The concept of the digital countryside was first introduced in the Strategic Plan for Rural Revitalization (2018–2022). As a critical component of China’s national rural revitalization strategy, DCC aims to modernize agriculture and rural areas through the application of advanced information technologies, thereby facilitating integrated urban–rural development (Li et al., 2025). In recent years, a growing body of scholarly research has explored the connotations and extensions of DCC from manifold perspectives.

From an agricultural perspective, existing studies predominantly concentrate on themes including high-quality agricultural development, green transformation, and rural common prosperity. Wen (2025) posited that DCC served as a pivotal strategy to foster the high-quality development of the rural economy and to facilitate the deep integration of rural industries. Empirical analysis conducted by Yang et al. (2025) and colleagues demonstrated that DCC significantly fostered green agricultural development by reducing energy consumption, diminishing pollution emissions, and enhancing agricultural productivity. Similarly, Wang (2025) asserted that DCC was an essential strategy for achieving common prosperity in rural areas. Empowered by information technology, DCC is capable of optimizing agricultural production models, elevating farmers’ incomes, and narrowing the urban–rural development gap.

From a broader perspective, scholars have examined the impact of DCC on urban–rural integration and county-level economic development. Shen and Zheng (2024) found that DCC significantly promoted high-quality urban–rural integration, with market-oriented factor allocation (MFA) serving as a key moderating factor. Sun et al. (2025) concluded that within the expansive framework of “digital China,” DCC had altered the bias of technological progress in county economies—shifting toward capital-intensive development with an increasing degree of capital bias.

As an integral segment of the contemporary service economy, the sports industry possess substantial significance in fostering economic growth, enhancing public health, and enriching social and cultural life (Abrahamyan, 2023). In recent years, with the implementation of national policies supporting the sports industry, academic research has increasingly concentrated on its development, yielding a wealth of theoretical and empirical findings.

At the theoretical level, studies have explored foundational frameworks, functional mechanisms, and pathways for optimizing the development of the sports industry. Kang et al. (2024) emphasized that institutional infrastructure constituted the foundational framework for the effective functioning of the sports industry, arguing for the importance of top-level design in establishing a mutually reinforcing system. Zhang and Wang (2021) identified factor supply and market demand as the dual endogenous driving forces essential for the high-quality development of the sports industry. Xu et al. (2019) and colleagues believed that the essence of high-quality development of the sports industry lay in the expansion of the sports program sector, innovation in content, and the breaking of traditional development constraints.

At the empirical level, scholars have examined relevant themes such as industrial synergy and structural transformation. As the sports industry evolves toward greater integration and intelligence, new patterns have emerged. For example, Li et al. (2023) discovered that the integration of the digital economy and the sports industry demonstrated a strong and growing degree of coupling coordination, evolving from fragile to robust levels. Zheng et al. (2023) highlighted the challenges facing the development of AI-empowered sports, including the digital DCCide, limited mastery of core technologies, and insufficient high-level talent.

As a vital component of the rural revitalization strategy, DCC utilizes information technology to stimulate rural development by enhancing digital infrastructure and facilitating the digital transformation of agriculture. In this context, the sports industry contributes to upgrading rural industrial structures by fostering rural outdoor sports, folk sports events, and recreational programs, thereby transforming ecological resources into distinctive local industries.

On one hand, research on the integration of DCC with the sports sector remains limited. Liang (2024) demonstrated that DCC significantly promoted the development of rural sports tourism by analyzing its underlying mechanisms, with seven key mechanisms identified, including the construction of informatization infrastructure and the enhancement of digital services. Similarly, Gao et al. (2024) and colleagues posited that the theory of holistic governance accurately aligned with the value logic of providing public services for national fitness in rural areas.

On the other hand, in the realm of rural revitalization and the integration of the sports industry, researchers have uncovered a variety of valuable insights. Lu et al. (2024) and co-authors proposed that to address the current challenges faced by the rural sports industry, emphasis should be placed on ecological transformation, innovation in resource structures, and enhancing resilience for high-quality development. Wang (2025) and colleagues discovered a significant positive spatial correlation between the coupling coordination level of the sports industry and rural revitalization, exhibiting clear spatial clustering characteristics.

Nevertheless, a significant academic gap persists regarding the intersection of DCC and sports integration. The present study aims to explore the mechanisms through which DCC influences the development of the sports industry, which would offer meaningful scholarly value.

