IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v64y2024ics1544612324004604.html
   My bibliography  Save this article

Does increased digital transformation promote a firm's financial performance? New insights from the quantile approach

Author

Listed:
  • Vu, Dung Anh
  • Van Nguyen, Thinh
  • Nhu, Quang Minh
  • Tran, Tuyen Quang

Abstract

When studying how digital transformation affects company performance, a phenomenon known as the "digitalization paradox" frequently emerges. In previous studies, however, an average estimate has often been used to assess the relationship between digital transformation and firm performance. Using a fixed-effects quantile technique, this study examines the heterogeneous effect of digital transformation on firm performance in Vietnam. The findings reveal a nuanced relationship, indicating that only high-performing companies gain from digital transformation while others do not. The extensive robustness tests in the empirical analysis support this result. It becomes clear that the mean approach may hide the genuine consequences of digital transformation on firm performance.

Suggested Citation

  • Vu, Dung Anh & Van Nguyen, Thinh & Nhu, Quang Minh & Tran, Tuyen Quang, 2024. "Does increased digital transformation promote a firm's financial performance? New insights from the quantile approach," Finance Research Letters, Elsevier, vol. 64(C).
  • Handle: RePEc:eee:finlet:v:64:y:2024:i:c:s1544612324004604
    DOI: 10.1016/j.frl.2024.105430
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324004604
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2024.105430?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    2. Chernozhukov, Victor & Fernández-Val, Iván & Weidner, Martin, 2024. "Network and panel quantile effects via distribution regression," Journal of Econometrics, Elsevier, vol. 240(2).
    3. McGuinness, Seamus & Bennett, Jessica, 2007. "Overeducation in the graduate labour market: A quantile regression approach," Economics of Education Review, Elsevier, vol. 26(5), pages 521-531, October.
    4. Guo, Xiaochuan & Li, Mengmeng & Wang, Yanlin & Mardani, Abbas, 2023. "Does digital transformation improve the firm’s performance? From the perspective of digitalization paradox and managerial myopia," Journal of Business Research, Elsevier, vol. 163(C).
    5. Ivan A. Canay, 2011. "A simple approach to quantile regression for panel data," Econometrics Journal, Royal Economic Society, vol. 14(3), pages 368-386, October.
    6. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    7. O’Donnell, C.J., 2016. "Using information about technologies, markets and firm behaviour to decompose a proper productivity index," Journal of Econometrics, Elsevier, vol. 190(2), pages 328-340.
    8. Zhao, Tianyu & Yan, Na & Ji, Liya, 2023. "Digital transformation, life cycle and internal control effectiveness: Evidence from China," Finance Research Letters, Elsevier, vol. 58(PA).
    9. Huong Vu & Tuyen Quang Tran & Tuan Nguyen & Steven Lim, 2018. "Corruption, Types of Corruption and Firm Financial Performance: New Evidence from a Transitional Economy," Journal of Business Ethics, Springer, vol. 148(4), pages 847-858, April.
    10. Jens Dibbern & Rudy Hirschheim, 2020. "Introduction: Riding the Waves of Outsourcing Change in the Era of Digital Transformation," Progress in IS, in: Rudy Hirschheim & Armin Heinzl & Jens Dibbern (ed.), Information Systems Outsourcing, edition 5, pages 1-20, Springer.
    11. Sadok El Ghoul & Omrane Guedhami & Yongtae Kim, 2017. "Country-level institutions, firm value, and the role of corporate social responsibility initiatives," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 48(3), pages 360-385, April.
    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. Van, Huong Vu & Ly, Kim Cuong, 2021. "Does rising corporate social responsibility promote firm tax payments? New perspectives from a quantile approach," International Review of Financial Analysis, Elsevier, vol. 77(C).
    2. Michael T. Kiley, 2024. "Growth at risk from climate change," Economic Inquiry, Western Economic Association International, vol. 62(3), pages 1134-1151, July.
