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CSR marketing through social media and contextual effects on stakeholder engagement: a multinational cross-industry analysis

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Abstract

Multinational Enterprises (MNEs) use social media to reach a global audience. Simultaneously, Corporate Social Responsibility (CSR) has become an important feature of MNEs’ communications with stakeholders via social media. It is, therefore, important to understand the country and industry level differences in how stakeholders engage with CSR communications of MNEs via social media. We examine this across four countries and three industries by focusing on stakeholders’ engagement with CSR (vs. non-CSR) posts on Twitter. We find significant differences across industries within countries for three separate aspects of behavioural engagement (likes, retweets and replies). In addition, CSR posts have a positive effect on stakeholder engagement based on likes and retweets at the industry-within-country level. Moreover, CSR posts are not fully effective in developed countries. Hence, achieving legitimacy through CSR on social media is a complex challenge, requiring a nuanced understanding of stakeholder reactions based on specific industry and country contexts.

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Authors and Affiliations

  1. Graduate School of Management and Economics, Sharif University of Technology, Tehran, Iran

    Arash Khalili Nasr & Ashkan Salehi Sadaghiani

  2. Sussex Business School, University of Sussex, Brighton, UK

    Mona Rashidirad

  3. Queen Mary, University of London, London, UK

    Vignesh Yoganathan

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  1. Arash Khalili Nasr
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  2. Mona Rashidirad
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Correspondence to Arash Khalili Nasr.

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Appendix: Stata® codes for the generalised structural equation model analysis

Appendix: Stata® codes for the generalised structural equation model analysis

Variance components models

gsem (M1[country] -> NETL NETT NETR), family(gaussian) link(identity) covstruct(_lexogenous, diagonal) difficult latent(M1 ) nocapslatent

gsem (M1[country] M2[country > industry] -> NETL NETT NETR), family(gaussian) link(identity) covstruct(_lexogenous, diagonal) difficult latent(M1 M2 ) nocapslatent

Random intercept model with Level 1 predictor

gsem (i.pos_ty M1[country] M2[country > industry] -> NETL NETT NETR), family(gaussian) link(identity) covstruct(_lexogenous, diagonal) difficult latent(M1 M2 ) nocapslatent

Random intercept model with Level 1 and Level 2 predictor

gsem ( pos_CxI_mean i.pos_ty M1[country] M2[country > industry] -> NETL NETT NETR), family(gaussian) link(identity) covstruct(_lexogenous, diagonal) difficult latent(M1 M2 ) nocapslatent

Random slope model

gsem (pos_ty pos_CxI_mean M1[country] M2[country > industry] M3[country > industry]#pos_ty -> NETL NETT NETR), family(gaussian) link(identity) covstruct(_lexogenous, diagonal) variance(M1[country]@1 M2[country > industry]@1 M3[country > industry]@1) difficult latent(M1 M2 M3) nocapslatent

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Nasr, A.K., Rashidirad, M., Yoganathan, V. et al. CSR marketing through social media and contextual effects on stakeholder engagement: a multinational cross-industry analysis. Inf Syst Front 26, 987–1004 (2024). https://doi.org/10.1007/s10796-022-10273-6

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