you choose to participate in this study, you will be asked some questions to evaluate your
online shopping experience. Then you will read a scenario which describes online retailer
behavioral marketing practice. After viewing the scenario, you will be asked to answer
second part of survey. This survey will present several questions about your evaluations of
your online shopping experience. If you agree to take part in this study, your participation
will take approximately 7-10 minutes.
WHAT ARE THE RISKS OF THIS STUDY?
There are no foreseeable risks associated with your participation in the study.
WHAT ARE THE BENEFITS OF THIS STUDY?
This study is not designed to benefit you directly, besides the extra credit you will receive
from your instructor for participating. You do not have to complete this survey for extra
credit; your instructor will provide other opportunities for extra credit in lieu of completing
this survey. In the future, we hope that other people might benefit from this study because
the results will help online retailers learn how to adjust their online behavioral marketing
practices. In addition, we hope you find the study interesting.
WILL I BE PAID FOR PARTICIPATING?
You will not be paid for participating.
WHO WILL SEE THE INFORMATION I GIVE?
The information you provide during this research study will be kept confidential to the
extent permitted by law. To help protect your confidentiality, nowhere on the survey asks
for any identifying information. Also, all information collected will be securely locked in a
filing cabinet and out of view to the public. Therefore, there is no ways to identify survey
information with any personal identifiable information. If the results of this project are
published, identities will not be published and results will be presented in an aggregate
form so individual responses are not given.
DO I HAVE A CHOICE TO BE IN THE STUDY?
Participation in this study is completely voluntary. You can stop at any time during the
133
study and still keep the benefits and rights you had before volunteering. You are free to skip
any question you prefer not to answer. Choosing not to participate or withdrawing will not
affect your grade in the course or your standing in the class or at the university. If you
choose to withdraw from this project before it ends, the researchers may keep information
collected from you and this information may be included in study reports.
WHAT IF I HAVE QUESTIONS?
If you have any questions about this research project, please contact: Tunmin (Catherine)
Jai at (541) 737-3797 or by email at jait@onid.orst.edu, as well as Dr. Leslie D. Burns, at
(541) 737-0983 or by email at Leslie.Burns@oregonstate.edu. If you have questions about
your rights as a participant, please contact the Oregon State University Institutional
Review Board (IRB) Human Protections Administrator, at (541) 737-8008 or by email
at IRB@oregonstate.edu.
Your consent to participate in this study is indicated by your completion of the online
questionnaire.
134
3. Dissertation Research #1
To many people, buying or searching for products online has already become a common experience.
In this study, we would like to know how you evaluate one of the websites at which you often shop.
1. What is the name of the website at which you shop most frequently?
(Here "shop" means either just searching for product or actually making
purchases).
2. Which category of products best describes your shopping choices at this
website?
Books/magazines
Clothing/ shoes/accessories
Computer hardware or software
Consumer electronics (TV, VCR, stereo, cellular phones)
Entertainment (compact disks, videos, concert tickets)
Financial services
Food/beverage/grocery
Health and medical
Sporting / Hobby goods
Travel
Other (please specify)
3. How often have you patronized(or visited) this website in the past three
months?
more than once a week
once a week
2-3 times a month
once a month
less than once a month
4. Have you ever made purchases on this website?
No
Yes
135
5. Think about this website and state your agreement with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I am a loyal patron of this website.
I believe that my values are in line
I felt very little loyalty to the website.
I introduce/recommend this website to
with the values of the website.
I care about the fate of the website
(ie, stays in business).
my friends.
I spend a lot of time on this website
searching for or purchasing products.
6. Innovativeness--Please state your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
When I see a new or different brand
on a shelf, I often pick it up just to see
Strongly
2
Agree 7
what it is like.
A new store or restaurant is not
something I would be eager to find out
about.
I am very cautious in trying
new/different products.
I would rather wait for others to try a
new store or restaurant than try it
myself.
Investigating new brands of grocery
and other similar products is generally
a waste of time.
7. General Privacy Concern--Please state your agreement
with the following statements.
Strongly
Disagree
3
4
5
6
1
Consumers have lost all control over
how personal information is collected
Strongly
2
Agree 7
and used by companies.
Most businesses handle the personal
information they collect about
consumers in a proper and confidential
way.
Existing laws and organizational
practices provide a reasonable level of
protection for consumer privacy today.
136
8. Your "Cookie" Knowledge-- Please tell us your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
I know a "cookie" is a small text file that a
website’s server places on my computer’s web
Strongly
2
Agree 7
browser.
I know the cookie transmits information back to
the website’s server about my browsing activities
on the site, such as pages and content viewed,
the time and duration of visits, search queries
entered into search engines, and whether a
computer user clicked on an advertisement.
I know cookies also can be used to maintain data
related to a particular individual, including
passwords or items in an online shopping cart.
I know some websites allow other third-party
companies to place cookies into customers' hard
drives to track shopping behaviors.
9. Have you ever deleted cookies from your internet browser (IE, Firefox)?
No
Yes
10. Releasing Personal Information--Please state your
agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
In general, it is risky to give my
personal information to online
Strongly
2
Agree 7
companies.
There is high potential for loss
associated with giving my personal
information to online firms.
There is too much uncertainty
associated with giving my personal
information to online firms.
Providing online firms with my personal
information would involve many
unexpected problems.
137
In next section, you will see a scenario description.
Please carefully read the following scenario,
imagine this happened on the website where you
just stated you frequently shop and answer the
following questions.
Your friend tells you to use a software program which
helps you to identify whether third-party cookies are
placed in your computer drive when you visit a website.
After you use it, you find out that:
P
YourFavoriteStore.com (where you frequently
shop) does not allow third-party cookies to be
placed on your hard drive.
However, YourFavoriteStore.com does share your
personal information with their corporate family.
The website stated the following information in their
privacy policy:
YourFavoriteStore.com shares your personal
information with our corporate family.
P
We may share information such as your name, postal
and email address, customer preferences, and
purchase history within our corporate family (affiliates
- companies under common ownership) so that they
may market to you.
P
When you visit our Web site, we collect your
navigational information, such as service-provider
identification, the IP address of your computer, the
138
site that you navigate from, and the site that you
navigate to when you leave. We may associate this
navigational information with your personal
information.
Please read the following statements carefully. For each statement, please choose the
response that best represents your opinion.
11. Fair Information Practice-Please state your agreement with the following statements
about the Fair Information Practice of
YourFavoriteStore.com after reading the descriptions of the
behavioral tracking practices of the company.
