Consumers' perceptions about personalized advertising

International Journal of Consumer Studies ISSN 1470-6423

‘Hello, Mrs. Sarah Jones! We recommend this product!’ Consumers’ perceptions about personalized advertising: comparisons across advertisements delivered via three different types of media ijcs_784

503..514

Jay (Hyunjae) Yu1 and Brenda Cude2 1

Manship School of Mass Communication, Louisiana State University, Baton Rouge, LA, USA College of Family and Consumer Sciences, University of Georgia, Athens, GA, USA

2

Keywords Personalized advertising, privacy, advertising effect, consumer behaviour. Correspondence Jay (Hyunjae) Yu, Manship School of Mass Communication, Louisiana State University, Baton Rouge, LA 70808, USA. E-mail: [email protected] doi: 10.1111/j.1470-6431.2009.00784.x

Abstract As new technologies (e.g. online, mobile and interactive TV) develop worldwide, numerous types of personalized advertising, in which companies use an individual’s name and/or other types of personal information, have become more popular in many countries. Using many types of information about specific individuals, personalized advertising is designed to convey a customized message at the right time to the right person using diverse media. However, despite its universally increased use, few academic studies have explored the effectiveness of personalized advertising and consumers’ response to it. This exploratory study focused on consumers’ perceptions of personalized advertising delivered online (e-mail) and offline (letter and telephone call). The results show that consumers generally have negative perceptions of personalized advertising, regardless of how it is delivered, with the strongest negative reaction to telephone calls.

Companies’ interest in planning and conducting personalized advertising is increasing around the world (Poon and Jevons, 1997; Gal-Or and Gal-Or, 2005). Researchers from diverse countries including the US, China, South Korea, Greece, Mexico, Taiwan, Poland and Germany have recently investigated several issues regarding this miraculous boom in personalized advertising (Bozios et al., 2001; Yuan and Tsao, 2003; Chorianopoulos et al., 2004; Tsang et al., 2004; Bulander et al., 2005; Kazienko and Adamski, 2007). One of the major motivations for this universal interest in personalized advertising is directly related to marketers’ increasing doubts about the effectiveness of many traditional advertising methods that target mass audiences, methods they have long relied upon to market a variety of products (Jin and Villegas, 2007). The effectiveness of traditional mass advertising, which is generally produced in identical messages for a non-specific audience, has been questioned due to diverse reasons, such as increasing advertising clutter (Rotfeld, 2006), people’s general avoidance of advertising (Kim and Pasadeos, 2007), and the development of several technologies such as DVRs (Digital Video Recorders) that allow consumers to avoid exposure to advertisements if they choose (‘Digital Home Technology: Tivo Builds Real Time DVR Advertising Research Offering’, 2006). The development of new communication technologies may not only have weakened traditional advertising’s effectiveness, but it also has made delivery of diverse types of personalized advertising

International Journal of Consumer Studies 33 (2009) 503–514 Journal compilation © 2009 Blackwell Publishing Ltd

possible (Pramataris et al., 2001; Howard and Kerin, 2004; Morimoto and Chang, 2006). not just to developed western countries, but worldwide (Consumers International, 2002). Personalized advertising can be delivered using techniques more advanced than traditional e-mails, including personalized web pages that use cookies to capture an individual’s history of web surfing, personalized interactive television advertising, smart banners and mobile advertising (Bozios et al., 2001; Pramataris et al., 2001; Yuan and Tsao, 2003). The Internet’s popularity in daily life in many countries around the world has also given companies another way to gather consumer information for marketing purposes (M2PressWIRE, 2006; Trollinger, 2006). Companies use all possible channels, both online and offline, to develop personal information databases about consumers (Marketing News, 2006). These databases make it possible to create personalized advertisments with customized messages for each individual consumer (Kim et al., 2001; Yuan and Tsao, 2003; Lekakos and Giaglis, 2004; Wolin and Korgaonkar, 2005). However, despite the increase in the amount of personalized advertising, as well as the development of diverse new technologies that can be used to deliver it, few academic researchers have examined consumer responses to it (Sundar and Kim, 2005). Researchers from many countries (e.g. Li et al., 2002; Sheehan and Hoy, 1999; Wu, 2006) have noted the need to learn more about 503

Consumers’ perceptions about personalized advertising

consumers’ attitudes towards the phenomenon known as personalized advertising. While a personalized advertising message may be more effective because the message is individualized (Pavlou and Stewart, 2000), it also may be rejected by consumers who are concerned about their privacy (Sheehan and Hoy, 1999; Miyazaki and Fernandez, 2000; Sacirbey, 2000; Phelps et al., 2001). This could possibly lead to negative attitudes as well as the marketer (Sheehan and Gleason, 2001). Motivated by the controversy surrounding the effects of personalized advertising, this exploratory study investigated consumers’ actual attitudes towards personalized advertising. More specifically, this study aimed to learn if consumers’ perceptions of personalized advertising differ depending on the type of media used to deliver it: online (e-mail), offline mail (letter), and telephone (solicitation phone call). In addition, this study examined consumers’ self-reported responses upon receiving personalized advertising, their privacy concerns and their intentions to purchase the product in the personalized advertisement. Finally, this research investigated the relationships between consumers’ intentions to purchase the advertised product and three independent variables (i.e. general perceptions of personalized advertising, actual responses to personalized advertising and privacy concerns). The influence of these three variables on consumers’ purchase intentions was examined for each of the three media types. Even though the sample for this study only included American consumers, the researchers expect that the results will provide important implications for marketers and researchers in other countries. In a global economy, consumers in diverse cultures have much in common in terms of exposure to advertising, especially advertising delivered online, and thus share some common attitudes about advertising (e.g. Wolburg and Kim, 1998; Adler et al., 2004; Yu et al., 2008).

This study’s definition of personalized advertising In this study, personalized advertising was defined as advertising that is created for an individual using information about the individual (Yuan and Tsao, 2003; Wolin and Korgaonkar, 2005). This information includes either personally identifying information such as one’s e-mail address, name, or residence, and/or personal information such as shopping history, websites visited, preference for a specific product, or one’s hobby. Further, personalized advertising in this study was limited to advertising delivered without the individual’s prior permission (Pavlou and Stewart, 2000). Other terms have been commonly used to mean something similar to personalized advertising, such as ‘customized advertising’ (Tsang et al., 2004; Gal-Or and Gal-Or, 2005) and ‘interactive advertising’ (Sasser et al., 2007). However, personalized advertising is a broader term that is relevant to advertising delivered via any type of media, and thus was more appropriate for this study.1

1

The terms interactive advertising and customized advertising have been mainly used in online advertising and mobile advertising contexts because of their technological interactivity (Pramataris et al., 2001; Xu et al., 2008).

