Abstract
Advertising investment on the Internet is currently growing at a faster rate than in all other means of communication. Specifically, companies’ integrated marketing communications (IMC) are using the Internet as a main means of advertising and, increasingly, social networks as part of their communication strategies. Given their growing importance, this chapter performs an exhaustive theoretical analysis of the efficacy of online advertising. First, we perform a detailed inventory of the main forms of advertising used on the Web and social networking sites. Afterward, we analyze the variables shown, through literature, to be most influential on online advertising effectiveness, paying special attention to the banner ad format. Next, the topic of advertising effectiveness in the specific context of social network sites is discussed. In conclusion, some relevant implications for practitioners and research opportunities are presented.
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Notes
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References
Ahn, S. J., & Bailenson, J. N. (2011). Self-endorsing versus other-endorsing in virtual environments. Journal of Advertising, 40(2), 93–106.
Amblee, N., & Bui, T. (2011). Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts. International Journal of Electronic Commerce, 16(2), 91–114.
Baltas, G. (2003). Determinants of internet advertising effectiveness: An empirical study. International Journal of Market Research, 45(4), 505–513.
Bayles, M. (2000). Just how ‘blind’ are we to advertising banners on the web. Usability News, 2(2), 520–541.
Bayles, M. E. (2002). Designing online banner advertisements: should we animate? In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Changing Our World, Changing Ourselves (pp. 363–366).
Benevenuto, F., Rodrigues, T., Almeida, V., Almeida, J., & Ross, K. (2009). Video interactions in online video social networks. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), 5(4), 30:1–30:25.
Benway, J. P. (1998). Banner blindness: The irony of attention grabbing on the World Wide Web. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 42(5), 463–467.
Benway, J. P (1999). Banner blindness: What searching users notice and do not notice on the World Wide Web, United States—Texas: Rice University, http://hdl.handle.net/1911/19353
Bergkvist, L. (2009). The role of confidence in attitude–intention and beliefs–attitude relationships. International Journal of Advertising, 28(5), 863–880.
Blazquez, J. J., Molina, A., Esteban, A., & Martín-Consuegra, N. D. (2008). Análisis de ka eficacia publicitaria en Internet. Investigaciones Europeas de Dirección y Economía de la empresa, 14(1), 159–176.
Brajnik, G., & Gabrielli, S. (2010). A review of online advertising effects on the user experience. International Journal of Human-Computer Interaction, 26(10), 971–997.
Brehm, S., & Brehm, J. W. (1981). Psychological reactance: A theory of freedom and control. New York: Academic Press.
Briggs, R., & Hollis, N. (1997). Advertising on the Web: Is there response before click-through? Journal of Advertising Research, 37(2), 33–45.
Brigham, C. M. (2011). Sport website advertising: the impact of congruity and endorsement on banner advertising effectiveness. Thesis, available at: http://centralspace.ucmo.edu/xmlui/handle/10768/10 (February 12, 2012).
Brown, M. (2002). The use of banner advertisements with pull-down menus: A copy testing approach | JIAD. Journal of Interactive Advertising, 2(2).
Burke, M., Gorman, N., Nilsen, E., & Hornof, A. (2004). “Banner ads hinder visual search and are forgotten”, in CHI’04 extended abstracts on Human factors in computing systems, CHI EA’04 (pp. 1139–1142). New York: ACM.
Burke, M., Hornof A., Nilsen E., & Gorman N. (2005). High-cost banner blindness: Ads increase perceived workload, hinder visual search, and are forgotten. ACM Transactions on Computer-Human Interaction (TOCHI), 12(4), 423–445.
Burns, J. J., & Anderson, D. R. (1993). Attentional inertia and recognition memory in adult television viewing. Communication Research, 20(6), 777–799.
Cacioppo, J. T., Chuan, F. K., Petty, R. E., & Rodriguez, R. (1986). Central and peripheral routes to persuasion: an individual difference perspective. Journal of Personality and Social Psychology, 51(5), 1032.
Calisir, F., & Karaali, D. (2008). The impacts of banner location, banner content and navigation style on banner recognition. Computers in Human Behavior, 24(2), 535–543.
Carroll, A., Barnes, S. J., Scornavacca, E., & Fletcher, K. (2007). Consumer perceptions and attitudes towards SMS advertising: recent evidence from New Zealand. International Journal of Advertising, 26(1), 79–98.
Cauberghe, V., & De Pelsmacker, P. (2008). The impact of banners on digital television: The role of program interactivity and product involvement. CyberPsychology and Behavior, 11(1), 91–94.
