The dynamic interrelationship between economic development and land use has long stood at the forefront of debates on global sustainable development (Prabhakar, 2025). Despite striking disparities in development levels between developed and developing countries, both face acute sustainability challenges rooted in the inherent contradiction between the demand for economic growth and the finite capacity of urban land resources (Turok et al., 2023; Yanbo et al., 2023). Overcome the unsustainable trajectory of traditional growth models, the international community has collectively turned toward green economic strategies and more intensive modes of urban land utilization. For example, the Netherlands has been promoting the “compact city” policy, and managing idle land through land banks to prioritize its allocation to ecological projects (Bakker et al., 2015). Korea has taken a comprehensive strategy of compact urban development and territorial planning and land management, implementing land efficient use and low-carbon transition by regulatory mandates and market-based incentives (Cho et al., 2023). Singapore, meanwhile, has fused the green economy with land intensification by mandating vertical greenery and promoting multifunctional land use (Song et al., 2022). In China, a wide range of initiatives—such as the National Main Functional Zone Plan, low-carbon city pilots, new energy demonstration zones, and policies on green and low-carbon industrial land—have yielded notable progress in fostering both green economic transformation and intensive land use (Ma and Zhang, 2025; Nie et al., 2025; Wang and Chen, 2025). Compared to developed nations, China faces more severe challenges, as economic development has been accompanied by large-scale urban expansion and widespread inefficiencies in land use. This has led to the overconsumption of land resources, placing immense pressure on both the environment and urban infrastructure. During the process of urbanization, the expansion of cities often exceeds the land resources’ carrying capacity, further intensifying the risk of unsustainable economic development. In this context, achieving effective coupling between green economic efficiency (GEE) and urban land development intensity (ULDI) becomes especially crucial. Moreover, China’s land resources are relatively scarce, and regional disparities are pronounced. Therefore, promoting the coordination between these two factors requires tailored strategies for different regions, necessitating the exploration of driving pathways for their coordination development.

The green economic efficiency (GEE) reflects the economic efficiency of a country or region after considering resource depletion and environmental impacts (Zhao et al., 2020). The GEE can clearly demonstrate the relationship between economic development, resource consumption, and ecological environment impact, to support the development of green economy (Loiseau et al., 2016; Lorek and Spangenberg, 2014; Zhao et al., 2022). Previous studies have directly or indirectly measured GEE by constructing single factor GEE indicators or composite factor GEE indicator systems. Some scholars have constructed composite factor indicators to directly measure the efficiency of green economy. Pitt-man first included the cost of controlling environmental pollution as an unexpected output in the production function and used the Solow residual method to measure green economic productivity. In this way, scholars are gradually considering technology and other factors as new input factors, and haze, carbon emissions and other factors as new output factors to measure GEE (Chen et al., 2019). In terms of measurement methods, the DEA model can measure the efficiency of green economy under multiple input factors and multiple input–output scenarios, but due to the inability to consider the impact of input–output relaxation variables, the results can easily be biased (Liu et al., 2023). In recent years, scholars have mostly used the relaxation variable based SBM model (SBM) proposed by Tone and the super efficiency SBM model that can compensate for the problem of ranking decision units with multiple efficiency values of 1 in the SBM model to measure GEE (Liu B., 2023; Yang H. et al., 2023).

The urban land development intensity (ULDI) is a comprehensive evaluation of the current status of urban land development and utilization, which is often used as an important indicator to characterize the intensive use of urban land. Previous research has achieved certain results in terms of the conceptual connotation and quantitative measurement of ULDI. Some scholars define the concept of urban land development intensity from the perspective of the relationship between urban development and spatial control of construction land (Fu et al., 2025; Wang M. et al., 2025). Scholars are constantly expanding the connotation of ULDI based on the changing requirements of socio-economic development for urban land use, and selecting indicators from different perspectives to comprehensively evaluate ULDI. Some studies use a single indicator to measure the ULDI, such as the proportion of regional construction land area to regional land area (Fan, 2013), building density (Tang and Yiu, 2010), compactness (Yu P. H. et al., 2023), and plot ratio (Qiao et al., 2015). Some studies have constructed a composite indicator system from multiple levels to comprehensively evaluate the ULDI based on the functions and characteristics of urban land development in urban development (Chakrabortty et al., 2025; Luo et al., 2025). In summary, the concept connotation and evaluation index system construction of ULDI reflect the practical performance of urban land development. The practical manifestation of urban land development is that with the expansion of the quantity and scale of construction land, the reduction of arable land, forest land, water bodies, etc. meets the needs of social and economic activities (Yu et al., 2025). Socio economic activities can lead to changes in the level of urban land development, further altering the structure of construction land types (Fu et al., 2025). Based on existing literature and the practical performance of urban land development, ULDI includes a comprehensive representation of the scale of land space development based on breadth perspective, the benefits of land space development based on depth perspective, and the structure of land space development based on limit perspective.

