Empirical Analysis on the Mechanism of Industrial Park Driving Urban Expansion: A Case Study of Xining City

Abstract

Taking Xining City as an example, this article analyzes the mechanism by which industrial park construction drives the expansion of urban population size and built-up area, based on a review of the process of industrial park development and urban population growth. It also discusses future urban governance models in light of urban development trends. The research finds: (1) In the process of urban development, industrial park construction is often the initial factor in the cumulative and cyclical development of a city; (2) As the level of development improves and the mode of economic growth changes, the government should timely adjust its strategies, shifting from the expansion of industrial park construction towards structural optimization and quality improvement. The most significant difference from previous research is that this paper emphasizes the importance of government planning. This study can not only demonstrate the general process of industrial parks promoting urban expansion, but more importantly, it explains the fundamental reasons for the transition of urban expansion to adjustment from a mechanism perspective, thereby eliminating the drawbacks of simply predicting urban scale evolution through data models.

1. Introduction

Urban population serves as a crucial carrier of urban nature and function. Understanding and grasping the mechanisms and processes underlying changes in urban population size are foundational for urban managers to determine reasonable urban population sizes in urban planning, accurately judge and predict future urban trends, and more importantly, establish a rational urban governance way. In the research on population size prediction, major methods include the Logistic model [1], the Grey model [2], and the neural network model [3], as well as the Grey-neural network model [4,5,6] derived from the combination of the Grey model and the neural network model. These models all statistically analyze historical data on factors affecting changes in urban population size, explore their temporal variation patterns, and derive long-term trends in population size changes to predict their future variations [7]. These methods are mostly applicable to regions or entire countries with low cross-border migration speeds and small migration scales. For cities undergoing rapid urbanization, influenced by numerous factors, and experiencing significant uncertainty in population changes, model predictions based on historical data have been criticized for their accuracy [8,9,10]. More importantly, while models can output future evolution results, they cannot reveal the mechanisms and reasons behind these results. In the process of urban development and growth, apart from natural population changes, economic growth drives employment expansion, which attracts a large influx of migrant populations, further propelling population size growth. This increased population size, in turn, fuels urban economic growth, forming a cumulative cyclical process that is the fundamental mechanism sustaining urban population development.

According to the theory of cumulative cyclic causality, in a dynamic social process, there exists a cumulative cyclic causal relationship between various socioeconomic factors. A change in one socioeconomic factor will induce a change in another socioeconomic factor, which, in turn, reinforces the initial change and leads the socioeconomic process to develop along the direction of the initial change, thereby forming a cumulative cyclical development trend [11]. Economic growth drives employment expansion, which facilitates labor transfer and agglomeration, further leading to population agglomeration in cities [12,13], promoting the expansion of urban population size and land use scale. Conversely, the growth of urban population size also drives economic growth. Since the reform and opening-up policy, numerous cities in China have established various types of development zones, industrial parks, and new towns, which have played a significant role in economic development. Many of these have served as “initial factors” at certain stages, driving rapid urbanization and becoming urban growth poles [14]. The role of various development zones, industrial parks, and even new urban areas in urban development is not difficult to understand, but there is a lack of systematic analysis and empirical research on how these new areas propel urban development. Secondly, since the 18th National Congress of the Communist Party of China, innovative and green development have become the themes of the era. Cities at all levels are gradually abandoning their original extensive development models and transforming and adjusting various industrial parks and economic development zones. After high-speed expansion and subsequent adjustment in industrial parks, it is necessary to delve into the processes and situations that urban development will undergo. Lastly, in the process of urban development, guided by different stages and goals, the concepts and methods of urban governance will change accordingly [15]. How should urban governance adjust to changes in the urban development process?

Taking Xining City, Qinghai Province, as an example, this paper analyzes the mechanism by which the construction of industrial parks drives urban development and urban population expansion, aiming to conduct a comprehensive and deep study on this issue. This study can not only demonstrate the general process of industrial parks promoting urban expansion, but more importantly, it explains the fundamental reasons for the transition of urban expansion to adjustment from a mechanism perspective, thereby eliminating the drawbacks of simply predicting urban scale evolution through data models.

