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Article

Rural Industry Integration in Yan’an City: Development Trends, Driving Factors, and Regional Stratification

by
Xiaoying Ren
1,2,
Guobing Ruan
1,2,
Yimeng Han
1,2,
Dingding Zhang
1,2,
Yaqi Wei
1,2 and
Yongzhong Feng
1,2,*
1
College of Agronomy, Northwest A & F University, Yangling, Xianyang 712100, China
2
The Research Center of Recycle Agricultural Engineering and Technology of Shaanxi Province, Yangling, Xianyang 712100, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(4), 1447; https://doi.org/10.3390/su17041447
Submission received: 18 November 2024 / Revised: 10 January 2025 / Accepted: 13 January 2025 / Published: 10 February 2025
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Abstract

:
With the advancement of the rural revitalization strategy, the integration of primary, secondary, and tertiary industries has become an important approach to promoting rural economic development and agricultural modernization. Yan’an City, as a typical agricultural region in northwestern China, has made significant progress in rural industry integration in recent years, driven by policy support and technological innovation. This study, based on data from 2012 to 2021, analyzes the overall development trends, key driving factors, and regional differences in rural industry integration in Yan’an City, explores changes in economic and social benefits during the integration process, and proposes corresponding policy recommendations. The findings indicate that, under the influence of policy support, service sector development, and technological innovation, the integration of rural industries in Yan’an City has accelerated. However, regional disparities in integration levels still exist, with some remote areas facing challenges due to insufficient infrastructure and resource allocation. Therefore, the study suggests that future efforts should focus on further integrating ecological benefit indicators and exploring differentiated policies to promote the sustainable development of industrial integration. The results of this study provide practical references for industrial integration in the central and western regions, especially underdeveloped areas, and offer theoretical support for regional policy formulation and industrial development.