Yun, C., Kim, K., & Stout, P. (2004). Assessing the effects of animation in online banner advertising: hierarchy of effects model | JIAD, journal of intera, 4(2).
Chandon, J. L., Chtourou, M. S., & Fortin, D. R. (2003). Effects of configuration and exposure levels on responses to web advertisements. Journal of Advertising Research, 43(2), 217.
Chang, Y., & Thorson, E. (2004). Television and web advertising synergies. Journal of Advertising, 33(2), 75–84.
Chatterjee, P. (2008). Are unclicked ads wasted? Enduring effects of banner and pop-up ad exposures on brand memory and attitudes. Journal of Electronic Commerce Research, 9(1), 51–61.
Chen, L. D., & Tan, J. (2004). Technology adaptation in E-commerce: Key determinants of virtual stores acceptance. European Management Journal, 22(1), 74–86.
Chen, Y., Wang, Q., & Xie, J. (2011). Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of Marketing Research (JMR), 48(2), 238–254.
Cheng, S.-C., & Kao, Y.-H. (2011). Which colour is better? The influence of website photo colour on consumer: The incongruity viewpoint. The Business Review, Cambridge, 17(2), 117–123.
Chang, C. (2011). The influence of editorial liking and editorial-induced affect on evaluations of subsequent ads. Journal of Advertising, 40(3), 45–58.
Cho, C. H. (1999). How advertising works on the WWW: Modified elaboration likelihood model, 21, 33–50.
Cho, C.-H. (2003a). The effectiveness of banner advertisements: Involvement and click-through. Journalism and Mass Communication Quarterly, 80(3), 623–645.
Cho, C.-H. (2003b). Factors influencing clicking of banner ads on the WWW. CyberPsychology and Behavior, 6(2), 201–215.
Cho, C.-H., & Cheon, H. J. (2004). Why do people avoid advertising on the internet? Journal of Advertising, 33(4), 89–97.
Cho, C.-H., & Leckenby, J. (2003). The effectiveness of banner advertisements: Involvement and click-through. Journalism and Mass Communication Quarterly, 80(3), 623–645.
Cho, C.-H., Lee, J.-G., & Tharp, M. (2001). Different forced-exposure levels to banner advertisements. Journal of Advertising Research, 41(4), 45–56.
Choi, S., & Rifon, N. (2002). Antecedents and consequences of web advertising credibility: A study of consumer response to banner ads | JIAD. Journal of Interactive Advertising, 3(1),
Christodoulides, G., Jevons, C., & Bonhomme, J. (2012). Memo to marketers: Quantitative evidence for change. How user-generated content really affects brands. Journal of Advertising Research, 52(1), 53–64.
Coulter, K., & Sarkis, J. (2005). Development of a media selection model using the analytic network process. International Journal of Advertising, 24(2), 193–215.
Cramphorn, M. F., & Meyer, D. (2009). The Gear model of advertising. International Journal of Market Research, 51(3), 319–339.
An, D. (2007). Advertising visuals in global brands’ local websites: a six-country comparison. International Journal of Advertising, 26(3), 303–332.
Dahlen, M. (2001). Banner advertisements through a New Lens. Journal of Advertising Research, 41(4), 23–30.
Dahlén, M., Ekborn, Y., & Mörner, N. (2000). To click or not to click: An empirical study of response to banner ads for high and low involvement products. Consumption Markets and Culture, 4(1), 57–76.
Danaher, P. J., & Mullarkey, G. W. (2003). Factors affecting online advertising recall: A study of students. Journal of Advertising Research, 43(03), 252–267.
Darvell, M. J., Walsh, S. P., & White, K. M. (2011). Facebook tells me so: Applying the theory of planned behavior to understand partner-monitoring behavior on facebook. Cyberpsychology, Behavior, and Social Networking, 14(12), 717–722.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance. MIS Quarterly, 13(3), 319.
Day, R.‐F., Shyi, G. C.‐W., & Wang, J.‐C. (2006). The effect of Flash banners on multiattribute decision making: Distractor or source of arousal?. Psychology and Marketing, 23(5), 369–82.
Yeo, T. E. D. (2012). Social-media early adopters don’t count. Journal of Advertising Research, 52(3), 297–308.
Meirinhos, G. D. S. (2007). El tamaño y la posición de los web banners publicitarios y su recuperación de la memoria episódica. Un análisis desde el enfoque del procesamiento de la información. Thesis, Universidad Autónoma de Barcelona. Available at: http://www.tdx.cat/handle/10803/4127 (March 17, 2012).
Dreze, X., & Hussherr, F.-X. (2003). Internet advertising: Is anybody watching? Journal of Interactive Marketing, 17(4), 8–23.
