1. Introduction
For cities, which are the primary engine of economic and social progress, urbanization is an irreversible globalization trend in the process of development. Based on the World Cities Report 2022, released by UN-Habitat, the urban population constituted 56% of the overall global population in 2021 and is expected to increase to 68% by 2050. As global urbanization continues to advance, natural disasters and public safety incidents such as extreme weather, earthquakes, financial crises, and the COVID-19 pandemic are occurring frequently. These calamities continuously challenge cities’ capacity to withstand and mitigate risks, severely constraining safety and sustainable development [
1]. Among these, developing countries bear a heavier burden from disasters compared to developed nations. In particular, China, as the largest developing country, had an urbanization rate of 66.16% in 2023, with a proportional increase in a variety of urban problems such as extreme events and natural disasters [
2,
3]. According to the official data, China experienced varying degrees of impact from natural disasters affecting 95,444,000 people in 2023, with direct economic losses totaling CNY 345.45 billion. Given these challenges, it has become an urgent imperative to ensure the stable and secure operation of cities and the attainment of sustainable development.
With the escalation of instability risk, resilience has been gradually incorporated into urban-planning studies, and UR has become a key strategy for achieving sustainable development. The term “resilience” stems from the Latin word “
resilio”, which means “restore to an original state” [
4]. Its concept has evolved from “engineering resilience—ecological resilience—evolutionary resilience” [
5]. Given the complexity of urban systems, evolutionary resilience provides a foundational framework for UR research [
6]. UR is a capacity for change, adaptation, and alteration inspired by complex socio-ecological systems in response to pressures and constraints [
7]. UR breaks through the traditional rigid thinking of urban safety management. Beyond focusing solely on disaster resilience, it also emphasizes the improvement of the city’s adaptive, restorative, absorptive, and learning capacities through the systematic integration of elements [
5]. This provides a new way of managing risks and addressing urban challenges. In recent years, the Chinese government has increasingly prioritized UR. The 14th Five-Year Plan (2021–2025) has explicitly proposed the construction of resilient cities, called for improving the level of urban governance and strengthening risk prevention and control in the megacities’ governance. Concurrently, the Chinese government has launched pilot programs such as Sponge City and Climate-Adaptive City to enhance UR and foster urban development.
As the importance of UR continues to be recognized, the study of its enhancement dynamics has become a focus of scholarly research. From the point of the intrinsic economic drivers, some scholars have identified that various elements, such as human capital [
8], infrastructure development [
9], industrial structure [
10], and innovation activities [
11], all have a certain impact on UR. From the point of view of policy instruments, some scholars have revealed that the institutional environment of a region is a crucial determinant of UR [
12]. Ezcurra and Rios [
3] found that urban economic resilience was closely associated with the quality of local governments, noting that effective local governance can bolster urban economic resilience. Similarly, Lu and Teng [
13] verified that innovative urban policies, which functioned through efficient markets and responsive governance, played a vital role in enhancing urban economic resilience. Taken together, the existing studies offer valuable insights into improving UR. However, there remains a gap in the literature regarding UR from the standpoint of land allocation.
As a crucial element and spatial foundation of urban economic activities [
14], the allocation mode and efficiency of land utilization directly correlate with the resilience of cities and sustainable development. Since the reform and opening up, China’s approach to land supply has experienced several revolutions, realizing a shift from allocation in a planned manner to market-oriented mechanisms by “tendering, auctioning, and listing”. Unlike developed countries such as the United States, which utilize a market-oriented land allocation system, LM in China does not equate to privatization, but only the marketization of the method of offering land. Based on the data from the China Land Market Transaction Network, the proportion of urban land transferred through “tendering, auctioning, and listing” has increased significantly, rising from 46% in 2001 to 91% in 2021. This trend indicates a deepening marketization of land resources. Simultaneously, related research is emerging. Multiple studies have demonstrated that LM has generated substantial “institutional dividends”, effectively addressing issues of land resource mismatches and inefficient utilization [
15,
16], while also fostering urban economic development [
17,
18]. Furthermore, research on the economic impacts of LM is expanding in the direction of adapting to the characteristics and planning of economic development. Some scholars have focused on the environmental consequences of LM, arguing that it can lower energy consumption and enhance green total factor output [
19,
20,
21]. Yuan and Zhao [
22] found that spatial mismatches in construction land significantly hinder the resilience of urban economies. These findings underscore the considerable influence of LM on urban system development.
