Ambidextrous Innovation, Organizational Resilience, and the High-Quality Development of Enterprises: A Dynamic Analysis Based on the Enterprise Life Cycle

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for inviting me to review this paper. I think this study is very interesting and the author has put in a lot of effort. My revision suggestions are as follows:

1. The abstract section needs to be streamlined.
2. The article lacks a literature review section.
3. Endogeneity and robustness tests need to be supplemented. The lagged core explanatory variable as an instrumental variable is not scientific, and the author needs to strengthen the testing in this regard.
4. Before conducting regression analysis, the author should test for multicollinearity among variables.
5. The T-values of the regression analysis results are generally large, and the author needs to consider the accuracy of the data carefully.

Author Response

Comment 1: The abstract section needs to be streamlined.

Response 1: Thank you for pointing this out, we agree with this comment. To address this, We have taken it seriously and made corresponding revisions. Here are the details of the modifications.（1）For the research background part, we realized that the original abstract contained some overly elaborate descriptions that were not essential for quickly grasping the core idea of the study. Hence, we carefully pruned those details and retained only the key elements that directly set the stage for our research topic. （2）Regarding the research results, we simplified the presentation to make it more straightforward and to the point. Instead of elaborating on each finding in a complex manner, we extracted the most significant and conclusive aspects.

Comment 2: The article lacks a literature review section.

Response 2: Thank you for your valuable comment, we agree with this comment. We sincerely appreciate this valuable feedback. In response, we have thoroughly reexamined and systematically reorganized the relevant literature. A dedicated and comprehensive literature review section has been added to the manuscript, which can be found on pages 1-2. In this section, we have carefully selected and critically analyzed the most relevant and recent studies aligned with our core research themes: ambidextrous innovation, organizational resilience, and enterprise high-quality development. This addition not only strengthens the theoretical foundation of our research but also clearly positions our study within the existing body of knowledge,

Comment 3: Endogeneity and robustness tests need to be supplemented. The lagged core explanatory variable as an instrumental variable is not scientific, and the author needs to strengthen the testing in this regard.

Response 3: Thank you for pointing this out, we agree with this comment. We sincerely appreciate this insightful comments. We acknowledge that using the lagged core explanatory variable as an instrumental variable may lack scientific validity. After careful consideration and further analysis, and in alignment with suggestions from another reviewer, we have decided to remove this approach from our model. To address endogeneity more effectively, we have reconstructed our methodology by adopting the two-stage least squares (2SLS) method (see page 16), which provides a more robust and scientifically sound analysis. To further strengthen the reliability of our findings, we have conducted comprehensive robustness tests. Specifically, we employed the replacement of explained variable measures to verify the stability and consistency of our results. These revisions aim to ensure the robustness and credibility of our conclusions.

Thank you again for your professional advice.

Comment 4: Before conducting regression analysis, the author should test for multicollinearity among variables.

Response 4: Thank you for your valuable comment, we agree with this comment. To address this, we have conducted the Variance Inflation Factor (VIF) test to assess multicollinearity among the variables prior to performing regression analysis. The results of the VIF test are presented in Table 5 (see Page 11). All VIF values for the variables are significantly below the commonly used threshold, indicating that there is no serious multicollinearity issue in our model. This ensures the reliability and validity of our subsequent regression analysis.

 Comment 5: The T-values of the regression analysis results are generally large, and the author needs to consider the accuracy of the data carefully.

Response 5: Thank you for your valuable comment, we agree with this comment. This comment has prompted us to thoroughly re-examine our data and analytical processes. During the data collection stage, we strictly followed scientific norms, obtained data from multiple channels and repeatedly checked them. When entering the data, we also arranged for dedicated personnel to conduct verification to ensure its accuracy as much as possible. Regarding the relatively large T-values, we have re-examined the entire analysis process and haven't found any obvious mistakes for now. Our preliminary speculation is that it might be caused by the relatively strong correlation among variables. In the follow-up, we will carefully check the data again and verify its accuracy from different perspectives, such as using other statistical tools for cross-validation. If any problems are found, we will promptly correct them and re-evaluate the results to ensure the rigor and reliability of our research.