1. Introduction

Globally, rural economic development models are undergoing profound structural changes. With slowing population growth and the impact of globalization, traditional agricultural models are struggling to meet modern society’s demand for diversified and high-value agricultural products [1,2]. Against this backdrop, the integration of primary, secondary, and tertiary industries in rural areas has become a vital path for countries to promote agricultural modernization and rural economic transformation [3,4]. Rural industry integration involves more than just connecting agriculture with secondary and tertiary industries. It is a multifaceted approach that includes the diversification of agricultural activities, the development of rural services, and the incorporation of sustainable practices [5,6]. For example, integrating agriculture with renewable energy production, environmental conservation efforts, and information technology can help reduce the ecological footprint of rural industries while increasing their economic output. This integration not only enhances agricultural efficiency but also fosters a more resilient rural economy capable of withstanding global economic fluctuations and environmental changes. Developed countries like Europe, the United States, and Japan have pioneered the integration of agriculture and services to diversify rural economies. For instance, European countries have activated rural resources through the “agriculture + tourism” model, increasing farmers’ income while promoting the protection and utilization of rural ecological resources [7]. In the United States, agricultural technological innovation has driven the scale and modernization of agriculture, supporting the agricultural product processing industry and agricultural services to form a complete industrial chain [8,9]. In Japan, rural communities supported by policies have promoted the integration of agriculture with other industries, especially in tourism, healthcare, and education, greatly enhancing the economic level and employment opportunities in rural areas [10,11].
In addition to the general trend of globalization and demographic changes, rural areas worldwide face specific challenges that complicate traditional agricultural practices. These include rising pressures to balance environmental sustainability with economic development [12], the migration of young people to urban areas [13], and the increasing need for rural areas to adapt to technological advancements [14]. Many rural regions are also grappling with the decline of small-scale farming, which has led to the concentration of agricultural activities in a few large-scale operations [15]. These challenges underscore the urgent need for diversified economic models that incorporate various sectors to revitalize rural areas.
In China, with the in-depth implementation of the rural revitalization strategy, rural industry integration is seen as an important means to enhance rural economic vitality and increase farmers’ income [16]. The integration of primary, secondary, and tertiary industries in rural areas not only expands the multifunctionality of agriculture and promotes the deep integration of agricultural production with other industries but also plays a crucial role in optimizing resource allocation and improving the overall economic level of rural areas [17]. Industrial integration mainly improves rural economic levels by extending the agricultural industrial chain, developing agricultural multifunctionality (such as tourism and experiential agriculture), and expanding agricultural services. In recent years, the Chinese government has introduced various policies to support rural industry integration [18]. For example, the “Rural Revitalization Strategy Plan (2018–2022)” sets important goals such as “building a modern agricultural industrial system, production system, and operation system” and “promoting the integrated development of primary, secondary, and tertiary industries in rural areas.” These policies have laid the foundation for the development of industrial integration and have effectively promoted collaboration in resource integration, agricultural product processing, and rural services [19,20,21]. In China, rural industry integration is a cornerstone of the government’s Rural Revitalization Strategy, which aims to reduce regional inequalities and stimulate sustainable growth. Key policies such as the “Rural Revitalization Strategy Plan (2018–2022)” [22] have facilitated investments in infrastructure, technology, and human capital, allowing for the convergence of primary industries like agriculture with secondary and tertiary industries. Notably, initiatives such as “agriculture + tourism” and “agriculture + e-commerce” have led to the development of new business models in rural areas, providing new income sources for farmers while fostering rural development and ecological preservation. However, despite these successes, challenges persist in less-developed regions where the pace of integration is slower, and the potential for synergy between industries remains underexplored [23].
Internationally, there is a broad consensus on rural industry integration, particularly in developed countries, where it is regarded as a vital means of enhancing agricultural competitiveness and achieving rural economic diversification [24]. European countries typically combine agriculture with tourism and handicrafts to promote economic diversity and increase employment opportunities in rural areas. For example, countries like France and Italy have extended the wine industry value chain into agritourism, significantly enhancing the added value of agricultural products [25,26]. In the United States, research focuses more on the role of agricultural value chain extension and supply chain innovation in boosting rural economies, particularly advancements in agricultural product processing and logistics systems, which have provided strong support for rural economic modernization [27,28,29]. Japan, on the other hand, emphasizes the integration of agriculture with services like healthcare and eldercare, effectively increasing employment and economic levels in aging rural areas through multi-industry integration [30,31,32].
Domestically, scholars widely recognize the positive role of industry integration in boosting rural incomes and promoting urban-rural development coordination [33,34]. Empirical research indicates that by extending the agricultural value chain and developing multifunctionality, rural industry integration has not only significantly enhanced agriculture’s value-adding capacity but also boosted the added value of agricultural products [35,36,37]. Studies have shown that industry integration is particularly effective in economically developed regions, where modern agricultural parks in coastal areas often adopt an “agriculture + tourism + experience” model to effectively promote local rural consumption levels [38,39]. Furthermore, the role of rural industry integration in increasing farmers’ income and narrowing the urban-rural income gap has also been validated, aligning with international findings and underscoring the broad applicability of this integrated model across different countries and regions [40,41,42].
However, despite the numerous studies on industrial integration at home and abroad, most research has focused on economically developed regions along the eastern coast. For mid-level regions, especially underdeveloped areas in the central and western parts of China, there is a lack of in-depth analysis regarding regional differences, driving factors, and dynamic changes in the benefits of integration [43,44,45]. Additionally, limited research explores how rural industry integration balances ecological sustainability with resource optimization, highlighting the necessity of conducting in-depth research on typical cases in western China to provide policy and practical guidance for agricultural areas in the central and western regions [46,47]. The impact of rural industry integration is not uniform across regions, and it is particularly important to consider the unique characteristics of different areas. For instance, rural areas in the eastern coastal regions of China benefit from more advanced infrastructure and better access to technology and capital, which accelerates the pace of industry integration [48]. In contrast, rural areas in central and western China, such as Yan’an, face distinct challenges such as lower levels of industrialization, less-developed infrastructure, and weaker connectivity to urban markets [49]. Understanding these regional differences is crucial for tailoring policies that effectively support industry integration and ensure equitable development across all regions [50].
Located in northwestern China, Yan’an City is an important agricultural area in Shaanxi Province with abundant agricultural resources. However, it also faces challenges such as high resource development intensity and significant ecological protection pressures. In recent years, with the support of government policies, Yan’an City has actively promoted the integration of primary, secondary, and tertiary industries in rural areas, achieving significant progress, particularly in extending the agricultural industrial chain, developing agricultural multifunctionality, and promoting the integration of agricultural product processing and rural services [48]. Selecting Yan’an City as a research object has the following justifications: First, Yan’an is a typical northwestern agricultural area, with substantial differences in rural industry structure and integration modes compared to the eastern coastal areas. An in-depth analysis of Yan’an City can fill the research gap in the central and western regions. Second, the government of Yan’an has actively promoted rural industry integration in recent years, implementing various supportive policies and exploring diversified models of industry integration, making it a representative case for the central and western regions. Research on Yan’an’s industry integration development path can provide important empirical support and policy references for the western region in areas such as industrial chain extension, resource integration, and social well-being improvement.
This study aims to systematically analyze the overall development trend, key driving factors, and regional differences in rural industry integration in Yan’an City from the dimensions of time series and spatial stratification, and proposes targeted policy recommendations. The specific research objectives are as follows:
(1)
Describe the temporal changes in rural industry integration in Yan’an City, clarify the characteristics of different periods and their impact on economic and social benefits.
(2)
Identify the key driving factors promoting industry integration in Yan’an City by analyzing third-level indicators, focusing on their roles in economic growth, farmers’ income, and rural consumption.
(3)
Based on county-level data, use cluster analysis to reveal the differences in industry integration levels across counties in Yan’an City and propose corresponding region-specific development path recommendations.
This study not only explores the integration of rural industries in Yan’an, an agricultural region in northwestern China, but also contributes to achieving the United Nations Sustainable Development Goals (SDGs), particularly Goal 1 (No Poverty), Goal 8 (Decent Work and Economic Growth), and Goal 12 (Responsible Consumption and Production). The integration of rural industries in Yan’an offers a model for sustainable agricultural practices, inclusive economic growth, and poverty alleviation, providing insights that can be applied globally.

