Persuasive Recommendation: Serial Position Effects in Knowledge-Based Recommender Systems

  • A. Felfernig
  • G. Friedrich
  • B. Gula
  • M. Hitz
  • T. Kruggel
  • G. Leitner
  • R. Melcher
  • D. Riepan
  • S. Strauss
  • E. Teppan
  • O. Vitouch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4744)


Recommender technologies are crucial for the effective support of customers in online sales situations. The state-of-the-art research in recommender systems is not aware of existing theories in the areas of cognitive and decision psychology and thus lacks of deeper understanding of online buying situations. In this paper we present results from user studies related to serial position effects in human memory in the context of knowledge-based recommender applications. We discuss serial position effects on the recall of product descriptions as well as on the probability of product selection. Serial position effects such as primacy and recency are major building blocks of persuasive, next generation knowledge-based recommender systems.


persuasive technologies recommender systems knowledge-based recommendation human memory interactive selling 


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  1. 1.
    Atkinson, R.C., Shiffrin, R.M.: Human Memory: A proposed system and its control processes. In: Spence, K.W., Spence, J.T. (eds.) The psychology of learning and motivation: Advances in research and theory, pp. 89–195. Academic Press, New York (1968)Google Scholar
  2. 2.
    Baddeley, A.D., Hitch, G.: Recency re-examined. In: Dornic, I S. (ed.) Attentional and performance, vol. VI, pp. 647–667. Erlbaum, Hillsdale, New York (1977)Google Scholar
  3. 3.
    Bellman, S., Johnson, E.J., Lohse, G.L., Mandel, N.: Designing Marketplaces of the Artificial with Consumers in Mind: Four Approaches to Understanding Consumer Behavior in Electronic Environments. Jrnl. of Interactive Marketing 20, 21–33 (2006)CrossRefGoogle Scholar
  4. 4.
    Berdichevsky, D., Neuenschwander, E.: Towards an ethics of persuasive technology. Communications of the ACM 42(5) (1999)Google Scholar
  5. 5.
    Bettman, J.R., Luce, M.F., Payne, J.: Constructive Consumer Choice Processes. Journal of Consumer Research 25, 187–217 (1998)CrossRefGoogle Scholar
  6. 6.
    Burke, R.: Knowledge-based Recommender Systems. Encyclopedia of Library & Information Systems 69(32) (2000)Google Scholar
  7. 7.
    Burke, R.: Hybrid Recommender Systems: Survery and Experiments. User Modeling and User-Adapted Interaction 12, 331–370 (2002)zbMATHCrossRefGoogle Scholar
  8. 8.
    Ebbinghaus, H.: Memory: A contribution to experimental psychology. Columbia University, Teachers College, New York (1913)Google Scholar
  9. 9.
    Felfernig, A., Gula, B.: An Empirical Study on Consumer Behavior in the Interaction with Knowledge-based Recommender Applications. In: IEEE Joint Conference on E-Commerce Technology (CEC 2006) and Enterprise Computing, E-Commerce and E-Services (EEE 2006), pp. 288–296. IEEE Computer Society, San Francisco, California (2006)Google Scholar
  10. 10.
    Fogg, B.J.: Persuasive computers: Perspectives and research directions. In: Proceedings of the SIGCHI conference on Human factors in computing systems CHI 1998 (1998)Google Scholar
  11. 11.
    Fogg, B.J.: Persuasive Technology. Morgan Kaufmann Publishers, San Francisco (2003)Google Scholar
  12. 12.
    Gasser, R., Brodbeck, D., Degen, M., Luthiger, J., Wyss, R., Reichlin, S.: Persuasiveness of Mobile Lifestyle Coaching Application Using Social Facilitation. In: IJsselsteijn, W., de Kort, Y., Midden, C., Eggen, B., van den Hoven, E. (eds.) PERSUASIVE 2006. LNCS, vol. 3962, pp. 27–38. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. 13.
    Gershberg, F.B., Shimamura, A.P.: Serial position effects in implicit and explicit tests of memory. Journal of Experimental Psychology: Learning, Memory, and Cognition 20, 1370–1378 (1994)CrossRefGoogle Scholar
  14. 14.
    Gretzel, U., Fersenmaier, D.R.: Persuation in Recommender systems. International Journal of Electronic Commerce 7(2), 81–100 (2007)Google Scholar
  15. 15.
    Häubl, G., Murray, K.B.: Preference Construction and Persistence in Digital Marketplaces: The Role of Electronic Recommendation Agents. Journal of Consumer Psychology 13, 75–91 (2003)CrossRefGoogle Scholar
