
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12658-8
10.1016/j.heliyon.2024.e36627
e36627
Research Article
A study on the relationship between high-quality development of the logistics industry and rural revitalization across different levels of industrial structure
Yan Borui a
Yao Bo a
Wang Yamin wangyamin_csnu@163.com
b⁎
a School of Economics and Management, Xianyang Normal University, Xianyang, China
b School of Primary Education, Changsha Normal University, Changsha, 410100, Hunan, China
⁎ Corresponding author. wangyamin_csnu@163.com
22 8 2024
15 9 2024
22 8 2024
10 17 e3662726 1 2024
2 8 2024
20 8 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Due to regional differences in industrial structure levels, the development of the logistics industry in rural areas faces various challenges and opportunities. The objective is to explore how the high-quality development of the logistics industry influences rural revitalization at various tiers of industrial structure. It employs a benchmark regression model to dissect the influence that the logistics industry's high-quality development exerts on fostering rural revitalization. Moreover, a panel threshold model is employed to examines this impact across different levels of industrial structure. It demonstrates that enhancing the logistics industry significantly supports rural revitalization, with its impact varying across different levels of industrial structure. Hence, it is imperative to develop customized strategies for the logistics industry that account for the varying industrial structure in rural areas. It emphasizes the logistics industry's role in facilitating rural growth and recommends adopting tailored development strategies corresponding to the industrial structure's evolution to boost rural revitalization. Despite valuable insights, this study has limitations in reflecting regional trends and exploring other factors beyond the direct impact of logistics on rural revitalization, pointing to potential avenues for future research.

Keywords

Industrial structure
Rural revitalization
High-quality development of the logistics industry
Threshold effect
==== Body
pmc1 Introduction

As an important strategy of the Chinese government in recent years, rural revitalization aims to achieve its grand goal through strategies like boosting the rural economy, increasing farmers' incomes, and improving rural infrastructure. Within this framework the logistics industry, serving as a crucial link between producers and consumers is evident [1]. It serves an indispensable function in fostering rural industrial growth and enhancing the marketing of agricultural commodities [2]. Nevertheless, due to regional differences in industrial structure levels, across regions, the connection between the logistics industry and rural revitalization development differs [3]. It explores the intrinsic link between the logistics industry and rural revitalization development from the perspective of industrial structure levels.

Currently, China is experiencing a pivotal period of economic growth, marked by ongoing adjustments to its industrial framework and economic modalities. As the urban economy rapidly advances, many traditional industries are gradually shifting to rural regions, leading to an imbalanced development between urban and rural areas, and it has widened the chasm between urban-centered economies and rural economies, resulting in significant differences in industrial structures [4]. In urban regions, the service and high-tech industries are continuously growing, forming a modern industrial system centered around knowledge and technology. However, in rural areas, traditional agriculture remains dominant, and rural infrastructure and public services are relatively weak [2,3]. This imbalance in industrial structure significantly impact rural economic growth and the enhancement of living standards for rural residents [4]. It is precisely because of this imbalanced industrial structure that the logistics industry is vital for rural revitalization. Agriculture serves as the foundation, and agricultural products are cornerstone of the local economy. However, the efficient distribution of these products heavily relies on the support of the logistics industry [5]. In countryside regions, the logistics industry serves as a bridge between farmers and the market. facilitating the swift transport of agricultural products from rural areas to the market through processes such as transportation, warehousing and distribution, thereby meeting the demands of urban residents [1]. Simultaneously, the logistics industry also drives the development of related service sectors, such as packaging, processing, and agricultural product sales, forming an industry chain centered around logistics and creating more employment opportunities for rural areas.

Simultaneously, due to the limitations of the industrial framework in countryside regions, the logistics industry faces some difficulties and challenges in rural revitalization. Firstly, because rural areas are primarily dominated by small-scale agricultural economies, the logistics industry's development is constrained by limited funds and technology. It remains in a rudimentary stage, with relatively simple transportation and warehousing facilities that need efficiency improvements [6]. Secondly, poor transportation conditions in rural areas, such as narrow roads and traffic congestion, impedes the logistics industry's advancement. Thirdly, the limited market demand in rural areas poses a challenge of limited market scale for the logistics industry, making it difficult for enterprises to achieve economies of scale [7]. The rural revitalization strategy presents substantial opportunities for the logistics industry, as the government endeavors to bolster rural economic growth and increased support for the logistics industry. It has also accelerated the construction of rural infrastructure, leading to improvements in transportation and logistics facilities, fostering more conducive environments for the logistics industry's growth [8,9]. Additionally, with the widespread adoption of internet technology and the promotion of logistics informatization, logistics companies can leverage advanced technologies to improve logistics efficiency, reduce costs, expand their market coverage, and achieve better development.

Evidently, the integration of the logistics industry with rural revitalization is apparent, showcasing its pivotal role as a catalyst for the enhancement of rural industries, integral to fostering rural economic growth and boosting farmers' income [10]. Nonetheless, existing research has relatively underexplored the adaptability and reciprocal dynamics between the high-quality development of the logistics industry and the industrial structure. Furthermore, there exists a lack of comprehensive exploration regarding how the logistics industry promotes the development of rural revitalization strategies under different industrial structures. Under varying industrial structures, the logistics industry confronts varied challenges and avenues for growth. It is imperative to delve into further research on crafting specific development strategies tailored to different industrial structures, which constitutes the primary emphasis of this paper.

