How Does Digital Economy Drive High-Quality Agricultural Development?—Based on a Dynamic QCA and NCA Combined Approach

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. While the paper introduces the Technology-Organization-Environment (TOE) framework, its analysis of the inherent logical relationships and interaction mechanisms among the three dimensions is insufficient. For example, the transmission mechanism by which the technology dimension influences the environment dimension through the organization dimension is not clearly explained. It is recommended to supplement the theoretical derivation and establish a causal chain among the three dimensions.

2. The literature review section fails to adequately cover cutting-edge research on digital economy and green agricultural development in recent years, especially the latest achievements from 2023-2025.

3. The paper uses both NCA and QCA methods, but does not sufficiently explain how the two methods complement each other. NCA is often used to test the necessity of a single condition, while QCA is used to analyze the sufficiency of combinations of conditions. However, the paper does not explain why dynamic QCA was chosen instead of static QCA, nor how to resolve the potentially contradictory results produced by the two methods.

4. Section 3.2.3 mentions using quantiles for direct calibration, but does not explain the theoretical basis for choosing the upper quartile (75%), median (50%), and lower quartile (25%) as anchor points.

5. The paper proposes regional strategies based on path coverage, but fails to test the applicability of these strategies to specific provinces.

6. Although the paper uses dynamic QCA, the analysis of the intrinsic dynamics of path evolution over time is insufficient. It is recommended to add time-series analysis to explore the impact of typical key event cases on path formation.

7. The English grammatical expression of this article is poor, and further modifications are recommended.

Comments on the Quality of English Language

The English grammatical expression of this article is poor, and further modifications are recommended.

Author Response

We sincerely thank Reviewer 1 for the careful reading of our manuscript and for the constructive and insightful comments. We have revised the manuscript accordingly. Below, we respond to each comment point-by-point and indicate how the manuscript has been improved.

Comment 1: While the paper introduces the Technology-Organization-Environment (TOE) framework, its analysis of the inherent logical relationships and interaction mechanisms among the three dimensions is insufficient. For example, the transmission mechanism by which the technology dimension influences the environment dimension through the organization dimension is not clearly explained. It is recommended to supplement the theoretical derivation and establish a causal chain among the three dimensions.

Response 1: Thank you very much for this insightful comment. We agree that the original version did not sufficiently elaborate the internal logical relationships and interaction mechanisms among the three TOE dimensions.

In the revised manuscript, we have added a new subsection “2.2. Interdimensional Linkages within the TOE Framework” to explicitly clarify the causal chain and interaction mechanisms among technology (T), organization (O) and environment (E). In this subsection, we: Conceptualize the TOE framework as a dynamic, interdependent system, where the technological dimension acts as the foundational enabler providing digital “tools” for transformation, the organizational dimension mediates the deployment and utilization of these tools through resource allocation and governance, and the environmental dimension is where the combined effects of T and O are realized and amplified. Explicitly articulate the transmission mechanism T→O→E: robust digital infrastructure (T) generates massive agricultural data, which induces organizations to invest in digital resources and build digital government systems (O), thereby creating a stable, predictable environment that attracts and fosters digital finance and digital industry development (E). Acknowledge direct and feedback effects .

We also clarify that our configurational approach is well suited to capturing these complex, non-linear interdependencies, and we link the refined theoretical logic to our three core hypotheses (H1–H3) and Figure 1, which now visually presents the causal chain T → O → E and the feedback loops.

 

Comment 2: The literature review section fails to adequately cover cutting-edge research on digital economy and green agricultural development in recent years, especially the latest achievements from 2023-2025.

Response 2: We appreciate this important suggestion. We fully agree that the literature review in the original manuscript did not sufficiently reflect the latest advances in the digital economy and green/high-quality agricultural development.

Accordingly, we have substantially expanded and updated the literature review in the Introduction section by incorporating work published between 2023 and 2025. In particular, we have: Added studies such as Hong et al. (2023), which show that the digital economy positively affects green agricultural development and exhibits spatial spillover effects across regions.

Included more recent contributions such as Sun et al. (2024), Ye (2025), Zhang and Zhang (2024), and Liang and Qiao (2025), which extend the analysis to the broader notion of high-quality agricultural development and document how the digital economy enhances agricultural quality, efficiency and greenness, while displaying threshold effects, spatial spillovers and regional heterogeneity.

Added recent work on digital inclusive finance, such as Fu and Guo (2025) and Xiao et al. (2023), which demonstrate that digital inclusive finance promotes agricultural modernization, facilitates urban–rural integration, and improves agricultural total factor productivity at the provincial level.

