Chapter

Persuasive Technology

Volume 4744 of the series Lecture Notes in Computer Science pp 283-294

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

  • A. FelfernigAffiliated withComputer Science and Manufacturing
  • , G. FriedrichAffiliated withComputer Science and Manufacturing
  • , B. GulaAffiliated withCognitive Psychology
  • , M. HitzAffiliated withInteractive Systems, Klagenfurt University, Universitaetsstrasse 65-67, A-9020 Klagenfurt
  • , T. KruggelAffiliated withComputer Science and Manufacturing
  • , G. LeitnerAffiliated withInteractive Systems, Klagenfurt University, Universitaetsstrasse 65-67, A-9020 Klagenfurt
  • , R. MelcherAffiliated withInteractive Systems, Klagenfurt University, Universitaetsstrasse 65-67, A-9020 Klagenfurt
  • , D. RiepanAffiliated withComputer Science and Manufacturing
  • , S. StraussAffiliated withCognitive Psychology
    • , E. TeppanAffiliated withComputer Science and Manufacturing
    • , O. VitouchAffiliated withCognitive Psychology

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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.

Keywords

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