Study on the Carbon Emission Reduction Effect of China’s Commercial Circulation Industry

Abstract

The circulation industry, centered on the flow of commodities and supported by logistics, information, and capital flows, serves as a vital link between production and consumption, playing a pivotal role in enhancing production efficiency and facilitating economic transformation and upgrading. Through the spatial aggregation and interconnection of industries such as wholesale and retail, logistics, and catering, the circulation industry forms an economic system characterized by spatial cohesion and resource sharing, thereby significantly impacting carbon emissions through improved production efficiency. This study integrates both the “production side” and “consumption side” into an analytical framework examining the relationship between the circulation industry and carbon emissions. It looks into the mechanisms underlying the industry’s influence on carbon reduction and empirically tests these mechanisms using systematic estimation methods based on data from 30 Chinese provinces spanning 2011 to 2020. The results reveal a pronounced carbon reduction effect within the circulation industry, which intensifies across quantiles, exhibiting regional disparities with stronger effects in central regions compared to eastern regions and insignificant effects in western regions. On the production side, the circulation industry significantly reduces carbon emissions through scale, technology, and structural effects. Conversely, on the consumption side, while the upgrading of rural residents’ consumption structure exhibits a carbon emission suppression effect, the same upgrade among urban residents leads to an enhancement of carbon emissions. The primary contribution of this study lies in constructing an analytical framework that explores the nexus between the circulation industry and carbon emissions. It empirically validates the mechanisms through which the industry impacts carbon emissions at both the production and consumption ends, uncovering regional heterogeneities in carbon reduction efforts. This work provides novel theoretical insights and empirical evidence that can inform global carbon reduction strategies.

1. Introduction

In recent years, global climate change, exacerbated by excessive carbon emissions, has emerged as a dire threat to the equilibrium of Earth’s ecosystem and the wellbeing of humanity. Consequently, the development and implementation of effective carbon emission reduction strategies are paramount to achieving the global aspiration of “carbon peaking and carbon neutrality”. For developing nations, this imperative not only necessitates an urgent response but also constitutes a pivotal component of their future sustainable economic and social development strategies. From an environmental economics standpoint, production, distribution, and consumption represent the primary avenues of carbon emissions. Therefore, comprehensively advancing the low-carbon transformation of production, circulation, and consumption patterns, while mitigating carbon emissions from socio-economic activities, is essential for making substantial progress in combating climate change [1]. Consequently, exploring a comprehensive low-carbon transition pathway that encompasses production, distribution, and consumption is central to realizing overarching carbon emission reduction goals, fostering a low-carbon economy, and promoting environmentally sustainable development.

In the academic discourse surrounding global climate change and carbon emissions, substantial research has converged on the dual focal points of production and consumption. Within the realm of production, scholars have meticulously scrutinized the intricate interplay between economic scale expansion, industrial structure transformation, technological advancements, and carbon emissions. Drawing upon the theoretical framework of the “Environmental Kuznets Curve (EKC)”, the relationship between economic growth and carbon emissions is depicted as an inverted U-shaped curve, where the inflection point—marking the transition from an increase to a decrease in carbon emissions—is contingent upon the extent of technological innovation and the pace of industrial structure upgrading [2]. The progression towards higher-order industries, notably those characterized by high technological content, intensive capital, and knowledge, such as the secondary and tertiary sectors, contributes to mitigating energy intensity and optimizing energy structures, thereby alleviating the burden of regional carbon emissions [3]. Technological advancements, particularly those pertaining to green technology innovation and clean technology applications, are widely acknowledged as pivotal in the pursuit of economic decarbonization and climate change mitigation. These advancements significantly enhance energy efficiency and propel the transition towards cleaner energy sources [4]. At the consumption end, the shift towards low-carbon consumption patterns is recognized as a vital strategy for achieving societal-level carbon emission reductions. Environmentally conscious consumer choices not only directly diminish final energy consumption and associated carbon emissions but also exert an indirect influence by shaping market demands. These green preferences encourage producers to embrace their environmental and social responsibilities, adopt cleaner production technologies, and foster green management innovations. Consequently, a virtuous cycle is established, where consumers drive producers towards sustainability, fostering a new, low-carbon economy power chain that spans from the consumer to the producer [5].

As the strategic significance of the circulation industry in the national economy continues to escalate, academic inquiry into this sector has intensified considerably. Xia Chunyu (2022) [6] posits that circulation encompasses not merely the exchange of commodities within markets but also the circulation of capital, technology, labor, and other essential factors [6]. Conversely, Yan Weilong (2003) conceptualizes circulation as an expansive process that embodies the dynamic equilibrium system intertwining nature, society, and humanity [7]. Despite these disparate perspectives, a consensus emerges among scholars that circulation constitutes a multifaceted industry comprising wholesale, retail, trade logistics, among others, with business flow serving as its core and being underpinned by logistics, information flow, and capital flow. This composite nature underscores the complexity and interconnectedness of the circulation industry within the broader economic landscape.

In contemporary socio-economic contexts, circulation transcends being merely a platform for commodity exchange; it serves as a pivotal nexus for value realization, capital accumulation, and market mechanism construction. The optimization of logistics systems not only ensures the seamless transformation of commodity value chains but also mitigates economic fluctuations and enhances the efficient allocation of production factors [8]. Within the realm of production, enhancing logistics efficiency not only serves as a cost-effective and productivity-boosting measure but also accelerates the circulation of product value and capital accumulation, thereby fostering rational resource allocation [9]. Additionally, an advanced circulation system mitigates information asymmetries, enhances market transparency, incentivizes environmentally sustainable production practices, fosters product and process innovation, enables sustainable economic growth, and effectively curbs resource consumption and carbon emissions [10]. On the consumption front, circulation exerts an indirect yet significant impact on reducing the carbon footprint of various industries by capturing and adapting to market demands, shaping consumer behavior and expectations, influencing production and market strategy adjustments, reshaping consumption patterns, and driving improvements in the industrial chain’s energy efficiency and environmental compliance [11]. Consequently, looking into how the circulation industry subtly reconfigures production and consumption structures, thereby influencing carbon emission levels, constitutes a vital and underexplored domain within environmental economics that warrants profound investigation.

As the world’s manufacturing hub, second largest economy, and a significant trading power, China’s substantial industrial output and consumer demand result in significant energy consumption and carbon emissions, necessitating heightened efforts in energy conservation and emission reduction [12,13,14]. Against this backdrop, China’s transition towards a green and low-carbon economy emerges as both a complex and pressing endeavor. In this study, we focus on China as our research subject. We develop a theoretical framework centered on circulation and regional carbon emissions, encompassing both production and consumption aspects. Our objective is to investigate the profound impact of the circulation industry on regional carbon emissions, with particular emphasis on elucidating the roles of production and consumption within this process.

