摘要
本文采用元分析法对36篇实证研究成果进行分析,得到以下结论:第一,高层管理人员间差异性与企业绩效间呈正相关关系,相关系数为0.162,且达到显著性水平(p<0.05),因此高管团队异质性有助于企业绩效提升。同时,两者间的相关系数随行业科技含量降低而减小。第二,从变量测量的结果看,异质性的维度和类型对两者间关系具有显著的调节作用,因此自变量的不同测量方式是造成两者间关系存在差异的原因之一。第三,情景分析的结果表明,企业的成立时间、所有制形式等都能够调节二者间关系。因此,企业在变幻莫测的环境下开展经营活动,除了根据情况调整团队异质性外,还应重视内外部因素间相互配合和协调,以此实现企业绩效的提升。
In this paper, we use meta analysis to analyze 36 empirical research results, and get the following conclusions: first, there is a positive correlation between the difference of senior managers and enterprise performance, the correlation coefficient is 0.162, and it reaches a significant level (p〈0.05). Therefore, the heterogeneity of senior management team is helpful to the improvement of enterprise performance. At the same time, the correlation coefficient between the two decreases with the decrease of technology content in the industry. Second, from the result of variable measurement, the dimensions and types of heterogeneity have a significant regulating effect on the relationship between the two. Therefore, the different measurement methods of the independent variables are one of the reasons for the difference in the relationship between the two. Third, the results of scenario analysis indicate that the establishment time and form of ownership can regulate the relationship between the two parties. Therefore, in a changeable environment, business activities should be carried out in a changeable environment. In addition to adjusting the heterogeneity of the team according to the situation, the cooperation and coordination between the internal and external factors should be paid more attention to the promotion of the enterprise performance.
作者
舒业弘
丁修平
SHU Yehong;DING Xiuping(College of Economics & Trade,Guangdong Mechanical & Electrical Polytechnic,Guangzhou 510515,China)
出处
《东莞理工学院学报》
2018年第4期62-68,共7页
Journal of Dongguan University of Technology
基金
国家自然科学基金项目"集中度对乳品供应链垂直协作影响的理论与实证研究"(71573098)
国家自然科学基金项目"集中度效应分离及其在农产品加工产业组织绩效评估中的应用研究"(71173085)
关键词
高管团队异质性
企业绩效
元分析
调节效应
management team heterogeneity
enterprise performance
meta-analysis
regulatory effect