2. Materials and Methods

2.1. Research Hypotheses

In the study of rural industrial integration, it is widely recognized that integration not only promotes agricultural productivity but also enhances the overall vitality of the rural economy through the optimized allocation of resources. With the in-depth implementation of China’s rural revitalization strategy, industrial integration has gradually been applied in various regions as an important means to drive agricultural modernization and rural economic transformation [51]. Rural industrial integration typically involves the deep integration of agricultural production, processing industries, and services. It can break the traditional single-agriculture model, promote the collaborative development of agriculture with other industries, thereby increasing the added value of agriculture and boosting farmers’ income. Moreover, regional differences, infrastructure development, and policy support are factors that significantly influence the effectiveness of industrial integration [52].
Based on the above background, this study proposes the following hypotheses:
H1: 
The integration of primary, secondary, and tertiary industries in Yan’an City has significantly enhanced agricultural competitiveness and increased farmers’ income.
This hypothesis focuses on how industrial integration improves agricultural competitiveness and increases farmers’ income through the extension of agricultural value chains and agricultural product processing. By analyzing the extension of agricultural value chains and the effects of deep industrial integration, we can verify the role of industrial integration in enhancing agricultural competitiveness and income growth.
H2: 
There are significant regional differences in the level of industrial integration across counties in Yan’an City, and these differences are influenced by factors such as infrastructure, policy support, and ecological conditions.
This hypothesis posits that due to differences in infrastructure, policy support, and ecological conditions across counties in Yan’an, there will be notable regional disparities in the level of industrial integration. These factors not only affect the effectiveness of industrial integration but may also produce different economic and social impacts in different regions. Therefore, analyzing the impact of county-level differences on industrial integration will help reveal the spatial heterogeneity of integration effects.
H3: 
Industrial integration contributes to multifunctional development in rural areas, particularly through the collaborative development of agricultural value chain extension, agricultural tourism, and agricultural services.
This hypothesis explores how industrial integration, through the fusion of agriculture with tourism and agricultural services, promotes multifunctional development in rural areas. By extending the agricultural value chain and integrating agriculture with tourism, industrial integration not only improves agricultural productivity but also drives the development of rural tourism, promoting employment and diversified income sources in rural areas.

2.2. Materials and Methods

This study employs three primary analytical methods: Entropy method, coupling coordination degree analysis, and cluster analysis. The purpose and application approach for each method are outlined below:
Entropy Method: The entropy method is primarily used to determine the weights of each indicator in the evaluation system. By calculating the information entropy of each indicator, the entropy method can objectively reflect the contribution of each indicator [53]. In this study, the entropy method is used to process multidimensional data and ensure that each indicator contributes reasonably to the overall evaluation result. Specifically, the entropy method quantifies the information provided by each indicator, thus determining its weight in the analysis and avoiding subjective bias, ensuring objectivity in the data [54].
Coupling Coordination Degree Analysis: Coupling coordination degree analysis is used to evaluate the coupling and coordination between different systems [55]. In this study, coupling coordination degree analysis is used to reveal the relationship between economic and social benefits in Yan’an City, and to analyze the level of industrial integration across different counties. This method helps identify the degree of coordination between regions and analyzes which factors influence the effectiveness of industrial integration. By calculating the coupling degree and coordination degree, it helps us understand the interdependence and coordination between systems and sheds light on the performance of counties in industrial integration [56].
Cluster Analysis: Cluster analysis is used to group the counties in Yan’an City based on their level of industrial integration, aiming to reveal the differences and commonalities among counties [57]. Through cluster analysis, we can group counties based on their similarities in the industrial integration process, thereby helping to develop regional development strategies. Cluster analysis not only identifies counties with higher or lower integration levels but also provides insights for formulating differentiated policies for different regions [58].
These three methods work together in this study, each assessing the overall level, regional differences, and the impact of industrial integration on agricultural competitiveness and farmers’ income from different angles.

