Article: Collaborative filtering: theoretical positions and a research agenda in marketing Journal: International Journal of Technology Management (IJTM) 2004 Vol.28 No.1 pp.31 - 45 Abstract: The internet offers many choices of products, services and content. But the multitude of choices has made it more difficult for customers to find quickly what they are looking for. Collaborative Filtering (CF), or recommender system based-CF, is a methodology designed to perform such a recommendation task. These systems allow users to use expressed preferences of thousands of other people to find the product they desire, based on the level of similarity between tastes. The concept has emerged from convergent research on search browsers, intelligent agents and data mining, and it permits to escape the difficult question of ||why|| consumers prefer a particular product or brand. Furthermore, CF is open for the end-user and allows customers to discover things within an information environment that they probably never would have discovered otherwise. On a more practical perspective, CF through the internet allows us to focus exclusively on the similarity of preferences without ||social contamination||: the consumer obtains recommendations to purchase a given product or brand on the basis of his or her own past preferences and on the basis of the preferences of a large group of anonymous consumers. In this paper, we will review the current state of research in consumer behaviour that provides the theoretical foundations underlying collaborative filtering. Then we will propose a research agenda in marketing keeping in mind the perspective of users i.e. consumers or marketers. Inderscience Publishers - linking academia, business and industry through research

Title: Collaborative filtering: theoretical positions and a research agenda in marketing

Authors: Richard Vezina, Dorin Militaru

Addresses: Department of Marketing, Faculte des Sciences de l'Administration, Universite Laval, Quebec, (Quebec) G1K 7P4, Canada. ' Groupe de Recherche sur le Risque, l'Information et la Decision (GRID), 61, Avenue du President Wilson, 94235 Cachan Cedex, France

Abstract: The internet offers many choices of products, services and content. But the multitude of choices has made it more difficult for customers to find quickly what they are looking for. Collaborative Filtering (CF), or recommender system based-CF, is a methodology designed to perform such a recommendation task. These systems allow users to use expressed preferences of thousands of other people to find the product they desire, based on the level of similarity between tastes. The concept has emerged from convergent research on search browsers, intelligent agents and data mining, and it permits to escape the difficult question of ||why|| consumers prefer a particular product or brand. Furthermore, CF is open for the end-user and allows customers to discover things within an information environment that they probably never would have discovered otherwise. On a more practical perspective, CF through the internet allows us to focus exclusively on the similarity of preferences without ||social contamination||: the consumer obtains recommendations to purchase a given product or brand on the basis of his or her own past preferences and on the basis of the preferences of a large group of anonymous consumers. In this paper, we will review the current state of research in consumer behaviour that provides the theoretical foundations underlying collaborative filtering. Then we will propose a research agenda in marketing keeping in mind the perspective of users i.e. consumers or marketers.

Keywords: electronic commerce; e-commerce; collaborative filtering; recommender systems; marketing; experimentation; consumer preferences.

DOI: 10.1504/IJTM.2004.005051

International Journal of Technology Management, 2004 Vol.28 No.1, pp.31 - 45

Published online: 24 Aug 2004 *

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Title: Collaborative filtering: theoretical positions and a research agenda in marketing

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