Board caste diversity in Indian MNEs: The interplay of stakeholder norms and social embeddedness

• 成果类型: Article
• 署名作者: Garg, Suyash; Lin, Zhiang; Yang, Haibin
• 署名单位: University of Texas System; University of Texas Dallas; Chinese University of Hong Kong
• 刊物名称: JOURNAL OF INTERNATIONAL BUSINESS STUDIES
• ISSN/ISSBN: 0047-2506
• DOI: 10.1057/s41267-022-00588-6
• 发表日期: 2023
• 页码: 797-828
• 关键词: board caste diversity; social networks; institutions-based view

摘要

Although stakeholder norms originating in developed economies influence firms' board composition, including board diversity, less is known about firms in emerging economies, specifically India. In this heterogeneous institutional context, firms' strategic choices are subject to changing institutional forces and complex social structures. Bridging the institutions-based view with the network theory, this study examines Indian MNEs' strategic choices regarding an important socio-economic diversity, namely board caste diversity. Specifically, we contend that Indian firms' exposure to stakeholder norms from developed economies would increase their board caste diversity. However, such adaptations can face constraints and opportunities embedded in multiple social structures of India. Analyses of three large Indian datasets between 2010 and 2018 suggest that Indian MNEs' board caste diversity is indeed driven by their exposures to stakeholder norms from developed economies. Further, such adaptations are strengthened when firms occupy key positions - prominence (centrality) and brokerage - in a network with market-based affiliations (i.e., banks), but are weakened when firms occupy prominence (centrality) and brokerage in a network with tradition-based affiliations (i.e., family and kinship). Our findings imply that managers should be cognizant of interactions between local social structures and international exposure in organizational adaptation toward stakeholder orientation in emerging economies. Managers are also advised to assess the often divergent effects on firms' learning and adaptations from varying network affiliations.