2. Research Methods and Data of the Case Study Area

This study takes Xining City as an example to analyze the mechanism of how industrial park construction promotes urban population and land expansion based on the cumulative causation theory. Also known as the circular cumulative causation theory, this theory was first proposed by renowned economist Gunnar Myrdal in 1957 and later developed and formalized into models by Nicholas Kaldor, R.W. Dixon, and Gunnar Myrdal himself, among others. Myrdal and his colleagues believed that in a dynamic social process, there exists a circular and cumulative causal relationship among various socio-economic factors. A change in one socio-economic factor triggers a change in another, which in turn reinforces the initial change, leading the socio-economic process to evolve in the direction of the initial change, thus forming a cumulative and circular development trend [16,17,18]. Based on this concept, the analytical framework proposed in this paper is illustrated in Figure 1.

Another explanation for the driving force behind the development of industrial zones lies in the industrial clustering effect [19]. Clusters are formed by interconnected enterprises and institutions that are geographically concentrated and belong to similar industries within a specific field [20]. Industrial clusters are a common phenomenon in the process of industrialization, and various industrial clusters can be clearly seen in all developed economies [21]. The rise of industrial clusters stems from the discovery of positive externalities of agglomeration by scholars such as Marshall [22]. The agglomeration of enterprises in industrial clusters can build a stable regional innovation network [23], generating network effects and knowledge spillover effects, thereby driving the development of industrial parks. The coupling of internal and external networks within industrial agglomerations can bring about complementary and win-win results. The local innovation network is an essential guarantee for the spillover of relevant knowledge within the cluster, while the external global innovation network can, to a certain extent, bring more heterogeneous knowledge to the local cluster, thereby promoting the development of local innovation clusters [24]. Due to the similarity in cognition, technology, and other aspects brought about by geographical proximity, the internal connections within the cluster arise from the flow of homogeneous innovation knowledge with a high degree of relevance [25]. Related diversification is an important foundation for effective knowledge spillover [26].

Xining City, located on the eastern edge of the Qinghai–Tibet Plateau, in the eastern part of Qinghai Province, and within the river valley basin in the middle reaches of the Huangshui River, is the capital of Qinghai Province and one of the key cities in the Lanzhou-Xining urban agglomeration. It is an important city supporting the ecological security barrier of the Qinghai–Tibet Plateau and maintaining prosperity and stability in the northwest region. Xining City administers five districts and two counties, with a total municipal area of 7660 km². In 2020, the resident population was 2.468 million, with an urban population of 1.9406 million and an urbanization rate of 78.63%. The urban population in the central city area was 1.739 million, and the built-up area of the central city was 208 km². Xining is the only provincial capital city on the Qinghai–Tibet Plateau with an urban population exceeding one million and a built-up area exceeding 100 km². In 2020, the total GDP of Xining City was CNY 137.298 billion, accounting for 46.26% of the total GDP of Qinghai Province, with a per capita GDP of CNY 55,631, which is 13.58% higher than the provincial average.

Since 2000, within the central city area composed of five municipal districts including Chengzhong District, Chengdong District, Chengxi District, Chengbei District, and Huangzhong County (District), Xining City has successively established the Xining (National) Economic and Technological Development Zone, High-tech Industrial Development Zone (Biotechnology Industrial Park, located in Chengbei District), Chengnan New Area, Haihu New Area, Beichuan Industrial Park, and other new urban functional areas. Among them, the Xining (National) Economic and Technological Development Zone adopts a diversified management model within one zone, including the Dongchuan Industrial Park located in Chengdong District, the Ganhe Industrial Park located in Huangzhong County, and the Nanchuan Industrial Park located in Chengzhong District (see Figure 2). Driven by the development and construction of industrial parks and new urban areas, Xining City has entered a high-speed phase of economic and population growth as well as built-up area expansion, providing an excellent sample for observing and studying the expansion of population size and urban environmental changes driven by industrial parks.

