Unlocking ESG Performance Through Intelligent Manufacturing: The Roles of Transparency, Green Innovation, and Supply Chain Collaboration

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

• The abstract must be slightly changed and refined based on the research results.
• Did the announcement of China's goal of promoting ECG strategies run parallel to the other 50 countries worldwide, or was it separate? Please give us some literature sources, especially if there are differences or similarities.
• The terms intelligent and smart production have other specific applications and significance regarding production processes and supply chains. Please give us a more precise connection between Industry 4.0 and intelligent and smart manufacturing.
• Can you tell us which technologies are used for intelligent and which for smart manufacturing and whether there is such a division or is it intertwined?
• You mention the optimization of production processes. How do you see the application of the circular economy as a business model in this context?
• Is there a connection between Resource Dependence Theory and elements of the circular economy? You have listed all the elements of the model in great detail without any literature coverage.
• Suddenly, the term intelligent equipment appears. Please provide some clarification regarding this term.
• Give concrete examples of information transparency in improving corporate social responsibility. In which fields is this reflected the most? Does it mean the type of production, supply chain, product brand, and investment in information security?
• What is the role of artificial intelligence in this matter, and how does it manifest itself in the new approach of Industry 5.0? A brief explanation, please!
• You wrote that intelligent manufacturing improves the efficiency of green innovation through the facilitation effect of technologies and the effect of cost reduction. Can you give a parallel with today's application of additive technologies and the impact of those technologies in terms of cost reduction?
• It is mentioned that simulation and cooperation with customers and other actors in implementing green technology are essential. Give us concretely what you mean by that term, and give us a summary of what the steps would be.
• When you mention supply chains, have you considered implementing Lean manufacturing tools? Could you provide some link between lean and intelligent manufacturing here?
• Suggestion: Equation 3 should be equated so that it is in a series like equations 1 and 2.
• You used a two-way fixed-effects model. Please tell us why this model?
• Figure 2 needs a good explanation. I think the elements of this block diagram should have been put somewhat in the introduction as the elements under consideration. However, it is not problem to explain in detail here either. (Fascinating and helpful map).

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This work examines how Intelligent Manufacturing (IM) influences corporate Environmental, Social, and Governance (ESG) performance through mechanisms such as information transparency, green innovation, and supply chain collaboration. While the study addresses an important topic, its contributions are not clearly distinguished from existing literature, and there is some overlap with prior work. Overall, the paper is structured adequately, but significant revisions are needed to address the methodological and conceptual concerns outlined below before it can be reconsidered for publication.

1- The study overlaps with existing literature, but its unique contributions could be better highlighted. Specifically, the authors should differentiate how this research extends prior works like Shen et al. (2019) or Chen (2023) by focusing on the mediating mechanisms and heterogeneity of IM's impact on ESG.

Address the apparent overlap in experimental design with prior studies (e.g., Chen, 2023), ensuring that due credit is given and originality is maintained.

 2- The selection of IM keywords and their frequency as a proxy for IM implementation requires further justification. The authors should provide a detailed explanation of how the keywords were chosen and validated.

Address the limitations of using the Huazheng ESG index alone as a measure of ESG performance, suggesting potential triangulation with other indexes like Bloomberg ESG.

3- The description of the model construction is unclear, particularly the rationale behind the choice of mediating variables. The authors should elaborate on the theoretical grounding for including specific mediators such as green technology innovation and information transparency.

Explicitly state the assumptions of the two-way fixed-effects model used in the study and provide evidence that these assumptions hold.

4- While endogeneity concerns are addressed using instrumental variables, the validity and limitations of these instruments should be explained. Additionally, consider incorporating alternative robustness checks like propensity score matching.

Broaden the heterogeneity analysis to explore why certain industries (e.g., high-carbon sectors) experience amplified effects from IM.

 

5- According to AI content detection tools, 56% of the text may be flagged as AI-generated. This may raise concerns regarding originality and quality. A thorough rewrite of flagged sections to ensure clarity and human-authored precision is necessary.

 

6- The tables are overly complex and difficult to interpret. Simplify the structure and ensure consistency in formatting across all figures and tables.

Add detailed captions summarizing key findings for figures and tables to make them more reader-friendly.

7- Provide specific policy examples to illustrate how fiscal incentives like tax breaks or subsidies have successfully driven IM adoption in various industries.

Expand on limitations, particularly regarding the study's focus on Chinese listed firms, and suggest future directions for research in global and private-sector contexts.

 8- Confirm that all referenced studies are appropriately cited, including Shen et al. (2019) and Chen (2023). If the experimental design is highly similar, explicitly state the differences and contributions of this study.

 

[1]        Shen, Yan, Yun Chen, and Zhuo Huang. "Application of text big data analysis in economics and finance: A literature review." Economic Quarterly 4 (2019): 1153-1186.

 

[2]        Chen, Shu. "How Does Digital Technology Drive Total Factor Productivity in Enterprises? Empirical Evidence from Text Analysis." Open Journal of Business and Management 11.5 (2023): 2525-2554.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors could successfully address the initial comments.