[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-110":3,"related-110":51},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":8,"secondary_topics":30,"classification":31,"search_phrases":44,"slug":47,"view_count":48,"doi":49,"paper":8,"created_at":50},110,"Research on the impact of the digital economy on the urban-rural consumption gap: evidence from Chinese cities","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1823645\u002Ffull","Qian Qu, Dongmei Yang, Yuntao Tan基于中国城市数据,实证研究数字经济发展对城乡消费差距的影响。研究发现数字经济通过促进农村消费便利化、降低交易成本等机制缩小城乡消费差距。",null,"## Abstract\n\nAchieving coordinated development between urbanization and rural revitalization requires narrowing the urban–rural consumption gap sustainably. This study investigates the association between the digital economy and the urban–rural consumption gap. Unlike previous studies focused on isolated factors or single mechanisms, this research examines both supply-side and demand-side channels simultaneously. Using panel data from 288 prefecture-level cities of China. The results suggest that the digital economy is negatively associated with the urban–rural consumption gap. We further explore the mediating roles of industrial structure optimization (supply-side) and income disparity reduction (demand-side), finding that both channels contribute to the observed association. Additionally, our results indicate that the relationship between the digital economy and the consumption gap is conditional on the level of government intervention, with a threshold of approximately 11.17% of GDP for fiscal expenditure. This study contributes to a clearer understanding that the digital economy may shape urban–rural consumption patterns through dual pathways.\n\n## 1 Introduction\n\nThe digital economy has emerged as the central driver of contemporary economic growth, fundamentally reshaping consumption patterns, environments, and structures. The rapid diffusion of digital technologies, accompanied by the expansion of platform-based markets, has accelerated the integration of online and offline consumption and facilitated the widespread adoption of contactless transaction services. China, the world’s largest digital consumer market, is a market where digital consumption continues to expand amid international trade uncertainties and post-pandemic structural adjustments. The recent evidence indicates that core digital economy industries account for approximately 10% of gross domestic product (GDP), while the deepening digitalization of the service sector enables China to maintain its position as the world’s largest online retail market for more than a decade.\n\nHowever, in a dual urban–rural economic structure, the distribution of digital dividends remains highly uneven. Significant disparities persist between urban and rural residents in terms of consumption environments, purchasing power, and access to information (). Existing studies suggest that the digital economy may exert opposing effects on the urban–rural consumption gap: it can unlock rural consumption potential by lowering transaction costs and broadening market access (). Yet it may also worsen resource allocation imbalances between urban and rural areas due to the “digital divide” (; ). This complex dynamic suggests that while the digital economy boosts overall consumption, it might simultaneously deepen stratification by widening the digital gap. The result is a situation where overall growth coexists with structural inequality. Therefore, determining the net effect of the digital economy on urban–rural consumption disparities becomes extremely essential to achieving the goals of expanding consumer markets and fostering common prosperity.\n\nDuring the early development of e-commerce, internet technologies and industrial resources were heavily concentrated in urban areas (Wang et al., 2021). This allowed urban residents to capitalize on the resulting convenience and price advantages rapidly. Meanwhile, rural residents, constrained by lagging infrastructure and limited digital literacy, were unable to participate in this process simultaneously. Consequently, the consumption gap between urban and rural regions has been widened. From the perspective of potential adverse effects of the digital economy, some studies have shown that e-commerce may, under certain conditions, reinforce this disparity (). At the current stage, with the deep penetration of Chinese e-commerce into rural grassroots communities, academic research generally affirms that the digital economy injects new vitality into the consumption market by driving technological innovation, thereby systematically enhancing the overall consumption levels of both urban and rural residents (). The continuous emergence of new digital technologies has spurred the development of diverse consumer