The population data for the main years in this article are primarily derived from the five population censuses conducted from the beginning of reform and opening-up until 2020. The population data, labor and employment data, and economic data for other years are sourced from the statistical yearbooks of Xining City from 1990 to 2021. In cases of inconsistent data within the statistical yearbooks, the data from the most recent year’s statistical yearbook are used. Relevant information on industrial parks, new urban areas, and built-up areas is obtained from the Xining Development and Reform Commission, the Economic and Technological Development Zone Management Committee, as well as policy documents such as the “Twelfth Five-Year Plan for National Economic and Social Development of Xining City”, the “Thirteenth Five-Year Plan for National Economic and Social Development of Xining City”, and the “Fourteenth Five-Year Plan for National Economic and Social Development of Xining City”. All maps were produced by the authors using ArcGIS 10.5.

3. Industrial Park Construction and Urban Scale Expansion

3.1. Process of Industrial Park Construction and Urban Population Expansion

As a western inland province with ethnic minorities as the main population, compared to eastern regions and other parts of the country, Xining City implemented reform initiatives and related policies relatively late in the process of reform. In 1979, the Shekou Industrial Zone in Shenzhen was established, and in 1984, China’s first batch of economic and technological development zones was newly established. By 1999, the total number of various urban new areas reached 815 [14]. However, as the capital city of Qinghai Province, Xining City was not approved to start construction of its first development zone, the Xining Economic and Technological Development Zone, until 2000. The development zone is located in Chengdong District, the eastern part of Xining City, Qinghai Province, and was renamed the Dongchuan Industrial Park of the Xining Economic and Technological Development Zone in 2006. Soon after, in April 2002, the Biotechnology Industrial Park was established in Chengbei District of Xining City, and in July 2002, the Ganhe Industrial Park was established in Huangzhong County (now Huangzhong District). The three industrial parks were unified and incorporated into the management system of the Xining Economic and Technological Development Zone in 2005 and 2006, forming a management framework of one zone with three parks. In February 2008, the Nanchuan Industrial Park of the Xining Economic and Technological Development Zone was established in Chengzhong District, forming a layout of one zone with four parks. In November 2010, the Biotechnology Industrial Park was upgraded to a national high-tech industrial development zone upon approval by the State Council and named the Qinghai High-tech Industrial Development Zone, becoming the only national high-tech zone in Qinghai Province. It was separated from the management system of the economic and technological development zone in 2017 for independent management.

As a carrier and engine driving rapid economic development, industrial parks have gradually played their role. In the 10 years before 2000, Xining City’s average annual GDP growth rate was 7.56%, with the highest year being 1998 at 10.1%. In other years, it did not exceed double digits and was not significantly different from the economic growth rate of Qinghai Province (see Figure 3). However, Xining’s economic growth continued to rise and gradually surpassed the provincial economic growth rate, reaching a peak of 18.2% in 2010. It maintained a double-digit growth rate for 16 consecutive years until it dropped to 9.8% in 2016, far exceeding the economic growth rate of Qinghai Province. This period roughly coincides with the development and construction of industrial parks, and the contribution of industrial parks to economic growth has gradually increased. In 2007, the industrial added value of the four major industrial parks accounted for 25.7% of the city’s total industrial added value. By 2009, the proportion exceeded 50% for the first time, reaching 50.51%, and peaked at 73.9% in 2016. After 2016, although the proportion of industrial added value from the parks in the city began to decline, it still accounted for about 55% by 2019, before the outbreak of the pandemic (see Figure 4).

Rapid economic growth inevitably generates significant demand for labor. During the “12th Five-Year Plan” period from 2006 to 2010, Xining City created 95,000 new urban jobs. During the subsequent “12th Five-Year Plan” period from 2011 to 2015, the cumulative number of new urban jobs reached 150,400. During the “13th Five-Year Plan” period from 2016 to 2020, the cumulative number of new urban jobs was 159,000, and by 2020, the number of urban employees in Xining City surpassed one million, reaching a high of 1.04 million. Correspondingly, the urban population increased from 910,000 in 2000 to 1.1483 million in 2010 and reached 1.688 million in 2020, with an increase of 778,000 urban residents over the past 20 years. In contrast, during the entire 90s of the last century, the urban population of Xining City increased by only 260,000 (see Figure 5).

