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Buffering or Aggravating Effect? Examining the Effects of Prior Corporate Social Responsibility on Corporate Social Irresponsibility

Author

Listed:
  • Zhe Zhang

    (Xi’an Jiaotong University)

  • Mijia Gong

    (Xi’an Jiaotong University)

  • Shanshan Zhang

    (Xi’an Jiaotong University)

  • Ming Jia

    (Northwestern Polytechnical University)

Abstract

Prior studies on stakeholders’ responses to firms with high prior corporate social responsibility (CSR) engaging in corporate social irresponsibility (CSIR) show inconsistent results. To explore this inconsistency, we focus on the intentionality of CSIR and draw upon cognitive dissonance theory to examine how transgressional CSIR and accidental CSIR differently influence investors’ responses to firms with high prior CSR through both emotional (e.g., anger) and cognitive (e.g., moral judgment) processes. An experimental study using a facial expression analysis technology— FaceReader 5.0 (Study 1) and a scenario experiment (Study 2), reveal that high prior CSR is a double-edged sword. Specifically, high prior CSR elicits an aggravating effect on investor responses (more anger, more negative moral judgment, and more negative effects on investment) in light of transgressional CSIR, but it has a buffering effect on investor responses (less anger, less negative moral judgment, and less negative effects on investment) in light of accidental CSIR. Moreover, we find that when prior CSR and CSIR are in the same (vs. different) domain, the aggravating effect of transgressional CSIR is strengthened, but the buffering effect of accidental CSIR is weakened. Our findings provide important theoretical and practical insights into the effect of prior CSR on investor responses in cases of different CSIR.

Suggested Citation

  • Zhe Zhang & Mijia Gong & Shanshan Zhang & Ming Jia, 2023. "Buffering or Aggravating Effect? Examining the Effects of Prior Corporate Social Responsibility on Corporate Social Irresponsibility," Journal of Business Ethics, Springer, vol. 183(1), pages 147-163, February.
    • Handle: RePEc:kap:jbuset:v:183:y:2023:i:1:d:10.1007_s10551-022-05036-x
    DOI: 10.1007/s10551-022-05036-x
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    Cited by:

    1. Landmann, Elisa, 2023. "I can see how you feel—Methodological considerations and handling of Noldus's FaceReader software for emotion measurement," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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