products and services, effectively meeting residents’ growing personalized demands. Moreover, the digital economy expands the supply of “long-tail” consumption, unleashing dispersed demand that is difficult to meet in traditional markets (). It also fosters a secure, convenient, and transparent consumption environment, boosting the residents’ confidence and stimulating the consumption growth (). Addressing the core challenge of the urban–rural consumption gap, some studies focus on analyzing specific mechanisms: Internet penetration builds information bridges across urban and rural areas, breaking geographical barriers and enabling rural residents to access market resources more conveniently, demonstrating a significant convergence effect on narrowing the gap (). Digital inclusive finance further strengthens this effect by providing equitable financial services, thereby enhancing rural residents’ payment capacity (). However, existing research predominantly focuses on isolated factors or partial dimensions, lacking a systematic investigation of the overall effect, intrinsic mechanisms, and spatial interconnectedness of the digital economy’s impact on the urban–rural consumption gap. Particularly noteworthy is the scholarly consensus that regional imbalances in digital economic development, as evidenced by disparities in infrastructure, technology adoption levels, and talent reserves (), will lead to significant regional heterogeneity in its moderating effect on urban and rural residents’ consumption.\n\nBefore proceeding, it is worth clarifying the scope and rationale of this study. Some scholars may argue that narrowing the urban–rural income gap is a more fundamental policy priority than narrowing the consumption gap. We fully acknowledge this view and do not claim that the consumption gap is more important than the income gap. Rather, we suggest that the consumption gap has independent research value for several complementary reasons. First, consumption expenditure is often viewed as a more direct indicator of household welfare and living standards than income, as it reflects actual material wellbeing rather than transitory earnings. Second, the consumption gap is not merely a mechanical reflection of the income gap; it is also shaped by factors such as consumption expectations, liquidity constraints, access to digital platforms, and the availability of goods and services in rural markets. The digital economy may influence these channels independently of its effects on income. Third, as will be shown in our mediation analysis, narrowing the income gap explains only part of the association between the digital economy and the consumption gap, suggesting that the consumption gap captures dynamics beyond those explained by the income gap alone. Therefore, while recognizing the primacy of income convergence, we believe that examining the consumption gap offers a distinct and understudied perspective on urban–rural integration. Our contribution should be seen as complementary to, rather than competing with, research on income disparities. Second, while existing studies have typically examined the mediating role of industrial structure or income disparities in isolation, few have compared the relative importance of both mechanisms simultaneously. We incorporate both industrial structure optimization (supply-side) and the narrowing of urban–rural income disparities (demand-side) into a unified mediation analysis framework, quantifying the proportions of transmission effects attributable to each. Third, while existing research has rarely explored the role of government intervention in shaping the digital economy’s effects on the urban–rural consumption gap, we use a panel threshold regression model to examine this non-linear relationship. Our results suggest that the digital economy is associated with a narrower consumption gap, with GDP below approximately 11.17%.\n\nAgainst this backdrop, this study focuses on the core issue of how the digital economy affects the urban–rural consumption gap. It aims to integrate theoretical and empirical findings to conduct an in-depth analysis of the mechanisms, heterogeneous characteristics, and policy thresholds through which the digital economy affects the urban–rural consumption disparity, thereby providing valuable theoretical support and practical guidance for narrowing the urban–rural consumption gap and advancing coordinated regional development. The marginal contributions of this study are threefold. Unlike studies that rely solely on either city-level or provincial-level data, we combine both spatial scales using prefecture-level city data for the main analysis and provincial-level data for robustness tests. This allows us to examine the localized effects of the digital economy while validating the stability of findings across different spatial scales.