3.2. Process of Urban Built-Up Area Expansion

The construction of industrial parks and new cities relying on these parks has driven rapid expansion of Xining’s urban area. The built-up area expanded from 52 km² in the early 2000s to 91 km² in 2010 and reached 208 km² by 2020 (see Figure 6 and Figure 7), representing an increase of 108% over the past decade. In contrast, during the entire 90s of the last century, the built-up area of Xining increased by only 2 km². The expansion of the built-up area has been achieved through two modes, where one is the expansion driven by the construction of industrial parks themselves. The Dongchuan Industrial Park, the first established in Xining, has a planned area of 12.79 km²; the Biotechnology Industrial Park initially had a planned construction area of 10 km²; the Ganhe Industrial Park has a planned area of 10.89 km²; and the Nanchuan Industrial Park has a planned area of approximately 10 km². By around 2010, except for the Dongchuan Industrial Park due to terrain constraints, the other three industrial parks had all undergone expansion, with the Biotechnology Industrial Park expanding by 23.5 km², Nanchuan expanding to 31.39 km², and Ganhe Industrial Park reaching 35.28 km². The planned area of the parks increased from the initial 53.78 km² to 101.06 km².

With the development of information technology, the dominant type of industrial parks has gradually shifted from suburban or suburban-like park models to urban models with more “urban characteristics” [15]. As the urban population grows, new city construction has become another major pathway for the expansion of Xining’s built-up area. When the Ganhe Industrial Park underwent its second expansion in 2008, it also initiated the Kangchuan New City relocation and resettlement project involving 26,000 people. As the largest relocation and resettlement project in Qinghai Province at that time, it was equipped with medical, educational, commercial, cultural, and other living service facilities. The construction of the Ganhe Industrial Park also facilitated the transformation of Huangzhong County into a district, becoming part of Xining’s urban area in 2019—Huangzhong District. During the construction of the Nanchuan Industrial Park and the Ganhe Industrial Park, Xining developed the Chengnan New Area between the Nanchuan Industrial Park in the southern part of the city and the Ganhe Industrial Park, with a total area of 30 km². In 2007, construction of the Haihu New City began in the Chengxi District, covering an area of 10.5 km² and planned to accommodate a population of 150,000. In 2014, relying on the Biotechnology Industrial Park (Qinghai National High-tech Industrial Development Zone), the Beichuan New Area was officially developed and constructed, with a planned area of 8.6 km². Many new campuses of universities such as Qinghai University and Qinghai Normal University are located in the new area. The construction of three new cities relying on the three major industrial parks in the south, north, and west has basically completed the expansion of Xining’s central urban built-up area, forming the current built-up area of 208 km².

From the perspective of the entire process of Xining’s urban development, industrial parks have been the “initial factor” driving urban development since 2000. This “initial factor”, under the cumulative and circular causal law, has brought rapid economic growth and increased the urban employment capacity, thereby driving the expansion of the urban population and land use. The expansion of the city scale, in turn, promotes economic growth, creating a virtuous cycle. This process of development and expansion is summarized and illustrated in the following diagram (see Figure 8).

