• For Contributors +
• Journal Search +
Journal Search Engine
ISSN : 2287-1063(Print)
ISSN : (Online)
The Journal of Advertising and Promotion Research Vol.2 No.1 pp.123-161

# The Antecedents of Attitude toward IPTV Advertising : The Role of Interactivity and Advertising Value

Sung Wook Shim , Chunsik Lee, Dae-Hee Kim
Associate Professor, Department of Advertising, Hanyang University
Assistant Professor, Department of Communication, University of North Florida
Lecturer, Department of Marketing, Christopher Newport University

### Abstract

JAPR_2-1_123.pdf344.3KB

### 1. INTRODUCTION

John was watching a basketball game on TV. At a moment when a player made a skillful move, he recognized a red dot on the screen with saying if you want information about the player's basketball shoes, press the red button on your remote. Thinking about his worn-out basketball shoes, John pressed the red button and it led him to a brand page of basketball shoes. After browsing several pages in the micro-site of the brand, John printed out a discount coupon for a basketball shoe, then he went back to watch the game again. At least since 1990s, this kind of scenario has been expected as the scenes of future TV and advertising (Cuniff 1993; Hoffman & Novak 1996).

In fact, recent media technologies enable viewers to interact with video content through various television platforms, including Internet broad-band, satellite, and digital cable (Bellman, Schweda & Varan 2009; Cauberghe & Pelsmacker 2006/2008; Jensen 2005). Contrasting inter-active television with traditional television, Cauberghe & Pelsmacker (2006) list various factors that are key characteristics of interactive tele-vision, including two-way communication, active users, time-shifting, ubiquitous, narrowcasting, and ad-skipping.

The market size of interactive television has been increased with grow-ing numbers of providers and platforms. An industrial report (Multimedia Research Group 2010) estimates that 28 million people in the global market are currently subscribing to interactive television services, and that that number will nearly triple to 83 million in 2013. In addition, global market revenues from interactive television will more than triple, from $12 billion in 2009 to$38 billion in 2013. In recent years, some prominent companies from information technology sectors joined the interactive television market. For example, Apple and Yahoo have their own services for inter-active television. Lately, Google announced to provide interactive formats of television service named as Google TV (Patel 2010).

In spite of its steady growth in the market size, there have been industrial skepticisms about the success of interactive television (e.g. Ries 2004; Dudar 2010). One of major concerns behind the skepticisms is that TV viewer will not adopt interactive TV because they cling to their current be-haviors and patterns to watch televisions as a lean back medium so they are not willing to interact with televisions and its contents. In fact, several cases of early businesses under the concept of interactive television from the 90s such as WebTV and AOLTV failed to capture the majority of tele-vision audiences (Ries 2004). In addition, an academic survey (Cauberghe & De Pelsmacker 2006) with advertising practitioners identified technical and perceptual hurdles to create effective advertising through interactive television.

Therefore, understanding consumer's usages of interactive television and potential mechanisms to process advertising through interactive tele-vision are important issues to predict the success of interactive television and also it can increase our theoretical knowledge about the effectiveness of interactive advertising in the new context. In addition, this knowledge can contribute to practitioners to run more effective advertising practices through interactive televisions.

### 2. LITERATURE REVIEW

#### 1) The Definition and types of IPTV advertising

Internet Protocol TV (e.g. IPTV), the merging of the Internet and TV, has been launched in most Western countries and East Asia, such as Hong Kong, Japan, and S. Korea. IPTV in its essence combines broadcast content (multimedia content) with interactivity. This multimedia content is dis-tributed via broadband networks (Cauberghe & Pelsmacker 2008). IPTV is exposed on different end devices, such as a TV. Some applications in IPTV such as video on demand blurred the line between a TV and a PC. Another potential for the IPTV technology makes programs more inter-active for the viewers. For example, viewers can enjoy a real time live quiz program using interactive IPTV interface. Many definitions of IPTV em-phasized the interactive nature of IPTV services such as the Interactive Program Guide, enhanced broadcasting, web browsing, Video on Demand, and communication services. Different characteristics between traditional television and IPTV are one way communication vs. two way communication, passive viewer vs. active viewer, Push model vs. pull model, and time restricted vs. time shifting and so on. IPTV has been often conceptualized as the convergence of traditional TV and the Internet. As presented in Table 1 (Cauberghe & Pelsmacker 2010), IPTV has the strengths of both media as an advertising channel.

