Factors Influencing the Acceptance of Self-Service Technologies:A Meta-Analysis

Blut, Markus, Wang, Cheng and Schoefer, Klaus (2016). Factors Influencing the Acceptance of Self-Service Technologies:A Meta-Analysis. Journal of Service Research, 19 (4), pp. 396-416.


To facilitate efficient and effective service delivery, firms are introducing self-service technologies (SSTs) at an increasing pace. This article presents a meta-analysis of the factors influencing customer acceptance of SSTs. The authors develop a comprehensive causal framework that integrates constructs and relationships from different technology acceptance theories, and they use the framework to guide their meta-analysis of findings consolidated from 96 previous empirical articles (representing 117 independent customer samples with a cumulative sample size of 103,729 respondents). The meta-analysis reveals the following key insights: (1) SST usage is influenced in a complex fashion by numerous predictors that should be examined jointly; (2) ease of use and usefulness are key mediators, and studies ignoring them may underestimate the importance of some predictors; (3) several determinants of usefulness impact ease of use, and vice versa, thereby revealing crossover effects not previously revealed; and (4) the links leading up to SST acceptance in the proposed framework are moderated by SST type (transaction/self-help, kiosk/Internet, public/private, hedonic/utilitarian) and country culture (power distance, individualism, masculinity, uncertainty avoidance). Results from the meta-analysis offer managerial guidance for effective implementation of SSTs and provide directions for further research to augment current knowledge of SST acceptance.

Publication DOI: https://doi.org/10.1177/1094670516662352
Divisions: Aston Business School
Aston Business School > Marketing & Strategy
Additional Information: Factors Influencing the Acceptance of Self-Service Technologies: A Meta-Analysis Blut, M., Wang, C. & Schoefer, K. 1 Nov 2016 In : Journal of Service Research. 19, 4, p. 396-416 21 p. Copyright © 2016 (The Authors). Reprinted by permission of SAGE Publications.
Uncontrolled Keywords: meta-analysis,self-service technology,technology acceptance,Information Systems,Sociology and Political Science,Organizational Behavior and Human Resource Management
Full Text Link: http://eprint.n ... 545E0056A79.pdf
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
Published Date: 2016-11-01
Authors: Blut, Markus ( 0000-0003-0436-6846)
Wang, Cheng
Schoefer, Klaus



Version: Accepted Version

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