Collectively, existing research primarily investigated the relationship between digital technology and industrial development from two key perspectives: Firstly, studies on DCC have employed quantitative methods to verify its macro-level contributions to rural economic growth and household consumption. Secondly, research on the sports industry has predominantly concentrated on the impact of specific factors—such as the digital economy and digital finance—on the transformation and upgrading of the sector. However, despite these studies offering important theoretical foundations, a significant research gap remains: few have systematically examined how comprehensive DCC—as a holistic strategy—affects the development of the rural sports industry through specific mechanisms. This study seeks to bridge the existing gap by developing an empirical model to elucidate the intrinsic causal relationship between DCC and the sports industry.

Compared to previous studies, the contributions of the present study are threefold: (1) it examines the theoretical relationship between DCC and the development of the sports industry, thus expanding the literature in this field; (2) it incorporates MFA and rural consumption upgrade (RCU) as mediating and moderating variables to explore the inherent mechanisms using appropriate econometric models, thereby contributing novel perspectives to the development of the sports industry; and (3) it investigates regional heterogeneity to assess inter-city differences in the relationship between DCC and sports industry development, offering rational explanations based on regional disparities.

As a key component of China’s rural revitalization strategy, the core objective of DCC is to drive the modernization and transformation of sectors such as agriculture, culture, education, and healthcare through the integration of digital technologies. In recent years, the Chinese government has introduced a series of supportive policies to facilitate DCC and encourage the application of digital technologies to upgrade rural industries.

In this context, the sports industry—an essential driver of rural economic development and a contributor to enhancing residents’ quality of life—has been significantly influenced by DCC. Specifically, DCC has enhanced the informatization level of rural sports infrastructure. Technologies such as IoT, big data, and AI have enabled intelligent management of rural sports facilities, thereby enhancing their utilization rates (Zhao X. et al., 2024; Zhao Y. et al., 2024). Systems for online reservations, intelligent monitoring, and digital operations have optimized the allocation of sports resources, reduced venue idleness, and reinforced the capacity of rural public sports services. Moreover, digital technologies have facilitated the market-oriented development of the rural sports industry. The emergence of e-commerce and short-video platforms has created new marketing and promotional avenues for rural sports tourism, training programs, and event hosting (Zhao X. et al., 2024; Zhao Y. et al., 2024). Through the integration of “Internet + Sports,” rural programs—including traditional ethnic sports, outdoor adventures, and grassroots competitions such as “Rural BA” and “Rural Super”—have been able to overcome geographical constraints and attract a extensive consumer base. These have contributed to the expansion of the rural sports tourism and event markets, extending the value chain of the sports industry (Tan and Bu, 2025).

Moreover, DCC has transformed the sports consumption behavior of rural residents. The prevalence of smart devices has facilitated convenient access to fitness content, while services such as remote coaching and online classes have increased sports participation. These changes have not only stimulated rural demand for sports consumption but also prompted the sports industry to optimize its supply structure to meet the DCCerse and personalized market needs (Zhang and Dong, 2024). Based on the above analysis, the following research hypothesis is proposed:

Digital technologies have significantly enhanced the allocation efficiency of key production factors—such as capital, technology, and labor—by reshaping the pathways of factor circulation and redefining value creation models. They also assist in overcoming traditional barriers of time, space, and information asymmetry within factor markets (Zhang et al., 2025).

Firstly, in the context of DCC, technologies such as big data, remote sensing, and blockchain are applied to land information management systems, enhancing the scientific planning and utilization of rural sports infrastructure. This alleviates issues of idle land and inefficiency, optimizes the structure of land resource allocation, and revitalizes the market for land use in rural sports development (Fan and Kang, 2023).

Secondly, the rural sports industry has historically suffered from limited financing channels and long capital return cycles. The advent of digital finance has offered solutions by expanding funding sources. Progressive digital tools—such as inclusive finance, crowdfunding models, and blockchain-enabled risk control mechanisms based on big data—have provided the rural sports industry with increased social capital, improved capital allocation efficiency, and reduced investment risks, thereby fostering its market-oriented development (QI et al., 2020).

Thirdly, DCC has also promoted the optimal allocation of human resources within the sports industry. Supported by digital tools such as distance education and online training platforms, rural residents are able to access more professional instruction, which enhances the overall skill level of practitioners in the rural sports industry (Wang and Wu, 2024). Furthermore, the establishment of digital employment platforms helps to overcome geographic barriers, enabling professional sports talents to accurately meet rural demands, thus optimizing the human resources structure and spurring industry competitiveness. Based on the above analysis, the following hypothesis is proposed:

DCC serves not only as a strategic path for rural revitalization but also as a key catalyst for RCU (Wang et al., 2021). It enhances digital infrastructure, improves information flow, and raises residents’ income levels, thereby effectively stimulating the consumption demand and promoting the expansion and upgrade of the rural sports industry.