Coupling coordination refers to the process of multiple systems interacting and influencing each other, ultimately tending towards a coordinated development state. The coupling coordination theory was first applied in the field of economic and social problem research, and gradually expanded to study the interactions and influencing relationships between various systems such as ecological environment, society, and economy (Cheng et al., 2023). Urban land is both the material and spatial carrier of production, living and ecological activities in economic development, and the most basic input element to promote urban economic development (Guo et al., 2025). The content of urban economic development will also be reflected in land development and utilization, which is manifested in the increase of construction land and the expansion and interaction of regional spatial scope (Zhou, 2025). There is a coupling coordination relationship between urban land development and utilization and green economic development theoretically. Quantitative evaluation methods for coupling coordination relationships mainly include correlation analysis (Koçak and Şarkgüneşi, 2017), impulse response analysis (Guan and Jin, 2020), and coupling degree and coupling coordination degree models (Lu et al., 2016). With the increasingly severe problems of land resource depletion and environmental pollution in traditional economic growth, the application research field of coupling and coordination in the relationship between urban land and utilization and green economic development is expanding. The application of coupling coordination in the field of the relationship between urban land and utilization and green economic development has focused on exploring the relationship between economic growth and resource environment (Zhou et al., 2017), urbanization and resource environment (Reid et al., 2010), and urban land development and resource environment carrying capacity (Nakajima and Ortega, 2016; Ye et al., 2016). Furthermore, scholars have identified external factors that affect the coupling coordination relationship. It has been shown that the urbanization level, economic development level, population size, industrial development level and the level of opening to the outside world are the key influencing factors (Li et al., 2025; Yao et al., 2025). As such, three significant research challenges may be identified:

Is there a coupling and coordination relationship between GEE and ULDI? How to measure the coupling and coordination relationship between the two? The existing literature has shown that there is a coupling and coordinated relationship between GEE and ULDI, but these literature only analyzed the one-way causal between GEE and ULDI. The research that directly explores the interaction between the two based on the coupling coordination theory is missing. Although there are also studies that have used the impulse response analysis method to verify the interactive relationship between the two (Hou et al., 2022), the theoretical discussion of the coupling and coordination mechanism between GEE and ULDI has been neglected.

Therefore, this study takes 283 cities in China as the research unit, and on the basis of analyzing the coupling and coordination mechanism between GEE ULDI, the coupling and coordination relationship between GEE and ULDI is examined empirically by using the coupling and coordination model, and the spatial–temporal evolution characteristics of the and coordination degree are analyzed. In addition, the time series qualitative comparative analysis method is used to identify the key factors and their paths affecting the coupling and coordination degree from the perspective configuration.

This paper makes several theoretical and practical contributions. First, from the perspective of research innovation, it explores the interactive mechanism between GEE and ULDI through coupling coordination theory, revealing the driving factors and configurational mechanisms underlying their coordinated development. Second, in terms of research scale, unlike previous studies that focused on nations, regions, provinces, or individual cities, this paper examines all prefecture-level cities in China, providing a more comprehensive understanding of the spatial–temporal evolution of GEE–ULDI coordination. Third, methodologically, it breaks through traditional linear analytical frameworks by introducing the qualitative comparative analysis approach, identifying driving factors and their configurational paths from a multi-dimensional perspective.

This study aims to theoretically explore the coupling and coordination mechanism between GEE and ULDI, assess their current level of interaction, and empirically identify the key external driving factors and their configurational effects on the coupling and coordinated development between the two. Based on this analysis, the study examines both pathways that promote coupling and coordination as well as those that may hinder it, with a view to achieving sustainable urban development.

First, the results indicate that, by 2019, the coupling and coordination degree between GEE and ULDI in China was barely coordinated, still in a transitional phase. The coupling and coordinated development reflects the dynamic balance between socio-economic demand and natural resource supply (Hou et al., 2022). This essentially reflects that the inertia of the traditional extensive development path is still continuing, and the speed and scale of land development have not yet been fully converted into green intensive and efficient output. To crack this dilemma and promote the two to evolve to a higher level of synergy is an important goal for the sustainable development of Chinese cities in the future. In practice, China has put forward Ecological Civilization Construction and People-centered New-type Urbanization strategy, in which the overall planning of production, living and ecological spaces is clearly proposed. The establishment and implementation of this territorial spatial planning system, the disorderly expansion of urban development is constrained from the source (Fang and Yu, 2016; Pan, 2018). Meanwhile, the continuous investment in green technology innovation in China under the goal of achieving “double carbon” is encouraging various cities to explore a new model of industrial that is “low land consumption and high value-added output” (Zhang Y. et al., 2023). China is transforming the binding constraints of urban land resources into a reverse incentive mechanism for economic transformation through these institutional designs, guiding the green development of the urban economy. And China is moving towards a higher level of dynamic equilibrium between GEE and ULDI through governance and innovation-driven development, which is an important practice path for to enter a stage of high-quality development.