Duff, B. R. L., & Faber, R. J. (2011). Missing the mark. Journal of Advertising, 40(2), 51–62.
Edwards, S. M., Li, H., & 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.
Eighmey, J., & McCord, L. (1998). Adding value in the information age: Uses and gratifications of sites on the World Wide Web. Journal of Business Research, 41(3), 187–194.
Fang, X., Singh, S., & Ahluwalia, R. (2007). An examination of different explanations for the mere exposure effect. Journal of Consumer Research, 34(1), 97–103.
Fourquet-Courbet, M.-P., Courbet, D., & Vanhuele, M. (2007). How web banner designers work: The role of internal dialogues, self-evaluations, and implicit communication theories. Journal of Advertising Research, 47(2), 183–192.
Zeng, F., Huang, L., & Dou, W. (2009). social factors in user perceptions and responses to advertising in online social networking communities. Journal of Interactive Advertising, 10(1), 1–13.
Fulgoni, G. M., & Mörn, M. P. (2009). Whither the click? How online advertising works. Journal of Advertising Research, 49(2), 134–142.
Garrigos-Simon, F. J., Lapiedra Alcamí, R., & Barberá Ribera, T. (2012). Social networks and Web 3.0: Their impact on the management and marketing of organizations. Management Decision, 50(10), 1880–1890.
Geissler, G. L., Zinkhan, G. M., & Watson, R. T. (2006). The influence of home page complexity on consumer attention, attitudes, and purchase intent. Journal of Advertising, 35(2), 69–80.
Gong, W., & Maddox, L. M. (2003). Measuring web advertising effectiveness in China. Journal of Advertising Research, 43(1), 34.
Goodrich, K. (2010). What’s up? Exploring upper and lower visual field advertising effects. Journal of Advertising Research, 50(1), 91–106.
Graham, J., & Havlena, W. (2007). Finding the ‘Missing Link’: advertising’s impact on word of mouth, web searches, and site visits. Journal of Advertising Research, 47(4), 427–435.
Griffith, D. A., & Chen, Q. (2004). The influence of virtual direct experience (vde) on on-line ad message effectiveness. Journal of Advertising, 33(1), 55–68.
Ha, L., & McCann, K. (2008). An integrated model of advertising clutter in offline and online media. International Journal of Advertising, 27(4), 569–592.
Li, H., Li, A., & Zhao, S. (2009). Internet advertising strategy of multinationals in China. International Journal of Advertising, 28(1), 125–146.
Hart, K. (2007). Online networking goes small, and sponsors follow. Online Networking Goes Small, and Sponsors Follow, The Washington post, http://search.proquest.com/docview/410179234 (March 28, 2012).
Havlena, W., Cardarelli, R., & De Montigny, M. (2007). Quantifying the isolated and synergistic effects of exposure frequency for TV, print, and internet advertising. Journal of Advertising Research, 47(3), 215–221.
Hervet, G., Guérard, K., Tremblay, S., & Chtourou, M. S. (2011). Is banner blindness genuine? Eye tracking internet text advertising. Applied Cognitive Psychology, 25(5), 708–716.
Voorveld, H. A. M. (2011). Media multitasking and the effectiveness of combining online and radio advertising. Computers in Human Behavior, 27(6), 2200–2206.
Hoch, S. J., & Deighton, J. (1989). Managing what consumers learn from experience. Journal of Marketing, 53(2), 1–20.
Hong, W., Thong, J. Y. L., & Tam, K. Y. (2007). How do Web users respond to non-banner-ads animation? The effects of task type and user experience. Journal of the American Society for Information Science and Technology, 58(10), 1467–1482.
Hsieh, Y.-Ch., & Chen, K.-H. (2011). How different information types affect viewer’s attention on internet advertising. Computers in Human Behavior, 27(2), 935–945.
Hughes, D. J., Rowe, M., Batey, M., & Lee, A. (2012). A tale of two sites: Twitter versus Facebook and the personality predictors of social media usage. Computers in Human Behavior, 28(2), 561–569.
Hung, K., Li, S. Y., & Tse, D. K. (2011). Interpersonal trust and platform credibility in a Chinese multibrand online community. Journal of Advertising, 40(3), 99–112.
Hussain, R., Sweeney, A., & Mort, G. S. (2010). Typologies of banner advertisements’ attributes: A content analysis. Journal of Promotion Management, 16(1–2), 96–113.
Hye-Jin, P., Hove, T., Jeong, H. J., & Kim, M. (2011). Peer or expert? International Journal of Advertising, 30(1), 161–188.
