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论文编号：	8583
作者编号：	1120120799
上传时间：	2016/6/21 9:16:38
中文题目：	政治关联、网络中心性与企业创新业绩
英文题目：	Political Connections, Network Centrality and Innovation Performance of Enterprises
指导老师：	马连福
中文关键字：	政治关联；创新业绩；网络中心性；市场化程度
英文关键字：	Political Connections; Innovation Performance; Network Centrality;
中文摘要：	近年来，随着中国经济环境变化，创新推动政策的不断推出，“供给侧”改革的不断深化，民营企业创新能力和创新业绩的提升成为中国未来经济的主要增长方向，成为相关政策推动的重中之重，以及相关民营企业发展壮大的制胜法宝。同时，由于中国经济尚处于发展阶段，以市场规制为代表的正式制度尚不完善，民营企业，特别是民营上市企业都或多或少的依赖政治关联开展业务，进行创新活动。在上述市场环境和制度条件下，企业政治关联成为了研究中国民营企业创新业绩问题所必须关注的重要影响因素。然而，现有的企业政治关联对企业创新业绩影响研究上存在一些可以更进一步研究的方面：首先，企业政治关联存在不同的来源，并且发挥着不同的创新业绩作用，在企业初创阶段，企业往往依靠企业家个人与政府的特殊关系建立政治关联，但在企业壮大发展之后，企业往往会产生一些组织化的、不再依赖于个别管理人员的政府关系。上述不同政治关联的不同创新业绩影响情况尚未经过清晰地研究。另外，企业政治关联、企业网络中心性和企业创新业绩之间的相互影响关系和影响机制尚未得到透彻的研究。与之相对的，在不同市场条件下，上述关系的不同作用机理，以及不同市场门限条件所带来的不同的企业政治关联创新业绩作用还没有得到有效的实证分析。上述欠缺的主要原因一方面是因为，一些相关变量，诸如企业组织化的政治关联、企业网络条件等难以利用传统的数据收集方式有效地进行数据收集与整理。另一方面，数据内生性的存在可能扰乱上述运行机制研究的实证效果。最后，管理学界尚未引入有效的工具对企业政治关联相关因素的门限效应进行研究。综上所述，本文利用数据挖掘方法，利用PHP软件，基于中国民营企业上市公司年报和网络相关数据，编程抓取了相关的企业政治关联、企业网络中心性与企业创新业绩等相关数据，结合企业所处地区市场化指数，生成了315个民营上市公司5年，包括1575个变量的面板数据库。进而利用倾向评分匹配模型、面板数据中介模型以及面板数据门限效应模型等前沿的计量模型，剔除了相关数据内生性，研究了上述变量之间动态的影响机制，并且研究了相关门限效应。主要解决了以下几个议题：企业不同来源的政治关联各自的企业创新业绩影响机制；企业政治关联、企业网络中心性和企业创新业绩之间的影响关系；企业所处地区市场化程度对企业政治关联创新业绩的调节与门限效应,并且得出了相关理论结论，进一步发展了现有理论，进而提出了相应的政策和企业策略建议，最终为企业政治关联与创新业绩相关研究做出了贡献。
英文摘要：	Currently, as economic environment changes in China, innovation-driven policies are continuously brought out, and “supply side” reformation goes deeper, improvement of private firms’ innovation capabilities and innovation performance has become the main growing direction of China’s economy in the future. It is also the most important in relevant policies, as well as key of success for private firms’ development. At the same time, China’s economy is still developing, formal institution represented by market rules are not perfect, private firms especially private listed firms depend on political connections to do business and to carry out innovation activities more or less. Under the circumstances of the above market environment and institution conditions, firm political connections have become important influencing factors for studying China private firms’ innovation performance. However, previous studies on firm political connections’ influence on innovation performance are not sufficient: Firstly, firm political connections have different sources and play distinct roles in innovation performance. In the start-up stage, firms rely on entrepreneurs to establish special political connections with government. But when firms develop and become more organized, they will not rely on individual relationships with government. The above different political connections’ distinct effects on innovation performance have not been clearly studied. In addition, the relationships and influencing mechanisms between firm political connections, firm network centrality and firm innovation performance are not clear. In addition, mechanisms of the above relationships under different market conditions, and different innovation performance influenced by firm political connections in different market threshold conditions have been empirically examined. The fact that some relevant variables, such as firm organized political connections, firm network conditions are difficult to collect and organized in traditional ways. On the other hand, the existence of data endogenousness may disturb the effects of the above mechanisms. Finally, effective tools have not been introduced to study firm political connections’ threshold effects in the field of management. In conclusion, based on data from annual reports of China private listed firms and Internet, we use data mining and PHP software, and obtain relevant data of firm political connections, firm network centrality and firm innovation performance. Combined with marketization index in local regions, we generate a panel database that includes 1575 variables of 315 private listed firms in 5 years. Then we use propensity score matching model, panel data moderated mediation model and data threshold effect model to remove data endogenousness, study dynamic influencing mechanisms between the above variables, and pay further attentions to the threshold effect. We have mainly addressed the following issues: influencing mechanisms of firm innovation performance, which root in different sources of firm political connections; relationships between firm political connections, firm network centrality and firm innovation performance; threshold effects of local marketization index on firm political connections and innovation performance. We have made the following contributions to the field of firm political connections and innovation performance: The theoretical conclusions supplement current literature and relevant policy and firm strategic suggestions make sense in practice.
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