Strongly
Disagree
3
4
5
6
1
I feel that I was not informed by the
company about who is collecting my
Strongly
2
Agree 7
information.
I feel that I was not informed by the
company about what kinds of personal
information will be collected.
I feel that I was not informed by the
company about how my personal
information will be collected.
I feel that I have no choice about how
my personal information will be used.
I feel that I have no choice about
which parties my personal information
will be disclosed to.
The exchange of personal information
is equitable.
I have control over my personal
information.
I am adequately informed about the
use of the data.
The site clearly explains how user
information is used.
The online retailer only collects
personal information necessary for the
transaction to be completed.
139
12. Now, please tell us how do you feel about shopping on
YourFavoriteStore.com?
Strongly
Disagree
3
4
5
6
1
I think that buying a product from
MyFavoriteStore.com would be risky
Strongly
2
Agree 7
because of the possibility of
unauthorized access to my personal
information.
I think that buying a product from
MyFavoriteStore.com would be risky
because my personal information may
be released to other third-party.
I feel I don't have control over my
personal information when I shop at
MyFavoriteStore.com.
13. Please tell us how likely you are to prefer personalized
promotions online rather than nonpersonalized promotions/
advertisements.
Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I am pleased when I receive
personalized advertising that has my
Strongly
2
Agree 7
name on the title from an advertiser
(company or brand) where I never
shopped before.
I am pleased when I receive
personalized advertising that has my
name on the title from stores I have
shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising
tailored to my interests when I surfing
online.
I am pleased to see the
advertisements of the brands I
shopped when I use my social network
website (e.g., facebook, myspace).
I am pleased to see the personalized
advertisements when when I go to a
news website (e.g., msn news, New
York Times).
I am pleased to see the
advertisements of the brands I
shopped when I use online email
services (e.g., Gmail, hotmail, yahoo!
mail).
140
14. Perceived Fairness--After learning that
YourFavoriteStore.com (where you frequently shop)
engages in the behavioral tracking practices presented in
the scenario, please think about your shopping experience
on YourFavoriteStore.com and state your agreements with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an
unfair deal.
15. Perceived Trust-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I can count on Myfavoritestore.com to
protect my privacy.
Myfavoritestore.com is a trustworthy
store.
I can count on Myfavoritestore.com to
protect customers’ personal
Strongly
2
Agree 7
information from unauthorized use.
Myfavoritestore.com can be relied on
to keep its promise.
Promises made by Myfavoritestore.com
are likely to be reliable.
I do not doubt the honesty of
Myfavoritestore. com
I expect that Myfavoritestore.com will
keep promises they make.
I expect that Myfavoritestore.com has
good intentions toward me.
141
16. Moods-After learning about
MyFavoriteStore.com's behavioral
tracking practices, shopping at
MyFavoriteStore.com makes me
feel:
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Attentive
Curious
Aroused
Excited
17. Repurchase Loyalty--Please state your agreement with
the following statements.
Strongly
Disagree
3
4
5
6
1
I intend to return to shop at
MyFavoriteStore.com.
I will use this store the next time I
want to make a purchase.
I probably won't switch to another
website to make purchases.
I would recommend this store to my
friends.
Strongly
2
Agree 7
You are almost done! Last, please tell us a little bit about yourself!
18. Gender
Male
Female
No response
142
19. Your age? (Format: 0-120)
20. Which college you are attending?
21. What is your class standing?
22. What is your ethnicity background?
23. Have you ever personally experienced the following?
Please check the box(es) that applied.
Spam/junk e-mails
ID theft
Credit card fraud
Others learning your personal info from online activities
Computer virus attack
e -mail read by someone other than recipient
N/A (I have never experienced any of above)
143
4. Dissertation Research #2
To many people, buying or searching for products online has already become a common experience.
In this study, we would like to know how you evaluate one of the websites at which you often shop.
1. What is the name of the website at which you shop most frequently?
(Here "shop" means either just searching for product or actually making
purchases).
2. Which category of products best describes your shopping choices at this
website?
Books/magazines
Clothing/ shoes/accessories
Computer hardware or software
Consumer electronics (TV, VCR, stereo, cellular phones)
Entertainment (compact disks, videos, concert tickets)
Financial services
Food/beverage/grocery
Health and medical
Sporting / Hobby goods
Travel
Other (please specify)
3. How often have you patronized(or visited) this website in the past three
months?
more than once a week
once a week
2-3 times a month
once a month
less than once a month
4. Have you ever made purchases on this website?
No
Yes
144
5. Think about this website and state your agreement with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I am a loyal patron of this website.
I believe that my values are in line
I felt very little loyalty to the website.
I introduce/recommend this website to
with the values of the website.
I care about the fate of the website
(ie, stays in business).
my friends.
I spend a lot of time on this website
searching for or purchasing products.
6. Innovativeness--Please state your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
When I see a new or different brand
on a shelf, I often pick it up just to see
Strongly
2
Agree 7
what it is like.
A new store or restaurant is not
something I would be eager to find out
about.
I am very cautious in trying
new/different products.
I would rather wait for others to try a
new store or restaurant than try it
myself.
Investigating new brands of grocery
and other similar products is generally
a waste of time.
7. General Privacy Concern--Please state your agreement
with the following statements.
Strongly
Disagree
3
4
5
6
1
Consumers have lost all control over
how personal information is collected
Strongly
2
Agree 7
and used by companies.
Most businesses handle the personal
information they collect about
consumers in a proper and confidential
way.
Existing laws and organizational
practices provide a reasonable level of
protection for consumer privacy today.
145
8. Your "Cookie" Knowledge-- Please tell us your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
I know a "cookie" is a small text file that a
website’s server places on my computer’s web
Strongly
2
Agree 7
browser.
I know the cookie transmits information back to
the website’s server about my browsing activities
on the site, such as pages and content viewed,
the time and duration of visits, search queries
entered into search engines, and whether a
computer user clicked on an advertisement.
I know cookies also can be used to maintain data
related to a particular individual, including
passwords or items in an online shopping cart.
I know some websites allow other third-party
companies to place cookies into customers' hard
drives to track shopping behaviors.
9. Have you ever deleted cookies from your internet browser (IE, Firefox)?
No
Yes
10. Releasing Personal Information--Please state your
agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
In general, it is risky to give my
personal information to online
Strongly
2
Agree 7
companies.
There is high potential for loss
associated with giving my personal
information to online firms.
There is too much uncertainty
associated with giving my personal
information to online firms.
Providing online firms with my personal
information would involve many
unexpected problems.
146
In next section, you will see a scenario description.