IAB (2011). IAB Internet Advertising Revenue Report, IAB & PwC, 26.
Internet World Stats (2011). Internet World Stats—Usage and Population Statistics, Internet World Stats, http://www.internetworldstats.com/ (Dec 13, 2011).
Janiszewski, C. (1998). The influence of display characteristics on visual exploratory search behavior. Journal of Consumer Research, 25(3), 290–301.
Jessen, T. L., & Rodway, P. (2010). The effects of advertisement location and familiarity on selective attention. Perceptual and Motor Skills, 110(3), 941–960.
Kanso, A. M., & Nelson, R. A. (2004). Internet and magazine advertising: Integrated partnerships or not? Journal of Advertising Research, 44(4), 317–326.
Katona, Z., Zubcsek, P. P., & Sarvary, M. (2011). Network effects and personal influences: The diffusion of an online social network. Journal of Marketing Research (JMR), 48(3), 425–43.
Kim, J., & McMillan, S. J. (2008). Evaluation of internet advertising research: A bibliometric analysis of citations from key sources. Journal of Advertising, 37(1), 99–112.
Kim, S., & Choi, S. M. (2010). The effects of corporate credibility and website reputation on banner advertising effectiveness: The moderating role of product-website congruency. American Academy of Advertising Conference Proceedings, 29.
Kivetz, R. (2005). Promotion reactance: The role of effort-reward congruity. Journal of Consumer Research, 31(4), 725–736.
Krugman, H. E. (1983). Television program interest and commercial interruption. Journal of Advertising Research, 23(1), 21–23.
Kuisma, J., Simola, J., Uusitalo, L., & Öörni, A. (2010). The effects of animation and format on the perception and memory of online advertising. Journal of Interactive Marketing, 24(4), 269–282.
Lapa, C. (2007). Using eye tracking to understand banner blindness and improve website design. Thesis, Rochester Institute of Technology, NY.
LaPointe, P. (2012). Measuring Facebook’s impact on marketing. Journal of Advertising Research, 52(3), 286–287.
Lavrakas, P. J., Mane, S., & Laszlo, J. (2010). Does anyone really know if online ad campaigns are working? Journal of Advertising Research, 50(4), 354–373.
Lee, M., & Youn, S. (2009). Electronic word of mouth (eWOM). International Journal of Advertising, 28(3), 473–499.
Lees, G., & Healy, B. (2005). A test of the effectiveness of a mouse pointer image in increasing clic through for a web banner advertisement. Marketing Bulletin, 16.
Li, H., & Bukovac, J. L. (1999). Cognitive impact of banner ad characteristics: An experimental study. Journalism and Mass Communication Quarterly, 76(2), 341–353.
Li, H., Edwards, S. M., & Lee, J.-H. (2002). Measuring the intrusiveness of advertisements: Scale development and validation. Journal of Advertising, 31(2), 37–47.
Lipsman, A., Mud, G., Rich, M., & Bruich, S. (2012). The power of ‘Like’: How brands reach (and influence) fans through social-media marketing. Journal of Advertising Research, 52(1), 40–52.
Liu, Y. (2001). Interactivity and its measurement. (973), 1–28.
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, 31(4), 53–64.
Lohtia, R., Donthu, N., & Hershberger, E. K. (2003). The impact of content and design elements on banner advertising click-through rates. Journal of Advertising Research, 43(4), 410–418.
Manchanda, P., Dubé, J.-P., Goh, K. Y., & Chintagunta, P. K. (2006). The effect of banner advertising on internet purchasing. Journal of Marketing Research (JMR), 43(1), 98–108.
Meyers-Levy, J., & Malaviya, P. (1999). Consumers’ processing of persuasive advertisements: An integrative framework of persuasion theories. The Journal of Marketing, 45–60.
Moe, W. W. (2006). A field experiment to assess the interruption effect of pop-up promotions. Journal of Interactive Marketing (Wiley), 20(1), 34–44.
Möller, J., & Eisend, M. (2010). A global investigation into the cultural and individual antecedents of banner advertising effectiveness. Journal of International Marketing, 18(2), 80–98.
Moore, R. S., Stammerjohan, C. A., & Coulter, R. A. (2005). Banner advertiser–web site context congruity and color effects on attention and attitudes. Journal of Advertising, 34(2), 71–84.
Murdough, C. (2009). Social media measurement: It’s not impossible. Journal of Interactive Advertising, 10(1), 94–99.
Nelson-Field, K., Riebe, E., & Sharp, B. (2012). What’s not to ‘Like?’. Journal of Advertising Research, 52(2), 262–269.