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The increasing prevalence of personalized advertising Given the popularity of one-to-one marketing (Friedman and Vincent, 2005), database marketing (Wehmeyer, 2005) and relationship marketing (Palmatier et al., 2006), companies’ interest in collecting consumers’ personal information is greater than ever worldwide. In the US, the Federal Trade Commission (FTC) reported that approximately 92% of websites collected personal information for future marketing (FTC, 2000). Some specialized third parties collect and sell information to other companies as well (Pavlou and Stewart, 2000). Basic database programs can be merged to provide an in-depth portrait of a consumer’s individual purchasing behaviour (Foxman and Kilcoyne, 1993), including personalized information that can be diverse and include demographic characteristics, geographic information and psychographic information (Lekakos and Giaglis, 2004). The FTC (2009) reported that information for personalized advertising comes from multiple sources, such as consumers’ online activities including the searches they routinely conduct, the web pages they visit, and even the specific content they view. Personalized advertising’s popularity even challenges the longstanding definition of advertising. According to the American Marketing Association (Alexander, 1960) and several researchers (Rosenberg, 1995; Perreault and McCarthy, 1999; Armstrong and Kotler, 2000), advertising is defined as any paid form of nonpersonal presentation and promotion of ideas, goods or services by an identified sponsor through mass communication media. As some important elements surrounding the definition change, there is room for re-thinking the concept of ‘non-personal’. New technology that transforms mass communication into a series of personalized advertising messages may eventually shift the focus of traditional mass advertising to more individualized and focused audiences (Pavlou and Stewart, 2000).

Perspective 1: positive effects of personalized advertising Positive aspects of personalized advertising for both consumers and marketers have been repeatedly noted. Several researchers have indicated that personalized advertising can increase user involvement and thus the advertisement’s effectiveness (Stewart and Ward, 1994; Roehm and Haugtvedt, 1999; Pavlou and Stewart, 2000; Yuan and Tsao, 2003; O’Leary et al., 2004). In personalized advertising, consumers receive only messages that are relevant to them, which are more likely to generate purchase intentions or other desired responses (Pavlou and Stewart, 2000). McKeen et al. (1994) suggested that consumers’ greater involvement in advertising also increases their satisfaction with advertising. Howard and Kerin (2004) also found that personalization in the advertising copy increased advertising effectiveness. In their experiments, the response rate to advertisements with personalized notes such as ‘Hello Miss OOO! Try this. It works!’ was higher than the response rate to non-personalized advertising messages. An important benefit of personalized advertising is the potential for increased interaction between the consumer and the advertising. Nowak et al. (1999) found in their empirical study that personalized online advertising increased the possibility of clicking behaviour among consumers. Rodgers and Thorson


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(2000) also noted that referring to users by name and mentioning consumers’ specific interests in an advertisement can increase interaction. Pavlou and Stewart (2000) hypothesized that the degree to which advertising is perceived to be personalized and individually focused would be an important measure of advertising’s effectiveness.

Perspective 2: negative effects of personalized advertising While personalized advertising has benefits for both marketers and consumers, several scholars have noted its negative effects and speculated about whether the negatives might offset the positives (Sheehan, 1999; Sacirbey, 2000; Phelps et al., 2001). Tsang et al. (2004) found that consumers who responded to their survey generally had negative attitudes towards personalized mobile advertising unless they had specifically consented to it. Also, they confirmed a direct relationship between unfavourable consumer attitudes and future consumer behaviour and suggested that it is unwise to send personalized advertising messages to potential customers without prior permission. Further, many have discussed whether personalized advertising violates consumers’ privacy rights (Sheehan and Hoy, 1999; Miyazaki and Fernandez, 2000). In their study of online personalized advertising, Sheehan and Hoy (1999) found that many participants did not respond to personalized advertisements; in fact, many asked their Internet Service Providers to remove them from the mailing list. The respondents also reported that they were less likely to register for websites that requested their personal information. According to the recent UPI-Zogby International Poll (2007), more than 90% of the participants from diverse countries were concerned about their privacy or the possibility of identity theft in their daily lives. Under this situation, personalized advertising becomes less effective for consumers everywhere if they view it as a serious invasion of their privacy (Sheehan, 1999; Gurau et al., 2003). The dilemma of ‘personalization vs. privacy’ epitomizes this complicated situation regarding the effects of personalized advertising (Long et al., 1999; Caudill and Murphy, 2000; Mabley, 2000). As online users become more sophisticated and advertisers create more ways to deliver targeted content, both consumers and marketers expect personalized advertising more than ever. Gurau et al. (2003) reported that many customers want more individualized attention, one-to-one communication and personalized offers. On the other hand, the potential for abuse to individual consumers has increased exponentially as the amount of personal data collected in consumer marketing database has grown (Caudill and Murphy, 2000). Therefore, several researchers have warned marketers not to use personalized advertising without questioning its possible negative effects (e.g. Nowak et al., 1999; Sacirbey, 2000). The possibility of violating consumers’ privacy has lead to new discussions about regulations for diverse types of personalized advertising in many countries including the US, China and several European countries (Gao, 2005; King, 2008). Issues surrounding personalized advertising and privacy are a comparatively new realm because the major topics in advertising regulation have traditionally dealt with specialized audiences (e.g. children, adolescents senior citizens) (Ward, 1976; Pereira et al., 2005), offen-



sive content in advertising (e.g. sex, violence) (Nathanson, 1999), the sensitive nature of some products advertised (e.g. cigarettes, alcohol, medications) (Sheehan, 2005; Yu et al., 2008), and fraud in advertising (e.g. messages in diet advertising) (Moschis and Moore, 1979). In 2008, the FTC proposed guidelines for advertisers regarding personalized advertising (FTC Staff Report 2009). The FTC, as well as regulators in several other countries (Gao, 2005), has relied upon self-regulation rather than establishing strict regulations (Bulander et al., 2005). Even countries with more restrictive traditions in advertising regulations, such as China, Taiwan and South Korea (Tsang et al., 2004; Gao, 2005), have adopted a self-regulation approach to personalized advertising. Thus, understanding consumers’ perceptions of personalized advertising is important. Self-regulation increases the opportunities for marketers to make mistakes in preparing and delivering personalized advertising, mistakes that can harm consumers.