Please carefully read the following scenario,
imagine this happened on the website where you
just stated you frequently shop and answer the
following questions.
Your friend tells you to use a software program which
helps you to identify whether third-party cookies are
placed in your computer drive when you visit a website.
After you use it, you find out that:
P
YourFavoriteStore.com (where you frequently
shop) does not allow third-party cookies to be
placed on your hard drive.
However, YourFavoriteStore.com does share your
personal information with their corporate family and
companies outside.
The website stated the following information in their
privacy policy:
YourFavoriteStore.com shares your personal
information with our corporate family.
P
We may share information such as your name, postal
and email address, customer preferences, and
purchase history within our corporate family (affiliates
- companies under common ownership) so that they
may market to you.
P
When you visit our Web site, we collect your
navigational information, such as service-provider
147
identification, the IP address of your computer, the
site that you navigate from, and the site that you
navigate to when you leave. We may associate this
navigational information with your personal
information.
YourFavoriteStore.com also shares your personal
information with companies outside of our
corporate family.
P
We may also share your name, postal and email
address, customer preferences, and purchase history
with other merchants and merchant exchanges (nonaffiliate companies that are not in our corporate
family).
P
Other merchants may, in turn, use this information to
send you offers about their products and services.
Please read the following statements carefully. For each statement, please choose the
response that best represents your opinion.
148
11. Fair Information Practice-Please state your agreement with the following statements
about the Fair Information Practice of
YourFavoriteStore.com after reading the descriptions of the
behavioral tracking practices of the company.
Strongly
Disagree
3
4
5
6
1
I feel that I was not informed by the
company about who is collecting my
Strongly
2
Agree 7
information.
I feel that I was not informed by the
company about what kinds of personal
information will be collected.
I feel that I was not informed by the
company about how my personal
information will be collected.
I feel that I have no choice about how
my personal information will be used.
I feel that I have no choice about
which parties my personal information
will be disclosed to.
The exchange of personal information
is equitable.
I have control over my personal
information.
I am adequately informed about the
use of the data.
The site clearly explains how user
information is used.
The online retailer only collects
personal information necessary for the
transaction to be completed.
12. Now, please tell us how do you feel about shopping on
YourFavoriteStore.com?
Strongly
Disagree
3
4
5
6
1
I think that buying a product from
MyFavoriteStore.com would be risky
Strongly
2
Agree 7
because of the possibility of
unauthorized access to my personal
information.
I think that buying a product from
MyFavoriteStore.com would be risky
because my personal information may
be released to other third-party.
I feel I don't have control over my
personal information when I shop at
MyFavoriteStore.com.
149
13. Please tell us how likely you are to prefer personalized
promotions online rather than nonpersonalized promotions/
advertisements.
Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I am pleased when I receive
personalized advertising that has my
Strongly
2
Agree 7
name on the title from an advertiser
(company or brand) where I never
shopped before.
I am pleased when I receive
personalized advertising that has my
name on the title from stores I have
shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising
tailored to my interests when I surfing
online.
I am pleased to see the
advertisements of the brands I
shopped when I use my social network
website (e.g., facebook, myspace).
I am pleased to see the personalized
advertisements when when I go to a
news website (e.g., msn news, New
York Times).
I am pleased to see the
advertisements of the brands I
shopped when I use online email
services (e.g., Gmail, hotmail, yahoo!
mail).
14. Perceived Fairness--After learning that
YourFavoriteStore.com (where you frequently shop)
engages in the behavioral tracking practices presented in
the scenario, please think about your shopping experience
on YourFavoriteStore.com and state your agreements with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an
unfair deal.
150
15. Perceived Trust-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I can count on Myfavoritestore.com to
protect my privacy.
Myfavoritestore.com is a trustworthy
store.
I can count on Myfavoritestore.com to
protect customers’ personal
Strongly
2
Agree 7
information from unauthorized use.
Myfavoritestore.com can be relied on
to keep its promise.
Promises made by Myfavoritestore.com
are likely to be reliable.
I do not doubt the honesty of
Myfavoritestore. com
I expect that Myfavoritestore.com will
keep promises they make.
I expect that Myfavoritestore.com has
good intentions toward me.
151
16. Moods-After learning about
MyFavoriteStore.com's behavioral
tracking practices, shopping at
MyFavoriteStore.com makes me
feel:
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Attentive
Curious
Aroused
Excited
17. Repurchase Loyalty--Please state your agreement with
the following statements.
Strongly
Disagree
3
4
5
6
1
I intend to return to shop at
MyFavoriteStore.com.
I will use this store the next time I
want to make a purchase.
I probably won't switch to another
website to make purchases.
I would recommend this store to my
friends.
Strongly
2
Agree 7
You are almost done! Last, please tell us a little bit about yourself!
18. Gender
Male
Female
No response
152
19. Your age? (Format: 0-120)
20. Which college you are attending?
21. What is your class standing?
22. What is your ethnicity background?
23. Have you ever personally experienced the following?
Please check the box(es) that applied.
Spam/junk e-mails
ID theft
Credit card fraud
Others learning your personal info from online activities
Computer virus attack
e -mail read by someone other than recipient
N/A (I have never experienced any of above)
153
5. Dissertation Research #3
To many people, buying or searching for products online has already become a common experience.
In this study, we would like to know how you evaluate one of the websites at which you often shop.
1. What is the name of the website at which you shop most frequently?
(Here "shop" means either just searching for product or actually making
purchases).
2. Which category of products best describes your shopping choices at this
website?
Books/magazines
Clothing/ shoes/accessories
Computer hardware or software
Consumer electronics (TV, VCR, stereo, cellular phones)
Entertainment (compact disks, videos, concert tickets)
Financial services
Food/beverage/grocery
Health and medical
Sporting / Hobby goods
Travel
Other (please specify)
3. How often have you patronized(or visited) this website in the past three
months?
more than once a week
once a week
2-3 times a month
once a month
less than once a month
4. Have you ever made purchases on this website?
No
Yes
154
5. Think about this website and state your agreement with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I am a loyal patron of this website.
I believe that my values are in line
I felt very little loyalty to the website.
I introduce/recommend this website to
with the values of the website.
I care about the fate of the website
(ie, stays in business).
my friends.
I spend a lot of time on this website
searching for or purchasing products.
6. Innovativeness--Please state your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
When I see a new or different brand
on a shelf, I often pick it up just to see
Strongly
2
Agree 7
what it is like.
A new store or restaurant is not
something I would be eager to find out
about.
I am very cautious in trying
new/different products.
I would rather wait for others to try a
new store or restaurant than try it
myself.
