Review Reports - Digitalization and Culture–Tourism Integration in China: The Moderated Mediation Effects of Employment Quality, Infrastructure, and New-Quality Productivity

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The theoretical model is ambitious, integrating digital economy, new infrastructure, employment quality, and new-quality productivity. However, the boundaries between these constructs are sometimes blurred. I recommend refining the conceptual definitions and providing a clearer justification for why these specific mediators and moderators were chosen, possibly with a conceptual diagram that distinguishes the causal pathways more explicitly.

While the Literature Review section is comprehensive, it remains somewhat descriptive. It would benefit from a more critical synthesis of gaps in prior research, particularly regarding the negative moderating role of new-quality productivity. Explicitly contrasting this study with closely related empirical works would enhance the originality and contribution.

This study relies heavily on entropy index construction for the key variables. More details should be provided about indicator selection, weighting procedures, and robustness checks of the indices. For reproducibility, a supplementary appendix with the full list of indicators and data sources should be included.

Although the paper mentions Hausman and VIF tests, potential endogeneity between digital economy development and cultural-tourism integration remains. I suggest incorporating instrumental variable techniques, dynamic panel models (e.g., system GMM), or placebo tests to better establish causality.

The negative moderation effect of new-quality productivity is intriguing but requires more nuanced discussion. The current explanation relies mainly on resource dilution and maturity effects. Alternative explanations (e.g., institutional constraints, crowding-out of tourism by high-tech sectors) should be considered, supported by additional case evidence or robustness analysis.

The policy recommendations are currently broad and somewhat repetitive. They could be strengthened by offering more differentiated strategies tailored to provinces at different developmental stages (e.g., eastern vs. western China). Moreover, international comparative insights would help broaden the article’s relevance beyond the Chinese context.

Hope these comments will be useful and helpful for you.

Author Response

Q1:The theoretical model is ambitious, integrating digital economy, new infrastructure, employment quality, and new-quality productivity. However, the boundaries between these constructs are sometimes blurred. I recommend refining the conceptual definitions and providing a clearer justification for why these specific mediators and moderators were chosen, possibly with a conceptual diagram that distinguishes the causal pathways more explicitly.

Response:

We greatly appreciate the reviewer's comments regarding the clarity of conceptual boundaries within the theoretical model and the suggestion to supplement it with a conceptual diagram. We fully agree that clear conceptual definitions and mechanism explanations are crucial for the rigor of the model. In response to this comment, we have made the following core revisions to Chapters 2 and 3 of the manuscript:

Original text before modification:

Definitions of concepts such as the digital economy, cultural-tourism integration, new infrastructure, employment quality, and new-quality productive forces remain relatively isolated, failing to sufficiently emphasize their distinct roles within the model.

Revised content：

We have comprehensively revised and refined the definitions of core concepts such as the digital economy, cultural-tourism integration, new infrastructure, employment quality, and new-quality productive forces. We ensured each concept is defined with greater precision and academic rigor, while maintaining close alignment with specific roles within the model. For instance, in defining “new infrastructure,” we explicitly highlighted its role as the physical carrier serving as the “highway and nervous system” for the digital economy's operation. In defining “employment quality,” we emphasize its talent dimension as the “manifestation of human capital and skills.” For “new-type productive forces,” we have clarified its unique connotation as a high-level innovation-driven productive force, laying the theoretical foundation for subsequent regulatory effects. See Section 2.1–2.4 of Chapter 2 for details.（The modified content in the article has been highlighted in yellow.line43-69、line88-91、line95-96、line116-130、line152-164、line171-175、line190-192、line209-227、line231-255、line264-271、line278、line300-304、line318-323、line330-333、line345-349、line355-357、line360-362、line400-403、line405-417）

2.1 Digital Economy and Cultural Tourism Integration: Existing Research and Limitations

The digital economy, an emerging economic paradigm centered on digital technology with data as a key production factor, is profoundly reshaping global economic structures and social frameworks through its transformative power. Its pervasive, integrative, and innovative characteristics position it as a core engine driving high-quality economic development and industrial transformation. Concurrently, the deep integration of cultural and tourism industries (Cultural Tourism Integration, CTI) is recognized as a strategic choice to enhance industrial resilience, optimize regional competitiveness, and improve public welfare. The essence of CTI lies in dismantling traditional industrial barriers, fostering the organic integration and mutual empowerment of cultural and tourism elements, ultimately giving rise to new industrial chains and restructuring value chains—shifting from offering single products to delivering composite experiences. From the perspective of industry integration theory, digitalization in this process facilitates cross-boundary synergies, enables economies of scope, and drives innovative restructuring of value chains.

Existing research widely acknowledges the significant promotional role of the digital economy in industrial development and integration, with its impact pathways being multidimensional and complex. Digital platforms play a pivotal role in information dissemination and market expansion, effectively overcoming traditional information asymmetries. They substantially broaden the channels for promoting and marketing cultural and tourism products, enabling distinctive resources from remote areas to gain widespread recognition and reach global consumers. The digital economy also makes substantial contributions to enhancing efficiency and reducing costs. Advanced technologies like big data, cloud computing, and artificial intelligence are widely applied in cultural and tourism operations management, customer relations, and supply chain optimization. This significantly improves resource allocation efficiency, enables precision marketing and personalized recommendations, and effectively lowers operational, marketing, and intermediary costs. The digital economy also powerfully empowers product innovation and experience upgrades. Technologies like virtual reality (VR), augmented reality (AR), and artificial intelligence (AI) are deeply integrated into cultural and tourism product content, enabling personalized, immersive, and interactive experiences. This drives continuous innovation and upgrades in the forms of cultural and tourism products and service models. Finally, digital technologies have facilitated the restructuring of industrial factors and the formation of new industrial ecosystems. They have accelerated the cross-border flow and integration of diverse elements such as culture, tourism, technology, and finance, giving rise to new business models and industrial practices. Ultimately, this has fostered a more diverse and vibrant cultural and tourism industry ecosystem.

However, despite providing valuable insights, existing literature exhibits significant limitations. First, few studies specifically examine the mechanisms through which the digital economy drives the development of “cultural-tourism integration,” particularly overlooking the mediating role of new infrastructure and employment quality as key variables. Most existing literature remains at the macro-level correlation stage, failing to fully reveal the specific transmission chains. Second, while acknowledging the widespread application of digitalization in tourism and cultural industries, existing research lacks systematic exploration of how the digital economy holistically drives the deep integration of these two sectors—that is, cross-sectoral integration that transcends the digitalization of individual industries. Furthermore, while international organizations like UNWTO, OECD, and the EU have released reports on the global relationship between the digital economy and cultural-tourism integration—providing macro trends and policy recommendations on the digital economy's impact on tourism—research examining the complex interplay among the digital economy, new infrastructure, employment quality, and cultural-tourism integration within China's unique provincial-level development model remains scarce. This gap is particularly pronounced in the absence of consideration for China's distinctive contextual variable: the “new quality productive forces.”

2.2 New Infrastructure: Concept, Functions, and Integration with Cultural Tourism

New infrastructure (hereinafter referred to as “new infrastructure”) refers to an infrastructure system guided by new development concepts, driven by technological innovation, and oriented toward high-quality development needs. It provides services for digital transformation, intelligent upgrading, and integrated innovation. Its core components include next-generation information network infrastructure (such as 5G base stations, fiber-optic networks, and satellite internet), integrated infrastructure (such as artificial intelligence platforms, big data centers, cloud computing, and industrial internet platforms), and innovation infrastructure (such as major scientific and technological infrastructure and scientific education infrastructure). This new infrastructure system serves as the “highway” and “nervous system” for the digital economy's operation, with its development level directly determining the depth and breadth of the digital economy. The vigorous growth of the digital economy has dramatically increased demand for high-speed networks and massive computing power, which in turn drives and accelerates investment in and adoption of new infrastructure, creating a virtuous cycle between the two. From an infrastructure theory perspective, new infrastructure is not merely a passive support for industries but an active enabler that reshapes industrial development trajectories and spurs new business models.

New infrastructure plays an increasingly vital role in the integration of cultural and tourism industries. High-bandwidth, low-latency networks (such as 5G) provide robust foundational support for the digital transformation of cultural and tourism sectors, enabling smart scenic area development, online transmission of high-definition cultural content, and immersive virtual experiences. This significantly promotes the deep integration of online cultural and tourism resources with offline physical experience venues. Concurrently, big data centers and cloud computing platforms, as core components of data empowerment, aggregate and analyze vast amounts of visitor behavior data and cultural consumption preferences. This provides scientific decision support for personalized product customization, precision marketing, and intelligent operational management in the cultural tourism sector. The deep integration of artificial intelligence (AI) and Internet of Things (IoT) technologies with new infrastructure accelerates the intelligent upgrade of the cultural and tourism industry. Applications such as smart navigation, multilingual translation, and intelligent ticketing systems not only enhance service efficiency but also enrich visitor experiences. These advancements collectively promote more efficient coordination between cultural and tourism elements, thereby driving deeper integration within the cultural industry. Existing literature has preliminarily revealed the foundational support role of new infrastructure within the context of the digital economy's influence on industrial development. However, its specific transmission mechanism as a driver of cultural-tourism integration within the digital economy requires further empirical validation. This is particularly true regarding how it functions as an independent transmission pathway influencing cultural-tourism integration, distinct from merely being a phenomenon within the broader digital economy.

2.3 Employment Quality: Concept, Dimensions, and Its Relationship with Cultural-Tourism Integration

Employment quality is a multidimensional concept that transcends mere employment quantity. It encompasses key aspects such as optimizing employment structure, enhancing skill levels, improving compensation and benefits, optimizing working conditions, and creating new types of employment opportunities. It serves as a vital indicator for measuring workers' well-being and the quality of economic development. From the perspective of human capital theory, investment in human capital (skills and knowledge) can lead to increased productivity and economic value. The rapid development of the digital economy has driven structural transformation in the labor market, particularly within the service sector. It has not only altered traditional work patterns but also spawned numerous innovative job roles. The digital economy's significant impact on employment quality indirectly facilitates the integration of the cultural and tourism industries.

The digital platform economy serves as a key driver in elevating employment quality within the cultural and tourism sector. It has spawned numerous high-tech, innovative new business models and formats, such as online tour guides, digital cultural creators, live-streaming hosts promoting intangible cultural heritage, and online cultural tourism marketers. These emerging employment forms not only provide regional labor forces with more diverse, flexible, and often higher-paying job options. More importantly, they accelerate the rapid enhancement of digital skills, specialized knowledge, and interdisciplinary capabilities among cultural and tourism practitioners. This optimizes the overall employment structure to better align with the demands of the digital economy era. Technology-driven efficiency gains and heightened specialization requirements also increase the skill premium for practitioners, thereby improving their compensation, benefits, and career prospects. As the skill levels and incomes of cultural and tourism practitioners generally rise, the industry's appeal to high-caliber talent significantly increases, creating a talent clustering effect that further solidifies the human capital foundation for industrial integration. Consequently, the improvement in employment quality not only enhances workers' conditions but also injects critical human capital support into the deep integration of the cultural and tourism industries through talent aggregation and skill benefits. This demonstrates that employment quality serves as an independent and indispensable transmission mechanism through which the digital economy empowers cultural-tourism integration.

2.4 New Quality Productivity: Concept, Economic Drivers, and Theoretical Foundations

New Quality Productivity (NQP) is a strategically significant economic development concept proposed and consistently emphasized by China in recent years. It transcends the simple aggregation and accumulation of traditional production factors, representing an advanced form of productive forces primarily driven by technological innovation and characterized by high-quality development. Its core essence lies in achieving leapfrog development through technological breakthroughs, innovative allocation of production factors, and deep industrial transformation and upgrading—encompassing workers, means of production, objects of labor, and their optimized integration. New Quality Productivity is characterized by high technology, high efficiency, and high quality. It not only emphasizes enhanced production efficiency but also prioritizes green, intelligent, and integrated development, reflecting a fundamental shift in economic growth from traditional resource-driven models to higher-level innovation-driven approaches. At the national level, cultivating new-quality productive forces is regarded as crucial for seizing the high ground in international competition, achieving sustainable development, and building a modern economic system. Consequently, it plays a pivotal role in resource allocation, industrial structure optimization, and regional economic model transformation, shaping the overall direction and capacity of regional economic development.

From different perspectives, understanding new-quality productive forces reveals that, in the theory of innovation ecosystems, highly developed new-quality productive forces herald a mature and vibrant innovation ecosystem. Within such ecosystems, regions typically prioritize developing cutting-edge technologies and strategic emerging industries. This implies scarce resources may be redirected toward these sectors, thereby influencing the marginal empowerment of the digital economy in specific industries (such as cultural tourism). From a resource-based view, as new-quality productive forces are cultivated and established, their valuable, scarce, difficult-to-imitate, and irreplaceable resources (such as top talent, advanced R&D laboratories, and venture capital) may be reallocated to areas most critical for achieving new competitive advantages. This strategic resource redistribution may implicitly shift the marginal focus of digital economy empowerment. Under dynamic capability theory, it posits that enterprises and regions develop the ability to sense, capture, and reconfigure resources. High-level new-quality productive forces imply that regions possess advanced dynamic capabilities, potentially prompting them to pursue complex, specialized, and “hard-tech”-intensive integration pathways in cultural-tourism convergence. This approach may diminish the relative importance of universal digital economic empowerment. Building on this foundation, existing research has begun exploring the positive impacts of new-quality productive forces on macroeconomic growth and industrial upgrading. However, its role as a moderating variable influencing the enabling effects of the digital economy within specific industries—particularly its potential negative moderating effects—remains an under-explored academic frontier. This study aims to precisely fill this gap and delve into the theoretical logic underlying this counterintuitive phenomenon.

3.1 Theoretical Framework Construction

Based on a comprehensive literature review of concepts including the digital economy, cultural-tourism integration, new infrastructure, employment quality, and new-quality productive forces, this study constructs a theoretical framework integrating mediation and moderation effects. This framework aims to comprehensively and deeply reveal the mechanisms through which the development of the digital economy influences the integration of the cultural-tourism industry across Chinese provinces. Within this framework, the level of digital economy development (DigitalEconomy) serves as the core independent variable, while the level of cultural and tourism industry integration (Integration) functions as the dependent variable. The proposed levels of new infrastructure (NewInfra) and employment quality (EmploymentQuality) represent two key mediating pathways through which the digital economy influences cultural-tourism integration. These pathways respectively embody the construction of physical and digital infrastructure during digital transformation, as well as the enhancement of human capital. These pathways were selected because they correspond to the hard conditions (infrastructure) and soft conditions (talent quality) required for industrial transformation, representing two fundamental and independent transmission dimensions through which the digital economy empowers industrial development, with clearly defined conceptual boundaries. Furthermore, we introduce New Quality Productivity (NQP) as a moderating variable to examine whether the intensity of the digital economy's promotional effect on cultural-tourism integration varies with regional economic development stages and industrial upgrading directions. This framework aims to transcend simple correlation analysis, delve into the “black box” of how the digital economy empowers cultural-tourism integration, and reveal the boundary conditions of its effects. The following outlines the theoretical mechanism roadmap of this paper.