<Table 1> Characteristics of Traditional TV, Internet and IPTV as an Advertising Medium

Another stream of research related to IPTV ads investigated the effects on attention and memory of simultaneous exposure to television content and interactive advertising. Cauberghe & Pelsmacker (2008) showed that IPTV advertising is less effective when consumers interact with content other than the advertising (e.g., a puzzle). Cauberghe & Pelsmacker(2008) maintained that the detrimental effects of interaction with the program con-tent might be due to the limited capacity of cognitive activity.  On the other hand, some researchers (Cauberghe, Pelsmacker & Janssens 2009; Giotis & Lekaks 2009) have found that interactive advertising is more effective when the advertised products are congruent with the content of the tele-vision program. In sum, previous research on IPTV advertising has sug-gested that the new formats and enhanced interactivity of IPTV advertising can provide new opportunities for advertisers and that interactivity is a fac-tor in the effectiveness of IPTV advertising.

#### 2) MODEL OF IPTV advertising effectiveness

Since the early stage of Internet advertising, researchers have proposed and tested the concept of interactivity as a critical antecedent of effective Internet advertising (e.g., Bezjian-Avery, Calder & Iacobucci 1998; Cho & Leckenby 1999; Jee & Lee 2002; Coyle & Thorson 2001; Ko, Cho & Roberts 2005; Liu & Shrum 2002; Macias 2003; Rosenkrans 2009; Sundar & Kim 2005). Several empirical studies (Cho 1999; Coyle & Thorson 2001; Macias 2003; Sundar & Kim 2005) have manipulated levels of inter-activity in Internet advertising to demonstrate that higher levels of inter-activity in Internet advertising can produce more positive attitudes toward advertising and brands. To the best of our knowledge, however, few empiri-cal studies have applied and tested these findings in the IPTV context.

#### 3) Interactivity and Advertising Value

Although different scholars have proposed different sets of interactivity definitions, the common recurring theme is interactivity can be defined as user's ability to control over information. McMillan & Hwang (2002) offered a wide review of interactivity and classified interactivity as (1) process, (2) feature, (3) perception, and (4) combination of process, fea-ture, and/or perception. Wu (2005) also classified it as actual interactivity and perceived interactivity. Actual interactivity focuses on the feature of media or capabilities of creating interactive content or message or potential for interaction in general. Perceived interactivity is a psychological state experienced by a site-visitor during the interaction process. It has three di-mensions: (1) perceived control over (a) site navigation; (b) the pace or rhythm of the interaction; (c) the content being accessed, (2) perceived re-sponsiveness from (a) the site-owner; (b) from the navigation cues and signs; (c) the persons online, (3) perceived personalization of the site with regard to (a) acting as if it were a person; (b) acting as if it wants to know the site visitors; and (c) acting as if it understands the site visitor (Wu, 2000). In general, perceived interactivity will have an impact on the effects of ac-tual interactivity on consumers' attitudes and behaviors. Rafaeli & Ariel (2007) summarized interactivity as synchronicity, control, rapidity and speed, participation, choice variety, directionality, hypertextuality, con-nectedness, experience and finally responsiveness. Through the literature, they identified distinction between a focus on functions of features and a focus on users. A focus on function leads to claims that interactivity is an attribute of technology. Steuer (1992) defines interactivity as the extent to which users can participate in modifying the form and content of a medi-ated environment in real time. He viewed interactivity as a feature of the medium. Contrary to this, Rogers defines interactivity as users' control un-der which participants in communication process can exchange roles. Among this literature, interactivity in this paper can be defined as a percep-tion experienced by a participants during interaction process.

This study proposes that interactivity has three dimensions: control, personalization, and participation. Control is related to a wide range of means to manipulate the content. As for the personalization factor, IPTV can send personalized messages to consumers. Personalized messages in-clude what consumers want to know and what they want to buy. IPTV ad-vertising has the potential to ensure that consumers receive relevant mes-sages (Pavlou & Stewart, 2010). Participation has been widely used as a means of improving advertising effectiveness (Stewart & Ward, 1994). IPTV advertising offers options for consumers' participation. IPTV adver-tising focuses on involving consumers in the advertising and purchase process by allowing them to participate in their search process. For exam-ple, IPTV helps consumers identify the specific product of their choice based on their preference.