Investigating new brands of grocery
and other similar products is generally
a waste of time.
7. General Privacy Concern--Please state your agreement
with the following statements.
Strongly
Disagree
3
4
5
6
1
Consumers have lost all control over
how personal information is collected
Strongly
2
Agree 7
and used by companies.
Most businesses handle the personal
information they collect about
consumers in a proper and confidential
way.
Existing laws and organizational
practices provide a reasonable level of
protection for consumer privacy today.
155
8. Your "Cookie" Knowledge-- Please tell us your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
I know a "cookie" is a small text file that a
website’s server places on my computer’s web
Strongly
2
Agree 7
browser.
I know the cookie transmits information back to
the website’s server about my browsing activities
on the site, such as pages and content viewed,
the time and duration of visits, search queries
entered into search engines, and whether a
computer user clicked on an advertisement.
I know cookies also can be used to maintain data
related to a particular individual, including
passwords or items in an online shopping cart.
I know some websites allow other third-party
companies to place cookies into customers' hard
drives to track shopping behaviors.
9. Have you ever deleted cookies from your internet browser (IE, Firefox)?
No
Yes
10. Releasing Personal Information--Please state your
agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
In general, it is risky to give my
personal information to online
Strongly
2
Agree 7
companies.
There is high potential for loss
associated with giving my personal
information to online firms.
There is too much uncertainty
associated with giving my personal
information to online firms.
Providing online firms with my personal
information would involve many
unexpected problems.
156
In next section, you will see a scenario description.
Please carefully read the following scenario,
imagine this happened on the website where you
just stated you frequently shop and answer the
following questions.
Your friend tells you to use a software program which
helps you to identify whether third-party cookies are
placed in your computer drive when you visit a website.
After you use it, you find out that:
P
YourFavoriteStore.com (where you frequently
shop) allows 1 third-party cookie to be placed on
your hard drive.
At the same time, YourFavoriteStore.com also shares
your personal information with their corporate family and
companyies outside.
The website stated the following information in their
privacy policy:
YourFavoriteStore.com shares your personal
information with our corporate family.
P
We may share information such as your name, postal
and email address, customer preferences, and
purchase history within our corporate family (affiliates
- companies under common ownership) so that they
may market to you.
P
When you visit our Web site, we collect your
navigational information, such as service-provider
157
identification, the IP address of your computer, the
site that you navigate from, and the site that you
navigate to when you leave. We may associate this
navigational information with your personal
information.
YourFavoriteStore.com also shares your personal
information with companies outside of our
corporate family.
P
We may also share your name, postal and email
address, customer preferences, and purchase history
with other merchants and merchant exchanges (nonaffiliate companies that are not in our corporate
family).
P
Other merchants may, in turn, use this information to
send you offers about their products and services.
Please read the following statements carefully. For each statement, please choose the
response that best represents your opinion.
158
11. Fair Information Practice-Please state your agreement with the following statements
about the Fair Information Practice of
YourFavoriteStore.com after reading the descriptions of the
behavioral tracking practices of the company.
Strongly
Disagree
3
4
5
6
1
I feel that I was not informed by the
company about who is collecting my
Strongly
2
Agree 7
information.
I feel that I was not informed by the
company about what kinds of personal
information will be collected.
I feel that I was not informed by the
company about how my personal
information will be collected.
I feel that I have no choice about how
my personal information will be used.
I feel that I have no choice about
which parties my personal information
will be disclosed to.
The exchange of personal information
is equitable.
I have control over my personal
information.
I am adequately informed about the
use of the data.
The site clearly explains how user
information is used.
The online retailer only collects
personal information necessary for the
transaction to be completed.
12. Now, please tell us how do you feel about shopping on
YourFavoriteStore.com?
Strongly
Disagree
3
4
5
6
1
I think that buying a product from
MyFavoriteStore.com would be risky
Strongly
2
Agree 7
because of the possibility of
unauthorized access to my personal
information.
I think that buying a product from
MyFavoriteStore.com would be risky
because my personal information may
be released to other third-party.
I feel I don't have control over my
personal information when I shop at
MyFavoriteStore.com.
159
13. Please tell us how likely you are to prefer personalized
promotions online rather than nonpersonalized promotions/
advertisements.
Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I am pleased when I receive
personalized advertising that has my
Strongly
2
Agree 7
name on the title from an advertiser
(company or brand) where I never
shopped before.
I am pleased when I receive
personalized advertising that has my
name on the title from stores I have
shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising
tailored to my interests when I surfing
online.
I am pleased to see the
advertisements of the brands I
shopped when I use my social network
website (e.g., facebook, myspace).
I am pleased to see the personalized
advertisements when when I go to a
news website (e.g., msn news, New
York Times).
I am pleased to see the
advertisements of the brands I
shopped when I use online email
services (e.g., Gmail, hotmail, yahoo!
mail).
14. Perceived Fairness--After learning that
YourFavoriteStore.com (where you frequently shop)
engages in the behavioral tracking practices presented in
the scenario, please think about your shopping experience
on YourFavoriteStore.com and state your agreements with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an
unfair deal.
160
15. Perceived Trust-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I can count on Myfavoritestore.com to
protect my privacy.
Myfavoritestore.com is a trustworthy
store.
I can count on Myfavoritestore.com to
protect customers’ personal
Strongly
2
Agree 7
information from unauthorized use.
Myfavoritestore.com can be relied on
to keep its promise.
Promises made by Myfavoritestore.com
are likely to be reliable.
I do not doubt the honesty of
Myfavoritestore. com
I expect that Myfavoritestore.com will
keep promises they make.
I expect that Myfavoritestore.com has
good intentions toward me.
161
16. Moods-After learning about
MyFavoriteStore.com's behavioral
tracking practices, shopping at
MyFavoriteStore.com makes me
feel:
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Attentive
Curious
Aroused
Excited
17. Repurchase Loyalty--Please state your agreement with
the following statements.
Strongly
Disagree
3
4
5
6
1
I intend to return to shop at
MyFavoriteStore.com.
I will use this store the next time I
want to make a purchase.
I probably won't switch to another
website to make purchases.
I would recommend this store to my
friends.
Strongly
2
Agree 7
You are almost done! Last, please tell us a little bit about yourself!
18. Gender
Male
Female
No response
162
19. Your age? (Format: 0-120)
20. Which college you are attending?
21. What is your class standing?
22. What is your ethnicity background?
23. Have you ever personally experienced the following?
Please check the box(es) that applied.