Nielsen (2010). Advertising effectiveness: Understanding the value of social media impression. Nielsen Company.
Nielsen (2012). The social media report 2012. Nielsen online company.
Nutley, M. (2007). It’s the influencers, not the social media, that brands need to target | Opinion | Marketing Week. http://www.marketingweek.co.uk/its-the-influencers-not-the-social-media-that-brands-need-to-target/2056151.article (March 28, 2012).
Okazaki, S. (2009). Social influence model and electronic word of mouth. International Journal of Advertising, 28(3), 439–472.
Pagendarm, M., & Schaumburg, H. (2001). Why are users banner-blind? The impact of navigation style on the perception of web banners. Journal of Digital Information, 2(1).
Pergelova, A., Prior, D., & Rialp, J. (2010). Assessing advertising efficiency. Journal of Advertising, 39(3), 39–54.
Pfeiffer, M., & Zinnbauer, M. (2010). Can Old Media Enhance New Media? How Traditional Advertising Pays off for an Online Social Network, 42–49.
Prendergast, G., & Chia Hwa, H. (2003). An Asian perspective of offensive advertising on the web. International Journal of Advertising, 22(3), 393–411.
Prendergast, G., Ko, D., & Yuen, S. Y. V. (2010). Online word of mouth and consumer purchase intentions. International Journal of Advertising, 29(5), 687–708.
Quinones, P.-A., Vora, J., Steinfeld, A., Smailagic, A., Hansen, J., Siewiorek, D. P., et al. (2008). The effects of highlighting and Pop-up interruptions on task performance. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 52(3), 177–181.
Raacke, J., & Bonds-Raacke, J. (2008). MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites. Cyberpsychology and Behavior, 11(2), 169–174.
Rae, N., & Brennan, M. (1998). The relative effectiveness of sound and animation in web banner advertisments. Marketing bulletin-department of marketing massey university, 9, 76–82.
Riegner, C. (2007.). Word of mouth on the web: The impact of Web 2.0 on consumer purchase decisions. Journal of Advertising Research, 47(4), 436–47.
Robinson, H., Wysocka, A., & Hand, C. (2007). Internet advertising effectiveness. International Journal of Advertising, 26(4), 527–541.
Rodgers, S. (2003). The effects of sponsor relevance on consumer reactions to internet sponsorships. Journal of Advertising, 32(4), 67–76.
Romaniuk, J. (2009). The efficacy of brand-execution tactics in TV advertising, brand placements, and internet advertising. Journal of Advertising Research, 49(2), 143–150.
Ryu, G., Ching Lim, E. A., Tan, L. T. L., & Han, Y. J. (2007). Preattentive processing of banner advertisements: The role of modality, location, and interference. Electronic Commerce Research and Applications, 6(1), 6–18.
San José-Cabezudo, R., & Camarero-Izquierdo, C. (2012). Determinants of opening-forwarding E-Mail messages. Journal of Advertising, 41(2), 97–112.
Smith, T., Coyle, J. R., Lightfoot, E., & Scott, A. (2007). Reconsidering models of influence: The relationship between consumer social networks and word-of-mouth effectiveness. Journal of Advertising Research, 47(4), 387.
Soares, A. M., Pinho, J. C., & Nobre, H. (2012). From social to marketing interactions: The role of social networks. Journal of Transnational Management, 17(1), 45–62.
Sohn, D., & Jee, J. (2005). Network structures of commercial portal sites. International Journal of Advertising, 24(4), 425–440.
Soontae, A., & Stern, S. (2011). Mitigating the effects of advergames on children. Journal of Advertising, 40(1), 43–56.
Sternberg, R. J., & Mio, J. S. (2008). Cognitive psychology, Cengage Learning.
Steyn, P., Ewing, M. T., van Heerden, G., Pitt, L. F., & Windisch, L. (2011). From whence it came. International Journal of Advertising, 30(1), 133–160.
Sun, S., & Wang, Y. (2010). Familiarity, beliefs, attitudes, and consumer responses toward online advertising in china and the united states. Journal of Global Marketing, 23(2), 127–138.
Sundar, S. S., & Kalyanaraman, S. (2004). Arousal, memory, and impression-formation effects of animation speed in web advertising. Journal of Advertising, 33(1), 7–17.
Sundar, S., & Kim, J. (2005). Interactivity and persuasion: influencing attitudes with information and involvement | JIAD. Journal of interactive, 5(2),
Taylor, D. G. (2012). Self-enhancement as a motivation for sharing online advertising. Journal of Interactive Advertising, 12(2).
Taylor, D., Lewin, J., & Strutton, D. (2011). Friends, fans, and followers: Do ads work on social networks? Journal of Advertising Research, 51(1), 258–275.