To summarize, while the existing literature provides valuable insights, some limitations also remain. Specifically, despite numerous studies focusing on UR and LM separately, few have integrated them into a unified research framework. Prior research on the correlation between LM and urban development has predominantly explored economic or ecological effects, ignoring the complexity of cities as systems comprising multiple subsystems whose interactions shape urban development. Therefore, this raises the following research question of this paper: Does LM affect the urban system resilience? And what are the specific mechanisms involved?
To answer the above questions, this paper integrates LM and UR within a comprehensive framework and analyzes their relationship. Initially, it constructs a systematic framework and a comprehensive assessment index system for UR, employing the entropy method for measurement. Subsequently, building on a robust theoretical foundation of the mechanisms through which LM affects UR, the paper empirically estimates both direct and indirect impact between the two using panel data from Chinese prefecture-level and above cities from 2001 to 2021. The conclusions drawn from this study aim to provide insights and recommendations for enhancing UR and promoting sustainable development.
The primary contribution of this study is mostly found in the following aspects: Firstly, despite a substantial body of research that has analyzed the driving factors of UR, there remains a gap in understanding the impacts of LM. Furthermore, previous studies investigating the impacts of LM have predominantly focused on economic or ecological aspects alone. UR is a multidimensional and complex system. This paper links LM with system resilience, which not only enriches the research on drivers of UR from the standpoint of land resource distribution but also broadens the investigation of the effects of LM. Secondly, this paper systematically and comprehensively analyzes the influence mechanism of LM on urban system resilience toughness from resource allocation, industrial structure upgrading, and technological innovation; opens up the “black box” of the role between the two; and improves the theoretical extension of the process of both. Thirdly, this paper utilizes data at the city level for empirical research, enabling a nuanced exploration of the influence relationship and providing practical insights for the advancement of UR systems in the new era.
The subsequent organization is as follows: The “Theoretical Analysis and Research Hypotheses” section constructs a conceptual framework for UR, develops the hypotheses, and builds a theoretical model. The “Methodology and Data Sources” section presents research methods, definitions of variables, and the research data collected. The “Empirical Results and Analysis” section reports empirical results, which include a spatiotemporal analysis, benchmark analysis, robustness test, mechanism analysis, and heterogeneity analysis. The “Discussion” presents the results, offers policy recommendations, and clarifies research limitations.
5. Conclusions and Discussion
5.1. Conclusions
China, as the world’s largest developing country and the second-largest economy, plays a crucial role in achieving the Sustainable Development Goals (SDGs) through its efforts to promote UR. This paper investigates the direct and indirect effects of LM on UR using panel data from Chinese prefecture-level and above cities, spanning from 2001 to 2021. The main findings are as follows: (1) LM efficiently facilitates UR, and the results remain strong even after undergoing several robustness tests. (2) The mechanism analysis shows that LM serves not only a direct role but also an indirect role through resource allocation, industrial structure optimization, and technological innovation. (3) The heterogeneity analysis shows that cities with better geographic locations, larger population sizes, and lower administrative levels are more effective in improving UR as a result of LM.
5.2. Discussion
More specifically, our empirical analysis is divided into two primary components. The first part examines the direct impact of LM on UR. The second part analyzes the path of influence between the two on this basis, aiming to open the “black box” of the impact process of LM on UR.
Firstly, the results show that LM plays a significant positive role in the enhancement of UR. Specifically, when LM increases by one standard deviation, the mean value of UR increases by 7.8% accordingly. Previous studies have shown that LM can promote economic growth, ecological protection, etc. [
18,
20]. Our results once again confirm the positive outcomes and expand the research on LM effects by focusing on urban system resilience. As the carrier of urban production activities, LM effectively mitigates rent-seeking and corruption [
57], addresses mismatches and inefficiencies in land resources [
15], relieves the pressure on urban finances, fosters infrastructure improvement, and strengthens the ability to deal with various external shocks.