The primary contributions of this paper are twofold. Firstly, it comprehensively establishes the developmental orientation and index for the circulation industry, empirically examines its influence on regional carbon emissions, and offers a novel theoretical perspective on the nexus between the circulation industry and environmental benefits. This contribution enriches our understanding of the relationship between the two and provides valuable insights. Secondly, the paper adopts the social reproduction theory, integrating factors such as economic scale, industrial structure, and technological advancements at the production end, alongside the upgrading of urban and rural consumption structures at the consumption end. This holistic approach refines the analytical framework, examining the circulation industry’s impact on regional carbon emissions, elucidating its internal mechanisms and effect pathways. Theoretically, this study broadens the scope of research on the environmental implications of the circulation industry, establishing a multi-faceted analytical framework to assess its contributions to ecological civilization and carbon emission reduction. Practically, it underscores the delicate balance between ecological protection and economic growth, highlighting the pivotal role of the circulation industry in achieving carbon emission reductions and fostering ecological civilization. Furthermore, it emphasizes the significance of promoting high-quality development within the circulation industry for global carbon emission reduction efforts, offering empirical evidence and strategic insights for developing nations to chart a green future through the lens of the development of the circulation industry.

2. Theoretical Analysis and Hypothesis Research

This study endeavors to look into the intricate relationship between the development of the circulation industry and regional carbon emission intensity, with a particular focus on elucidating the mediating roles of industrial and consumption ends. To systematically dissect this relationship, we devise a two-dimensional theoretical framework. Firstly, we scrutinize the circulation industry’s specific impacts on carbon emission intensity through the lens of scale, structural, and technological effects operating at the production level. Secondly, we examine the intermediary function of the upgrading of urban and rural consumption structures in modulating the influence of the circulation industry on carbon emission intensity, adopting a consumption-centric perspective. Through this comprehensive analysis, we aim to meticulously dissect the multifaceted mechanisms and pathways employed by the circulation industry in mitigating carbon emissions, thereby contributing to a deeper understanding of its role in environmental sustainability.

2.1. Influence Path Based on Production

(1) Scale effects. The development of the circulation industry significantly propels the expansion of economic activities. By enhancing logistics efficiency, it accelerates the interface between production and consumption, thereby expanding market size and minimizing transaction costs, ultimately fostering regional economic growth. Building upon the work of Rushton, Croucher, and Baker (2014), the optimization of the logistics system within the circulation industry notably improves product flow efficiency, abbreviates transportation and inventory cycles, and realizes the effective allocation of capital flows, all of which exert a substantial stimulatory influence on economic growth [14]. From a market perspective, echoing Krugman’s (1980) insights, the circulation industry, by eliminating transactional barriers and fostering market integration, empowers enterprises to augment production scales, diminish fixed costs per unit of output, and elevate overall production efficiency, thereby catalyzing an increase in economic output [15]. Furthermore, the advent of digitalization and the proliferation of e-commerce have significantly augmented the information transfer efficiency within the circulation industry, mitigating information asymmetry, reducing transaction costs, enhancing market transparency, and bolstering operational efficiency. These advancements have, in turn, facilitated the further expansion of market size and accelerated economic output growth, as Bailey (1998) observes [16]. Considering these factors collectively, the advancement of the circulation industry indirectly impacts regional carbon emissions by augmenting the scale of economic output. As the expansion of economic activities often coincides with heightened energy consumption, the efficiency gains and market expansion achieved by the circulation industry may stimulate an increased demand for energy, particularly fossil fuels, thereby positively contributing to regional carbon emissions.

(2) Structural effects. The business circulation industry constitutes a crucial juncture in expediting the seamless flow of information and mitigating market information asymmetry, thereby fostering greater market transparency and optimizing industrial structures. Drawing upon neoclassical economic theory, the efficacious operation of the circulation industry diminishes transaction costs and information disparities, stimulating more effective allocation of production factors and fostering industrial innovation. Furthermore, it propels the evolution of the economic structure towards greater efficiency and higher value-addedness, as posited by North (1990) [17]. In the context of the theory of industrial upgrading, the circulation industry, being an integral component of the service sector, serves as a direct indicator of a nation’s economic modernization level. Its development level can effectively catalyze the transition from secondary to tertiary industries, as argued by Fisher (1939) [18]. International experiences highlight the pivotal role played by the circulation industry in developed nations, acting as an engine for industrial structural transformation. By leveraging advanced information technology and logistics systems, it enhances inter-industry synergies and accelerates the optimization and upgrading of industrial structures, as evidenced by the works of Clark (1940) and Porter (1990) [19,20].Therefore, the advancement of the circulation industry stands as a pivotal factor in facilitating the optimization and upgrading of a nation’s industrial structure within its economy. Research has demonstrated that industrial structure upgrading fosters improved energy utilization efficiency across the economy and enhances the cleanliness of production processes through a strategic shift towards high-technology, low-energy-consumption industries. This, in turn, contributes to the mitigation of regional carbon emissions (Zhang, Pingtan, & Tu, X. W., 2023) [21]. Specifically, the low-carbon transformation of industries is instrumental in diminishing carbon dioxide emissions and accelerating the development of a sustainable, low-carbon economy (Lee et al., 2023) [22].

(3) Technology effect. As a vital component of the national economy, the circulation industry assumes a pivotal role in propelling industrial technological advancement. Its development effectively minimizes transaction costs, enhances resource allocation efficiency, and cultivates a conducive market atmosphere conducive to technological exchanges and innovations (Arora et al., 2004) [23]. Contemporary logistics and supply chain management incessantly incorporate novel technologies, such as informatization and automation, which directly expedite the rapid progression of industrial technology (Christopher, 2016) [24]. Furthermore, by facilitating the geographical dissemination of products and services, the circulation industry accelerates the dissemination of technological innovations and market penetration, thereby indirectly fostering the technological upgrading of the entire industry (Porter, 1998) [25]. Consequently, the circulation industry not only elevates efficiency through its own technological innovations but also acts as a catalyst, providing the impetus and conditions necessary for the industrial technological progress of the national economy. Empirical evidence underscores that technological progress can markedly diminish regional carbon emissions by augmenting energy efficiency, promoting the adoption of clean energy sources, and facilitating the optimization of industrial structures. As Popp et al. (2010) eloquently articulate, technological innovation and more efficient energy utilization present viable avenues for achieving greenhouse gas emission reductions, with the development of low-carbon technologies representing a cornerstone in mitigating carbon footprints [26].

Based on the aforementioned theoretical rationale, this study posits the following hypotheses:

Hypothesis 1: 

The advancement of the circulation industry fosters regional carbon emissions via the mechanism of output scale expansion.

Hypothesis 2: 

The evolution of the circulation industry mitigates regional carbon emissions by virtue of inducing industrial structure upgrading.

Hypothesis 3: 

The progress of the circulation industry curtails regional carbon emissions through the facilitation of technological advancements.