Research questions This study investigated consumers’ perceptions of and attitudes towards the three types of personalized advertising. Data were collected via a four-part online survey. The survey addressed (1) general perceptions of personalized advertising, (2) self-reported responses upon receipt of personalized advertising, (3) opinions about personal privacy regarding personalized advertising, and (4) intentions to purchase the advertised product. The results from the four parts indicated above were compared among the three different types of personalized advertising (through e-mails, letters and telephone calls). Reflecting the personalization vs. privacy debate, this study set out to answer the following research questions (RQ): • RQ 1: What are consumers’ general perceptions of personalized advertising? Are their perceptions positive, negative or neutral? • RQ 2: How do consumers respond when they receive personalized advertising? • RQ 3: What are consumers’ perceptions of the effect of personalized advertising on their privacy? • RQ 4: How does personalized advertising affect consumers’ intentions to purchase the advertised product? The next research question examined possible differences between the media used to deliver personalized advertising. Chaudhuri and Buck (1995) indicated that media differences are one of the key determinants of consumers’ emotional and rational responses to advertising. According to their study, media differences were the best predictor of consumers’ responses to advertising. Several other researchers also have documented the relationship between media type and attitudes towards advertising (e.g. Krugman, 1965; Petty and Cacioppo, 1986; Cutler and Thomas, 2000; Chachko, 2004). More specifically, Trollinger (2006) recently suggested media balance in using personalized advertising, suggesting that e-mail and traditional offline mail together achieve a better result than e-mail alone. He recommended the combination based upon the notion that consumers generally respond differently to the two types of media. 505


Thus, Research Question 5 asked: • RQ 5: How do the different media used to deliver personalized advertising affect general perceptions of personalized advertising, self-reported response to personalized advertising, perceptions of the interaction of personalized advertising with privacy, and consumers’ purchase intentions? The next question dealt with the effect of gender differences on consumers’ opinions about personalized advertising through the three types of media. Sheehan (1999) and Wolin and Korgaonkar (2005) have identified gender as a significant factor in the level of privacy concern experienced when exposed to personalized advertising. Thus, the sixth research question was: • RQ 6: How does gender affect general perceptions of personalized advertising, self-reported response to personalized advertising, perceptions of the interaction of personalized advertising with privacy, and consumers’ intentions to purchase the product advertised? Lastly, the possible relationships between consumers’ intentions to purchase the advertised product and the three independent variables (general perceptions of personalized advertising, self-reported responses to personalized advertising and privacy concerns) were examined. The three variables’ influence on consumers’ purchase intentions has been an important topic in consumer marketing literature for a long time (e.g. Phelps et al., 2001; Tsang et al., 2004). Research Question 7 specifically dealt with an implication of the relationships above in a personalized advertising context: • RQ 7: How do general perceptions about personalized advertising, self-reported responses to personalized advertising and privacy concerns influence consumers’ intentions to purchase the product in personalized advertising delivered via three different types of media (online, letter and telephone calls)?

Method Sample A total of 231 young adults (college students, between the ages of 19 and 24) were recruited as the participants for the survey. Young adults in this age range are one of the major consumer groups for diverse products not only in the US but also in many other countries (Huang, 1998; Sheehan, 1999; Tsang et al., 2004; Paek, 2005). To recruit a convenience sample, the researchers selected an introductory journalism class at a state university in the southeastern part of the US. With the professor’s authorization, one of the authors visited the class and briefly explained the nature of the survey. Only the title and topic of the study were made known to the participants. The online survey was conducted using Survey Monkey website (http://www.surveymonkey.com). An author sent e-mails to all 231 students in the class to invite them to participate in the survey; the e-mail provided the link to the survey questionnaire. Among the 231 participants, 195 participants responded to the survey (84.4%), and all but three provided complete responses. Consequently, 192 completed surveys were used for the analysis. The survey was conducted over a period of 506

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5 days. In addition to receiving extra credit from their professors, the participants were entered in a drawing for a $50 gift card to the campus bookstore. The questionnaire included four major sections reflecting the first four research questions (see Table 1–4). As indicated above, the four topics have been a main focus in discussions related to personalized (customized) advertising and one-to-one marketing: (1) general perceptions of personalized advertising (Nowak et al., 1999; Pavlou and Stewart, 2000); (2) actual behaviours in response to personalized advertising (Sheehan and Hoy, 1999; Howard and Kerin, 2004); (3) consumers’ privacy concerns regarding personalized advertising (Sacirbey, 2000; Phelps et al., 2001); and (4) consumers’ intentions to purchase the product advertised (Chachko, 2004; Sundar and Kim, 2005). Each section of the survey included five specific statements asking for consumers’ opinions using an agree–disagree 5-point scale, with ‘5’ representing agreement. In each section, the same questions were asked three times about the three different media: (1) online (e-mail), (2) offline mail (letter), and (3) offline (phone call). The participants were given the researchers’ definition of personalized advertising prior to taking the survey (‘Personalized advertising is defined as advertising that is created for an individual using information about the individual, either personally identifying information such as one’s e-mail address, name, or residence, and/or personal information such as shopping history, preference of a specific product or hobby. Also, personalized advertising in this study is limited to advertising delivered without the individual’s prior permission’). All of the items in the survey questionnaire were pre-tested with 30 randomly selected consumers who had characteristics similar to those of the actual participants. Each set of questions regarding the three different types of media was preceded by one of the following statements to put the questions in context: • Have you ever received an e-mail that had your name (or your online name) in the title such as ‘Hello, Sarah’ or ‘Hello, Shopgirl 501’ from advertisers you don’t know? • Have you ever received mail (offline, letter) that had your name (or your address) in the title such as ‘Mr. Douglas, Mrs. Jones’ from advertisers (company, store, brand, people) you don’t know? • Have you ever received a phone call that indicated your name (or your other personal information) such as, ‘Hello, Mr. Geller’ or ‘Hello, Mrs. Jones’ from advertisers (people, company, brand, store) you don’t know?’ Participants responded to a total of 60 statements (20 per each media type). In addition, they also indicated their gender and age as well as their e-mail address to contact them regarding compensation for participation in the survey.

Results (RQ1) General perceptions regarding three types of personalized advertising Overall, the consumers’ general perceptions of personalized advertising were negative (see Table 1). However, they were less likely to take personalized advertising seriously if it was delivered online (mean 4.1) rather than offline by mail (mean 3.6) or telephone (mean 3.97). All differences by media type were significant in the t-tests at the P < 0.01 level. The typical response to the International Journal of Consumer Studies 33 (2009) 503–514 Journal compilation © 2009 Blackwell Publishing Ltd

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Table 1 General perceptions of personalised advertising

Statement

Mean

When I receive personalized advertising that has my name on the title from an advertiser (company, brand, people) who I don’t know, I don’t generally take it seriously. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I feel curious and uncomfortable because the advertisers got my personal information without letting me know. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, even though it is an unfamiliar advertiser, I will be interested if it is about a product I like. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I feel I am being treated with special care. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I am upset because my e-mail address (address, telephone number) is my important personal information. Online mail Offline mail Telephone call

statement, ‘When I receive that kind of personalized advertising, I feel curious and uncomfortable because the advertisers got my personal information without letting me know’ was general agreement – means of 3.92 for online personalized advertising, 3.08 for offline mail, and 3.63 for a telephone call. The responses to a somewhat stronger reaction (‘being upset’) to personalized advertising were similar with the most negative response being to a telephone call. The two statements that described potential benefits of personalized advertising to consumers were met with the strongest levels of disagreement. Consumers generally were not very interested in the products in personalized advertising; interest was strongest for products in personalized advertisements delivered via offline mail (3.07) and weakest if the advertisement was delivered via a telephone call (1.84). The strongest level of disagreement was for the statement ‘When I receive that kind of personalized advertising, I feel I am being treated with special care’. Respondents were more negative about a telephone call (mean 1.63) than online mail (1.45) or offline mail (2.09).