Commencing with a quantification of the logistics industry's high-quality development and the development of rural revitalization, it delves into the influence of the former on the latter. It conducts an analysis based on different industrial structure thresholds. By examining how the logistics industry's high-quality development correlates with rural revitalization, coupled with empirical analyses across diverse industrial structure development, it endeavors to offer strategic recommendations for the logistics industry's advancement amidst rural revitalization initiatives. The subsequent sections are as follows: Part 2 covers relevant literature and hypotheses, Part 3 introduces the research methodology, Part 4 discusses research findings, Part 5 provides the discussion, and the conclusion rounds off the paper.

2 Literature review and hypothesis

2.1 Industrial structure and the high-quality development of the logistics industry

The logistics industry refers to the process of transporting products from the production site to the consumption site, involving various aspects such as transportation, warehousing, packaging, distribution, and information management. It holds a pivotal position in ensuring the smooth functioning of the supply chain and product distribution, enhancing the efficiency of product circulation, reducing costs, improving service quality, fostering market integration and optimal resource allocation. Furthermore, the logistics industry is deemed an essential element within the industrial structure. Its development is intricately linked to a country's economic growth, trade liberalization, and technological advancement [11,12]. It is acknowledged as a key part of regional economic development [13]. The high-quality development of the logistics industry involves optimizing the industrial structure, improving the standards of logistics services, and promoting sustainable development. It can enhance a country's competitiveness and accelerate its economic growth. As the industrial structure transitions from traditional industries to modern industries, the logistics industry also undergoes continuous optimization and upgrading. The swift advancement of the service industry and high-tech industries imposes higher demands on the logistics industry, such as timeliness, accuracy, and security.

2.2 Industrial structure and rural revitalization

Rural economies exhibit unique characteristics and challenges in different countries and regions. Typically, economic activities in rural areas are mainly concentrated in agricultural production and agro-processing sectors. Rural economic development faces a series of challenges, such as agricultural modernization, increasing farmers' income, upgrading rural industries, and raising the living standards of rural populations. To achieve sustainable development, the rural economy needs to explore new development paths and growth drivers [14]. Rural revitalization is a comprehensive process that involves improving living conditions, driving economic growth, and ensuring ecological sustainability [15]. The advancement of rural industries can elevate the income of rural populations and foster balanced development between urban and rural areas. A well-structured industrial structure can create employment opportunities and promote rural economic growth [4].

2.3 High-quality development of the logistics industry and rural revitalization

The logistics industry serves as a crucial intermediary in transforming production factors into goods and services. An efficient logistics system contributes to improved production efficiency and product quality, reduced logistics costs, and ultimately enhances the competitiveness and market share of rural products. A well-structured logistics industry can facilitate connections between rural areas and urban markets, reduce logistics costs, and improve supply chain efficiency [16]. Therefore, some studies have explored the role of the logistics industry in propelling rural economic growth. The logistics industry emerges as a vital enabler of rural economic advancement through enhancing the quality of agricultural products, reducing sales costs, and driving the development of other rural industries [17]. It also fosters rural industrial development, increases employment opportunities, and improves the living conditions of rural populations [10]. The logistics industry effectively promotes rural industrial development and increases farmers' incomes by enhancing the circulation efficiency of agricultural products, advancing e-commerce for agricultural products, facilitating the upgrading of rural industries, improving farmers' living conditions, and strengthening rural logistics infrastructure. In China, the government has recognized the significance of the logistics industry in advancing rural revitalization and has implemented numerous policies to enhance rural logistics infrastructure, including the establishment of rural logistics parks, promoting e-commerce in rural areas, and developing rural logistics service providers. These policies aim to elevate the standard of logistics services in rural regions, reduce logistics costs, and promote rural industrial development [18,19]. Additionally, fostering sustainable logistics practices contribute to enhancing the ecological environment in rural areas and promoting green development [[20], [21], [22]].

Drawing from the aforementioned, we propose the first hypothesis.H1 The high-quality development of the logistics industry has a positive impact on rural revitalization.

2.4 The influence of industrial structure on logistics industry and rural economic

At various stages of industrial development, the correlation between the high-quality of the logistics industry and rural revitalization exhibits unique characteristics. In scenarios with a comparatively lower industrial structure level, the logistics industry might encounter limitations. Nevertheless, as the industrial structure upgrades, the high-quality development of the logistics industry will provide stronger support for rural revitalization [20]. In areas where the industrial structure is more advanced, the connection between the high-quality development of the logistics industry and rural revitalization becomes more intimate, making the logistics industry a significant driving force for rural revitalization.(1) The Logistics Industry and Rural Economic Development in Agriculture-Dominated Economic Structures. In regions with an agriculture-dominated economic structure, where agricultural production takes the lead, the logistics industry plays a critical role in the transportation of agricultural products and market access. It facilitates the efficient circulation of agricultural products from the fields to the market, thus promoting their sales and achieving market value realization. Furthermore, the provision of logistics services can drive rural industrial upgrading. Through processing, packaging, and transportation, the logistics industry increases the value-added quotient of agricultural products, leading to higher incomes for farmers [23].

