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

The quality of user experiences for mobile recommendation systems: an end-user perspective

Woon Kian Chong (SP Jain School of Global Management, Singapore, Singapore)
Zhuang Ma (International Business School, Chongqing Technology and Business University, Chongqing, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 16 March 2021

Issue publication date: 30 April 2021

434

Abstract

Purpose

This paper attempts to identify key factors (i.e., personalization, privacy awareness and social norms) that affect user experiences (UXs) of mobile recommendation systems according to the user involvement theory (push-based and pull-based) and their relationships.

Design/methodology/approach

The study is based on an online survey with students from an international business school located in southwestern China. The sample population for the study included randomly selected 600 university students who are active mobile phone users. A total of 470 questionnaires were returned; 456 were valid (14 were invalid due to the incompleteness of their responses), providing a response rate of 65%.

Findings

Social norms have the largest impact on user experience quality, followed by personalization and privacy awareness. User involvement in mobile recommendation systems has mediating effects on the above relationships, with larger effects on pull-based systems than on push-based systems.

Originality/value

This study provides an integrated framework for researchers to measure the effects of social, personal and risk factors on the quality of user experience. The results enrich the literature on user involvement, mobile recommendation systems and UX. The findings provide significant implications for both retailers and developers of mobile recommendation systems.

Keywords

Citation

Chong, W.K. and Ma, Z. (2021), "The quality of user experiences for mobile recommendation systems: an end-user perspective", Industrial Management & Data Systems, Vol. 121 No. 5, pp. 1063-1081. https://doi.org/10.1108/IMDS-07-2020-0389

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

Related articles