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Advances in Decision Sciences (ADS)

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Effects of Digital Transformation and Green Technology Innovation on Manufacturing’s Financial Performance: Evidence from China

Effects of Digital Transformation and Green Technology Innovation on Manufacturing's Financial Performance: Evidence from China

Title

Effects of Digital Transformation and Green Technology Innovation on Manufacturing’s Financial Performance: Evidence from China

Authors

  • Caiqing Liang
    Faculty of Forestry and Environment, University Putra Malaysia, Malaysia. , Faculty of Economics and Management, BoZhou University, China
  • Mohd Rusli Yacob
    Faculty of Forestry and Environment, University Putra Malaysia, Malaysia
  • Siong Hook Law
    School of Business and Economics, Universiti Putra Malaysia, Malaysia
  • Irina Harun
    Faculty of Forestry and Environment, University Putra Malaysia, Malaysia

Abstract

Purpose: This study aims to examine the impact of digital transformation on the financial performance of manufacturing firms, with a particular focus on the mediating role of green technology innovation.
Design/methodology/approach: This study employs panel data from Chinese A-share manufacturing firms spanning 2013 to 2022. A fixed-effects model and a mediation model are constructed to analyze the relationships, and the Driscoll-Kraay standard errors are applied to address potential cross-sectional dependence and autocorrelation, ensuring robust estimation of the effects of digital transformation and green technology innovation on financial performance.
Findings: The results reveal that digital transformation significantly enhances the financial performance of manufacturing firms. These findings remain robust across alternative dependent variables, exclusion of specific samples, and the inclusion of additional control variables. Furthermore, green technology innovation serves as a mediating mechanism in this relationship, accounting for approximately 5.1% of the total effect. Heterogeneity analysis further suggests that the positive impact of digital transformation is more pronounced in state-owned enterprises (SOEs), large-scale firms, and those located in China’s central and western regions.
Research limitations/implications: Corporate financial performance is shaped by a wide range of factors, yet this research focuses primarily on digital transformation and green innovation. Future studies could extend this scope by incorporating additional determinants such as artificial intelligence adoption and environmental regulation. Moreover, although the measurement of digital transformation in this study is relevant and widely used, it may not fully capture the depth of firms’ digitalization.
Originality/value: This research clarifies the mediating mechanism and transmission pathway through which digital transformation affects corporate financial performance, thereby addressing a critical gap in the literature regarding the performance–transformation–innovation nexus. By introducing an integrated framework that connects digital capabilities with innovation efficiency, the study offers new theoretical and empirical insights distinct from prior works. The findings provide actionable guidance for managers and policymakers to leverage digital capabilities and enhance innovation efficiency to improve corporate financial outcomes.

Keywords

digital transformation, financial performance, green technology innovation, manufacturing enterprises, Driscoll-Kraay estimator, China

Classification-JEL

B26, Q55

Pages

92-119

How to Cite

Liang, C., Yacob, M. R., Law, S. H., & Harun, I. (2024). Effects of Digital Transformation and Green Technology Innovation on Manufacturing’s Financial Performance: Evidence from China. Advances in Decision Sciences, 28(4), 92-119.

https://doi.org/10.47654/v28y2024i4p92-119

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ISSN 2090-3359 (Print)
ISSN 2090-3367 (Online)

Scientific and Business World

Asia University, Taiwan

8.3
2024CiteScore
 
88th percentile
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SCImago Journal & Country Rank
Q2 in Scopus
CiteScore 2024 = 8.3
CiteScoreTracker 2025 = 8.2
SNIP 2024 = 0.632
SJR Quartile = Q1
SJR 2024 = 0.814
H-Index = 18

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