(2) The Logistics Industry and Rural Economic Development in Industry-Dominated Economic Structures. The logistics in regions with an industry-dominated economic structure, where industrial production takes the lead, it plays a crucial role in facilitating the transportation and market expansion endeavors of rural industrial products. It ensures the smooth transportation of rural industrial products and the unimpeded supply chain of raw materials and finished goods, thereby enhancing the market competitiveness of rural industrial products. Additionally, the construction of logistics infrastructure is significant for promoting rural industrial development and attracting investment. Logistics infrastructure includes roads, railways, ports, and warehousing facilities, and their construction and improvement can effectively reduce logistics costs, increase transportation efficiency, and it underscores the critical role of infrastructure investments in bolstering rural economic. Good logistics infrastructure can attract more investors and enterprises to rural areas, promoting the diversification and advancement of rural industries. Simultaneously, the construction of logistics infrastructure augments storage capabilities and optimizes the logistics environment for agricultural products, reducing losses and waste, while elevating product quality and bolstering market competitiveness [24].

(3) The Logistics Industry and Rural Economic Development in Service-Dominated Economic Structures. In regions dominated by the service industry in the economy, the logistics industry assumes a pivotal position in fostering the growth of rural services and logistics distribution. As rural residents' income levels escalate and the shift in consumption patterns, the rural service industry is rapidly emerging. The logistics industry can provide efficient distribution services for the rural service industry, ensuring timely delivery of goods and services to meet diverse demands of rural residents. Moreover, innovations in logistics technology provide new opportunities for rural industrial transformation and innovation. For instance, the rise of agricultural e-commerce and logistics platforms supports online sales of agricultural products and the digitization of rural industries [25].

It can be seen that rural revitalization and the development of the logistics industry are mutually reinforcing, and the logistics industry is intricately linked to rural economic development, showing diverse characteristics under different industrial structures. Adjustments in industrial structure significantly impact the high-quality development of the logistics industry, which subsequently assumes a pivotal role in driving rural revitalization. Conversely, the success of rural revitalization also relies on the support of logistics system and policy guidance. As industrial structure transitions from traditional agriculture to modern industry and services, the demand for logistics in rural areas continues to grow. This is especially true with the development of new industries like agricultural processing and rural e-commerce, which place higher demands on logistics services. There has also been a shift in demand structure from traditional agricultural product transportation to more diversified logistics services, including integrated services such as agricultural product processing, packaging, warehousing, and distribution. To meet the logistics demands brought by industrial structural transformation, rural areas need to upgrade their logistics facilities and enhance the level of logistics informatization. Simultaneously, the transformation of industrial structure is driving innovation in rural logistics service models, with diversification and personalization of logistics services emerging as new trends. Depending on the specific industry requirements, rural logistics need to provide more customized and specialized services, thereby catering to the diverse needs of a multifaceted clientele. Hence, conducting additional research on the collaborative development mechanism between the high-quality development of the logistics industry and rural revitalization under various industrial structures, along with the enactment of customized policies and initiatives, holds significant importance in promoting the high-quality development of the rural economy.

Based on these, we propose the second hypothesis.H2 The impact of the logistics industry's high-quality development on rural revitalization varies under different levels of industrial structure.

3 Methodology

3.1 Model design

3.1.1 Benchmark regression model

To assess the influence of the high-quality development of the logistics industry on rural revitalization, a panel model was constructed for empirical research. The detailed estimation model isas follow:(1) lnrri，t=α1+β1lnlhi,t+γ1Xi,t+μi+εi,t

Where, the dependent variable, denoted as "rr," indicates the level of rural revitalization. The core independent variable, denoted as "lh", indicates the level of high-quality development of the logistics industry across different regions. The control variables, represented by "X", include the regional economic development level ("re"), the income ratio of urban and rural residents ("ir"), and the level of infrastructure construction ("ic"). Within the model equation, "i" and "t" respectively represents the region and year, and μi captures the unobserved individual effects. εi,t represents the random error term, accounting for other factors and errors affecting rural revitalization development that are not explained by the model. Additionally, a logarithmic transformation is applied to the pertinent time series data to prevent significant data fluctuations and alleviate potential heteroskedasticity.