Spam/junk e-mails
ID theft
Credit card fraud
Others learning your personal info from online activities
Computer virus attack
e -mail read by someone other than recipient
N/A (I have never experienced any of above)
163
6. Dissertation Research #4
To many people, buying or searching for products online has already become a common experience.
In this study, we would like to know how you evaluate one of the websites at which you often shop.
1. What is the name of the website at which you shop most frequently?
(Here "shop" means either just searching for product or actually making
purchases).
2. Which category of products best describes your shopping choices at this
website?
Books/magazines
Clothing/ shoes/accessories
Computer hardware or software
Consumer electronics (TV, VCR, stereo, cellular phones)
Entertainment (compact disks, videos, concert tickets)
Financial services
Food/beverage/grocery
Health and medical
Sporting / Hobby goods
Travel
Other (please specify)
3. How often have you patronized(or visited) this website in the past three
months?
more than once a week
once a week
2-3 times a month
once a month
less than once a month
4. Have you ever made purchases on this website?
No
Yes
164
5. Think about this website and state your agreement with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I am a loyal patron of this website.
I believe that my values are in line
I felt very little loyalty to the website.
I introduce/recommend this website to
with the values of the website.
I care about the fate of the website
(ie, stays in business).
my friends.
I spend a lot of time on this website
searching for or purchasing products.
6. Innovativeness--Please state your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
When I see a new or different brand
on a shelf, I often pick it up just to see
Strongly
2
Agree 7
what it is like.
A new store or restaurant is not
something I would be eager to find out
about.
I am very cautious in trying
new/different products.
I would rather wait for others to try a
new store or restaurant than try it
myself.
Investigating new brands of grocery
and other similar products is generally
a waste of time.
7. General Privacy Concern--Please state your agreement
with the following statements.
Strongly
Disagree
3
4
5
6
1
Consumers have lost all control over
how personal information is collected
Strongly
2
Agree 7
and used by companies.
Most businesses handle the personal
information they collect about
consumers in a proper and confidential
way.
Existing laws and organizational
practices provide a reasonable level of
protection for consumer privacy today.
165
8. Your "Cookie" Knowledge-- Please tell us your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
I know a "cookie" is a small text file that a
website’s server places on my computer’s web
Strongly
2
Agree 7
browser.
I know the cookie transmits information back to
the website’s server about my browsing activities
on the site, such as pages and content viewed,
the time and duration of visits, search queries
entered into search engines, and whether a
computer user clicked on an advertisement.
I know cookies also can be used to maintain data
related to a particular individual, including
passwords or items in an online shopping cart.
I know some websites allow other third-party
companies to place cookies into customers' hard
drives to track shopping behaviors.
9. Have you ever deleted cookies from your internet browser (IE, Firefox)?
No
Yes
10. Releasing Personal Information--Please state your
agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
In general, it is risky to give my
personal information to online
Strongly
2
Agree 7
companies.
There is high potential for loss
associated with giving my personal
information to online firms.
There is too much uncertainty
associated with giving my personal
information to online firms.
Providing online firms with my personal
information would involve many
unexpected problems.
166
In next section, you will see a scenario description.
Please carefully read the following scenario,
imagine this happened on the website where you
just stated you frequently shop and answer the
following questions.
Your friend tells you to use a software program which
helps you to identify whether third-party cookies are
placed in your computer drive when you visit a website.
After you use it, you find out that:
P
YourFavoriteStore.com (where you frequently
shop) allows 14 third-party cookies to be placed
on your hard drive.
At the same time, YourFavoriteStore.com also shares
your personal information with their corporate family and
companyies outside.
The website stated the following information in their
privacy policy:
YourFavoriteStore.com shares your personal
information with our corporate family.
P
We may share information such as your name, postal
and email address, customer preferences, and
purchase history within our corporate family (affiliates
- companies under common ownership) so that they
may market to you.
P
When you visit our Web site, we collect your
navigational information, such as service-provider
167
identification, the IP address of your computer, the
site that you navigate from, and the site that you
navigate to when you leave. We may associate this
navigational information with your personal
information.
YourFavoriteStore.com also shares your personal
information with companies outside of our
corporate family.
P
We may also share your name, postal and email
address, customer preferences, and purchase history
with other merchants and merchant exchanges (nonaffiliate companies that are not in our corporate
family).
P
Other merchants may, in turn, use this information to
send you offers about their products and services.
Please read the following statements carefully. For each statement, please choose the
response that best represents your opinion.
168
11. Fair Information Practice-Please state your agreement with the following statements
about the Fair Information Practice of
YourFavoriteStore.com after reading the descriptions of the
behavioral tracking practices of the company.
Strongly
Disagree
3
4
5
6
1
I feel that I was not informed by the
company about who is collecting my
Strongly
2
Agree 7
information.
I feel that I was not informed by the
company about what kinds of personal
information will be collected.
I feel that I was not informed by the
company about how my personal
information will be collected.
I feel that I have no choice about how
my personal information will be used.
I feel that I have no choice about
which parties my personal information
will be disclosed to.
The exchange of personal information
is equitable.
I have control over my personal
information.
I am adequately informed about the
use of the data.
The site clearly explains how user
information is used.
The online retailer only collects
personal information necessary for the
transaction to be completed.
12. Now, please tell us how do you feel about shopping on
YourFavoriteStore.com?
Strongly
Disagree
3
4
5
6
1
I think that buying a product from
MyFavoriteStore.com would be risky
Strongly
2
Agree 7
because of the possibility of
unauthorized access to my personal
information.
I think that buying a product from
MyFavoriteStore.com would be risky
because my personal information may
be released to other third-party.
I feel I don't have control over my
personal information when I shop at
MyFavoriteStore.com.
169
13. Please tell us how likely you are to prefer personalized
promotions online rather than nonpersonalized promotions/
advertisements.
Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I am pleased when I receive
personalized advertising that has my
Strongly
2
Agree 7
name on the title from an advertiser
(company or brand) where I never
shopped before.
I am pleased when I receive
personalized advertising that has my
name on the title from stores I have
shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising
tailored to my interests when I surfing
online.
I am pleased to see the
advertisements of the brands I
shopped when I use my social network
website (e.g., facebook, myspace).
I am pleased to see the personalized
advertisements when when I go to a
news website (e.g., msn news, New
York Times).
I am pleased to see the
advertisements of the brands I
shopped when I use online email
services (e.g., Gmail, hotmail, yahoo!
mail).
14. Perceived Fairness--After learning that
YourFavoriteStore.com (where you frequently shop)
engages in the behavioral tracking practices presented in
the scenario, please think about your shopping experience
on YourFavoriteStore.com and state your agreements with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an
unfair deal.