2.2. Influence Path Based on the Consumption End: The Perspective of Urban and Rural Consumption Structure

The innovative evolution of the circulation industry holds a pivotal position in the ongoing green transformation of consumption patterns. Internet e-commerce behemoths, including Alibaba and JD.com, have not only effectively bridged the information and material disparities between urban and rural consumption but also adeptly discerned the increasingly diversified consumer preferences by optimizing the commodity circulation and distribution framework [27]. For instance, innovative circulation practices, such as the direct-to-consumer e-commerce model for agricultural products, have fortified the linkage between urban and rural economies, aligning health needs, and vigorously propelled a transition from high-carbon to low-carbon consumption trends, thereby fostering an overarching green upgrade of consumption patterns and industrial structures. This paradigm shift notably enhances the system’s energy and resource recycling efficiency, mitigates the regional carbon footprint, and provides a robust foundation for the establishment of a low-carbon economic model [28]. In summary, while refining the consumption structure in both urban and rural settings, the circulation industry effectively accelerates the process of energy conservation, emission reduction, and the green transformation of the economic system through the environmentally conscious guidance of production, thereby pioneering a novel avenue towards realizing the global aspirations of carbon reduction and climate initiatives.

Based on the aforementioned theoretical rationale, this study proposes hypothesis 4: the development of the circulation industry inhibits regional carbon emissions through its positive impact on the consumption structure of urban and rural residents.

Drawing upon a comprehensive analysis of both production and consumption aspects, we present a analyzing framework diagram for the carbon emission reduction effect of the circulation industry, encompassing intermediary effects (Figure 1).

3. Description of the Model, Variables, and Data

3.1. Base Model and Estimation Method

(1)

Base model

To investigate the potential impact of the circulation industry’s development on regional carbon emission intensity, this study establishes a benchmark regression model and empirically examines the relationship between the circulation industry’s level of development and carbon emission intensity. The model’s specifications are outlined below:

$${\mathrm{CRE}}_{\mathrm{it}}={\mathsf{\beta }}_0+{\mathsf{\beta }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\beta }}_2{\mathrm{UR}}_{\mathrm{it}}+{\mathsf{\beta }}_3\ln {\mathrm{agdp}}_{\mathrm{it}}+{\mathsf{\beta }}_4{\mathrm{Labor}}_{\mathrm{it}}+{\mathsf{\beta }}_5{\mathrm{FBI}}_{\mathrm{it}}+{\mathsf{\beta }}_6{\mathrm{GOV}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(1)

In this equation, $CR{E}_{it}$ represents the carbon emission intensity for province i in year t; $LC{D}_{it}$ denotes the level of development of the circulation industry for province i in year t; ${\beta }_0$ represents the intercept term; ${\mathrm{UR}}_{\mathrm{it}}$ stands for the urbanization rate; $\ln {\mathrm{agdp}}_{\mathrm{it}}$ signifies the level of economic development; ${\mathrm{Labor}}_{\mathrm{it}}$ represents the scale of human capital; ${\mathrm{FBI}}_{\mathrm{it}}$ denotes the degree of openness; ${\mathrm{GOV}}_{\mathrm{it}}$ represents the degree of government intervention; ${\mathsf{\lambda }}_{\mathrm{t}}$ accounts for the time effect, which controls for unobservable omitted variables that vary over time but not across individual units; ${\mathrm{U}}_{\mathrm{i}}$ represents the individual effect, which controls for time-invariant unobservable omitted variables; ${\epsilon }_{it}$ represents the random disturbance term.

(2)

Mediated effect model

In examining the role of the development of the circulation industry in carbon emissions, this study adopts a mediation effects model, focusing on the two major aspects of production and consumption. Firstly, in terms of production, this paper selects output scale, industrial structure, and technological progress as mediating variables, and employs a stepwise regression analysis to accurately capture their mediating effects in the relationship between the development of the circulation industry and carbon emissions.

$$\ln {\mathrm{OS}}_{\mathrm{it}}={\mathsf{\pi }}_0+{\mathsf{\pi }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\pi }}_2{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(2)

$${\mathrm{IS}}_{\mathrm{it}}={\mathsf{\pi }}_0+{\mathsf{\pi }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\pi }}_2{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(3)

$${\mathrm{TA}}_{\mathrm{it}}={\mathsf{\pi }}_0+{\mathsf{\pi }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\pi }}_2{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(4)

$${\mathrm{CRE}}_{\mathrm{it}}={\mathsf{\theta }}_0+{\mathsf{\theta }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\theta }}_2{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\theta }}_3{\mathrm{IND}}_{\mathrm{it}}+{\mathsf{\theta }}_4\ln {\mathrm{OS}}_{\mathrm{it}}+{\mathsf{\theta }}_5{\mathrm{IS}}_{\mathrm{it}}+{\mathsf{\theta }}_6{\mathrm{TA}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(5)

In Equations (2)–(5), $\ln OS$ represents the mediating variable of scale effect, $\mathrm{IS}$ represents the mediating variable of industrial structure effect, $\mathrm{TA}$ represents the mediating variable of technological progress effect, and control represents the set of control variables.

Furthermore, from the perspective of consumption, the upgrading of urban residents’ consumption structure and rural residents’ consumption structure are considered as mediating variables for regression estimation.

$${\mathrm{UC}}_{\mathrm{it}}={\mathsf{\pi }}_0+{\mathsf{\pi }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\pi }}_3{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(6)

$${\mathrm{RC}}_{\mathrm{it}}={\mathsf{\pi }}_0+{\mathsf{\pi }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\pi }}_3{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(7)

$${\mathrm{CRE}}_{\mathrm{it}}={\mathsf{\theta }}_0+{\mathsf{\theta }}_1{\mathrm{LCD}}_{\mathrm{it}}+{\mathsf{\theta }}_2{\mathrm{control}}_{\mathrm{it}}+{\mathsf{\theta }}_3{\mathrm{IND}}_{\mathrm{it}}+{\mathsf{\theta }}_4{\mathrm{UC}}_{\mathrm{it}}+{\mathsf{\theta }}_5{\mathrm{RC}}_{\mathrm{it}}+{\mathsf{\lambda }}_{\mathrm{t}}+{\mathrm{U}}_{\mathrm{i}}+{\mathsf{\epsilon }}_{\mathrm{it}}$$

(8)

In Equations (6)–(8), $\mathrm{UC}$ represents the mediating variable for the upgrading of urban residents’ consumption structure, and $\mathrm{RC}$ represents the mediating variable for the upgrading of rural residents’ consumption structure.

