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What’s important for relationship management? : the mediating roles of relational trust and satisfaction for loyalty of cooperative banks’ customers
Citation Link: https://doi.org/10.15480/882.4072
Publikationstyp
Journal Article
Date Issued
2022
Sprache
English
Author(s)
TORE-DOI
Journal
Volume
10
Issue
1
Start Page
3
End Page
18
Citation
Journal of Marketing Analytics 10 (1): 3–18 (2022)
Publisher DOI
Scopus ID
Publisher
Palgrave Macmillan
Building on the corporate reputation model, this study investigates the drivers of customer-based corporate reputation. We consider two corporate reputation dimensions (i.e., the cognitive dimension competence and the affective dimension likeability, and their effects on customer satisfaction and loyalty). Adapting the model to the banking sector, we theoretically extend this model by reasoning that customer satisfaction and relational trust are mediators of the relationship between the two corporate reputation dimensions and loyalty. Studying a sample of 675 customers and members of cooperative banks in Germany, we find perceived attractiveness to be the most important driver of corporate reputation. Furthermore, we confirm a positive relationship between corporate reputation and loyalty, and a mediating effect of both satisfaction and relational trust. With our study, we give support for the proposition of customer satisfaction's as well as relational trust’s role as mediators of the relationship between corporate reputation and loyalty. With this research, we expand our knowledge on the well-known corporate reputation model, which has high relevance and important implications for marketing research and relationship management practice.
Subjects
Corporate reputation
Customer loyalty
Customer satisfaction
Mediation
Partial least squares
PLS-SEM
Relational trust
Structural equation modeling
DDC Class
330: Wirtschaft
Funding(s)
Funding Organisations
Förderverein Industrielles Management (FIM) e.V.
More Funding Information
We kindly thank the Förderverein Industrielles Management (FIM) e.V. for supporting the funding of our data collection. This research uses the statistical software SmartPLS 3 (https://www. smart pls. com). Ringle acknowledges a financial interest in SmartPLS.
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