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Improving high-tech enterprise innovation in big data environment: A combinative view of internal and external governance

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  • Lin, Runhui
  • Xie, Zaiyang
  • Hao, Yunhong
  • Wang, Jie

Abstract

The emergence of big data brings both opportunities and challenges to high-tech enterprises. How to keep competitive advantages and improve innovation performance is important for enterprises in big data environment. Except from organizational learning ability and the use of advanced technology, the corporate governance also plays an important role in the process of enterprise’s innovation practice. This article creatively combines with the insights of internal and external governance, and explores how the managerial power and network centrality affects enterprise’s innovation performance in big data environment. Considering about the differences among distinct regional big data environment (strong/weak), this paper also takes classification research on it. The research findings show that managerial power has a significant positive impact on innovation performance, managerial power could enhance enterprise’s centrality in network, and the enterprise which located in network central position has more advantages in obtaining resources and significantly improves firm’s innovation performance. Network centrality plays a mediating role on managerial power and innovation performance. Further research finds that the positive effects of managerial power and network centrality are more significantly in the strong big data environment. These findings enrich the research of high-tech enterprise innovation from a combinative governance view, and contribute to the literatures on enterprise innovation in big data environment.

Suggested Citation

  • Lin, Runhui & Xie, Zaiyang & Hao, Yunhong & Wang, Jie, 2020. "Improving high-tech enterprise innovation in big data environment: A combinative view of internal and external governance," International Journal of Information Management, Elsevier, vol. 50(C), pages 575-585.
    • Handle: RePEc:eee:ininma:v:50:y:2020:i:c:p:575-585
    DOI: 10.1016/j.ijinfomgt.2018.11.009
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    Citations

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    Cited by:

    1. Zhong, Meirui & Huang, Gangli & He, Ruifang, 2022. "The technological innovation efficiency of China's lithium-ion battery listed enterprises: Evidence from a three-stage DEA model and micro-data," Energy, Elsevier, vol. 246(C).
    2. Mutasim Asa’d & Wan Norhayati Wan Ahmad & Hazeline Ayoup, 2024. "Environmental Management Accounting Information and Environmental Performance, the Mediating Effect of Environmental Decision Quality," International Journal of Energy Economics and Policy, Econjournals, vol. 14(2), pages 562-573, March.
    3. Shivam Gupta & Théo Justy & Shampy Kamboj & Ajay Kumar & Eivind Kristoffersen, 2021. "Big data and firm marketing performance: Findings from knowledge-based view," Post-Print hal-03609916, HAL.
    4. Tan, Xiujie & Yan, Yaxue & Dong, Yuyang, 2022. "Peer effect in green credit induced green innovation: An empirical study from China's Green Credit Guidelines," Resources Policy, Elsevier, vol. 76(C).
    5. Rui Li & Jing Rao & Liangyong Wan, 2022. "The digital economy, enterprise digital transformation, and enterprise innovation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 2875-2886, October.
    6. Gao(高凯), Kai & Wang(王玲), Ling & Liu(刘婷婷), Tingting & Zhao(赵华擎), Huaqing, 2022. "Management executive power and corporate green innovation——Empirical evidence from China's state-owned manufacturing sector," Technology in Society, Elsevier, vol. 70(C).
    7. Jinlin Li & Litai Chen & Ying Chen & Jiawen He, 2022. "Digital economy, technological innovation, and green economic efficiency—Empirical evidence from 277 cities in China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(3), pages 616-629, April.
    8. Fu-Hsiang Chen & Ming-Fu Hsu & Kuang-Hua Hu, 2022. "Enterprise’s internal control for knowledge discovery in a big data environment by an integrated hybrid model," Information Technology and Management, Springer, vol. 23(3), pages 213-231, September.
    9. Xiaohui Chen & Kongbiao Lu, 2024. "How does digital technology administrative penalty affect big data technology innovation: evidence from China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.

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