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The Impact of Data Elements on Enterprises’ Capital Market Performance: Insights from Stock Liquidity in China and Implications for Global Markets

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  • Rong Cui

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Yuda Wang

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Yujing Wang

    (Business School, University of Bristol, Bristol BS8 1QU, UK)

Abstract

Amidst a backdrop of global economic challenges and shifting market dynamics, this study highlights the transformative role of data elements in enhancing enterprise performance within capital markets, particularly focusing on China’s leading position in the digital economy as a model with implications for global markets. This study utilized a panel data set consisting of 10,493 observations from 2687 listed enterprises in Shanghai and Shenzhen A-shares from 2015 to 2023. An econometric analysis was conducted using a two-way fixed effects model to explore the impact of enterprise data elements on capital market performance in the digital economy and its underlying mechanisms. The research reveals that the digitization of enterprise production factors can significantly enhance performance in the capital market. The study further suggests that enterprise innovation and enterprise value play a crucial role in mediating this effect. This paper introduces a new concept called “data elements”, which expands the definition and assessment methods of enterprise data capabilities. It goes beyond just digital transformation at the application level and includes data governance at the basic ability level. This approach provides a more accurate and comprehensive understanding of the different elements of data. Moreover, the research expands the research scope of microeconomic entities’ economic benefits, thereby extending the value contributed by enterprise data elements to their performance in the capital market. Additionally, this study reveals the relationship between enterprise data elementization and capital market performance through intermediary analysis of enterprise innovation performance and enterprise value, which unveils the “black box” and clarifies the transmission pathway. The findings of this research hold considerable theoretical value and have far-reaching practical implications for government policies concerning data elements and the development of high-quality enterprises, suggesting pathways for global markets to leverage data for enhanced enterprise performance and economic resilience. The results are particularly useful for policymakers, enterprise managers, and scholars in understanding and implementing data-driven strategies in capital markets.

Suggested Citation

  • Rong Cui & Yuda Wang & Yujing Wang, 2024. "The Impact of Data Elements on Enterprises’ Capital Market Performance: Insights from Stock Liquidity in China and Implications for Global Markets," Sustainability, MDPI, vol. 16(9), pages 1-30, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3585-:d:1382108
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    1. Richard S J Tol, 2018. "The Economic Impacts of Climate Change," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 4-25.
    2. Amihud, Yakov & Mendelson, Haim, 1986. "Asset pricing and the bid-ask spread," Journal of Financial Economics, Elsevier, vol. 17(2), pages 223-249, December.
    3. Benedict Oramah & Richman Dzene, 2019. "Globalisation and the Recent Trade Wars: Linkages and Lessons," Global Policy, London School of Economics and Political Science, vol. 10(3), pages 401-404, September.
    4. Bronwyn H. Hall & Nathan Rosenberg (ed.), 2010. "Handbook of the Economics of Innovation," Handbook of the Economics of Innovation, Elsevier, edition 1, volume 1, number 1.
    5. Imai, Kosuke & Kim, In Song, 2021. "On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data," Political Analysis, Cambridge University Press, vol. 29(3), pages 405-415, July.
    6. Martin Obschonka & David B. Audretsch, 2020. "Artificial intelligence and big data in entrepreneurship: a new era has begun," Small Business Economics, Springer, vol. 55(3), pages 529-539, October.
    7. Truant, Elisa & Broccardo, Laura & Dana, Léo-Paul, 2021. "Digitalisation boosts company performance: an overview of Italian listed companies," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    Full references (including those not matched with items on IDEAS)

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