2.2.1. Evaluation Indicator System

To further validate our findings, we compared our methods with other commonly used approaches, such as fuzzy clustering and decision tree analysis. While these methods also offer valuable insights, we found that the methods used in this study provide a more reliable and comprehensive framework for assessing rural industry integration. For instance, decision tree analysis could identify specific drivers of integration but lacks the depth of clustering analysis in grouping regions based on integrated development [59].
Based on the intrinsic characteristics of rural primary, secondary, and tertiary industry integration and relevant theoretical foundations, and under the principles of scientific rigor, systematization, and accessibility, this study constructs an evaluation indicator system for rural industry integration in Yan’an City [60]. This is done after extensive review of the literature on rural industry integration and referencing the research results of scholars in this field. Following the guidance from the “Guiding Opinions on Promoting the Integration of Primary, Secondary, and Tertiary Industries in Rural Areas” issued by the State Council General Office, which includes developing multiple types of rural industry integration models, fostering diverse rural industry integration subjects, establishing various interest connection mechanisms, improving multi-channel rural industry integration services, and enhancing the promotion mechanism of rural industry integration, this study focuses on achieving clear improvements in agricultural competitiveness, sustained increases in farmers’ income, and significantly enhanced rural vitality. The indicator system is tailored to the actual situation of rural industry integration in Yan’an City [61].
To measure the integration level of rural primary, secondary, and tertiary industries, both the integration process and its outcomes need to be considered. Therefore, two first-order indicators—rural industry integration process and rural industry integration benefits—are established. These indicators, respectively, reflect the depth and breadth of rural industry integration and the economic and social effects brought about by industrial integration. Additionally, five second-order indicators are selected: Agricultural value chain extension, multifunctional development of agriculture [62], integration of agricultural services, economic benefits, and social benefits. Under these second-order indicators, 15 third-order indicators are chosen to construct the evaluation indicator system for the integration level of rural primary, secondary, and tertiary industries in Yan’an City (Table 1).
(1)
Main business income from agricultural product processing (C1): Refers to the income generated from processing agricultural products. It is an economic indicator reflecting the development level of the agricultural processing industry and can objectively reflect the production capacity and business conditions of agricultural products. It is an important indicator of the extension of the agricultural value chain.
(2)
Ratio of main business income from agricultural product processing to total agricultural output (C2): Reflects the relative development level of agricultural processing in relation to agriculture. The larger the value, the higher the degree of agricultural industrialization, and the stronger the agricultural processing industry’s ability to drive agriculture.
(3)
Proportion of primary industry added value to GDP (C3): Refers to the proportion of the primary industry output value in the region’s GDP. It reflects changes in the role of the primary industry in the industrial development of Yan’an City and is an important indicator for observing industrial structural adjustments.
(4)
Rural broadband penetration rate (C4): The ratio of the number of villages with broadband access to the number of village committees, reflecting the level of internet penetration in rural areas. As agriculture and information technology integrate, new industries and business forms such as e-commerce and internet-based agricultural product sales have emerged and developed rapidly. Due to limited data availability on e-commerce transactions, rural broadband penetration rate is used as an indicator to reflect the integration of agriculture and new rural business models.
(5)
Per capita grain production (C5): The basic function of agriculture is to meet the food needs for human survival and development. Stable food production is the foundation for social stability and national economic development. Per capita grain production reflects the basic food security function.
(6)
Fertilizer application intensity (C6): An indicator of agricultural ecological function, calculated as the amount of fertilizer applied per unit area of cultivated land. It reflects the degree of coordinated development between agricultural production and the ecological environment. A smaller value indicates better ecological conditions in agricultural production.
(7)
Total output value of agricultural, forestry, animal husbandry, and fishery services (C7): An economic indicator of agricultural socialized services, reflecting the level of agricultural social services in agricultural production and the degree of integration between the agricultural service industry and agriculture.
(8)
Postal package volume (C8): The development of rural primary, secondary, and tertiary industries relies on logistics support. With the rise of rural e-commerce, an increasing number of agricultural products are being sold online, expanding sales channels and promoting rural development. The volume of postal packages reflects the integration of agriculture and e-commerce logistics.
(9)
Growth rate of total agricultural output value (C9): Reflects the role of rural industry integration in driving overall agricultural development. While agricultural output growth cannot be entirely attributed to rural industry integration, it is undoubtedly influenced by the integration process. The increase in total agricultural output value can be seen as a reflection of the effects of rural industry integration.
(10)
Per capita disposable income of rural residents (C10): The core goal of rural industry integration is to increase farmers’ income. Per capita disposable income of rural residents is an important indicator reflecting farmers’ income, showcasing the impact of industry integration on income growth. However, like agricultural output value, this indicator reflects how rural industry integration has promoted income increase, but does not capture its full impact.
(11)
Rural consumption retail sales (C11): An economic indicator reflecting rural consumption. With the influence of the “Internet+” model, rural agricultural products are reaching broader markets, increasing farmers’ incomes. Additionally, the internet has provided more consumption choices for rural residents, driving rural consumption upgrades. This indicator reflects the changes in farmers’ living standards due to the integration of rural industries.
(12)
Ratio of per capita disposable income of rural residents to urban residents (C12): An important indicator reflecting the narrowing income gap between urban and rural areas. Promoting rural industry integration can provide more employment opportunities for farmers, achieve multi-channel income growth, and reduce income disparities, thus contributing to social fairness.
(13)
Proportion of agricultural, forestry, and water affairs expenditure to fiscal expenditure (C13): Reflects the level of government financial support for rural development. A higher value indicates greater support, which is beneficial to rural infrastructure construction and provides strong external support for rural industry integration, promoting income growth and rural development.
(14)
Urbanization rate (C14): An important indicator reflecting the level of urban-rural integration, as well as a manifestation of the social benefits brought about by rural industry integration. The integration of rural industries enriches rural development business models, increases farmers’ income, reduces the urban-rural gap, and facilitates urban-rural integration.
(15)
Rural non-agricultural employment rate (C15): Refers to the proportion of rural workers employed in secondary and tertiary industries. It reflects the extent to which rural industry integration drives employment. A higher value indicates greater participation in secondary and tertiary industries, thus demonstrating the stronger driving force of rural industry integration.