\n\n## 2 Theory and hypotheses\n\n### 2.1 Direct effect of the digital economy on the urban–rural consumption gap\n\nThe digital economy may affect the urban–rural consumption gap through multiple channels. On the supply side, digital tools such as mobile payments and e-commerce platforms can help dismantle service barriers, granting rural residents more equitable access to consumption, thereby releasing latent demand and activating lower-tier markets (). Digital platforms can also integrate diverse rural industrial resources to foster cross-regional linkages among market entities, incubating innovative products, services, and business models (), thereby significantly expanding employment and income-generating channels. On the demand side, digital consumption methods can continuously unleash rural consumption potential by reducing transaction costs, information search expenses, and decision-making burdens (). Leveraging detailed user data, firms may be able to match supply and demand more efficiently through personalized products and services, thereby laying a micro-level foundation for integrating urban–rural consumption markets (). However, the digital economy may also exacerbate existing inequalities. During the early development of e-commerce, internet technologies and industrial resources were heavily concentrated in urban areas (Fan et al., 2021), enabling urban residents to capitalize on digital convenience and price advantages rapidly. Rural residents, constrained by lagging infrastructure and limited digital literacy, were unable to participate in this process simultaneously. Consequently, the net effect of the digital economy on the urban–rural consumption gap is an empirical question that warrants careful investigation (; ).\n\nBased on the above discussion, this study posits the following hypothesis H1: The digital economy is negatively associated with the urban–rural consumption gap.\n\n### 2.2 Mediating effects of industrial structure upgrading and the urban–rural income gap\n\n#### 2.2.1 Digital economy, industrial structure upgrading, and the urban–rural consumption gap\n\nAt present, China’s digital economy ranks among the largest globally. The coordinated evolution of digital industrialization and industrial digitalization has generated sustained expectations of income growth. The in-depth development of this digital ecosystem significantly drives industrial structure optimization and upgrading, providing critical momentum for China to transcend the middle-income trap and transition toward high-income status. Industrial restructuring impacts labor markets through three primary pathways. First, it generates technology-intensive employment by enabling the cross-regional reallocation of labor factors, facilitating the transfer of surplus rural workers to urban non-agricultural sectors, thereby driving human capital appreciation and welfare enhancement (). Second, it revitalizes the value of rural production factors by digitally empowering traditional agriculture and expanding the distribution of agricultural products via e-commerce platforms (). Third, it elevates labor compensation share, particularly amplifying income elasticity for low-income groups (). According to the law of diminishing marginal consumption propensity, income growth within these populations amplifies multiplier effects on consumption expansion, providing microfoundations for upgrading China’s consumption structure. Consistent with Friedman’s permanent income hypothesis, such stability in expectations substantially strengthens residents’ propensity to consume immediately. Crucially, rural consumption patterns are undergoing a fundamental transformation: accelerating shifts from subsistence-oriented expenditures (e.g., education, healthcare) toward developmental and enjoyment-focused consumption (e.g., smart homes, cultural tourism), driving a persistent narrowing of urban–rural consumption-tier gaps (). From a supply-side structural reform perspective, industrial upgrading enhances total factor productivity, propelling product and service supply systems toward differentiation and quality refinement. This progress effectively bridges structural supply–demand mismatches while expanding the foundational scale of the consumption market.\n\nBased on the above discussion, this study hypothesizes that H2: The digital economy significantly reduces the urban–rural consumption gap through the transmission channel of industrial structure upgrading.