(RQ2) Self-reported responses to personalized advertising Regarding the consumers’ typical response to personalized advertising, many participants agreed that they reject it immediately (mean 4.18 online mail; 3.04 offline mail; 3.72 telephone call) (see Table 2). The differences by media type were significant in the t-tests at the P < 0.01 level. Also, most participants answered that they were not willing to open unsolicited e-mail or mail or to listen


Gender difference

Media difference P < 0.01

4.10 3.60 3.97 P < 0.01 3.92 3.08 3.63

P < 0.01 (female)

P < 0.01 2.06 3.07 1.84 P < 0.01 1.45 2.09 1.63

P < 0.05 (female)

P < 0.01 3.68 3.09 3.79

to a phone call even if it was personalized (mean 1.95 online mail; 3.32 offline mail; 1.81 telephone call). They were more likely to open offline mail than to open an e-mail or take a telephone call. Although respondents answered that they tended not to read or listen to personalized advertising, they also did not complain to marketers about the advertising or seek more information about the advertised products. Respondents generally did not demand to know how the advertiser got their personal information (mean 1.6 online mail; 1.62 offline mail; 2.23 telephone call) or to ask not to receive future advertisements (mean 2.43 online mail; 1.72 offline mail, 3.53 telephone call). Nor did they request more information about the product being advertised (mean 1.35 online mail; 1.74 offline mail; 1.81 telephone call).

(RQ3) Perceptions about privacy and personalized advertising The scores for all of the statements concerning privacy and personalized advertising were greater than 3.0, indicating an overall negative relationship between personal privacy and personalized advertising (see Table 3). Answers to three of the five statements were significantly different at the P < 0.01 or the P < 0.05 level. Respondents generally thought that advertisers were violating their privacy (mean 3.65 online mail; 2.99 offline mail; 3.63 telephone call) by delivering personalized messages. Also, they worried about what other personal information advertisers might have (mean 3.70 online mail; 3.46 offline mail; 3.58 telephone call). Participants generally agreed that acquiring their e-mail addresses/mailing addresses/telephone numbers without any 507


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Table 2 Actual response to personalized advertising

Statement

Mean

When I receive personalized advertising that has my name in the title from an advertiser (company, brand, store, people) who I don’t know, I am willing to open it and read it (listen to it). Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I delete it (throw away, hang up) immediately. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I have sent an email (mail, called back) to an advertiser demanding to know how they got my personal information. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I have sent an e-mail (mail, called back) to an advertiser asking them not to send (call) advertisements to me anymore. Online mail Offline mail Telephone call When I receive that kind of personalized advertising, I have sent an e-mail (mail, called back) to an advertiser asking for more information about the product being advertised. Online mail Offline mail Telephone call

Gender difference


1.95 3.32 1.81 P < 0.01 4.18 3.04 3.72

P < 0.05 (male) P < 0.01

1.60 1.62 2.23

P < 0.05 (male) P < 0.01

2.43 1.72 3.53

P < 0.05 (female)

P < 0.01 1.35 1.74 1.81

P < 0.01 (male)

Table 3 Privacy concerns and personalized advertising

Statement When I receive personalized advertising that includes my name from an advertiser (company, brand, store, people) who I don’t know, I believe my information can be accessed by all advertisers if they want it. Online mail Offline mail Telephone calls When I receive personalized advertising, I feel my privacy has been violated. Online mail Offline mail Telephone calls When I receive personalized advertising, I don’t consider my e-mail address (address, telephone number) to be private. Online mail Offline mail Telephone calls When I receive the personalized advertising, I am worried about what other information about me they also have. Online mail Offline mail Telephone calls When I receive the personalized advertising, I think getting e-mail addresses (address, telephone number) without any authorization is a type of crime. Online mail Offline mail Telephone calls

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Mean

Gender difference

3.64 3.62 3.65

P < 0.05 (female)

Media difference

P < 0.01 3.65 2.99 3.63

P < 0.05 (female)

3.45 3.38 3.42 P < 0.05 3.70 3.46 3.58

P < 0.05 (female)

P < 0.05 3.07 2.79 3.02


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Table 4 Attitude towards advertiser in personalized advertising and purchase intentions

Statement

Mean

When I receive personalized advertising including my name from an advertiser (company, brand, store, people) who I don’t know, I feel terrible about this advertiser. Online mail Offline mail Telephone calls After I receive personalized advertising, I have made purchases from the advertiser who sent me the e-mail (direct mail, calling). Online mail Offline mail Telephone calls When I have received personalized advertising, I have told my friends or family not to buy products from the advertiser. Online mail Offline mail Telephone calls After getting this kind of personalized advertising, I am likely to buy from this advertiser. Online mail Offline mail Telephone calls After getting this kind of personalized advertising, I don’t trust the advertiser and its products, because they got my e-mail address (address, telephone number) without my knowledge. Online mail Offline mail Telephone calls

authorization is a type of crime (mean 3.07 online mail; 2.79 offline mail; 3.02 telephone call). In general, their concern about privacy was stronger for online mail and telephone calls than for offline mail.

(RQ4) Consumers’ intentions to purchase the product advertised Overall, consumers’ intentions to purchase the products in personalized advertising were low (see Table 4). The mean scores indicated that personalized advertisements generated negative attitudes towards the advertisers (mean 3.42 online mail; 2.91 offline mail; 3.43 telephone call) and caused mistrust in the advertisers (mean 3.52 for online mail; 2.88 offline mail; 3.55 telephone call). All differences by media type were significant at the P < 0.01 level. In addition, mean scores were very low for having purchased a product advertised in personalized advertisements (mean ranging from 1.71 for online mail to 2.60 for offline mail) and intentions to buy advertised products in this way (1.84 for online mail to 2.40 for offline mail). Respondents were generally unlikely to recommend products promoted via personalized advertisements to others (means of 2.13 to 2.50 across the three media types).