3.1.2 Panel threshold model

To further explore the potential nonlinear impact and threshold conditions of the high-quality development of the logistics industry on rural revitalization, we utilize Hansen's threshold regression model to formulate the threshold effect model. If there is only one threshold, the model can be represented as follow:(2) lnrri，t=α2+β2Ri,tI(Qi,t≤q)+δ2Ri,tI(Qi,t>q)+γ2Xi,t+μi+εi,t

Where, "R" stands as the threshold-dependent variable and core explanatory variable, indicating the logistics industry's high-quality development level. "I(·)" denotes the indicator function. "Q" serves as the threshold variable, representing the industrial structure level, while "q" is the corresponding threshold value. β2 represents the coefficient when Qi,t≤q. δ2 represents the coefficient when Qi,t>q. When β2≠δ2, it signals the existence of a threshold effect; otherwise, there is none. In the case of two thresholds, the model (2) is expanded into a double threshold model (3):(3) lnrri，t=α3+β3Ri,tI(Qi,t≤q1)+δ3Ri,tI(q1<Qi,t≤q2)+ρ3Ri,tI(Qi,t>q2)+γ3Xi,t+μi+εi,t

Where, "q1″ and "q2″ represent the two threshold values, with q1 < q2. These thresholds segment the sample into three intervals. The coefficients β3,δ3, and ρ3 respectively represent the impact of the core independent variable "R" on the dependent variable within each intervals. This method can be extended to a multi-threshold effect model if there are three or more thresholds.

3.2 Variable selection

3.2.1 Dependent variable

In this study, the dependent variable is rural revitalization (rr), a multidimensional concept encompassing the development and improvement of agriculture, rural regions, and farmers. Hence, multiple indicators are necessary to measure the extent of rural revitalization. The rural revitalization strategy encompasses the objectives and tasks related to "prosperous industries, livable environments, cultural enrichment, effective governance, and affluent living." It scientifically addresses how to achieve agricultural prosperity, rural growth and increased farmer income. Based on the content and theoretical significance of rural revitalization, following the approach of Xu Xue (2022) [26], the development level of rural revitalization is calculated from five dimensions: thriving industries, livable ecology, civilized rural customs, effective governance, and affluent living (Table 1). The entropy weight-TOPSIS method is used to compute both the comprehensive index and the individual subsystem indices, offering a holistic assessment of rural revitalization progress.Table 1 Comprehensive indicator framework for assessing rural revitalization level.

Table 1Primary Indicator	Secondary Indicator	Measurement Method	Nature	
Thriving Industries	Agricultural Labor Productivity	Agricultural total output/rural population	+	
Agricultural Mechanization Degree	Total agricultural machinery power	+	
Agricultural Development Level	Total grain output/rural population	+	
Rural Production Efficiency	Value-added of primary industry/Gross Regional Product	+	
Rural Industrial Investment	End-of-year actual area of productive buildings/rural population	+	
Natural Disaster Situation	Cropped area affected by disasters	–	
Livable Ecology	Renewable Energy Utilization	Solar water heaters' total quantity/rural population	+	
Chemical Inputs	Standardized application of fertilizers + Standardized use of pesticides in agriculture	–	
Village Greening Degree	Green coverage	+	
Rural Domestic Waste Management	(Transfer stations for domestic waste + Environmental sanitation vehicles and equipment)/rural population	+	
Rural Water Security	Rate of water usage	+	
Rural Toilet Hygiene	Public toilet quantity	+	
Civilized Rural Customs	Rural Traditional Virtues	Proportion of rural population by marital status relative to the total rural population	–	
Cultural and Entertainment Consumption Level	Average expenditure on cultural and entertainment activities per rural resident	+	
Educational Attainment of Farmers	Proportion of the rural population aged 15 and above who are illiterate	+	
Accessibility of Cultural and Entertainment Facilities	Number of comprehensive cultural stations per town/total number of towns	+	
Accessibility of Cultural and Entertainment Activities	Combined coverage rate of rural radio programs and TV programs	+	
Rural Ethos	Investment in the construction of public building in villages	+	
Effective Governance	Urban-Rural Income Gap	Rural per capita disposable income/urban per capita disposable income	+	
Urban-Rural Living Gap	Rural per capita consumption expenditure/urban per capita consumption expenditure	+	
Medical Standards	Number of village clinics + Number of rural doctors + Number of health personnel	+	
Rural Poverty Level	Number of rural residents receiving minimum living guarantee	–	
Rural Land Governance	Effective irrigated area	+	
Environmental and Sanitary Construction	Investment in environmental and sanitary construction	+	
Affluent Living	Rural Resident Income Level	Rural per capita net income	+	
Rural Resident Consumption Level	Social commodity rural retail sales	+	
Rural Resident Housing Standards	Average residential building area per capita	+	
Engel Coefficient	Rural residents' food expenditure/consumption expenditure	–	
Public Facilities Construction	Investment in public facilities construction	+	
Level of Common Prosperity	1 - Incidence rate of rural poverty	+	

3.2.2 Core independent variable

The core independent variable in this study is the high-quality development level of the logistics industry(lh). Utilizing key indicators from previous scholarly work, a comprehensive input-output indicator system was designed, as shown in Table 2 [27,28]. A Super-SBM (Slacks-based Measure) model that consider undesirable outputs was constructed and calculated using MAXDEA ultra7.10 software. Due to the ABSENCE of specific logistics industry data, it uses data from transportation, warehousing, and postal services as substitutes for logistics industry data.Table 2 Comprehensive Indicator Framework for Assessing the High-Quality development Level of the Logistics Industry.

