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Journal of the Academy of Marketing Science

Erschienen in:

29.10.2019 | REVIEW PAPER

Understanding and managing customer relational benefits in services: a meta-analysis

verfasst von: Dwayne D. Gremler, Yves Van Vaerenbergh, Elisabeth C. Brüggen, Kevin P. Gwinner

Erschienen in: Journal of the Academy of Marketing Science | Ausgabe 3/2020

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Abstract

Recent meta-analyses provide clear insights into how service firms can benefit from relationship marketing, whereas investigations of customers’ relational benefits (1) are unclear about the absolute and relative strengths by which different relational benefit dimensions induce different customer responses and (2) have not simultaneously examined the various mediating processes (including perceived value, relationship quality, and switching costs) through which relational benefits reportedly affect customer loyalty. To consolidate extant research on the benefits of relationship marketing for customers, this meta-analysis integrates 1242 effect sizes drawn from 235 independent samples across 224 papers disseminated in the past two decades. The results reveal that all three relational benefits affect loyalty, though confidence benefits and social benefits have the strongest effects. Among the three identified mediation paths through which relational benefits influence customer loyalty, the sequential path through perceived value and relationship quality is the strongest. From a service research perspective, this study provides novel empirical generalizations; managerially, the findings suggest that a primary goal for service managers should be strengthening confidence and social benefits.

Vorheriger Artikel Customer satisfaction and firm performance: insights from over a quarter century of empirical research

Nächster Artikel Cross-price elasticities and their determinants: a meta-analysis and new empirical generalizations

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Several scholars use the term “relationship benefits” (e.g., Morgan and Hunt 1994; Palmatier et al. 2006; Verma et al. 2016) as a synonym for “relational benefits.” Rather than switch terms, we use “relational benefits” throughout.

Over time, additional relational benefits have emerged, including identity-related benefits (Fournier 1998), respect benefits (Chang and Chen 2007), hedonic benefits (Meyer-Waarden et al. 2013), and quality improvement benefits (Sweeney and Webb 2002). However, these additional benefits have not appeared frequently in empirical studies, so we limit our focus to confidence, social, and special treatment benefits.

The terms “confidence” and “trust” are often used interchangeably. However, confidence explicitly refers to “perceived certainty about satisfactory partner cooperation” (Das and Teng 1998, p. 492) and the belief that the partner will behave in a desired manner (Scheer 2012), so it involves expectations about the partner’s predictable behavior but does not address the underlying reasons. In contrast, “Trust is the belief that one’s partner [a service provider] can be relied upon to fulfill its future obligations and to behave in a manner that will serve the firm’s [customer’s] needs and long-term interests” (Scheer and Stern 1992, p. 134), because the partner is motivated by more than its own immediate, direct self-interest, a motive that should persist in the future. Thus, trust and confidence are not equivalent; confidence may exist, despite a lack of trust. But trust and confidence also can be related, in that trust can generate general confidence in a business partner (Scheer 2012, p. 338).

In several places herein, we refer to this sequential mediation path (relational benefits → perceived value → relationship quality → customer loyalty). Generally, if either perceived value or relationship quality is present, customers perceive them in a positive light, so these factors keep customers in relationships because they want to (cf. switching costs, often viewed in a negative light, such that they keep customers in the relationship because they have to) interact. We use “PV/RQ path” to refer to this sequential mediation path in the remainder of the text.

Over time, firms providing encounter services may learn about the positive effects of relational benefits and move toward a shared industry norm of providing such benefits, tilting the transactional–relational balance more toward a relationship-based setting. Take Starbucks as an example: Buying a cup of coffee once was clearly an encounter service, but Starbucks added relationship elements to its service (e.g., remembering the names and favorite drinks of regular customers). Over time, coffee shops largely adopted these relationship elements, moving the entire industry toward a stronger relationship focus. Still, in the short run and in line with the accessibility–diagnosticity perspective, we predict that confidence, social, and special treatment benefits have stronger relationships with customer outcomes for encounter services than for relationship services.

We are grateful to one of the reviewers for the suggestion to include these additional keywords.

We are grateful to the Associate Editor and a reviewer for their suggestion to include a dummy variable to represent changes in the relationship marketing environment. To define a reasonable time lag between the year of data collection and the year of publication, we calculated the differences between the date a paper was received and the date it was published in the May 2019 volume of Journal of the Academy of Marketing Science (average: 1.7 years), then added an extra year to account for the manuscript writing process. Therefore, we anticipate an average time lag of about three years, such that a paper published in 2009 likely reflects data collected in 2006. Our results remain stable if we use two- or four-year time lags instead.

We also coded the means and standard deviations of the three relational benefits reported in the 235 samples and recalibrated them to 0–100 scales. The average levels are 67 (SD = 16) for confidence benefits, 51 (SD = 19) for social benefits, and 49 (SD = 18) for special treatment benefits. The t-tests reveal that these average levels do not differ significantly between B2B and B2C contexts (all p > .10). The average level of confidence benefits also does not differ between encounter and relationship services (p > .10), whereas that of social benefits is significantly higher in relationship services (56) than in encounter services (48; t(77) = 2.404, p < .05). The average level of special treatment benefits is marginally significantly higher in relationship services (55) than in encounter services (47; t(77) = 1.929, p < .06). Web Appendix H provides further detail.

Although not hypothesized, the results reveal that the indirect effect from relational benefits to customer loyalty through perceived value and relationship quality (confidence: .14, p < .001; social: .11, p < .001; special treatment: .02, p < .001) is stronger than the indirect effect from relational benefits to customer loyalty through switching costs (confidence: .02, p < .001; social: .01, p < .001; special treatment: .01, p < .001). Imposing equality constraints on these indirect paths significantly worsens model fit (Δχ²(3) = 2590.71, p < .001).

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Titel: Understanding and managing customer relational benefits in services: a meta-analysis
verfasst von: Dwayne D. Gremler
Yves Van Vaerenbergh
Elisabeth C. Brüggen
Kevin P. Gwinner
Publikationsdatum: 29.10.2019
Verlag: Springer US
Erschienen in: Journal of the Academy of Marketing Science / Ausgabe 3/2020
Print ISSN: 0092-0703
Elektronische ISSN: 1552-7824
DOI: https://doi.org/10.1007/s11747-019-00701-6

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