AccScience Publishing / AJWEP / Online First / DOI: 10.36922/AJWEP025430333
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ORIGINAL RESEARCH ARTICLE

How corporate social responsibility improves green transformation technologies inventory output: Evidence from Japanese companies

Jiaming Jiang1* ,  Yu Zhao2 ,  Junshi Feng3
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1 School of Information and Data Sciences, Nagasaki University, Nagasaki, Japan
2 Department of Management, School of Management, Tokyo University of Science, Tokyo, Japan
3 School of International Economics and Trade, Jilin University of Finance and Economics, Changchun, Jilin, China
AJWEP, 025430333 https://doi.org/10.36922/AJWEP025430333
Received: 24 October 2025 | Revised: 19 December 2025 | Accepted: 26 December 2025 | Published online: 15 January 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

Corporate social responsibility (CSR) refers to businesses’ contributions to sustainable development. Today, it is expected that economic, social, and industrial structures that have long depended on fossil fuels will ultimately transition to clean energy-driven structures, and that green transformation (GX) will be achieved through an overall transformation of economic and social systems. To the best of our knowledge, this study is the first to examine the relationship between the CSR of Japanese companies and their GX inventory output (GXIO). Using machine learning algorithms, we tested the hypothesis that CSR activities influence GXIO at both the individual company and the overall industry levels. The results of our empirical analysis show that CSR not only affects GXIO but also has significant effects at the individual company and overall industry levels. These results are used to provide decision makers with useful guidelines for integrating social sustainability into procurement procedures.

Graphical abstract
Keywords
Social responsibility
Green transformation technology
Innovation
Japanese corporations
Statistical analysis
Environment
Patent
Machine learning
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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Asian Journal of Water, Environment and Pollution, Electronic ISSN: 1875-8568 Print ISSN: 0972-9860, Published by AccScience Publishing
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