Thank you again for your constructive feedback, which has significantly contributed to enhancing the quality and reliability of our research.

 

 

 

Reviewer 2 Report

Comments and Suggestions for Authors

This paper explores the mechanism by which ambidextrous innovation affects the high-quality development of enterprises through organizational resilience based on the data of Chinese A-share listed companies, which has certain theoretical and practical significance. However, it still needs to be further revised and improved in the following aspects:

(1) The definition of high-quality enterprise development in the paper is not clear enough. Is high-quality development only "the improvement of firm total factor productivity"? High-quality development should also include other dimensions, such as environmental sustainability, social responsibility fulfillment, and employee satisfaction. Theoretical review and concept definition in this regard need to be strengthened.

(2) The paper compares the different promoting effects of exploratory innovation and exploitative innovation on high-quality development at different stages of the enterprise life cycle. This comparison is only judged by comparing the size of regression coefficients in the empirical analysis, but the size of regression coefficients cannot directly indicate the magnitude of the effect. A T-test comparison should also be conducted.

(3) There are significant differences in total factor productivity, as well as the indicators of exploratory innovation and exploitative innovation such as invention patents and utility model patents involved in the paper between manufacturing enterprises and service enterprises. It is necessary to add a comparison and discussion of industry differences.

(4) The description of the measurement of organizational resilience in the paper is not clear enough. It is necessary to clearly explain which references are referred to for specific modifications and adjustments and why such a measurement method is adopted.

(5) References published in Chinese account for a relatively large proportion in the references cited in the paper, and some of them are not from core journals. It is recommended to cite authoritative journals as much as possible to increase the validity and persuasiveness of the paper.

 

Comments on the Quality of English Language

There are still some minor issues with the English expression in this paper, and a detailed check of grammar and expression should be conducted.

Author Response

Comment 1: The definition of high-quality enterprise development in the paper is not clear enough. Is high-quality development only "the improvement of firm total factor productivity"? High-quality development should also include other dimensions, such as environmental sustainability, social responsibility fulfillment, and employee satisfaction. Theoretical review and concept definition in this regard need to be strengthened.

Response 1: Thank you for pointing this out, we agree with this comment. In response to this comments, we have significantly expanded and refined the conceptual framework surrounding high-quality enterprise development. Moving beyond the initial narrow focus on total factor productivity, we have incorporated a more comprehensive perspective that encompasses several critical dimensions of enterprise development. This broader conceptualization provides a more holistic understanding of high-quality development in contemporary enterprises.

The revised theoretical framework and refined conceptual definitions can be found in the enhanced literature review section, specifically between lines 94-103 of the revised manuscript.

 Comment 2: The paper compares the different promoting effects of exploratory innovation and exploitative innovation on high-quality development at different stages of the enterprise life cycle. This comparison is only judged by comparing the size of regression coefficients in the empirical analysis, but the size of regression coefficients cannot directly indicate the magnitude of the effect. A T-test comparison should also be conducted.

Response 2: Thank you for your valuable comment, we agree with this comment. Regarding this comments, we have the following considerations.

In this study, we focused on establishing a preliminary analytical framework to examine the relationship between two types of innovation and high-quality development across different stages, using regression coefficients to indicate direction and approximate magnitude. This approach provides a foundation for future in-depth research.

Due to the uneven distribution of sample data across enterprise life cycle stages, conducting T-tests at this stage could introduce bias and fail to accurately reflect actual effects. Given the study's scope and resource constraints, we prioritized regression analysis to comprehensively assess the combined impacts of multiple factors on high-quality development.

That said, we recognize the value of T-tests for comparing the effects of the two innovation types. In subsequent research, we plan to optimize the sample structure, supplement additional data, and incorporate T-tests to more precisely evaluate the magnitude of their effects.

Thank you again for your professional advice.

 Comment 3: There are significant differences in total factor productivity, as well as the indicators of exploratory innovation and exploitative innovation such as invention patents and utility model patents involved in the paper between manufacturing enterprises and service enterprises. It is necessary to add a comparison and discussion of industry differences.