Table 2Primary Index	Secondary Index	Unit	
Input Index	Logistics Fixed Asset Investment	100 million yuan	
Logistics Employment	10,000 persons	
Logistics Energy Consumption	10,000 tons of standard coal	
Output Index	Logistics Value Added	100 million yuan	
Logistics Carbon Emission	Million metric tons of CO2	

3.2.3 Threshold variable

The threshold variable, the advanced level of industrial structure (is), represents the ratio of tertiary to secondary industry output. Higher ratios indicate greater industrial advancement, reflecting economic quality and modernization, which can impact logistics industry and rural revitalization efforts.

3.2.4 Control variables

Regional economic development level (re), indicated by the per capita GDP of each province. Higher levels of economic development directly stimulate faster growth in the logistics industry and rural revitalization, as evidenced by research [29,30].

Income gap between urban and rural residents (ir), represented by the ratio of urban to rural per capita disposable income, it affects the allocation of resources and consumption levels, further influencing logistics demand and rural revitalization [27].

The level of infrastructure construction (ic), represented by the road density, which is calculated as the road mileage divided by the area of each province. It is an essential supporting factor for economic development, especially for the logistics industry and rural revitalization. well-developed infrastructure can enhance logistics efficiency and promote rural development [28].

3.3 Data source and descriptive statistics

Due to incomplete data from Tibet, Hong Kong, Macau, and Taiwan, this study analyzes data from 30 Chinese provinces/cities for the years 2010–2020. The data primarily comes from publications such as the "China Statistical Yearbook" and the "China Energy Statistical Yearbook," among others. When there are missing values in the original data, interpolation methods are used to fill in the gaps (the same applies to subsequent analyses). Descriptive statistics for the primary variables are provided in Table 3.Table 3 Descriptive statistics of primary variables.

Table 3Category	Variable	Obs	Mean	Std.Dev.	Min	Max	
Dependent Variable	lnrr	330	−1.507	0.370	−2.210	−0.588	
Explanatory Variable	lnlh	330	−1.204	0.572	−2.265	0.273	
Threshold Variable	lnis	330	0.176	0.384	−0.640	1.657	
Control Variables	lnre	330	10.743	0.465	9.464	12.009	
lnir	330	0.949	0.145	0.613	1.318	
lnic	330	−0.285	0.772	−2.452	0.786	

4 Results

4.1 Benchmark regression analysis

Utilizing the panel data of Chinese provinces (2010–2020), empirical analysis was performed using the Stata software. The F-test and Hausman test results guided the selection of our estimation method. The F-statistic is 47.40 (P-value is 0.0000), indicating significant regional effects on rural revitalization development levels across different provinces. The Hausman statistic is 13.50 (P-value is 0.0091), strongly rejecting the null hypothesis that the regional effects are random, suggesting that a fixed-effects model (FE) is more suitable. Table 4 displays the regression outcomes: Model (1)a focuses on the core independent variable and Model (1) include the control variables.Table 4 Benchmark regression results.

Table 4Variables	Model(1)a	Model(1)	
lnlh	0.212c	0.0815b	
	(0.0340)	(0.0336)	
lnre		0.0974a	
		(0.0525)	
lnir		−0.533c	
		(0.144)	
lnic		0.131c	
		(0.0264)	
_cons	−1.251c	−1.912c	
	(0.0450)	(0.632)	
Fix effect	yes	yes	
N	330	330	
adj. R-sq	0.078	0.280	
F	38.76	35.52	
Standard errors in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

The regression analysis for Model (1)a and Model (1) in Table 4 shows that the coefficient of the primary independent variable, lnlh, remains a significantly positive coefficient at the 5%level. Even when control variables are added. This implies that the development of the logistics industry has a positive impact on rural revitalization, thereby confirming Hypothesis 1. Among the control variables, - regional economic development positively impacts rural revitalization, as does infrastructure construction, highlighting its importance in improving rural revitalization. Nevertheless, the negative coefficient for the income ratio between urban and rural residents suggests that a widening income gap adversely affects rural revitalization. This negative impact is likely due to decreased economic vitality in rural areas, exacerbated by labor migration to uban centers, further reducing rural economic activity.

4.2 Threshold effect analysis

To evaluate the influence of industrial structure on the relationship between the high-quality development of the logistics industry and economic growth, the industrial structure level is designated as a threshold variable, with threshold values estimated via Model (2). Subsequently, significance tests based on these thresholds are conducted to ascertain the presence of threshold effects. The Stata 16 statistical software is used to perform 300 iterations of bootstrapping for single, double, and triple threshold tests. The results are displayed in Table 5.Table 5 Threshold test results.

Table 5Threshold Variable	Threshold Number	F	P-value	Critical Value	Threshold	95%CI	
10 %	5 %	1 %	
lnis	Single	27.67	0.043	22.739	26.469	35.208	1.394	−0.051	0.028	
Double	22.56	0.070	16.215	26.756	47.728	0.826	0.057	0.185	
Triple	14.12	0.230	23.601	34.556	45.278	–	–	–	

Model (2) yields a statistically significant single threshold effect, with the P-value of the F-value is 0.043, indicating a significant single threshold effect in Model (2). Consequently, additional testing for the double threshold effect is warranted. The P-value for the double threshold is 0.07, showing significance at 10 % level. Testing for a triple threshold yields a P-value of 0.230, which is not significant triple threshold effect. Hence, the double threshold is adopted. These threshold effects indicate that the impact of logistics industry development on rural revitalization varies among regions with varied industrial structure, confirming Hypothesis 2.