170
15. Perceived Trust-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I can count on Myfavoritestore.com to
protect my privacy.
Myfavoritestore.com is a trustworthy
store.
I can count on Myfavoritestore.com to
protect customers’ personal
Strongly
2
Agree 7
information from unauthorized use.
Myfavoritestore.com can be relied on
to keep its promise.
Promises made by Myfavoritestore.com
are likely to be reliable.
I do not doubt the honesty of
Myfavoritestore. com
I expect that Myfavoritestore.com will
keep promises they make.
I expect that Myfavoritestore.com has
good intentions toward me.
171
16. Moods-After learning about
MyFavoriteStore.com's behavioral
tracking practices, shopping at
MyFavoriteStore.com makes me
feel:
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Attentive
Curious
Aroused
Excited
17. Repurchase Loyalty--Please state your agreement with
the following statements.
Strongly
Disagree
3
4
5
6
1
I intend to return to shop at
MyFavoriteStore.com.
I will use this store the next time I
want to make a purchase.
I probably won't switch to another
website to make purchases.
I would recommend this store to my
friends.
Strongly
2
Agree 7
You are almost done! Last, please tell us a little bit about yourself!
18. Gender
Male
Female
No response
172
19. Your age? (Format: 0-120)
20. Which college you are attending?
21. What is your class standing?
22. What is your ethnicity background?
23. Have you ever personally experienced the following?
Please check the box(es) that applied.
Spam/junk e-mails
ID theft
Credit card fraud
Others learning your personal info from online activities
Computer virus attack
e -mail read by someone other than recipient
N/A (I have never experienced any of above)
173
7. Dissertation Research #0
To many people, buying or searching for products online has already become a common experience.
In this study, we would like to know how you evaluate one of the websites at which you often shop.
1. What is the name of the website at which you shop most frequently?
(Here "shop" means either just searching for product or actually making
purchases).
2. Which category of products best describes your shopping choices at this
website?
Books/magazines
Clothing/ shoes/accessories
Computer hardware or software
Consumer electronics (TV, VCR, stereo, cellular phones)
Entertainment (compact disks, videos, concert tickets)
Financial services
Food/beverage/grocery
Health and medical
Sporting / Hobby goods
Travel
Other (please specify)
3. How often have you patronized(or visited) this website in the past three
months?
more than once a week
once a week
2-3 times a month
once a month
less than once a month
4. Have you ever made purchases on this website?
No
Yes
174
5. Think about this website and state your agreement with
the following statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I am a loyal patron of this website.
I believe that my values are in line
I felt very little loyalty to the website.
I introduce/recommend this website to
with the values of the website.
I care about the fate of the website
(ie, stays in business).
my friends.
I spend a lot of time on this website
searching for or purchasing products.
6. Innovativeness--Please state your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
When I see a new or different brand
on a shelf, I often pick it up just to see
Strongly
2
Agree 7
what it is like.
A new store or restaurant is not
something I would be eager to find out
about.
I am very cautious in trying
new/different products.
I would rather wait for others to try a
new store or restaurant than try it
myself.
Investigating new brands of grocery
and other similar products is generally
a waste of time.
7. General Privacy Concern--Please state your agreement
with the following statements.
Strongly
Disagree
3
4
5
6
1
Consumers have lost all control over
how personal information is collected
Strongly
2
Agree 7
and used by companies.
Most businesses handle the personal
information they collect about
consumers in a proper and confidential
way.
Existing laws and organizational
practices provide a reasonable level of
protection for consumer privacy today.
175
8. Your "Cookie" Knowledge-- Please tell us your agreement with the
following statements.
Strongly
Disagree
3
4
5
6
1
I know a "cookie" is a small text file that a
website’s server places on my computer’s web
Strongly
2
Agree 7
browser.
I know the cookie transmits information back to
the website’s server about my browsing activities
on the site, such as pages and content viewed,
the time and duration of visits, search queries
entered into search engines, and whether a
computer user clicked on an advertisement.
I know cookies also can be used to maintain data
related to a particular individual, including
passwords or items in an online shopping cart.
I know some websites allow other third-party
companies to place cookies into customers' hard
drives to track shopping behaviors.
9. Have you ever deleted cookies from your internet browser (IE, Firefox)?
No
Yes
10. Releasing Personal Information--Please state your
agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
In general, it is risky to give my
personal information to online
Strongly
2
Agree 7
companies.
There is high potential for loss
associated with giving my personal
information to online firms.
There is too much uncertainty
associated with giving my personal
information to online firms.
Providing online firms with my personal
information would involve many
unexpected problems.
In next section, we would like to know your evaluations of shopping on
YourFavoriteStore.com (where you just stated you frequently shop).
For each statement, please choose the response that best represents your opinion.
176
11. Fair Information Practice-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I feel that I was not informed by
MyFavoriteStore.com (where you stated
Strongly
2
Agree 7
you frequently shop) about who is
collecting my information.
I feel that I was not informed by the
company about what kinds of personal
information will be collected.
I feel that I was not informed by the
company about how my personal
information will be collected.
I feel that I have no choice about how
my personal information will be used.
I feel that I have no choice about
which parties my personal information
will be disclosed to.
The exchange of personal information
is equitable.
I have control over my personal
information.
I am adequately informed about the
use of the data which the company
collected from me.
The site clearly explains how user
information is used.
The online retailer only collects
personal information necessary for the
transaction to be completed.
12. Please tell us how do you feel about shopping on
YourFavoriteStore.com (where you stated frequently
shop)?
Strongly
Disagree
3
4
5
6
1
I think that buying a product from
MyFavoriteStore.com would be risky
Strongly
2
Agree 7
because of the possibility of
unauthorized access to my personal
information.
I think that buying a product from
MyFavoriteStore.com would be risky
because my personal information may
be released to other third-party.
I feel I don't have control over my
personal information when I shop at
MyFavoriteStore.com.
177
13. Please tell us how likely you are to prefer personalized
promotions online rather than non-personalized
promotions/ advertisements.
Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I am pleased when I receive
personalized advertising that has my
Strongly
2
Agree 7
name on the title from an advertiser
(company or brand) where I never
shopped before.
I am pleased when I receive
personalized advertising that has my
name on the title from stores I have
shopped before (such as
MyFavoriteStore.com).
I am pleased to see the advertising
tailored to my interests when I surfing
online.
I am pleased to see the
advertisements of the brands I
shopped when I use my social network
website (e.g., facebook, myspace).
I am pleased to see the personalized
advertisements when when I go to a
news website (e.g., msn news, New
York Times).