Terlutter, R., Diehl, S., & Mueller, B. (2010). The cultural dimension of assertiveness in cross-cultural advertising. International Journal of Advertising, 29(3), 369–399.
Thota, S. C., Hee, S. J., & Larsen, V. (2010). Do animated banner ads hurt websites? The moderating roles of website loyalty and need for cognition. Academy of Marketing Studies Journal, 14(1), 91–116.
Trusov, M., Bodapati, A. V., & Bucklin, R. E. (2010). Determining influential users in internet social networks. Journal of Marketing Research (JMR), 47(4), 643–658.
Tucker, C. (2011). Social networks, personalized advertising, and privacy controls, SSRN eLibrary.
Tuenti (2012). Publicidad tuenti, Tuenti, 1–25.
Wakolbinger, L. M., Denk, M., & Oberecker, K. (2009). The effectiveness of combining online and print advertisements. Journal of Advertising Research, 49(3), 360–372.
Wells, W. D. (1997). Measuring Advertising Effectiveness, Routledge.
Wood, O. (2012). How emotional tugs trump rational pushes: The time has come to abandon a 100-year-old advertising model. Journal of Advertising Research, 52(1), 31–39.
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), 45–60.
Yang, K. C. C. (2006). The influence of humanlike navigation interface on users’ responses to Internet advertising. Telematics and Informatics, 23(1), 38–55.
Chang, Y., Yan, J., Zhang, J., & Luo, J. (2010). Online in-game advertising effect: Examining the influence of a match between games and advertising. Journal of Interactive Advertising, 11(1), 63–73.
Yaveroglu, I., & Donthu, N. (2008). Advertising repetition and placement issues in on-line environments. Journal of Advertising, 37(2), 31–44.
Yinghong, W., Frankwick, G. L., Gao, T., & Zhou, N. (2011). Consumer adoption intentions toward the internet in China. Journal of Advertising Research, 51(4), 594–607.
Yoo, C. Y., Kim, K., & Stout, P. A. (2004). Assessing the effects of animation in online banner advertising: Hierarchy of effects model. Journal of Interactive Advertising, 4(2), 49–60.
Yoo, C. Y. (2008). Unconscious processing of Web advertising: Effects on implicit memory, attitude toward the brand, and consideration set. Journal of Interactive Marketing, 22(2), 2–18.
Yoo, C. Y. (2012). An experimental examination of factors affecting click-through of keyword search ads. Journal of Current Issues and Research in Advertising, 33(1), 56–78.
Yu, B. M., & Roh, S. Z. (2002). The effects of menu design on information-seeking performance and user’s attitude on the World Wide Web. Journal of the American Society for Information Science and Technology, 53(11), 923–933.
Yoo, C. Y., & Kim, K. (2005). Processing of animation in online banner advertising: The roles of cognitive and emotional responses. Journal of Interactive Marketing, 19(4), 18–34.
Zanjani, S. H. A., Diamond, W. D., & Chan, K. (2011). Does Ad-context congruity help surfers and information seekers remember ads in cluttered E-magazines? Journal of Advertising, 40(4), 67–84.
Acknowledgments
The authors would like to thank the Research Project ECO2012-31712 under Subprogram for Non-Oriented Fundamental Research Projects, Ministry of Economy and Competitiveness, Spain for their financial support.
