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Data element investment strategy: How can leaders and followers innovate in dynamic market environments

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  • Yinhai Fang
  • Wei Wei
  • Rengang Su

Abstract

In the era of the digital economy, the data element investment strategy decisions and game mechanisms of leaders and followers are crucial issues to be studied. To explore the environment in which digital collaboration between enterprises benefits both parties, this study initially proposes a three-stage game model of leaders and followers based on the sequential game method. Subsequently, we analyze the investment strategy choices for leading and following enterprises across six scenarios within dynamic market environments. Finally, numerical simulations are employed to examine the effect of both strategies on the industry and society as a whole. The simulation shows that (1) The cooperation strategy is a more effective approach for enhancing data-driven innovation performance, but when it comes to mature markets, this strategy may conflict with the interests of followers. (2) Followers can benefit from the cooperation strategy by significantly boosting the growth rate of data elements, but it may cause enterprises to lose their original market scale. (3) Excessively high initial production costs can negatively affect the innovative performance of the industry and social wealth, whereas mature industries can achieve greater industry performance and social welfare through investment in data elements. Considering the environmental characteristics of the digital economy, the findings of this study elucidate the ramifications of innovation strategies on enterprises, industries, and society, providing positive insights for two types of enterprises with different strengths to make apt decisions regarding digital cooperation.

Suggested Citation

  • Yinhai Fang & Wei Wei & Rengang Su, 2024. "Data element investment strategy: How can leaders and followers innovate in dynamic market environments," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-22, August.
    • Handle: RePEc:plo:pone00:0309659
    DOI: 10.1371/journal.pone.0309659
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    References listed on IDEAS

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    1. Wang, Hongxia & Li, Ming & Wang, Zhiru & Deng, Wenyueyang & Zhang, Zenglian, 2024. "Technological innovation strategies of information and communication technology enterprises: A comparative study of China, US, and Europe," Finance Research Letters, Elsevier, vol. 61(C).
    2. Jiayi Jia & Yongzeng Lai & Zheng Yang & Lin Li, 2022. "The Optimal Strategy of Enterprise Key Resource Allocation and Utilization in Collaborative Innovation Project Based on Evolutionary Game," Mathematics, MDPI, vol. 10(3), pages 1-25, January.
    3. Peng, Yu & Lu, Qian, 2015. "Complex dynamics analysis for a duopoly Stackelberg game model with bounded rationality," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 259-268.
    4. Mailath George J., 1993. "Endogenous Sequencing of Firm Decisions," Journal of Economic Theory, Elsevier, vol. 59(1), pages 169-182, February.
    5. Guojun Ji & Muhong Yu & Kim Hua Tan & Ajay Kumar & Shivam Gupta, 2024. "Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes," Annals of Operations Research, Springer, vol. 333(2), pages 871-894, February.
    6. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    7. Aleš Popovič & Ray Hackney & Rana Tassabehji & Mauro Castelli, 2018. "The impact of big data analytics on firms’ high value business performance," Information Systems Frontiers, Springer, vol. 20(2), pages 209-222, April.
    8. Kanger, Laur & Sovacool, Benjamin K. & Noorkõiv, Martin, 2020. "Six policy intervention points for sustainability transitions: A conceptual framework and a systematic literature review," Research Policy, Elsevier, vol. 49(7).
    9. Kostas Mavromaras & Jason Qu & Ric Simes & John O'Mahony, 2017. "How Do Digital Technologies Drive Economic Growth?," The Economic Record, The Economic Society of Australia, vol. 93, pages 57-69, June.
    10. Wang, Ye & Jiang, Zongzheng & Li, Xiao & Chen, Yang & Cui, Xiao & Wang, Shipeng, 2023. "Research on antecedent configurations of enterprise digital transformation and enterprise performance from the perspective of dynamic capability," Finance Research Letters, Elsevier, vol. 57(C).
    11. Bichuch, Maxim & Hobbs, Benjamin F. & Song, Xinyue, 2023. "Identifying optimal capacity expansion and differentiated capacity payments under risk aversion and market power: A financial Stackelberg game approach," Energy Economics, Elsevier, vol. 120(C).
    12. Calvano, Emilio & Polo, Michele, 2021. "Market power, competition and innovation in digital markets: A survey," Information Economics and Policy, Elsevier, vol. 54(C).
    13. Baogui Xin & Yue Liu & Lei Xie, 2024. "Data capital investment strategy in competing supply chains," Annals of Operations Research, Springer, vol. 336(3), pages 1707-1740, May.
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