    3. Martina Pons, 2022. "The impact of air pollution on birthweight: evidence from grouped quantile regression," Empirical Economics, Springer, vol. 62(1), pages 279-296, January.
    4. Yu-Yen Ku & Tze-Yu Yen, 2016. "Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-33, September.
    5. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    6. Machado, José A.F. & Santos Silva, J.M.C., 2019. "Quantiles via moments," Journal of Econometrics, Elsevier, vol. 213(1), pages 145-173.
    7. Minh, Thanh Nguyen & Kim, Van Pham Thi & Ngoc, Anh Mai, 2021. "Political connections, government support and SME tax payments: A note from fixed-effect quantile regression," Finance Research Letters, Elsevier, vol. 40(C).
    8. Vial, Virginie & Hanoteau, Julien, 2015. "Returns to Micro-Entrepreneurship in an Emerging Economy: A Quantile Study of Entrepreneurial Indonesian Households’ Welfare," World Development, Elsevier, vol. 74(C), pages 142-157.
    9. Neil Foster-McGregor & Anders Isaksson & Florian Kaulich, 2014. "Outward Foreign Direct Investment, Exporting and Firm-Level Performance in Sub-Saharan Africa," Journal of Development Studies, Taylor & Francis Journals, vol. 50(2), pages 244-257, February.
    10. Neil Foster-McGregor & Anders Isaksson & Florian Kaulich, 2014. "Importing, exporting and performance in sub-Saharan African manufacturing firms," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 150(2), pages 309-336, May.
    11. Montresor, Sandro & Vezzani, Antonio, 2015. "The production function of top R&D investors: Accounting for size and sector heterogeneity with quantile estimations," Research Policy, Elsevier, vol. 44(2), pages 381-393.
    12. Dogan, Eyup & Altinoz, Buket & Tzeremes, Panayiotis, 2020. "The analysis of ‘Financial Resource Curse’ hypothesis for developed countries: Evidence from asymmetric effects with quantile regression," Resources Policy, Elsevier, vol. 68(C).
    13. Bargain, Olivier & Etienne, Audrey & Melly, Blaise, 2021. "Informal pay gaps in good and bad times: Evidence from Russia," Journal of Comparative Economics, Elsevier, vol. 49(3), pages 693-714.
    14. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, Center for Economic and Financial Research (CEFIR).
    15. Fernández-Val, Iván & Gao, Wayne Yuan & Liao, Yuan & Vella, Francis, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," IZA Discussion Papers 15236, Institute of Labor Economics (IZA).
    16. Harding, Matthew & Lamarche, Carlos, 2019. "A panel quantile approach to attrition bias in Big Data: Evidence from a randomized experiment," Journal of Econometrics, Elsevier, vol. 211(1), pages 61-82.
    17. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    18. Razzaq, Asif & Ajaz, Tahseen & Li, Jing Claire & Irfan, Muhammad & Suksatan, Wanich, 2021. "Investigating the asymmetric linkages between infrastructure development, green innovation, and consumption-based material footprint: Novel empirical estimations from highly resource-consuming economi," Resources Policy, Elsevier, vol. 74(C).
    19. Battagliola, Maria Laura & Sørensen, Helle & Tolver, Anders & Staicu, Ana-Maria, 2022. "A bias-adjusted estimator in quantile regression for clustered data," Econometrics and Statistics, Elsevier, vol. 23(C), pages 165-186.
    20. Bargain, Olivier & Etienne, Audrey & Melly, Blaise, 2018. "Public Sector Wage Gaps over the Long-Run: Evidence from Panel Administrative Data," IZA Discussion Papers 11924, Institute of Labor Economics (IZA).

    More about this item

    Keywords

    Digital transformation; Financial performance; Fixed effect quantile regression; Vietnam;
    All these keywords.

    JEL classification:

    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D25 - Microeconomics - - Production and Organizations - - - Intertemporal Firm Choice: Investment, Capacity, and Financing

    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:eee:finlet:v:64:y:2024:i:c:s1544612324004604. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.