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论文编号：	8330
作者编号：	2120142541
上传时间：	2016/6/7 19:22:51
中文题目：	医药上市企业知识搜索行为影响因素的研究
英文题目：	The influencing factors of knowledge search behavior in pharmaceutical listed companies
指导老师：	李颖
中文关键字：	知识搜索；影响因素；专利数据；医药企业；企业创新
英文关键字：	Knowledge Search; Influencing factors; Patent Data; Pharmaceutical Listed Companies; Innovative Performance
中文摘要：	研究的目的是分析我国医药上市企业知识搜索行为的影响因素及其作用机制。研究将智慧Pat-snap数据库作为企业知识搜索行为专利数据的来源，将Wind资讯金融终端以及国泰安数据库作为企业财务数据的来源，利用专利数据表征企业知识搜索行为，利用专利数据、企业财务数据、国家统计数据表征企业知识搜索的各影响因素。通过对比分析1995-2014年20年间55家A股上市企业的专利数据和企业财务数据、国家统计数据的关系，利用描述性统计、单因素ANOVA分析以及Pearson相关性分析方法，分析出不同影响因素对于企业知识搜索行为的影响。其中，具体的分析内容包括企业研发投入、企业冗余资源、市场增长率、市场竞争程度、技术积累性、技术机会等因素分别对我国医药上市公司的知识搜索广度、知识搜索宽度的影响。此外，控制变量设为企业规模、企业年龄、细分行业、企业所有制、所在省份等。 研究发现企业的研发投入力度对企业知识搜索深度存在正向影响。冗余资源和企业知识搜索活动的深度呈正相关关系。市场竞争程度对企业知识搜索深度和知识搜索广度均存在负向影响，市场竞争越强烈，企业的知识搜索行为越少；行业的技术积累性、技术机会与知识搜索深度、知识搜索广度均为正相关关系。此外，知识搜索深度及知识搜索广度均与企业创新绩效成正相关关系。图5幅，表16个，参考文献102篇。
英文摘要：	The purpose of this study is to analyze what kinds of factors influence knowledge search behaviors in pharmaceutical listed companies. This study uses patent data as measure variables of knowledge search behaviors, and uses patent data, financial data and national statistics as measure variables of influencing factors of knowledge search behaviors. And the sample of this study consists of 55 A-share listed companies. What’s more, the data for the analysis are downloaded from PatSnap Database, Wind Financial Terminal and CSMAR. According to analyzing related literature, this study chooses Knowledge Search Breadth and Knowledge Search Depth as independent variables, and dependent variables including R&D Investment, Slack Resource, Degree of Market Competition, Degree of Market Growth, Technological Cumulativeness and Technological Opportunities, and control variables including Firm Size, Firm Age, Sub-sectors, Firm Ownership and Provinces. And the methods of data analysis consist of Descriptive statistics, One-way ANOVA and Pearson correlation analysis. Further, this study finds that R&D investment has a positive impact on knowledge search depth, and so do Slack resource. Besides, the degree of market competition is negative to both knowledge search depth and knowledge search breadth. Technological cumulativeness and technological opportunities have positive relation to knowledge search depth and knowledge search breadth respectively. In addition, knowledge search depth and knowledge search breadth both have a good impact on innovative performance. Figure 5 and Table 16, reference 102.
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