Response 3: Thank you for pointing this out, we agree with this comment. To address this comment, we have conducted the heterogeneity analysis (see page 20). During this process, we systematically compared and examined multiple dimensions. This in-depth analysis has enabled us to identify and elucidate the fundamental drivers behind the observed differences between manufacturing and service sectors. The insights gained from this heterogeneity analysis not only contribute to the theoretical understanding of industry-specific innovation dynamics but also provide valuable practical implications for guiding enterprise development strategies tailored to different industrial contexts (see lines 800-810).

 Comment 4: The description of the measurement of organizational resilience in the paper is not clear enough. It is necessary to clearly explain which references are referred to for specific modifications and adjustments and why such a measurement method is adopted.

Response 4: Thank you for your valuable comment, we agree with this comment. In response to your comment, we have thoroughly revised the relevant section to provide a clearer and more detailed explanation of our measurement approach. Specifically, on page 7, lines 313-324.

As detailed in the revised manuscript, we conceptualize organizational resilience as a two-dimensional construct comprising high-performance growth and low financial volatility. For measuring long-term performance growth, we employ the three-year cumulative sales revenue growth as the primary indicator, following established academic practices. This approach is preferred over year-on-year growth metrics as it better captures the sustained development trajectory of enterprises. Financial volatility, the second dimension of organizational resilience, is quantified through stock return volatility, calculated as the standard deviation of monthly stock returns over a one-year period, providing a robust measure of financial stability and risk expos.

 Comment 5: References published in Chinese account for a relatively large proportion in the references cited in the paper, and some of them are not from core journals. It is recommended to cite authoritative journals as much as possible to increase the validity and persuasiveness of the paper.

Response 5: Thank you for pointing this out, we agree with this comment. To address this, we have made significant revisions to enhance the quality and relevance of our citations. Specifically, we have:

Added several high-quality English-language references from authoritative journals in relevant fields (see References 2, 4, 10-13, 18, and 39), which have strengthened the theoretical foundation of our research and provided more robust support for our arguments.

Conducted a thorough review of our original reference list and removed citations from non-core journals to ensure the academic rigor and credibility of our work.

These modifications have significantly improved the quality of our reference list and, consequently, the overall academic value of our paper. We believe these changes have enhanced the theoretical depth and persuasiveness of our research. Thank you again for your constructive feedback, which has helped us improve the quality of our manuscript.

Thank you again for your professional advice.

Comment 6: There are still some minor issues with the English expression in this paper, and a detailed check of grammar and expression should be conducted.

Response 6: Thank you for pointing this out, we agree with this comment.  To address this, we have taken the following actions to improve the language quality: We have sought the assistance of a native English-speaking colleague to thoroughly review and polish the entire manuscript. We have carefully checked and improved the grammar, syntax, and overall expression throughout the paper.We have conducted multiple rounds of proofreading to ensure consistency and clarity in language use. Particular attention has been paid to technical terms and academic expressions to ensure they meet international publication standards.

Thank you again for your constructive feedback, which has significantly contributed to enhancing the quality and reliability of our research.

 

 

Reviewer 3 Report

Comments and Suggestions for Authors

PFA my comments.

Comments for author File: Comments.pdf

Author Response

Comment 1: Proof-reading: In general, the manuscript could benefit from being proof-read by a native speaker of the English language. The exercise should aim to address: (1)Reducing the length of some sentences that read very long. This tends to be a common practice in Asia. (2) Reconstructing some sentences with a focus on maintaining active voice.

Response 1:Thank you for your valuable comment, we agree with this comment. To address this, we have taken the following actions to improve the language quality: We have sought the assistance of a native English-speaking colleague to thoroughly review and polish the entire manuscript. We have carefully checked and improved the grammar, syntax, and overall expression throughout the paper.We have conducted multiple rounds of proofreading to ensure consistency and clarity in language use. Particular attention has been paid to technical terms and academic expressions to ensure they meet international publication standards.