(RQ5) Different attitudes towards personalized advertising among the three media types To examine differences in participants’ answers by type of media, one-way analysis of variance (ANOVA) tests were used. Negatively worded items were re-coded before conducting the ANOVAs. After the reverse coding, all the answers could be


Gender difference


3.52 2.88 3.55 P < 0.01 1.71 2.60 1.83 P < 0.01 2.20 2.13 2.50

P < 0.05 (male) P < 0.01

1.84 2.40 1.92 P < 0.01 3.42 2.91 3.43

polarised into (1) favourable to personalized advertising, and (2) not favourable to personalized advertising. As seen in the fourth column of Tables 1–4, there were significant differences among 18 of the 20 questions by type of media used to deliver the advertising, and 16 out of 18 were significant at the P < 0.01 level. Based on the results from the one-way anovas, the Post hoc (Bonferroni) test was conducted to learn more detailed information about the differences among the three different types of personalized advertising. In general, participants were less negative about personalized advertising delivered via offline mail than about advertising delivered via either of the other two types of media (Table 1–4). Differences were significant at the P < 0.01 level. For example, the participants strongly agreed with the statements, ‘When I receive that kind of personalized advertising, even though it is an unfamiliar advertiser, I will be interested if it is about a product I like’ and ‘When I receive that kind of personalized advertising, I feel I am being treated with special care’ if the media were offline mail. On the other hand, the answers to these statements were more negative if the medium used to deliver the advertising was an e-mail or a phone call. Participants were also significantly more likely to read personalized advertising in a letter than to read an e-mail or listen to a phone call. However, there were fewer differences by media type among participants’ answers to the questions dealing with privacy issues (see Table 3). The three items that were significantly different indicated that respondents were somewhat less concerned about their privacy when personalized advertising was delivered via offline mail compared to e-mail or a phone call. 509


(RQ6) Gender differences and attitudes towards personalized advertising There were significant differences between the answers of males and females in only 10 of the 60 statements (see Tables 1–4). T-tests indicated that women felt more uncomfortable about personalized advertising than males (see Table 1, P < 0.01). However, women were more likely to agree with the statement, ‘When I receive that kind of e-mail, I feel I am being treated with special care’ (see Table 1, P < 0.05). Women were also more likely than men to say they respond to a personalized advertisement by asking not to receive the advertising in the future (see Table 2, P < 0.05). Females were more concerned than males about the possibility that the advertiser might have other personal information about them (see Table 3, P < 0.05) and to feel that personalized advertising violates their privacy (see Table 3, P < 0.05). Male respondents were more likely than females to say they immediately reject a personalized advertisement and to demand to know how the advertiser got their personalized information (see Table 2, P < 0.05). Interestingly, males were more likely to say they request information about the product being advertised (see Table 2, P < 0.01). In a contradictory finding, males also were more likely than females to say they tell family or friends not to buy from the advertiser involved in a personalized advertisement (see Table 4, P < 0.05).

(RQ7) Influence of general perceptions of personalized advertising, actual responses to personalized advertising and privacy concerns on the purchase intentions of the product advertised To answer this research question, a series of hierarchical logistic regression analyses was performed using the three independent variables (general perceptions of personalized advertising, actual responses to personalized advertising, and privacy concerns). The dependent variable was the participants’ intentions to purchase the product advertised. Each of the independent variables significantly influenced consumers’ intentions to purchase the product advertised when personalized advertising was delivered online (see Table 5).

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The significant influences of the three independent variables (general perceptions of personalized advertising, actual responses to personalized advertising and privacy concerns) on the participants’ purchase intentions of the product advertised also were found for offline personalized advertising (Table 6) and telephone calls (Table 7). In other words, the results of the regression analyses clearly showed that there were not meaningful differences among the three types of personalized advertising in terms of the relationship between intentions to purchase the product advertised and the three independent variables (general perceptions of personalized advertising, actual responses to personalized advertising and privacy concerns).

Discussion Rethinking personalized advertising Marketers worldwide have spent large sums of money to create and deliver personalized advertising (Low, 2000; Kim et al., 2001; Pramataris et al., 2001; Gurau et al., 2003) with the general belief that the advertisement will be more effective because it is personalized (Roehm and Haugtvedt, 1999; Pavlou and Stewart, 2000). However, this study revealed that personalized advertising delivered via all three types of media generated more negative than positive effects among the respondents. Although there were some exceptions, participants tended to not like receiving personalized advertising. The results clearly suggested that all marketers should think seriously about the possible negative effects of personalized advertising before using it. In the case of online personalized advertising, the most typical response from participants was to delete the advertisement before even opening it. Therefore, smarter ways to create and send customized messages online require special effort on the part of the company, as the targeted consumer may see it as junk e-mail and delete it without even reading it. Actually, consumers’ general avoidance of online advertising is evident in the current literature (Jin and Villegas, 2007) and is a worldwide trend (Hoeken et al., 2003). For example, Cho and Cheon (2004) found that consumers from both western and eastern countries generally avoid online advertising messages. They suggested three important variables that cause advertising avoidance

Table 5 Online personalized advertising Predictors Model 1

Model 2

Model 3

B General perceptions about personalized advertising Adjusted R square d.f. = 1, MS = 15.420, F = 65.076, P = 0.000 General perceptions about personalized advertising and responses to the personalized advertising Adjusted R square d.f. = 1, MS = 9.045, F = 40.316, P = 0.000 General perceptions about personalized advertising, responses to the personalized advertising, and consumers’ privacy concerns Adjusted R square d.f. = 1, MS = 6.985, F = 33.167, P = 0.000

0.501* 0.247 0.444* 0.287 0.303* 0.331

Hierarchical regression for predicting consumers’ attitude towards the advertisers/purchase intention using three variables (general perceptions about personalized ads, actual responses and privacy concerns). DV, Consumers’ attitude towards the advertisers/purchase intention, *P < 0.01.

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Table 6 Letter/package personalized advertising Predictors Model 1

Model 2

Model 3


0.559 0.308 0.531 0.364 0.389 0.404

Hierarchical regression for predicting consumers’ attitude towards the advertisers/purchase intention using three variables (general perceptions about personalized ads, actual responses and privacy concerns).

