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. 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Consumers’ perceptions about personalized advertising: comparisons across advertisements delivered via three different types of media. International Journal of Consumer Studies, 33(4), 503-514. 117 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