Figure 1 Theoretical Mechanism Roadmap

3.2.2 Intermediary Pathway 1: The Conduction Effect of New Infrastructure

The promotional effect of the digital economy on the integration of the cultural and tourism industries is effectively transmitted through the development and improvement of new infrastructure. The rapid growth of the digital economy has triggered explosive demand for high-speed network connectivity, massive data storage, and advanced analytical capabilities. This has directly driven extensive investment and deployment in new infrastructure such as 5G base stations, big data centers, and artificial intelligence platforms. These advanced hardware and platforms provide indispensable physical infrastructure and technological support for the digital transformation, intelligent upgrading, and online-offline integration of the cultural and tourism industry. This aligns closely with the foundational role of infrastructure in industrial development, as revealed by infrastructure theory.

Specifically, in terms of connectivity empowerment, high-bandwidth, low-latency networks like 5G provide the essential low-latency, high-reliability connections required for smart scenic area development, high-definition online cultural content transmission, and immersive virtual reality (VR)/augmented reality (AR) experiences. This significantly promotes the deep integration of online cultural and tourism resources with offline physical experiences. In data empowerment, big data centers aggregate and analyze vast amounts of visitor behavior data and cultural consumption preferences. This provides scientific decision support for personalized customization of cultural and tourism products, precision marketing, and intelligent operational management, thereby optimizing the efficiency of supply-demand matching. In terms of intelligent empowerment, the deep integration of artificial intelligence and IoT technologies with new infrastructure accelerates the intelligent upgrade of the cultural tourism industry. Applications such as smart navigation, multilingual translation, and intelligent ticketing systems not only enhance the intelligence level and operational efficiency of cultural tourism services but, more importantly, reduce the cost of factor circulation. This promotes the cross-border flow and integration of diverse elements including culture, tourism, and technology. This ultimately accelerates the transformation of the cultural and tourism industry from single-sector operations to composite models, and from superficial collaboration to deep integration. Therefore, new infrastructure serves as the critical bridge between digital economic development and cultural-tourism integration. Its construction and refinement are pivotal for converting digital economy dividends into driving forces for cultural-tourism convergence. As the material foundation empowering the digital economy, it possesses an independent and distinct transmission mechanism.

3.2.3 Mediating Pathway 2: The Transmission Effect of Employment Quality

The promotional effect of digital economic development on the integration of the cultural and tourism industries can also be achieved through the pathway of enhancing employment quality. Employment quality is a multidimensional concept encompassing aspects such as optimization of employment structure, improvement in skill levels, enhancement of compensation and benefits, and creation of new employment opportunities. It serves as a key indicator for measuring workers' well-being and the quality of economic development. This aligns with the emphasis in human capital theory [Becker, 1964] on the role of human capital investment in boosting productivity and economic value. The vigorous development of the digital economy, particularly the rise of platform-based business models, has brought profound structural changes to the labor market, significantly diversifying employment forms within the cultural and tourism sector.

Specifically, the digital economy has spawned numerous high-tech, innovative new business formats and models. Examples include online tour guides, digital cultural creators, live-streaming hosts promoting intangible cultural heritage, and online cultural tourism marketers [Research on Digital Platform Economy, 2020; Research on the Gig Economy, 2021]. These emerging employment forms not only provide regional labor with more diversified, flexible, and often higher-income job options. More importantly, they drive rapid improvements in cultural and tourism practitioners' digital skills, professional knowledge, and interdisciplinary capabilities, thereby optimizing the overall employment structure to better adapt to the demands of the digital economy era. Technology-driven efficiency gains and specialization requirements have also increased the skill premium for practitioners, improving their compensation, benefits, and career prospects. As the skill levels and incomes of cultural and tourism workers generally rise, the industry's attractiveness to high-quality talent has significantly increased, creating a talent aggregation effect that further strengthens the human capital foundation for industrial integration. Therefore, the improvement in employment quality not only directly enhances workers' conditions but also injects critical human capital support into the deep integration of the cultural and tourism industries through talent aggregation and skill spillovers. This demonstrates that employment quality, as the human capital foundation empowered by the digital economy, possesses clear conceptual boundaries and independent mechanisms.

Q2:While the Literature Review section is comprehensive, it remains somewhat descriptive. It would benefit from a more critical synthesis of gaps in prior research, particularly regarding the negative moderating role of new-quality productivity. Explicitly contrasting this study with closely related empirical works would enhance the originality and contribution.（The modified content in the article has been highlighted in yellow.line229-255）

Response:

We fully agree with the reviewer's comment regarding the insufficient criticality of the literature review and appreciate the suggestion to highlight the originality and contributions of the study through a more critical synthesis and comparison. We have made the following major revisions to Chapter 2, “Literature Review”:

Strengthen the critical synthesis of research gaps：

The original text before revision: The summary of research gaps is relatively straightforward and lacks critical engagement with existing literature.

Research gap summary is relatively straightforward, lacking critical engagement with existing literature.

（1）There is a lack of systematic mechanism analysis regarding the complex process of digital economy empowering cultural and tourism integration, particularly in-depth examination of micro-level transmission pathways such as new infrastructure and employment quality. We emphasize that existing literature largely remains at the macro-level correlation stage, failing to fully reveal specific transmission chains.

（2）While international reports exist on the macro-level relationship between the digital economy and tourism, theoretical frameworks or empirical tests have yet to be developed regarding how the digital economy promotes cultural-tourism integration (especially cross-sectoral integration beyond single-industry digitization) or the effects of new-quality productive forces as a moderating variable (particularly its counterintuitive negative moderating role).

（3）Existing research rarely focuses on the provincial level in China, particularly considering the impact of regional heterogeneity, and has also failed to adequately account for China's unique contextual variable of “new quality productive forces.”

Revised Content: We have rewritten Section 2.5, “Research Prospects and Summary of Academic Gaps,” to enhance its criticality and focus. We now explicitly identify shortcomings in existing research across the following three dimensions:

Clearly contrast similarities and differences with existing research, highlighting originality (see Section 2.5 for details):

Original text: Less direct comparison of specific differences between this paper and existing empirical work.

Revised content: We have added explicit comparisons with existing research in Section 2.5. While acknowledging the prevailing literature that recognizes the positive impact of the digital economy on industrial development, we emphasize the uniqueness and originality of our study through the following approaches: 1) Focusing on the complex topic of cultural-tourism integration; 2) Deeply analyzing two specific transmission mechanisms: new infrastructure and employment quality; 3) Innovatively introducing and validating the unique moderating variable of new-quality productivity, particularly its counterintuitive negative effect; 4) Discussing China's provincial-level experience within a global context. This comparison powerfully highlights the paper's innovations in theoretical depth and research scope.

2.5 Research Outlook and Summary of Academic Gaps

Based on the above literature review, while existing research has preliminarily explored the impact of the digital economy on industrial development, significant gaps remain in understanding how the digital economy profoundly drives the integration of cultural and tourism industries: First, there is a lack of systematic analysis of the mechanisms through which the digital economy enables the complex process of cultural-tourism integration, particularly in-depth examination of micro-level transmission pathways such as new infrastructure and employment quality. Most existing literature remains at the macro-level correlation stage, failing to fully reveal specific transmission chains.

Second, while international reports from organizations like UNWTO, OECD, and the EU on the digital economy and tourism have outlined macro trends and policy recommendations regarding the digital economy's impact on tourism, the role of the digital economy in promoting cultural-tourism integration—particularly within China's unique developmental context—remains understudied. The effects of new-quality productive forces as a key moderating variable (especially its negative moderating role) have yet to be theoretically constructed or empirically tested. This constitutes a significant and counterintuitive gap in understanding the boundary conditions and contextual nuances of digital economy effects, particularly how advanced innovation-driven development alters the logic of digital empowerment.

Third, existing research rarely focuses on the complex interactions between the digital economy and cultural-tourism integration at China's provincial level, especially considering the impact of regional heterogeneity. Furthermore, existing studies predominantly rely on official statistics, potentially underestimating the contribution of informal cultural and tourism activities to integration—a limitation in data representativeness.

This study aims to address these gaps by constructing and empirically testing an integrated theoretical framework incorporating mediation and moderation mechanisms. It seeks to deeply reveal the pathways, intensity, and boundary conditions through which digital economic development influences the integration of cultural and tourism industries across Chinese provinces. By synthesizing international research with Chinese experience, it provides more refined theoretical guidance and policy recommendations for high-quality development of the cultural and tourism industries in the digital era, while exploring its applicability to other developing countries.

Q3:This study relies heavily on entropy index construction for the key variables. More details should be provided about indicator selection, weighting procedures, and robustness checks of the indices. For reproducibility, a supplementary appendix with the full list of indicators and data sources should be included.（The modified content in the article has been highlighted in yellow.line429-444）

Response:

We fully agree with the reviewer's emphasis on the importance of transparency and reproducibility in index construction. In response to this comment, we have submitted the data metric system used in this paper's entropy weight method in the supplementary appendix.

Original text before revision: Only mentioned the use of the entropy method to calculate the index, lacking details on specific sub-indicators and the weighting process.

Revised Content: In Section 4.1, we have explicitly listed the dimensions and sub-indicators included in each core composite index (cultural-tourism integration, digital economy development, employment quality, new infrastructure, and new productive forces). Additionally, the appendix provides a detailed breakdown of all indicators derived using the entropy weighting method.

4.1 Data Sources and Definitions

This study utilizes annual balanced panel data from 2011 to 2023, spanning 13 consecutive years, covering 31 provinces, autonomous regions, and municipalities directly under the central government in China (excluding Hong Kong, Macao, and Taiwan regions). The primary data sources include the China Statistical Yearbook, China Cultural and Tourism Statistical Yearbook, China Digital Economy Development White Paper, China Labor Statistical Yearbook, as well as provincial statistical yearbooks and statistical bulletins on national economic and social development from each province, autonomous region, and municipality. The indicator system employed in this study includes control variables such as cultural and tourism industry integration, digital economy development, employment quality, new infrastructure construction, new quality productive forces, economic development, fiscal investment, openness index, urbanization level, and resident consumption index. The dependent variable is the level of cultural and tourism industry integration, while the independent variable is the level of economic development. The mediating variables—employment quality and new infrastructure construction—and the moderating variable—new quality productive forces—are quantified using entropy indices. The cultural and tourism integration indicator system comprises one primary indicator (cultural and tourism industry integration), two tertiary indicators (industry integration resource foundation, industry integration support, industry integration scale), and 28 corresponding tertiary indicators. The new infrastructure indicator system comprises one primary indicator (new infrastructure), three secondary indicators (information infrastructure, convergence infrastructure, innovation infrastructure), and 32 corresponding tertiary indicators. The employment quality indicator system similarly consists of one primary indicator (employment quality), four secondary indicators (employment environment, employment compensation, employment capability, employment protection), and 18 tertiary indicators. The New Quality Productivity indicator system comprises 3 first-level indicators (New Quality Workforce, New Quality Labor Objects, New Quality Labor Resources), 7 second-level indicators (New Quality Human Capital Input, New Quality Human Capital Output, Informatization Level, Ecological Environment, Technology R&D and Innovation, Infrastructure Construction), and 20 corresponding indicators. Specific indicator quantities are shown in Table 1.

Q4:Although the paper mentions Hausman and VIF tests, potential endogeneity between digital economy development and cultural-tourism integration remains. I suggest incorporating instrumental variable techniques, dynamic panel models (e.g., system GMM), or placebo tests to better establish causality.

（The modified content in the article has been highlighted in yellow.line524-532）

Response:

We are deeply grateful to the reviewers for their critical suggestions regarding endogeneity issues. We acknowledge that endogeneity represents a core challenge affecting the rigor of causal inference in panel data analysis. In response to this comment, we have made the following modifications and clarifications in Chapter 4, “Model Design and Instrument Selection”:

Introduction of instrumental variables (IV) regression (2SLS) (see Section 4.3.1 for details):

Original text: Only mentioned that two-way fixed effects can control for time-invariant heterogeneity.

Revised text: We explicitly stated in Section 4.3.1 “Addressing Endogeneity Issues” that we would introduce an instrumental variables (IV) regression and employ two-stage least squares (2SLS) for estimation. We selected the lagged two-period value of digital economy development (L2.Digital_Economy_w) as the instrumental variable. We explain the theoretical rationale for selecting a lagged variable as the instrument: Prior digital economic development can influence the current level of digital economy (correlation), but its direct impact on the current level of cultural-tourism integration (beyond the path through the current digital economy) is weak (exogeneity). We commit to reporting the identification tests for the instrumental variables, including weak identification, non-identification, and over-identification tests (where applicable).

4.3.1 Addressing Endogeneity Issues

There may exist a “common origin” (bidirectional causality) between the integration of the digital economy and the cultural tourism industry, as well as shared influence from other unobserved time-varying variables. Although all core models employ bidirectional fixed effects (implemented via the reghdfe command), which largely eliminate omitted variable bias caused by province-level variables that do not vary over time, further testing is required to address potential bidirectional causality and time-varying omitted variables.

(1) Hausman Test: This study will conduct a Hausman test on the benchmark model to assess the suitability of the fixed-effects model relative to the random-effects model, thereby providing statistical justification for selecting the bidirectional fixed-effects model.

(2) VIF Test: Subsequently, a variance inflation factor (VIF) test will be performed to evaluate whether severe multicollinearity exists among the explanatory variables in the model, ensuring the stability of the estimation results.

(3) Instrumental Variables (IV) Regression (2SLS): To address potential reverse causality and time-varying omitted variable issues, this study employs instrumental variables (IV) regression using two-stage least squares (2SLS) estimation. We select the lagged two-period value of digital economy development (L2.Digital_Economy_w) as the instrumental variable (iv_DE). The theoretical rationale for selecting a lagged variable as the instrument lies in the fact that prior digital economic development influences the current level of the digital economy (correlation), but its direct impact on the current integration of culture and tourism (beyond the path through the current digital economy) is weak (exogeneity). We will report the identification tests for the instrumental variables, including the Weak Identification Test, the Underidentification Test, and the Overidentification Test (if applicable).

Q5:The negative moderation effect of new-quality productivity is intriguing but requires more nuanced discussion. The current explanation relies mainly on resource dilution and maturity effects. Alternative explanations (e.g., institutional constraints, crowding-out of tourism by high-tech sectors) should be considered, supported by additional case evidence or robustness analysis.（The modified content in the article has been highlighted in yellow.line354-357、line360-362、line400-403）

Response:

We greatly appreciate the reviewer's keen attention to the core finding regarding the negative moderating effect of new-type productive forces and concur that it requires more detailed and comprehensive theoretical elaboration and justification. In response to this comment, we have made the following substantial revisions to Section 3.2.4 of Chapter 3 and Section 5.5.6 of Chapter 5:

Expanding the Theoretical Foundation and Diverse Interpretations of Negative Moderation Mechanisms (see Section 3.2.4 of Chapter 3):

Original Text: Explanations for negative moderation effects primarily relied on resource dilution and maturity effects.

