Abstract
Online content providers need a loyal user base for achieving a profitable revenue stream. Large number of visits and long clickstreams are essential for business models based on online advertising. In e-commerce settings, personalized recommendations have already been extensively researched on their effect on both user behavior and related economic performance indicators. We transfer this evaluation into the online content realm and show that recommender systems exhibit a positive impact for online content provider as well. Our research hypotheses emphasize on those components of an advertising-based revenue stream, which are manipulable by personalized recommendations. Based on a rich data set from a regional German newspaper the hypotheses are tested and conclusions are derived.
This is a preview of subscription content, log in via an institution to check access.
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
Anderson, C.: The Long Tail: Why the Future of Business is Selling Less of More. Hyperion, New York (2006)
Bhat, S., Bevans, M., Sengupta, S.: Measuring Users’ Web Activity to Evaluate & Enhance Advertising Effectiveness. Journal of Advertising 31(3), 97–106 (2002)
Bodenbenner, P., Neumann, D.: Are Personalized Recommendations the Savior for Online Content Providers? In: Proceedings of MKWI 2012, pp. 1933–1945 (2012)
Brynjolfsson, E., Hu, Y., Smith, M.: From Niches to Riches: The Anatomy of the Long Tail. Sloan Management Review 47(4), 67–71 (2006)
Bucklin, R., Sismeiro, C.: A Model of Web Site Browsing Behavior Estimated on Click-stream Data. Journal of Marketing Research 40(3), 249–267 (2003)
Chen, P., Wu, S., Yoon, J.: The Impact of Online Recommendations and Consumer Feedback on Sales. In: ICIS 2004 Proceedings, paper 58 (2004)
Clemons, E., Gu, B., Lang, K.: Newly-Vulnerable Markets in an Age of Pure Information Products. In: Proc. of the 35th Hawaii Int. Conf. on System Sciences, p. 218 (2002)
Das, A.S., Datar, M., Garg, A., Rajaram, S.: Google News Personalization: Scalable Online Collaborative Filtering. In: Proc. of the 16th Int. Conf. on WWW, pp. 271–280. ACM (2007)
Davenport, T., Beck, J.: The Attention Economy: Understanding the New Currency of Business. Harvard Business School Press, Boston (2001)
Demers, E., Lev, B.: A Rude Awakening: Internet Shakeout in 2000. Review of Accounting Studies 6(2-3), 331–359 (2001)
Dias, M., Locher, D., Li, M., El-Deredy, W., Lisboa, P.: The Value of Personalized Recommender Systems to E-Business. In: Proceedings of the ACM RecSys, pp. 291–294 (2008)
Elberse, A.: Should You Invest in Long Tail? Harvard Business Review 86(7-8), 88 (2008)
Evans, D.: The Online Advertising Industry: Economics, Evolution, and Privacy. Journal of Economic Perspectives 23(3), 37–60 (2009)
Fleder, D., Hosanagar, K.: Blockbuster Culture’s Next Rise or Fall: Impact of Recommender Systems on Sales Diversity. Management Science 55(5), 697–712 (2009)
Hinz, O., Eckert, J.: The Impact of Search and Recommendation Systems on Sales in Electronic Commerce. Business & Information Systems Engineering 2(2), 67–77 (2010)
Komiak, S., Benbasat, I.: The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents. MIS Quarterly 30(4), 941–960 (2006)
Kumar, N., Benbasat, I.: The Influence of Recommendations and Consumer Reviews on Evaluations of Websites. Information Systems Research 17(4), 425–439 (2006)
Liu, J., Dolan, P., Pedersen, E.R.: Personalized News Recommendation Based on Click Behavior. In: Proc. of the 14th Int. Conference on Intelligent User Interfaces, pp. 31–40 (2010)
Mooney, R., Roy, L.: Content-based Book Recommending Using Learning for Text Categorization. In: Proc. of 5th ACM Conference on Digital Libraries, pp. 195–204 (2000)
Pathak, B., Garfinkel, R., Gopal, R.D., Venkatesan, R., Yin, F.: Empirical Analysis of the Impact of Recommender Systems on Sales. Journal of Management Information Systems 27(2), 159–188 (2010)
Peterson, E.: Web Analytics Demystified: The Big Book of Key Performance Indicators. Web Analytics Demystified, Inc. (2006)
Resnick, P., Varian, H.R.: Recommender Systems. Communications of the ACM 40(3), 56–58 (1997)
Schafer, J.B., Konstan, J., Riedl, J.: Recommender Systems in E-Commerce. In: Proc. of the 1st ACM Conference on Electronic Commerce, pp. 158–166 (1999)
Zhu, F., Zhang, X.: Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. Journal of Marketing 74(2), 133–148 (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bodenbenner, P., Hedwig, M., Neumann, D. (2012). Impact of Recommendations on Advertising-Based Revenue Models. In: Shaw, M.J., Zhang, D., Yue, W.T. (eds) E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life. WEB 2011. Lecture Notes in Business Information Processing, vol 108. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29873-8_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-29873-8_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29872-1
Online ISBN: 978-3-642-29873-8
eBook Packages: Computer ScienceComputer Science (R0)