 Comment 2: Sample period: Most of the analysis in the paper rests on a ten-year sample from China. Two things become important: (1) Why is it important to study this effect in China? What unique feature (institutional setting) of the market is exploited that is not available in other markets? (2) What is the reason for choosing the cut-off periods as 2012 and 2022, respectively? Does anything prevent the authors from extending the sample on either side? How is the choice of sample selection relevant to the research questions at hand?

 Response 2: Thank you for pointing this out, we agree with this comment.

Response to the Importance of Conducting the Research in China.

Our study focuses on China for several compelling reasons that offer unique theoretical and practical insight.

Firstly, China's vast and rapidly growing economy, characterized by rich and diverse economic activities, provides an ideal research setting. The coexistence of enterprises across various industries and scales offers sufficient and diversified samples, covering complex economic interaction scenarios that are difficult to observe in smaller markets. This diversity enhances the generalizability and robustness of our findings.

Secondly, China's distinctive policy environment, marked by strong guidance and coherence, presents unique research opportunities. The government's implementation of long-term plans and industrial policies, particularly in areas such as technological innovation over the past decade. These policy interventions facilitate our analysis of how such measures affect the generation and transmission of the studied effect, offering insights that might be difficult to obtain in other market economic systems with less pronounced policy backgrounds.

These unique characteristics of the Chinese context not only provide rich empirical material for our study but also offer valuable insights that could contribute to the broader theoretical understanding of these phenomena in emerging markets and transitional economies.

 Response to the Selection of the Sample Period from 2012 to 2022.

The choice of 2012-2022 as our research window was carefully considered based on several important factors that ensure the scientific rigor and contextual relevance of our study.The year 2012 marks a significant turning point as China entered the "New Normal" phase of economic development, characterized by fundamental shifts in economic structure and growth patterns. This period initiated a new economic cycle that culminated in 2022, providing a complete cycle for our analysis.

We have consciously limited our sample to this period for two main reasons: First, data availability and consistency issues in earlier years could compromise the reliability of our analysis. Second, extending beyond 2022 would include an incomplete economic cycle, potentially distorting our findings. This approach ensures the scientific validity of our research while capturing a representative period of China's economic transformation.

We have incorporated this explanation into the manuscript as per your suggestion. For detailed information, please refer to the added content in Lines 280-285 on page 6, where we have provided a comprehensive justification for the selected time frame and its significance to our study.

Thank you again for your professional advice.

 Comment 3: Interpretation of Results: The paper describes the main results along with the significance of relationships. However, the authors should also consider if their findings show a causal relationship or not. Further, please consider distinguishing your claims as mere associations and/or how they differ from potential threats of reverse causality or reverse relationships. I am not asking you to re-perform or introduce new tests. This comment is meant to inspire precise writing and well-defined (albeit limited) claims. Placing relevant disclaimers against causal interpretations may be most helpful to readers.

Response 3: Thank you for pointing this out, we agree with this comment. We have taken your advice seriously and have supplemented the analysis of causal relationships in the paper. Specifically, we have clearly elaborated on both the direct causal connections between relevant variables and the causal chains mediated by other factors. These additional explanations aim to make the nature of the causal relationships in our findings more explicit and comprehensible. We believe these modifications address your concerns and significantly enhance the overall quality of the paper. (See lines 456-461, 484-490, and 519-522 for detailed revisions).

 Comment 4: Multi-collinearity: Table 4 shows strong correlation among many covariates/control variables. Please discuss why (or why not) this may influence the variance-covariance matrix of your main estimators due to multi-collinearity. Shedding light on this basic requirement of the BLUE OLS would enhance the readers’ takeaways from the paper.

Response 4: Thank you for your valuable comment, we agree with this comment. To address this, we have thoroughly addressed this concern through the following steps: We conducted a comprehensive Variance Inflation Factor (VIF) analysis for all covariates in our model. The results, presented in Table 5 (see Page 11), show that all VIF values are well below the threshold of 5. This confirms that multicollinearity does not significantly affect our model.

Thank you again for your professional advice.