\n\n#### 2.2.2 Digital economy, urban–rural income gap, and the urban–rural consumption gap\n\nAmidst the convergence of global value chain restructuring and digital technological revolution, the digital economy has transitioned from an efficiency tool to an institutional public good, manifesting spatially heterogeneous and stage-dependent income distribution effects (). China’s deepening openness is accelerating the expansion of this digital ecosystem, now established as a core engine of national high-quality economic development. Empirical evidence confirms that most Chinese regions lie within a developmental window in which digital economic growth converges on the urban–rural income gap, with a statistically significant negative correlation between the two (). Rapid digital advancement leverages industrial structure optimization and integration to curb the widening trajectory of income disparity. Crucially, it directly elevates rural residents’ per capita disposable income while indirectly empowering rural prosperity through enhanced urbanization efficiency (), thereby epitomizing its inclusive nature. Given the validated role of the urban–rural income gap as a primary determinant of consumption disparities, its narrowing fundamentally reshapes expenditure patterns on goods and services, key metrics that reflect residents’ welfare. During consumption upgrading, developmental expenditures (e.g., education, cultural activities) systematically rise relative to subsistence consumption, a trend amplified by digital transformation. Consequently, the income gap exhibits a strong positive correlation with service consumption disparities: income convergence directly contracts consumption gaps, whereas divergence exacerbates them.\n\nBased on the above discussion, this study proposes the following hypothesis H3: The digital economy significantly narrows the urban–rural consumption gap through the transmission channel of reducing the urban–rural income gap.\n\n### 2.3 The threshold effect of government intervention level\n\nGovernment intervention, as a pivotal institutional variable mediating the digital economy’s impact on the urban–rural consumption gap, operates through the exercise of public power to regulate the efficiency of market resource allocation and shapes the institutional environment. When maintained within moderate bounds, such intervention enables administrative measures to optimize the distribution of digital economy dividends via coordinated mechanisms. Specifically, implementing digital inclusive financial policies and constructing public service platforms for rural e-commerce reduces barriers to digital technology adoption in rural areas, facilitating the diffusion of the digital economy’s penetration effects to low-income populations and establishing foundational institutional infrastructure (). Concurrently, while ensuring market-based circulation of data elements, the government utilizes redistribution tools, including fiscal transfers and tax incentives, to address the digital economy’s Matthew effect, characterized by disproportionate advantages for capital-intensive industries, consequently establishing an inclusive regulatory framework (). Additionally, investments in vocational skill training and digital education enhance rural residents’ adaptability to emerging employment forms and strengthen their capacity to secure sustainable income through the digital economy, thus advancing the human capital development system (). Essentially, this embodies the role of a “market-augmenting” government, which preserves the self-organizing innovative dynamism of the digital economy while mitigating urban–rural disparities in factor endowments through institutional compensation mechanisms.\n\nHowever, excessive government intervention may induce dual distortion effects. Firstly, frequent industrial planning and selective support policies can precipitate resource misallocation. Such practices risk diverting digital economy development into prestige-driven projects, allocating substantial fiscal investments to repetitive hardware construction while neglecting the cultivation of market entities’ innovation capabilities. Consequently, rural areas become trapped in a low-efficiency equilibrium characterized by high digital investment yet limited returns (). Secondly, stringent market access regulations, coupled with local protectionism, fragment the unified data factor market, thereby suppressing cross-regional synergistic effects of digital technologies. Notably, preferential policies disproportionately favoring state-owned digital platforms may marginalize private enterprises in county-level markets, undermining the capacity of small and medium-sized enterprises (SMEs) to leverage digital tools for consumer market penetration. At a deeper institutional level, intensive intervention often catalyzes the formation of power-capital nexuses. This distorts the wealth creation mechanism of the digital economy to serve specific interest groups, exacerbating structural disparities in factor returns between urban and rural regions. Crucially, the inherent institutional rigidity of such models fundamentally conflicts with the adaptive efficiency of market mechanisms, ultimately reversing the digital economy’s marginal effect in narrowing the urban–rural consumption gap.