As a result, the total number of references has increased from 49 to 69, and we ensured that all newly cited studies are fully listed and accurately formatted in the References section. These additions strengthen the state-of-the-art background and position our contribution more clearly within the most recent literature.

(Please see the revised literature review in the Introduction section and the updated References list.)

 

Comment 3: The paper uses both NCA and QCA methods, but does not sufficiently explain how the two methods complement each other. NCA is often used to test the necessity of a single condition, while QCA is used to analyze the sufficiency of combinations of conditions. However, the paper does not explain why dynamic QCA was chosen instead of static QCA, nor how to resolve the potentially contradictory results produced by the two methods.

Response 3: Thank you for this very helpful methodological comment. We agree that the complementarity between NCA and QCA, the rationale for using dynamic QCA, and the interpretation of seemingly contradictory results required clearer explanation.

In response, we have substantially rewritten Section 3.1.1, to clarify our integrated approach:

1. Complementary roles of NCA and dynamic QCA

We explain that QCA, grounded in set theory and Boolean algebra, identifies multiple concurrent configurations of antecedent conditions that are sufficient for an outcome, thereby capturing causal asymmetry, equifinality and complexity in medium-sized samples. NCA, in contrast, is used to test whether any single condition constitutes a necessary condition for the outcome and to quantify bottleneck levels.

We emphasize that our design is sequential: we first use NCA to test if any digital economy element is an indispensable condition for high AGTFP; finding that no single necessary condition exists supports the QCA premise of configurational causality and justifies the subsequent search for multiple sufficient paths.

2. Justification for dynamic (rather than static) QCA

We explicitly argue that high-quality agricultural development is a dynamic and cumulative process, and our data are structured as a panel (31 provinces over 2011–2023).

Static QCA would only capture a cross-sectional snapshot, whereas dynamic QCA is able to reveal how the causal configurations evolve and stabilize over time, which is central to our research questions on the temporal stability and evolution of pathways.

3. Interpreting seemingly contradictory results

We note that NCA and QCA test different causal relationships (necessity vs. sufficiency). Therefore, it is entirely possible, and substantively meaningful, that a condition is a core component of some sufficient configurations (per QCA) without being a universal necessary condition for the outcome (per NCA.

We explicitly discuss how we interpret such cases as evidence of context-specific critical enablers rather than contradictions. For example, if digital finance appears as a core condition in several high-AGTFP pathways in QCA but is not necessary in NCA, we view it as crucial in certain contexts but not an absolute “show-stopper” for all provinces.

We conclude the subsection by summarizing that the explicit comparison and integration of NCA and dynamic QCA allow us to understand the mechanisms behind high-quality agricultural development through the joint lenses of necessity vs. sufficiency and static snapshot vs. dynamic evolution. (Please see revised Section 3.1.1 “NCA and Dynamic QCA Method”.)

 

Comment 4: Section 3.2.3 mentions using quantiles for direct calibration, but does not explain the theoretical basis for choosing the upper quartile (75%), median (50%), and lower quartile (25%) as anchor points.

Response 4: We appreciate this important clarification request. We agree that the theoretical and methodological reasoning behind our choice of calibration anchors needed to be made explicit.

In the revised Section 3.2.3 “Data Calibration”, we now provide a clearer justification:

We state that, following established practices in fuzzy-set QCA (fsQCA) for medium-N samples, we use the 75th percentile as the threshold for full membership, the 50th percentile (median) as the crossover point, and the 25th percentile as the threshold for full non-membership.

We further emphasize that this approach leverages the empirical distribution of the data to define meaningful thresholds, ensuring that the calibration is both data-driven and theoretically reasonable.

We also note that this strategy helps differentiate cases with comparatively high, medium, and low levels of each condition in a transparent and replicable way.

The following sentence has been added to the text to make this clear:

“The selection of these quantiles as calibration anchors follows established practices in fsQCA research for medium-N samples. This approach leverages the empirical distribution of the data to define meaningful thresholds, ensuring that the calibration is grounded in the sample’s characteristics while maintaining theoretical relevance.”(Please see revised Section 3.2.3.)

 

Comment 5: The paper proposes regional strategies based on path coverage, but fails to test the applicability of these strategies to specific provinces.

Response 5:Thank you for this constructive suggestion. We agree that tracing the regional strategies back to specific provinces can significantly enhance the practical relevance and applicability of our findings.