2.2.2. Research Methods

This study uses several methods to analyze the level of integration of rural primary, secondary, and tertiary industries in Yan’an City. These methods include the entropy method, coupling coordination degree analysis, and cluster analysis, each of which plays a crucial role in evaluating various aspects of the integration process.
(1)
Entropy Method
The entropy method is used to calculate the weights of different indicators in the evaluation system. The entropy value measures the amount of information that an indicator contributes to the evaluation system. The lower the entropy value, the more important the indicator is. The formula for calculating the entropy of indicator i is as follows:
E i = − 1 l n   m ∑ j = 1 n   x i j · l n   x i j ∑ i = 1 m x i j
where
  • xij represents the value of indicator i in year j;
  • m is the total number of indicators;
  • n is the total number of years.
Next, the weight of each indicator Wi is calculated based on the entropy values:
w i = 1 − E i ∑ i = 1 m 1 − E i
(2)
Coupling Coordination Degree Analysis
Coupling coordination degree analysis is used to evaluate the degree of coupling and coordination between economic and social benefits, as well as between different industries. The coupling degree C between two systems X and Y is defined as:
C = 2 ⋅ X ⋅ Y X + Y
where
  • X and Y represent the two systems being compared (e.g., economic benefits and social benefits, or different industrial sectors).
The coordination degree D is calculated to evaluate the balance between these two systems:
D = C C 1 ⋅ C 2
where C1 and C2 are the coupling degrees for each of the systems involved.
(3)
Cluster Analysis
Cluster analysis is applied to reveal the different levels of industrial integration among counties in Yan’an City. The analysis groups counties into different categories based on their industry integration levels. The clustering process generally follows these steps:
①
Normalize the data to ensure that all variables are on the same scale.
②
Calculate the distance or dissimilarity between each county’s indicator data using a distance measure (e.g., Euclidean distance).
③
Use hierarchical clustering to group counties into different clusters based on their similarities.
The Euclidean distance formula is
d x , y = ∑ i = 1 n x i − y i 2
where
  • x and y are the indicator vectors for two counties;
  • n is the number of indicators.

2.3. Data Sources

The data used in this study is sourced from several reliable publications and government reports covering the period from 2012 to 2021. The primary data sources are as follows:
Yan’an City Statistical Yearbook: This annual publication provides comprehensive statistical data on various economic, social, and agricultural aspects of Yan’an City from 2012 to 2021.
Shaanxi Province Statistical Yearbook: This yearbook contains statistical data for Shaanxi Province, including information relevant to Yan’an City, covering the period from 2012 to 2021.
Yan’an City National Economic and Social Development Statistical Bulletin: Published annually, this bulletin offers detailed information on the economic and social development of Yan’an City for the years 2012 through 2021.

3. Results

3.1. Time Series Trend of Overall Industry Integration Level in Yan’an City

The overall integration level of primary, secondary, and tertiary industries in rural Yan’an City shows a significant upward trend from 2012 to 2021, as observed in the chart, with particularly notable growth after 2018 (Figure 1).
Early Stability Phase (2012–2015): During 2012–2015, the overall integration level grew slowly, indicating that rural industry integration in Yan’an was in an initial exploratory and developmental stage, with limited advancement in integration levels.
Acceleration Phase (2016–2019): Beginning in 2016, the integration level shows a clear upward trend, with growth rates accelerating after 2018. This growth likely reflects the influence of supportive government policies, infrastructure improvements, and other factors driving the integration of rural industries, particularly in extending the agricultural value chain and integrating service industries.
High-Level Stability Phase (2020–2021): In 2020 and 2021, the integration level reached a relatively high plateau, indicating that Yan’an’s industrial integration had entered a mature development stage. By this time, the synergy between different industries had consolidated, maintaining rural industry integration at a high level.
Overall, the integration of primary, secondary, and tertiary industries in rural Yan’an City has steadily increased over the past decade, driven particularly by policy support and industrial synergy, gradually transitioning from an exploratory phase to a mature stage.

3.2. Significant Changes in the Integration Process and Integration Benefits at Different Periods

Early Slow Growth (2012–2015): Between 2012 and 2015, A1 showed a slow rate of increase, indicating that the integration of rural industries was still in its initial stages during this period (Figure 2).
Significant Acceleration (after 2016): Starting in 2016, A1 showed a marked upward trend, with a further acceleration after 2018, reflecting the effectiveness of Yan’an City’s efforts in promoting the coordinated development of agriculture, secondary industries, and services. This phase of rapid acceleration likely benefited from policy support, the extension of the agricultural value chain, and the development of multifunctional agriculture.
Steady Growth in Integration Benefits (A2):
Since 2012, A2 has shown a steady increase, although at a slower rate compared to A1. This indicates that, while rural industry integration in Yan’an City has generated certain economic and social benefits, the growth of these benefits requires cumulative time.
After 2018, the growth rate of A2 began to accelerate, showing that the integration of industries is gradually impacting rural residents’ income and consumption levels.
Relationship between A1 and A2:
Overall, the rapid growth of A1 has laid a foundation for the improvement of A2, suggesting that the advancement of the integration process has created conditions for the realization of integration benefits.
Particularly after 2018, the synchronized growth of A1 and A2 indicates that industrial integration has had a more direct impact on the economic and social benefits in Yan’an City.
This trend demonstrates that the integration process of rural industries in Yan’an City has significantly accelerated in recent years, driving the growth of integration benefits and thereby achieving a win-win outcome for economic and social benefits.

