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Explaining the differing effects of corporate reputation across nations: a multilevel analysis

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Abstract

Although multinational corporations increasingly use their reputation as an important differentiation criterion, little is known about the varying effects of corporate reputation in an international context. In this study, the effects of corporate reputation across nations, particularly the moderating role of important institutional country differences, are analyzed. To provide insight into these issues, the authors refer to hierarchical data on 13,665 consumer evaluations of a multinational corporation in 40 countries. The results indicate a strong link between corporate reputation and consumers’ loyalty, but this relationship is reinforced or diminished by cultural, economic, or knowledge differences between countries. These moderators represent important factors when managing corporate reputations across nations.

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Notes

  1. Although this theorizing emphasizes a smaller set of institutional dimensions than the theory of business systems, the underlying logic is also one of institutional variations that produce larger differences between countries (Berry et al. 2010, p. 1463).

  2. Because distances from a focal country are not the focus of this study, geographic distance and administrative distance were not observed (Berry et al. 2010, p. 1465). The financial dimension (e.g., stock market capitalization) was not observed because theoretical arguments for consumer behavior are not obvious.

  3. Schwartz (1994, 1999) distinguishes seven value types: embeddedness, intellectual autonomy, affective autonomy, hierarchy, egalitarianism, mastery, and harmony. Societies that score high on one value type in a dimension (e.g., high mastery) are known to have lower value scores on the opposite value type in the same dimension (e.g., low harmony) and vice versa.

  4. A robustness check was conducted by estimating the models without the replaced countries. The results remained substantively the same.

  5. Effect sizes (ES) were computed as ES = (2*b*SD predictor )/SD outcome, where b is the unstandardized regression coefficient, SD predictor is the predictors’ standard deviation and SD outcome is the standard deviation of the outcome variable (Marsh et al. 2009). This effect size is comparable to Cohen’s d (Cohen 2013).

  6. The number of patents in a country as a known indicator of the ability of a country to create knowledge was not analyzed because of weak theoretical reasoning for its effects on the CR–loyalty link. However, testing of the moderator patents per 1 million population (provided by the WIPO IP Statistics Data Center) show non-significant results (b = .076; p > .05).

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Acknowledgments

We wish to thank Professor Shalom H. Schwartz, Hebrow University of Jerusalem, Israel, for his helpful comments on culture and for providing the most recent cultural data, and Dr. Tassilo Schuster, Friedrich-Alexander University of Erlangen-Nürnberg, Germany, for his helpful comments. We thank three anonymous reviewers for their very constructive comments which have essentially helped us to develop this research further. Finally we thank Professor G. Tomas M. Hult for the possibility to revise and resubmit the manuscript.

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  1. University of Trier, Universitaetsring 15, 54286, Trier, Germany

    Bernhard Swoboda & Cathrin Puchert

  2. University of Fribourg, Boulevard de Pèrolles 90, 1700, Fribourg, Switzerland

    Dirk Morschett

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Swoboda, B., Puchert, C. & Morschett, D. Explaining the differing effects of corporate reputation across nations: a multilevel analysis. J. of the Acad. Mark. Sci. 44, 454–473 (2016). https://doi.org/10.1007/s11747-015-0457-2

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