In the revised manuscript, we have strengthened Section 5.3 “Practical Significance”, particularly the subsection “(1) Differentiated Regional Strategies Based on Path Characteristics”, in the following ways:

We explicitly link each dominant configuration path to representative provinces that strongly exhibit that pathway in our empirical results (as identified in Section 4.3.1).

For example, in the eastern region, where the financial–government dual-driver type dominates (e.g., Jiangxi, configuration H1a), we show how provincial government initiatives and targeted financial instruments (such as “Agricultural Low-Carbon Loan” programs) jointly support green agriculture.

In the central and western regions, where the infrastructure–government dual-driver pathway is prevalent (e.g., Hebei, configuration H2a), we illustrate how national computing power hubs and initiatives like the “Digital Hebei” Action Plan reflect and reinforce this configuration through substantial digital infrastructure investment and upgraded data governance.

In the northeast, where an industry-led pathway is salient (e.g., Shaanxi, configuration H4), we discuss how the success of the “Luochuan Apple” brand demonstrates the role of industrial upgrading and branding in compensating for weaker digital dimensions and how policy can foster enterprise–technology partnerships and technical training to enhance digital capabilities.

By grounding the regional strategies in concrete provincial cases, we demonstrate that the proposed configuration-based recommendations are not purely conceptual but are consistent with and applicable to specific provincial trajectories. We also propose establishing a “regional digital agriculture development type identification system” to help policymakers identify the dominant development path based on regional resource endowments and target policies accordingly. (Please see revised Section 5.3, subsection “(1) Differentiated Regional Strategies Based on Path Characteristics”.)

 

Comment 6: Although the paper uses dynamic QCA, the analysis of the intrinsic dynamics of path evolution over time is insufficient. It is recommended to add time-series analysis to explore the impact of typical key event cases on path formation.

Response 6:Thank you very much for this valuable comment. We agree that the original version did not fully exploit the dynamic potential of the QCA framework to reveal the intrinsic evolution of configurational paths over time. In the revised manuscript, we have substantially strengthened the dynamic analysis in Section 4.3.2 “Inter-group Consistency Analysis”.

Specifically, we move beyond simply assessing path stability and conduct a time-series analysis of inter-group consistency for the four main pathways from 2011 to 2023. The results uncover two distinct evolutionary patterns. First, digital finance–driven pathways (H1b, H3) display high and sustained consistency in the early years, with a pronounced increase after 2014–2015. We explicitly link this surge to the rollout of national strategies such as “Broadband China” and the “Internet Plus” action plan, which rapidly expanded internet access and catalyzed the growth of digital financial services, thereby lowering barriers for financial capital to enter the agricultural sector and supporting green transformation. Second, the infrastructure–government pathway (H2b) shows a delayed-but-ascending pattern: its consistency remains moderate initially but rises steadily from around 2018, which we relate to the “Digital Village Development Strategy Outline” and the “14th Five-Year Plan for National Informatization”, both of which place unprecedented emphasis on rural digital infrastructure. We further note a slight dip in consistency across several paths during 2021–2023 and interpret this as reflecting exogenous shocks, in particular the pandemic-related disruptions to supply chains and economic activity.

Taken together, these additions allow us to move from merely stating that certain paths are stable to explaining why and how their relative importance shifts in response to key national policy initiatives and external shocks. We believe this enriched, policy-aware dynamic analysis better reflects the intent of dynamic QCA and directly addresses the reviewer’s suggestion.

 

Comment 7: The English grammatical expression of this article is poor, and further modifications are recommended.

Response 7: We sincerely appreciate this candid and helpful comment. We fully acknowledge that the previous version contained grammatical and stylistic problems that affected readability.

In the revised version, we have carefully edited the entire manuscript in English. Specifically, we:

Systematically reviewed and corrected grammar, syntax, punctuation, and word choice.

Simplified overly long or complex sentences and improved paragraph structure to enhance clarity and coherence.

Sought assistance from a professional language editing service to further polish the manuscript.(I have uploaded the polishing certificate from a professional institution.)

We believe that these efforts have significantly improved the overall quality, clarity, and readability of the English expression.

Once again, we sincerely thank Reviewer 1 for the thoughtful and constructive comments, which have helped us substantially improve the theoretical framing, methodological clarity, empirical analysis, and presentation of our work.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

This paper presents a study on the impact of digital economy on high-quality agricultural development, especially on the total factor productivity in the green agriculture. The study is based on a Chinese case and applies both Dynamic Qualitative Comparative Analysis (QCA) and Necessary Condition Analysis (NCA).

