A Study of the Non-Linear Impact of Climate Policy Uncertainty on Enterprises’ Technological Innovation Based on China’s Industrial Enterprise Digital Peer Effect

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper investigates the effect of climate policy uncertainty (CPU) on technological innovation using panel data from Chinese A-share industrial enterprises (2007–2023), where a nonlinear (inverted U-shaped) relationship was identified and the mediating variable -- digital peer effect -- is confirmed through solid econometric analysis, including empirical regresions and robustness checks.

This paper is well-written and the results are clearly presented: (1) It identifies a nonlinear relationship between CPU and technological innovation; (2) It incorporates the digital peer effect to assess heterogeneous responses to policy uncertainty. These make this paper worth publicating. Below are my two major suggestions.

(1) The data source should be described more clearly. For instance, is the CPU index re-constructed by the authors or drawn from existing work ([28])?

(2) The authors may consider adding a significance test (e.g., Sobel test) to improve the statistical rigor of the mediation analysis.

Author Response

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Reviewer 2 Report

Comments and Suggestions for Authors

The paper investigates the non-linear relationship between climate policy uncertainty and firms’ technological innovation, incorporating the moderating role of digital peer effects. 

However, the manuscript still has several important shortcomings related to causal identification, measurement robustness, and theoretical clarity. Addressing these issues would significantly enhance the credibility and scholarly contribution of the study. I recommend major revision.

1. The study mainly relies on observational associations and lagged specifications to infer causality. However, without a stronger identification strategy, the causal interpretation of climate policy uncertainty’s impact on innovation remains questionable. construct stronger instrumental variables. Otherwise, frame the findings more cautiously as associations rather than causal effects.
2. The model imposes a one-year lag between uncertainty and innovation responses without testing whether this lag is appropriate.
3. The moderating role of the digital peer effect is modeled as exogenous, but firms may self-select into high-digitalization environments, creating endogeneity.
4. The innovation measure based on patent counts and R&D intensity may not fully capture innovation quality or commercial success.
5. While the inverted U-shaped relationship is proposed, the critical turning point and slope tests are not systematically reported. Report the estimated turning point, confirm slopes before and after the turning point, and include marginal effects plots for visualization.
6. The digitalization index is treated as a black box without detailed discussion of whether it captures basic ICT use or advanced digital technologies.
7. The study’s findings are based on Chinese industrial firms, yet broader conclusions are drawn without discussing potential limitations in other contexts.

Comments on the Quality of English Language

Reduce to use too complicated expression

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

The paper ‘A Study of the Non-linear Impact of Climate Policy Uncertainty on Enterprises’ Technological Innovation: Based on China's Enterprise Digital Peer Effect' tackles an interesting research topic. The authors focused their attention on the problem of the impact of climate policy uncertainty on corporate technological innovation. A comprehensive dataset was used to investigate the impact of this uncertainty on selected listed companies in China over the period 2007-2023. The results of the findings lead to multi-faceted conclusions confirming the extent and scale of the impact of climate policy on corporate innovation. This is an interesting study.
The abstract of the paper presents the purpose of the study and its scope. The abstract should point out the gap in the literature that the paper responds to. Much attention is given in the abstract to the agreement of the findings. Too little prominence is given to the methodology used, which needs to be supplemented.  

The introduction raises issues presenting the background of the research, pointing to the issue of digital and low-carbon economies in light of the challenges of climate policy. In discussing the research background, the authors indicate the scope of the research of the reviewed paper. The authors also highlight the importance of the conclusions reached, which should not be the case in the introduction (summary and conclusion), and therefore this aspect should be removed from the introductory content. In this respect, the introduction should be improved.
The introductory content and the scope of the literature review should be expanded. It is worth pointing out global observations in terms of the challenges of innovative sustainability-oriented companies. It is worthwhile to move from global experiences to the companies under study. There is a recent literature in this area. It is worth studying, among others, https://doi.org/10.3390/su17062417, or https://doi.org/10.3390/su17020454. The above will strengthen the cognitive value of the study and allow to reinforce the range of sources that need strengthening.
In the next section of the study, the authors defined 6 hypotheses. The hypotheses were developed with reference to the literature, which is correct. The Authors then presented Figure 1 ‘Mechanisms for the impact of climate policy uncertainty on firms’ technological innovation capabilities’ - lines 231, which needs more discussion, which should be completed.

Section 3 discusses ‘Research Methodology’, where the sources of Variables and Data are explained, with a breakdown of the types of variables. This was followed by a discussion of the research model adopted for the study, which was presented with reference to the literature. The next section of the paper in this area is devoted to discussing the scope and presenting the results of the Descriptive Statistics and Correlation Test. The discussion section of the paper is prepared correctly. The discussion is clear and detailed. I do not bring additional observations to this section.
The empirical tests in Section 4 need to be supplemented by a more extensive discussion of the results presented in Tables 4-8 below the tables, for greater readability of the results presented.
The discussion section should precede the summary, rather than being part of it. The section further needs to be expanded and a stronger discussion of the results of the authors' findings against the background of alternative literature. The above should be supplemented.