Prior research has suggested that consumer interactions with IPTV ad-vertising may affect three sub-dimensions related to advertising value per-ceptions, so the current study posits that:

H1: Interactivity of IPTV ads has an overall positive effect on advertis-ing value.

#### 4) The Construct Variables of Attitude toward Advertising

H2: Interactivity has a direct positive effect on attitudes toward IPTV advertising.

Ducoffe (1996) examined the relationship between advertising value and attitude toward advertising. He expected that the two constructs would be strongly associated. People rating Internet advertising high in its value would tend to hold favorable attitude toward Internet advertising. The con-struct of advertising value (Ducoffe 1996) positively affects attitudes to-ward Internet advertising, so the same logic can be applied to the IPTV context in the current study.

H3: Advertising value has a direct positive effect on attitudes toward IPTV advertising.

Established relationships between attitudes toward advertising and at-titudes toward the brand and purchase intention have been well docu-mented in prior literature (Brown & Stayman 1992; MacKenzie & Lutz 1989). Previous studies have consistently found linear relationships be-tween attitudes toward advertising and the brand, and purchase intention within various contexts, including Internet advertising (e.g., Ko et al. 2005; Cho & Leckenby 1999). Increased interactivity on a website has positive effects on users' perceived satisfaction, effectiveness, efficiency, value and overall attitude toward a website (Teo et. al., 2003). Macias (2003) found that interactive advertising has a positive influence on consumers' percep-tions of brands and advertising. In several empiricalstudies, the effects of interactivity had reached attitude toward brand or product and purchase intention or revisit intention (Wu 2005). Thus, the current study expects that these relationships occur with the same patterns in the context of IPTV advertising. The proposed hypotheses are included in the structural model shown in Figure 1.

[Figure 1] Hypothesized structural equation model of IPTV advertising

H4: Positive attitudes toward IPTV advertising have a positive effect on attitudes toward the brand.

H5: Positive attitudes toward the brand have a positive effect on pur-chase intention.

### 3. METHODS

#### 1) Sample and Data Collection Procedure

The current study used self-administered surveys and a computer lab experiment to obtain empirical data on users' attitudes toward IPTV adver-tising and its antecedents. Participants viewed an example of IPTV adver-tising before they completed a questionnaire on attitudes and correlates of IPTV advertising acceptance. The survey method in a forced exposure context is a commonly used method in studies on the effectiveness of inter-active advertising (Appiah 2006; Reading et al. 2006; Sundar & Kim 2005). This study employed this method because IPTV advertising is relatively new in the United States, so recruiting participants who have experience with IPTV advertising is difficult.

Two hundred fifty-seven undergraduate students participated in the study. Of these, 37% (n = 94) were male and 63% (n = 123) were female. Respondents' ages ranged from 18 to 29, with a median age of 20 years.

#### 2) Experimental Stimulus

The current study used two versions of the experimental IPTV advertis-ing, one to demonstrate how to operate the IPTV, and the other for the main task completion. The experimental IPTV was simulated on the computer screen and it was operated through the simulated remote control on the com-puter screen. Shampoo was used in the IPTV advertising stimulus because it has been considered generally relevant to college students and moder-ately involvement product. Attitude toward the ad research has been using non-durable goods such as shampoo, facial tissues, cola, tooth pastes as the advertised product in the studies (Mitchell & Olson 1981; Shimp 1981). Our data indicated the mean of shampoo involvement was 4.58 (sd=1.55) in the seven point scales. The appendix shows the sample images of the stimuli.

The experimental brand page and questionnaire were developed using a translation and back-translation method with two bilingual speakers. The brand used in the current study was unknown to the participants in order to rule out brand familiarity and bias and because the use of foreign editorial content excludes the potential effects of program involvement in studying the effectiveness of embedded advertising such as irritation perception.