It must be pointed out that the version available does not include references – error appears.

Abstract: This section contains all the necessary elements required to describe the design and results of a study.

Introduction: This section presents the study’s background and demonstrates its contribution to the knowledge on the topic. I suggest adding a short paragraph on the paper’s structure as it is not typical of the paper’s in this journal.

Theoretical Model Construction: In this section the authors described the theoretical approach applied in the study. It is compelling and clearly presented. I highly appreciate figure 1 as it is a well-designed depiction of the whole theoretical approach.

Research Design: This section is divided into sub-sections. Sub-section 3.1. Research Method is further divided into sub-sub-sections. Sub-sub-section 3.1.1. presents the NCA and Dynamic QCA Method. Sub-sub-section 3.1.2. describes the SBM-GML Model.

Sub-section 3.2. Data Sources is also divided into sub-sub-sections. Sub-sub-section 3.2.1. shows the outcome variable, while sub-sub-section 3.2.2. the condition variables and sub-sub-section 3.2.3. data calibration.

Data Analysis and Empirical Results: This section is also divided into sub-sections. Sub-section 4.1. presents the necessary condition analysis’s results, while sub-section 4.2. the findings of analysis of single-condition necessity. Sub-section 4.3. demonstrates the results of the analysis of sufficiency for condition configurations. The following sub-section shows summary of results analysis, while the next sub-section presents inter-group consistency analysis. There is also a sub-section on regional differences analysis of high-quality agricultural development pathways. Finally, there is a robustness test.

All the findings are clearly described and are compelling.

Discussion and Implications: This section is also divided into sub-sections. Sub-section 5.1. Research Conclusion presents the research conclusions of the study. The authors not only present them but refer them to similar studies. Sub-section 5.2. Practical Significance clearly and in detail refers to implications of the study for policymakers. I highly appreciate the last sub-section 5.3. Limitations and Prospects showing in detail the study’s limitations and future study needs.

Author Response

We would like to sincerely thank Reviewer 2 for the careful reading of our manuscript and for the encouraging and constructive comments. We are very grateful for your positive evaluation of the theoretical approach, empirical analysis, and policy implications. Based on your suggestions, we have revised and improved the manuscript as detailed below.

Comment 1: This paper presents a study on the impact of digital economy on high-quality agricultural development, especially on the total factor productivity in the green agriculture. The study is based on a Chinese case and applies both Dynamic Qualitative Comparative Analysis (QCA) and Necessary Condition Analysis (NCA).

Response 1: We thank the reviewer for this positive summary of our study. We appreciate your recognition of the topic, the Chinese case background, and the combined use of Dynamic QCA and NCA. This encouragement has been very helpful for us in refining the manuscript.

Comment 2:It must be pointed out that the version available does not include references – error appears.

Response 2:We are very grateful to the reviewer for pointing out this important issue and we sincerely apologize for the inconvenience caused by the missing references in the previous version (most likely due to a technical or formatting error during submission).

In the revised manuscript, we have:

Restored and carefully checked the complete reference list, ensuring that all in-text citations are properly matched with full entries in the References section.

Expanded the reference list to include recent studies related to the digital economy and high-quality/green agricultural development (especially from 2023–2025), so that the literature review reflects the latest developments in the field.

Verified that the manuscript now displays correctly in PDF and system preview, without any missing or corrupted reference section.

We hope that this correction resolves the problem you encountered and that the references are now fully accessible in the revised version.

Comment 3: Abstract: This section contains all the necessary elements required to describe the design and results of a study.

Response 3: We sincerely thank the reviewer for the positive assessment of the Abstract. Following your overall comments and those of Reviewer 1, we have made only minor wording refinements in the Abstract to further enhance clarity and readability, while keeping its structure and content unchanged.

Comment 4: Introduction: This section presents the study’s background and demonstrates its contribution to the knowledge on the topic. I suggest adding a short paragraph on the paper’s structure as it is not typical of the paper’s in this journal.

Response 4: Thank you very much for this helpful suggestion. We fully agree that adding a brief paragraph on the structure of the paper can improve the readability and make the manuscript more consistent with the journal’s style.

In the revised manuscript, we have added a short paragraph at the end of the Introduction that outlines the structure of the paper. For example, we now state:

“The remainder of this paper is organized as follows. Section 2 constructs the theoretical model based on the TOE framework and proposes the core research hypotheses. Section 3 describes the research design, including the NCA–dynamic QCA methodology, variables and data calibration. Section 4 reports the empirical results of the necessary condition analysis and the configurational sufficiency analysis, as well as the regional differentiation and robustness tests. Section 5 summarizes the main findings, discusses their practical implications for policymakers, and highlights the limitations and directions for future research.”