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Appendix
Appendix
Summary of relevant conclusions on the variables that affect the efficacy of the banner format on the Internet
Physical characteristics of the banner | ||
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Color (coherence) | • The banner’s color in relation to its containing website affects the perception of coherency and affects attitudes towards the ad | Moore et al.(2005) |
• The incoherence between a banner and its containing website produces a favorable effect on memory and recognition, generating more attention and leading to a more thorough process of the message | ||
• The font’s color attracts attention towards the ad in cases of high contrast between the background and the font, while ads with low contrast do not affect attention | ||
Size or shape | • The larger the ad’s size, the better the impression it makes on the consumer | Baltras (2003) |
• Horizontal banners work better than skyscrapers (vertical banners) | ||
• The ad’s shape is less important than its content | ||
• The banner’s size is less relevant than the location it occupies within the website | Dos Santos (2007) | |
• Users show a certain cognitive regularity in the processing of banners with distinct sizes. There is not empirical evidence that indicates that larger banners are more remembered than smaller banners | ||
Animation level: dynamic | • Animation generates greater attention, a greater number of clicks (CTR) and better recall | (Li and Bukovac, 1999) |
• Animation reduces blindness towards the banner | Bayles (2000) | |
• Animation does not produce an effect on ad recognition | Bayles (2002) | |
• Animation does not produce an effect on memory of recognition | Dreze and Hussherr (2003) | |
• Having a dynamic banner is preferable to a static one as it generates greater attention | Sundar and Kalyanaraman (2004) | |
• The animated banner is irrelevant as there is a tendency to ignore it | ||
• It delays visual exploration and reduces memory | ||
• Animation speed matters | Sundar and Kalyanaraman (2004) | |
• Greater speed, greater attention | ||
• Animation improves the attitude towards the ad but worsens the ad towards the product | (Sundar and Kim 2005) | |
• Excessive animation can generate negative cognitive and emotional effects. If the banner is perceived as coercive, it causes skepticism and distrust, negatively influencing the user’s attitude towards the website, brand or their intentions to revisit the site | Yun and Kim (2005) | |
• Animation increases CTR, prolongs navigation time, and reduces the focus of the user’s attention, causing them to examine fewer elements which affects their search process | Hong et al. (2007) | |
• Dynamic banners are better remembered than static banners but this does not coincide with a significant effect on recognition of the message | Kuisma et al. (2010) | |
• Negative effects of animation are moderated by loyalty to the website and by the users’ need for knowledge | Thota et al. (2010) | |
Animation level: static | • Lack of animation attracts the users’ attention, while the presence of animation increases the likelihood of clicking and purchasing | Hong et al. (2007) |
Banner content | ||
Creativity | • Users prefer banners with short, clear messages to ones with long messages | Baltras (2003) |
• Promotions and encrypted messages to have an impact on visitors | ||
• Complex creativity that lengthens download time has a negative influence, leading to users changing websites or to not seeing the ad | ||
• Creative banners are more efficacious in terms of increased CTR when compared to large banners with large messages and an absence of promotional incentives | Robinson et al. (2007) | |
Incorporated graphic images | • Inclusion of visual elements such as a cursor (mouse) does not improve CTR | Lees and Healy (2005) |
Source credibility | • Source credibility is vital for understanding the efficacy of online advertising. When a source is highly credible, there is an increase in the ad’s relevancy, positive attitudes towards the brand and purchasing intentions | Choi and Rifon (2002) |
Location within the website | ||
Page position | • Ads located in a website’s periphery play a different role than those shown at the top of the page | Benway (1999) |
• Flash banners in a website’s periphery accelerate the decision-making process, although users infrequently glance at them in response to their flashes | Day et al. (2006) | |
• Peripheral banners, instead of attracting participants attention, elevate their arousal level, which in turn, increases their decision making speed when faced with a decision between several choices | ||
• Users regularly remember a banner’s content independently of its position | Dos (2007) | |
• When sizes are similar, users better remember banners found at the bottom of the website over those found at the top of the page. Therefore, position outweighs size in terms of affecting memory | ||
Order of the webpages layout | • Users pay more attention to banners situated in the first pages encountered during navigation | Hsieh and Chen (2011) |
• The first page is always the best at attracting the users’ attention towards the ad. However, the first text-based pages or mixed text/image-based pages are worse at capturing attention than pages based solely on video or images | ||
• Navigating different pages, within a single website, with distinct types of information affects attention towards the ad. Also, users are more affected by the ad’s content when it is placed on the landing page in comparison to any other page of a website | ||
• In image or video based pages, attention towards the banner is reduced as the user follows the natural order of a site’s distinct pages | ||
• Websites with ads based in videos or images do a better job of capturing the users’ attention than websites whose ads are solely based in text or in a mixture of text and images | ||
• Video-based websites are the best at attracting the users’ attention towards the ad | ||
Coherence with the website | • In the absence of coherency between the advertised products and the website, the message will largely be seen as irrelevant and little interest will be aroused. This results in a lower CTR. | Cho (1999) |
• Coherency between the advertised product and the website’s content has an effect on the sources credibility | Kim and Choi (2010) | |
• In the case of highly credible businesses, coherency between advertised and website product will lead to the banner being more persuasive | ||
