IDEAS home Printed from https://ideas.repec.org/a/spt/admaec/v14y2024i3f14_3_9.html
   My bibliography  Save this article

The Impact of Digital Transformation on the Performance of Listed Automobile Manufacturing Enterprises in China

Author

Listed:
  • Shuangjie Li
  • Ruoqi Li
  • Fang Liu

Abstract

The paper investigates the impact of digital transformation on the performance of automobile manufacturing enterprises in China based on the sample data of 66 listed enterprises from 2012 to 2022, finding that digital transformation can improve the performance of automobile manufacturing enterprises and the improvement is long-term. Mechanism analysis shows that improving the human capital level of enterprises is an important path for digital transformation to promote enterprise performance. Moderating effect analysis shows that enterprise capacity has a significant moderating effect. Specifically, weaker business capacity undermines the positive effect of digital transformation on the performance of enterprises, and stronger development capacity plays a positive moderating role in the impact of digital transformation on the performance of enterprises. Heterogeneity analysis reveals that digital transformation has a more significant positive impact on the performance of non-state, small and medium-sized, and eastern automobile manufacturing enterprises. Based on the research conclusions, targeted policy recommendations are put forward to provide a reference for promoting digital transformation and the performance of automobile manufacturing enterprises. JEL classification numbers: C12, M21.