We believe this addition makes the structure of the paper clearer and better aligned with the journal’s usual format.

 

Comment 5: Theoretical Model Construction: In this section the authors described the theoretical approach applied in the study. It is compelling and clearly presented. I highly appreciate figure 1 as it is a well-designed depiction of the whole theoretical approach.

Response 5: We are very grateful for your positive evaluation of the theoretical model and Figure 1. In response to Reviewer 1’s comments, we have further elaborated on the interdimensional linkages within the TOE framework in a new subsection. We appreciate your recognition, which encourages us that the theoretical presentation is now both compelling and clear.

 

Comment 6: Research Design: This section is divided into sub-sections. Sub-section 3.1. Research Method is further divided into sub-sub-sections. Sub-sub-section 3.1.1. presents the NCA and Dynamic QCA Method. Sub-sub-section 3.1.2. describes the SBM-GML Model.

Response 6: We thank the reviewer for carefully examining the structure of the Research Design section and for the positive remarks. Based on the comments from both reviewers, we have slightly refined the exposition in Section 3.1.1 (NCA and Dynamic QCA Method) to clarify the complementary roles of NCA and dynamic QCA and to better explain the rationale for using a dynamic rather than a static QCA framework. The overall structure of Section 3.1 remains as you described and we are glad that it was found to be clear.

 

Comment 7: Sub-section 3.2. Data Sources is also divided into sub-sub-sections. Sub-sub-section 3.2.1. shows the outcome variable, while sub-sub-section 3.2.2. the condition variables and sub-sub-section 3.2.3. data calibration.

Response 7: We sincerely appreciate your positive evaluation of the Data Sources section and its internal structure. In response to Reviewer 1’s suggestion, we have added a brief explanation in Section 3.2.3 regarding the theoretical and methodological rationale for using the 75th, 50th, and 25th percentiles as calibration anchors in the fsQCA framework. Apart from this clarification and minor wording improvements, the structure and content of Section 3.2 remain consistent with your description.

 

Comment 8: Data Analysis and Empirical Results: This section is also divided into sub-sections. Sub-section 4.1. presents the necessary condition analysis’s results, while sub-section 4.2. the findings of analysis of single-condition necessity. Sub-section 4.3. demonstrates the results of the analysis of sufficiency for condition configurations. The following sub-section shows summary of results analysis, while the next sub-section presents inter-group consistency analysis. There is also a sub-section on regional differences analysis of high-quality agricultural development pathways. Finally, there is a robustness test. All the findings are clearly described and are compelling.

Response 8: We are very grateful for your careful reading and for this comprehensive and positive assessment of the Data Analysis and Empirical Results section. Building on your encouraging comments and Reviewer 1’s suggestions, we have:

Enhanced the dynamic analysis of inter-group consistency in Section 4.3.2 by explicitly relating the evolution of configurational paths (2011–2023) to key national digital and agricultural policy initiatives;

Slightly refined the narrative in the subsections on regional differences and robustness tests to improve clarity.

We are pleased that you find the findings clearly described and compelling, and we hope that the revised version further strengthens this impression.

 

Comment 9: Discussion and Implications: This section is also divided into sub-sections. Sub-section 5.1. Research Conclusion presents the research conclusions of the study. The authors not only present them but refer them to similar studies. Sub-section 5.2. Practical Significance clearly and in detail refers to implications of the study for policymakers. I highly appreciate the last sub-section 5.3. Limitations and Prospects showing in detail the study’s limitations and future study needs.

Response 9: We sincerely thank the reviewer for the very encouraging comments on the Discussion and Implications section. We are glad that you find the research conclusions well grounded in the existing literature, the practical implications for policymakers clearly articulated, and the limitations and future research directions sufficiently detailed. In the revised manuscript, we have made only minor wording and structural refinements in Section 5 to improve coherence and readability, while keeping the core content and logic unchanged.

 

Once again, we would like to express our heartfelt gratitude to Reviewer 2 for the thoughtful and positive evaluation of our work. Your suggestions—especially regarding the reference list and the structural paragraph in the Introduction—have helped us substantially improve the clarity, completeness, and overall presentation of the manuscript.