I am pleased to see the
advertisements of the brands I
shopped when I use online email
services (e.g., Gmail, hotmail, yahoo!
mail).
14. Perceived Fairness--How do you evaluate your shopping
experiences on YourFavoriteStore.com (where you stated
frequently shop)?
Please state your agreements with the following
statements.
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
I was treated unfairly.
I was treated wrong.
Shopping on MyFavoriteStore.com is an
unfair deal.
178
15. Perceived Trust-Please state your agreement with the following statements.
Strongly
Disagree
3
4
5
6
1
I can count on MyFavoriteStore.com to
protect my privacy.
MyFavoriteStore.com is a trustworthy
store.
I can count on MyFavoriteStore.com to
protect customers’ personal
Strongly
2
Agree 7
information from unauthorized use.
MyFavoriteStore.com can be relied on
to keep its promise.
Promises made by
MyFavoriteStore.com are likely to be
reliable.
I do not doubt the honesty of
MyFavoriteStore. com
I expect that MyFavoriteStore.com will
keep promises they make.
I expect that MyFavoriteStore.com has
good intentions toward me.
16. Shopping at
MyFavoriteStore.com (where you
stated frequently shop) makes me
feel:
Strongly
Disagree
2
3
4
5
6
1
Strongly
Agree 7
Fearful
Anxious
Frustrated
Conflictful
Irritated
Mad
Joyful
Happy
Delighted
Loving
Affectionate
Friendly
Attentive
Curious
Aroused
Excited
179
17. Repurchase Loyalty--Please state your agreement with
the following statements.
Strongly
Disagree
3
4
5
6
1
I intend to return to shop at
MyFavoriteStore.com.
I will use this store the next time I
want to make a purchase.
I probably won't switch to another
website to make purchases.
I would recommend this store to my
friends.
Strongly
2
Agree 7
You are almost done! Last, please tell us a little bit about yourself!
18. Gender
Male
Female
No response
19. Your age? (Format: 0-120)
20. Which college you are attending?
21. What is your class standing?
22. What is your ethnicity background?
23. Have you ever personally experienced the following?
Please check the box(es) that applied.
Spam/junk e-mails
ID theft
Credit card fraud
Others learning your personal info from online activities
Computer virus attack
e -mail read by someone other than recipient
N/A (I have never experienced any of above)
180
8. This is ending page
Thank you for your participation!!!
Your information will be used only for this study of “The effects of unsolicited behavioral tracking on
consumers’ evaluation of their online shopping experiences and attitudes toward trusted online retailers”.
The survey is completely anonymous and all information collected will be kept confidential.
If you have any questions about this research project, please contact: Tunmin (Catherine) Jai at
(541) 737-3797 or by email at jait@onid.orst.edu or Dr. Leslie Burns at (541) 737-0983 or by email at
Leslie.Burns@oregonstate.edu.
If you have questions about your rights as a participant, please contact the Oregon State University
Institutional Review Board (IRB) Human Protections Administrator, at (541) 737-8008 or by email
at IRB@oregonstate.edu.
Again, Thank You Very Much. Have a Great Spring Term!
181
Appendix 4
Category-Clothing/shoes/accessories
No. Website
Freq. Percentage
No. Website
1
Nordstrom.com
66
17.65%
2
Forever 21.com
50
13.37%
3
Victoria's secret.com 37
9.89%
28 Footlocker.com
2
0.53%
4
Amazon.com
30
8.02%
29 Free people
2
0.53%
5
Ebay.com
29
7.75%
30 Rei
2
0.53%
6
Urbanoutfitters.com 23
6.15%
31 Steep and cheap
2
0.53%
7
Nike.com
12
3.21%
32 Swell.com
2
0.53%
8
AE.com
10
2.67%
33 Tennis Warehouse
2
0.53%
9
Zappos.com
8
2.14%
34 Wet Seal
2
0.53%
10 Hollisterco.com
5
1.34%
35 Whiskey Malitia
2
0.53%
11 Macy's
5
1.34%
36 Bebe.com
1
0.27%
12 Anthropologie.com
4
1.07%
37 Betsey Johnson
1
0.27%
13 Eastbay.com
4
1.07%
38 Bing
1
0.27%
14 Google.com
4
1.07%
39 Buckle.com
1
0.27%
15 Jcrew.com
4
1.07%
40 Cabellas
1
0.27%
16 Karmaloop.com
4
1.07%
41 Coach.com
1
0.27%
17 Abercrombie.com
3
0.80%
42 DrJays.com
1
0.27%
18 Delias
3
0.80%
43 Ellendegeneres.com 1
0.27%
19 Oldnavy.com
3
0.80%
44 Endless.com
1
0.27%
20 Overstock. Com
3
0.80%
45 Etsy.com
1
0.27%
21 Saksfifthavenue.com 3
0.80%
46 Express.com
1
0.27%
22 Soccer.com
3
0.80%
47 Finishline.com
1
0.27%
23 Target.com
3
0.80%
48 Foxsoccershop
1
0.27%
24 Alloy
2
0.53%
49 Gap
1
0.27%
25 American Apparel
2
0.53%
50 Gilt.com
1
0.27%
26 BananaRepublic.com 2
0.53%
51 H&M
1
0.27%
27
Freq. Percentage
Body Central
www.bodyc.com
2
0.53%
182
No. Website
Freq. Percentage
52 Hautelook.com
1
0.27%
53 Hypebeast.com
1
0.27%
54 JC Penny
1
0.27%
55 Jessica London
1
0.27%
56 Kohl’s
1
0.27%
57 Lids.com
1
0.27%
58 Luckybrand.com
1
0.27%
59 Lulus.com
1
0.27%
60 Maurices.com
1
0.27%
61 TheNorthFace.com
1
0.27%
62 Pacsun.com
1
0.27%
63 Shopbop.com
1
0.27%
64 Sierrasnowboard.com 1
0.27%
65 Childrensplace.com
1
0.27%
66 Torrid.com
1
0.27%
67 Walmart.com
1
0.27%
68
WhiteHouseBlackMa
rket.com
1
0.27%
69 Woot.com
1
0.27%
Total
374
100.00%
183
Category-Book/Magazine
No.
Website
Freq. Percentage
1
Amazon.com
91
74.59%
2
Ebay.com
15
12.30%
3
Barnesandnoble.com 5
4.10%
4
Half.com
2
1.64%
5
Borders.com
1
0.82%
6
Chegg.com
1
0.82%
7
Craigslist
1
0.82%
8
Google
1
0.82%
10
Osubookstore.com
1
0.82%
11
Magazines.com
1
0.82%
12
Overstock.com
1
0.82%
13
Powell’s
1
0.82%
14
Urbanoutfitters.com
1
0.82%
122
100.00%
Total
Category-Entertainment (CD, videos, concert ticket)
No.
