张道潘:南京审计大学讲师,南京航空航天大学经济与管理学院博士研究生。研究方向:产学研合作,技术创新管理。
F273.1
本文系江苏省高等学校自然科学项目(项目编号:19KJA180002、18KJB610010)的阶段性成果。沈佳为本文通讯作者。
本文基于组织差异性视角,研究产学研合作伙伴之间的组织邻近对知识转移和合作创新绩效的影响机理。对328家产学研合作企业问卷调查数据的实证分析结果表明:组织邻近对产学研合作创新绩效有显著的提升作用;知识转移扮演了中介变量的角色,是组织邻近到合作绩效的关键传递路径;大数据采纳正向调节了这种中介作用,即企业利用大数据技术能够有效地实现合作伙伴间的知识转移和创新绩效提升。本文不仅能丰富产学研领域的理论和实证研究,还可为促进政府、企业和学研机构的产学研合作成果产出提供借鉴。
Based on organizational difference perspective, this paper studies the influence of organizational proximity on knowledge transfer and innovation performance of Industry-University-Research collaborative partners. Using a survey of 328 enterprises, the empirical analysis shows that: (1) organizational proximity has a significant role in promoting Industry-University-Research collaborative innovation performance; (2) knowledge transfer plays the mediating role of this relationship as the key mechanism; (3) big data adoption positively moderates the mediation effect, that is, big data technology can effectively realize knowledge transfer among partners and improve innovation performance. This study not only enriches the theoretical and empirical research in the field of Industry-University-Research collaboration, but also provides guidelines for the governments, enterprises, and institutions.
张道潘,沈佳.组织邻近、知识转移、大数据采纳与产学研合作创新绩效:基于被调节的中介模型检验*[J].上海对外经贸大学学报,2019,(6):49-58.
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