3.2. Variable Selection

(1)

Explained variables:

Carbon Emission Intensity (CRE). In this study, the ratio of total carbon emissions to regional Gross Domestic Product (GDP) is selected as the Carbon Emission Intensity (CRE) to measure the effectiveness of carbon reduction. Carbon emission data are derived from the Carbon Dioxide Emission Inventory published by the Chinese Academy of Environmental Sciences (CEADs), and adjusted based on energy consumption data released by the National Bureau of Statistics, taking into account carbon emissions from fossil fuel combustion and industrial production processes. Following the methodology of Shan et al., this study accurately calculates carbon emissions resulting from the consumption of primary energy sources such as raw coal, crude oil, and natural gas ($C{E}_{ref-i}$), as well as carbon emissions from cement production processes ($C{E}_t$), ensuring the accuracy of carbon emission data and the scientific validity of the results [29]. The specific calculation method is as follows:

$$C{E}_{ref-i}=A{D}_{ref-i} \times E{F}_i$$

(9)

$$\begin{gathered} A{D}_{ref-i}=\text{Local energy production}+\text{Import quantity}-\text{Export quantity}+ \\ \text{Inter-provincial (city, district) inward transfer quantity}- \\ \text{Inter-provincial (city, district) outward transfer quantity}+\text{Inventory change quantity}- \\ \text{Non-energy usage quantity}-\text{Loss quantity} \end{gathered}$$

(10)

$$C{E}_t=A{D}_t \times E{F}_t$$

(11)

$$C{E}_t=C{E}_{ref-i} +C{E}_t$$

(12)

Formula (9) calculates the emissions of fossil fuels ($C{E}_{ref-i}$), where ($A{D}_{ref-i}$) represents the consumption of fossil fuels, and $\mathrm{i}$ represents the types of fossil fuels, namely raw coal, crude oil, and natural gas. Revised emission factors EF are used, with the latest research setting the emission factors for raw coal, crude oil, and natural gas at 0.499, 0.838, and 0.590 respectively; for cement, an emission factor of 0.2906 is used to more accurately reflect the Chinese context [30]. Formula (10) references the latest energy consumption data provided in the “China Energy Statistical Yearbook”, while the cement production data $A{D}_t$ in Formula (11) is directly sourced from the latest statistical results released by the National Bureau of Statistics.

(2)

Core explanatory variables:

The primary explanatory variable in this study is the level of the circulation industry’s development (LCD). Drawing from the operational dynamics and industry trends, and adhering to established scientific principles and recognized standards, a comprehensive evaluation index system (

Table 1. Comprehensive index system of the development level of the circulation industry.

First Indexes	Second Indexes	Index Measure Method
Scale of circulation industry (Distri1)	Per capita total retail sales of social consumer goods	Total retail sales of social consumer goods/Total resident population
	Total fixed assets investment per capita circulation industry at the end of the year	Total fixed asset investment/Total resident population at the end of the circulation industry
	Commodity market turnover of more than CNY 100 million	Commodity market turnover of more than CNY 100 million
Structure of circulation industry (Distri2)	The proportion of urban unit employees in circulation industry in urban unit employees	Employment of urban units in circulation industry/Employment of urban units
	The added value of the circulation industry as a proportion of GDP	The added value of circulation industry/Gross domestic product
	The added value of circulation industry accounts for the proportion of the added value of the tertiary industry	Value added of circulation industry/Value added of tertiary industry
Circulation industry efficiency (Distri3)	Wholesale and retail cost profit margins	Total profit of wholesale and retail industry/Cost of circulation industry
	Wholesale and retail inventory ratios	Total wholesale and retail inventory/Total wholesale and retail sales
	Wholesale and retail turnover rate	Wholesale and retail business income/Average inventory balance
Circulation industry facilities (Distri4)	Number of circulation legal person enterprises	Number of corporate enterprises in circulation industry
	The number of commodity trading markets above CNY 100 million	The number of commodity trading markets above CNY 100 million
	Average railway freight distance	Cargo turnover/Freight volume
	Road network density	Highway mileage/Area
	Highway quality	Class highway/Highway mileage

) has been formulated to gauge the overall advancement of the circulation sector. This index system aims to illuminate regional discrepancies in circulation industry competitiveness while delineating the sector’s overarching developmental trajectory. In constructing this system, insights were gleaned from the “Report on the Competitiveness of Circulation in Chinese Cities” issued by the China International Electronic Commerce Centre (CIECC) and the Institute of Financial and Strategic Studies of the Chinese Academy of Social Sciences (IFSAS). The framework comprises four primary indicators: scale, structure, efficiency, and infrastructure of the circulation industry, which are further disaggregated into fourteen secondary indicators. These measures are devised to provide a comprehensive assessment and analysis of the competitive landscape and developmental quality across various facets of the circulation industry. Details are outlined below:

The Magnitude of the Circulation Industry. The scale of the circulation industry serves as a comprehensive indicator reflecting the industry’s development status. It facilitates the analysis of supply and demand dynamics, as well as the comparison and evaluation of resources and value across different regions, thereby enabling more effective management of the overall disparities and circumstances within the regional circulation sector. In this study, several key indicators are utilized to gauge the scale of the circulation industry, focusing on both input and output factors. These indicators include: the per capita total retail sales of consumer goods, the per capita year-end investment in fixed assets within the circulation industry, and the turnover of commodity markets exceeding CNY 100 million.

Structure of the circulation Industry. The circulation industry exerts a pivotal and foundational influence, whether through the direct impact of various sectors on Gross National Product (GNP) or the indirect contribution stemming from continually expanding investments. Its structure offers insights into the relative contributions of each sector to GNP and their inherent interconnections. This study employs three sub-indicators to delineate the structure of the circulation industry, namely: the proportion of urban employment within the circulation industry relative to total urban employment, the proportion of the circulation industry’s added value to GDP, and the proportion of the circulation industry’s added value to the total added value of the tertiary industry. These indicators serve as proxies for assessing the circulation industry’s structure.

Efficiency of the Circulation Industry. The efficiency of the circulation industry stands as a crucial driver of its developmental trajectory. Whether the circulation industry can foster high-quality economic development, promote industrial structural optimization, and facilitate national infrastructure construction largely hinges on its efficiency. This study employs three sub-indicators—namely, the cost-profit margin of the wholesale and retail industry, the inventory rate of the wholesale and retail sector, and the turnover rate of wholesale and retail—as proxies for assessing the efficiency of the circulation industry.

Infrastructure of the Circulation Industry. Serving as a vital nexus in the societal reproduction process, the circulation industry fulfills dual roles: gathering terminal consumption data and guiding upstream investment and production. It acts as the primary transmission hub for both information and commodities. The facilities of the circulation industry, including transport hubs, commodity trading markets, and logistics infrastructure, constitute essential guarantees and prerequisites for its development. This study employs five sub-indicators—namely, the number of legal-person enterprises, the number of commodity trading markets with transactions exceeding CNY 100 million, the quality of highways, road network density, and the average distance of railway freight transport—to gauge the facilities of the circulation industry.

Drawing inspiration from the approach of Wang Yue, Wang Wei, and Cao Yidan, this study employs the entropy method to evaluate the developmental status of China’s provincial-level circulation industry across four dimensions: scale, structure, efficiency, and facilities [31]. To mitigate the influence of index scale, the raw data are initially standardized during the measurement process. Given that the selected indices encompass both enabling and constraining factors, this study delineates between them during data standardization, ensuring consistency and comparability across various indices. This approach lays a robust data foundation for subsequent empirical analyses.