The threshold regression results are shown in Table 6.Table 6 Threshold variable regression results.

Table 6lnrr	Coef.	Robust Std. Err.	t	P > t	[95 % Conf.	Interval]	
lnre	0.403	0.083	4.89	0.000	0.235	0.572	
lnir	0.136	0.306	0.45	0.660	−0.489	0.761	
lnic	0.392	0.193	2.03	0.052	−0.003	0.787	
lnis≤0.826	−0.011	0.019	0.58	0.566	−0.051	0.029	
0.826＜lnis≤1.394	0.121	0.031	3.89	0.001	0.057	0.185	
lnis＞1.394	0.314	0.034	9.21	0.000	0.244	0.383	
_cons	−5.853	1.109	5.28	0.000	−8.122	−3.584	
The impact of high-quality development of the logistics on rural revitalization varies with industrial structure (lnis). At low levels (lnis ≤0.826), it is not significant. However, when 0.826 < lnis ≤1.394, it's significant (coef. = 0.121, p＜0.01). When lnis >1.394, the impact intensifies (coef. = 0.314, p＜0.01), suggesting a threshold effect: higher industrial structure levels amplify logistics' role in rural revitalization.

4.3 Robustness test

To assess model robustness, we substituted the independent variable (high-quality development of the logistics industry) with logistics industry added value and re-ran the regression (Table 7). This change did not alter the significance, aligning with the benchmark regression. Thus, confirming the robustness of the findings.Table 7 Robustness test results.

Table 7	(1)		(2)	
	Model4		Model1	
Lnlav	0.200c	lnlh	0.0815b	
	(0.0216)		(0.0336)	
lnre	0.0293	lnre	0.0974a	
	(0.0472)		(0.0525)	
lnir	−0.505c	lnir	−0.533c	
	(0.128)		(0.144)	
lnic	0.0412	lnic	0.131c	
	(0.0252)		(0.0264)	
_cons	−2.756c	_cons	−1.912c	
	(0.574)		(0.632)	
Fix effect	yes	Fix effect	yes	
N	330	N	330	
Adj. R2	0.424	adj. R2	0.280	
F	63.98	F	35.52	
Standard errors in parentheses.

a p < 0.1.

b p < 0.05.

c p < 0.01.

5 Discussion

It initially examined the positive influence of high-quality development of the logistics industry on rural revitalization and subsequently confirmed that this impact varies across different levels of industrial structure.(1) High-Quality Logistics Development and Rural Revitalization: The results indicate a robust positive link echoing prior research highlighting logistics' importance in rural economic growth, increasing farmers' income, and enhancing rural vitality [11,17]. Our study further demonstrates that by optimizing logistics network layout, enhancing logistics service quality, and innovating logistics models intensifies this positive impact on rural revitalization.

(2) Regional Economic Growth and Rural Revitalization: The study confirms a significant positive impact of regional economic development on rural revitalization, Echoing literature emphasizing its pivotal role in fostering rural growth [3]. This indicates that enhancing regional economic development contributes to promoting rural revitalization. Governments and enterprises can take measures such as investing in infrastructure construction, optimizing industrial structure, and increasing residents' income to promote economic development and drive rural revitalization.

(3) Infrastructure and Rural Revitalization: Key to progress, infrastructure construction displays a marked positive impact on rural revitalization, emphasizing its centrality in bolstering rural revitalization. This result supports the conclusions that emphasized the importance of infrastructure in rural development [31,32]. Governments and enterprises should boost investments in rural infrastructure, improve transportation, communication, energy, and other infrastructure conditions in rural areas, thereby promoting rural revitalization.

(4) Urban-Rural Income Gap and Rural Revitalization: The widening gap negatively affects rural revitalization, consistent with literature advocating narrowing this disparity as a key strategy for rural advancement [33]. To narrow the income gap, governments and enterprises should implement measures such as increasing farmers' income, promoting rural employment, and optimizing agricultural industry structure, thus promote rural revitalization.

(5) Industrial Structure Level, High-Quality Logistics Development, and Rural Revitalization: Industrial structure level crucially shapes logistics development quality and rural revitalization. Lower levels yield limited impact, while higher levels significantly enhance rural revitalization through logistics development. This underscores the importance of optimizing the industrial structure and fostering industrial upgrading in rural revitalization, as noted by some scholars [34].

(6) Limitations of the Study: First, our sample may not comprehensively capture logistics industry and rural revitalization trends in all regions due to regional disparities in development， economic structure, resource endowments, and policy environments. Excluding Tibet, Hong Kong, Macau, and Taiwan, robustly analyzed across 30 provinces, restricts nationwide explanation. Unique positions of these regions may yield distinct logistics-rural revitalization dynamics. Additionally, the missing data might introduce sample selection bias. Since the data from these regions were not included, the research sample might not fully represent all provinces nationwide. This bias could introduce uncertainty when generalizing the research findings to the entire country.