4. Transformation of Economic Growth Patterns and Trends in Urban Evolution

4.1. Adjustment and Transformation of Economic Growth Patterns

The rapid expansion of urban population size and land use scale will inevitably put pressure on the ecological environment, leading to sustainable development issues [26]. Since the 18th National Congress of the Communist Party of China, the country has increasingly emphasized the quality of economic development rather than solely emphasizing the speed of development. Economic development has shifted from the unsustainable model that relied on extensive resource input to a sustainable development model mainly driven by technological progress and improvements in labor productivity. On the one hand, the economy has entered a new stage of medium-to-low-speed development from high-speed growth. Since 2013, Xining’s economic development has entered a downward trend, necessitating the exploration of new economic growth points. On the other hand, the pressure on the ecological environment caused by large-scale development has prompted the city to adjust its development strategy. In the “12th Five-Year Plan”, the Xining municipal government proposed to “increase industrial structural adjustments, significantly reduce energy and resource consumption and environmental pollution through technological innovation and technological transformation, gradually form a sustainable development model, establish and improve the characteristic industrial system, and embark on a path of new industrialization”. During the “13th Five-Year Plan” period, Xining intensified the adjustment of industrial parks, proposing that each industrial park should focus on its leading industries, promote industrial upgrading, rationally divide labor in space, improve land use efficiency, and form agglomeration advantages: “Dongchuan focuses on silicon material photovoltaics and light alloy materials; Nanchuan focuses on lithium-ion battery new energy and Tibetan carpet and woolen textile industry; Chengbei focuses on biomedicine and equipment manufacturing; Ganhe focuses on non-ferrous metal deep processing and specialty chemicals; Beichuan focuses on high-tech industries”. The recent “14th Five-Year Plan” identifies green development and innovation development as the two core pillars of Xining’s development: “Accelerate the formation of a system, industrial system, and production and lifestyle that match ecological protection, follow the path of green development, and build an ecological civilization city; adhere to the core position of innovation in the overall situation of modernization, accelerate the construction of a modern industrial system, and actively promote high-quality development”.

The shift from past extensive development to the pursuit of high-quality development will reshape the trajectory of urban development. Improvements in labor productivity will further reduce the employment elasticity coefficient of economic growth, lower the labor absorption capacity, and thereby reduce the speed of urban population agglomeration. At the same time, due to the decline in the birth rate and the increase in the aging population, although the child dependency ratio of the working-age population has decreased, the elderly dependency ratio has increased. The migrant population is the main source of population growth in central cities, and changes in the bringing-family coefficient will also be an important factor affecting future urban scale changes.

4.2. Changes in the Employment Elasticity Coefficient of Economic Growth

Different economic growth patterns and different industrial types have different labor demand intensities and labor intensity at different stages of development, leading to varying abilities to drive new employment through economic growth. Since 2013, Xining’s economy has entered a downward trend, and along with the decline in development speed, the scale of new employment brought by GDP growth has also shown a downward trend, manifested as a decline in the overall employment elasticity coefficient. From 2000 to 2013, the employment elasticity coefficient of economic growth in Xining was above 0.3 in most years, with the highest reaching 0.55 in 2011. After 2012, the employment elasticity coefficient gradually declined, with no year exceeding 0.3, and the highest in 2016 was only 0.27 (see Figure 9). Especially for the secondary industry, with industrial parks as the main carrier, after experiencing scale expansion, the number of employees peaked in 2011 and 2012 and then tended to decline (see Figure 10), contributing most significantly to the decline in the employment elasticity coefficient. It can be seen here that the decline in the employment elasticity coefficient is not only driven by the government’s proactive response and active promotion but also an objective requirement for industrial upgrading and development to a certain extent.

4.3. Dependency Ratio and Changes in Urban Population Size

The urban economy is an economic system primarily based on the secondary and tertiary industries. Employment expansion in cities leads to spatial migration and agglomeration of population, thereby driving the expansion of urban size and being the primary mode for the growth and development of urban population size. In terms of net population migration, since 2000, the net migration of population in the central urban area of Xining has been continuously increasing, particularly evident in Chengdong District and Chengbei District. The net migration of population in the four central districts increased from 295,000 in 2010 to 522,700 in 2020 (see

Table 1. Net migration of population in Xining City counties and districts in major years (10,000 people).