3.3. Key Driving Factors of Industry Integration

The heatmap reveals the correlations among the third-level indicators (C1–C15), providing insights into the key driving factors for the integration of primary, secondary, and tertiary industries in rural Yan’an City. Indicators with high positive correlations, such as C1 (main business income from agricultural product processing) and C2 (ratio of main business income to total agricultural output), suggest that extending the agricultural processing value chain directly enhances the share of total agricultural output. Additionally, a strong correlation between C7 (total output of agricultural, forestry, animal husbandry, and fishery services) and C8 (postal package volume) indicates that the growth of agricultural services and rural logistics development are mutually reinforcing (Figure 3).
The economic and social benefits are also reflected in the indicator relationships. For example, C10 (per capita disposable income of rural residents) and C11 (retail sales of rural consumer goods) are highly correlated, showing that increased rural incomes lead directly to higher consumption, an important economic outcome of integration. Similarly, the correlation between C14 (urbanization rate) and C15 (rural non-agricultural employment rate) suggests that urbanization advances non-agricultural employment in rural areas, contributing to the growth of social benefits.
There are also negative correlations indicating potential constraints, such as between C6 (fertilizer application intensity) and C5 (per capita grain yield). This relationship suggests that over-reliance on fertilizer may hinder the sustainable growth of grain yield, highlighting the need for policymakers to consider ecological sustainability in agricultural modernization. Overall, these correlations underscore the critical roles of certain indicators (such as C1 and C2 for economic benefits and C14 and C15 for social benefits) in driving rural industry integration and enhancing rural development.

3.4. Analysis of Coupling and Coordination Changes Between Economic and Social Benefits

From the path plot, we can observe the dynamic changes in the coupling degree and coordination degree between economic and social benefits in the rural industry integration process of Yan’an City from 2012 to 2021. In the early stage (2012–2015), the coupling degree was close to 1, indicating a high coupling between economic and social benefits. However, the coordination degree was only 0.1, reflecting an imbalance in their actual development. During this period, although there was some linkage between economic and social benefits, they were still developing relatively independently, suggesting insufficient resource coordination in the initial stages of industry integration (Figure 4).
From 2016 to 2019, the path gradually moved upward, showing a significant improvement in the coordination degree. This phase marked a more apparent synergistic development between economic and social benefits, likely driven by policy support and adjustments in agricultural and rural economic development models. The integration of rural industries increasingly achieved coordinated development, leading to a more balanced integration process.
In 2020 and 2021, both the coupling degree and coordination degree approached 1, indicating that the rural industry integration in Yan’an City had entered a mature stage. The synergy between economic and social benefits became more evident. During this period, the effects of industry integration were fully realized, achieving significant progress in optimizing resource allocation and enhancing social welfare, ultimately resulting in a virtuous cycle of economic and social benefits.

3.5. Hierarchical Clustering of Industry Integration Levels in Yan’an City’s Districts and Counties

From the dendrogram, it is clear that there are significant differences in the performance of Yan’an City’s districts and counties across five key indicators: Industry chain extension (B1), agricultural multifunctionality expansion (B2), agricultural service industry integration (B3), economic benefits (B4), and social benefits (B5). These differences are represented by multiple branching clusters in the dendrogram, reflecting various levels of industrial integration development. Based on the position of each district or county in the dendrogram, they can be preliminarily categorized into three levels (Figure 5).
High-level integration areas include Baota District and Fuxian County, which scored highly in industry chain extension and economic benefits, demonstrating strong industry integration capabilities, particularly in driving regional economic development. Mid-level integration areas, such as Luochuan County and Huanglong County, show moderate scores across various indicators, indicating substantial development potential but still room for improvement, especially in social benefits and service industry integration. Low-level integration areas, such as Wuqi County and Ansai District, exhibit relatively lower scores across all integration indicators, showing significant potential for improvement, especially in industry chain extension and service industry integration.
Differentiated development strategies can be proposed: For high-level integration areas, further strengthening the advantages in industry chain extension and economic benefits would enhance their demonstration effect and guide more innovative industrial models. For mid-level integration areas, efforts should focus on addressing weaknesses in areas such as social benefits and service industry integration, potentially through policy guidance. For low-level integration areas like Wuqi County, prioritizing resource investment and policy support is recommended, particularly in enhancing industrial foundations, especially in agricultural multifunctionality expansion and service industry integration.

