Abstract
With Internet advertising revenue ever increasing, mobile advertising revenue is rapidly growing as well. One of the main characteristics of the Internet and mobile advertising is that they can deliver personalized advertisements to each user. However, the notion of personalized ad method is not a single concept, and the required information for personalization depends upon the type of service platform. So some personalized ad method matches with a certain service platform better than the others. To characterize the mapping between personalized ad methods and service platform, this research measures the supportiveness of typical Internet and mobile platforms for the seven types of personalized ad methods. For the measurement, a constraint satisfaction problem (CSP) approach is adopted to assess the degree of the match between the personalized ad methods and platforms via the required information that are necessary to create the personalized ads. The results of this research help web publishers assess their potential to deliver specific personalized ad methods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Debes, M., Lewandowska, A., Seitz, J.: Definition and Implementation of Context Information. In: Navigation and Communication (WPNC 2005) & 1st Ultra-Wideband Expert Talk (UET 2005), pp. 63–68 (2005)
De Bock, K.W., Van den Poel, D.: Predicting Website Audience Demographics for Web Advertising Targeting Using Multi-Website Clickstream Data. Fundamenta Informaticae 98, 49–70 (2010)
Abowd, G.D., Dey, A.K.: Towards a Better Understanding of Context and Context-Awareness. In: Gellersen, H.-W. (ed.) HUC 1999. LNCS, vol. 1707, pp. 304–307. Springer, Heidelberg (1999)
Dey, A.K., Salber, D., Abowd, G.D.: A Conceptual Framework and a Toolkit for Supporting the Rapid Prototyping of Context-Aware Applications. Human-Computer Interaction (HCI) Journal 16, 97–166 (2001)
Dhar, S., Varshney, U.: Challenges and Business Models for Mobile Location based Services and Advertising. Communications of the ACM 54, 121–128 (2011)
Elliot, S.: For Foursquare, It’s Not an Ad, It’s a Promoted Update, http://www.nytimes.com/2012/07/26/business/media/foursquare-to-test-paid-ads-advertising.html
eMarketer: Twitter Tops Facebook in US Mobile Advertising Revenue, http://www.emarketer.com/newsroom/index.php/emarketer-twitter-tops-facebook-mobile-advertising-revenue/
Facebook, https://www.facebook.com/ads/create/
Goldfarb, A., Tucker, C.E.: Privacy Regulation and Online Advertising. Management Science 57, 57–71 (2011)
Groupon, http://www.groupon.com/now/about
Heine, C.: Foursquare Takes Aim at Retail Chains (Again), http://www.adweek.com/news/technology/foursquare-takes-aim-retail-chains-again-141978
Hofacker, C.F., Murphy, J.: Clickable World Wide Web Banner Ads and Content Sites. J. of Interactive Marketing 14, 49–59 (2000)
IAB: IAB Internet Advertising Revenue Report: 2012 First Six Months’ Results, http://www.iab.net/insights_research/industry_data_and_landscape/adrevenuereport
Kim, J.S., Lee, J.K.: Comparison of Personalized Ad Methods on the Internet and Mobile Platforms. Asia Pacific Journal of Information Systems 22, 125–149 (2012) (in Korean)
Komulainen, R., Nadeem, W., Satokangas, S., Salo, J.: Rewarding In-Game Banner Ad Clicks with Tangible Incentives. In: Douligeris, C., Polemi, N., Karantjias, A., Lamersdorf, W. (eds.) I3E 2013. IFIP AICT, vol. 399, pp. 286–297. Springer, Heidelberg (2013)
Lee, J.K., Kwon, S.B.: ES∗: An Expert Systems Development Planner Using a Constraint and Rule-Based Approach. Expert Systems with Applications 9, 3–14 (1995)
Li, H., Leckenby, J.: Internet Advertising Formats and Effectiveness. In: Schumann, D., Thorson, E. (eds.) Internet Advertising, Theory and Research. Lawrence Erlbaum Associates, New Jersey (2006)
Meyer, M., Balsam, M., O’keefe, A., Schluter, C.: Admotional: Towards Personalized Online Ads. International Journal of Computer Science and Applications 8, 59–80 (2011)
Nadel, B.A.: Representation Selection for Constraint Satisfaction: A Case Study Using N-Queens. IEEE Expert 5, 16–23 (1990)
Peterson, T.: Google Expands Its Ad Formats with Lightbox, http://www.adweek.com/news/advertising-branding/google-expands-its-ad-formats-lightbox-144119
PewInternet: Trend Data (Adults), http://www.pewinternet.org/Static-Pages/Trend-Data-Adults/Online-Activites-Total.aspx
Reed, R.: The SoLoMo Manifesto, http://momentfeed.com/whitepaper/
Rodgers, S., Thorson, E.: The Interactive Advertising Model: How Users Perceive and Process Online Ads. J. of Interactive Advertising 1, 42–61 (2000)
Salo, J., Tähtinen, J.: Retailer Use of Permission-Based Mobile Advertising. In: Clarke III, I., Flaherty, T.B. (eds.) Advances in Electronic Marketing, pp. 139–156. Idea Group Publishing, PA (2005)
Salo, J., Karjaluoto, H.: Mobile Games as an Advertising Medium: Towards a New Research Agenda. Innovative Marketing 3, 71–82 (2007)
Turban, E., King, D., Lee, J., Liang, T., Turban, D.: Electronic Commerce 2012: Managerial and Social Networks Perspectives. Prentice Hall, NJ (2012)
Vasquez, D.: Stunner: Online Ad $ Could Pass TV by 2017, http://www.medialifemagazine.com/shocker-online-ad-could-pass-tv-by-2017/
Xu, D.J., Liao, S.S., Li, Q.: Combining Empirical Experimentation and Modeling Techniques: A Design Research Approach for Personalized Mobile Advertising Applications. Decision Support Systems 44, 710–724 (2008)
Yan, J., Liu, N., Wang, G., Zhang, W., Jiang, Y., Chen, Z.: How Much Can Behavioral Targeting Help Online Advertising? In: 18th International Conference on World Wide Web, pp. 261–270. ACM (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kim, J.S., Lee, J.K. (2013). Measuring Supportiveness of the Internet and Mobile Platforms for Personalized Ad. In: Järveläinen, J., Li, H., Tuikka, AM., Kuusela, T. (eds) Co-created Effective, Agile, and Trusted eServices. ICEC 2013. Lecture Notes in Business Information Processing, vol 155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39808-7_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-39808-7_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39807-0
Online ISBN: 978-3-642-39808-7
eBook Packages: Computer ScienceComputer Science (R0)