Perceived effectiveness of recommendation agent routines: search vs. experience goods Online publication date: Sat, 30-Jul-2005
by Praveen Aggarwal, Rajiv Vaidyanathan
International Journal of Internet Marketing and Advertising (IJIMA), Vol. 2, No. 1/2, 2005
Abstract: The vast amount of information available in online shopping environments has led to the development of shopping agents that seek to assist customers in their purchase decisions. Such recommendation agents use one of two common approaches to build a recommendation: rule-based filtering agents typically ask buyers their product preferences and make a recommendation by comparing these preferences to product features; collaborative filtering agents match users with other buyers who have similar profiles and preferences, and make recommendations based on shared likes and dislikes. We examine how consumers react to these different processes to develop recommendations for both search and experience goods. Our results show that consumers evaluated recommendation agents more favourably for search goods than experience goods. Further, rule-based recommendations were preferred for search goods but not for experience goods. Implications of these results are discussed.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Internet Marketing and Advertising (IJIMA):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com