The effects of time and number of personalized items on USERS' amount of sampling

David Bodoff, Shuk Ying Ho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With advances in personalization technologies, websites are increasingly able to personalize web content and provide users with a unique experience. This research examines the effects of personalization on the amount of sampling of (1) personalized and (2) stock items. Two theories, Elaboration Likelihood Model (ELM) and Consumer Search Theory (CST), provide the basis for four hypotheses about these extended indicators. The two theories differ in theoretical level of abstraction. ELM models a user's response to an appealing item, whereas CST models a user's overall search strategy. They complement each other, but sometimes lead to competing hypotheses. This research conducts an online field experiment to examine these predictions and provide empirical evidence to validate the proposed hypotheses. Theoretically, our research extends personalization literature by providing a more complete picture of the effects of personalization on users' sampling behavior. Practically, our research reveals how effective personalization influences various users' sampling in return visits. This provides insights for online merchants who plan to invest in personalization technologies.

Original languageAmerican English
Title of host publicationECIS 2014 Proceedings - 22nd European Conference on Information Systems
PublisherAssociation for Information Systems
ISBN (Print)9780991556700
StatePublished - 2014
Event22nd European Conference on Information Systems, ECIS 2014 - Tel Aviv, Israel
Duration: 9 Jun 201411 Jun 2014

Publication series

NameECIS 2014 Proceedings - 22nd European Conference on Information Systems

Conference

Conference22nd European Conference on Information Systems, ECIS 2014
Country/TerritoryIsrael
CityTel Aviv
Period9/06/1411/06/14

Keywords

  • Clicks
  • Recommendations
  • Sampling
  • Web personalization

All Science Journal Classification (ASJC) codes

  • Information Systems

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