Enhancing comparison shopping agents through ordering and gradual information disclosure

Chen Hajaj, Noam Hazon, David Sarne

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

The plethora of comparison shopping agents (CSAs) in today’s markets enables buyers to query more than a single CSA when shopping, thus expanding the list of sellers whose prices they obtain. This potentially decreases the chance of a purchase within any single interaction between a buyer and a CSA, and consequently decreases each CSAs’ expected revenue per-query. Obviously, a CSA can improve its competence in such settings by acquiring more sellers’ prices, potentially resulting in a more attractive “best price”. In this paper we suggest a complementary approach that improves the attractiveness of the best result returned based on intelligently controlling the order according to which they are presented to the user, in a way that utilizes several known cognitive-biases of human buyers. The advantage of this approach is in its ability to affect the buyer’s tendency to terminate her search for a better price, hence avoid querying further CSAs, without spending valuable resources on finding additional prices to present. The effectiveness of our method is demonstrated using real data, collected from four CSAs for five products. Our experiments confirm that the suggested method effectively influence people in a way that is highly advantageous to the CSA compared to the common method for presenting the prices. Furthermore, we experimentally show that all of the components of our method are essential to its success.

Original languageEnglish
Pages (from-to)696-714
Number of pages19
JournalAutonomous Agents and Multi-Agent Systems
Volume31
Issue number3
DOIs
StatePublished - 1 May 2017

Bibliographical note

Publisher Copyright:
© 2016, The Author(s).

Keywords

  • Belief adjustment
  • Comparison shopping agents
  • E-commerce
  • Experimentation
  • Ordering effects

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