Table 7 Telephone personalized advertising Predictors Model 1

Model 2

Model 3


0.583 0.336 0.523 0.381 0.373 0.421

Hierarchical regression for predicting consumers’ attitude towards the advertisers/purchase intention using three variables (general perceptions about personalized ads, actual responses and privacy concerns).

through their cross-cultural survey: (1) perceived goal impediment, (2) perceived ad clutter, and (3) prior negative experience. Among those, the authors found that perceived goal impediment was the most significant reason people generally wanted to avoid online advertising. In many cases, online users have their own goals when they access the Internet. Therefore, they pay little or no attention to online advertising that is not related to their task. In addition, a fourth negative influence is present for those who view the advertising as an invasion of their privacy (Sheehan, 1999). This study presents the dilemma posed by personalized advertising for both marketers and consumers. How can marketers convey personalized advertising messages without giving the offensive impression of violating their customers’ privacy? How can consumers take advantage of advertising tailored to their interests and still protect their privacy? It is the right time for a more comprehensive discussion about how to deliver personalized advertising for a net positive effect. Future research could explore various avenues including copy testing, creating less intimidating titles for e-mails, or asking for pre-consent before sending personalized advertising to consumers.

The differences among the three media and gender’s influence Among the three types of media used to deliver personalized advertising, this study’s respondents showed comparably more


favourable responses towards delivery via offline mail than the other two types of media. They were less likely to reject the mail immediately, more likely to take it seriously, less threatened by the personalized advertisement as a violation of their privacy, and somewhat more likely to view it as personal attention. Actually, these results support the conclusions of some researchers (e.g. Trollinger, 2006) who have suggested that companies need to balance online personalized advertising with traditional personalized advertising in their marketing efforts. Consumers may find traditional mail less threatening because if one opens it and finds it uninteresting, it can be thrown away and no harm is done. However, it may not be as easy to end a phone call with a telemarketer or to deal with the after effects of opening an e-mail that potentially contains a harmful virus or worm. In general, personalized advertising delivered via a phone call generated the most negative response, as well as privacy concerns equal to those about online advertising. Approximately 100 million telephone numbers are registered in the US ‘Do Not Call Registry’, and more than half of the states in the US have withdrawn their Motor Vehicle Registry data from marketing use (Marketing News, 2006). Researchers in multiple countries have concluded that phone calls no longer seem to be an effective delivery option for personalized advertising (Hoeken et al., 2003). The results also confirmed the findings of previous researchers (Sheehan, 1999; Wolin and Korgaonkar, 2005) that females are more concerned about privacy than males. However, it is unclear 511


why this is the case. Do the differences actually reflect differences in experience, especially online? Or do they reflect differences in willingness to trust or other psychographic variables? This area is one for further exploration.

Public policy and personalized advertising Many of the US consumers who completed the survey agreed that using one’s personal contact information to deliver personalized advertising without any authorization ‘is a type of crime’. In fact, in the US, there are few legal restrictions on businesses’ ability to collect and use or even sell personal information. An exception is the US Do Not Call Registry; there are significant fines for telemarketers who call consumers who have registered their telephone numbers with this list. The FTC’s proposed guidelines for self-regulation when conducting personalized advertising include an expectation that any company collecting or storing consumers’ private information should provide reasonable security for that information, and should retain the data only as long as is necessary to fulfil a legitimate business or law enforcement need (The Computer & Internet Lawyer, 2008). The FTC also has recommended that companies only collect an individual’s information for personalized advertising if they obtain affirmative, expressed consent from the consumer to receive such advertising. In contrast to the US approach of no national policy on privacy, the European Union (EU) has adopted strict rules, with mechanisms for global enforcement. The EU rules require retailers to seek consumers’ permission before they collect and use personal data in their own marketing, trade it to partners or sell it. In the EU, how much information and how long it can be kept is restricted and consumers have open access to data about themselves and the right to collect any inaccuracies. Privacy laws modelled after those in the EU are now in place in Canada, Australia, New Zealand, and parts of Asia and Latin America (Stephens, 2007).

Limitations and suggestions for future research Because the subjects in this study were US college students living in the southeast, the generalizability of the results to other populations with different demographics could be relatively limited. Even though young adults are considered a major consumer group for diverse product categories not only in the US but also in many other countries (Huang, 1998; Sheehan, 1999; Tsang et al., 2004; Paek, 2005), other consumer groups might respond to personalized advertisements differently. For example, young adults likely use the Internet and cell phones more than other generations, thus influencing their perceptions positively or negatively about personalized advertising delivered via e-mail and telephone. In addition, consumers in European or Asian countries where policies about protecting one’s personal privacy are different than in the US could have different opinions about personalized advertising. Therefore, future studies should consider using a more diverse sample of consumers with different demographic characteristics and/or different nationalities. Regarding the measurements, the researchers developed the questionnaire for this exploratory study because a single scale to investigate responses to personalized advertising was unavailable. Thus, measurement validity may be a limitation of this research. 512

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Using the findings of this research as a springboard, one of the next steps could be to establish a scale to more accurately reflect consumers’ different insights on diverse types of personalized advertising. In addition, the questionnaire used in this study did not include questions about personalized advertising delivered as a text-message through mobile phones which have been a popular type of personalized ads (Nantel and Sekhavat, 2008). Thus, future studies about personalized advertising should include new and popular styles of personalized advertising. Lastly, additional research is needed to explore ways in which companies can use personalized advertising without alienating consumers who feel that the advertising violates their privacy. Because the current study did not explore what consumers like and do not like about personalized advertising, the results could not provide useful information about how marketers could design personalized advertising to be less offensive style to those concerned about personal privacy. Thus, an alternative approach for future researchers would be to use an experimental design to better understand what personalized advertisements communicate to consumers. Personalized advertisements in the experiments should be diverse in terms of types of media used to deliver them, the message style, the e-mail subject line and so forth. In addition, it would be interesting to compare the effectiveness of an explicitly personalized advertisement (‘Dear Mr. Smith: Look at this option for your new Toyota Camry!’) vs. one that matches the consumer’s personal interests but is not explicitly personalized (‘Look at this option for a new Toyota Camry’). Creating personalized advertising without violating privacy may not be easy; however, the efforts could pay off for marketers and consumers.

