To read this content please select one of the options below:

Consumer acceptance of social recommender systems in India

Preeti Virdi (Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Mumbai, India)
Arti D. Kalro (Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Mumbai, India)
Dinesh Sharma (Shailesh J. Mehta School of Management, Indian Institute of Technology Bombay, Mumbai, India)

Online Information Review

ISSN: 1468-4527

Article publication date: 3 April 2020

Issue publication date: 10 June 2020




Collaborative filtering based recommender systems (CF–RS) are widely used to recommend products based on consumers' preference similarity. Recommendations by CF–RS merely provide suggestions as “people who bought this also bought this” while, consumers are unaware about the source of these recommendations. By amalgamating CF–RS with consumers' social network information, e-commerce sites can offer recommendation from social networks of consumers. These social network embedded systems are known as social recommender systems (SRS). The extant literature has researched on the algorithms and implementation of these systems; however, SRS have not been understood from consumers' psychological perspective. This study aims to qualitatively explore consumers' motives to accept SRS in e-commerce websites.


This qualitative study is based on in-depth interviews of frequent online shoppers. SRS are currently not very widespread in the Indian e-commerce space; hence, a vignette was shown to respondents before they responded to the questions. Inductive qualitative content analysis method was used to analyse these interviews.


Three main themes (social-gratification, self-gratification and information-gratification) emerged from the analysis. Out of these, social-gratification acts as an enabler, while self-gratification along with some elements of information-gratification act as inhibitors towards acceptance of social recommendations. Based on these gratifications, we present a conceptual model on consumer's acceptance of social recommendations.


This study is an initial attempt to qualitatively understand consumers' attitudes and acceptance of social recommendations on e-commerce websites, which in itself is a fairly new phenomenon.



The authors would like to thank the editor and the anonymous reviewers for their valuable feedback. The authors are grateful to Prof. Shishir Jha and Prof. S. Bhargava for their feedback and useful comments. The authors would also like to thank the coders for their help.


Virdi, P., Kalro, A.D. and Sharma, D. (2020), "Consumer acceptance of social recommender systems in India", Online Information Review, Vol. 44 No. 3, pp. 723-744.



Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

Related articles