(3)

Control variables:

Drawing on the current literature [32,33,34], this study selects the following control variables: (1) Urbanization Rate (UR), reflecting the proportion of urban residents to the total population of the province, to explore its potential impact pathways on carbon emissions, including changes in population structure, social structure, economic structure, and spatial structure; (2) Level of Human Capital (Labor), represented by the proportion of students enrolled in regular higher education institutions to the total population of the province, to assess its potential contribution to energy conservation and emission reduction; (3) Foreign direct investment (FDI), measured by the ratio of total exports to GDP, to analyze its role in promoting the export of green and low-carbon products and reducing energy consumption and carbon emissions; (4) Degree of Government Intervention (GOV), represented by the proportion of local government expenditure to regional GDP, considering its role in environmental protection policies and energy conservation and emission reduction actions; (5) Level of Economic Development (lnagdp), by using the natural logarithm of per capita GDP, to investigate the relationship between economic scale and carbon emissions.

(4)

Mediating variables:

Based on the theoretical analysis in the preceding sections, this study constructs intermediate variables at the output and consumption ends. At the production end, we select the following intermediate variables: Output Scale (OS), measured by regional gross domestic product; Industrial Structure (IS), represented by the ratio of the value added of the secondary industry to the value added of the tertiary industry; Technological Advancement (TA), assessed using the number of patents granted per ten thousand people in the region. At the consumption end, drawing on the method of Liu Zilan and Yao Jian, we use the proportion of expenditures on cultural education and entertainment, medical care and health, and transportation and communication to total household expenditures as indicators of consumption structure upgrading [35]. Specifically, Urban Residents’ Consumption Structure Upgrading (UC) is quantified by the ratio of per capita expenditures on the three categories mentioned above to the total per capita expenditures of urban residents; Rural Residents’ Consumption Structure Upgrading (RC) is calculated by the ratio of per capita expenditures on the three categories mentioned above to the total per capita expenditures of rural residents. Such design of intermediate variables helps to reveal the pathways through which the circulation industry affects regional carbon emissions, providing new perspectives and empirical evidence for the study of the relationship between the circulation industry and carbon emissions.

3.3. Data Description and Statistical Characteristics

In this study, we selected 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) as research samples spanning from 2011 to 2020. The primary data utilized in this research are sourced from the China Statistical Yearbook, China High Technology Industry Statistical Yearbook, China Science and Technology Statistical Yearbook, and the EPS (Economic Forecasting System) database. To address missing values in the dataset, interpolation and average growth rate methods were employed for imputation. The specific names and descriptive statistical characteristics of the relevant variables are outlined in

Table 2. Variable name and statistical characteristics.

Variable Name	Code	Observations	Mean	Standard	Min	Max
Carbon emission intensity	CRE	300	2.3497	1.7376	0.1697	8.2880
Development level of the circulation industry	LCD	300	0.2143	0.1040	0.0682	0.6068
Urbanization rate	UR	300	0.5835	0.1253	0.3381	0.8960
Level of economic development	lnagdp	300	12,612.81	7900.19	4756.41	47,118.4
Human capital scale	Labor	300	0.0197	0.0054	0.0079	0.0412
Degree of openness	FDI	300	0.2713	0.3065	0.0076	1.5482
Degree of government intervention	GOV	300	0.2475	0.1030	0.1058	0.6430
Output scale	$\ln OS$	300	9.8383	0.8483	7.4208	11.4882
Industrial structure	IS	300	0.8632	0.0527	0.7728	1.0423
Technological progress	TA	300	1.8993	1.0461	−0.1512	4.3092
Consumption structure of urban residents	UC	300	−1.1298	0.0924	−1.3931	−0.8888
Consumption structure of rural residents	RC	300	−1.1624	0.1799	−1.6695	−0.8003

Source: Calculated by the author on the basis of relevant data.

.

4. An Empirical Test of the Carbon Emission Reduction Effect in China’s Trade and Circulation Industry

4.1. Benchmark Regression

To investigate the influence of the circulation industry’s development on carbon emission intensity, this study initially employs the Hausman test to select the most appropriate econometric model. The test outcome (p-value = 0.001) rejects the null hypothesis of the random effects model at the 1% significance level, indicating the fixed effects model as the superior choice for this analysis. After controlling for other potential influencing factors, along with time and area fixed effects, the fixed effect model is utilized for parameter estimation, and the ensuing results are delineated in

Table 3. Baseline regression results.

Variable	(1) CRE	(2) CRE	(3) CRE	(4) CRE
	PLOS	IFE	TFE	FE
LCD	−18.698 ***	−2.921 ***	−1.757 *	−1.571 *
	(−11.88)	(−3.34)	(−1.93)	(−1.76)
UR	10.248 ***	−4.769 ***	−1.212	−3.022
	(6.43)	(−4.51)	(−0.69)	(−1.70)
lnagdp	0.000 ***	−0.000 ***	−0.000 ***	−0.000 ***
	(5.25)	(−3.84)	(−2.90)	(−3.91)
Labor	−174.67 ***	−44.411 **	−79.116 ***	−85.559 ***
	(−9.00)	(−2.37)	(−3.94)	(−4.20)
FDI	−3.804 ***	−0.137	−0.127	−0.213
	(−7.92)	(−0.41)	(−0.31)	(−0.48)
GOV	−2.347 ***	1.909 *	3.403 ***	2.492 **
	(−2.34)	(2.04)	(3.73)	(2.55)
Time	No	No	Yes	Yes
Region	No	Yes	No	Yes
_cons	3.487 ***	10.968 ***	5.408 ***	10.124 ***
	(5.98)	(9.92)	(6.67)	(6.98)
N	300	300	300	300
r2	0.476	0.613	0.666	0.6742

Note: ***, **, * are significant at the level of 1%, 5%, and 10%, respectively.

. Specifically, column (1) presents the regression outcomes of the mixed OLS model, while columns (2) and (3) introduce control variables for area and time effects, respectively. Subsequently, the estimation findings from column (4) are comprehensively examined and discussed in this paper.

The results exhibit a significant and consistently negative estimated coefficient for the primary explanatory variable, the level of circulation development (LCD), across all models (coefficient = −1.571). This suggests that a 1% rise in the circulation industry level diminishes carbon emission intensity by 1.571 units, underscoring the pivotal role of the circulation sector in enhancing resource allocation efficiency and fostering the transition toward a low-carbon economic paradigm. Consequently, within the context of pursuing global objectives such as “peak carbon” and “carbon neutrality”, proactive circulation industry development emerges as an effective avenue to attain high-quality economic advancement. Moreover, it reaffirms that optimizing the economic structure, particularly modernizing the circulation sector, is imperative for realizing sustainable development in tandem with environmental and economic harmony.

Regarding the analysis of control variables, it is revealed that the economic growth level and human capital accumulation exert a substantial mitigating influence on carbon emission intensity. This indicates that as economic growth quality and efficiency elevate, energy consumption structures may undergo optimization, thereby contributing to decreased carbon emissions per economic unit. Furthermore, human capital expansion implies heightened education levels and skills, often associated with enhanced environmental consciousness and green technology adoption, hence leading to reduced carbon emissions. Conversely, the escalating degree of government intervention exhibits a positive correlation with carbon emission intensity, possibly signaling that excessive or inappropriate intervention could lead to resource misallocation, energy inefficiency, and consequently, heightened carbon emissions. This observation underscores the necessity for policymakers to strike a balance between intervention and market mechanisms to avert policy-induced uneconomical and environmentally unfriendly production patterns.