Second, we used necessary condition analysis and the single-factor necessity test in fsQCA to determine whether a single influencing factor-governmental, market-based, or societal factors would affect the coupling coordination degree between GEE and ULDI. The necessary condition analysis shows that no single governmental, market, or societal factor alone can explain either high or non-high levels of coupling coordination. While previous research has used conventional econometric regression methods such as the panel model, spatial statistical models, and geographically and temporally weighted regression to identify influencing factors of the coupling coordination degree (Gao et al., 2025; Zhang C. H. et al., 2025). Moreover, these studies mainly focused on the impact of a single factor on the coupling and coordinated development and used quantitative analysis methods to identify their independent impact and quantify their net effect. Thus, the findings of this paper are complementary to existing research.

Third, according the results of configuration analysis, this study refines a Chinese paradigm of tripartite synergy—government, market, and society—for driving GEE and ULDI coupling and coordination. This paradigm can be summarized in four dimensions: first, establishing a regulatory bottom line through government environmental regulation; second, providing development momentum via government fiscal support and financial market development; third, enabling value transformation through consumption vitality; and fourth, defining the potential boundaries of exogenous resource substitution under “non-high” conditions of foreign capital markets and human capital. For sustainable urban development in China, this paradigm offers a systematic approach to escape the “pollute first, treat later” trap and overcome resource constraints, providing valuable insights for other countries seeking sustainable pathways by enhancing GEE and optimizing ULDI. Moreover, this paradigm also allows for diversity and differentiation in specific combination pathways, serving as a guide for urban sustainability. Only by accurately matching urban endowments with pathway conditions can cities leap from a “low-coordination trap” to “high-quality coupling.” Accordingly, this study further examines city types and their corresponding enabling configuration pathways, applying the five high-coupling configurations and one non-high coordination configuration, and proposes differentiated policy combinations tailored to local development conditions (Figure 8).

The coupling and coordination pathways between China’s GEE and ULDI highlight the crucial role of endogenous government policies and consumer demand. Without effective government fiscal support and consumption vitality, high-level coordination is difficult to achieve, as illustrated by the NH1 pathway—even when foreign investment, financial capital, and human capital are present. H1 shows that in cities with low human capital but strong government fiscal support, environmental regulation, foreign investment, and consumption vitality, financial development is not essential for achieving high coupling and synergy between GEE and ULDI. Typical examples include first-tier or new first-tier cities such as Beijing, Shanghai, and Shenzhen. In practice, these cities promote sustainable development by: establishing green infrastructure funds to subsidize low-carbon urban land development; enforcing “dual carbon” land transfer standards; issuing green REITs; and stimulating consumption vitality through mechanisms like carbon credit systems, allowing property tax deductions for purchasing green buildings.

In summary, this study offers valuable theoretical and practical insights but has certain limitations that point to future research directions. First, the GEE and ULDI index systems require further refinement. While this study establishes evaluation frameworks based on existing literature and Chinese practice, there is currently no unified authoritative measurement system. Future research should incorporate additional indicators to create a richer, more practically aligned evaluation system. Second, government, market, and social factors were identified as core conditions, and this result remains robust across different calibration points and case frequency thresholds, reinforcing prior findings regarding drivers of GEE-ULDI coupling. However, the large sample size may contribute to this robustness, which warrants further investigation. Finally, updating GEE and ULDI data in future research is essential to capture the latest trends in urban sustainability.

Realizing the coupling and coordinated development of GEE and ULDI is a critical pathway toward sustainable urban development. Building on an analysis of the coupling and coordination mechanism between GEE and ULDI, this study employs a coupling coordination model to quantitatively measure the degree of coupling and coordination, and utilizes the time series qualitative comparative analysis (TSQCA) method to identify the key driving factors and their configurational effects on the coupling and coordinated development of China’s GEE and ULDI. The main findings are as follows.

First, using the coupling coordination model, the spatio-temporal patterns of the coupling coordination degree between GEE and ULDI were calculated and analyzed. The results show that the mean coupling coordination degree ranges from 0.4 to 0.6 during the study period, indicating that China remains in a transitional stage of coupling and coordinated development. Spatially, the coupling coordination degree exhibits a clear pattern of “high in the east and low in the west” and “high in the south and low in the north.”

Second, the study theoretically analyzes the direct effects and configuration effects of governmental, market-based, and societal factors on GEE-ULDI coupling and coordination, and tests these relationships empirically using fsQCA. The necessary condition analysis shows that no single governmental, market, or societal factor alone can explain either high or non-high levels of coupling coordination. Rather, the observed coupling coordination outcomes are attributable to the synergistic configuration of these factors. Specifically, five configurations (H1, H2, H3a, H3b, H4) were identified as promoting high coupling coordination, while one configuration (NH1) leads to non-high coupling coordination.

Finally, based on the theoretical and empirical findings, a Chinese paradigm of tripartite synergy—government, market, and society—can be refined for promoting GEE-ULDI coupling and coordination. This paradigm involves: setting the bottom line through government environmental regulation, providing development momentum through fiscal support and financial market development, and achieving value transformation through consumption vitality. Meanwhile, external resources such as the foreign capital market and human capital status play a substitutable role in achieving coupling coordination. Ultimately, only by accurately matching urban endowments with appropriate pathways can cities break free from the “low coordination trap” and achieve high-quality coupling.