Promoting economic recovery: the silver lining of digital transformation and corporate innovation
Abstract
With the unstable international environment, the global economy has experienced a slowcession. Previous research on digital innovation in firms has often neglected the impact of macroeconomic cycles. This paper examines the moderating effect of the economic slowcession in the digital transformation and corporate innovation nexus, by using the China’s A-share listed companies’data during 2001 and 2021. The empirical results find that the positive impact of digitization on innovation is countercyclical. During recession, the positive impact of digital transformation on innovation is even greater compared to economic prosperity. Grouped regression results indicate that State-owned listed companies, Non-high tech companies, Large-scale companies, and Eastern companies are more affected by the positive moderating effect of the recession. This indicates that getting out of recession requires more aggressive support of these companies, which promotes innovation and economic recovery. This study provides a useful reference for countries in recession and provides an important complement to traditional economic cycle theory and innovation cycle theory.
First published online 15 November 2024
Keyword : digital transformation, corporate innovation, recession, corporate heterogeneity
How to Cite
Du, Z.-Y., & Wang, Q. (2024). Promoting economic recovery: the silver lining of digital transformation and corporate innovation. Technological and Economic Development of Economy, 1-26. https://doi.org/10.3846/tede.2024.22019
This work is licensed under a Creative Commons Attribution 4.0 International License.
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Ertugrul, M., Lei, J., Qiu, J., & Wan, C. (2017). Annual report readability, tone ambiguity, and the cost of borrowing. Journal of Financial and Quantitative Analysis, 52(2), 811–836. https://doi.org/10.1017/S0022109017000187
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Harrison, R., Li, Y., Vigne, S. A., & Wu, Y. (2022). Why do small businesses have difficulty in accessing bank financing? International Review of Financial Analysis, 84, Article 102352. https://doi.org/10.1016/j.irfa.2022.102352
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. The Guilford Press.
He, Z., Huang, H., Choi, H., & Bilgihan, A. (2022). Building organizational resilience with digital transformation. Journal of Service Management, 34(1), 147–171. https://doi.org/10.1108/JOSM-06-2021-0216
Hodder, A. (2020). New technology, work and employment in the era of COVID-19: Reflecting on legacies of research. New Technology, Work and Employment, 35(3), 262–275. Scopus. https://doi.org/10.1111/ntwe.12173
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Im, H. J., & Shon, J. (2019). The effect of technological imitation on corporate innovation: Evidence from US patent data. Research Policy, 48(9), Article 103802. https://doi.org/10.1016/j.respol.2019.05.011
Jae-Hoon, S. (2018). An empirical analysis of FDI, human capital and China’s regional economic growth. The Journal of Eurasian Studies, 15(4), 43–56. https://doi.org/10.31203/aepa.2018.15.4.003
Jiang, K., Du, X., & Chen, Z. (2022). Firms’ digitalization and stock price crash risk. International Review of Financial Analysis, 82, Article 102196. https://doi.org/10.1016/j.irfa.2022.102196
Khan, A., & Tao, M. (2022). Knowledge absorption capacity’s efficacy to enhance innovation performance through big data analytics and digital platform capability. Journal of Innovation & Knowledge, 7(3), Article 100201. https://doi.org/10.1016/j.jik.2022.100201
Kilic, E., & Cankaya, S. (2016). Consumer confidence and economic activity: A factor augmented VAR approach. Applied Economics, 48(32), 3062–3080. https://doi.org/10.1080/00036846.2015.1133902
Kim, J. (2016). Consumer confidence and economic activity: What causes what? Korea and the World Economy, 17(2), 183–212.
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