Revised Content: We substantially expanded Section 3.2.4, “Moderation Effects: Boundary Conditions for New Quality Productivity,” providing richer and more theoretically grounded interpretations:

Resource Dilution or Crowding-Out Effects: We now explicitly incorporate the Resource-Based View (RBV) [Penrose, 1959; Barney, 1991] to explain how scarce digital economy resources (including policies, funding, and talent) in high-NQP regions are strategically prioritized for high-tech and strategic emerging industries. This creates a “crowding-out” or “dilution” effect on universal digital empowerment within the cultural-tourism integration sector. We explicitly mention the “crowding-out effect of high-tech industries on tourism” as a concrete manifestation of resource dilution.

Differentiated Integration Pathways or Maturity Effect: We now incorporate innovation ecosystem theory [Adner, 2006] and disruptive innovation theory [Christensen, 1997] to explain that in high NQP regions, cultural-tourism integration has entered a more mature stage. Its trajectory shifts toward more refined, specialized, and even “hardcore technology”-driven integration models, thereby diminishing the marginal effects of universal digital empowerment.

Development stage and priority differences: We emphasize how economic development stages determine industrial strategic priorities. In high NQP regions, cultural-tourism integration may serve more as a supplement to economic development rather than a priority area for digital resource allocation. This section also indirectly addresses the “institutional constraints” perspective: in advanced NQP regions, institutional frameworks may favor technological innovation over the cross-departmental coordination and flexible policies required for cultural-tourism integration, thereby impacting the effective utilization of digital economy resources.

5.5.6 Moderation Effect Robustness Test: NQP Subgroup Analysis

To further validate the negative moderating effect of new quality productivity on the promotion of cultural-tourism integration through the digital economy, this study categorizes the sample provinces into a high NQP group (R=1) and a low NQP group (R=0) based on their NQP levels. Separate regression analyses are conducted for the impact of digital economic development on cultural-tourism integration within each group.

Table 11 Moderation Effect Robustness Test: Regression Results for NQP Group Subsamples
VARIABLES	Low NQP Group Cultural and Tourism Industry Integration	High NQP Group: Cultural and Tourism Industry Integration
Digital Economy	0.4418*** (0.1147)	0.1512** (0.0587)
Contorls	Yes	Yes
Constant	0.1168*** (0.0087)	0.1982*** (0.0115)
Observations	201	201
R-squared	0.9831	0.9900
Robust standard errors in parentheses * p<0.01, p<0.05, * p<0.1

The results of the NQP subgroup sample analysis strongly support the negative moderating effect of new-quality productive forces on the promotion of cultural-tourism integration by the digital economy. In the low NQP group (R=0), the level of digital economic development significantly and substantially promotes cultural-tourism integration, with a coefficient of 0.4418, significant at the 1% level (P=0.001). This indicates that in regions with relatively underdeveloped NQP, investments in the digital economy yield stronger marginal effects and more pronounced promotional impacts. In the high NQP group (R=1), the digital economy's level significantly promotes cultural-tourism integration (coefficient 0.1512, significant at the 5% level, P=0.015), though its coefficient magnitude is notably smaller than that of the low NQP group (0.1512 < 0.4418). Inter-group coefficient difference calculations reveal that the promotion effect in the high NQP group is approximately 0.2906 smaller than that in the low NQP group (0.4418 - 0.1512 = 0.2906). Given the significant disparity in coefficient magnitude and respective statistical significance, this difference holds both economic relevance and statistical indication. This result provides intuitive and robust validation of the negative moderating effect of new-quality productivity on the promotion of cultural-tourism integration by the digital economy. Specifically, higher NQP levels weaken the digital economy's promotional effect on cultural-tourism integration. This further reinforces the theoretical interpretation of this study: digital empowerment exhibits contextual dependency, potentially facing resource dilution, transformation of integration pathways, or adjustments in development priorities under high NQP conditions.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This is a timely and relevant study linking the digital economy, cultural–tourism integration, and regional development in China. Its strengths lie in the application of a moderated mediation model with provincial panel data and the novel introduction of new-quality productivity (NQP) as a boundary condition. Nonetheless, substantial revisions are needed to clarify methodological details, deepen the interpretation of findings, and strengthen the policy implications for sustainability and inclusivity.

1. Methodology
Sampling & Data Sources: The study uses panel data from 31 provinces (2011–2023), drawing on multiple statistical yearbooks. While comprehensive, the reliance on official statistics may underrepresent informal cultural and tourism activities. This limitation is noted but should be more clearly emphasized as it affects representativeness.
Framework: The integration of digital economy variables with mediators (infrastructure, employment quality) and moderator (NQP) is theoretically sound. However, more transparency is needed in operationalization and entropy-based index construction. For example, how were “employment quality” and “new infrastructure” validated, and do they align with existing benchmarks?
Data Analysis: The two-way fixed effects model is appropriate. Yet the treatment of results is largely descriptive. The study would benefit from additional inferential robustness tests (e.g., lagged variables, endogeneity checks beyond Hausman) and clearer interpretation of effect sizes in substantive terms.

2. Results and Discussion
Findings: The study demonstrates that digital economy growth significantly promotes cultural–tourism integration, with infrastructure and employment quality serving as mediators. NQP negatively moderates this relationship. These results are novel but require deeper theoretical interpretation. Why does NQP dilute digital economy effects—resource diversion, maturity effects, or changing policy priorities? A more systematic linkage to resource allocation and innovation ecosystem theories would help.
Regional Analysis: The heterogeneity findings (east vs. west vs. central China) are important. However, the discussion could further explore why the western region shows the strongest incremental benefits and how policy capacity differs across regions.
Policy Implications: While the manuscript provides broad suggestions (digital infrastructure, employment quality, differentiated strategies), they remain generalized. Stronger, context-based recommendations (e.g., VR/AR in heritage tourism, blockchain for cultural IP, targeted workforce training) would enhance policy relevance.

3. Conclusions
The conclusions align with the empirical results, emphasizing the catalytic role of the digital economy and the mediating importance of infrastructure and human capital. However, the study risks overgeneralization by assuming similar effects across all provinces. In provinces with high NQP, integration may follow very different trajectories. This limitation should be explicitly discussed, as it affects the generalizability of the model beyond China.

Comments on the Quality of English Language

The manuscript is generally well-written and understandable, but the English could be improved to enhance clarity and readability. Several sentences are overly long and complex, which may obscure the main points. A light to moderate language edit focusing on conciseness, grammar, and flow would help ensure that the arguments and findings are communicated more clearly to an international readership.

Author Response

Q1. 1.1Methodology Sampling & Data Sources: The study uses panel data from 31 provinces (2011–2023), drawing on multiple statistical yearbooks. While comprehensive, the reliance on official statistics may underrepresent informal cultural and tourism activities. This limitation is noted but should be more clearly emphasized as it affects representativeness.
Framework: The integration of digital economy variables with mediators (infrastructure, employment quality) and moderator (NQP) is theoretically sound. However, more transparency is needed in operationalization and entropy-based index construction. For example, how were “employment quality” and “new infrastructure” validated, and do they align with existing benchmarks?
Data Analysis: The two-way fixed effects model is appropriate. Yet the treatment of results is largely descriptive. The study would benefit from additional inferential robustness tests (e.g., lagged variables, endogeneity checks beyond Hausman) and clearer interpretation of effect sizes in substantive terms.(The modified content in the article has been highlighted in yellow.line997-1001、line1013-1015、line1020-1028)

Response :

We appreciate the reviewer's keen insight into the limitations of data sources. We fully agree that underestimating informal economic activities is a common challenge in studies based on official statistics. In response to this comment, we have made the following revisions to the “Limitations” section in Chapter 7, “Conclusions, Limitations, and Future Research Prospects”:

More clearly emphasize the limitations of data sources (see Section 7.2 of Chapter 7):

Original text: The limitations section may broadly mention data constraints.

Revised text: We have added and more clearly emphasized this limitation in Section 7.2 “Limitations”: "The data for this study primarily originate from official statistical yearbooks, which may to some extent underestimate the contribution of informal cultural and tourism activities to the integration of culture and tourism. Informal activities, such as those by individual artisans or unregistered cultural events, may play significant roles in regional cultural-tourism ecosystems. Their absence may affect the representativeness of the data in certain aspects." We also suggest that future research could attempt to address this gap by combining big data, surveys, or qualitative studies.

7.2 Limitations

Despite rigorous methodology and analytical depth, this study has certain limitations that warrant future refinement:

(1)Limitations in Index Construction: This study employed the entropy method to construct composite indices for cultural-tourism integration, digital economic development, new infrastructure, employment quality, and new-quality productive forces. While the entropy method enables objective weighting, these composite indices—particularly for complex concepts like “cultural-tourism integration” and “new-quality productive forces”—may not fully capture all nuanced dimensions. Examples include qualitative aspects of cultural experiences or the specific technological components of NQP. Furthermore, data primarily sourced from official statistical yearbooks may underestimate the contribution of informal cultural and tourism activities to integration. Such informal sectors—including individual artisans and unregistered cultural events—potentially play vital roles in regional cultural-tourism ecosystems, and their exclusion may compromise representativeness in certain dimensions.

(2)Challenges in Causal Inference: Although this study employs a robust two-way fixed-effects model and conducts multiple robustness tests to mitigate potential endogeneity issues (e.g., omitted variable bias due to time-invariant factors), completely eliminating interference from all unobserved time-varying factors remains challenging. Specifically, potential reverse causality (e.g., highly integrated cultural-tourism industries may more actively drive digital economic development) or unmeasured time-varying confounding factors remain. Future research could explore stronger identification strategies, such as quasi-natural experiments stemming from policy shocks or instrumental variable methods, to further strengthen the rigor of causal inference.

(3)In-depth Analysis of Negative Moderation Mechanisms: This paper theoretically explains the negative moderating effects on new quality productivity through resource dilution, integration path maturity, and development priorities. However, the intrinsic operational logic and relative importance of these proposed mechanisms require more granular empirical validation. For instance, quantifying the extent of resource reallocation or specifying the characteristics of “differentiated integration paths” at high NQP levels would enrich the analysis.

(4)Data granularity limitations: This study relies on provincial-level aggregated data, which while reflecting macro-regional characteristics and general trends, may obscure heterogeneity at sub-provincial, city, or enterprise levels. Specific manifestations of cultural-tourism integration and digital economy empowerment may exhibit significant variations across finer geographic or organizational scales.

(5)Limitations of Model Generalizability: While this study explores the complex relationship between the digital economy and cultural-tourism integration at the provincial level, its findings—particularly the negative moderating effect of new-quality productivity—suggest potential limitations in the model's generalizability across different developmental stages and industrial structure contexts. In provinces with high NQP levels, the development trajectory of cultural-tourism integration may indeed follow markedly different logic, driven more by deep innovation and specific technology applications than by the inclusive empowerment of the digital economy. This context-dependence implies that caution is warranted when directly extrapolating the model's specific findings to other countries or regions—especially those with vastly different NQP development levels and industrial structures.

Q1.1.2 Framework: The integration of digital economy variables with mediators (infrastructure, employment quality) and moderator (NQP) is theoretically sound. However, more transparency is needed in operationalization and entropy-based index construction. For example, how were “employment quality” and “new infrastructure” validated, and do they align with existing benchmarks?（The modified content in the article has been highlighted in yellow.line429-444、)

Response :

We greatly appreciate the reviewers' requests for operational transparency and details regarding index construction. This overlaps with Reviewer 1's comment 1.3, and we have implemented comprehensive measures to address it:

Original text before revision: Only mentioned the use of the entropy method to calculate the index, lacking details on specific sub-indicators and the weighting process.

4.1 Data Sources and Definitions

Explanation of benchmarking and validation for “employment quality” and “new infrastructure” (see Chapter 2, Sections 2.2 and 2.3, and the newly added Appendix A):（The modified content in the article has been highlighted in yellow.line152-157、line162-164、line170-175、line190-192)

Original text before revision: Lack of clear explanation on whether the index benchmarks against existing standards.

Revised Content:

In the literature review sections of Section 2.2 “New Infrastructure” and Section 2.3 “Employment Quality,” we have supplemented the explanation that the measurement dimensions for these concepts are constructed based on definitions and guidelines from relevant international organizations (e.g., ILO, UNCTAD) or authoritative domestic institutions (e.g., National Development and Reform Commission, Ministry of Culture and Tourism). This ensures theoretical alignment with existing benchmarks.

In the newly added Appendix A, we further detail how each sub-indicator selection references commonly used indicator systems from domestic and international research to enhance validity and benchmarking. For instance, the sub-indicators for “employment quality” encompass dimensions such as compensation, benefits, job stability, and skills training, all of which align with the ILO's “Decent Work” framework. Similarly, the sub-indicators for “new infrastructure” include metrics like the number of 5G base stations and data center investments, which are highly consistent with the definitions established by the National Development and Reform Commission.

2.2 New Infrastructure: Concept, Functions, and Integration with Cultural Tourism

2.3 Employment Quality: Concept, Dimensions, and Its Relationship with Cultural-Tourism Integration

Q1.1.3 Data Analysis: The two-way fixed effects model is appropriate. Yet the treatment of results is largely descriptive. The study would benefit from additional inferential robustness tests (e.g., lagged variables, endogeneity checks beyond Hausman) and clearer interpretation of effect sizes in substantive terms.（The modified content in the article has been highlighted in yellow.line524-532、line554-564)

Response :

We greatly appreciate the reviewers' suggestions regarding the depth of data analysis and interpretation of results. We fully agree on the need for stronger inferential robustness tests and more substantive effect interpretations. This overlaps with Reviewer 1's comment 1.4, and we have implemented the following comprehensive measures:

Strengthening inferential robustness tests (see Sections 4.3.1 and 4.3.2 in Chapter 4):

Original text: Only mentioned Hausman and VIF tests along with two-way fixed effects.

Revised content:

In Section 4.3.1 “Addressing Endogeneity Concerns,” we explicitly plan to introduce instrumental variables (IV) regression using two-stage least squares (2SLS). We emphasize that 2SLS effectively addresses endogeneity in independent variables and omitted unobserved individual effects, significantly enhancing the rigor of causal inference. We will report relevant instrumental variable tests (weak identification, non-identifiability, over-identification).

4.3.1 Addressing Endogeneity Issues

5.5.5 Endogeneity Testing: Instrumental Variables (IV) Regression (2SLS)

To further address potential endogeneity issues, this study employs instrumental variables (IV) regression, specifically the two-stage least squares (2SLS) method. We select the lagged two-period value of the digital economy development level (L2.Digital_Economy_w, denoted as iv_DE) as the instrumental variable for the core independent variable (Digital_Economy_w). Table 5-9 presents the primary results of the 2SLS regression, including the instrumental variable diagnostic statistics from the first-stage regression and the results from the second-stage regression.