Reviewer 3 Report

Comments and Suggestions for Authors

1. The article's topic appears highly relevant. Its primary focus is on analyzing the impact of the digital economy on agricultural green total factor productivity (AGTFP). The authors examined this impact using data from 31 Chinese provinces over a long period from 2011 to 2023. They substantiate key digital economy pathways that contribute to the development of green agriculture in China. The study's relevance is convincingly argued. The relevance of the research topic to the journal's profile is unambiguous.
2. The authors provide a detailed theoretical review. This review is integrated into the theoretical model section of the study. Based on this review, the authors substantiate three limitations of existing research in this area. This is a positive development. Unfortunately, the authors do not identify research gaps based on their literature review.
3. I believe this study adds some analytical foundations to the field of sustainable agricultural development. In particular, the authors substantiate an original conclusion about the central role of multifactor synergies in the green transformation of agriculture. The authors also substantiate their conclusion about the dynamic stability of each path of green agriculture development. In my opinion, these are original and meaningful analytical justifications.
4. The article appears promising for publication in the journal. However, there are some minor comments.
First, the authors do not formulate their research questions in the Introduction section. Furthermore, the Introduction section lacks a clearly defined study objective.
Second, they did not formulate the research hypotheses.
Third, the Discussion section lacks an analysis of the validity of the research hypotheses.
5. The study's conclusions are clearly formulated. I would like to highlight the very interesting and informative subsection of recommendations for practice. However, an analysis of the theoretical significance of the study is missing. I recommend providing specific justification for the theoretical significance of the study's results.
6. The article contains a small number of references from 49 sources. A significant portion of the sources are dated within the last five-year period. The bibliography is high-quality. However, the references in the text are not formatted according to the journal's standards (in square brackets with numbering). Furthermore, there is a technical error throughout the article, indicating that the source was not found.
7. The article contains 4 figures, 8 tables, and 2 formulas. The results appear to be visualized sufficiently. The study is based on a combination of dynamic qualitative comparative analysis (QCA) and necessary conditions analysis (NCA). The research procedure is clear and straightforward. It is recommended that sources for tables and figures be cited. In particular, the source should be stated as the authors' calculations.

Author Response

We would like to sincerely thank Reviewer 3 for the careful reading of our manuscript and for the very encouraging and constructive comments. We greatly appreciate your positive evaluation of the topic relevance, theoretical analysis, methodological design, and practical recommendations. Based on your suggestions, we have revised and improved the manuscript as detailed below.

Comment 1: The article's topic appears highly relevant. Its primary focus is on analyzing the impact of the digital economy on agricultural green total factor productivity (AGTFP). The authors examined this impact using data from 31 Chinese provinces over a long period from 2011 to 2023. They substantiate key digital economy pathways that contribute to the development of green agriculture in China. The study's relevance is convincingly argued. The relevance of the research topic to the journal's profile is unambiguous.

Response 1: We sincerely thank the reviewer for this very positive assessment of the topic, empirical setting, and relevance to the journal. Your recognition of the long-term provincial panel data (2011–2023) and the focus on digital economy pathways to AGTFP is very encouraging. In revising the manuscript, we have maintained this core focus while further clarifying our theoretical framing and empirical contributions in response to your and the other reviewers’ comments.

Comment 2: The authors provide a detailed theoretical review. This review is integrated into the theoretical model section of the study. Based on this review, the authors substantiate three limitations of existing research in this area. This is a positive development. Unfortunately, the authors do not identify research gaps based on their literature review.

Response 2: Thank you very much for highlighting both the strengths and the missing element in our theoretical review. We fully agree that the literature review should not only summarize limitations but also explicitly articulate the research gaps that our study addresses.

In the revised manuscript, we have added a dedicated paragraph in the Introduction that clearly formulates the research gap and links it to our research questions. Specifically, after discussing the limitations of existing studies, we now state that there is no comprehensive, dynamic, and configurational framework capable of untangling the causal complexity of how the digital economy—through the interplay of its various components—drives AGTFP.

Comment 3: I believe this study adds some analytical foundations to the field of sustainable agricultural development. In particular, the authors substantiate an original conclusion about the central role of multifactor synergies in the green transformation of agriculture. The authors also substantiate their conclusion about the dynamic stability of each path of green agriculture development. In my opinion, these are original and meaningful analytical justifications.

Response 3: We are very grateful for your positive evaluation of the analytical contribution of our study. We particularly appreciate your recognition of our conclusions regarding the central role of multifactor synergies and the dynamic stability of green development paths. In the revised version, we have further clarified these contributions in the Discussion section and, as suggested in your later comments, we now explicitly summarize the theoretical significance of these findings (see our response to Comment 5).

