The Role of Product Recommendation Agents in Collaborative Online Shopping
نویسندگان
چکیده
Over the last decade, a wealth of research has examined the potential benefits of product recommendation agents (PRAs) for improving outcomes for e-commerce consumers and vendors. To date, however, this research has largely overlooked the fundamentally social nature of shopping. In particular, people often shop collaboratively (together) and for hedonic reasons (for enjoyment), but researchers have focused almost exclusively on isolated individuals using a PRA for utilitarian reasons. This study aims to extend past research by examining the effect of PRAs on both utilitarian and hedonic value in the context of collaborative online shopping (COS). Because communication is an inherent part of any collaborative activity, our model examines both the indirect effect of PRA use on shopping value through its effect on communication among shoppers, and the direct effect of PRA use on shopping value. We propose a moderated mediation model that predicts that: task-oriented communication (TOC) positively affects utilitarian shopping value, and social-emotional communication (SEC) positively affects hedonic shopping value; (2) PRA use reduces the amount of SECs, (3) PRA use reduces the importance of TOC; and (4) PRA use directly increases utilitarian value and directly reduces hedonic value. We describe an experiment where we are planning to test the proposed model, and its intended contributions for theory and practice.
منابع مشابه
Assessing the impact of recommender agents on on-line consumer unplanned purchase behavior
Recommendation agents (RAs) have been used by many Internet businesses such as Amazon and Netflix. However, few authors have studied how consumer behavior is affected by those that make suggestions to online consumers based on their recent shopping behavior. Fewer still have examined the role that RAs play in influencing impulse purchasing decisions online. Our study developed a theoretical mod...
متن کاملApplication of Web usage mining and product taxonomy to collaborative recommendations in e-commerce
The rapid growth of e-commerce has caused product overload where customers on the Web are no longer able to effectively choose the products they are exposed to. To overcome the product overload of online shoppers, a variety of recommendation methods have been developed. Collaborative filtering (CF) is the most successful recommendation method, but its widespread use has exposed some well-known ...
متن کاملBarriers and Crucial factors affecting Iranian consumer mind during online shopping
E-commerce has made life simple and innovative of individuals and groups consumer Behavior in online shopping is different from the physical market where he has access to see the product. The purpose of the research was to study the consumer behavior in online shopping of electronics especially in Iran. Primary data was collected through the questionnaire survey and by emails from personal cont...
متن کاملA Collaborative Recommender System: Lexicographic Consensus and Web Usage Mining Approach
Collaborative filtering (CF) is one of the most successful and widely used methods of automated product recommendation domain [1, 2, 3]. However, cardinal scale generally used for representing the preference intensity is also ineffective owing to its increasing estimation errors. In this paper, we propose a new CF-based recommendation methodology that constructs an ordinal scale-based customer ...
متن کاملUtilizing popularity characteristics for product recommendation in internet shopping malls
Abstract This chat presents a novel approach to automated product recommendation that uses the popularity characteristics of products. Although they play a significant role in the consumer purchasing process, there has been little attention paid to the use of popularity in recommendation research so far. In order to use popularity features, this paper develops a threedimensional model of popula...
متن کامل