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Is corporate social responsibility a motivator or hygiene factor? Insights into its bivalent nature

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Abstract

This study fills extant gaps in the marketing literature by further probing the multi-faceted impact of a company’s corporate social responsibility (CSR) practices on customer relationships, and it marks the first systematic marketing study devoted to investigating CSR as a bivalent mechanism that encompasses both motivation and hygiene properties. Via a field study utilizing three separate samples of customer survey data (combined n = 2,408) collected over three seasons from a professional basketball team, results support a moderated mediation model wherein CSR is shown to be a necessary and sufficient mechanism for stronger customer relationships. While business leaders typically support the notion of CSR for largely altruistic reasons, our research brings new understanding as to how CSR operates in customers’ minds and suggests that CSR is not only something that a company should engage in based on principled grounds but also something that a company must practice for strategic reasons as their customers demand it and place relational value on it.

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Acknowledgments

This article is dedicated to the memory of our co-author, Chris Manolis. Your contribution to this article was invaluable, and you are greatly missed by so many including those of us in the marketing community. In addition, we would like to thank Tomas Hult and the four anonymous JAMS reviewers who guided us through this process. We also would like to thank Mike Dorsch and Vishal Kashyap for their constructive feedback on earlier versions of this manuscript.

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Authors and Affiliations

  1. Williams College of Business, Department of Marketing, Xavier University, 316 Smith Hall 1002 Francis Xavier Way, Cincinnati, OH, 45207-1214, USA

    Russell Lacey

  2. Department of Marketing and Logistics, University of New Orleans, Kirschman Hall, Room 343F 2000 Lakeshore Drive, New Orleans, LA, 70148, USA

    Pamela A. Kennett-Hensel

  3. Williams College of Business, Department of Marketing, Xavier University, 306 Smith Hall 1002 Francis Xavier Way, Cincinnati, OH, 45207-1214, USA

    Chris Manolis

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  1. Russell Lacey
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Correspondence to Russell Lacey.

Appendices

Appendix 1

Table 5 Correlations, means, and standard deviations
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Appendix 2

Tests of invariance

The first test of invariance was a test of form to determine whether the measurement model for the three samples has the same number of latent variables (factors) with the same indicators and the same specification of fixed and free parameters. Although we find a significant χ 2 (398) = 3,629.14 (p < 0.001) when comparing samples one and two on model form, the result is not surprising given the results of the single-group analyses. The relatively high values for the fit indices (e.g., CFI = 0.91, IFI = 0.91, SRMR = 0.056), however, lead to the conclusion that the model form holds similarly for samples one and two. We obtain similar results when comparing samples one and three (χ 2 (398) = 4,017.37, CFI = 0.91, IFI = 0.91, SRMR = 0.054) and two and three (χ 2 (398) = 3,287.22, CFI = 0.91, IFI = 0.91, SRMR = 0.057). Having received support for this initial test of invariance, we next test whether the factor coefficients are equal across the three groups/samples.

The second invariance test restricts the regression of the items on the factors (i.e., slopes relating the measures to the latent variables) to be equal across the samples. First we compare samples one and two, and although the χ 2 (414) = 3,723.06 is statistically significant (p < 0.001), the relatively high goodness of fit measures accompanying this test (CFI = 0.90, IFI = 0.90, SRMR = 0.055) provide evidence that the factor structure is invariant across these two groups. A χ 2 difference (Δχ 2) between this multi-sample invariance model and the initial model (corresponding to the same two samples) is χ 2 (16) =93.92 (p < 0.001). This suggests caution in accepting the postulate that the differences in factor coefficients across samples one and two are similar. The individual parameter estimates for the two samples (models), however, indicate that the two sets of factor coefficients are actually highly similar. The average difference in standardized factor coefficients across samples one and two is 0.017 with the single largest difference equal to 0.036. This suggests that the Δχ 2 test is very sensitive (Hair et al. 2006).

Conducting the same invariance test (and utilizing the same procedure) with samples one versus three, we get similar results: χ 2 (414)=4,067.93 (p < 0.001), CFI = 0.91, IFI = 0.91, SRMR = 0.053; Δχ 2 (16) = 50.56 (p < 0.001). Although the multi-sample test itself suggests similarity across samples one and three in terms of the regressions of the items on the factors, the Δχ 2 test indicates some caution as to whether these loadings are indeed similar. As before, we compare the actual loadings across samples one and three and find the average difference to be 0.012 with a maximum difference of 0.026. Again, the Δχ 2 test appears to be particularly sensitive (Hair et al. 2006). In comparing samples two and three in terms of factor loadings we get the following results: χ 2 (414) = 3,315.01, CFI = 0.91, IFI = 0.91, SRMR = 0.052; Δχ 2 (16) = 27.79 (p < 0.05). Again we find evidence of invariance (the multi-sample CFA findings, etc.) interspersed with caution in accepting this position (the Δχ 2 test). When comparing actual factor loadings across these two samples (samples two and three), however, we find the average difference to be 0.03, which once more attests to the sensitivity inherent in the Δχ 2 test (Hair et al. 2006).

The final test of invariance adds the restriction that the covariance matrix for the five empirically derived factors (perceived CSR, CSR-relationship motivator, CSR-relationship hygiene factor, relationship quality, and WOM) is invariant across the three samples. This implies that the factor covariances (or interfactor correlations) are equal in the samples. In comparing samples one and two, this test results in a χ 2 (424) = 3,742.66 (p < 0.001) estimate, with fit indices that are still reasonably and relatively high (CFI & IFI = 0.90, SRMR = 0.057), thus providing continued support for the invariance premise. An examination of interfactor correlations reveals similar values across these samples (see Appendix 1) even though the Δχ 2 of this multi-sample model and the one immediately preceding it (comparing the same two samples)—19.6 with 10° of freedom—is significant (p < 0.05). In the end, there appears to be ample evidence to suggest that the factor intercorrelations are nearly equivalent across these two independent groups or samples (samples one and two).

Comparing samples one and three in terms of the similarity of covariance matrices test of invariance reveals the following: χ 2 (424) = 4,076.68 (p < 0.001), CFI = 0.91, IFI = 0.91, and SRMR = 0.056. In this case, the Δχ 2 of this multi-sample model and the one immediately preceding it (comparing the same two samples) is not significant: Δχ 2 (10) = 8.75 (p > 0.05). By all accounts, the covariance matrices for samples one and three are statistically identical. In the final test of invariance, we compare samples two and three in terms of covariance matrices and get the following results: χ 2 (424) = 3,324.24 (p < 0.001), CFI = 0.91, IFI = 91, and SRMR = 0.054. And, the Δχ 2 of this multi-sample model and the one immediately preceding it (comparing samples two and three) is again not significant (Δχ 2 (10) = 9.23, p > 0.05), thus providing strong support for this test of invariance. Overall, the multi-sample analyses corroborate the consistency of the empirically derived measurement models across the three independent samples.

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Lacey, R., Kennett-Hensel, P.A. & Manolis, C. Is corporate social responsibility a motivator or hygiene factor? Insights into its bivalent nature. J. of the Acad. Mark. Sci. 43, 315–332 (2015). https://doi.org/10.1007/s11747-014-0390-9

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