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Do Social Networks of Listed Companies Help Companies Recover from Financial Crises?

doi: 10.3390/su14095044
This study aims to examine how the social networks of top management affect the recovery of their companies when facing a financial crisis. We mainly use the logit and Cox regression models to investigate whether social networks help overcome the financial distress and shorten the crisis duration. The empirical findings suggest that companies with characteristics of low degree centrality of the chairman’s bank networks and high closeness centrality of the general manager’s general networks and bank networks are more likely to overcome financial distress and get back to normal status. Furthermore, for companies with characteristics of low degree centrality of the chairman’s personal general networks, low closeness centrality of the financial executive’s personal general networks, and high degree centrality of the financial executive’s personal bank networks, it was easier to shorten the crisis duration. The practical implication is that companies need to prioritize quality over quantity in order to survive or shorten the crisis. All company top managers should not look only at the size of the company but consider how the social network is configured.
- Chaoyang University of Technology Taiwan
- Asian University Taiwan
- Asian University Taiwan
- National Yunlin University of Science and Technology Taiwan
- Chaoyang University of Technology Taiwan
Environmental effects of industries and plants, cox regression, financial crisis, degree centrality, TJ807-830, 650, TD194-195, Renewable energy sources, closeness centrality, Environmental sciences, logit regression, social network; degree centrality; closeness centrality; financial crisis; logit regression; cox regression, social network, GE1-350, logit regression; cox regression
Environmental effects of industries and plants, cox regression, financial crisis, degree centrality, TJ807-830, 650, TD194-195, Renewable energy sources, closeness centrality, Environmental sciences, logit regression, social network; degree centrality; closeness centrality; financial crisis; logit regression; cox regression, social network, GE1-350, logit regression; cox regression
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