4. Discussion and Policy Implications

4.1. Core Driving Factors of Rural Industry Integration and Considerations for Sustainable Development

This study reveals the critical roles of policy, technological innovation, and the development of the service sector in promoting the integration of the primary, secondary, and tertiary industries in Yan’an City. In addition to policy support, which serves as a direct driving force, technological innovation has played a pivotal role in the transformation of agriculture and rural industries. In recent years, countries around the world have focused on the intelligent and digital transformation of agriculture, integrating technology across the entire agricultural value chain to improve productivity and resource utilization [63]. In comparison with global trends in smart agriculture and precision farming, this study finds that while agricultural technology in Yan’an has promoted the integration process regionally, further exploration is needed to achieve a deeper integration of technology and industries, and create a sustainable growth model across the entire value chain [64].
In addition to improving agricultural productivity, technological innovation should focus on enhancing supply chain efficiency, introducing renewable energy in agricultural production, and advancing smart irrigation technologies to optimize water use. For instance, the application of IoT-based monitoring systems has been successfully used in precision agriculture to reduce water and energy use while increasing productivity [65]. Drawing lessons from precision agriculture practices in the United States and Japan, Yan’an could adopt similar data-driven models to align agricultural innovation with ecological protection. Studies in the United States and Japan have shown that integrating smart technologies such as drone-based monitoring and renewable energy systems can drive sustainable agricultural development [66].
To enhance the credibility of our findings, we compared our clustering results with alternative methods such as fuzzy clustering and decision tree analysis. While these methods also offer insights into regional development, our approach using K-means clustering and hierarchical analysis provided a more robust understanding of the varying levels of industry integration in Yan’an. Compared to fuzzy clustering, which often leads to overlapping group memberships, and decision tree analysis, which focuses primarily on specific drivers without emphasizing spatial differentiation, our method provided clearer insights into the stratified development needs across Yan’an’s counties [67]. This allows policymakers to target support more effectively based on robust classification results.
From the perspective of sustainable development, Yan’an’s integration process must balance economic benefits with ecological protection. Technological innovation should not be limited to increasing agricultural output but should also focus on reducing environmental impacts, particularly in areas such as water resource management and soil protection. In future integration development, technological innovation can be combined with sustainable development goals (SDGs) by adopting low-carbon, water-efficient production methods, which will enhance the resilience of the entire industry chain and promote comprehensive and coordinated development of the regional economy, society, and environment [68].

4.2. Synergy Mechanism Between Economic and Social Benefits and Policy Recommendations

The findings of this study indicate that rural industry integration has shown positive effects in both economic and social benefits. However, the sustainability and widespread impact of these effects remain challenging. Drawing on the industrial integration experiences of other countries (such as rural economic revitalization in the United States and urban-rural integration policies in Europe), it can be observed that improvements in social benefits often depend on long-term mechanisms for social infrastructure, public service equalization, and the fair allocation of resources. In Yan’an City, economic benefits have gradually emerged, but the enhancement of social benefits remains uneven across different regions [69].
For example, in the United States, rural economic revitalization has focused on fostering small and medium-sized enterprises (SMEs) in rural areas, providing subsidies for renewable energy projects, and leveraging community-level cooperatives to bridge urban-rural disparities. In Europe, policies such as the LEADER program have successfully leveraged local community engagement and resource pooling to enhance rural economic and social benefits [70]. These strategies highlight the importance of long-term investment in infrastructure and inclusive economic planning.
For Yan’an City, policies could focus on establishing cooperative models that incentivize farmers to participate in shared agricultural processing and marketing initiatives. Strengthening rural financial services, such as providing microloans and subsidies, can further boost rural participation in integrated industries. Empirical studies suggest that access to microloans and targeted subsidies significantly improves rural household participation in integrated agricultural industries [71]. Additionally, fostering public-private partnerships (PPPs) could help accelerate investments in education, vocational training, and digital infrastructure in underserved rural areas. These measures would promote both economic and social benefits, narrowing the urban-rural gap and fostering inclusive development.

4.3. Optimizing Regional Differences and Layered Policy Strategies

This study reveals regional differences in integration levels across different counties and districts in Yan’an City through cluster analysis, providing a basis for more targeted policy development. Yan’an City’s industrial integration development can benefit from the “layered policy” approach, adopting differentiated development strategies for high and low integration areas. For instance, high-integration regions (such as Baota District) can focus on developing high-value-added service industries, becoming demonstration and innovation centers for the entire city. Meanwhile, regions with lower integration levels (such as Wuqi County and Ansai District) should focus on improving infrastructure, enhancing agricultural industrial chains, and gradually reducing regional development gaps [72].
For high-integration areas, policies could focus on promoting low-carbon technologies, such as solar-powered irrigation systems and organic farming practices, to ensure that economic benefits do not come at the cost of environmental degradation. Meanwhile, in low-integration regions, efforts should prioritize soil restoration projects, sustainable forestry, and the development of basic green infrastructure to lay a foundation for further industrial integration. In regions with lower levels of integration, investments in basic infrastructure and ecological restoration have been shown to generate long-term economic and environmental returns [73].

4.4. Implications and Recommendations for Future Research

This study provides a preliminary theoretical and empirical foundation in the field of regional industry integration but still offers room for further development. For instance, the coupling coordination analysis and cluster analysis in this study are primarily based on time-series and static data. Future research could employ dynamic models to capture the long-term effects of industry integration more precisely. Dynamic panel data models or system dynamics simulations could be particularly effective in capturing the long-term feedback mechanisms between industrial integration and ecological impacts. Studies employing system dynamics models have demonstrated their efficacy in capturing feedback loops and long-term policy impacts in rural development [74,75,76,77].
Additionally, the indicators used in this study focus primarily on economic and social aspects, and future research could consider integrating ecological indicators such as carbon emissions, biodiversity indices, and water resource consumption to assess the environmental impacts of industry integration. For example, integrating ecological indicators into agricultural evaluation frameworks has been highlighted as a critical step in aligning with global sustainability goals [78,79].
Future research could also draw on modern data analysis techniques such as machine learning to conduct more accurate causal analysis, identify direct links between policies and industry integration outcomes, and uncover deeper factors influencing regional development. Machine learning techniques, such as random forests or gradient boosting algorithms, could be applied to identify the most influential factors driving successful integration outcomes. These methods allow for non-linear relationships to be captured, providing policymakers with more accurate insights into the causal mechanisms of industry integration [80].