Additionally, urbanization and economic openness demonstrate no statistically significant effect on carbon emission intensity, underscoring the nuanced role of these factors. Urbanization may enhance energy utilization efficiency through agglomeration effects, yet it might also escalate energy consumption due to urban expansion. Similarly, economic openness could enhance environmental conditions via technology transfer and cleaner energy adoption, albeit it may exacerbate national environmental burdens owing to the “polluter’s paradise” effect of international trade. Thus, these outcomes advocate for nuanced assessments when interpreting the environmental ramifications of urbanization and economic openness.

4.2. Robustness and Endogeneity Tests

(1)

Robustness Tests

Economic phenomena are often influenced by various factors, and if the model is highly sensitive to small changes in certain assumptions or data, the reliability of the model results is compromised. Therefore, to ensure the robustness of the benchmark results presented above, this study conducts a robustness test using three methods, with the outcomes displayed in

Table 4. Robustness and endogeneity tests.

Variable	Robustness Test				Endogeneity Test
	$\left(1\right)\mathbf{ln}\mathit{C}\mathit{R}\mathit{E}$	(2) CRE	(3) CRE	(4) PCEE	(5) CRE	(6) CRE	(7) CRE
	Take Logarithm	2% Tail Reduction			5% Tail Reduction	Replace the Explained Variable	Lag Core Explanatory Variables
L.LCD					−2.676 **
					−2.25
LCD	−0.857 ***	−1.614 *	−1.889 **	−35.084 ***			−6.113 *
	(−4.00)	(−1.88)	(−2.31)	(−5.40)			(−1.71)
IV						0.043 **
						(3.04)
Control variable	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Time	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Region	Yes	Yes	Yes	Yes	Yes	Yes	Yes
_cons	2.049 ***	7.184 ***	6.922 ***	−6.484	7.629 ***	−0.378 *	10.343 ***
	(10.01)	(8.79)	(8.87)	(−1.04)	(7.65)	(−1.99)	(6.51)
N	300	300	300	200	300	300	300
r2	0.809	0.690	0.697	0.368	0.607	0.948	0.973

Note: ***, **, * are significant at the level of 1%, 5%, and 10%, respectively.

, columns (1) to (4).

Firstly, the explanatory variables are transformed into logarithmic form. To address data heteroskedasticity without altering the fundamental nature and relevance of the data, this paper takes the logarithm of carbon emission intensity and the circulation industry’s development for re-estimation using fixed effects. As shown in column (1), the regression coefficient is −0.857, passing the 1% significance test. Secondly, a trimming approach is applied to address extreme values’ adverse impact on results. Specifically, carbon emission intensity, as the explanatory variable, undergoes 2% and 5% tail shrinking treatments, respectively. As illustrated in columns (2) and (3), both treatments yield negative regression coefficients at significant levels. Thirdly, substitution variables are introduced. Per capita carbon emissions (PCCE) is a pivotal indicator for assessing carbon emission levels, reflecting efficiency and equity in economic development processes. Hence, per capita carbon emissions are selected as a proxy indicator for carbon emission intensity, and regression analysis is conducted accordingly. The results in Column (4) reveal that after incorporating control variables and adjusting for time and regional effects, the coefficient indicating the influence of the circulation industry’s development on per capita carbon emissions is negative at the 1% significance level. This suggests that the circulation industry’s development continues to exert a significant effect on reducing carbon emissions even when explanatory variables are substituted.

In conclusion, the significance and direction of the impact of the circulation industry’s development on carbon emission intensity remain consistent across the robustness tests conducted above. This indicates that the baseline regression results of this study are robust, underscoring the pivotal role of the circulation industry’s development in attenuating carbon emission intensity.

(2)

Endogeneity test

In addressing the endogeneity issue arising from potential bidirectional causality or omitted variables between the circulation industry and carbon emission reduction, this study employs the instrumental variable method along with lagged core explanatory variables treatment. Firstly, to mitigate the endogeneity problem resulting from potential reverse causality, adjustments are made to the core explanatory variables. Specifically, lagged periods of circulation industry development and carbon emission intensity are incorporated for re-estimation using fixed effects. As shown in column (1) of Table 4, the coefficient of the circulation industry’s development remains negative and passes the 5% significance test, consistent with benchmark regression results.

Secondly, this study utilizes freight volume as an instrumental variable (IV) for the circulation industry’s development and applies the Two Stage Least Square (2SLS) method for regression. Freight volume is chosen as the instrumental variable due to its significant impact on the circulation industry’s development and its lack of direct association with carbon emissions, satisfying both the correlation and exclusivity requirements of instrumental variables. Columns (5) to (7) of Table 4 present the results of the endogeneity test based on the instrumental variable method. It is evident that the effect of the circulation industry’s development on carbon emissions is significantly negative at the 10% level, indicating that the circulation industry’s development contributes to carbon emission reduction and facilitates energy conservation and emission reduction efforts.

4.3. Heterogeneity Test

(1)

Heterogeneity test based on different quartiles of carbon emission intensity

Quantile regression offers unique advantages in elucidating the heterogeneity effects among economic variables. Unlike traditional regression analysis, which primarily focuses on average effects, quantile regression delves deeper into the impact of explanatory variables across different conditional probability circulations, specifically different quartiles. This method unveils a comprehensive view of how explanatory variables influence dependent variables [36]. Particularly noteworthy is its ability to offer richer and more nuanced insights when data fail to meet the standard assumptions of ordinary least squares (OLS) regression. Adopting this approach, our study meticulously assesses the impact of carbon emission intensity across various quantiles (0.25, 0.5, and 0.75 quantiles). The detailed estimation results are presented in

Table 5. Quantile regression.

Variable	(1)	(2)	(3)
	CRE_0.25	CRE_0.5	CRE_0.75
LCD	−3.406 **	−8.437 ***	−14.578 ***
	(−2.26)	(−2.90)	(−3.96)
Control variable	Yes	Yes	Yes
Time	Yes	Yes	Yes
Region	Yes	Yes	Yes
_cons	0.925	1.595	2.007
	(1.59)	(1.42)	(1.41)
N	300	300	300

Note: ***, ** are significant at the level of 1% and 5%, respectively.

.

The regression analysis reveals a significant and negative correlation between the development of the circulation industry and carbon emission intensity across all quartiles. Moreover, this negative correlation becomes more pronounced as carbon emission intensity increases. Specifically, at the 25th percentile, a 1% increase in the circulation industry’s development leads to a reduction in carbon emission intensity by 3.406 units. Similarly, at the 50th and 75th percentiles, the corresponding reductions are 8.437 and 14.578 units, respectively. These findings suggest that a logistics and circulation system with a higher level of development holds greater potential for reducing carbon emissions in regions with higher emission levels.

