Customer Perceived Value: A Comprehensive Meta-analysis

Author:

Blut Markus1ORCID,Chaney Damien2,Lunardo Renaud3,Mencarelli Rémi4,Grewal Dhruv567

Affiliation:

1. Professor of Marketing, Durham University Business School, Durham University, UK

2. Professor of Marketing, EM Normandie Business School, Metis Lab, France

3. Professor of Marketing, Kedge Business School, France

4. Professor of Marketing, IAE Savoie Mont Blanc, Université de Savoie Mont Blanc, France

5. Toyota Chair of Commerce and Electronic Business and Professor of Marketing, Babson College, Babson Park, MA, USA

6. Fractional Professor of Marketing, University of Bath, UK

7. Honorary Distinguished Visiting Professor of Retailing and Marketing, Tecnológico de Monterrey, Mexico

Abstract

Customer perceived value (CPV) is a cornerstone of marketing literature. However, myriad studies have generated contradictory empirical findings. In addition, though some existing literature reviews help clarify the conceptual foundations of CPV, the literature lacks a meta-analysis of empirical evidence about the CPV model and its effects. To consolidate existing research, the current meta-analysis assesses the findings of 687 articles, involving 780 independent samples and 357,247 customers. The most integrative CPV model, which includes benefits, sacrifices, and overall value, performs best. Empirical generalizations also reveal the relative weights of various benefits and sacrifices integrated into this CPV model and causal chains between CPV and different outcomes (satisfaction, word-of-mouth, and repurchase intentions). Finally, this analysis uncovers moderating effects of multiple relational contexts: nonprofit/for-profit, public/private, contractual/non-contractual, online/offline, business-to-business/business-to-consumer, and goods/services. For scholars, this article synthesizes existing findings on CPV; for managers, the results provide suggestions for ways to increase CPV.

Publisher

SAGE Publications

Subject

Organizational Behavior and Human Resource Management,Sociology and Political Science,Information Systems

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