Secondly, in promoting UR, LM serves not only a direct role but also an indirect role through resource allocation, industrial structure optimization, and technological innovation. These findings are consistent with those of previous research, which indicates that resource allocation, industrial structure upgrading, and technological innovation are pivotal for enhancing urban risk management and UR [
10,
12,
90]. Specifically, these three effects contribute to a more sensitive perception of urban risk, a better response when risk occurs, and a faster repair after disaster, thereby contributing to sustainable urban resilience.
Thirdly, the effect of LM areas varies across cities. This promotion effect is significantly stronger in large cities than in small- and medium-sized cities. Additionally, it is more pronounced in the eastern regions of the country compared to the central and western regions and is greater in prefectural-level cities than in cities at the sub-provincial level and above.
5.3. Policy Suggestions
Based on the results described above, some policy recommendations are presented for promoting UR.
Firstly, we recommend continuously improving the market-oriented land transfer system. The empirical data demonstrate that LM contributes to the enhancement of resilience. Hence, local governments must persist in advancing market-oriented land reforms through enhancing the land system. On the one hand, it is necessary to clearly define the authority and obligations of local governments during the land transfer process. On the other hand, it is necessary to enhance the oversight and evaluation of the land transfer activities carried out by local governments. This is to ensure that the land transfer procedures are legal and the land use is in compliance with the law.
Secondly, we recommend optimizing resource allocation and stimulating efficiency. From the empirical results, LM can enhance UR through resource allocation. Therefore, government departments should foster a favorable market environment that promotes the unrestricted flow of various production factors and ensures their optimal allocation. Additionally, collaboration among various stakeholders—universities, research institutes, and enterprises—should be encouraged to develop a comprehensive talent cultivation system. This approach involves optimizing talent development pathways, promoting the rational allocation of labor resources, and ultimately driving improvements in UR.
Thirdly, we recommend formulating a comprehensive development strategy and effectively promoting industrial structure upgrading and transformation. The empirical results demonstrate that LM can promote UR through industrial structure upgrading. Therefore, government departments should focus on optimizing the city’s economic structure. On the one hand, it is essential to refine and enhance industrial service policies, guiding the market to create a fair development environment and accelerating the upgrading of industrial structures. On the other hand, establishing an effective capacity exit mechanism is necessary to bolster local industrial competitiveness and upgrade capacity. This approach will stimulate market demand, accelerate industrial adjustment within the service industry, and promote the rationalization of regional industries.
Fourthly, deepen technological innovation. The empirical results show that technological innovation is an important path to promote UR. To this end, the government should increase the new investment in scientific research, rationally allocate innovation support funds, and improve the depth of technological research and development to enhance the resilience of the city. Additionally, the government can improve the policy support for technological innovation, optimize the innovation environment, and release more innovative kinetic energy, thereby improving the quality and efficiency of urban resilience development.
Lastly, we recommend implementing regional differentiation policies. The heterogeneity analysis reveals variations in the influence of LM across different regions. Therefore, when pushing the land marketization reform, it is crucial to thoroughly consider the distinctive features of various regions and designate targeted policy initiatives according to local conditions. In the West or the smaller cities, it is crucial to tap the potential of the LM; improve the market environment; and pay attention to the contributions of science and technology, capital, and other elements to enhance the city’s resilience development more vigorously.
5.4. Limitations
Although this paper provides a detailed empirical analysis of the relationship between LM and UR, it still has certain limitations. First, this paper explores the transmission mechanism of LM on UR from allocation effect, structural effect, and technology effect. However, in both theoretical construction and empirical testing, there are still several factors that remain unaddressed, such as the spatial spillover effect of the influence and the moderating effect. Future research should aim to deepen the theoretical model by incorporating adjustment variables, spatial spillovers, and other relevant factors. Secondly, this paper controls the city-fixed effects, a series of control variables, and examines heterogeneity related to the size or area of cities during empirical analysis. To a certain extent, the external disturbing factors affecting the resilience of the city were controlled. However, each city possesses different levels of political, economic, cultural, and natural environments, all of which have an impact on UR. Future research should consider these diverse factors more comprehensively when selecting sample cities, thereby providing a more nuanced understanding of the relationship between LM and UR.