Furthermore, the differentiation in quantiles highlights significant variations in the role of circulation development in environmental management across regions with different carbon emission levels. In regions characterized by lower carbon emission quartiles, the circulation industry’s structure may already be more optimized, resulting in limited additional emission reduction benefits from its enhancement. Conversely, in regions with higher carbon emissions, the enhancement of the circulation industry not only presents greater potential for emission reduction but also underscores the higher policy importance and urgency of increasing the modernization of the circulation industry in these areas.

(2)

Based on the test of heterogeneity of different regions

China’s regional economic development exhibits significant disparities, raising questions about whether regional heterogeneity influences the impact of the circulation industry’s development on carbon intensity. To address this issue, this study divides the sample provinces into eastern, central, and western regions and conducts separate regression estimations to evaluate the heterogeneous effects of the circulation industry’s development on carbon emission intensity across different regions. The regression results are presented in

Table 6. Based on the heterogeneity analysis of the eastern, central, and western regions.

Variable	(1) CRE	(2) CRE	(3) CRE
	Eastern	Central	Western
LCD	−0.055 **	−10.158 ***	0.520
	(−0.06)	(−4.76)	(0.21)
Control variable	Yes	Yes	Yes
Time	Yes	Yes	Yes
Region	Yes	Yes	Yes
_cons	8.170 ***	3.163	13.466 ***
	(7.47)	(1.56)	(4.28)
N	109	101	90
r2	0.793	0.817	0.743

Note: ***, ** are significant at the level of 1% and 5%, respectively.

.

Empirical findings reveal significantly negative coefficients for the influence of both the eastern and central regions on carbon emission intensity, indicating that the circulation industry’s development in these regions has tangible effects on reducing carbon emissions. Furthermore, the absolute value of the impact coefficient for the central region (−10.158) surpasses that of the eastern region (−0.055), underscoring regional heterogeneity in the impact of the circulation industry’s development on carbon emission intensity, with a more pronounced effect observed in the central region. However, column (3) indicates that the western region’s impact on carbon emission intensity is not statistically significant.

The regional disparities in the circulation industry’s role in reducing carbon emission intensity may stem from variations in economic development levels, industrial structures, and technological advancements across regions. Compared to the eastern region, the central region may offer greater opportunities for upgrading and reform, enabling more tangible emission reduction effects resulting from circulation industry enhancements. Conversely, the eastern region, being more economically developed, may already possess a mature and efficient circulation industry, thereby yielding less noticeable marginal emission reduction effects compared to the central region. Additionally, the lack of a significant impact in the western region could be attributed to its relatively underdeveloped economic and technological conditions, limiting the strength of the impact of the circulation industry’s development on carbon emissions. Alternatively, the region’s industrial structure may not sufficiently support significant emission reduction effects compared to the circulation industry’s development.

4.4. Tests of Mediating Effects

(1)

Based on the intermediary effect test of the production side

Based on the preceding results indicating a discernible impact of the circulation industry’s development on carbon emission reduction, this study delves deeper to investigate whether scale, structure, and technological advancements mediate the relationship between the circulation industry’s development and carbon emission reduction. The findings regarding the mediating effects of output scale, industrial structure, and technological progress are presented in

Table 7. Estimation results of the mediating effect based on the production end.

Explained Variable	LnOS (1)	IS (2)	TA (3)	CRE (4)
LCD	0.037 ***	0.049 **	1.093 *	−6.003 ***
	(6.05)	(2.02)	(1.82)	(−3.52)
LnOS				−0.900 ***
				(−4.88)
IS				−1.219 *
				(−1.94)
TA				−0.193 *
				(−1.73)
Control variable	Yes	Yes	Yes	Yes
Time	Yes	Yes	Yes	Yes
Region	Yes	Yes	Yes	Yes
_cons	−0.299 ***	0.077	0.085 ***	14.434 ***
	(−4.15)	(1.21)	(3.28)	(5.20)
N	300	300	300	300
r2	0.361	0.800	0.786	0.400

Note: ***, **, * are significant at the level of 1%, 5%, and 10%, respectively.

.

In columns (1) to (3) of Table 7, we introduce output scale (lnOS), industrial structure (IS), and technological progress (TA) as mediating variables into the model for estimation. The results indicate that the development of the circulation industry positively influences carbon emission reduction through the expansion of output scale, optimization of industrial structure, and promotion of technological progress. Among these, the scale effect demonstrates the most pronounced impact on driving the circulation industry’s development. Additionally, the findings presented in column (4) demonstrate that when output scale, industrial structure, and technological progress are simultaneously incorporated into the model, all three, in conjunction with the circulation industry’s development, significantly reduce carbon emission intensity. This underscores the multifaceted role of the circulation industry in facilitating carbon emission reduction. In conclusion, this study suggests that advancing the modernization of the circulation industry at a macro level not only directly decreases carbon emission intensity but also fosters the transition to a low-carbon economy by influencing various pivotal intermediary pathways of economic growth. These insights offer policy guidance for implementing China’s “dual-carbon” strategy and underscore the broad economic and societal benefits of strengthening the circulation system to mitigate carbon emissions.

(2)

Based on the mediation effect test of the consumption side

To examine whether the transition in urban or rural residents’ consumption patterns serves as a mediating mechanism in the circulation industry’s impact on carbon emission reduction, this study conducts regression analysis using Equations (2) to (9), with results presented in

Table 8. Estimation results of the mediating effect based on the consumption end.

Explained Variable	UC (1)	RC (2)	CRE (3)
LCD	−0.313 ***	0.171 **	−7.680 ***
	(−3.02)	(2.38)	(−4.74)
UC			18.263 ***
			(5.21)
RC			−3.890 *
			(−1.66)
Control variable	Yes	Yes	Yes
Time	Yes	Yes	Yes
Region	Yes	Yes	Yes
_cons	0.284 ***	0.094 ***	−2.419 **
	(7.05)	(3.71)	(−2.21)
N	300	300	300
r2	0.803	0.785	0.422

Note: ***, **, * are significant at the level of 1%, 5%, and 10%, respectively.

.

In Table 8, column (1) demonstrates negative estimated coefficients for the circulation industry, while column (2) exhibits positive ones. These findings suggest that the circulation industry’s development restrains urban residents’ consumption structure but optimizes that of rural residents to some extent. This could be attributed to China’s dual urban-rural structure, wherein the circulation industry also exhibits a dual nature. Lagging rural circulation infrastructure impedes the spread of durable consumer goods in rural areas, creating a paradox between the increasing demand for improved rural living standards and inadequate circulation infrastructure. Consequently, enhancing the circulation industry’s development, improving rural circulation infrastructure, reducing transport costs for rural consumer goods, and integrating circulation with the internet can enrich rural residents’ consumption choices, thereby promoting rural consumption. Moreover, urban areas benefit from increased employment opportunities and enhanced life security due to the circulation industry’s development, attracting population influx into more developed regions. However, limited land resources elevate living costs, with soaring property prices burdening residents, inhibiting urban consumption upgrades and diverting spending from other areas.