#### 3) Key Measure

All factor loadings for observed items, their descriptive statistics, and reliabilities for constructs are shown in Table 2. The questionnaire used to measure attitudes toward IPTV advertising and brand is from the Attitudes toward Advertising measure used by Lutz (1985) and Muheling (1987). The purchase intention measure applies the scales in Lutz, MacKenzie and Belch's (1983) study. The control measures for three sub-dimensions of interactivity are from Liu (2003) and Wu (2000), the participation measures are from Babin et al. (1994) and Liu & Arnett (2000), and the personalization measures are from Srinivasan, Anderson & Ponnavolu (2002). The measures of perceptions of adverting val-ueinformativeness, entertainment, and irritationapplies the scales in Ducoffe's (1996) study.

### 4. RESULTS

Structural equation modeling was used to estimate the hypothesized model among the constructs, and the correlation matrix of 257 respondents was used to estimate the structural equation model. There were no missing data. Following the two-step approach proposed by Anderson & Gerbing (1998), this study estimated a measurement model prior to examining the structural model relationships. Both the measurement and model and si-multaneous equation model were estimated with LISREL 8.80 using the method of maximum likelihood. Given an acceptable measurement model, the optimal structural equation model was identified by way of model com-parison tests (also known as 2 difference tests).

#### 1) Measurement Model and Simultaneous Equation Model

Two antecedents contributing to attitudes toward IPTV adverti-singinteractivity and perception of valuewere hypothesized. Prior research (Babin and Darden 1994; Ducoffe 1996; Liu 2003; Srinivasan, Anderson and Ponnavolu 2002) has postulated that interactivity has three sub-di-mensionscontrol, participation, and personalizationand that perceptions of advertising value also have three sub-dimensions: informativeness, en-tertainment, and irritation. To test the hypothesized structure of the contrib-utors to attitude toward IPTV advertising (see Figure 1), this study analyzed a second-order hierarchical confirmatory factor analysis for the measure-ment model. This analysis helps to simplify the structural nature of the ante-cedent to attitude toward IPTV advertising.

The measurement model was selected on the basis of the good-ness-of-fit indices (see Table 3). The final measurement model (2 (308) = 572.14 (p > .05)) fit the data well, and the key goodness-of-fit indices (SRMR = .047, RMSEA = .059, TLI = .98, CFI = .99) met the conventional cut-points (SRMR = .09, RMSEA = .06, CFI = .95, TFI = .95). In addition, all factor loadings were above 0.5 and were significant at the 0.01 level, as presented in Table 2. As for the evidence of convergent validity, average variance extracted for each construct was found to exceed .50 for a con-struct (Fornell & Larcker, 1981). The AVE for all latent variables was larger than its squared correlations (Table 2), suggesting that the measures were considered to possess discriminant validity. In addition, pairwise X2 dif-ference tests showed that all correlations between factors were sig-nificantly different from 1.0.

<Table 3> Goodness of fit indices for alternative models

<Table 4> Correlation matrix between factors

H1 predicted the influence of interactivity on perceived advertising value. The path coefficient from interactivity to perceived advertising val-ue was significant ( = .91, p < .001), so H1 was supported. H2 and H3 pro-posed that interactivity and advertising value influenced attitude toward IPTV advertising, respectively. H2 was not supported because the path co-efficient from interactivity to attitude toward IPTV advertising was not significant ( = -.13, p > .05) and because the original path model did not fit the data well. The revised model suggested that advertising value sig-nificantly influenced attitude toward IPTV advertising ( = .78, p < .001) so H3 was supported. In light of the non-significant relationship between interactivity and attitude toward IPTV advertising, advertising value ap-peared to play a mediating role between interactivity and attitude toward IPTV advertising.

H4, which predicted the path from attitude toward IPTV advertising to brand attitude, was supported ( = .71, p < .001). The literature in the adver-tising field has suggested that evaluation of an advertisement is often trans-ferred to brand evaluation (Lutz 1985; MacKenzie & Lutz 1989), and the findings of the current study suggest that this prevalent hypothesis was con-firmed in the context of IPTV advertising. The revised model also con-firmed a significant influence of brand attitude on purchase intention (H5).

[Figure 2] Path coefficients for the revised model

### 5. DISCUSSION

Third, the study also finds evidence of the established linear relation-ship between attitude toward advertising and brand, and purchase intention in the IPTV advertising context. As proven in numbers of Internet advertis-ing studies (e.g. Cho 1999; Coyle & Thorson 2001; Macias 2003; Sundar & Kim 2005), attitude toward an advertisement is a valid measure of the effectiveness of IPTV advertising.

