Institutional forces and knowledge search strategies as predictors of entrepreneurial venture performance

ABSTRACT

We examine how institutional factors influence the strategies entrepreneurial ventures use as they seek the knowledge they need to perform and compete. With a focus on economic and ecosystem development, we propose a framework of interrelations between two principal knowledge-search strategies, their interactions with varying levels of institutional development, and the joint effects on venture performance. We utilize a sample of 1,470 entrepreneurial ventures to examine two hypotheses. Results, based on hierarchical regression, distributed lag analyses, and several assumption and robustness checks show that knowledge-search strategy interrelations are complementary when institutional development is high but substitutive when institutional development is low. We execute a post hoc analysis using separate data sources to replicate these results and strengthen our findings. Finally, we discuss implications for entrepreneurial practitioners, policymakers, and scholars.

KEYWORDS:

• Knowledge
• search strategy
• institutionalism

Acknowledgment

We are grateful to JSBM editor Eric Liguori and three anonymous reviewers for insightful comments on previous versions of this paper. We also acknowledge the guidance and input from Haiyang Li, the International Finance Corporation’s Enterprise Surveys program, and the Chinese National Bureau of Statistics. This research was supported by grants SRG2019-00146-FBA and CPG2020-00018-FBA awarded to Jean Jinghan Chen by the University of Macau.

Notes

¹ The empirical data collection portion of this research was supported in part by the university of the first author. The targeted cities included Benxi, Changchun, Changsha, Chongqing, Dalian, Guiyang, Haerbin, Hangzhou, Jiangmen, Kunming, Lanzhou, Nanchang, Nanning, Shenzhen, Wenzhou, Wuhan, Xian, and Zhengzhou.

² We also executed two-period lagged value scores. Results were consistent with the use of the one-period lagged scores but necessarily reduced the number of sample observations to 721.

³ Beijing, Chengdu, Guangzhou, Shanghai, and Tianjin.