5. Conclusions

The integration of primary, secondary, and tertiary industries in rural Yan’an City has significantly accelerated, with policy support and technological advancements driving the synchronized improvement of both economic and social benefits across regions. By analyzing data from 2012 to 2021, this study reveals the overall trends and driving factors of industrial integration, highlighting the important impact of policies and service sector development on the extension of rural industrial chains and the enhancement of social benefits. However, regional disparities in integration levels remain, with some remote areas facing constraints due to insufficient infrastructure and resource allocation. Overall, Yan’an City’s experience provides practical references for industrial integration in underdeveloped areas. Moving forward, it is essential to further integrate ecological benefit indicators and explore differentiated policy strategies to achieve sustainable and balanced industrial development.

Author Contributions

Conceptualization, Y.H. and Y.F.; methodology, X.R.; software, X.R.; validation, Y.W. and Y.F.; formal analysis, X.R.; investigation, G.R.; writing—original draft preparation, X.R.; writing—review and editing, D.Z.; funding acquisition, Y.F. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Northwest A&F University Innovation Team Project “Rural Revitalization Planning Innovation Team (2452023079).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

Thank the reviewers and editors for their insightful suggestions to the manuscript that improved the quality of the article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Time series trend of overall integration level in Yan’an City.
Figure 1. Time series trend of overall integration level in Yan’an City.
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Figure 2. Time series trend of integration process (A1) and integration benefits (A2) in Yan’an City.
Figure 2. Time series trend of integration process (A1) and integration benefits (A2) in Yan’an City.
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Figure 3. Correlation heatmap of third-level indicators (C1–C15) in Yan’an City.
Figure 3. Correlation heatmap of third-level indicators (C1–C15) in Yan’an City.
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Figure 4. Path plot of coupling and coordination degree between economic and social benefits.
Figure 4. Path plot of coupling and coordination degree between economic and social benefits.
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Figure 5. Hierarchical clustering dendrogram of Yan’an City’s districts and counties. Note:The different colors represent the three levels of integration of Yan’an City’s districts and counties: Orange for high integration level, pink for medium integration level, and blue for low integration level.
Figure 5. Hierarchical clustering dendrogram of Yan’an City’s districts and counties. Note:The different colors represent the three levels of integration of Yan’an City’s districts and counties: Orange for high integration level, pink for medium integration level, and blue for low integration level.
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Table 1. Evaluation index system of the integration level of rural primary, secondary, and tertiary industries in Yan’an City.
Table 1. Evaluation index system of the integration level of rural primary, secondary, and tertiary industries in Yan’an City.
Target LayerFirst-Order IndicatorsSecondary IndicatorsThree-Level IndicatorsUnitIndicator Attribute
Integrated development level of primary, secondary, and tertiary industries in rural areas of Yan’an CityRural industry integration process (A1)Agricultural industry chain extension (B1)Main business income from agricultural product processing (C1)billion yuanpositive
Ratio of main business income from agricultural product processing to total agricultural output (C2)%positive
Proportion of primary industry added value to GDP (C3)%positive
Agricultural multifunctionality expansion (B2)Rural broadband penetration rate (C4)%positive
Per capita grain production (C5)kg per personpositive
Fertilizer application intensity (C6)Kg/hm2negative
Agricultural service industry integration (B3)Total output value of agricultural, forestry, animal husbandry, and fishery services (C7)billion yuanpositive
Postal package volume (C8)ten thousand piecespositive
Growth rate of total agricultural output value (C9)%positive
Rural industry integration benefits (A2)Economic benefits (B4)Per capita disposable income of rural residents (C10)yuanpositive
Rural consumption retail sales (C11)billion yuanpositive
Ratio of per capita disposable income of rural residents to urban residents (C12)%positive
Social benefits (B5)Proportion of agricultural, forestry, and water affairs expenditure to fiscal expenditure (C13)%positive
Urbanization rate (C14)%positive
Rural non-agricultural employment rate (C15)%positive
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Ren, X.; Ruan, G.; Han, Y.; Zhang, D.; Wei, Y.; Feng, Y. Rural Industry Integration in Yan’an City: Development Trends, Driving Factors, and Regional Stratification. Sustainability 2025, 17, 1447. https://doi.org/10.3390/su17041447

AMA Style

Ren X, Ruan G, Han Y, Zhang D, Wei Y, Feng Y. Rural Industry Integration in Yan’an City: Development Trends, Driving Factors, and Regional Stratification. Sustainability. 2025; 17(4):1447. https://doi.org/10.3390/su17041447

Chicago/Turabian Style

Ren, Xiaoying, Guobing Ruan, Yimeng Han, Dingding Zhang, Yaqi Wei, and Yongzhong Feng. 2025. "Rural Industry Integration in Yan’an City: Development Trends, Driving Factors, and Regional Stratification" Sustainability 17, no. 4: 1447. https://doi.org/10.3390/su17041447

APA Style

Ren, X., Ruan, G., Han, Y., Zhang, D., Wei, Y., & Feng, Y. (2025). Rural Industry Integration in Yan’an City: Development Trends, Driving Factors, and Regional Stratification. Sustainability, 17(4), 1447. https://doi.org/10.3390/su17041447

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