Fourth, a second-order confirmatory factor analysis confirms the di-mensions of interactivity and advertising value. While prior literature has defined interactivity in many different ways, the current study finds that the three sub-dimensions of personalization, participation, and control ac-count for interactivity. Advertising value (informativeness, entertainment and irritation), as proposed by Ducoffe (1996), is also confirmed in the cur-rent study in that the advertising value of Web advertising applies to IPTV advertising.

Fifth, the structural model proposed in this study represents the IPTV advertising process shown in Figure 2. The first factor for processing IPTV advertising is interactivity. As posited in the proposed model, the inter-activity of IPTV advertising is a key to initiating a positive attitude toward IPTV advertising. For example, the degree of control consumers have when they operate IPTV advertising in pursuit of their own goals is a critical factor in the effectiveness of IPTV advertising. Therefore, consumers' per-ceptions about control, personification, and participation are the most im-portant factors in the development of interactivity.

### 6. IMPLICATIONS

Results of the current study suggest that the interactive features of IPTV advertising generate positive attitudes toward brand and purchase intention via advertising value and attitudes toward the advertisement. Interactivity appears to be an important and unique factor in that it initiates positive re-actions and leads to positive attitudes toward the advertisement. However, practitioners need to note that interactivity in itself may not always result in positive attitudes toward advertising. The results highlight the mediating role of advertising value in the effectiveness of interactive characteristic, so practitioners should keep irritation as low as possible while enhancing the interactive features of personalization and customization.

The key point for IPTV advertising is the interactivity, which is an effec-tive way to increase the effectiveness of IPTV advertising. For consumers to feel the value of interactivity, they must be free to enter and operate IPTV advertising. For example, when consumers view a program in IPTV, they should not have difficulty figuring out how to use menus and options for the advertisement.