On one hand, advancements of information and communication technologies have narrowed the digital DCCide between urban and rural areas. Consequently, rural production and lifestyles have been significantly altered by enhanced information infrastructure, optimized factor allocation, and expanded agricultural product circulation channels. This, in turn, enhances the digital literacy and consumption capacity of farmers, stimulates rural domestic demand, and reshapes the rural consumption structure—from subsistence-level consumption to development-oriented and enjoyment-oriented consumption. These alterations offer robust technological and institutional support for RCU (Bi and Chu, 2025).

On the other hand, RCU is accompanied by increased health consciousness and transformed residential lifestyles, which results in a growing, DCCerse, and multi-level demand for sports consumption. The rising demand for physical fitness, leisure, and recreation services in rural areas has spurred the expansion of the sports industry, enriching its product offerings and services. Against the backdrop of urban–rural integration, this trend fosters the extension of sports resources to grassroots communities and hastens the optimization of the sports industry’s spatial distribution, service models, and value chains. Consequently, RCU has emerged as a crucial driver in fostering the coordinated development of regional economies and enhancing national physical fitness (Wan and Wang, 2024). Based on the above analysis, the following hypothesis is proposed:

In summary, according to the research hypothesis of this paper, the model path diagram of H1-H3 is constructed. As shown in Figure 1 below.

To verify H1, Model 1 was constructed to examine the impact of digital countryside construction (DCC) on the development of the sports industry (Sic_it). This model also incorporated various selected control variables, such as government intervention (Gov_it), the level of financial development (Fin_it), farmers’ investment capacity (Fic _it), the extent of rural road governance (Roa_it), and the level of education (Edu_it). The regression coefficients of these variables were also introduced, denoted by { α j } j = 1 6 . If H1 holds, the regression coefficient of DCC (α₁) is expected to be significantly greater than 0, indicating that Sic promotion is greater than 0. This confirms that DCC fosters the development of the sports industry. Additionally, Year_t represents the fixed temporal effect, while City_t dneotes the fixed regional effect. These variables are used to control for the common shock of unobservable temporal and regional factors on the development of the sports industry, and ε is a random error term. Therefore, Sic_it is calculated as:

Subsequently, Model 2 was constructed to examine the moderating effect of FMA on the relationship between DCC and the sports industry. This model highlighted the effect of the interaction between DCC and FMA on the sports industry, which is represented by DCC_it × FMA_it . Consequently, Sic_it is calculated as:

To examine the mediating effect of rural consumption upgrading (RCU) on the relationship between DCC and the development of the sports industry, Model 3 was constructed, yielding:

Descriptive statistical analysis was initially conducted to clarify the variation characteristics of each variable and achieve a more comprehensive understanding of the samples’ development patterns. To mitigate potential heteroskedasticity in empirical regression, natural logarithmic transformation was applied to the following variables: financial development, rural household investment capacity, rural road governance level, education level, and RCU. As shown in Table 3, the mean and standard deviation for DCC were 0.1122 and 0.0963, respectively, whereas those for the sports industry were 0.1182 and 0.0943. These values suggest a relatively low variability and a concentrated distribution across samples. Subsequent analysis of the standard deviation, maximum, and minimum values for other variables reveals considerable variations in financial development, rural investment capacity, and road governance levels across different provinces. Regional disparities in economic policy, geographic coverage, and resource endowments likely explain these discrepancies.

To account for individual regional and temporal fixed effects, a panel two-way fixed-effects model (Equation 7) was employed, with the growth of the sports industry serving as the dependent variable and DCC as the key independent variable. Government intervention, financial development, rural household investment capacity, road governance level, and education level were included as control variables. The regression results are presented in Table 4.

Model Sic (1) presents the baseline regression without control variables. Model Sic (2) includes control variables but omits fixed effects, while Model Sic (3) incorporates both control variables and regional and temporal fixed effects. In all three models, the regression coefficients for digital countryside construction (DCC) are 0.3359, 0.3791, and 0.3129, respectively—all of which are positive and statistically significant at the 1% level. This suggests that digital countryside construction significantly promotes the development of the sports industry.

