Exploring Explanation Effects on Consumers’ Trust in Online Recommender Agents

Jingjing Zhang, Shawn P. Curley

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This paper explores how explanations within an online recommender agent (RA) affect consumers’ trust in the RA and their willingness to adopt its recommendations. The paper proposes a theoretical research model which employs a multidimensional notion of trust and considers the effects of varying two features of the RA: explanation availability, i.e., providing, or not, an explanation of the underlying reasoning process of an RA; and explanation mode, i.e., using graphs or text as the means of providing explanations. In addition, we investigate the impact of a consumer’s perceived level of personalization of the RA as a measured variable. Two dimensions of trust—trust in integrity and trust in competence—along with intention to accept the recommendations serve as the dependent variables within the model. A within-subject experiment is conducted with four RAs. Empirical data provide evidence that explanation availability, explanation mode, and perceived personalization all have significant influence on consumers’ trust beliefs in an RA and willingness to adopt its recommendations. Effects of both the availability and mode of explanations on consumers’ trust beliefs are found to be mediated by consumers’ perceived personalization of the RA that, in turn, mediate the effects on intention to use.

Original languageEnglish (US)
Pages (from-to)421-432
Number of pages12
JournalInternational journal of human-computer interaction
Volume34
Issue number5
DOIs
StatePublished - May 4 2018

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