### Reference

1.Anderson, J.C., & Gerbing, D.W. (1998). Structural Equation Modeling in Practice: a Review and Recommended Two-step Approach. Psychological Bulletin, 103(3), 411-423.
2.Appiah, O. (2006). Rich Media, Poor Media: The Impact of Audio/video vs. Text/picture Testimonial Ads on Browsers' Evaluations of Commercial Web Sites and Online Products. Journal of Current Issues and Research in Advertising, 28(1), 73-86.
3.Babin, B.J., William, R.D. & Mitch G. (1994). Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value. Journal of Consumer Research, 14(6), 644-656.
4.Bellman, S., Schweda, A. & Varan, D. (2009). A Comparison of Three Interactive television Ad Formats. Journal of Interactive Advertising, 10(1), 14-34.
5.Berte, K., P. Vyncke & E. De Bens (2010). Opportunities of Interactive Formats for Innovative Advertising on Digital Television. In Proceedings of the 8th International Interactive Conference on Interactive TV&Video, Tampere, Finland, 55-58.
7.Brown, S. P. & Stayman, D. M. (1992). Antecedents and Consequences of Attitude toward the Ad: A meta-Analysis. Journal of Consumer Research, 19(June), 34-51.
8.Cauberghe, V. & De Pelsmacker, P. (2006). Opportunities and Thresholds for Advertising on Interactive Digital TV: A View from Advertising Professionals. Journal of Interactive Advertising, 7(1), 12-23.
9.Cauberghe, V. & De Pelsmacker, P. (2008). The Advertising Impact of an Interactive TV Program on the Recall of an Embedded Commercial. Journal of Advertising Research, 48(3), 352-362.
10.Cauberghe, V., De Pelsmacker, P., & Wim, J. (2009). Simultaneous Exposure to a Program and Advertising Content in an Interactive Context: Perceptual and Semantic Interference and Reinforcement. Journal of Business Research, 63, 972-979.
11.Cauberghe, V. & De Pelsmacker, P. (2010). The Effectiveness of Telescopic Ads Delivered Via Interactive Digital Television: The Impact of the Amount of Information and the Level of Interactivity on Brand Responses. Journal of Interactive Marketing, 24 (4), 297308.
12.Cho, C.H. (1999). How Advertising Works on the WWW: Modified Elaboration Likelihood Model. Journal of Current Issues and Research in Advertising, 21(1), 33-50.
13.Cho, C.H. & Cheon, H.J. (2004). Why do People Avoid Advertising on the Internet. Journal of Advertising, 33(4), 89-97.
14.Cho, C.H. & John, D.L. (1999). Interactivity as a Measure of Advertising Effectiveness. In Proceedings of the 1999 Conference of the American Academy of Advertising, M. S. Roberts, eds. Gainesville, FL: American Academy of Advertising, 162-179.
15.Coyle, J.R. & Esther, T. (2001). The Effects of Progressive Levels of Interactivity and Vividness in Web Marketing Sites. Journal of Advertising, 30(3), 65-77.
16.Cuniff, T. (1993). The Second Creative Revolution; Interactive Advertising on Television Offers the Greatest Challenge Yet. Advertising Age, 22.
17.Ducoffe, R. H. (1995). How Consumers Assess the Value of Advertising. Journal of Current Issues and Research in Advertising, 17(1), 1-18.
19.Dudar, E. (2010). Five Reasons Consumers Won't Tune in to Google TV. Advertising Age; Retrieved September 18, 2010, from http://adage.com/digitalnext/article?article_id=144060.
20.Edwards, S.M., Hairong, .L & Lee, J.H. (2002). Forced Exposure and Psychological Reactance: Antecedents and Consequences of the Perceived Intrusiveness of Pop-up ads. Journal of Advertising, 31(3), 83-95.
21.Giotis, P. & Lekaks, G. (2009). Effectiveness of Interactive Advertising Presentation Models. In Proceedings of the seventh European conference on European Interactive Television Conference (pp. 157-160).
22.Hoffman, D.L. & Thomas P.N. (1996). Marketing in Hypermedia Computer-mediated Environments: Conceptual Foundations. Journal of Marketing, 60(3), 5068.
23.International Telecommunication Union. (2010). ITU-T Newslog IPTV Standardization on Track say Industry Experts, 2006, from http://ww w.itu.int/ITU-T/newslog/IPTV+ Standardization+On+Track+Say+ Industry+Experts.aspx (accessed July 5, 2010).
24.Jee, J.H. & Lee, W.N. (2002). Antecedents and Consequences of Perceived Interactivity: An Exploratory Study. Journal of Interactive Advertising, 3(1), 34-45.
25.Jensen, J.F. (2005). Interactive Television: New Genres, New Format, New Contents. In Proceedings of the Second Australasian Conference on Interactive Entertainment (pp.89-96).
26.Ko, H.J., Cho, C.H. & Roberts, M.S. (2005). Internet Uses and Gratifications: A Structural Equation Model of Interactive Advertising. Journal of Advertising, 34(2), 57-70.
27.Liu, C. & Arnett, K.P. (2000). Exploring the Factors Associated with Web Site Success in the Context of Electronic commerce. Information & Management, 38(1), 22-33.