Column (3) presents regression outcomes of the mediating variable, urban or rural residents’ consumption structure, alongside core explanatory variables on carbon emission intensity. Notably, the regression coefficient for rural residents’ consumption structure is negative, while that for urban residents’ consumption structure is positive. Under the influence of both urban and rural residents’ consumption structures, the estimated coefficient for the circulation industry’s development is significantly negative at the 1% level. This amalgamation suggests that upgrading rural consumption structures may exacerbate carbon emission intensity to some extent, while upgrading urban consumption structures may also heighten carbon emission levels. Importantly, the consumption structures of rural or urban residents play pivotal intermediary roles in the circulation industry’s influence on carbon emissions.

5. Research Findings, Policy Implications, and Research Outlook

5.1. Research Findings

The establishment and development of the circulation system hold immense importance in enhancing the operational mechanisms of the domestic market, aligning with China’s objectives of achieving “carbon peak, carbon neutrality”, and fostering green and low-carbon economic growth. As the pivotal link between production and consumption, the circulation industry stands as a cornerstone of the national economy. Thus, leveraging panel data from 30 provincial panels spanning 2011 to 2020, excluding Tibet, Hong Kong, Macao, and Taiwan, this study delves into the mechanisms and pathways through which the circulation industry impacts carbon emissions, encompassing both the “production side” and “consumption side” of the social reproduction process. By concurrently integrating the “production side” and “consumption side” of the social reproduction process into the analytical framework, the study illuminates the nuanced interplay between the circulation industry and carbon emissions. The results show that: (1) The development of the circulation industry helps to curb carbon emission intensity, and the effect will show the same heterogeneity characteristics with the continuous increase of quantiles, which shows that the provinces with high carbon emission intensity are significantly better than the provinces with low carbon emission intensity, alleviating the phenomenon of regional carbon emission imbalance. (2) There is regional heterogeneity in the impact of the circulation industry’s development on carbon emission intensity, showing that the central region is stronger than the eastern region, but the western region has no significant impact on carbon emission intensity. (3) The mediating effect test on the production side shows that the circulation industry can reduce carbon emissions through the output scale effect, structural effect and technical effect, and the promotion effect of output scale on carbon emission reduction is more significant than that of industrial structure and technological progress. On the consumption side, the mediating effect of the upgrading of rural residents ‘consumption structure is carbon emission reduction effect, and the mediating effect of the upgrading of urban residents’ consumption structure is carbon emission increase effect.

5.2. Policy Implications

Firstly, efforts should be directed towards actively expanding the depth and breadth of the circulation industry’s development to facilitate industrial scale expansion, technological progress, and structural transformation. This expansion should be instrumental in promoting industrial economies of scale, fostering green technological advancements, and driving digital transformation to mitigate carbon emissions in production and operational processes. Specifically, we should promote the deep integration of multiple industries, innovate and develop new formats and new models with each passing day, effectively promote the operation efficiency of the circulation industry, and boost the industrial scale to obtain economies of scale; through the digital technology contained in the circulation industry, it can significantly promote the digitization of the circulation industry, shorten the R & D cycle for circulation enterprises, provide excess returns, strengthen the market competitiveness of enterprises, and promote the development and upgrading of the whole cycle; continue to develop green technology and apply it to practice, continue to develop clean energy and invest in the circulation industry, gradually transform and enhance traditional industries with high energy consumption, high emissions, and low efficiency, eliminate old and high energy consumption production methods and management methods, and strengthen carbon emission reduction effects.

Secondly, tailored development strategies should be formulated to support the attainment of the “dual-carbon” goal. Provinces should refrain from adopting a one-size-fits-all approach to carbon emission reduction policies. Instead, strategies should be tailored based on central policy guidance and local circulation industry characteristics to provide applicable and implementable policy support. For provinces with high carbon emissions in the circulation industry, circulation enterprises should make full use of existing resources, increase their emphasis on improving quality and efficiency, accelerate the replacement of high-pollution production equipment, upgrade production processes, promote the green development of the circulation industry, significantly reduce carbon emissions, and achieve the goal of ‘carbon neutrality’. In the provinces with low-carbon emissions in circulation industry, circulation enterprises can expand their business scale as soon as possible on the basis of green development, increase the income of circulation businesses, and increase investment in research and development and the application of low-carbon technology in circulation, so as to contribute to the goal of ‘carbon neutrality’.

Thirdly, it is imperative to enhance laws and regulations governing the circulation industry to support carbon emission reduction efforts effectively. As traditional laws governing logistics have become outdated and inadequate to meet the evolving needs of the industry, there is a pressing need to revise and supplement existing laws to accommodate emerging industry trends. Addressing regional economic disparities, the introduction of relevant laws and regulations at the right time is crucial to provide institutional guarantees for coordinated regional economic development. China’s regional differences in carbon emissions are actually one of the manifestations of uncoordinated regional economic development in China. Although the state has put forward a series of regional development strategies such as the development of the western region, the revitalization of the old industrial base in the northeast region, and the promotion of the rise of the central region, there is no basic law to guide and guarantee the coordinated development of the region. Although the policy also has a guiding role, its implementation effect is greatly reduced due to operational difficulties. The state should introduce relevant laws and regulations at the right time to provide institutional guarantees for coordinating regional economic development.

Lastly, through the circulation industry, residents, especially rural residents, can upgrade their consumption structure and curb carbon emissions caused by consumption. With the help of the circulation industry to release the consumption potential and the advantages of online and offline organic integration, it provides rural consumers with training on the use of online trading platforms. At the same time, it builds convenient and safe payment methods, smooths urban and rural trading channels, reduces the proportion of offline consumption, expands the depth and breadth of online consumption, promotes the upgrading and optimization of consumption structure, and inhibits carbon emissions. Improve the infrastructure of the rural circulation industry, provide customized platform services for the special needs of the rural market, such as agricultural product information release, logistics circulation, and other services, in order to meet the consumption needs of urban and rural areas, increase the penetration of digital knowledge and technology into the field of rural residents’ consumption, enhance the application ability of digital technology and e-commerce, and shape healthy, low-carbon, and efficient consumption patterns and lifestyles.

5.3. Research Outlook

The primary contribution of this study lies in its construction of a comprehensive analytical framework that examines the intricate relationship between the circulation industry and carbon emissions. This framework not only uncovers the underlying mechanisms through which the circulation industry influences carbon emissions at both the production and consumption ends but also delves into its regional heterogeneity. As a result, it provides a novel theoretical foundation and empirical evidence essential for informing global carbon emission reduction strategies. Nonetheless, it is acknowledged that the current study is limited in scope, relying solely on data from 30 provinces within China, excluding Tibet, Hong Kong, Macao, and Taiwan. This limitation may potentially impact the comprehensiveness of the findings. To address this, future research endeavors should attempt to expand their scope, encompassing data from a broader array of countries and regions. Such an expansion would enable a more rigorous verification of the circulation industry’s impact on carbon emissions and facilitate the exploration of heterogeneous effects across diverse national contexts, thereby enriching both theoretical and empirical understanding in this critical area.