Comment 4: The article appears promising for publication in the journal. However, there are some minor comments.
First, the authors do not formulate their research questions in the Introduction section. Furthermore, the Introduction section lacks a clearly defined study objective.
Second, they did not formulate the research hypotheses.
Third, the Discussion section lacks an analysis of the validity of the research hypotheses.

Response 4: Thank you very much for these important suggestions concerning the structure and clarity of our research design.

Based on the research gap, we have added a new paragraph at the end of the introduction to elaborate on the research question and purpose. We introduce an overarching research question on how synergistic configurations of digital economy elements across technological, organizational, and environmental dimensions dynamically drive high-quality agricultural development in China. We then decompose this central question into three specific research questions (RQ1–RQ3), which focus on: (1) identifying configurations of digital economy conditions that are sufficient for high AGTFP, (2) examining how these configurations evolve over time, and (3) exploring how the driving paths differ across China’s major regions. We also explicitly state that the main purpose of the study is to systematically identify, compare, and track these configurational pathways.

We believe these additions make the research objective and the corresponding research questions much clearer and more tightly connected to the subsequent theoretical model and empirical analysis, thereby directly addressing the reviewer’s concern.
In addition,based on your suggestion, we now explicitly formulate the research hypotheses in the theoretical model section. Following the TOE-based theoretical derivation and the new subsection on interdimensional linkages, we propose three testable hypotheses (H1–H3), which are now clearly listed as:

H1: Multiple distinct configurations of digital economy conditions will be sufficient for high AGTFP.

H2: The core configurations driving high AGTFP will exhibit a significant degree of temporal stability over the study period.

H3: The prevalence and composition of these effective configurations will vary systematically across China's eastern, central, western, and northeastern regions.

(Please see the end of Section 2.2 for the explicit presentation of H1–H3.)

Analysis of the validity of the research hypotheses in the Discussion section
We agree that the Discussion should explicitly address whether and how the empirical results support the proposed hypotheses. In the revised Section 5.1 (Research Conclusion), we have reorganized the discussion so that it systematically revisits H1–H3:

For H1, we summarize how the dynamic QCA results identify several distinct configurations that are sufficient for high AGTFP, highlighting the central role of multifactor synergies.

For H2, we discuss the evidence for temporal stability and evolution of the core configurations over 2011–2023, drawing on the dynamic analysis and inter-group consistency results.

For H3, we connect the regional differentiation analysis to the hypothesis, explaining how the dominant configurations vary across eastern, central, western, and northeastern regions.

In this way, the Discussion now explicitly evaluates the validity of each hypothesis and links the empirical findings back to the theoretical expectations.

Comment 5: The study's conclusions are clearly formulated. I would like to highlight the very interesting and informative subsection of recommendations for practice. However, an analysis of the theoretical significance of the study is missing. I recommend providing specific justification for the theoretical significance of the study's results.

Response 5: We greatly appreciate the reviewer’s positive assessment of the clarity of our conclusions and the value of the practical recommendations. We fully agree that the manuscript should also articulate the theoretical significance of the study in a more explicit and structured way.

In the revised manuscript, we have added a new subsection “5.2. Theoretical Significance” to address this important point. In this subsection, we summarize the main theoretical contributions of the study as follows:

1. Extension of the TOE framework in a configurational and dynamic context.We extend the application of the Technology–Organization–Environment (TOE) framework to agricultural green total factor productivity by systematically integrating it with configurational theory (QCA) and explicitly modeling the causal chains (T→O→E) among its dimensions. This provides a more dynamic and interconnected analytical lens for understanding digital transformation in agriculture.
2. Methodological contribution through the integration of NCA and dynamic QCA.We demonstrate the value of combining Necessary Condition Analysis (NCA) with dynamic Qualitative Comparative Analysis (QCA), moving beyond static, correlation-based approaches. This integrated design uncovers complex, evolving, and equifinal causal pathways, thereby offering a richer methodological framework for studying the digital economy’s impact on sustainable agriculture.
3. A dynamic view of configurations and path effectiveness.We show that the effectiveness and persistence of different configurational paths are time-sensitive and policy-contingent, which qualifies purely cross-sectional inferences. Our findings robustly substantiate that the core mechanism driving AGTFP is multifactor synergy, and on this basis we propose a more nuanced and complex theoretical proposition about the nature of digital-enabled agricultural green transformation.

We believe that this new subsection makes the theoretical significance of our results clearer and more specific, and we hope it satisfactorily addresses the reviewer’s valuable suggestion.

