Social network governance and social sustainability-related knowledge acquisition: the contingent role of network structure

Abstract

Purpose: This study aims to understand how firms in developing economies acquire knowledge about social sustainability by leveraging the social capital embedded in firms' social network, through optimally governing relationships with network members. The study proposes that relational and contractual governance mechanisms interact with various structural facets of the network, resulting in varying degrees of social sustainability related knowledge acquisition. Design/methodology/approach: Primary data collected with a multiple respondent survey design from 204 manufacturing firms located in major industrial cities in Pakistan were used. Confirmatory factor analysis (CFA) followed by hierarchical regression analysis is used to test the hypotheses. Findings: The study finds that both relational and contractual governance mechanisms are positively related to a firm’s social sustainability-related knowledge acquisition, but their effectiveness is impacted by the structural facets of the network. Network size positively moderates the relationship between relational governance and social sustainability related knowledge acquisition, whereas both network range and strength of ties negatively moderate the relationship between contractual governance and social sustainability related knowledge acquisition. Practical implications: Practitioners with resource-constrained firms should interact with their social network to leverage the knowledge and resources embedded within. The findings prescribe optimal governance strategies for different combinations of network structure variables to gain maximum knowledge about social sustainability. Originality/value: The literature lacks information on the effect of network structure on the relationships between social network governance and social sustainability-related knowledge acquisition for resource-constrained firms in the developing economy context, making this study’s contributions unique.