Table 10 Instrumental Variables (IV-2SLS) Regression Results
VARIABLES	Digital Economy （Phase One）	Integration（Phase Two）
L2. Digital Economy (iv_DE)	1.1257* (0.0328)
Digital Economy		0.6368* (0.0449)
Contorls	Yes	Yes
Constant	0.0111*** (0.0018)	0.1092*** (0.0055)
Observations	341	341
R-squared	0.9901	0.9360
Cragg-Donald Wald F	7045.061*
Kleibergen-Paap rk Wald F	1177.858*
Stock-Yogo 10% IV Size	16.38
Robust standard errors in parentheses * p<0.01, p<0.05, * p<0.1

The instrumental variable (IV-2SLS) regression results significantly strengthen the causal inference power of this study regarding the promotion of cultural and tourism integration through digital economic development. First, regarding the validity of the instrumental variables, all metrics indicate the selection was appropriate: the unidentifiability test (Kleibergen-Paap rk LM statistic of 12.09, P-value of 0.0005) strongly rejects the null hypothesis of model unidentifiability, confirming significant correlation between the instrumental variables and the endogenous variables. In the weak identification test, both the Cragg-Donald Wald F-statistic (7045.061) and the Kleibergen-Paap rk Wald F-statistic (1177.858) far exceeded the 10% maximum IV size threshold of 16.38 for the Stock-Yogo weak identification test, ruling out weak identification issues and indicating sufficient explanatory power of the instrumental variables. Although the Hansen J statistic yields a P-value of 0.000, since this model is perfectly identified (one endogenous variable corresponds to one excluded instrumental variable), the Hansen J statistic is typically not used to test the over-identification constraint in this context, rendering its P-value non-interpretable. The core rationale lies in selecting two-period lagged values of the digital economy as instrumental variables, which theoretically ensures reasonable exogeneity: prior digital economic development can influence the current level of the digital economy, but its direct impact on the current cultural-tourism integration (beyond the path through the current digital economy) is relatively weak.

Q2. Results and Discussion

Q2.2.1Findings: The study demonstrates that digital economy growth significantly promotes cultural–tourism integration, with infrastructure and employment quality serving as mediators. NQP negatively moderates this relationship. These results are novel but require deeper theoretical interpretation. Why does NQP dilute digital economy effects—resource diversion, maturity effects, or changing policy priorities? A more systematic linkage to resource allocation and innovation ecosystem theories would help.（The modified content in the article has been highlighted in yellow.line354-357、line360-362、line400-403、line209-227、line881-909)

Response :

We are deeply grateful to the reviewers for acknowledging the novelty of our findings and highlighting the need for deeper theoretical interpretation. This comment overlaps significantly with Reviewer 1's Comment 1.5. We have incorporated the following comprehensive revisions in Section 3.2.4 of Chapter 3 and Section 6.2 of Chapter 6:

Deepening the Theoretical Explanation of Negative Moderation Effects (see Section 3.2.4 of Chapter 3):

Original Text: The explanation primarily relies on resource dilution and maturity effects.

Revised Content: We substantially expanded Section 3.2.4, “Moderation Effects: Boundary Conditions for New Quality Productivity,” introducing a richer, more theoretically grounded explanatory framework:

（1）Resource Dilution or Crowding-Out Effect: Explicitly incorporates the Resource-Based View (RBV) [Penrose, 1959; Barney, 1991] to explain how scarce digital economy resources (including policies, funding, and talent) in high-NQP regions are strategically prioritized for high-tech and strategic emerging industries. This creates a “crowding-out” or “dilution” effect on universal digital empowerment within the cultural-tourism integration sector. We explicitly mention the **“crowding-out effect of high-tech industries on tourism”** as a concrete manifestation of resource dilution.

（2）Differentiated Integration Pathways or Maturity Effect: Drawing on innovation ecosystem theory [Adner, 2006] and disruptive innovation theory [Christensen, 1997] to explain that in high NQP regions, cultural-tourism integration has entered a more mature and specialized development phase. Its trajectory shifts toward a “hardcore technology” integration model deeply intertwined with core high-tech industries, thereby diminishing the marginal effects of universal digital empowerment.

（3）Differences in Development Stage and Priorities: This section emphasizes how economic development stages influence industrial strategic priorities. In high NQP regions, cultural-tourism integration may serve more as a supplementary driver of economic growth rather than a priority area for digital resource allocation. This indirectly incorporates the “institutional constraints” perspective—where institutional frameworks may favor technological innovation over the cross-departmental coordination and flexible policies required for cultural-tourism integration, thereby impacting the effective utilization of digital economy resources.

3.2.4 Moderating Effect: Boundary Conditions of New Quality Productivity

One of the core findings of this study is that New Quality Productivity (NQP) exerts a significant negative moderating effect on the relationship between the digital economy and the integration of cultural and tourism industries. This implies that as a province's NQP level increases, the promotional role of the digital economy in cultural-tourism integration will relatively diminish. This empirical result may seem counterintuitive, yet it embodies profound theoretical logic and practical considerations, challenging simplistic linear interpretations of digital empowerment. Its underlying mechanisms can be explained through the following aspects:

First, the resource dilution or crowding-out effect. Provinces with higher NQP levels typically rely heavily on cutting-edge technological innovation and strategic emerging industries for economic development. From the Resource-Based View (RBV) perspective [Penrose, 1959; Barney, 1991], these regions possess valuable and often scarce digital economy resources, including policy support, fiscal investment, high-end technical talent, and venture capital. These resources are more likely to be prioritized for strategic emerging industries perceived as having greater future potential and “new-quality” attributes, such as AI chip R&D, biopharmaceuticals, quantum computing, high-end equipment manufacturing, or new materials. These industries often feature higher technological barriers, longer R&D cycles, stronger potential marginal returns, and greater international competitiveness, making them more attractive to high-quality resources within the digital economy. This implies that even provinces with large overall digital economies may allocate relatively less marginal investment and attention to cultural-tourism integration. Under this “lighthouse effect” of resource allocation, cultural-tourism integration may experience some ‘dilution’ or “crowding out” in benefiting from digital economy dividends, thereby weakening the digital economy's promotional role in this sector.

Second, there is the effect of differentiated integration pathways or maturity levels. In provinces driven by high NQP, the integration of cultural and tourism industries may have already reached a relatively high level of maturity. Their integration development path may no longer primarily rely on the universal empowerment of the digital economy, such as basic online platform construction or digital marketing. Instead, cultural and tourism integration in these regions may have shifted toward more refined, specialized, or even “hardcore technology” integration models deeply intertwined with core high-tech industries. This aligns with insights from innovation ecosystem theory [Adner, 2006] and disruptive innovation theory [Christensen, 1997], which suggest that within advanced innovation ecosystems, mature industries transcend basic digital applications to pursue more complex, specialized, and disruptive forms of integration. For instance, applying cutting-edge virtual reality (VR)/augmented reality (AR) technologies to create immersive digital museums and virtual tourism experiences; leveraging blockchain to secure cultural copyright transactions and traceability; or utilizing big data analytics and artificial intelligence for intelligent destination management and precision services. In such scenarios, the marginal incremental effect of universal digital economy empowerment becomes limited. This is because the drivers of convergence shift from simply increasing the level of digital economic development to deeper technological innovation capabilities, more complex innovation ecosystem coordination, and vertical applications of specific cutting-edge technologies. Consequently, once regional innovation capacity and industrial upgrading reach a certain stage, the higher the overall level of the digital economy, the less pronounced its universal effect on promoting cultural-tourism integration becomes—potentially even exhibiting diminishing marginal returns.

Finally, differences in development stages and priorities come into play. Economic development stages dictate strategic priorities across industries. In provinces with underdeveloped NQP, the cultural and tourism industry may be in the early stages of digital transformation. Any investment in the digital economy can deliver significant momentum, achieving rapid progress from “nothing to something” or “little to more.” This marginal effect is particularly critical and pronounced. However, in provinces that have already established NQP advantages, the economic focus may have successfully shifted toward strategic emerging industries with greater future growth potential and international competitiveness. In overall resource allocation considerations, the integrated development of the cultural and tourism industry may now serve more as a complementary or extended outcome of economic development rather than a priority area for concentrated digital economy resources. This difference in development priorities leads to diminishing marginal effects of the digital economy in promoting cultural-tourism integration. This implies that in provinces pursuing higher-quality development and innovation leadership, the additional catalytic role of the digital economy in cultural-tourism integration will be relatively weakened.

Systemic Linkage of Resource Allocation and Innovation Ecosystem Theory (see Section 2.4 of Chapter 2 and Section 6.2 of Chapter 6):

Original text before revision: The theoretical foundation of NQP is not strongly linked to the aforementioned theories.

Revised Content: In Section 2.4, “New Quality Productivity: Concept, Economic Drivers, and Theoretical Foundations,” we have added systematic links between NQP and theories of innovation ecosystems, the resource-based view, and dynamic capabilities theory, providing a robust theoretical foundation for explaining negative moderation effects. In Section 6.2, “Theoretical Contributions,” we elaborate on these theoretical dialogues as the core theoretical contributions of this paper.

2.4 New Quality Productivity: Concept, Economic Drivers, and Theoretical Foundations

New Quality Productivity (NQP) is an economic development concept of strategic significance proposed and consistently emphasized by China in recent years. It transcends the simple aggregation and accumulation of traditional production factors, representing an advanced form of productive forces primarily driven by technological innovation and characterized by high-quality development. Its core essence lies in achieving leapfrog development through technological breakthroughs, innovative allocation of production factors, and deep industrial transformation and upgrading—encompassing workers, means of production, objects of labor, and their optimized integration. New Quality Productivity is characterized by high technology, high efficiency, and high quality. It not only emphasizes enhanced production efficiency but also prioritizes green, intelligent, and integrated development, reflecting a fundamental shift in economic growth from traditional resource-driven models to higher-level innovation-driven approaches. At the national level, cultivating new-quality productive forces is regarded as crucial for seizing the high ground in international competition, achieving sustainable development, and building a modern economic system. Consequently, it plays a pivotal role in resource allocation, industrial structure optimization, and regional economic development model transformation, shaping the overall direction and capacity of regional economies.

From different perspectives, understanding new-quality productive forces reveals that, in the theory of innovation ecosystems, highly developed new-quality productive forces herald a mature and vibrant innovation ecosystem. Within such ecosystems, regions typically prioritize developing cutting-edge technologies and strategic emerging industries. This implies that scarce resources may be redirected toward these sectors, thereby influencing the marginal empowerment of the digital economy in specific industries (such as cultural tourism). From a resource-based view, as new-quality productive forces are cultivated and established, their valuable, scarce, difficult-to-imitate, and irreplaceable resources (such as top talent, advanced R&D laboratories, and venture capital) may be reallocated to areas most critical for achieving new competitive advantages. This strategic resource redistribution may implicitly shift the marginal focus of digital economy empowerment. Under dynamic capability theory, it posits that enterprises and regions develop the ability to sense, capture, and reconfigure resources. High-level new-quality productive forces imply that regions possess advanced dynamic capabilities, potentially prompting them to pursue complex, specialized, and “hard-tech”-intensive integration pathways in cultural-tourism convergence. This approach may diminish the relative importance of universal digital economy empowerment. Building on this foundation, existing research has begun exploring the positive impacts of new-quality productive forces on macroeconomic growth and industrial upgrading. However, its role as a moderating variable influencing the enabling effects of the digital economy within specific industries—particularly its potential negative moderating effects—remains an under-explored academic frontier. This study aims to precisely fill this gap and delve into the theoretical logic underlying this counterintuitive phenomenon.

6.2 Theoretical Contributions

The findings of this study contribute to existing theory and literature in multiple dimensions:

(1) Deepening the understanding of how the digital economy empowers industrial development. While prior research primarily focuses on the macro-level impact of the digital economy on industrial development, this study delves into how the digital economy specifically channels its promotional effects on cultural-tourism integration through two dimensions: new infrastructure as a physical carrier and employment quality as a human capital dimension. This provides empirical evidence for understanding micro-level transmission mechanisms, aiding in the development of more refined theories on the impact pathways of the digital economy.

(2) It innovatively introduces and validates the moderating role of new-quality productivity. This study is the first to introduce and empirically test the moderating effect of new-quality productivity (NQP) in the field of cultural-tourism integration, revealing its counterintuitive negative moderation phenomenon. This finding enriches our understanding of the boundary conditions for the driving effects of the digital economy, indicating that the enabling logic of the digital economy may shift under different developmental stages and industrial structures. It offers new perspectives and empirical support for applying resource endowment theory [Penrose, 1959], innovation ecosystem theory [Adner, 2006], and dynamic capability theory [Teece, 2018] within the digital economy context.

(3) Expanded the research scope of cultural tourism integration. By incorporating cutting-edge concepts such as the digital economy, new infrastructure, employment quality, and new-quality productive forces into the analysis framework of cultural-tourism integration, a more comprehensive and explanatory theoretical model was constructed. This broadens the boundaries of influencing factors in cultural-tourism integration and provides a new analytical paradigm for subsequent research in this field.

(4) It offers unique insights within the Chinese context while enhancing global perspectives. Focusing on the provincial level in China, the study accounts for regional heterogeneity and integrates analysis with China's distinctive development concept of “new quality productivity.” This provides empirical evidence for understanding the practices and complexities of the digital economy within China's socialist market economy system. By referencing and contrasting international literature, it helps the global academic community better comprehend the patterns and challenges of China's digital economic development, as well as its similarities and differences with global trends.

Q2.2.2 Regional Analysis: The heterogeneity findings (east vs. west vs. central China) are important. However, the discussion could further explore why the western region shows the strongest incremental benefits and how policy capacity differs across regions. Policy Implications: While the manuscript provides broad suggestions (digital infrastructure, employment quality, differentiated strategies), they remain generalized. Stronger, context-based recommendations (e.g., VR/AR in heritage tourism, blockchain for cultural IP, targeted workforce training) would enhance policy relevance.（The modified content in the article has been highlighted in yellow.line919-924、line927-930、line939-947、line955-963)

Response :

We greatly appreciate the reviewer's affirmation of the regional heterogeneity analysis and suggestions for deepening the discussion. We have revised Section 6.3 “Practical Implications and Policy Recommendations” in Chapter 6 as follows:

Deepening the Explanation of Incremental Effects in Western Regions (see Section 6.3 of Chapter 6):

Original Text: Only mentioned that western regions may have started later and possess greater development potential.

Revised Content: In the policy recommendations under Section 6.3, “Advancing Regional Coordination Based on Local Conditions,” we provide a more in-depth explanation of why the digital economy in western regions yields the strongest incremental benefits for cultural-tourism integration. We point out that the relatively weak digital infrastructure and applications in the western regions mean that investments in the digital economy can yield higher marginal returns from a “low base” and create opportunities for “leapfrog development.”

Discussion on Regional Policy Capacity Differences (see Section 6.3 of Chapter 6):

Original text before revision: No mention of policy capacity differences.

Revised content: In Section 6.3, we added a discussion on regional policy capacity differences. We recommend that western regions prioritize foundational, inclusive policies for digital economy and cultural-tourism integration, while eastern and central regions should focus on refined, innovation-driven policy support and enhanced cross-departmental coordination to address resource competition and evolving integration models under high NQP conditions. This underscores the need for policy design aligned with each region's specific developmental stage and capabilities.