Second, our focus on the direct logistics-rural revitalization link overlooks other potential factors. Additionally, the influence may extend spatially, with logistics development in one region potentially bolstering rural revitalization in others.

6 Conclusions

Our study highlights the need for targeted policies that enhance the logistics industry's quality, boost regional economic development, invest in infrastructure, narrowing the urban-rural income disparity, and optimize industrial structures to achieve effective rural revitalization. Policymakers should focus on creating an enabling environment for the logistics industry and regional development, as these are critical drivers of rural revitalization. Based on our detailed analysis and discussion of the findings, we offer the following policy recommendations.(1) Enhance the logistics industry's development: Governments and firms should enhance the logistics industry's growth through improving logistics network layout, enhancing logistics service quality, and implementing innovative logistics models. Specifically in rural regions with higher levels of industrial structure, there should be a focused effort to foster the logistics industry to effectively support rural revitalization efforts.

(2) Promote regional economic development: To drive rural revitalization, support for regional economic development should be strengthened. Governments can invest in infrastructure construction, optimize industrial structure, and increase residents' income to ensure sustainable economic progress, thereby promoting rural growth.

(3) Boost infrastructure investment: For rural revitalization, infrastructure construction is important, governments and enterprises should increase investments in infrastructure to improve transportation, communication, energy, and other infrastructure conditions in rural regions. Also, fortify rural logistics hubs, advancing information technology development, optimizing rural logistics service systems, establishing agricultural transportation insurance mechanisms, encouraging corporate investment in rural logistics markets, and promoting rural e-commerce logistics to strengthen the infrastructure backbone.

(4) Narrowing the urban-rural income gap: To foster rural revitalization, efforts should be undertaken to reduce the urban-rural income disparity. Governments can implement measures such as augmenting farmers' income, facilitating rural employment, and optimizing the agricultural industry structure, thereby propelling rural development.

(5) Optimize industrial structure: In less developed rural region, prioritize optimizing and upgrading industries. Governments and enterprises should aid the shift to modern agriculture and agro-processing, consequently elevating the development of the logistics industry and fostering rural revitalization.

Our study investigated the impact of high-quality development of the logistics industry on rural revitalization across various levels of industrial structure. Nevertheless, the study is subject to certain limitations, suggesting avenues for future research: forthcoming studies could enhance data sources and expand sample scope, consider more influencing factors, incorporate additional qualitative research methods, and explore the implementation of policy recommendations and collaborations within the logistics industry to offer more comprehensive and effective support for rural revitalization. It can also discuss the issues of regional heterogeneity and spatial effects, and consider using more appropriate models (such as spatial panel models) to capture these effects.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data reported in this study has been deposited in the OSF, (https://doi.org/10.17605/OSF.IO/ZT9DH).

Funding

This work was supported by the 10.13039/501100012456 National Social Science Foundation of China (NO. 22ATJ009 ).

CRediT authorship contribution statement

Borui Yan: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Bo Yao: Funding acquisition. Yamin Wang: Writing – review & editing.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Bo Yao reports financial support was provided by The National Social Science Fund of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
==== Refs
References

