题目：Socially Connected Supply Chain
摘要：Social connections built up via shared past working experience or non-business activities help gather and facilitate information, and therefore predict supply chain formation among firms. With a unique and comprehensive dataset incorporating social network and supply chain interactions, we find that social connections, measuring by either the existence or the number of manager-to-manager personal connections, predict supply chain network formation between firms. Besides promoting supply chain network formation, the presence of social connections also predicts less breakage of the already established supply chain links. Moreover, we provide some heterogeneities from the respect of social connections. We find that the facilitating effect of the social network is twice stronger for high-power connections, defined as personal connections between C-level executives, as compared with non-executive connections. While considering indirect social connections, our results indicate that higher-order social connections also significantly predict the formation of supply chains, albeit at a much smaller economic magnitude. We establish causality by studying shocks to a firm's social network using executive death and retirements. At last, we provide strong evidence that the socially connected supply chain performs as well as traditionally-formed supply chain in terms of short-run stock market announcement returns and returns on assets in the long run.
Professor Jing Wu is an assistant professor at the Department of Decision Sciences and Managerial Economics of CUHK Business School, the Chinese University of Hong Kong, and executive committee member of the Hong Kong-Shenzhen Finance Research Center. He receives both his Ph.D. (major in operations, minor in economics & finance) and MBA from the University of Chicago Booth School of Business, and receives his bachelor's degree in Electronic Engineering from Tsinghua University. Professor Wu's primary research fields are the operations-finance interface, economic networks, quantitative investment, and machine learning applications. His work appears in several INFORMS and IEEE journals. Professor Wu contributes to the industry by advising FinFabrik.com (a Hong Kong FinTech firm) and an asset management firm in Mainland China. Prior to Greater China, he worked at Deutsche Bank, New York, as a quantitative strategist.
吴靖教授是香港中文大学中大商学院决策科学与管理经济学系的助理教授，也是香港-深圳金融研究中心执行委员会委员。 他在芝加哥大学布斯商学院获得了博士及MBA学位，在清华大学获得电子工程学士学位。 吴教授的主要研究领域是运营和金融交叉、供应链和金融经济网络，他的论文发表在INFORMS和IEEE期刊中。吴教授在进入大学工作前，曾在纽约德意志银行担任定量策略师。