Sylvain Senecal and Jacques Nantel

Among all possible advantages offered by electronic commerce to retailers, the capacity to offer consumers a flexible and personalized relationship is probably one of the most important (Wind and Rangaswamy 2001). While there are several ways to personalize an online relationship, the capacity for an online retailer to make recommendations is certainly amongst the most promising (The e-tailing Group, 2003). Online, recommendation sources range from traditional sources such as other consumers (e.g., testimonies of customers on retail websites such as Amazon.com) to personalized recommendations provided by recommender systems (West et al. 1999).

The main objective of this study was to investigate and compare the relative influence of online recommendation sources on consumers’ product choices. A 3 (websites: retailer, third party commercially linked to other retailers, independent third party) X 4 (recommendation source: recommender system, human experts, other consumers; or no recommendation source) X 2 (product types: search or experience) online experiment was conducted with 487 subjects.

Results strongly suggest that consumers are influenced in their online product choices by online recommendations. In fact, products were selected twice as often if they were recommended. However, all online recommendation sources were not equally influential. The recommendation source “recommender system” was found to be the most influential recommendation source even if it was perceived as possessing less expertise than human experts and as being less trustworthy than other consumers. In addition, recommendations for the experience product were significantly more influential than recommendations for the search product. The type of website on which recommendation sources were used did not affect their perceived trustworthiness and did not influence consumers’ propensity to follow the product recommendation.

This paper’s main theoretical implication is related to the influence of recommender systems on consumers’ online choices. Results show that this type of information source indeed influences consumers’ online product choices, and that it is more influential than conventional recommendation sources. Thus, this study contributes to an emergent consumer research area, namely the use and influence of impersonal information sources providing personalized information (e.g., recommender systems and intelligent agents) on consumers’ decision-making processes.

This paper also has implications for marketers. First, results show that online recommendation sources influence consumers’ online choices. Thus, it seems that many consumers do not only consult product recommendations when shopping online, they also follow these recommendations. Second, this influence is moderated by the type of product and the type of recommendation source, but it is not moderated by the type of website. Based on our results, marketers of experience products should benefit the most from providing recommendations to online consumers, especially if the source is providing personalized recommendations. Results also suggest that a specific recommendation source will be as effective on a retailer website (e.g., Amazon) as it will be on an independent third party website such as Consumer Reports. It seems that consumers focus much more on the recommendation source itself than on the type of website on which the recommendation source is used.