Comment 5: Robustness results: It is impressive to see multiple robustness checks undertaken by the authors. However, these also increase the length of the manuscript and the discussion of results without introducing greater nuance to the findings. Please consider relegating some of the tangential tests to the internet appendix of the paper. You may retain only the most crucial tests that are directly applicable to the baseline/benchmark regressions in your main argument

Response 5: Thank you for pointing this out, we agree with this comment. In response to this comment, we have carefully revised the paper to enhance its focus and clarity. Specifically, we have streamlined the empirical analysis by removing less relevant and tangential test results, retaining only the most critical robustness checks that directly support our main findings and benchmark regressions. These adjustments have been implemented to achieve three key objectives: (1) to maintain the integrity and comprehensiveness of our core robustness tests, (2) to optimize the paper's length and improve its structural coherence, and (3) to ensure that our key findings and contributions are presented with greater prominence and clarity. We believe these modifications have significantly improved the paper's overall quality and readability while preserving the essential empirical evidence supporting our main arguments.

Thank you again for your constructive feedback, which has significantly contributed to enhancing the quality and reliability of our research.

 

 

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

I have re-reviewed this revised manuscript. I acknowledge that the authors have invested considerable effort in revising the paper. Unfortunately, my previous comments regarding endogeneity testing have not been substantively addressed. I am willing to grant the authors one final opportunity to revise the manuscript. If these issues remain unresolved, I will recommend rejection.

Endogeneity Testing: Using the lagged term of the core explanatory variable as an instrumental variable is highly inappropriate. There are multiple rigorous approaches to address endogeneity, such as propensity score matching (PSM), difference-in-differences (DID), or alternative instrumental variables. The authors must adopt a more robust instrumental variable or employ other established endogeneity testing methods.

Regression Tables: The values in parentheses (e.g., t-statistics) must be explicitly defined in the tables. For clarity, add a note such as "Values in parentheses represent t-statistics" below each table.

References: Several cited references are in Chinese. As this manuscript is intended for publication in an English-language journal, all references must be replaced with English-language sources.

 

Author Response

Comment 1: Endogeneity Testing: Using the lagged term of the core explanatory variable as an instrumental variable is highly inappropriate. There are multiple rigorous approaches to address endogeneity, such as propensity score matching (PSM), difference-in-differences (DID), or alternative instrumental variables. The authors must adopt a more robust instrumental variable or employ other established endogeneity testing methods.

Response 1:Thank you for your valuable comment, we agree with this comment. To address this, we have taken proactive steps to address the endogeneity issue. We have now adopted the propensity score matching (PSM) method as recommended. We have carefully implemented this approach, ensuring that all the necessary procedures were followed rigorously to obtain reliable and valid results.The detailed implementation process and relevant results can be found on pages16-17, lines 550 to 568.

Through this modification, we believe that the endogeneity problem has been effectively dealt with, and the robustness of our analysis has been enhanced. We hope that these changes meet the expectations and requirements of the journal.

Once again, we apologize for any initial shortcomings in our handling of the endogeneity issue and thank you for their valuable feedback that has guided us to improve our work.

Comment 2: Regression Tables: The values in parentheses (e.g., t-statistics) must be explicitly defined in the tables. For clarity, add a note such as "Values in parentheses represent t-statistics" below each table.

Response 2:Thank you for your valuable comment, we agree with this comment. Regarding the regression tables, I have clearly defined the values in parentheses within each table and included a note below each table, as follows: "Notes: The values in the table represent variable regression coefficients; the values in parentheses denote t-values; *, **, and *** indicate statistical significance at the 10%, 5%, and 1% levels, respectively". This approach significantly enhances the clarity and readability of the tables for readers. This change can be found on pages 13,14,16 -19, 21.

Thank you again for your professional guidance.

Comment 3: References: Several cited references are in Chinese. As this manuscript is intended for publication in an English-language journal, all references must be replaced with English-language sources.

Response 3:Thank you for your valuable comment, we fully agree with this comment. We have taken steps to address it. Specifically, we have carefully reviewed all references and replaced previously cited Chinese-language sources with English-language ones. Corresponding adjustments have been made throughout the text to ensure consistency. The specific modifications are clearly marked in the text for easy identification. This change can be found on pages 3-6, 26-27.