Comment 6: The article contains a small number of references from 49 sources. A significant portion of the sources are dated within the last five-year period. The bibliography is high-quality. However, the references in the text are not formatted according to the journal's standards (in square brackets with numbering). Furthermore, there is a technical error throughout the article, indicating that the source was not found.

Response 6: Thank you for your careful evaluation of the references and for pointing out the formatting and technical issues.

Regarding number and recency of references. As also noted by the other reviewers, we have expanded and updated the reference list in the revised manuscript. The total number of references has increased from 49 to 69, with additional recent studies (especially from 2023–2025) on the digital economy, green agriculture, and high-quality agricultural development. We appreciate your positive assessment that the bibliography is of high quality.

Regarding citation style and journal standards. We have carefully reformatted all in-text citations to conform to the journal’s standard style, that is, numbered references in square brackets (e.g., [1], [2–4]). We also checked that the numbering in the text and the sequence in the reference list are fully consistent.

Regarding technical error, We sincerely apologize for the previous technical error that resulted in “source not found” messages. In the revised version, we have systematically checked all citation fields and cross-references and corrected the underlying problems. The reference list now appears correctly, and all in-text citations link properly to their corresponding entries in the References section.

We hope that these corrections fully resolve the issues you identified.

Comment 7: The article contains 4 figures, 8 tables, and 2 formulas. The results appear to be visualized sufficiently. The study is based on a combination of dynamic qualitative comparative analysis (QCA) and necessary conditions analysis (NCA). The research procedure is clear and straightforward. It is recommended that sources for tables and figures be cited. In particular, the source should be stated as the authors' calculations.

Response 7: We sincerely thank the reviewer for the positive assessment of the visualization of results, the methodological combination of dynamic QCA and NCA, and the clarity of the research procedure. We also appreciate your practical recommendation regarding the sources of tables and figures.

In the revised manuscript, we have added explicit source notes beneath all tables and figures. For example, we now state:

“Source: Authors’ calculations based on provincial panel data (2011–2023).”

or similar wording, depending on the specific content of each table or figure. Where appropriate, we also indicate the original data sources (e.g., official statistical yearbooks or databases) that underlie our calculations.

We believe that this addition improves transparency and traceability of the empirical results, in line with your suggestion.

Once again, we are very grateful to Reviewer 3 for the thoughtful, encouraging, and constructive comments. Your suggestions—particularly regarding the explicit articulation of research gaps, research questions, hypotheses, and theoretical significance—have helped us substantially improve the clarity, coherence, and contribution of the manuscript.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The English grammatical expression of this article is poor, and further modifications are recommended.

Comments on the Quality of English Language

The English grammatical expression of this article is poor, and further modifications are recommended.

Author Response

Comment:
“The English grammatical expression of this article is poor, and further modifications are recommended.”

Response:
We sincerely thank the reviewer for pointing out the weaknesses in the English expression of our previous version. We fully agree with this comment.

In response, Building on the revisions made in the first round, we have conducted a thorough, sentence-by-sentence revision of the entire manuscript to improve grammar, clarity, and readability. In particular, we have:

• Simplified overly long and complex sentences and removed redundant expressions;

• Improved the logical flow between paragraphs, especially in the sections on research design, hypotheses, and empirical results;

• Standardized the use of technical terms, abbreviations, and symbols throughout the manuscript;

• Checked and corrected grammatical issues, including verb tenses, subject–verb agreement, article usage, and prepositions.

In addition, the revised manuscript has been edited by a professional English-language editing service, and the corresponding language editing certificate/report is provided as a supplementary file.

We hope that the current version now meets the journal’s language requirements, and we again thank the reviewer for this helpful and constructive suggestion.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors did a great job addressing the comments. All comments have been taken into account. The article has become significantly better.

Author Response

Dear Reviewer,

Thank you very much for your time and for the positive feedback on our revised manuscript, “How Does Digital Economy Drive High-Quality Agricultural Development? — Based on a Dynamic QCA and NCA Combined Approach” (Manuscript ID: sustainability-3982329).

We are truly delighted and encouraged to read your comments, especially your note that “The authors did a great job addressing the comments” and that “The article has become significantly better.” Your insightful suggestions during the previous round of review were invaluable in helping us improve the clarity, coherence, and overall quality of our work.

We sincerely appreciate your recognition of our efforts. Your expertise and guidance have been instrumental in shaping this manuscript.

Thank you once again for your constructive input throughout the review process. We look forward to the final decision from the editorial office.