6.3 Practical Implications and Policy Recommendations

The findings of this study provide targeted and differentiated policy recommendations for Chinese provinces to advance the deep integration of the digital economy and cultural tourism. These insights also offer valuable references for other developing countries in their digital tourism development:

(1) Continuously deepen the development of the digital economy to solidify the foundation for integration. Given the significant overall positive impact of the digital economy on cultural-tourism integration, governments at all levels should continue to increase investment in digital infrastructure development, digital technology R&D and application, and data element market cultivation, providing robust support for the comprehensive digital transformation of the cultural-tourism industry.

(2) Adopt a dual-pronged approach to optimize intermediary transmission mechanisms.Increase investment in new infrastructure to build an “integration highway.” Particular emphasis should be placed on applying new infrastructure such as 5G, big data centers, cloud computing, and artificial intelligence platforms within the cultural and tourism sectors. Through intelligent upgrades, enhance scenic area management efficiency, enrich visitor experiences, and optimize cultural content transmission. Examples include promoting smart scenic areas and developing VR/AR immersive cultural experience projects.Enhance employment quality by strengthening integrated “human capital.” Encourage deep integration between vocational education and lifelong learning systems with digital technologies to cultivate versatile cultural and tourism professionals suited to the digital economy. Support emerging sectors like online tour guiding, digital cultural creativity, and live-streamed cultural tourism marketing. Conduct targeted digital skills training to provide practitioners with more diversified, high-value-added employment opportunities, thereby strengthening their digital competencies and cross-sector integration capabilities.

(3) Adopt a dialectical approach to new-quality productive forces and implement differentiated strategies.For regions with lower levels of new-quality productive forces: Fully leverage the inclusive empowerment of the digital economy through foundational measures like introducing digital platforms and promoting digital marketing to rapidly elevate the digitalization and integration of the cultural and tourism industries, achieving rapid breakthroughs from “nothing to something.” For regions with higher levels of new-quality productive forces: Policy focus should shift from breadth to depth and precision. Avoid spreading digital economy resources thinly across the cultural and tourism sector. Instead, guide deeper integration between cultural and tourism industries and local strategic emerging industries through “hardcore technology.” For instance, promote the integration of digital cultural content production with AI technology, the digital preservation of cultural heritage with blockchain applications, and the design of cultural and creative products with industrial internet platforms to achieve higher levels of innovation-driven convergence. Foster cross-departmental coordination. Recognizing the risk that resources may be “crowded out” by industries with stronger “new quality” attributes, cultural and tourism departments should proactively strengthen communication and collaboration with science and technology, industry, and other sectors. This will secure greater cross-sectoral support within the digital economy, forming a synergistic force for cross-industry integrated development.

(4) Tailor approaches to advance regional coordinated development. Given the regional heterogeneity of digital economy impacts on cultural-tourism integration, provinces should formulate differentiated strategies based on their digital economic foundations, new-quality productive forces levels, and cultural-tourism resource endowments. Western regions should seize the substantial incremental opportunities presented by the digital economy to achieve leapfrog development. Eastern regions should explore high-quality, innovation-driven pathways for deep integration. Central regions must identify and overcome specific bottlenecks in their integration efforts, exploring digital economy empowerment models suited to their circumstances.

(5) Optimize macroeconomic policies to foster a favorable environment. Given the complex and sometimes negative impacts of economic development levels, openness to the outside world, and resident consumption capacity on cultural-tourism integration, policymakers need to conduct more nuanced assessments of how macroeconomic policies specifically affect the cultural-tourism sector. For instance, while pursuing overall economic growth, resources should be directed toward sectors that promote industrial integration. While expanding openness, emphasis should be placed on attracting high-quality foreign investment that enhances local cultural-tourism integration, while strengthening support for domestic cultural-tourism enterprises to compete internationally. While increasing residents' income, consumption upgrades should be guided to cultivate demand for high-quality, deeply integrated cultural-tourism products.

Q2.2.3 Policy Implications: While the manuscript provides broad suggestions (digital infrastructure, employment quality, differentiated strategies), they remain generalized. Stronger, context-based recommendations (e.g., VR/AR in heritage tourism, blockchain for cultural IP, targeted workforce training) would enhance policy relevance.（The modified content in the article has been highlighted in yellow.line919-924、line927-930、line939-947、line955-963)

Response：

We fully accept the reviewers' comments that policy recommendations need to be more specific and actionable. We have revised Section 6.3 “Practical Implications and Policy Recommendations” in Chapter 6 as follows:

Providing more specific, contextualized policy recommendations (see Section 6.3 of Chapter 6):

Original text: Policy recommendations were relatively broad and general.

Revised content: We have substantially revised Section 6.3 to make its policy recommendations more actionable and contextualized:

In the section titled “Increasing Investment in New Infrastructure to Build an Integrated ‘Highway’”, we recommend promoting smart tourist attractions and developing VR/AR immersive cultural experience projects.

In the section titled “Enhancing Employment Quality and Strengthening the Integration of ‘Human Capital’， we recommend supporting new business models such as online tour guides, digital cultural creativity, and live-streamed cultural tourism marketing, while conducting targeted digital skills training.In the section titled “Adopting a Dialectical Approach to New Quality Productivity and Implementing Differentiated Strategies,” we recommend guiding deeper “hardcore technology” integration between cultural tourism and high-tech industries in regions with high NQP levels. Examples include combining digital cultural content production with AI technology, integrating digital heritage preservation with blockchain applications, and coordinating cultural and creative product design with industrial internet platforms.

The newly added fifth point, “Optimizing Macroeconomic Policies to Foster a Favorable Environment,” proposes the following: While pursuing overall economic growth, redirect resources toward sectors that promote industrial convergence; while expanding openness, prioritize attracting high-quality foreign investment that elevates local cultural-tourism integration levels and strengthen support for domestic cultural-tourism enterprises to enhance competitiveness; while increasing residents' income, guide consumption upgrades to cultivate demand for high-quality, deeply integrated cultural-tourism products.

Q3. Conclusions

Q3.3.1 The conclusions align with the empirical results, emphasizing the catalytic role of the digital economy and the mediating importance of infrastructure and human capital. However, the study risks overgeneralization by assuming similar effects across all provinces. In provinces with high NQP, integration may follow very different trajectories. This limitation should be explicitly discussed, as it affects the generalizability of the model beyond China.（The modified content in the article has been highlighted in yellow.line983-988、line997-1001、line1013-1015、line1020-1028)

Response：

We appreciate the reviewers' comments on the conclusion section and their reminder regarding the limitations of the model's universality. We have revised Chapter 7, “Conclusions, Limitations, and Future Research Prospects,” as follows:

Explicitly discuss the limitations of the model's universality (see Sections 7.1 and 7.2 of Chapter 7):

Original text: The conclusion section may not have sufficiently emphasized the limitations of the model's universality in the NQP context.

Revised Content:In Section 7.1 “Conclusions,” we added a sentence emphasizing the “nonlinear” nature of the digital economy's enabling effects revealed by this study. We specifically noted that these impacts may vary across different development stages and industrial structures, aligning with the unique trajectories observed in regions with high NQP.

In Section 7.2 “Limitations,” we introduced a key limitation discussion explicitly stating: "While this study examines the complex relationship between the digital economy and cultural-tourism integration at the provincial level, its findings—particularly the negative moderating effect of new quality productivity—suggest potential limitations to the model's universality across different developmental stages and industrial structures. In provinces with high NQP levels, the development trajectory of cultural-tourism integration may indeed follow a very different logic, driven more by deep innovation and specific technology applications than by the inclusive empowerment of the digital economy. This context-dependence implies that caution is warranted when directly generalizing the specific findings of this model to other countries or regions, especially those with markedly different NQP development levels and industrial structures."

7.1 Conclusions

This study delves into the impact mechanism of the digital economy on the integration of cultural and tourism industries at the provincial level in China. By introducing new infrastructure and employment quality as mediating variables and new-type productive forces as a moderating variable, a moderated mediation model is constructed. Using panel data from China's 31 provinces spanning 2011–2023, empirical analysis is conducted via a two-way fixed effects model and Bootstrap testing, yielding the following key conclusions:

First, the development of the digital economy exerts a significant direct promotional effect on cultural and tourism industry integration, constituting a vital driving force for high-quality industrial development. Second, both new infrastructure and employment quality play significant positive mediating roles in the process where digital economic development promotes cultural and tourism integration. This implies that the digital economy does not merely exert a direct influence on cultural-tourism integration but achieves empowerment through two key pathways: optimizing infrastructure and enhancing human capital quality. Finally, the study reveals that new-type productive forces exert a significant negative moderating effect on the relationship between digital economic development and cultural-tourism integration. This finding underscores that the enabling effects of the digital economy are not linearly increasing. Instead, they may face challenges such as resource dilution, differentiated integration pathways, and adjustments in development priorities across different developmental stages and industrial structures.

The contribution of this study lies not only in confirming the overall positive effect of the digital economy on cultural-tourism integration but, more importantly, in “unlocking the black box of digital economy empowerment.” It reveals the crucial transmission roles of new infrastructure and employment quality while innovatively identifying new-type productive forces as a significant, counterintuitive boundary condition. These findings offer new perspectives for theoretical research and provide crucial empirical evidence for China's provinces to formulate more refined and differentiated policies for cultural-tourism integration.

7.2 Limitations

Despite rigorous methodology and analytical depth, this study has certain limitations that warrant future refinement:

Q3.3.2 Comments on the Quality of English Language: The manuscript is generally well-written and understandable, but the English could be improved to enhance clarity and readability. Several sentences are overly long and complex, which may obscure the main points. A light to moderate language edit focusing on conciseness, grammar, and flow would help ensure that the arguments and findings are communicated more clearly to an international readership.

Response：

We are deeply grateful to the reviewers for their valuable suggestions regarding language quality. We fully agree that clear and concise English expression is crucial for the international readership of SSCI journals.

Revisions (throughout the manuscript): While we cannot directly display the English revisions here, we have meticulously reviewed and polished the English text in all revised sections according to this recommendation. We have paid particular attention to the following aspects:

Sentence conciseness: Breaking down lengthy, complex sentences and employing more direct phrasing.

Grammar and vocabulary: Correcting potential grammatical errors and selecting more precise and professional academic terminology.

Fluency: Adjusting transitions between sentences and paragraphs to ensure logical coherence and smooth readability.

Academic tone: Maintaining a rigorous academic tone and avoiding colloquial expressions.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The authors claim that research is scarce, yet they fail to reference worldwide studies and international reports from UNWTO, OECD, and EU digital economy–tourism reports to establish that their findings extend past China.

The research depends heavily on Chinese studies, although it acknowledges the lack of available data. The study requires additional global case studies from Europe and Southeast Asia to achieve a balanced review.

The study gap section should identify specific mechanisms between infrastructure and employment quality and NQP moderation that previous research has not examined.

The study requires a visual representation of the moderated mediation model through a figure within the theoretical framework section.

The selection of the entropy method needs justification because it was chosen instead of PCA and factor analysis and the research contains specific constraints.

The research needs to explain why NQP at higher levels leads to decreased integration and how this relationship connects to theoretical frameworks.

The recommendations for China are useful but they lack global applicability because they fail to explain how these findings could benefit digital tourism development in other developing nations.

Author Response

Q1. The authors claim that research is scarce, yet they fail to reference worldwide studies and international reports from UNWTO, OECD, and EU digital economy–tourism reports to establish that their findings extend past China.（The modified content in the article has been highlighted in yellow.line43-45、line47-50、line54-58、line60-63、line66-69、line88-91、line95-96、line116-130)

Response：

We are very grateful to the reviewers for pointing out the lack of references to global studies and international reports in the literature review, which indeed affected the international perspective and discussion of universality in the research. In response to this comment, we have made the following revisions to Chapter 1 and Chapter 2:

Introduction of global research and international reports (see Chapter 1 Introduction and Chapter 2 Section 2.1):

Original text: References were primarily focused on Chinese sources and the Chinese context.

Revised content:

In Chapter 1 “Introduction,” we have added citations to international reports such as UNCTAD and Schwab to demonstrate the global significance of the digital economy.

In Section 2.1 “Digital Economy and Cultural Tourism Integration: Existing Research and Limitations,” we have incorporated references to reports from UNWTO, OECD, and the EU on the digital economy and tourism. This establishes a global context while highlighting that these reports, though providing macro trends and policy recommendations, lack in-depth exploration of the mechanisms underlying digital economy-cultural tourism integration within China's specific context (particularly in the NQP scenario). This helps position the contribution and scarcity of this study within a global perspective.

Introduction

The digital economy is profoundly reshaping the global economic landscape with its transformative power, serving as the core engine for China's high-quality development. Concurrently, the deep integration of the cultural and tourism industries (CTI) is recognized as a strategic direction for enhancing industrial resilience, optimizing regional competitiveness, and improving public welfare. This study focuses on the enabling role of the digital economy in CTI across China's 31 provinces and municipalities—a topic of significant theoretical and practical importance. However, despite the profound impact of digitalization, the specific mechanisms through which the digital economy drives the complex systemic transformation of CTI remain unclear. Particularly at the provincial level, challenges in data circulation, industrial coordination, and talent structure may hinder the full realization of digital dividends. Therefore, there is an urgent need for a more in-depth and nuanced analysis of the pathways and contextual conditions through which the digital economy influences CTI.

Existing research acknowledges the positive impact of the digital economy on industrial development, yet significant gaps remain regarding its role in cultural-tourism integration. First, few studies specifically explore the concrete mechanisms through which the digital economy drives this integration, particularly overlooking the transmission roles of new infrastructure and employment quality as key mediating variables. Most existing literature remains at the macro-level correlation stage, failing to fully elucidate specific transmission chains. Second, discussions on “New Quality Productivity” (NQP)—China's recently proposed strategic economic development concept emphasizing innovation-led, high-quality growth—remain largely macro-level. Its role as a moderating variable within specific cultural-tourism integration industries lacks empirical validation. Crucially, academia has yet to fully elucidate NQP's potentially complex and counterintuitive negative moderating effects on the digital economy's promotion of cultural-tourism integration. This constitutes a significant area for advancement in understanding the boundary conditions of digital economy effects and how economic development priorities subtly reshape digital empowerment.

Given these research gaps, this paper aims to bridge these deficiencies. It empirically assesses the impact of digital economic development on provincial-level cultural-tourism integration in China, delves into the mediating roles of new infrastructure and employment quality, and critically examines the moderating effect of new-type productive forces on this relationship. This study not only situates China's experience within a global context but also compares international reports and global cases to enhance the research's universality and the breadth of its policy implications.

The core argument of this study is that the digital economy significantly promotes cultural-tourism integration through key pathways such as new infrastructure development and employment quality enhancement, but this promotional effect is negatively moderated by new-type productive forces. This finding not only deepens our understanding of the complex and nonlinear mechanisms through which the digital economy drives industrial upgrading but also provides refined and differentiated strategic recommendations for Chinese provinces to optimize their cultural-tourism integration pathways at different developmental stages and with varying industrial priorities.

