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How social enterprises gain cognitive legitimacy in the post-pandemic period? Social welfare logic and digital transformation
Industrial Management & Data Systems ; 121(12):2697-2721, 2021.
Article in English | ProQuest Central | ID: covidwho-1806829
ABSTRACT
Purpose>This paper aims to propose a social enterprise legitimation mechanism by combining the established logic and transformational logic to test the validity of the conceptual model.Design/methodology/approach>The authors construct the theoretical framework based on integrating organizational identity theory, attention-based view and collected 128 social enterprises data during the post-pandemic period in China. The authors applied multiple hierarchical regression analysis and mediation analysis to test the research hypothesis.Findings>The results show that strong organizational identity contributes significantly to the cognitive legitimacy of social enterprise. Besides, we found that social welfare logic and digital transformation can positively mediate the correlation between organizational identity and cognitive legitimacy.Practical implications>Social enterprises enhance legitimacy significantly by social welfare logic comparing with commercial logic, which indicates that social enterprises should allocate more internal resources and attention to present the organization's social value through various distributions. More importantly, social enterprises should embrace digital transformation to enhance transparency and efficiency, decrease transaction costs, enlarge organizational social impact to strengthen cognitive legitimacy.Originality/value>The paper first proposed and empirically tested that digital transformation is an important mechanism to enhance the social enterprise's cognitive legitimacy.
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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Industrial Management & Data Systems Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ProQuest Central Language: English Journal: Industrial Management & Data Systems Year: 2021 Document Type: Article