How Does the Low-Carbon City Pilot Policy Affect Enterprises’ Green Innovation? Empirical Evidence from the Context of China’s Digital Economy Development

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. 1. While this paper exhibits research value and novelty, there is room for improvement in the discussion on marginal contribution. The authors should focus on enhancing the clarity of the paper's incremental significance, particularly within the introduction.

2. 2. The literature employs the mediation effect model for the mechanism test, but fails to provide a specific model formula. This omission hinders the understanding of the conduction path. It is advisable for the authors to elucidate the formula of the mediated effect model in the mechanism test section to enhance comprehension.

3. 3. In the section dedicated to heterogeneity analysis, further clarification is needed regarding the construction methods of indicators such as financing constraints, types of production factors, and the level of regional digital economy. Providing detailed insights into these aspects will enhance the overall robustness of the analysis.

4. 4. It is recommended that the authors incorporate mathematical results in the conclusion to elucidate the impact of low-carbon pilot city policies on the level of green innovation of enterprises. This inclusion will render the findings more transparent and intuitive, contributing to a clearer understanding of the paper's implications.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

After reviewing the article "How Does the Low-Carbon City Pilot Policy Affect Enterprises’ Green Innovation? Empirical Evidence from the Context of China’s Digital Economy Development," the article provides a comprehensive and empirical analysis of the impact of China's Low-Carbon City Pilot Policy on green innovation in enterprises. The use of panel data from 2003 to 2021 and the application of a difference-in-differences (DID) approach adds rigor to the research methodology. The focus on the digital economy context is timely and relevant, offering insights into the intersection of environmental policy and digital transformation.

Here are some suggestions for Improvement:

1. The theoretical framework could be expanded to include more diverse perspectives on green innovation, especially in relation to digital transformation. Please refer to https://doi.org/10.1057/s41599-023-02250-4.

2. While the methodology is robust, the article could benefit from a more detailed explanation of the choice of control variables and their relevance to the study. 

3. The discussion section could be enhanced by drawing more explicit connections between the findings and their implications for policy and practice in other contexts beyond China. Please refer to  https://doi.org/10.1016/j.jclepro.2022.135336

Given the relevance and methodological strength of the study, I would recommend accepting the article with minor revisions. The suggested improvements mainly pertain to expanding the theoretical discussion and providing more detailed justifications for methodological choices.  Please refer to https://doi.org/10.1002/bse.3664 

The article makes a significant contribution to the understanding of environmental policy impacts in the context of China's digital economy, offering valuable insights for policymakers and businesses. With minor improvements, it could provide a more comprehensive perspective on this critical issue.

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

 

1.    The paper examines a significant issue that offers a contribution to the literature of sustainable development. It is indeed a major step forward for China’s concerns and Green Innovation

2.    The paper is well organized, and the literature review is relevant to the topic of the paper.

3.    In p. 6, the estimation models require prerequisite tests to offer sufficient information about model identifications. These tests include linearity Vs non-linearity (RESET test), Fixed Vs Random Effects (using Hausman test), Heteroskedasticity tests (using Breusch-Pagan/ Cook-Weisberg test).

4.     As far as the “Empirical Results,” show, the estimation model is OLS. These must be justification of why it is used. In addition, the F stat, and p-value must be reported to tell the reader whether any of these models is significant, and at what level.

Author Response

Please see the attachment.

Author Response File: Author Response.docx