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Analysis on Stochastic Change Characteristics of Technological Innovation Efficiency under Endogenous Change in Technological Information and Investment of Knowledge Capital

Author

Listed:
  • Linsheng Yang

    (Institute of New Economics Research, Ningbo Polytechnic, Ningbo 315800, China)

  • Jintao Gong

    (Institute of New Economics Research, Ningbo Polytechnic, Ningbo 315800, China)

  • Bihao Wang

    (School of Economics and Management, East China Jiaotong University, Nanchang 330013, China)

Abstract

The allocation of innovation-related elements is influenced by intangible elements such as technological information, which affects knowledge capital, human capital, and material element investment, resulting in the stochastic change of technological innovation efficiency. The endogenous change in technological information in element investment reduces friction, lowers costs, improves efficiency, and gradually reduces the deviation between knowledge capital investment and technological innovation efficiency. In terms of small knowledge capital investment characterized by the low demand for technological information and a single source, it is easier to make more-accurate predictions, so the stochastic change in technological innovation efficiency tends to be gentle. The endogenous change in technological information continuously increases the proportion of replacing other elements with knowledge capital investment, and the efficiency of technological innovation improves steadily. Under the condition of unchanged investment in other elements, there is a great difference in the duration of technological information between the simultaneous selection and the successive selection of knowledge capital investment. When one-time instantaneous information and continuous complete information are respectively acquired, the stochastic variation of technological innovation efficiency is obvious. On the basis of the technological innovation data of 287 listed companies in eight industries, this paper compares and analyzes the measurement results of GMM and OLS to verify the above findings.

Suggested Citation

  • Linsheng Yang & Jintao Gong & Bihao Wang, 2023. "Analysis on Stochastic Change Characteristics of Technological Innovation Efficiency under Endogenous Change in Technological Information and Investment of Knowledge Capital," Sustainability, MDPI, vol. 15(6), pages 1-27, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:4799-:d:1091182
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    References listed on IDEAS

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    1. Mark Satterthwaite & Artyom Shneyerov, 2007. "Dynamic Matching, Two-Sided Incomplete Information, and Participation Costs: Existence and Convergence to Perfect Competition," Econometrica, Econometric Society, vol. 75(1), pages 155-200, January.
    2. Patrick W. Schmitz, 2006. "Information Gathering, Transaction Costs, and the Property Rights Approach," American Economic Review, American Economic Association, vol. 96(1), pages 422-434, March.
    3. Farrell, Joseph & Klemperer, Paul, 2007. "Coordination and Lock-In: Competition with Switching Costs and Network Effects," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 31, pages 1967-2072, Elsevier.
    4. Avinash Dixit, 2009. "Governance Institutions and Economic Activity," American Economic Review, American Economic Association, vol. 99(1), pages 5-24, March.
    5. Katz, Michael L & Shapiro, Carl, 1985. "Network Externalities, Competition, and Compatibility," American Economic Review, American Economic Association, vol. 75(3), pages 424-440, June.
    6. Qiuqi Wang & Yue Kuen Kwok, 2019. "Signaling game models of equity financing under information asymmetry and finite project life," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-38, March.
    7. Marco Battaglini & Rebecca B. Morton & Thomas R. Palfrey, 2008. "Information Aggregation and Strategic Abstention in Large Laboratory Elections," American Economic Review, American Economic Association, vol. 98(2), pages 194-200, May.
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    Cited by:

    1. Bo Zeng & Weimin Zhang & Defang Ma & Chenyang Zhang & Xiao Liu, 2023. "The Impact of Group Control on the Effectiveness of Enterprise Innovation: An Empirical Study," Sustainability, MDPI, vol. 15(13), pages 1-15, July.
    2. Defang Ma & Liangwei Li & Yuxi Song & Mengkai Wang & Qiaowen Han, 2023. "Corporate Sustainability: The Impact of Environmental, Social, and Governance Performance on Corporate Development and Innovation," Sustainability, MDPI, vol. 15(19), pages 1-16, September.

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