Suggested Citation

  • Shuangjie Li & Ruoqi Li & Fang Liu, 2024. "The Impact of Digital Transformation on the Performance of Listed Automobile Manufacturing Enterprises in China," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 14(3), pages 1-9.
    • Handle: RePEc:spt:admaec:v:14:y:2024:i:3:f:14_3_9
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/AMAE%2fVol%2014_3_9.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghi Tran Nha & Thu Nguyen Quang & Huan Ngo Quang & Trung Nguyen Tan, 2022. "Human capital, digital transformation, and firm performance of startups in Vietnam," Management, Sciendo, vol. 26(1), pages 1-18, January.
    2. Verhoef, Peter C. & Broekhuizen, Thijs & Bart, Yakov & Bhattacharya, Abhi & Qi Dong, John & Fabian, Nicolai & Haenlein, Michael, 2021. "Digital transformation: A multidisciplinary reflection and research agenda," Journal of Business Research, Elsevier, vol. 122(C), pages 889-901.
    3. Akter, Shahriar & Wamba, Samuel Fosso & Gunasekaran, Angappa & Dubey, Rameshwar & Childe, Stephen J., 2016. "How to improve firm performance using big data analytics capability and business strategy alignment?," International Journal of Production Economics, Elsevier, vol. 182(C), pages 113-131.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brewis, Claire & Dibb, Sally & Meadows, Maureen, 2023. "Leveraging big data for strategic marketing: A dynamic capabilities model for incumbent firms," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    2. Hossain, Md Afnan & Akter, Shahriar & Yanamandram, Venkata, 2021. "Why doesn't our value creation payoff: Unpacking customer analytics-driven value creation capability to sustain competitive advantage," Journal of Business Research, Elsevier, vol. 131(C), pages 287-296.
    3. Huang, Heshu & Wang, Caiting & Wang, Liukai & Yarovaya, Larisa, 2023. "Corporate digital transformation and idiosyncratic risk: Based on corporate governance perspective," Emerging Markets Review, Elsevier, vol. 56(C).
    4. Rajesh Chidananda Reddy & Biplab Bhattacharjee & Debasisha Mishra & Anandadeep Mandal, 2022. "A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy," Information Systems and e-Business Management, Springer, vol. 20(1), pages 223-255, March.
    5. Yin, Qiaoyi & Wang, Yunfei & Song, Dian & Lai, Fujun & Collins, Brian & Guo, Hangfei, 2024. "The impact of digitalization on operational risk: An organizational information processing perspective," International Journal of Production Economics, Elsevier, vol. 276(C).
    6. Mohammed T. Abusharbeh, 2024. "Technology-Profitability Paradox in Banking Sector: Evidence from Palestine," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 14855-14873, September.
    7. Mariani, Marcello M. & Fosso Wamba, Samuel, 2020. "Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies," Journal of Business Research, Elsevier, vol. 121(C), pages 338-352.
    8. Irene Bertschek & Joern Block & Alexander S. Kritikos & Caroline Stiel, 2024. "German financial state aid during Covid-19 pandemic: Higher impact among digitalized self-employed," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 36(1-2), pages 76-97, January.
    9. Yuanyuan Lou & Ahreum Hong & Yannan Li, 2024. "Assessing the Role of HRM and HRD in Enhancing Sustainable Job Performance and Innovative Work Behaviors through Digital Transformation in ICT Companies," Sustainability, MDPI, vol. 16(12), pages 1-18, June.
    10. Ludivine Ravat & Aurélie Hemonnet-Goujot & Sandrine Hollet-Haudebert, 2023. "Data-driven innovation capability of marketing: an exploratory study of its components and underlying processes," Post-Print hal-04151199, HAL.
    11. Dominik M. Wielgos & Christian Homburg & Christina Kuehnl, 2021. "Digital business capability: its impact on firm and customer performance," Journal of the Academy of Marketing Science, Springer, vol. 49(4), pages 762-789, July.
    12. Jinqiu He & Huiwen Su, 2022. "Digital Transformation and Green Innovation of Chinese Firms: The Moderating Role of Regulatory Pressure and International Opportunities," IJERPH, MDPI, vol. 19(20), pages 1-21, October.
    13. Ahmad Ibrahim Aljumah & Mohammed T. Nuseir & Md. Mahmudul Alam, 2021. "Traditional marketing analytics, big data analytics and big data system quality and the success of new product development," Post-Print hal-03538161, HAL.
    14. Alkaraan, Fadi & Elmarzouky, Mahmoud & Hussainey, Khaled & Venkatesh, V.G., 2023. "Sustainable strategic investment decision-making practices in UK companies: The influence of governance mechanisms on synergy between industry 4.0 and circular economy," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    15. Cano-Marin, Enrique & Mora-Cantallops, Marçal & Sánchez-Alonso, Salvador, 2023. "Twitter as a predictive system: A systematic literature review," Journal of Business Research, Elsevier, vol. 157(C).
    16. Rizvi, Syed Kumail Abbas & Rahat, Birjees & Naqvi, Bushra & Umar, Muhammad, 2024. "Revolutionizing finance: The synergy of fintech, digital adoption, and innovation," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    17. de Camargo Fiorini, Paula & Roman Pais Seles, Bruno Michel & Chiappetta Jabbour, Charbel Jose & Barberio Mariano, Enzo & de Sousa Jabbour, Ana Beatriz Lopes, 2018. "Management theory and big data literature: From a review to a research agenda," International Journal of Information Management, Elsevier, vol. 43(C), pages 112-129.
    18. Mohammad Ali Yamin, 2021. "Investigating the Drivers of Supply Chain Resilience in the Wake of the COVID-19 Pandemic: Empirical Evidence from an Emerging Economy," Sustainability, MDPI, vol. 13(21), pages 1-16, October.
    19. Rosa Lombardi & Raffaele Trequattrini & Federico Schimperna & Myriam Cano-Rubio, 2021. "The Impact of Smart Technologies on theManagement and Strategic Control: A Structured Literature Review," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(suppl. 1), pages 11-30.
    20. Ding, Jiantao & Yin, Yingkai & Kuang, Jinsong & Ding, Dezhi & Madsen, Dag.Øivind & Yang, Kunyu, 2024. "The impact of enterprise digital transformation on financial mismatch: Empirical evidence from listed companies in China," Finance Research Letters, Elsevier, vol. 66(C).

    More about this item

    Keywords

    Digital Transformation; Automobile Manufacturing; Enterprise Performance.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spt:admaec:v:14:y:2024:i:3:f:14_3_9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.