Year	Chengdong District	Chengzhong District	Chengxi District	Chengbei District	Huangzhong District	Datong County	Huangyuan County
1990	2.27	——	−3.89	——	0.31	0.41	0.05
2000	9.11	——	4.91	4.65	0.21	1.51	0.02
2010	11.1	6.62	3.26	8.56	−2.71	−1.04	−0.07
2020	22.56	7.23	5.4	17.08	−8.64	−2.66	−1.85

). The fundamental purpose of migration for non-household registered individuals is to secure employment and earn income. The results of net population migration in different districts and counties of Xining demonstrate the relationship between employment expansion and urban population growth. Although the employment elasticity coefficient of economic growth in Xining declined in the latter half of the past 20 years, the expansion of economic and employment scales still significantly contributed to population growth. Furthermore, the magnitude and trend of urban population growth, along with changes in the dependency ratio resulting from demographic structural evolution, are also important factors influencing employment-driven population changes.

The dependency ratio in Xining has experienced a trend of first decreasing and then increasing. It declined from nearly 2.5 in the early 21st century to around 2.0 in 2008 and further dropped to its lowest point in 2016. Since 2016, it has gradually risen over the past five years, forming a “U”-shaped trend (see Figure 11). This changing trend has solid practical implications and is influenced by changes in the population’s age structure. As shown in Figure 10, the total dependency ratio in Xining was 47.85 in 2000 and then declined to 40.52 in 2010. The primary reason for this decline was the significant drop in the child dependency ratio due to the decrease in the birth rate. In 2020, the total dependency ratio rose again to 43.82, primarily due to the impact of population aging, where the elderly dependency ratio increased significantly while the child dependency ratio remained relatively stable (see Figure 12). The evolution of the population structure is the root cause of changes in the dependency ratio. The changes in Xining indicate that with the adjustment of China’s family planning policy, while the birth rate and child dependency ratio remain stable, the increasing trend of aging will lead to a rise in the dependency ratio. This will be an important factor in judging the future changes in urban scale in China.

Another phenomenon emerging in the stage of high-quality development is the continuous optimization of urban land use structure, the improvement of public facilities, and the enhancement of urban space. In the process of urban population expansion, the expansion of built-up areas into urban districts has provided possibilities for incorporating larger green spaces and conditions for the renovation of old urban areas. In 2020, Xining established 124 parks and street green spaces. The green space ratio in built-up areas increased from 18.7% in 2000 to 35.6% in 2010 and 40.02% in 2020. The per capita public green space area rose from 3.94 m² to 12.82 m² (see

Table 2. Green space rate and public green space per capita in built-up areas of Xining City from 2000 to 2020.

	Year	2000	2005	2010	2015	2020
Road area per capita (m2)		6.48	6.81	7.35	7.8	12.9
Green space rate of Built-up areas (%)		18.7	28.0	35.6	39.02	40.02
Public green space per capita (m2)		3.94	6.16	9.00	12.0	12.82

). The improvement in the livability of the urban environment has increased its attractiveness, which is one of the factors driving population agglomeration. In the 14th Five-Year Plan, the Xining Municipal Government further proposed to “build a high-level park city”.

In the process of transforming economic growth from an extensive mode to a high-quality one, the decline in economic growth rate and the functional adjustment of industries and industrial parks have led to an increase in labor productivity, with a decreasing employment elasticity coefficient as a long-term trend. Along with the improvement of economic development, the decline in the birth rate and the deepening of aging are also long-term trends in social development, driving the dependency ratio to first decrease and then increase. The dual overlapping effects of the dependency ratio and the employment elasticity coefficient mean that compared to the period of extensive development, the growth rate of urban population will slow down, leading to a slower pace of land expansion and ushering in a period of internal optimization and adjustment for urban space. This process can be illustrated by Figure 13.

