Abstract
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.
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References
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)
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)
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)
Berdichevsky, D., Neuenschwander, E.: Towards an ethics of persuasive technology. Communications of the ACM 42(5) (1999)
Bettman, J.R., Luce, M.F., Payne, J.: Constructive Consumer Choice Processes. Journal of Consumer Research 25, 187–217 (1998)
Burke, R.: Knowledge-based Recommender Systems. Encyclopedia of Library & Information Systems 69(32) (2000)
Burke, R.: Hybrid Recommender Systems: Survery and Experiments. User Modeling and User-Adapted Interaction 12, 331–370 (2002)
Ebbinghaus, H.: Memory: A contribution to experimental psychology. Columbia University, Teachers College, New York (1913)
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)
Fogg, B.J.: Persuasive computers: Perspectives and research directions. In: Proceedings of the SIGCHI conference on Human factors in computing systems CHI 1998 (1998)
Fogg, B.J.: Persuasive Technology. Morgan Kaufmann Publishers, San Francisco (2003)
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)
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)
Gretzel, U., Fersenmaier, D.R.: Persuation in Recommender systems. International Journal of Electronic Commerce 7(2), 81–100 (2007)
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)
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)
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)
King, P., Tester, J.: The landscape of persuasion technologies. Communications of the ACM 42(5), 31–38 (1999)
Kirckpatrick, E.A.: An experimental study of memory. Psychological Review 1, 602–609 (1894)
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)
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)
Mandel, N., Johnson, E.J.: When Web pages influence choice: Effects of visual primes on novices. Journal of Consumer Research 29, 235–245 (2002)
Maylor, E.: Serial position effects in semantic memory: reconstructing the order of verses of hymns. Psychonomic Bulletin & Review 9, 816–820 (2002)
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)
Payne, J.W., Bettman, J.R., Johnson, E.J.: The Adaptive Decision Maker. Cambridge University Press, New York (1993)
Pazzani, M., Billsus, D.: Learning and Revising User Profiles: The Identification of Interesting Web Sites. Machine Learning 27, 313–331 (1997)
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)
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)
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)
Sehulster, J.R.: Content and temporal structure of autobiographical knowledge: Remembering twenty-five seasons of the Metropolitan Opera. Memory & Cognition 17, 590–606 (1989)
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)
Tversky, A.: Intransitivity of preferences. Psychological Review 76, 327–352 (1969)
Tversky, A.: Elimination by aspects: A theory of choice. Psychological Review 79, 281–299 (1972)
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)
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)
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Felfernig, A. et al. (2007). Persuasive Recommendation: Serial Position Effects in Knowledge-Based Recommender Systems. In: de Kort, Y., IJsselsteijn, W., Midden, C., Eggen, B., Fogg, B.J. (eds) Persuasive Technology. PERSUASIVE 2007. Lecture Notes in Computer Science, vol 4744. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77006-0_34
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DOI: https://doi.org/10.1007/978-3-540-77006-0_34
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