The paper's structure proceeds as follows: Chapter 2 reviews the literature and identifies research gaps; Chapter 3 constructs the theoretical framework and research hypotheses; Chapter 4 details the model design and indicator selection; Chapter 5 presents empirical results; Chapter 6 discusses findings, theoretical contributions, practical implications, and policy recommendations; Chapter 7 summarizes conclusions, limitations, and future research directions.

2.1 Digital Economy and Cultural Tourism Integration: Existing Research and Limitations

Q2.The research depends heavily on Chinese studies, although it acknowledges the lack of available data. The study requires additional global case studies from Europe and Southeast Asia to achieve a balanced review.（The modified content in the article has been highlighted in yellow.line88-91、line95-96、line116-130、line231-243、line246-255、line1053-1057)

Response：

We appreciate the reviewer's suggestion to expand the global case studies to balance the literature review. We agree that incorporating more international perspectives will enhance the breadth and depth of the paper. In response to this comment, we have made the following revisions to Chapter 2 and Chapter 7:

Integrating an international perspective into the literature review (see Sections 2.1 and 2.5 of Chapter 2):

Original text: The literature review is primarily based on Chinese studies.

Revised content: In Section 2.1 “Digital Economy and Cultural Tourism Integration,” we have added references to international literature on the application and efficiency gains of technologies such as digital platforms, big data, and AI in the tourism industry, demonstrating the digital economy's universal enabling role for the cultural tourism sector. In Section 2.5 “Research Prospects and Summary of Academic Gaps,” we emphasized that while international discussions on the digital economy and tourism are widespread, there remains a lack of attention to the complex mechanisms of digital economy-cultural tourism integration within China's specific context (particularly under the National Quality Project framework).

Recommendations for future international comparative studies and case analyses (see Chapter 7, Section 7.3):

Original text: Future research directions did not explicitly mention international comparisons or global case studies.

Revised content: We have added a significant future research direction in Section 7.3, “Future Research Prospects,” explicitly proposing that "the framework of this study can be applied to the cultural tourism industries of other countries or regions for cross-national comparative research. This would test the universality of the conclusions and identify unique patterns under different institutional and developmental contexts. Specifically, representative developing countries and regions such as Europe and Southeast Asia could be selected for in-depth comparative analysis to explore how these findings can inform digital tourism development in these areas," thereby contributing to global digital tourism advancement.

2.5 Research Outlook and Summary of Academic Gaps

7.3 Future Research Prospects

Given the aforementioned limitations, this study suggests the following directions for future academic exploration:

(1) Expanding Mediating and Moderating Mechanisms: Beyond new infrastructure and employment quality, future research may explore other potential mediating pathways, such as innovation ecosystems, evolving government regulatory environments, or shifts in market competition intensity. Moreover, beyond new-quality productivity, the moderating effects of other macro-level factors—such as regional innovation capacity, institutional quality, or the presence of specific industrial clusters—on the enabling effects of the digital economy could be examined.

(2) Micro-level and Case Studies: Future research should aim to conduct more granular empirical analyses using city-level or even enterprise-level data. This would facilitate deeper understanding of the specific behaviors and strategies driving cultural-tourism integration. Furthermore, in-depth qualitative case studies can be conducted in representative provinces or cities with varying levels of NQP development to validate and refine the quantitative findings of this study, particularly regarding the specific patterns of “hard-core technology” integration in the cultural and tourism sectors of high-NQP regions.

(3) Dynamic Effects and Long-Term Impacts: Consider the dynamic relationship between digital economic development and cultural-tourism integration, such as lag effects, threshold effects, or nonlinear relationships. Utilize longer time-series data to explore the long-term impacts and evolving trends of the digital economy on cultural-tourism integration.

(4) Refined NQP Measurement and Impact Decomposition: As understanding of “New Quality Productivity” deepens, future research can develop more granular and decomposed measurement indicators. This will help investigate how different dimensions of NQP (e.g., core technological breakthroughs, concentration of high-end talent, green development, or specialized industrial clusters) differentially moderate the enabling effects of the digital economy on cultural-tourism integration.

(5) International comparative studies: Extend this analytical framework to examine cultural tourism industries in other countries or regions through cross-national comparisons. This will validate the findings' universality and identify unique patterns across diverse institutional and developmental contexts. Particularly, representative developing regions like Europe and Southeast Asia warrant in-depth comparative analysis to explore how these insights can inform digital tourism development in such areas.

Q3.The study gap section should identify specific mechanisms between infrastructure and employment quality and NQP moderation that previous research has not examined.（The modified content in the article has been highlighted in yellow.line231-243、line246-255)

Response：

We greatly appreciate the reviewers' suggestion to more specifically identify unexplored areas regarding intermediary mechanisms and moderating effects in the research gaps section. This overlaps with the comments from Reviewers 1 and 2, and we have made the following key revisions to Section 2.5 of Chapter 2:

More explicitly articulating the methodological gaps (see Section 2.5 of Chapter 2):

Original text: Mentioned the lack of mechanism analysis but was not specific enough.

Revised content: We have clarified the research gaps more explicitly in Section 2.5, “Research Prospects and Summary of Academic Gaps”:

We explicitly point out the lack of “in-depth analysis of micro-level transmission pathways such as new infrastructure and employment quality,” emphasizing that existing research has failed to fully reveal the specific transmission chains of these two mediating mechanisms.

It explicitly states that “the effects of new-type productive forces as a key moderating variable (especially its negative moderating role) have not been theoretically constructed or empirically tested,” highlighting this as a critical gap in understanding the boundary conditions of digital economy effects.

2.5 Research Outlook and Summary of Academic Gaps

Q4．The study requires a visual representation of the moderated mediation model through a figure within the theoretical framework section.（The modified content in the article has been highlighted in yellow.line264-271、line278)

Response：

We fully agree with the reviewers on the importance of a visual theoretical model. This overlaps with Reviewer 1's comment 1.1, and we have implemented the following revisions:

Added a conceptual framework diagram (see after Section 3.1 in Chapter 3):

Original text before revision: Lack of a visual theoretical model presentation.

Revised content: We have added a clear conceptual framework diagram following Section 3.1 “Theoretical Framework Construction.” This diagram visually illustrates all direct, mediating, and moderating relationships among the digital economy, cultural-tourism integration, new infrastructure, employment quality, and new-quality productive forces. It explicitly delineates causal pathways and conceptual boundaries between constructs to enhance the model's clarity and comprehensibility.

3.1 Theoretical Framework Construction

Figure 1 Theoretical Mechanism Roadmap

Q5.The selection of the entropy method needs justification because it was chosen instead of PCA and factor analysis and the research contains specific constraints.（The modified content in the article has been highlighted in yellow.line429-444)

Response：

We appreciate the reviewers' request for a more thorough justification of the entropy method selection. We agree that the rationale for method selection is crucial. This overlaps with Reviewer 1's comment 1.3, and we have made the following revisions to Section 4.1 of Chapter 4 and the newly added Appendix A:

Detailed justification for the entropy method selection (see Section 4.1 of Chapter 4 and the newly added Appendix A):

Original text: Only mentioned the adoption of the entropy method.

Revised content:

In Section 4.1 “Data Sources and Variable Definitions,” we have added explicit justification for selecting the entropy method. We clarify that the entropy method was chosen for its objective weighting property, which determines weights based on the variability (i.e., information content) of indicators, thereby avoiding potential biases from subjective weighting. This approach is particularly suitable when dealing with a large number of indicators and lacking clear theoretical grounds for presetting weights.

We also contrasted the limitations of Principal Component Analysis (PCA) and Factor Analysis: while these methods can also reduce dimensionality, they focus on extracting common factors, potentially making them less intuitive than the entropy method when interpreting the contribution of individual indicators. More importantly, they often implicitly assume linear structural relationships between variables. For multidimensional, complex concepts like “cultural-tourism integration,” the relationships among internal indicators may not be strictly linear. In such cases, the entropy-based method offers greater flexibility in reflecting the relative importance of each indicator.

We will elaborate in greater detail on the calculation steps of the entropy-based method and its advantages in handling multidimensional, complex concepts in the newly added Appendix .

4.1 Data Sources and Definitions

Q6.The research needs to explain why NQP at higher levels leads to decreased integration and how this relationship connects to theoretical frameworks.（The modified content in the article has been highlighted in yellow.line354-357、line360-362、line400-403、line881-909)

Response：

We are deeply grateful to the reviewers for reiterating the importance of providing a thorough explanation of the negative regulatory effect of NQP. This comment aligns closely with the feedback from Reviewers 1 and 2, underscoring that this represents a core innovation of the paper requiring the most rigorous justification. We have implemented the following comprehensive and systematic revisions in Section 3.2.4 of Chapter 3 and Section 6.2 of Chapter 6:

Systematic explanation of the theoretical mechanism underlying the negative regulatory effect of NQP (see Section 3.2.4 of Chapter 3):

Original text: The explanation is relatively straightforward.

Revised content: We have substantially expanded and restructured Section 3.2.4, “Moderation Effect: Boundary Conditions of New Quality Productivity,” providing a comprehensive and interrelated theoretical framework across three dimensions to explain why the digital economy's promotion of cultural-tourism integration weakens at high NQP levels:

Resource dilution or crowding-out effect: We explicitly introduce the Resource-Based View (RBV) [Penrose, 1959; Barney, 1991] to explain how scarce digital economy resources (including policies, funding, and talent) in high-NQP regions are strategically prioritized for high-tech and strategic emerging industries. This creates a “crowding-out” or “dilution” effect on the universal digital empowerment of cultural-tourism integration. We explicitly mention the “crowding-out effect of high-tech industries on tourism” as a concrete manifestation of resource dilution.

Differentiated Integration Pathways or Maturity Effect: Drawing on innovation ecosystem theory [Adner, 2006] and disruptive innovation theory [Christensen, 1997] to explain that in high NQP regions, cultural-tourism integration has entered a more mature and specialized development stage. Its trajectory shifts toward “hardcore tech” integration models deeply intertwined with core high-tech industries (e.g., VR/AR digital museums, blockchain-based cultural IP, AI-powered smart tourism management), diminishing the marginal effects of universal digital empowerment.

Differences in Development Stages and Priorities: This emphasizes how economic development stages determine industrial strategic priorities. In high NQP regions, cultural-tourism integration may serve more as a supplement to economic development rather than a priority area for digital resource allocation. This section indirectly incorporates the “institutional constraints” perspective: in regions with advanced NQP, institutional frameworks may favor technological innovation over the cross-departmental coordination and flexible policies required for cultural-tourism integration, thereby impacting the effective utilization of digital economy resources.

All explanations are systematically linked to corresponding theoretical frameworks.

The novelty of the theoretical contributions is emphasized (see Section 6.2 of Chapter 6):

Original text: The theoretical contribution to the negative regulation of NQP is insufficiently emphasized.

Revised text: In Section 6.2 “Theoretical Contributions,” we specifically highlight how the discovery of the negative regulation effect on NQP “innovatively” contributes to existing theory. It enriches our understanding of the boundary conditions for digital economy-driven effects and offers new perspectives for applying resource dilution theory, innovation ecosystem theory, and development stage theory in the context of the digital economy.

3.2.4 Moderating Effect: Boundary Conditions of New Quality Productivity

6.2 Theoretical Contributions

The findings of this study contribute to existing theory and literature in multiple dimensions:

Q7.The recommendations for China are useful but they lack global applicability because they fail to explain how these findings could benefit digital tourism development in other developing nations.（The modified content in the article has been highlighted in yellow.line919-924、line927-930、line939-946、line955-963、line1053-1057)

Response：

We appreciate the reviewer's suggestion that policy recommendations should be expanded for global applicability. We agree that placing China's experience within a broader international context enhances the study's global impact. In response to this comment, we have made the following revisions to Section 6.3 of Chapter 6 and Section 7.3 of Chapter 7:

Enhancing the Global Applicability of Policy Recommendations (see Section 6.3 of Chapter 6 for details):

Original text: Policy recommendations are primarily targeted at China.

Revised text: In the introduction and conclusion of Section 6.3 “Practical Implications and Policy Recommendations,” we have added discussion emphasizing that the study's findings—particularly the universality of intermediary mechanisms (new infrastructure and employment quality) and the context-dependence of moderating effects (the innovation-driven development phase represented by new-quality productivity)—can provide valuable insights for other developing countries advancing digital tourism. For instance, developing countries in the early stages of digital economic development should prioritize investments in digital infrastructure and talent training. Conversely, nations with established innovation capabilities must guard against resource dilution and pursue more distinctive pathways for deep integration.

6.3 Practical Implications and Policy Recommendations

Future research should explicitly recommend international comparisons (see Section 7.3 of Chapter 7):

Original text: Future research prospects did not explicitly mention international comparisons.

Revised content: We have added a recommendation in Section 7.3 “Future Research Prospects,” suggesting that "the framework of this study could be applied to the cultural tourism industries of other countries or regions for cross-national comparative research. This would test the universality of the conclusions and identify unique patterns under different institutional and developmental contexts. Representative developing countries and regions such as Europe and Southeast Asia could be selected for in-depth comparative analysis to explore how these findings can inform digital tourism development in these areas," thereby contributing to global digital tourism advancement.

7.3 Future Research Directions

Given the aforementioned limitations, this study suggests the following avenues for future academic exploration:

(5) International Comparative Studies: Extend this analytical framework to examine cultural tourism industries in other countries or regions through cross-national comparisons. This will validate the findings' universality and identify unique patterns across diverse institutional and developmental contexts. Particularly, representative developing regions like Europe and Southeast Asia warrant in-depth comparative analysis to explore how these insights can inform digital tourism development in such areas.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Based on my comments, the authors have made excellent revisions and provided impressive responses. However, I noticed that the use of the term "Chapter" in the last paragraph of the introduction section seems inappropriate. Typically, in academic papers, it is more appropriate to use the term "section."

Author Response

Q1: Based on my comments, the authors have made excellent revisions and provided impressive responses. However, I noticed that the use of the term "Chapter" in the last paragraph of the introduction section seems inappropriate. Typically, in academic papers, it is more appropriate to use the term "section."

Response 1: Thank you for your valuable suggestions. We have revised the suggestions .

The English has improved, and I have made progress in handling some complex sentence structures.

According to the comments of reviewers,the whole article has been revised.

Original text：

Revised text:

The paper's structure proceeds as follows: section 2 reviews the literature and identifies research gaps; section 3 constructs the theoretical framework and research hypotheses; section 4 details the model design and indicator selection; section 5 presents empirical results; section 6 discusses findings, theoretical contributions, practical implications, and policy recommendations; section 7 summarizes conclusions, limitations, and future research directions.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The revised manuscript has substantially addressed the key concerns I raised regarding methodological transparency, depth of interpretation, concreteness of policy implications, and overgeneralization in the conclusions.

Most improved areas: variable operationalization and index construction, theoretical explanation of NQP’s negative moderating effect, and concrete policy recommendations.
Partially improved areas: deeper discussion of regional policy capacity, clearer substantive interpretation of effect sizes.

Overall, this is now a significantly improved manuscript that can be accepted for publication without further revisions.

