高技术企业如何配置大数据分析属性实现创新双元性？-基于中国236家高技术企业的fsQCA分析

How do high-tech enterprises confirgure big data analysis attributes for innovation ambidexterity- fsQCA analysis of 236 high-tech enterprises in China

摘要:

立足于数字经济背景，本研究采用fsQCA方法，以236家高技术企业为对象，探讨多维度大数据分析能力与内部动态能力联动实现双元创新的组态路径。研究发现：（1）大数据人员能力是创新双元性的核心条件。（2）存在两类驱动路径，即基础决策型、管理优化型的时间双元模式与分析协同型的结构双元模式。（3）知识协同辅助下，大数据管理及人员能力是实现创新双元性的关键。大数据基础设施与管理能力存在驱动与抑制效应的替代关系。本研究有助于厘清如何在数字化背景下整合利用不同类型数字能力帮助高技术企业兼顾探索式创新与利用式创新。

Abstract:

In the context of digital economy, we developed a theoretical model of high-tech firms" knowledge-based digital capabilities and dynamic capabilities combined to pursue innovation ambidexterity. We adopted the fsQCA method to conduct configurational analysis on the questionnaire data of 236 high-tech enterprises. The results showed that (1) There is no one factor in this paper is the necessary condition for facilitating innovation ambidexterity, but the big data personal expertise is the most important sufficient condition for pursuing innovation ambidexterity. (2) There are three types of configuration paths were sufficient for high-level innovation ambidexterity, namely ‘Foundation-decision type, Management-Optimization Type and Analysis-Collaboration Type’,The first two categories can be classified as temporal ambidexterity patterns, and the latter category can be classified as structural ambidexterity patterns. Especially, there is a substitution relationship between big data management capabilities and big data infrastructure structure in all path of both high-level and low level innovation ambidexterity. This study helps to clarify how to integrate and utilize knowledge-based dynamic capabilities in the context of digitalization, and provides practical guidance for enterprises to use digital capabilities to facilitate innovation ambidexterity.