1 Gu X. Niu Y. SWOT analysis of rural logistics industry chain under the background of rural revitalization, rural econ Technol. 34 6 2023 243 245 10.19592/j.cnki.scje.400225
2 Yu Q. Xiang C. Qiu X. Research on the development of rural logistics in China under the background of rural revitalization Agric. Econ. 10 2022 141 142
3 Qu R. Rhee Z. Bae S. Analysis of industrial diversification level of economic development in rural areas using Herfindahl index and two-step clustering Sustain. Times 14 11 2022 6733 10.3390/su14116733
4 Chen D. Ma Y. Effect of industrial structure on urban-rural income inequality in China China Agric. Econ. Rev. 14 3 2022 547 566 10.1108/CAER-05-2021-0096
5 Jia J. Yin L. Yan C. Urban-rural logistics coupling coordinated development and urban-rural integrated development: measurement, influencing factors, and countermeasures Math. Probl Eng. 7 2022 2969206 10.1155/2022/2969206
6 Chen X. Constraints and countermeasures of rural logistics development in China Theor. Explor 5 2005 81 82 10.16354/j.cnki.23-1013/d.2005.05.027
7 Lu H. Bao J. Spatial differentiation effect of rural logistics in urban agglomerations in China based on the fuzzy neural network Sustain. Times 14 15 2022 9268 10.3390/su14159268
8 Zhang L. Dong Q. Shen L. The correlation study of logistics industry and regional economy under the influence of transportation infrastructure Technol. Econ. Manag. Res 1 2015 112 116
9 Jia H. Wang M. Su W. Research on the adaptability of logistics infrastructure to rural economy in jiangsu province Manag. Obs. 29 2018 79 80+3
10 Yuan C. Li J. Wei Y. Rural logistics construction and its effect on farmers' income increase World Econ. 46 4 2023 111 139
11 Sezer S. Abasiz T. The impact of logistics industry on economic growth: an application in OECD countries, Eurasian J Soc. Sci. 5 1 2017 11 23 10.15604/ejss.2017.05.01.002
12 Cui H. Zhang L. Wang Z. Research on the correlation effect between logistics industry development and regional economic growth—based on panel data from the three major urban agglomerations of the Yangtze river economic belt Econ. Issues 3 2021 78 85 10.16011/j.cnki.jjwt.2021.03.011
13 Ivanov D. Dolgui A. Sokolov B. Ivanova M. Literature review on disruption recovery in the supply chain Int. J. Prod. Res. 55 20 2017 6158 6174 10.1080/00207543.2017.1330572
14 Zhou L. The interaction between rural economic development and modern logistics industry development: a study Rural Couns 19 2017 14
15 Xue E. Li J. Li X. Sustainable development of education in rural areas for rural revitalization in China: a comprehensive policy circle analysis Sustain. Times 13 23 2021 13101 10.3390/su132313101
16 Zhang X. Research on the path of rural logistics development under the rural revitalization strategy Contemp. Econ. Manag. 41 4 2019 46 51 10.13253/j.cnki.ddjjgl.2019.04.007
17 Ding Q. Deng Y. An X. Synergistic development of rural logistics and rural economy from the perspective of rural revitalization Bus. Econ. Res. 7 2021 4
18 Wang Q. Zhang F. Li R. Does artificial intelligence promote energy transition and curb carbon emissions? The role of trade openness J. Clean. Prod. 447 2024 141298 10.1016/j.jclepro.2024.141298
19 Wang Q. Zhang F. Li R. Free trade and carbon emissions revisited: the asymmetric impacts of trade diversification and trade openness Sustain. Dev. 32 1 2024 876 901 10.1002/sd.2703
20 Su J. Shen T. Ma W. Zhang J. Study on the effect of rural low carbon logistics industry development on rural economic growth IEEE Access 11 2023 37108 37122 10.1109/ACCESS.2023.3266513
21 Li R. Li L. Wang Q. The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces Sustain. Cities Soc. 82 2022 103880 10.1016/j.scs.2022.103880
22 Wang Q. Zhang F. Li R. Revisiting the environmental kuznets curve hypothesis in 208 counties: the roles of trade openness, human capital, renewable energy and natural resource rent Environ. Res. 216 2023 114637 10.1016/j.envres.2022.114637
23 Zhu X. Development problems and countermeasures of rural E-commerce logistics in the context of big data and internet of things J. Inf. Process. Syst. 19 2 2023 267 274 10.3745/JIPS.04.0273
24 J. Zhang, Research on the linkage development of agricultural product processing industry and logistics industry from the perspective of supply chain to promote upgrading, Agric. Econ. (5)2018136-2018137.
25 Zeng M. Liu R. Gao M. Jiang Y. Demand forecasting for rural E-commerce logistics: a gray prediction model based on weakening buffer operator Mob. Inf. Syst. 1 2022 3395757 10.1155/2022/3395757
26 Xu X. Wang Y. Measurement of China's rural revitalization level, regional difference decomposition, and dynamic evolution Quant. Econ. Tech. Econ. Res. 39 5 2022 64 83 10.13653/j.cnki.jqte.2022.05.009
27 Yan B. Dong Q. Li Q. A study on the coupling and coordination between logistics industry and economy in the background of high-quality development Sustain. Times 13 18 2021 10360 10.3390/su131810360
28 Yan B. Dong Q. Li Q. Yang L. Amin F.U.I. A study on the interaction between logistics industry and manufacturing industry from the perspective of integration field PLoS One 17 3 2022 e0264585 10.1371/journal.pone.0264585
29 Li R. Wang Q. Guo J. Revisiting the environmental Kuznets curve (EKC) hypothesis of carbon emissions: exploring the impact of geopolitical risks, natural resource rents, corrupt governance, and energy intensity J. Environ. Manag. 351 2024 119663 10.1016/j.jenvman.2023.119663
30 Wang Q. Hu S. Li R. Could information and communication technology (ICT) reduce carbon emissions? The role of trade openness and financial development Telecommun. Pol. 48 3 2024 102699 10.1016/j.telpol.2023.102699
31 Fei X. Feng J. Research on the high‐quality development model of China's grain industry from the perspective of rural revitalization Wirel. Commun. Mob. Comput. 1 1 2022 2661237 10.1155/2022/2661237
32 Bian X. Xu J. How to deal with the trade-off between development and decarbonization for rural logistics in China? Evidence from Jiangsu J. Syst. Sci. Syst. Eng. 32 6 2023 656 686 10.1007/s11518-023-5575-7
33 Li M. Huan K. Xie X. Dynamic evolution, regional differences and influencing factors of high-quality development of China's logistics industry Ecol. Indic. 159 2024 111728 10.1016/j.ecolind.2024.111728
34 Tang L. Wan W. Bi W. The impact of high-quality development of rural logistics on consumption: energy and healthcare consumption as an example Front. Energy Res. 11 2024 1321910 10.3389/fenrg.2023.1321910