References Adler, R., Rosenfeld, L., Proctor, II & R. (2004) Interplay: The Process of Interpersonal communication, 9th edn. Harcourt, Fort Worth, TX. Alexander, R. & the Committee on Definitions of the American Marketing Association. (1960) A Glossary of Marketing Terms. American Marketing Association, Chicago, IL. Armstrong, G. & Kotler, P. (2000) Marketing: An Introduction. PrenticeHall, Upper Saddle River, NJ. Bozios, T., Lekakos, G., Skoularidou, V. & Chorianopoulos, K. (2001) Advanced Techniques for Personalized Advertising in a Digital Environment: The iMedia System. Proceedings of the eBusiness and eWork Conference. [WWW document]. URL http://istlab.dmst.aueb. gr/~vsko/pubs/confs/ebew2002_paper2.html (accessed on 2 October 2006). Bulander, R., Decker, M., Schiefer, G. & Kolmel, B. (2005) Comparison of Different Approaches for Mobile Advertising. Proceedings of the 2005 Second IEEE International Workshop on Mobile Commerce and Services. Caudill, E.M. & Murphy, P.E. (2000) Consumer online privacy: legal and ethical issues. Journal of Public Policy And Marketing, 19, 7–19. Chachko, P. (2004) Reaching out to customers through e-mail and database marketing. Franchising World, 36, 16–17. Chaudhuri, A. & Buck, R. (1995) Media differences in rational and emotional responses to advertising. Journal of Broadcasting & Electronic Media, 39, 109–126. Cho, C.-H. & Cheon, H.J. (2004) Why do people avoid advertising on the Internet? The Journal of Advertising, 33, 89–97. Chorianopoulos, K., Lekakos, G. & Spinellis, D. (2004) The Virtual Channel Model for Personalized Television. Proceedings of the


H.J. Yu and B. Cude

EuroiTV2003, UK, Brighton. [WWW document]. URL http://www. brighton.ac.uk/interactive/euroitv/euroitv03/Papers/Paper7.pdf (accessed on 10 October 2006). Consumers International (2002) Credibility on the Web: An International Study of the Credibility of Consumer Information on the Internet. Office for Developed and Transition Economies. Cutler, Bob D. & Thomas, Edward D. (2000) Informational/ transformational advertising: differences in usage across media types, product categories; and national cultures. Journal of International Consumer Marketing, 12, 69–84. Foxman, E. & Kilcoyne, P. (1993) Information technology, marketing practice, and consumer privacy: ethical issues. Journal of Public Policy and Marketing, 12, 106–119. Friedman, B. & Vincent, S. (2005) Growing with web-based one-to-one marketing. CPA Practice Management Forum, 1, 10–23. Gal-Or, E. & Gal-Or, M. (2005) Customized advertising via a common media distributor. Marketing Science, 24, 241–253. Gao, Z. (2005) Harmonious regional advertising regulation? A comparative examination of government advertising regulation in China, Hong Kong, and Taiwan. Journal of Advertising, 34, 75–87. Gurau, C., Rachhod, A. & Gauzente, C. (2003) To legislate or not to legislate: a comparative exploratory study of privacy/personalization factors affecting French, UK and US websites. Journal of Consumer Marketing, 20, 652–664. Hoeken, H., van den Brandt, C., Crijns, R., Dominguez, N., Hendriks, B., Planken, B. & Starren, M. (2003) International advertising in western europe: should differences in uncertainty avoidance be considered when advertising in Belgium, France, The Netherlands and Spain? Journal of Business Communication, 40, 195– 218. Howard, D. & Kerin, Roger A. (2004) The effects of personalized product recommendations on advertisement response rates: the ‘Try This. It Works!’ technique. Journal of Consumer Psychology, 14, 271–279. Huang, M.-H. (1998) Exploring new appeals: basic, versus social, emotional advertising on a global setting. International Journal of Advertising, 17, 145–169. Jin, C.H. & Villegas, J. (2007) Consumer responses to advertising on the Internet: the effect of individual difference on ambivalence and avoidance. Cyber Psychology & Behavior, 10, 258–266. Kazienko, P. & Adamski, M. (2007) AdROSA-adaptive personalization of web advertising. Information Sciences, 177, 2269–2295. Kim, J.W., Lee, B.H., Shaw, M.J., Chang, H.-L. & Nelson, M. (2001) Application of decision-tree induction techniques to personalized advertisements on Internet storefronts. International Journal of Electronic Commerce, 5, 45–62. Kim, J.K. & Pasadeos, Y. (2007) Ad Avoidance by Audiences across Media: Modeling Beliefs, Attitudes and Behavior toward Advertising. American Academy of Advertising, Annual Conference, Burlington, Vermont. King, N. (2008) Direct marketing, mobile phones, and consumer privacy: ensuring adequate disclosure and consent mechanisms for emerging mobile advertising practices. Federal Communications Law Journal, 60, 229–324. Krugman, H.E. (1965) The impact of television advertising: learning without involvement. Public Opinion Quarterly, 29, 349– 356. Lekakos, G. & Giaglis, G.M. (2004) A lifestyle-based approach for delivering personalized advertisements in digital interactive television. Journal of Computer-Mediated Communication, 9, No Pagination Specified. Li, H., Daugherty, T. & Biocca, F. (2002) Impact of 3-D advertising on product knowledge, brand attitude, and purchase intention: the mediating role of presence. Journal of Advertising, 31, 43–57.



Long, G., Hogg, M.K., Hartley, M. & Angold, S.J. (1999) Relationship marketing and privacy: exploring the thresholds. Journal of Marketing Practice: Applied Marketing Science, 5, 4–20. Low, G.S. (2000) Correlates of integrated marketing communications. Journal of Advertising Research, 40, 27–39. M2PressWIRE (2006) Direct Mail Advertising in the US by IBIS World, Feb 14, 2006. [WWW document]. URL http://www.mindbranch.com/ products/R538 (accessed on 2 Oct 2006). Mabley, K. (2000) Privacy vs. personalization. Cyber Dialogue. [WWW document]. URL http://www.cyberdialogue.com/library/pdfs/wp-cd2000-privacy.pdf (accessed on 15 October 2006). McKeen, J.D., Gulmaraes, T. & Wetherbe, J.C. (1994) The relationship between user participation and user satisfaction: an investigation of four contingency factors. MIS Quarterly, 18, 427–451. Marketing News (2006) Outlook 2006. January 15, 16. Miyazaki, A.D. & Fernandez, A. (2000) Internet privacy and security: an examination of online retailer disclosures. Journal of Public Policy & Marketing, 19, 54–61. Morimoto, M. & Chang, S. (2006) Consumers’ attitude toward unsolicited commercial e-mail and postal direct mail marketing methods: intrusiveness, perceived loss of control, and irritation. Journal of Interactive Advertising, 7, 8–20. Moschis, G.P. & Moore, R.L. (1979) Family communication and consumer socialization. Advances in Consumer Research, 6, 359–363. Nantel, J. & Sekhavat, Y. (2008) The impact of SMS advertising on members of a virtual community. Journal of Advertising Research, September, 363–374. Nathanson, A.I. (1999) Identifying and explaining the relationship between parental mediation and children’s aggression. Communication Research, 26, 124–143. Nowak, G.J., Shamp, S., Hollander, B. & Cameron, G.T. (1999) Interactive media: a means for more meaningful advertising? In Advertising and the World Wide Web (ed. by D.W. Schumann & E. Thorson), pp. 99–117. Lawrence Erlbaum Associates, Mahwah, NJ. O’Leary, C., Rao, S. & Perry, C. (2004) Improving customer relationship management through database/Internet marketing: a theory-building action research project. European Journal of Marketing, 38, 338–354. Paek, H.-J. (2005) Understanding celebrity endorsers in cross-cultural contexts: a content analysis of South Korean and U.S. newspaper advertising. Asian Journal of Communication, 15, 133–153. Palmatier, R.W., Dant, R.P., Grewal, D. & Evans, K.R. (2006) Factors influencing the effectiveness of relationship marketing: a metaanalysis. Journal of Marketing, 70, 136–153. Pavlou, P.A. & Stewart, D.W. (2000) Measuring the effects and effectiveness of interactive advertising: a research agenda. Journal of Interactive Advertising, 1, 1–27. Pereira, M.A., Kartashov, A.I., Ebbeling, C.B., Van Horn, L., Slattery, M.L., Jacobs, D.R., Jr. & Ludwig, D.S. (2005) Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis. Lancet, 365, 36–42. Perreault, W.D., Jr. & McCarthy E.J. (1999) Basic Marketing: A GlobalManagerial Approach, 13th edn. McGraw-Hill Publishing, New York. Petty, R.E. & Cacioppo, J.T. (1986) Communication and Persuasion: Central and Peripheral Routes to Attitude Change. Springer-Verlag, New York. Phelps, J.E., D’Souza, G. & Nowak, G.J. (2001) Antecedents and consequences of consumer privacy concerns: an empirical investigation. Journal of Interactive Marketing, 15, 2–17. Poon, S. & Jevons, C. (1997) Internet-enabled international marketing: a small business network perspective. Journal of Marketing Management, 13, 29–41. Pramataris, K., Papakyriakopoulos, D.A., Lekakos, G. & Mylonopoulos, N.A. (2001) Personalized interactive TV advertising: the iMedia business model. Electronic Markets, 11, 17–25.

