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王国红 教授

博士、教授     研究方向:创业管理、技术创新与高技术产业化 辽宁省“百千万人才工程”百人层次人才(2009年),辽宁省教学名师 大连理工大学经济管理学院乐凡讲席教授 主持突发条件下多主体创新韧性与转换路径研究、面向不连续创新的传统大企业与新兴企业的协同价值创造实现研究等国家自然科学基金5项、省市及企事业科研与咨询项目40余项;主持辽宁省教改项目1项,校教改基金重点课题1项。 在中国软科学、预测、科研管理等国内外核心期刊发表论文90余篇,出版学术专著5部,创业管理课程教材3部;编写创新创业教学案例9篇,其中6篇入选全国百优案例;多次担任全国、辽宁省创业大赛指导教师及评委。 主...

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How entrepreneurial orientation affects firm performance? Examining the black box through MASEM

发布时间:2019-11-07 点击次数:

  • 论文类型:会议论文
  • 发表时间:2019-09-19
  • 收录刊物:EI
  • 卷号:1
  • 页面范围:589-598
  • 摘要:Understanding how firms can promote performance is of high interest for both scholars and practitioner. Entrepreneurial orientation (EO) which reflects the strategic posture of a firm to continuously engage in innovative, risk-taking, and proactive behaviours, is widely recognised as an important source of competitive advantage and superior performance of firms. Therefore many scholars have conducted in-depth researches on the EO-performance relationship. Some of them not only study whether EO affect firm performance, but also study the mechanism through which does EO affect performance, dynamic capabilities (DCs) are proposed as key driver factors to explain the relationship between EO and firm performance. Although a substantial body of research has been done, there are some unresolved issues, further research is needed. First, some results of empirical researches on the relationship between EO and firm performance have not been fully conclusive. Second, the mechanism through which EO influences firm performance remains unclear. In order to explore the truth and get convincing results, this study uses meta-analytic methods combined with structural equation modelling(MASEM) to synthesize extant empirical research. This study develops and empirically examines a model that investigates the mediating roles of two DCs (sensing and seizing, reconfiguring) on the relationship between EO (innovativeness, proactiveness and risk-taking) and firm performance. This study integrates findings from separate streams, covering 12 years of research, and uses a sample of 234 effect sizes from 49 studies to verify the model. Using R software, the results of MASEM show that the model fitting degree is good. Therefore, this paper agrees with the view that EO affects performance through DCs, which play a mediating role. The results thus provide valuable insights for managers to promote firm performance, as they provide a 'guiding map' which reveals how EO may use specific DCs to enhance firm performance. ? Proceedings of the 14th European Conference on Innovation and Entrepreneurship, ECIE 2019. All rights reserved.