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Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses

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  • Ashish Kumar Jha

    (Trinity College Dublin)

  • Nishant Kumar Verma

    (Indian Institute of Management Bangalore)

Abstract

Social media communication, and its impact on individuals and firms, is becoming increasingly important in today’s age. Firms are utilizing social media channels for communicating their sustainability-related initiatives. The role of social media as a mode for sustainability-related communication by firms has not been widely analyzed in the extant information systems literature. Given the increasingly important role of social media for information diffusion as well as increasing awareness for sustainability practices, this is a critical area of research. In this paper, we use an analytic model to theorize, coupled with empirical analysis to test the impact of firms’ sustainability practices. We have validated our proposed hypotheses using an empirical model based on panel data of firms’ sustainability performance and their Twitter communication over a 3-year period. Through our unique mixed-method study, we add additional methodological rigour to extant social media-based research in the information systems domain. Our research has significant theoretical and managerial significance as we identify how firms utilize social media for sustainability-related communication and its corresponding impact on customer response. Our research provides actionable insights for policymakers, firms as well as investors and consumers on understanding and managing sustainability-related communications on social media.

Suggested Citation

  • Ashish Kumar Jha & Nishant Kumar Verma, 2023. "Social Media Sustainability Communication: An Analysis of Firm Behaviour and Stakeholder Responses," Information Systems Frontiers, Springer, vol. 25(2), pages 723-742, April.
    • Handle: RePEc:spr:infosf:v:25:y:2023:i:2:d:10.1007_s10796-022-10257-6
    DOI: 10.1007/s10796-022-10257-6
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    2. Yasemin Lheureux, 2024. "Predictive insights: leveraging Twitter sentiments and machine learning for environmental, social and governance controversy prediction," Journal of Computational Social Science, Springer, vol. 7(1), pages 23-44, April.

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