The regression results in Table 4 indicated that enhanced digital infrastructure provided an essential foundation for connecting rural sports resources. The proliferation of online platforms and social media has reduced promotional costs, broadened market access for rural sports brands, and enhanced accessibility and participation in sports consumption for rural residents (Fu, 2024). Meanwhile, digital governance tools have assisted planning and performance assessment, enabling governments to adjust policies based on real-time data. This further enhances investment efficiency and fosters cross-sector integration through initiatives such as “Internet + Sports + Tourism” and “E-commerce + Rural Sports Equipment (Zhang et al., 2025).” This multi-dimensional integration, centered on sports events, drives the coordinated development of related sectors such as leisure, recreation, and tourism (Zhang et al., 2025).

However, there remains a paucity of research on the nexus between DCC and the growth of the sports industry in China. International literature suggests that the digital economy plays a significant role in facilitating the expansion of scale and diversification of services within the urban sports industry by enhancing resource allocation efficiency and reducing information asymmetry (Li and Han, 2023; Krishna et al., 2024). This study further indicates that such a mechanism may also be operative in rural contexts. Particularly against the backdrop of a national strategic emphasis on synergistically advancing “digital villages” and “mass fitness,” the catalytic role of digitalization in promoting the rural sports industry assumes heightened policy relevance and practical significance.

Regarding the control variables, Models Sic (2) and Sic (3) provide the following insights: Government intervention exhibits negative coefficients of −0.0479 and −0.1031, respectively. While not significant without fixed effects, the coefficient becomes significant at the 10% level when fixed effects are included, indicating that structural differences across regions and time periods highlight the negative influence of government intervention. Financial development shows positive coefficients of 0.0275 and 0.0411, both significant at the 1% level, suggesting that financial advancement supports optimized capital allocation, DCCersified financing, and reduced costs, thereby facilitating investment and innovation in the sports industry. The investment capacity of rural households also has a significant positive impact, indicating that increased capital supports infrastructure development and boosts local sports consumption, thus stimulating the synergistic growth of the sports industry chain (Liu et al., 2024). However, road governance and education levels do not exhibit statistically significant effects in this analysis, implying their influence may be limited or overshadowed by more dominant factors within this economic structure.

Given the substantial variations in natural conditions, economic resources, and development levels across different regions in China, a heterogeneity analysis was subsequently conducted, focusing on the regional divisions established by the National Bureau of Statistics. To examine the differential impact of DCC on the development of the sports industry across the entire country, the samples were classified into three primary regions: eastern China (including Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, and Guangdong), central China (including Shanxi, Inner Mongolia, Anhui, Jiangxi, Henan, Hubei, and Hunan), and western China (including Chongqing, Sichuan, Guizhou, and Yunnan).

As shown in Table 11, the impact of DCC on the development of the sports industry exhibited pronounced regional heterogeneity. The regression results demonstrated a significant positive effect in eastern China, a negative but statistically insignificant effect in central China, and a positive but also insignificant effect in western China. These disparities can be attributed to structural differences among different regions, including economic foundations, digital infrastructure, stages of sports industry development, and policy support.

Eastern China is characterized by a higher level of economic development, greater penetration of digital technology, and deeper urban–rural integration, thereby offering a favorable market environment and technological support for the growth of the sports industry.

In central China, the impact of DCC on sports industry development has been relatively limited. The reasons are twofold: Firstly, compared to eastern China, the central region may experience delays in policy coordination between DCC and sports industry development. Certain policies have not successfully integrated digital technologies into the local sports industry development plans, preventing policy benefits from creating synergies and impeding industrial advancement. Secondly, residents in central China may still favor traditional sports consumption habits, exhibiting relatively lower acceptance of digital sports services. Despite established digital infrastructure, the inertia of consumer preferences and habits hinders the potential simulative effect of digital technologies on sports consumption.

Regarding western China, the impact of DCC on sports industry development is minimal, or even negative, likely due to the following reasons: Firstly, considering the limited public resources in western China, substantial investments on digital infrastructure could temporarily divert critical resources from other sectors crucial to sports industry development, causing the “crowding-out effect” of infrastructure investments. This trade-off dynamic may explain why initial investments in DCC have failed to yield the anticipated positive effects. Secondly, given the significant geographical constraints, educational disparities, and digital literacy gaps in western China, it would take considerable time for the implementation of DCC to bridge the ever-expanding digital divide between urban and rural residents. Thirdly, compared to the eastern and central regions of China, the sports industry in the western part is underdeveloped, characterized by a low level of marketization and incomplete industrial chains. In this context, digital technology alone may find it challenging to generate a significant impact.