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Information Systems and e-Business Management

, Volume 13, Issue 4, pp 769–799 | Cite as

Understanding the moderating roles of types of recommender systems and products on customer behavioral intention to use recommender systems

  • Yen-Yao Wang
  • Andy Luse
  • Anthony M. Townsend
  • Brian E. Mennecke
Original Article

Abstract

This study investigates how consumers assess the quality of two types of recommender systems-collaborative filtering and content-based—in the context of e-commerce by using a modified version of the unified theory of acceptance and use of technology (UTAUT) model. Specifically, the concept of trust in the technological artifact is adapted to examine the intention to use recommender systems. Additionally, this study also considers hedonic and utilitarian product characteristics with the goal of presenting a comprehensive picture on recommender systems literature. This study utilized a 2 × 2 crossover within-subjects experimental design involving a total of 80 participants, who all evaluated each recommender system. The results suggest that the type of recommender system significantly moderates many relationships of the determinants of customer behavioral intent on behavioral intention to use recommender systems. Surprisingly, the type of product does not moderate any relationship on behavioral intention. This study holds importance in explaining the factors contributing to the use of recommender systems and understanding the relative influence of the two types of recommender systems on customer behavioral intention to use recommender systems. The finding also sheds light for designers on how to provide more effective recommender systems.

Keywords

Recommender systems UTAUT Trust Hedonic product Utilitarian product 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Yen-Yao Wang
    • 1
  • Andy Luse
    • 2
  • Anthony M. Townsend
    • 3
  • Brian E. Mennecke
    • 3
  1. 1.N204 North Business Complex, Department of Accounting and Information SystemsMichigan State UniversityEast LansingUSA
  2. 2.Department of Management Science and Information SystemsOklahoma State UniversityStillwaterUSA
  3. 3.Department of Supply Chain and Information SystemsIowa State UniversityAmesUSA

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