The Impact of Knowledge Attributes on Knowledge Maintenance Routine within Industrial Clusters: A Knowledge-Processing Perspective

被引：0

作者：

Guo Jingjing ^{[1
]}

Guo Wen ^{[1
]}

Wang Yi ^{[2
]}

机构：

[1] Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China

[2] Tsinghua Univ, Sch Econ & Management, Beijing 100084, Peoples R China

来源：

INNOVATION-DRIVEN CAPABILITY BUILDING AND INDUSTRY DEVELOPMENT (ISMOT'16) | 2016年

基金：

中国国家自然科学基金;

关键词：

industrial clusters; knowledge maintenance routine; knowledge tacitness; knowledge heterogeneity; APPLYING ORGANIZATIONAL ROUTINES; INNOVATION; NETWORKS;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper posits the concept of knowledge maintenance routine to systematically illustrate firms' knowledge storage behavior within industrial clusters on the basis of knowledge-processing perspective, and further demonstrates the impact of knowledge tacitness and knowledge heterogeneity on the diversity of firms' knowledge maintenance routine within industrial clusters. This paper uses survey data to conduct a regression analysis for testing the theoretical hypotheses. The research results show that knowledge tacitness and knowledge heterogeneity have significantly positive influence on the diversity of firms' knowledge maintenance routine within industrial clusters.

引用

页码：79 / 83

页数：5

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