When Electronic Recommendation Agents Backfire: Negative Effects on Choice Satisfaction, Attitudes, and Purchase Intentions

Joseph Lajos, Amitava Chattopadhyay and Kishore Sengupta
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Joseph Lajos: GREGH - Groupement de Recherche et d'Etudes en Gestion à HEC - HEC Paris - Ecole des Hautes Etudes Commerciales - CNRS - Centre National de la Recherche Scientifique
Amitava Chattopadhyay: INSEAD - Institut Européen d'administration des Affaires
Kishore Sengupta: INSEAD - Institut Européen d'administration des Affaires

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Abstract: The increasing breadth and complexity of information about product features available in the marketplace, especially online, has increased the difficulty of many purchase decisions. In order to assist consumers with these decisions, many websites provide electronic recommendation agents that ask users questions about individual factors and their preferences for product attributes and then rate and rank order the available products on the basis of their responses. In an era in which consumers often feel overwhelmed by the complexity of choice, previous research has hailed electronic recommendation agents as coming to the rescue by offering a quick and efficient means for consumers to form their consideration sets. However, in this article we report the results of an experiment in which use of an electronic recommendation agent negatively impacted participants' choice satisfaction, attitudes, and purchase intentions over a period of between one and two weeks. The data support our hypothesis that use of an electronic recommendation agent leads consumers to overweight utilitarian product attributes and underweight peripheral and trivial hedonic attributes in choice.

Keywords: consumer decision; making; feature fatigue; information; aids; behavior; impact; environments; marketplaces; incentives; knowledge (search for similar items in EconPapers)
Date: 2009
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Published in Advances in Consumer Research, 2009, Vol.36, pp.845-847

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00493183

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