  16. 16.
    Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating Collaborative Filtering Recommender Systems. ACM Trans. on Information Systems 22(1), 5–53 (2004)CrossRefGoogle Scholar
  17. 17.
    Hitch, G.J., Ferguson, J.: Prospective memory for future intentions: Some comparisons with memory for past events. European Journal of Cognitive Psychology 3, 285–295 (1991)CrossRefGoogle Scholar
  18. 18.
    King, P., Tester, J.: The landscape of persuasion technologies. Communications of the ACM 42(5), 31–38 (1999)CrossRefGoogle Scholar
  19. 19.
    Kirckpatrick, E.A.: An experimental study of memory. Psychological Review 1, 602–609 (1894)CrossRefGoogle Scholar
  20. 20.
    Komiak, S., Benbasat, I.: Comparing Persuasiveness of Different Recommendation Agents as Customer Decision Support Systems in Electronic Commerce. In: DSS 2004. International Conference on Decision Support Systems, Prato, Tuscany (2004)Google Scholar
  21. 21.
    Lashley, K.S., The, K.S.: problem of serial order in behavior. In: Jeffress, L.A. (ed.) Cerebral mechanisms in behaviour, pp. 112–136. Wiley, New York (1951)Google Scholar
  22. 22.
    Mandel, N., Johnson, E.J.: When Web pages influence choice: Effects of visual primes on novices. Journal of Consumer Research 29, 235–245 (2002)CrossRefGoogle Scholar
  23. 23.
    Maylor, E.: Serial position effects in semantic memory: reconstructing the order of verses of hymns. Psychonomic Bulletin & Review 9, 816–820 (2002)Google Scholar
  24. 24.
    Nipher, F.E.: On the distribution of errors in numbers written from memory. Transactions of the Academy of Science of St. Louis 3, CCX-CCXI (1878)Google Scholar
  25. 25.
    Payne, J.W., Bettman, J.R., Johnson, E.J.: The Adaptive Decision Maker. Cambridge University Press, New York (1993)Google Scholar
  26. 26.
    Pazzani, M., Billsus, D.: Learning and Revising User Profiles: The Identification of Interesting Web Sites. Machine Learning 27, 313–331 (1997)CrossRefGoogle Scholar
  27. 27.
    Petty, R.E., Zakary, L.T., Hawkins, C., Wegener, D.T.: Motivation to think and order effects in persuasion: the moderating role of chunking. Personality and Social Psychology Bulletin 27, 332–344 (2001)CrossRefGoogle Scholar
  28. 28.
    Pinto, A.C., Baddeley, A.D.: Where did you last park your car? Analysis of naturalistic long-term recency effect. European Journal of Cognitive Psychology 3, 297–313 (1991)CrossRefGoogle Scholar
  29. 29.
    Sarwar, B., Karypis, G., Konstan, J.A., Riedl, J.T.: Item-based collaborative filtering recommendation algorithms. In: 10th Int. World Wide Web Conf., pp. 285–295 (2001)Google Scholar
  30. 30.
    Sehulster, J.R.: Content and temporal structure of autobiographical knowledge: Remembering twenty-five seasons of the Metropolitan Opera. Memory & Cognition 17, 590–606 (1989)Google Scholar
  31. 31.
    Shih, Y.-Y., Liu, D.-R.: Hybrid recommendation approaches: collaborative filtering via valuable content information. In: HICSS 2005. 38th Hawaii International Conference on System Sciences, Big Island, Hawaii, p. 217b (2005)Google Scholar
  32. 32.
    Tversky, A.: Intransitivity of preferences. Psychological Review 76, 327–352 (1969)CrossRefGoogle Scholar
  33. 33.
    Tversky, A.: Elimination by aspects: A theory of choice. Psychological Review 79, 281–299 (1972)CrossRefGoogle Scholar
  34. 34.
    Young, R.K.: Serial Learning. In: Dixon, T.R., Horton, D.L. (eds.) Verbal behaviour and behaviour theory, pp. 122–148. Prentice Hall, Engelwood Cliffs, NJ (1968)Google Scholar
  35. 35.
    Zanker, M., Bricman, M., Gordea, S., Jannach, D., Jessenitschnig, M.: Persuasive online selling in quality & taste domains. In: Bauknecht, K., Pröll, B., Werthner, H. (eds.) EC-Web 2006. LNCS, vol. 4082, pp. 51–60. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • A. Felfernig
    • 1
  • G. Friedrich
    • 1
  • B. Gula
    • 2
  • M. Hitz
    • 3
  • T. Kruggel
    • 1
  • G. Leitner
    • 3
  • R. Melcher
    • 3
  • D. Riepan
    • 1
  • S. Strauss
    • 2
  • E. Teppan
    • 1
  • O. Vitouch
    • 2
  1. 1.Computer Science and Manufacturing 
  2. 2.Cognitive Psychology 
  3. 3.Interactive Systems, Klagenfurt University, Universitaetsstrasse 65-67, A-9020 KlagenfurtAustria

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