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The Impact of Ambidextrous Innovation Human Capital on the Technological Innovation Efficiency and Stage Efficiency of Big Data Enterprises

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  • Chang Liu

    (School of Business Administration, Southwest University of Finance and Economics, Chengdu 611130, China)

  • Hui-Lin Xiao

    (School of Business Administration, Southwest University of Finance and Economics, Chengdu 611130, China)

Abstract

Based on a resource-based view, we explore the relationship between ambidextrous innovation human capital and the efficiency of technological innovation and its stage efficiency in big data enterprises. We divide their technological innovation into two stages: technological development and the commercialization of technological achievements. For a more reasonable efficiency measurement, we construct an efficiency evaluation index system based on the entropy value method (EVM) and the analytical hierarchy process (AHP), and we measure and evaluate their technological innovation efficiency from both static and dynamic perspectives. We conduct an empirical analysis with a sample of Chinese big data listed companies from 2014–2017. After regression analysis and its robustness test, we find that ambidextrous innovation human capital has a significant impact on the technological innovation efficiency of big data enterprises, that incremental innovation human capital and radical innovation human capital have opposite impact relationships in the technological development stage and that radical innovation human capital may have a more significant economic significance on the efficiency of commercializing technological achievements of big data enterprises. In the course of our analysis, we also find some other relevant findings. Finally, we formulate some relevant management suggestions.

Suggested Citation

  • Chang Liu & Hui-Lin Xiao, 2022. "The Impact of Ambidextrous Innovation Human Capital on the Technological Innovation Efficiency and Stage Efficiency of Big Data Enterprises," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16636-:d:1001023
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    References listed on IDEAS

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