28.Liu, Y. (2003). Developing a Scale to Measure the Interactivity of Website. Journal of Advertising Research, 43(2), 207-216.
29.Liu, Y. & Shrum, L.J. (2002). What is Interactivity and Is it always Such a Good Thing? Implications of Definition, Person and Situation for the Influence of Interactivity on Advertising Effectiveness. Journal of Advertising, 21(4), 5364.
30.Lutz, R.J. (1985). Affective and Cognitive Antecedents of Attitude toward the Ad: A Conceptual Framework. In Psychological Process and Advertising Effects: Theory, Research and Application, L.F. Alwitt & A.A. Mitchell, eds. Hillsdale, NJ: Lawrence Erlbaum Associates, 45-63.
31.Lutz, R.J., MacKenzie, S.B. & Belch, G.E. (1983). Attitude toward the Ad as a Mediator of Advertising Effectiveness. In Association for Consumer Research, R.P. Bagozzi & A.M. Tybout, eds. vol. 10, Ann Arbor, MI. 532-539.
32.Macias, W. (2003). A Preliminary Structural Equation Model of Comprehension and Persuasion of Interactive Advertising Brand Web Sites. Journal of Interactive Advertising, 3(2), 36-48.
33.MacKenzie, S.B & Lutz, R.J. (1989). An Empirical Examination of the Structural Antecedents of Attitude toward the Ad in an Advertising Pretesting Context. Journal of Marketing. 53(April), 48-65.
34.McMillan, S.J. & Hwang, J.S. (2002). Measures of Perceived Interactivity: An Exploration of the Role of Direction of Communication, User control, and Time in Shaping Perceptions of Interactivity. Journal of Advertising, 31(3), 29-42.
35.Mitchell, A. A., & Olson, J. C. (1981). Are Product a Beliefs the Only Mediator of Advertising Effects on Brand Attitude, Journal of Marketing Research, 18 (August), 318-332.
36.Muheling, D.D. (1987). Comparative Advertising: The Influence of Attitude toward the Ad on Brand Evaluation. Journal of Advertising, 16(4), 43-49.
37.Multimedia Research Group. (2010). IPTV Global Forecast 2010 to 2014. Semiannual IPTV Global Forecast Report 2010. from http://www.mr gco.com/iptv/gf0610.Html (accessed July 5, 2010).
39.Pavlou, P & Stewart, D. W. (2000). Measuring the Effects and Effectiveness of Interactive Advertising: A Research Agenda. Journal of Interactive Advertising, 1(1), 62-78.
40.Rackham, N. & Vincintis, J.D. (1999). Rethinking the Sales Force: Redefining Selling to Create and Capture Customer Value. 1st ed., New York: McGraw Hill.
41.Rafaeli, S, & Ariel, Y. (2007). Assessing Interactivity in Computer-Mediated Research. In Oxford, UK: Oxford Unversity Press, Adam N. Joinson, Katelyn Y.A. Mckenna, Tom Postmes & Ulf-Dietrich Reips, eds. 71-88.
42.Rafaeli, S, & Sudweeks, F. (1997). Networked Interactivity, Journal of Computer- Mediated Communication, 2(4), 2: 0. doi: 10.1111/j.1083-6 101.1997.tb00201.x.
43.Reading, N., Bellman, S., Varan, D. & Winzar, H. (2006). Effectiveness of Telescopic Ads delivered via Personal Video Recorders. Journal of Advertising Research, 46(2), 217227.
44.Ries, A. (2004). Why Interactive Television Has No Future. Advertising Age. Retrieved September 18, 2010, from ruby.fgcu.edu/courses/tdugas/IDS3301/acrobat/interactivetvfailure.pdf.
45.Rosenkrans, G. (2009). The Creativeness and Effectiveness of Online Interactive Rich Media Advertising. Journal of Interactive Advertising, 9(2), 18-31.
46.Shimp, T.A., (1981). Attitude Toward The Ad as a Mediator of Consumer Brand Choice, Journal of Advertising, 10 (2), 9-15.
47.Shyam, S.S. & Kim, J.H. (2005). Interactivity and Persuasion: Influencing Attitudes with Information and Involvement. Journal of Interactive Advertising, 5(2), 5-18.
48.Srinivasan, S.S., Anderson, R. & Ponnavolu, K. (2002). Customer Loyalty in e-Commerce: an Exploration of its Antecedents and Consequence. Journal of Retailing, 78(1), 41-50.
49.Steuer, J. (1992). Defining virtual reality: Dimensions Determining Telepresence. Journal of Communication, 42(4), 73-93.
50.Stewart, D.W., & Ward, S. (1994). Media Effects on Advertising. In Hillsdale Media effects: Advances in Theory and Research, J. Bryant. & D. Zillman., eds. NJ: Lawrence Erlbaum, 315-363.
51.Sundar, S.S., Brown,J. & S. Kalyanaraman (1999). Reactivity vs. Interactivity, paper presented at the meeting of the International Communication Association, San Francisco, CA.
52.Teo, H.H., Oh, L.B., Liu, C., & Wei, K.K. (2003). An empirical study of the effects of interactivity on web user attitude. International Journal of Human-Computer Studies, 58(3), 281-305.
53.Wu, G. (2000). The Role of Perceived Interactivity in Interactive Ad Processing. Unpublished dissertation, University of Texas at Austin.
54.Wu, G. (2005). The Mediating Role of Perceived Interactivity in the Effect of Actual Interactivity on Attitude toward the Website. Journal of Interactive Advertising, 5(2), 29-39.