\n\nBased on the above discussion, this study proposes the following hypothesis H4: There exists a threshold effect of government intervention on the process by which the digital economy influences the urban–rural consumption gap. When the degree of government intervention falls within a moderate range, the digital economy can effectively narrow the urban–rural consumption gap. However, once government fiscal involvement becomes excessive, the impact of the digital economy may cease to exist.\n\n## 3 Methods\n\n### 3.1 Empirical model and estimation method\n\nAs theorized earlier, the digital economy can effectively narrow the urban–rural consumption gap. To mitigate heteroscedasticity and reduce scale differences, this study applies a logarithmic transformation to selected control variables. A two-way fixed effects model is employed to evaluate the relationship between the digital economy and the consumption gap, as specified in [Equation 1](https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Fart","Frontiers in Sustainable Food Systems 2026-07-02","2026-07-02T01:00:00Z","论文",10,false,76,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},20,22,18,14,2,1,"论文研究数字经济对城乡消费差距的影响，使用中国288个城市面板数据，方法新颖，结论可靠，但发表于一个月前，时效性较低。",[25],{"name":10,"url":6},[27,28,29],"数字经济","城乡消费差距","实证研究",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":35},"unclassified","2026-10-22.2","rules",{"candidates":36,"agricultural_evidence":42,"reason":43},[37],{"code":38,"score":22,"supported":14,"title":39,"abstract":40,"tags":41},"I6",[],[],[27],true,"缺少足够的主题证据",[45,46],"城乡消费差距 实证研究 数字经济","城乡消费差距 实证研究","城乡消费差距实证研究数字经济-110",11,"10.3389\u002Ffsufs.2026.1823645\u002Ffull","2026-07-31T00:00:56.007395Z",{"total":52,"page":22,"page_size":52,"items":53},6,[54,103,149,202,241,282],{"id":55,"title":56,"url":57,"summary":58,"summary_zh":8,"content":8,"source_name":59,"source_url":8,"published_at":60,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":61,"score_detail":62,"sources":67,"tags":69,"primary_topic":8,"secondary_topics":74,"classification":75,"search_phrases":87,"slug":90,"view_count":91,"doi":92,"paper":93,"created_at":102},5458,"数字经济对农业高质量发展的影响——以新疆14地州市为例 (Impact of Digital Economy on the High-Quality Development of Agriculture: Evidence from the 14 Prefectures and Cities of Xinjiang)","http:\u002F\u002Fzgnjhxb.niam.com.cn\u002FCN\u002F10.13733\u002Fj.jcam.issn.2095-5553.2026.10.041","基于2010—2022年新疆14地州市面板数据，熵值法测度双指数，中介与固定效应模型分析。数字经济对农业高质量发展影响系数0.132且显著，农业产业结构升级中介效应0.0649。区域异质性为东疆最强、南疆次之、北疆最弱。","中国农机化学报 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面板数据","新疆数字经济农业高质量发展-5458",0,"10.13733\u002Fj.jcam.issn.2095-5553.2026.10.041",{"doi":92,"openalex_id":8,"authors":94,"venue":8,"cited_by_count":91,"oa_url":8,"card":95,"direction":99,"ingested_from":101},[],{"tldr":96,"method":97,"finding":98,"direction":99,"opportunity":100},"基于新疆14地州市面板数据，实证检验数字经济对农业高质量发展的影响及中介机制。","2010—2022年新疆14地州市面板数据，熵值法测度指数，中介与固定效应模型。","数字经济显著促进农业高质量发展（系数0.132），农业产业结构升级起中介作用，效应东疆最强、南疆次之","数字乡村与农业信息化","可延伸至县域尺度、微观农户数据及数字基础设施异质性下的机制识别与政策分区研究。","agent","2026-10-21T00:10:08.003418Z",{"id":104,"title":105,"url":106,"summary":107,"summary_zh":8,"content":8,"source_name":108,"source_url":8,"published_at":109,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":110,"score_detail":111,"sources":114,"tags":116,"primary_topic":8,"secondary_topics":119,"classification":120,"search_phrases":136,"slug":139,"view_count":91,"doi":140,"paper":141,"created_at":148},5300,"张捷\u002F李林飞《中国林业经济》:数字经济政策对农业高质量发展的影响研究——基于国家大数据综合试验区的准自然实验","https:\u002F\u002Fzglyjj.nefu.edu.cn\u002Farticle\u002Fdoi\u002F10.13691\u002Fj.cnki.cn23-1539\u002Ff.2026.04.001","东北林业大学经济管理学院张捷、李林飞基于2011-2023年中国31个省级行政区面板数据,以国家大数据综合试验区建设为准自然实验,运用多期双重差分模型评估数字经济政策对农业高质量发展的影响;研究发现数字经济政策显著促进农业高质量发展且具滞后性和累积性;对本地区农业高质量发展具显著正向直接效应,但对其他地区产生负向空间溢出,呈现\"本地促进、外部抑制\"特征;非粮食主产区估计效应相对更强。","中国林业经济(2026,4)","2026-10-15T00:00:00Z",80,{"impact":19,"substance":18,"depth":19,"authority":20,"freshness":112,"relevant":22,"comment":113},8,"基于31省面板数据与国家大数据综合试验区的准自然实验，方法规范、结论有政策参考价值，但属学术论文且非时效热点，可入精选备选。",[115],{"name":108,"url":106},[27,70,117,118],"空间溢出","大数据试验区",[],{"status":32,"locked":14,"version":33,"method":34,"evidence":121},{"candidates":122,"agricultural_evidence":42,"reason":43},[123,128,132],{"code":124,"score":22,"supported":14,"title":125,"abstract":126,"tags":127},"I4",[],[],[117],{"code":38,"score":22,"supported":14,"title":129,"abstract":130,"tags":131},[],[],[27],{"code":83,"score":22,"supported":14,"title":133,"abstract":134,"tags":135},[],[],[70],[137,138],"国家大数据综合试验区 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