The summary of the paper needs to be developed. The summary should more strongly emphasise the study's contribution to the existing literature in response to the diagnosed gap. The above I suggest should be improved.
Also.
The literature is well selected but should be strengthened.
In conclusion. The paper needs some improvement before publication. The abstract, introduction, and research section need improvement. The structure of the paper needs refinement - the discussion section should not be an integral part of the summary. In addition, the summary should be developed. Detailed suggestions are included in the body of the review.

Author Response

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Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors,

I have been invited to review your paper "A Study of the Non-linear Impact of Climate Policy Uncertainty on Enterprises' Technological Innovation: Based on China’s Enterprise Digital Peer Effect"

I have the following comments and recommendations:

• Title:

It is not clear to me why you include in the title non-linear. Please explain and reconsider this. Moreover, in the title you refer to enterprises technological innovation while your paper focuses exclusively on industrial enterprises and the text refers to corporate technological innovation. Please revise the title and the text and make sure you are consistent throughout the paper.

• Introduction:

Please revise the introduction and make sure you provide a definition (and reference(-s)) of such key concepts as CPU, currently missing from the paper.

Moreover, it would be of critical importance that you provide relevant reference(-s) to substantiate the statements contained in your paper, if they are based on prior research. See, for instance, lines 31-34, 37-38, 52-55, 60-66, etc.

Please include an explanation on the rationale to focus your research on China.  

Please revise the whole text and ensure consistency in the terms and definitions used, e.g., technological innovation vs digital technological innovation.

Please revise the introduction and clarify whether your research focus is based on the backdrop of the digital and low-carbob economies (line 74) or a gap identified in the literature.

• Theory, literature review and Research hypotheses

Please ensure relevant references are included, e.g., lines 103-105, 115-116,118-2121, 124-128, 129-131, etc.

Figure 1 refers to non-linear effects. This is not explained at all in the text. Please revise the text and introduce the rationale and approach.

Please explain what is SA index, see line 290.

Table 1, you might to indicate the various sources of data (for each variable) you use for your research. 

• Conclusions:

Please revise the text and make sure it is clear to the reader that your conclusions are limited to the case of China.

All suden you refer to the non-linear impact of climate policy uncertainty in line 565 onwards. As previously requested, please explain this in the text from the outset, provide the audience with the rationale for this choice.

Also, please revise the text and make sure you use capital letters in a consistent manner throughout the text, e.g. Climate Policy Uncertainty vs climate policy uncertainty.

Future prospects: Has a similar analysis been conducted in other countries/ regions?

Thank you and best regards,

Anonymous reviewer

Author Response

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Reviewer 5 Report

Comments and Suggestions for Authors

Review Report

 A Study of the Non-linear Impact of Climate Policy Uncertainty on Enterprises' Technological Innovation: Based on China’s Enterprise Digital Peer Effect

(sustainability-3598459-peer-review-v1)

The paper examines a significant issue that offers a contribution to the literature that connects corporate business of climate policy uncertainty. The paper is well organized, and the literature review is relevant to the topic of the paper.

1. In the description of data, p. 6, line 240, the authors “excluded certain companies due to abnormal financial conditions.” Please mention specifically, how did you assess the “abnormal”, and what are the “financial conditions”? these are very sensitive issues in the description of data to ensure survivorship. These issues are not as easy as they seem.
2. Since the paper examines technological innovations, the authors must also present evidence of the extent to which the companies included in the study (3773) embrace “technological innovations.”
3. In line 253 – 261, please quote references to the show the relevance of using entropy weight method.
4. In this paper, the CPU is news-based, which has similar constructions as the EPU. In this sense, it is fine. Nevertheless, in this topic, the world bank database has many indicators of climate change. It would be quite informative that the authors justify the use of Ma et al., (2023) index rather than other well-known indicators of climate change.
5. I am afraid the choice of all independent variables is free from any theoretical ground… pp. 7-9 do not include one single reference, or even justifications how are these variables drawn? The same is true for using mediating variables. There must be an empirical justification of using mediation analysis.
6. In line 347, along with table 3, the correlation matrix must be replaced with the VIF, which is a well-known measure of multicollinearity.
7. The model specification does not show whether standard specification tested were carried out such as linearity Vs non-linearity (RESET test), Fixed Vs Random Effects (using Hausman test), Heteroskedasticity tests (using Breusch-Pagan/ Cook-Weisberg test).
8.  In a standard regression reporting, adjusted R square (table, 4) must be reported especially that the number of independent variables is small. Likewise, there must be a metric of significance. How can we tell whether the regression models are significant.

Author Response

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Reviewer 6 Report

Comments and Suggestions for Authors

The research investigates how climate policy uncertainty (CPU) affects enterprises' technological innovation activities, examining whether this relationship is non-linear (specifically, an inverted U-shaped pattern), and explores the moderating role of the digital peer effect.

The topic is relevant and relatively original.

It adds the idea that moderate uncertainty may stimulate innovation.

Offer stronger justification for the methods used.

Discussion of limitations is lacking and should be addressed to balance the conclusions.

Lacks engagement with recent international studies.

Similarity is 28.6%, it must be reduced under 15%.

Author Response

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Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have improved the article. 

Reviewer 6 Report

Comments and Suggestions for Authors

every remark has been implemented as advised