513


Rodgers, S. & Thorson, E. (2000) The interactive advertising model: how users perceive and process online ads. Journal of Interactive Advertising, 1, [WWW document]. URL http://www.jiad.org/vol1/ no1/rodgers/index.htm (accessed on 6 October 2006) Roehm, H. & Haugtvedt, C. (1999) Understanding interactivity of cyberspace advertising. In Advertising and the World Wide Web (ed. by D.W. Schumann & E. Thorson), pp. 27–39. Lawrence Erlbaum Associates, Mahwah, NJ. Rosenberg, J.M. (1995) Reinventing Advertising. Speech presented at the Groupe d’Ouchy (22 June). Rotfeld, H.J. (2006) Understanding advertising clutter and the real solution to declining audience to mass media commercial messages. Journal of Consumer Marketing, 23, 180–181. Sacirbey, O. (2000) Privacy concerns, advertising hamper E-commerce. IPO Reporter, 24, 11. Sasser, S.L., Koslow, S. & Riordan, E.A. (2007) Creative and interactive media use by agencies: engaging an IMC media palette for implementing advertising campaigns. Journal of Advertising Research, September, 237–256. Sheehan, K.B. (1999) An investigation of gender differences in on-line privacy concerns and resultant behaviors. Journal of Interactive Marketing, 13, 24–38. Sheehan, K.B. (2005) In poor health: an assessment of privacy policies at direct-to-consumer web sites. Journal of Public Policy & Marketing, 24, 273–283. Sheehan, K.B. & Hoy M.G. (1999) Flaming, complaining, abstaining: how online users respond to privacy concerns. Journal of Advertising, 28, 37–52. Sheehan, K.B. & Gleason, T.W. (2001) Online privacy: Internet advertising practitioners’ knowledge and practices. Journal of Current Issues and Research in Advertising, 23, 31–41. Stephens, D.O. (2007) Protecting personal privacy in the global business environment. The Information Management Journal, 41, 56–59. Stewart, D.W. & Ward, S. (1994) Media effects on advertising. In Media Effects: Advances in Theory and Research (ed. by J. Bryant & D. Zillmann), pp. 315–363. Lawrence Erlbaum Associates, Inc, Hillsdale, NJ. Sundar, S.S. & Kim, J. (2005) Interactivity and persuasion: influencing attitudes with information and involvement. Journal of Interactive Advertising, 5, [WWW document]. URL http://www.allacademic.com/ meta/p113152_index.html (accessed on 15 October 2006).

514

H.J. Yu and B. Cude

Trollinger, S. (2006) Striking a balance between e-mail and traditional direct marketing. Ingram’s, 32, 57. Tsang, M.M., Ho, S.-C. & Liang, T.-P. (2004) Consumer attitudes toward mobile advertising: an empirical study. International Journal of Electronic Commerce, 8, 65–78. UPI-Zogby International Poll (2007) UPI Poll: Don’t suspend privacy rights – Zogby/UPI Polls. [WWW document]. URL http://www.zogby.com/index.cfm (accessed on 6 April 2008). U.S. Federal Trade Commission (2000) Privacy Online: Fair Information Practices in the Electronic Marketplace. A Report to Congress, May. U.S. Federal Trade Commission (2009) Self-regulatory Principles for Online Behavioral Advertising. Tracking, Targeting, & Technology. FTC Staff Report, February. Ward, S. & Wackman, D. (1973) Children’s information processing of television advertising. In New Models for Mass Communication Research (ed. by P. Clarke). Sage Publications, Beverly Hills, CA. Wehmeyer, K. (2005) Aligning IT and marketing – the impact of database marketing and CRM. Journal of Database Marketing & Customer Strategy Management, 12, 243–256. Wolburg, J. & Kim, H. (1998) Messages of individualism and collectivism in Korean and American magazine advertising: a cross cultural study of values. 1998 American Academy of Advertising Proceedings, 147–154. Wolin, L. & Korgaonkar, P. (2005) Web advertising: gender differences in beliefs, attitudes, and behavior. Journal of Interactive Advertising, 6, 125–136. Wu, S.-I. (2006) The impact of feeling, judgment and attitude on purchase intention as online advertising performance measure. Journal of International Marketing & Marketing Research, 31, 89–108. Xu, D.J., Liao S.S. & Li, Q. (2008) Combining empirical experimentation and modeling techniques: a design research approach for personalized mobile advertising applications. Decision Support Systems, 44, 710–724. Yu, J.H., Paek, H.-J. & Bae B. (2008) Cross-cultural comparison of interactivity and promotional appeals in the U.S. and South Korean antismoking websites. The Journal of Internet Research, 18, 454–476. Yuan, S.-T. & Tsao, Y.W. (2003) A recommendation mechanism for contextualized mobile advertising. Expert Systems with Applications, 24, 399–414.