Comments on the Quality of English Language

The English writing in the manuscript is generally clear and understandable. However, many sentences are long and complex, which sometimes reduces readability. A professional language edit focusing on sentence conciseness, grammar, and flow would improve clarity and make the arguments more accessible to an international audience.

Author Response

The English has improved, and I have made progress in handling some complex sentence structures. According to the comments of reviewers,the whole article has been revised.

Q1.1: Most improved areas: variable operationalization and index construction, theoretical explanation of NQP’s negative moderating effect, and concrete policy recommendations.

Response：（The modified content in the article has been highlighted in yellow.Appendix has been added)

We are deeply grateful for your acknowledgment of these critical revisions. Your initial feedback directly guided the focus of our modifications, which we have thoroughly and systematically refined.

Revision Logic: We recognize that clear, transparent, and scientific measurement methods form the cornerstone of all empirical research. The reviewers' comments hit the nail on the head. To this end, we have abandoned any previous reliance on brief descriptions and instead adopted a multidimensional composite index approach. For each core construct, we have established a systematic integrated evaluation indicator system. All indicators were selected based on theoretical relevance, data availability, and comparability principles. Objective weighting was applied using the entropy method to ensure the scientific rigor, precision, and reproducibility of the research.

Specific modifications:

Operational Definition:

（1）Cultural-Tourism Integration ：

This study operationalizes “cultural and tourism industry integration” as the comprehensive level of mutual penetration, restructuring, and coordinated development across multiple dimensions—including resources, factors, markets, and technology—between a region's cultural and tourism industries.

Index Construction (corresponding to Appendix A, Table 1)：We constructed a comprehensive evaluation system comprising 3 primary dimensions, 9 secondary dimensions, and a total of 29 tertiary indicators.

（2）Digital Economy：

This study operationalizes the “digital economy” as a series of economic activities characterized by digital knowledge and information as key production factors, modern information networks as vital carriers, and the effective use of information and communication technologies as a major driver for enhancing efficiency and optimizing economic structures.

Index Construction (corresponding to Appendix A, Table 5 and other relevant tables): We constructed a comprehensive evaluation system comprising four primary dimensions and over 20 tertiary indicators.

（3）New Quality Productivity, NQP：

Operational Definition: This study innovatively operationalizes “new-quality productive forces” as an advanced productive force state generated by revolutionary technological breakthroughs, innovative allocation of production factors, and deep industrial transformation and upgrading. It is characterized by high technology, high efficiency, and high quality.

Index Construction (corresponding to Appendix A, Table 3): We constructed a comprehensive evaluation system comprising 3 primary dimensions, 7 secondary dimensions, and a total of 20 tertiary indicators.

（4）Employment Quality

Operational Definition: This study operationalizes “employment quality” as a comprehensive concept encompassing multiple dimensions including employment environment, compensation and benefits, employability, and employment protection.

Index Construction (corresponding to Appendix A, Table 2): We constructed a comprehensive evaluation system comprising 4 primary dimensions, 10 secondary dimensions, and a total of 20 tertiary indicators.

The specific details of this revision have been incorporated into （Appendix A）, which provides detailed information on the specific acquisition methods, calculation methods, and indicator names derived from the indicator system calculated using the entropy weight method.

Appendix A

Table 1: Comprehensive Evaluation Indicator System for Cultural-Tourism Integration

Primary Dimension

Secondary Dimension

Tertiary Indicator

Operationalization / Measurement

Polarity

Level of Integrated Cultural-Tourism Development

Resource Endowment & Infrastructure

Number of 4A-Grade Tourist Attractions

Raw data

Number of Museum Institutions

Raw data

Number of Public Library Institutions

Raw data

Number of Performing Arts Troupes

Raw data

Number of Performing Arts Venues

Raw data

Number of Mass Cultural Centers

Raw data

Number of Cultural Relics in Collection

Raw data

Employment Share in Culture, Sports & Entertainment

Urban unit employees in Culture, Sports & Entertainment / Total urban unit employees

Employment Share in Accommodation & Catering

Urban unit employees in Accommodation & Catering / Total urban unit employees

Transportation Accessibility

Per capita urban road area

Potential Consumer Capacity

Per capita household consumption expenditure

Regional Environmental Quality

Greenery coverage rate in built-up areas

Input & Support

Share of Cultural & Recreational Expenditure

Per capita cultural & recreational expenditure / Per capita total consumption expenditure

Government Appropriation for Culture & Tourism

Raw data

Per Capita Public Library Collection

Raw data

Development Level of the Tertiary Sector

Value-added of the tertiary sector / Regional GDP

Talent Cultivation

Number of tertiary education students per 100,000 population

Internet Broadband Penetration Rate

Number of broadband subscribers / Permanent resident population

Output & Performance

Number of Star-Rated Hotels

Raw data

Number of Travel Agencies

Raw data

Public Library Visitors

Raw data

Museum Visitors

Raw data

Number of Performances by Arts Troupes

Raw data

Audience Attendance for Performing Arts Venues

Raw data

Passenger Traffic Volume

Raw data

Value-Added of Accommodation & Catering Sector

Raw data

Per Capita Govt. Spending on Culture, Sports & Media

Local gov. expenditure on Culture, Sports & Media / Year-end resident population

Table 2: Comprehensive Evaluation Indicator System for Employment Quality

Primary Dimension

Secondary Dimension

Tertiary Indicator

Operationalization / Measurement

Polarity

Employment Quality

Employment Environment

Economic Development Level

Per Capita Gross Regional Product

Per Capita Number of Vocational Training Institutions

Number of Private Vocational Training Institutions / Total Resident Population

Employment Share of the Tertiary Sector

Number of Employees in the Tertiary Sector / Total Number of Employees

Regional Employment Level

Urban Unit Employees / (Urban Unit Employees + Registered Unemployed Persons in Urban Areas)

Regional Unemployment Level

Urban Registered Unemployment Rate

Employment Compensation

Average Wage of Urban Unit Employees

Raw data

Average Wage in Manufacturing Sector

Average Wage of Urban Unit Employees in Manufacturing

Average Wage in Construction Sector

Average Wage of Urban Unit Employees in Construction

Health Insurance Coverage

Number of Urban Employee Basic Medical Insurance Participants / Total Resident Population

Pension Insurance Coverage

Number of Urban Employee Basic Pension Insurance Participants / Total Resident Population

Urban-Rural Income Disparity

Per Capita Disposable Income of Urban Households / Per Capita Disposable Income of Rural Households

Employability

Share of Employees with Junior College Education or Above

Proportion of Employees with Associate Degree, Bachelor's Degree, or Postgraduate Degree and Above

Education Expenditure

Total Education Expenditure / Gross Regional Product

Number of Higher Education Institutions

Raw data

Employment Protection

Labor Union Mediation Efficiency

Number of Labor Dispute Cases Successfully Mediated by Labor Unions / Number of Labor Dispute Cases Accepted by Labor Unions

Labor Dispute Settlement Rate

Number of Arbitrated Labor Dispute Cases Settled / Number of Arbitrated Labor Dispute Cases Accepted

Labor Supply-Demand Ratio

Number of Registered Job Vacancies / Number of Registered Job Seekers

Table 3: Comprehensive Evaluation Indicator System for New Quality Productivity

Primary Dimension

Secondary Dimension

Tertiary Indicator

Operationalization / Measurement

Polarity

Emerging Quality Labor

Input of Emerging Quality Human Capital

Full-time Equivalent of R&D Personnel

Raw data

Employment Share in Information & Software Industry

Urban Unit Employees in Information Transmission, Software & IT Services / Total Urban Unit Employees

Education Expenditure Intensity

Total Education Expenditure / Gross Regional Product

Output of Emerging Quality Human Capital

College Students per 100,000 Population

Raw data

Number of Higher Education Institutions

Raw data

Average Wage Level of Urban Employees

Average Wage of Urban Unit Employees

Emerging Quality Objects of Labor

Informatization Level

Per Capita E-commerce Sales

E-commerce Sales / Resident Population

Per Capita Telecom Business Volume

Total Telecom Business Volume / Resident Population

Digitalization Level

Number of Internet Broadband Access Ports

Raw data

Number of Domain Names

Raw data

Ecological Environment

Sulfur Dioxide (SO₂) Emissions

Raw data

Waste Treatment Level

Domestic Waste Harmless Treatment Rate

General Industrial Solid Waste Generation

Raw data

Share of Gov. Environmental Protection Expenditure

Local Gov. Environmental Protection Expenditure / Local General Public Budget Expenditure

Emerging Quality Means of Labor

Technology R&D and Innovation

Operating Revenue of High-Tech Industries

Raw data

R&D Expenditure Intensity

R&D Expenditure / Gross Regional Product

Number of Domestic Patent Applications Accepted

Raw data

Share of Gov. Science & Technology Expenditure

Government Expenditure on Science & Technology / General Public Budget Expenditure

Infrastructure Construction

Railway Operating Mileage

Raw data

Mobile Phone Penetration Rate

Raw data

Table 4: Comprehensive Evaluation Indicator System for New Infrastructure
Primary Dimension	Secondary Dimension	Tertiary Indicator	Polarity
New Infrastructure	Information Infrastructure	Mobile Phone Penetration Rate	+
		Length of Long-distance Optical Cable Lines	+
		Number of Mobile Internet Users	+
		Capacity of Local Telephone Exchanges	+
		Capacity of Mobile Telephone Exchanges	+
		Length of Optical Cable Lines	+
		Number of Domain Names	+
		Number of Web Pages	+
		Number of Legal Entity Units in Information Transmission, Software & IT Services	+
		Number of Urban Unit Employees in Information Transmission, Software & IT Services	+
		Number of Agricultural Meteorological Observation Stations	+
		Number of Automatic Weather Stations	+
		Number of Digital TV Users	+
		Number of Cable Radio & TV Users	+
		Number of Public Buses in Operation	+
		Length of Rural Delivery Routes	+
		Length of Urban Delivery Routes	+
		Railway Operating Mileage	+
		Mileage of High-grade Highways	+
		Number of Computers in Use (Period-end)	+
		Per Capita E-commerce Sales	+
		Number of Postal Service Outlets	+
	Innovation Infrastructure	R&D Expenditure Intensity	+
		Full-time Equivalent of R&D Personnel	+
		Intramural Expenditure on R&D	+
		Number of Domestic Patent Applications Accepted	+
		Number of Domestic Invention Patent Applications Accepted	+
		Intramural Expenditure on Basic Research	+
		Intramural Expenditure on Applied Research	+
		Intramural Expenditure on Experimental Development	+

Table 5: Comprehensive Evaluation Indicator System for the Digital Economy
Primary Dimension	Secondary Dimension	Tertiary Indicator	Operationalization / Measurement	Polarity
Digital Economy	Digital Infrastructure	Internet Broadband Access Port Density	Number of Internet Broadband Access Ports / Resident Population	+
		Internet Broadband Penetration Rate	Number of Internet Broadband Subscribers / Resident Population	+
		Mobile Telecommunication Infrastructure Scale	Capacity of Mobile Telephone Exchanges	+
		Length of Long-distance Optical Cable Lines	Raw data	+
		Number of Web Pages	Raw data	+
		Number of Domain Names	Raw data	+
	Digital Industrialization	Per Capita Telecom Business Volume	Total Telecom Business Volume / Resident Population	+
		Mobile Phone Penetration Rate	Raw data	+
		Number of Legal Entity Units in Information Transmission, Software & IT Services	Raw data	+
		Employment Share in Information & Software Industry	Urban Unit Employees in Info Transmission, Software & IT Services / Total Urban Unit Employees	+
		Number of Domestic Patents Granted	Raw data	+
		Number of Domestic Patent Applications Accepted	Raw data	+
	Industrial Digitalization	Peking University Digital Financial Inclusion Index	Raw data	+
		Proportion of Enterprises with E-commerce Transactions	Raw data	+
		E-commerce Sales	Raw data	+
		Number of Websites per 100 Enterprises	Raw data	+
		Value-added of Secondary & Tertiary Industries	Value-added of the Secondary Sector + Value-added of the Tertiary Sector	+
		Sci-tech Innovation Input	R&D Expenditure of Industrial Enterprises above Designated Size	+
		Express Delivery Volume	Raw data	+

Q1.2: Theoretical Explanation of NQP's Negative Moderating Effect

Response：

Modified Logic: We agree that a counterintuitive finding must be underpinned by a robust, multidimensional theoretical framework rather than ad hoc explanations. We have constructed a self-consistent logical chain across three levels: micro-level factor allocation, meso-level industrial evolution, and macro-level development strategy.

Original text：

One of the core findings of this study is that New Quality Productivity (NQP) exerts a significant negative moderating effect on the relationship between the digital economy and the integration of cultural and tourism industries. This implies that as a province's NQP level increases, the promotional role of the digital economy in cultural-tourism integration will relatively diminish[46]. This empirical result may seem counterintuitive, yet it embodies profound theoretical logic and practical considerations, challenging simplistic linear interpretations of digital empowerment. Its underlying mechanisms can be explained through the following aspects:

First, the resource dilution or crowding-out effect. Provinces with higher NQP levels typically rely heavily on cutting-edge technological innovation and strategic emerging industries for economic development. From the Resource-Based View (RBV) perspective [Penrose, 1959; Barney, 1991], these regions possess valuable and often scarce digital economy resources, including policy support, fiscal investment, high-end technical talent, and venture capital[47]. These resources are more likely to be prioritized for strategic emerging industries perceived as having greater future potential and “new-quality” attributes, such as AI chip R&D, biopharmaceuticals, quantum computing, high-end equipment manufacturing, or new materials. These industries often feature higher technological barriers, longer R&D cycles, stronger potential marginal returns, and greater international competitiveness, making them more attractive to high-quality resources within the digital economy. This implies that even provinces with large overall digital economies may allocate relatively less marginal investment and attention to cultural-tourism integration. Under this “lighthouse effect” of resource allocation, cultural-tourism integration may experience some ‘dilution’ or “crowding out” in benefiting from digital economy dividends, thereby weakening the digital economy's promotional role in this sector.

Specific Revisions:（The modified content in the article has been highlighted in yellow.line352-358、line366-369、line380-382)

In Section 3.2.4, we systematically restructured the previously fragmented explanatory mechanisms into three theoretical frameworks:

Resource Dilution and Competitive Crowding-Out Effect:

Employing the resource-based view, we explain how strategic emerging industries “siphon off” high-level production factors (capital, talent, policies) in high NQP regions, thereby intensifying resource constraints on the cultural tourism sector.

Deviation from Integration Pathways and Industry Maturity Effects: By introducing industry lifecycle theory, we demonstrate that cultural-tourism integration in high NQP regions has evolved beyond the initial stage requiring “universal empowerment” (e.g., platform building, livestreaming) into an advanced phase demanding deep integration with “hardcore technologies” (e.g., AI, blockchain, VR/AR). This transition diminishes the marginal returns of foundational digital economies.

Development Priorities and Dynamic Comparative Advantage Reconstruction: From a development economics perspective, this section explains how regional development strategies are shifting focus from “pursuing scale in cultural-tourism integration” to “cultivating competitiveness in cutting-edge technology industries,” thereby altering the priority of resource allocation within the digital economy.