• Businesses with low credibility do not benefit from banner-website coherency | ||
Exposure level | • Banner repetition increases recall and recognition. It also improves affect and the user’s cognition towards the ad | Yaveroglu and Donthu (2008) |
User characteristics | ||
Gender | • Men mostly use the left hemisphere of their brain, which leads to them establishing global rules and categorical concepts during information processing | Meyers-Levy and Malaviya (1999) |
• Women tend to process with the right hemisphere, which leads to them fixating more on specificities and intrinsic values implied in the stimulus or information | ||
• Men process holistically and with a general approach, while women process advertising messages in a more detailed and elaborate fashion | ||
Influence of user’s culture | • Individualism has a high explanatory power of attitudes towards a banner ad | Möller and Eisend (2010) |
• Consumers who come from individualistic cultures value banner ads less and less likely to click on them than consumers from collectivist cultures | ||
Web experience | • High Internet expertise users will tend to unconsciously ignore banner ads when developing a sequential navigation process. | Burns and Anderson (1993) |
• Less experienced Internet users click on banners more often than more experienced users | Dahlen (2001) | |
• Less experienced users show higher levels of change in their knowledge and attitude towards a brand based on their interaction with a banner than experienced users | ||
• The effect of experience with animated formats can reduce distraction, produced by the animation, from the user’s task | Hong et al. (2007) | |
• The user’s level of experience with animated banners reduces the animation’s effects | ||
• When users lack experience with a particular website, they pay greater attention to ads during their first visits | Lapa (2007) | |
• After familiarizing themselves with a website’s design, the user’s attention continually diminishes | ||
Familiarity with the brand or product | • Familiarity implies growing accustomed to a stimulus, paying less and less attention to it | Cacioppo et al. (2007; pág. 166), Sternberg and Mio (2008, p. 137) |
• Familiarity occurs automatically and does not imply conscious effort. Thus, the stimulus’s relative stability and familiarity govern this process | ||
• Ads from known brands receive, on average, a greater number of clicks than ads from unknown brands | Dahlen (2001) | |
• For known brands, the number of clicks decreases with repeated exposure to the banner | ||
• For unknown brands, the number of clicks decreases with repeat exposure | ||
Involvement with the product or task | • At low levels of involvement, animation increases CTR | Cho and Leckenby (2003) |
• At high levels of involvement, animation does not influence CTR | ||
• At high levels of involvement, the odds of the user clicking on the banner are increased when it contains information about the product | ||
• In cases of low levels of involvement with the product, the odds of the user voluntarily seeking exposure to the banner by clicking on it is lower | ||
• Involvement leads to higher levels of memory and recognition | Yun et al. (2004) | |
Relevance of the message | • Relevance does not increase distraction | Cho (1999) |
• Relevance increases CTR in users with a positive attitude towards the website. | ||
• Relevance leads to a positive attitude towards the ad. When a message is relevant for users, they will tend to follow the so-called central route, as shown by the ELM model | Lapa (2007) | |
• If the message is relevant, time spent by users at the website does not affect their attitude towards the message or its efficacy | ||
Attitude towards the brand | • Attitude towards the ad is affected by the ad’s dimensions of evasion, which change depending on the degree of forced exposure to the ad | Fang et al. (2007) |
Type of navigation | • For users who navigate in a task-oriented manner, ads with animation diminish the users’ efficiency. In this case, animation also negatively affects users’ perception of the ad | Hong et al. (2007) |
• In the case of exploratory navigation, the negative effects caused by animation are worse than in the case of purpose-drive navigation | ||
• In the case of free or exploratory navigation, the longer the exposure time, the better memory and recognition of the ad are. This is effect is lesser in the case of users with goal-directed navigation | Danaher and Mullarkey (2003) | |
• Participants navigating freely recognize banner ads that include a URL address significantly better than banners with information about the advertised service but without a URL address | Calisir and Karaali (2008) | |
• Users navigating in a goal-oriented fashion, show better recognition of ads compared to users with exploratory behavior only when the banner includes some information about the advertised service and a URL address | ||
• For participants with a goal-directed navigation style, there are no significant differences in recognition of the banner’s distinct content types | ||
Type of position | • Voluntary exposure to the ad, captures the users’ attention and activates the cognitive learning process more intensely than involuntary exposure | Cho (1999) |
• Clicking on the banner is a precondition for beginning of the active processing of information. This, in turn, has positive effects on memory and therefore, on the degree of memory about the ad | ||
• Forced exposure to a banner makes the user perceive the ad in a more explicit manner. It also increases CTR and attention paid to the banner | Cho et al. (2001) | |
• If exposure of a banner is forced upon a user, it can generate a favorable attitude towards the ad and the brand. This furthermore produces an increase in purchasing intention | ||
• However, at certain levels of forced exposure, feelings of annoyance arise as well as irritation, which induces evasion (e.g. cognitive and physical) |
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Rejón-Guardia, F., Martínez-López, F.J. (2014). An Integrated Review of the Efficacy of Internet Advertising: Concrete Approaches to the Banner Ad Format and the Context of Social Networks. In: Martínez-López, F. (eds) Handbook of Strategic e-Business Management. Progress in IS. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39747-9_22
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