5. Conclusions and Discussion

Industrial parks are crucial factors driving urban economic growth and urban expansion. This study finds that the construction of industrial parks is often the “initial factor” in the cumulative and cyclical development process of cities. Firstly, in the urban development process, the construction of industrial parks drives the economy to a new growth platform, expands the capacity to absorb labor, drives population agglomeration, and provides impetus for the construction of new urban areas. The construction of new urban areas and the expansion of industrial parks become the two major ways for the expansion of built-up areas, marking the first wave of urban development driven by industrial parks. Secondly, with the improvement of the development level, the transition from an extensive development mode solely pursuing economic growth rate to a higher-quality development mode promotes the adjustment of industrial parks, the reorientation of industrial development, and leads to a decline in economic growth rate and the employment elasticity coefficient of economic growth. On this basis, coupled with changes in the dependency ratio caused by demographic structural changes, it results in a decrease in urban population growth and urban construction land expansion. At this point, the city enters a stage of internal land optimization and adjustment, accompanied by the improvement of urban infrastructure and the gradual increase in urban per capita road area and per capita green area, marking the second wave of intensive urban development. The understanding of the process and mechanism of urban expansion driven by the construction, development, and adjustment of industrial parks, as well as the changes in the employment elasticity coefficient and the dependency ratio brought by demographic structural changes, is a key to predicting urban population size. The “initial factor” or the dominant factor leading to development and change may vary in different cities, but understanding the process and mechanism and recognizing the development patterns of the studied city should be the premise for future predictions.

After the second phase of optimization and adjustment, during the pandemic years of 2021, 2022, and 2023, Xining’s GDP growth rates reached 8.1%, 2.1%, and 8.6%, respectively. Notably, the GDP growth rates in 2021 and (hypothetically) 2023 surpassed the provincial average by 2.4 and 3.4 percentage points, respectively. This underscores the role that Xining’s optimization of industrial parks has played in driving economic recovery post-pandemic. In 2023, China’s urbanization level reached 66.2%, entering the middle to late stages of urbanization. Based on the two-stage process of urban scale development driven by industrial parks, promoting urban intensification and sustainable development is not only a necessity for the situation and practical development but also supported by the theory of urban development patterns. In the future, with the continuation of the new normal of economic growth, labor productivity will increase with the improvement of the development level, the employment elasticity coefficient will decline, and the trend of large-scale urban expansion across the country will further reverse. Both urban population and land scale will enter a period of stable development. The focus of urban construction will shift from expanding urban scale to enhancing urban quality [27], and correspondingly, urban governance concepts and practices must also adapt to this transformation [15]. During the period of rapid urban expansion, the “incremental” construction of industrial parks and new towns must be addressed through an “incremental” governance model, expanding the spatial scope of urban governance and transitioning from a rural governance model to an urban governance model. When cities enter the “stock” construction period of stable development, the emphasis is on the optimization and upgrading of “stock”, with “stock” governance as the main focus, targeting the construction of livable, innovative, smart, green, humanistic, and resilient cities [28], and improving the scientific and refined level of urban governance with people as the core.

While industrial parks cannot explain all the reasons for urban expansion, they are a significant force and one of the key paths for promoting urban development. As a city in the underdeveloped western region of China, the study of Xining shows that for economically underdeveloped areas, following the conventional path of development is challenging to achieve economic “catch-up” and reverse their lagging status. However, through the concentrated development of industrial parks, improving the local investment environment, and enhancing infrastructure quality, it becomes possible to achieve catch-up growth. Nevertheless, the construction of industrial parks is a gradual process that must be coordinated with national and even global macroeconomic trends, avoiding unlimited development that could lead to disorderly expansion or even the emergence of “ghost cities”. Strategies must be flexibly adjusted according to different development stages and changes in macroeconomic conditions, with comprehensive support in land development and consolidation, infrastructure construction, labor and social security, and other aspects. All industrial parks in Xining are under the unified management of the Xining Municipal Government. To avoid vicious competition among different industrial parks, the government has conducted precise positioning and overall planning for the functions of each park. This highlights the critical importance of coordinating the positioning of different industrial parks within the same region.

The previous research on industrial districts and clusters emphasized the innovation networks formed within clusters by enterprises, as well as the knowledge sharing and spillover effects that arise from multiple similarities. These effects emerged spontaneously among enterprises. However, the most significant difference from previous studies lies in the emphasis placed on the importance of government planning in this paper. Specifically, it highlights that, especially in economically underdeveloped regions, governments should seize opportunities in a timely manner based on external environments and internal development needs, proactively promote the construction of industrial parks, and adjust the development strategies of industrial districts according to external and internal changes. This proactive approach is crucial for regional economic development.