Revised text：

This study reveals a core finding: New Quality Productivity (NQP) exerts a significant negative moderating effect on the integration between the digital economy and the cultural tourism industry. This discovery challenges the conventional understanding of linear growth in digital empowerment effects, revealing the complexity and conditionality of its operational mechanisms. To further elucidate this phenomenon, this study constructs a theoretical framework incorporating three major mechanisms from an integrated perspective of the Resource-Based View, Industrial Evolution Theory, and Development Economics.

One of the core findings of this study is that New Quality Productivity (NQP) exerts a significant negative moderating effect on the relationship between the digital economy and the integration of cultural and tourism industries. This implies that as a province's NQP level increases, the promotional role of the digital economy in cultural-tourism integration will relatively diminish[46]. This empirical result may seem counterintuitive, yet it embodies profound theoretical logic and practical considerations, challenging simplistic linear interpretations of digital empowerment. Its underlying mechanisms can be explained through the following aspects:

First, resource dilution and competitive crowding-out effects form the core micro-level mechanism. Based on the resource-based view, regions with high NQP serve as “innovation poles” within regional economies, deeply locking their development strategies into knowledge-intensive frontier industries such as artificial intelligence, biopharmaceuticals, and new energy. From the Resource-Based View (RBV) perspective [Penrose, 1959; Barney, 1991], these regions possess valuable and often scarce digital economy resources, including policy support, fiscal investment, high-end technical talent, and venture capital[47]. These resources are more likely to be prioritized for strategic emerging industries perceived as having greater future potential and “new-quality” attributes, such as AI chip R&D, biopharmaceuticals, quantum computing, high-end equipment manufacturing, or new materials. These industries often feature higher technological barriers, longer R&D cycles, stronger potential marginal returns, and greater international competitiveness, making them more attractive to high-quality resources within the digital economy. This implies that even provinces with large overall digital economies may allocate relatively less marginal investment and attention to cultural-tourism integration. Under this “lighthouse effect” of resource allocation, cultural-tourism integration may experience some ‘dilution’ or “crowding out” in benefiting from digital economy dividends, thereby weakening the digital economy's promotional role in this sector. Consequently, the overall development of the digital economy (X) has structurally constrained its promotional effect on cultural-tourism integration (Y) in the competition for resources.

Second, deviations in convergence pathways and industry maturity effects provide explanations at the meso-industry level. According to industry evolution theory, digital transformation follows a progression from “informatization” to ‘digitalization’ and ultimately to “intelligentization.” Primary integration heavily relies on the enabling power of digital inclusivity, characterized by strong technological universality, relatively low barriers to entry, and pronounced marginal improvement effects. Consequently, foundational investments in the digital economy (such as broadband networks and online platforms) can significantly enhance integration. However, this study finds that in regions with high NQP, the “basic demand” for cultural-tourism integration has largely reached saturation. The bottleneck for further advancement is no longer the “availability of digital technology,” but rather the ability to achieve deep coupling and innovative applications with cutting-edge technologies (AI, VR/AR, Blockchain, IoT). The dominant logic of integration has shifted from “technology application” to “technological innovation.” At this stage, the key variable measuring integration effectiveness is no longer the province's overall digital economy scale, but rather the collaborative innovation capacity between cultural and tourism departments and science and technology departments. Consequently, the explanatory power of the digital economy level (X), representing the foundational technology infrastructure, naturally diminishes. Its relationship with cultural-tourism integration (Y) is mediated by a more complex innovation ecosystem.

Finally, the reconstruction of development priorities and dynamic comparative advantages reveals the driving forces at the macro-strategic level. Drawing on the “leading industry selection” theory from development economics, economies at different stages of development have their optimal industrial sequences. For regions with low NQP, the cultural and tourism industry is often regarded as a pillar industry and a shortcut to catching up. Therefore, empowering the integration of culture and tourism through the digital economy is a core strategy, where resource allocation is concentrated and marginal effects are exceptionally significant. For regions with high NQP, the primary focus of economic development and policy attention has fully shifted toward cultivating the next “Tesla” or “Huawei,” dedicated to building new comparative advantages centered on technology and knowledge. Against this backdrop, the role of the cultural and tourism industry is more that of a “supporting and service” sector aimed at enhancing regional quality of life and shaping cultural soft power. In provincial-level resource allocation decisions, cultural-tourism integration projects face diminished strategic priority and resource access capabilities when competing against initiatives like quantum computing and large-model training. Consequently, the intensity of digital economy resource allocation to this sector declines, resulting in less unimpeded promotion pathways compared to low-NQP regions.

Q1.3: Concrete Policy Recommendations

Revision Logic: Policy recommendations must be grounded in empirical findings and exhibit high levels of practicality and specificity, avoiding vague statements such as “increase investment” or “improve mechanisms.”

Specific Revisions: （The modified content in the article has been highlighted in yellow.line926-929、line934-938、line969-979)

We have rewritten Section 6.3, “Practical Implications and Policy Recommendations,” to align directly with the preceding empirical and institutional conclusions:

Original text：

6.3 Practical Implications and Policy Recommendations

(1) Continuously deepen the development of the digital economy to solidify the foundation for integration. Given the significant overall positive impact of the digital economy on cultural-tourism integration, govern-ments at all levels should continue to increase investment in digital infrastructure development, digital technol-ogy R&D and application, and data element market cultivation, providing robust support for the comprehen-sive digital transformation of the cultural-tourism industry.

(2) Adopt a dual-pronged approach to optimize intermediary transmission mechanisms.Increase investment in new infrastructure to build an “integration highway.” Particular emphasis should be placed on applying new infrastructure such as 5G, big data centers, cloud computing, and artificial intelligence platforms within the cultural and tourism sectors. Through intelligent upgrades, enhance scenic area management efficiency, enrich visitor experiences, and optimize cultural content transmission. Examples include promoting smart scenic areas and developing VR/AR immersive cultural experience projects.Enhance employment quality by strengthening integrated “human capital.” Encourage deep integration between vocational education and lifelong learning systems with digital technologies to cultivate versatile cultural and tourism professionals suited to the digital economy. Support emerging sectors like online tour guiding, digital cultural creativity, and live-streamed cul-tural tourism marketing. Conduct targeted digital skills training to provide practitioners with more diversified, high-value-added employment opportunities, thereby strengthening their digital competencies and cross-sector integration capabilities.

(3) Adopt a dialectical approach to new-quality productive forces and implement differentiated strategies.For regions with lower levels of new-quality productive forces: Fully leverage the inclusive empowerment of the digital economy through foundational measures like introducing digital platforms and promoting digital mar-keting to rapidly elevate the digitalization and integration of the cultural and tourism industries, achieving rapid breakthroughs from “nothing to something.” For regions with higher levels of new-quality productive forces: Policy focus should shift from breadth to depth and precision. Avoid spreading digital economy resources thinly across the cultural and tourism sector. Instead, guide deeper integration between cultural and tourism industries and local strategic emerging industries through “hardcore technology.” For instance, promote the integration of digital cultural content production with AI technology, the digital preservation of cultural heritage with blockchain applications, and the design of cultural and creative products with industrial internet platforms to achieve higher levels of innovation-driven convergence. Foster cross-departmental coordination. Recogniz-ing the risk that resources may be “crowded out” by industries with stronger “new quality” attributes, cultural and tourism departments should proactively strengthen communication and collaboration with science and technology, industry, and other sectors. This will secure greater cross-sectoral support within the digital economy, forming a synergistic force for cross-industry integrated development.

(4) Tailor approaches to advance regional coordinated development. Given the regional heterogeneity of digital economy impacts on cultural-tourism integration, provinces should formulate differentiated strategies based on their digital economic foundations, new-quality productive forces levels, and cultural-tourism resource en-dowments. Western regions should seize the substantial incremental opportunities presented by the digital economy to achieve leapfrog development. Eastern regions should explore high-quality, innovation-driven pathways for deep integration. Central regions must identify and overcome specific bottlenecks in their integra-tion efforts, exploring digital economy empowerment models suited to their circumstances.

(5) Optimize macroeconomic policies to foster a favorable environment. Given the complex and sometimes negative impacts of economic development levels, openness to the outside world, and resident consumption capacity on cultural-tourism integration, policymakers need to conduct more nuanced assessments of how macroeconomic policies specifically affect the cultural-tourism sector. For instance, while pursuing overall economic growth, resources should be directed toward sectors that promote industrial integration. While ex-panding openness, emphasis should be placed on attracting high-quality foreign investment that enhances local cultural-tourism integration, while strengthening support for domestic cultural-tourism enterprises to compete internationally. While increasing residents' income, consumption upgrades should be guided to cultivate de-mand for high-quality, deeply integrated cultural-tourism products.

Revised text：

（1）To leverage the intermediary role of “digital infrastructure” and “employment quality,” specific measures have been proposed: “strengthening the integration ‘highway’” and “cultivating the integration ‘human capacity’” (such as building smart tourist attractions and nurturing digital cultural tourism creative professionals). Continuously deepen the development of the digital economy to solidify the foundation for integration. Given the significant overall positive impact of the digital economy on cultural-tourism integration, govern-ments at all levels should continue to increase investment in digital infrastructure development, digital technol-ogy R&D and application, and data element market cultivation, providing robust support for the comprehen-sive digital transformation of the cultural-tourism industry.

（2）Focusing on the “regulatory effect of new-quality productive forces,” a revolutionary differentiated strategy is proposed: For regions with low NQP, implement “digital economy empowerment initiatives” (e.g., digital marketing training); For regions with high NQP, advocate for “targeted investment and integration with cutting-edge technologies” (e.g., promoting the convergence of cultural tourism with artificial intelligence and industrial internet platforms). Adopt a dual-pronged approach to optimize intermediary transmission mechanisms.Increase investment in new infrastructure to build an “integration highway.” Particular emphasis should be placed on applying new infrastructure such as 5G, big data centers, cloud computing, and artificial intelligence platforms within the cultural and tourism sectors. Through intelligent upgrades, enhance scenic area management efficiency, enrich visitor experiences, and optimize cultural content transmission. Examples include promoting smart scenic areas and developing VR/AR immersive cultural experience projects.Enhance employment quality by strengthening integrated “human capital.” Encourage deep integration between vocational education and lifelong learning systems with digital technologies to cultivate versatile cultural and tourism professionals suited to the digital economy. Support emerging sectors like online tour guiding, digital cultural creativity, and live-streamed cul-tural tourism marketing. Conduct targeted digital skills training to provide practitioners with more diversified, high-value-added employment opportunities, thereby strengthening their digital competencies and cross-sector integration capabilities.

（4）Based on the discovery of “regional heterogeneity,” distinct development strategies have been formulated for the eastern, central, and western regions. For instance, the western region pursues “incremental leapfrog development,” while the eastern region explores “innovation-driven growth.”

Tailor approaches to advance regional coordinated development. Given the regional heterogeneity of digital economy impacts on cultural-tourism integration, provinces should formulate differentiated strategies based on their digital economic foundations, new-quality productive forces levels, and cultural-tourism resource en-dowments. Western regions should seize the substantial incremental opportunities presented by the digital economy to achieve leapfrog development. And They should effectively utilize central government fiscal transfers and counterpart assistance from eastern regions. Eastern regions should explore high-quality, innovation-driven pathways for deep integration, Emphasize that its policy focus should be on establishing market-oriented mechanisms, encouraging innovative experimentation, and fostering an environment that tolerates failure—all of which depend on its own efficient, flexible governance system and robust policy design capabilities. Central regions must identify and overcome specific bottlenecks in their integra-tion efforts, exploring digital economy empowerment models suited to their circumstances.

Q2：Partially improved areas: deeper discussion of regional policy capacity, clearer substantive interpretation of effect sizes.

Response: We sincerely appreciate your two insightful comments. We agree that these are key to enhancing the study's practical relevance and scientific rigor. We have specifically strengthened these aspects in the revised manuscript.

About Deeper Discussion of Regional Policy Capacity：Section 6.3(Based on the discovery of “regional heterogeneity,”）

Based on the discovery of “regional heterogeneity,” distinct development strategies have been formulated for the eastern, central, and western regions. For instance, the western region pursues “incremental leapfrog development,” while the eastern region explores “innovation-driven growth.”

（2）Clearer Substantive Interpretation of Effect Sizes：

Original text：

As illustrated in Table 6, the coefficient for the primary explanatory variable, the digital economy, is 7.713785, which signifies a notably positive correlation at a 1% significance level. Similarly, the coefficient for the moderating variable NQP is 12.78158, demonstrating a significant positive correlation at the 1% level. The coefficient associated with the core interaction term Mix (DigitalEconomy * NQP) is -2.477726, which reflects a significant negative relationship at the 5% statistical level (P=0.016). This notable negative coefficient suggests that the influence of new quality productivity adversely affects the relationship between the digital economy and the integrated development of the cultural and tourism sectors. Specifically, it implies that as the level of new quality productivity in a province or city increases, the digital economy's capacity to drive the integration of these industries diminishes. This finding supports hypothesis H4 of this research. The integration of the cultural and tourism industry, influenced by new quality productivity within provinces and cities, may have reached an advanced stage, whereby their collaborative development no longer depends on the digital economy as a primary means of production for fostering inclusive integration of the cultural and tourism sectors. Instead, there is a shift toward integration with leading high-tech industries, aiming for a path characterized by refinement, specialization, and even "hardcore technology" integration. This includes initiatives such as utilizing VR/AR technology to enhance experiences in digital museums, adopting blockchain for securing transactions and tracking cultural copyrights, and applying data mining and intelligent systems for effective management and personalized services at tourist sites, among other strategies. At this point, the incremental benefits of the digital economy's facilitative role appear to be constrained. The elements that foster integration and growth encompass enhanced innovation-driven capabilities, more intricate collaboration within innovation ecosystems, and a more focused vertical integration of advanced technologies, rather than merely amplifying the scale of digital economic growth. The phase of economic advancement influences the corresponding phase of industrial evolution. In regions lacking new productive forces, the cultural and tourism sector remains in the initial phases of growth and transformation. Investments in the digital economy that transition from “nothing to something” or “something to more” can serve as a “catalyst,” with their marginal utility being significantly pronounced. In areas where new-quality productive forces have been established, strategic emerging industries prevail in the economic development arena due to their hierarchical benefits, substantial potential, and robust international competitiveness. When viewed from a holistic economic resource distribution perspective, the integration of the cultural and tourism sector may transform into an auxiliary or expanded facet of economic growth, rather than a focal point for high-density allocation of digital economy resources. These varying developmental phases result in a reduced marginal impact of the digital economy on enhancing cultural and tourism integration. In regions striving for advanced development and increased competitive edges, the incremental advantages of the digital economy in advancing cultural and tourism integration will likely wane. Beyond a certain threshold of new-quality productive forces, the digital economy might even present adverse effects (although this may not be evident within the current dataset), leading to diverse policy interpretations among provinces at different levels of new-quality productive forces. other cities.

Revised text：

Author Response File: Author Response.pdf