Website
Freq. Percentage
1
Amazon.com
37
48.68%
2
Ebay.com
21
27.63%
3
itunes.com
3
3.95%
4
Craiglist.com
2
2.63%
5
Eastbay.com
2
2.63%
6
Google
2
2.63%
7
Half.com
2
2.63%
8
BestBuy.com
1
1.32%
9
Barnesandnoble.com
1
1.32%
10
Hypebeast
1
1.32%
11
Steampowered.com
1
1.32%
12
Target.com
1
1.32%
13
Thinkgeek.com
1
1.32%
75
150.00%
Total
184
Category-Consumer Electronics
No.
Website
Freq.
Percentage
1
Amazon.com
28
43.75%
2
Ebay.com
20
31.25%
3
BestBuy.com
4
6.25%
4
Google.com
3
4.69%
5
Craiglist.com
2
3.13%
6
Woot.com
2
3.13%
7
Bing.com
1
1.56%
8
Cabelas.com
1
1.56%
9
Eastbay.com
1
1.56%
10
Target.com
1
1.56%
11
Walmart.com
1
1.56%
64
128.00%
Total
Category-Computer Hardware or Software
No.
Website
Freq. Percentage
1
Amazon.com
21
42.00%
2
Ebay.com
11
22.00%
3
Newegg.com
4
8.00%
4
BestBuy.com
3
6.00%
5
Google.com
3
6.00%
6
Half.com
2
4.00%
7
Apple.com
1
2.00%
8
Craigslist.com
1
2.00%
9
Eastbay.com
1
2.00%
10
Steampowered.com
1
2.00%
11
UrbanOutfitters.com
1
2.00%
12
Walmart.com
1
2.00%
50
100.00%
Total
Appendix 5
Means, Standard Deviations and Intercorrelations among Indicators
1
1 pbenf4
2
3
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
0.78**
3 pbenf6
0.77** 0.81**
-
4 prisk1
0.03
-0.01
0.01
5 prisk2
0.03
-0.01
-0.03
6 prisk3
0.01
-0.02
0.00
7 pfair1_r
0.07
0.10*
0.04 -0.53** -0.48** -0.50**
8 pfair2_r
0.06
0.08
0.02 -0.51** -0.51** -0.53** 0.83**
9 pfair3_r
0.05
0.09
0.03 -0.58** -0.54** -0.55** 0.81** 0.86**
0.83**
-
0.72** 0.72**
-
10 ptrst3
0.12** 0.18** 0.13** -0.42** -0.44** -0.45** 0.39** 0.42** 0.44**
11 ptrst4
0.12** 0.16** 0.12** -0.39** -0.38** -0.36** 0.36** 0.41** 0.42** 0.81**
12 ptrst5
0.12** 0.15**
13 mpreas1
0.14** 0.21** 0.19** -0.38** -0.37** -0.43** 0.39** 0.38** 0.39** 0.39**
14 mpreas2
0.15** 0.22** 0.20** -0.39** -0.39** -0.44** 0.43** 0.43** 0.45** 0.41** 0.38** 0.41** 0.95**
15 mpreas3
0.15** 0.22** 0.20** -0.38** -0.38** -0.42** 0.42** 0.42** 0.43** 0.42** 0.37** 0.40** 0.90** 0.93**
16 mdom3
-0.09* -0.11**
-0.02
-0.09*
19 marous1
0.16** 0.19** 0.20**
-0.04
-0.05
-0.07
0.04
0.09*
0.11* 0.12**
-0.06
-0.04
-0.05
0.03
0.08*
21 loyal1
0.08
0.07
0.10*
0.09*
0.85**
-
0.37** 0.38**
-
-0.04
-
0.54** 0.54** 0.53** -0.53** -0.54** -0.59** -0.37** -0.29** -0.32** -0.45** -0.48** -0.46** 0.78**
0.01
-0.10*
0.09
-
-0.10* 0.54** 0.55** 0.55** -0.60** -0.63** -0.65** -0.45** -0.40** -0.44** -0.47** -0.52** -0.50**
18 mdom5
20 marous2
-
0.11* -0.41** -0.38** -0.38** 0.39** 0.46** 0.46** 0.77**
17 mdom4
-
-0.10* 0.53** 0.53** 0.57** -0.60** -0.63** -0.64** -0.44** -0.35** -0.40** -0.51** -0.55** -0.54** 0.85** 0.79**
0.09* 0.16** 0.18** 0.17** 0.35** 0.36** 0.38** -0.12**
0.07
0.09* 0.14** 0.14** 0.28** 0.30** 0.30**
-0.04
-
-0.09* -0.15**
-0.02
-
-0.08 0.58**
-
0.05 -0.49** -0.46** -0.40** 0.41** 0.46** 0.48** 0.55** 0.53** 0.56** 0.35** 0.38** 0.38** -0.51** -0.44** -0.50** 0.15** 0.18**
-
0.07 -0.42** -0.39** -0.32** 0.35** 0.40** 0.42** 0.51** 0.52** 0.53** 0.31** 0.33** 0.33** -0.46** -0.40** -0.43** 0.15** 0.16** 0.85**
-
0.15** 0.15** 0.13** -0.53** -0.50** -0.46** 0.46** 0.51** 0.54** 0.59** 0.58** 0.61** 0.44** 0.47** 0.45** -0.55** -0.49** -0.54** 0.17** 0.19** 0.83** 0.80**
23 loyal4
23
-
2 pbenf5
22 loyal2
15
-
Mean
3.3
3.08
3.03
4.04
4.27
4.33
4.51
4.65
4.77
3.94
4.11
4.18
3.13
3.19
3.11
3.64
3.59
3.63
3.98
4.35
4.74
4.44
4.5
S.D.
1.6
1.59
1.57
1.69
1.64
1.71
1.62
1.65
1.6
1.56
1.46
1.47
1.73
1.78
1.75
1.76
1.76
1.79
1.75
1.62
1.76
1.72
1.84
Note: pbenf= perceived benefit, prisk= perceived risk, pfair= perceived fairness, ptrst=trust, mpreas= pleasure, mdom=dominance,
marous=arousal, loyal=repurchase loyalty. *p<.05, **p<.01, ***p<.001 (two-tailed), The scale items are shown in Table 3.4.
185