Sheng-Hau Lin

Rural Resilience represents the ability of maintaining their core functions when facing internal changes and recovering to original conditions through transformation. Withdrawal from rural homesteads (WRH) is considered as one of critical strategy for rural revitalization of China but its systemic impacts on rural resilience remain underexplored. This study develops a multidimensional resilience evaluation framework encompassing economic, social, cultural, environmental, and governance dimensions through a Delphi-structured expert consultation process with 16 specialists. Considering the complexity of rural socio-ecological systems and the interplay among various dimensions of rural resilience, this paper uses the Fuzzy Decision-Making Trial and Evaluation Laboratory methodology to analyze the causal relationships between 22 resilience indicators. Results reveal economic resilience and social resilience as dominant causal dimensions, with economic diversification promotion and collective land marketization emerging as key drivers. Cultural and environmental dimensions exhibit effect characteristics, demonstrating dependence on economic, social, governance interventions. Notably, villagers’ income improvement and cooperative mechanisms demonstrate high centrality, while indicators related to culture and environment rank as vulnerable nodes. These findings provide policymakers with a prioritized intervention framework, emphasizing the need for economic restructuring coupled with institutional safeguards to balance developmental and conservation objectives in rural spatial reorganization processes.

Strategic emerging industries (SEIs) have the potential to be a nation’s leading industries in the post-industrialization era. Exploring the spatial distribution of SEIs and the impetuses of their location choice plays a key role in formulating policies conducive to regional industrial and economic development. However, most studies on relevant topics neglected the impact of institutional environment and local innovation on the formation of spatial patterns of SEIs. By investigating 12,979 industrial enterprises in China, this research applied spatial autocorrelation and spatial regression analysis to explore the spatial characteristics of SEIs and identify the variables affecting the location selection of SEIs that result in these spatial patterns. The findings indicated significant spatial differences in the spatial distributions and agglomeration patterns of SEIs. Institutional environment, local innovation, and regional economy have significant impacts on the location choice of SEIs. The interactive effects of local innovation and institutional environment on the spatial agglomeration of SEIs revealed that a higher degree of decentralization and stronger local innovation capability would promote a stronger agglomeration of SEIs. Regions with strong (weak) marketization and weak (strong) institutions of higher education would promote SEIs agglomeration. Based on the findings, policy options were suggested to facilitate SEIs planning and differentiated pathways of industrial transformation.

Achieving sustainable rural development is essential for countries worldwide to balance development between urban and rural areas; especially, sustainable social development is crucial. In the face of rapid urbanization in China, the withdrawal of rural homesteads (WRH) has become the core policy for attaining sustainable rural development. Compared with the literature that focuses on the economic or environmental impacts of the policy, few studies have evaluated how social sustainability is accomplished through such land-reform policies. Given the consensus that exploring sustainability emphasizes complex causal relationships between multiple dimensions, assessment models must further consider interdependencies. Based on Chinese expertise and perspective, this study proposes a hybrid multi-attribute decision analysis model to evaluate the contribution of WRH policies toward social sustainability. First, the Delphi method was used to build evaluation criteria covering four dimensions—the socio-ecological environment, social welfare, social equity, and social inclusion—and 20 criteria were based on the existing literature. Second, influential network relations maps (INRMs) were constructed based on the fuzzy decision-making trial and evaluation laboratory (DEMATEL), considering complex causal relationships between dimensions and criteria to further identify the key evaluation criteria for the social sustainability of the homestead exit policy. The results show that the five subdimensions are key to achieving sustainable social development through WRH. Based on our results, we propose certain policy recommendations.

Unlike most studies on urban innovation, which focus on the effects of land-use policies, this study investigates the effect of urban innovation (UI) on land finance dependence (LFD). In China, innovation-related policies are intended to create a shared business environment where new entrepreneurs can contribute to achieving sustainable economic growth. This study analyzes the spatiotemporal dynamics of LFD and UI from 2005 to 2019 using the spatial autocorrelation model and dynamic spatial Durbin model. It finds a positive spatial association between LFD and UI throughout the studied regions during the study period. It also reveals a significant inhibitory effect of UI on LFD and a negative impact on the LFD of neighbouring cities. Moreover, the inhibitory effects will increase over time. Lastly, this study shows varied impacts of UI on LFD in different regions, especially in eastern China. Important policy recommendations for high-quality development in China are provided.

The realization of sustainable social rental housing is regarded as an important policy to solve the housing burden, but social rental housing is often unsustainable. This study assesses the sustainability of social rental housing. However, the decision-making models, such as the classical decision-making hierarchy (AHP) used in the current study, conflict with the resolution of the complex influence of the relationship between evaluation dimensions/criteria. Based on this, we construct a new hybrid multi-attribute decision-making model (MADM) combining the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Fuzzy DEMATEL-based analytic network process (DANP) and the modified VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for the sustainability assessment of government-led social rental housing (SRH) using Taiwanese experts as the subject of the investigation. The Fuzzy DEMATEL found that economic sustainability (D₁), as the core dimension, affects environmental (D₃) and social sustainability (D₂). Furthermore, criteria with the “cause” position, including the reasonable development model (C₂), the provision of living facilities and services needed (C₅), the adoption of environmentally friendly technology and equipment (C₁₀), guaranteed rent and lease (C₁), the acquisition of working skill and employment opportunities (C₆) and space planning and design (C₃), should receive more attention from decision makers because improving these can further enhance the sustainability of the overall scheme. Combined with the DANP weight and modified VIKOR, we also indicate that these criteria should be optimized to make the evaluation more sustainable for a selected social housing case in Taiwan. The research also further proposes management strategy implications.

In response to China’s aims of becoming “carbon–neutral,” the development of green industries such as renewable energy and recycling has flourished. Based on 2015 and 2019 data, this study uses spatial autocorrelation to analyze the evolution of land use by the green industries in Jiangsu Province. The Geodetector model was also applied to identify the driving factors underlying these spatial patterns. The spatial variability of green industrial land use in Jiangsu Province is significant, with the land-use area gradually decreasing from Southern to Northern Jiangsu. In terms of spatial–temporal changes, there is an increase in land use and a trend of expansion in the central and northern regions of Jiangsu. Land use by green industries in the province exhibits a more significant spatial clustering pattern but with a weakened clustering effect. The clustering types are mainly H–H and L-L, with the H–H type distributed mainly in the Su-Xi-Chang region and the L-L type distributed mainly in the Northern Jiangsu region. The levels of technology, economic development, industrialization, and industrial diversification are important individual driving factors, and the interaction among the different factors enhances their driving forces. This study suggests that spatial spillover effects should be focused to promote the coordinated development of regional energy-saving and environmental protection industries. At the same time, joint efforts should be made from the aspects of resources, government, economy, and related industries to promote the agglomeration of land for energy-saving and environmental protection industries.

According to neoclassical growth theory, there are two main patterns of economic growth, namely, intensive growth, which depends on total factor productivity (TFP), and extensive growth, which relies on factor input. This study explores the impacts of property taxes on growth patterns by considering the property tax pilots in Shanghai and Chongqing as a quasi-natural experiment. For evaluation, we applied multiple causal inference methods, including DID, PSM-DID, and a panel data approach for program evaluation. We found that the pilot of Shanghai contributed to intensive growth, while the pilot of Chongqing reinforced the prevailing extensive growth. Specifically, Shanghai's property taxes restricted the buying of multiple homes and oversized homes, thereby reducing house prices and increasing TFP. Chongqing's property taxes are mainly for high-end houses, causing the substitution effect between high-end homes and ordinary houses; thus, the pilot increased the prices of ordinary houses and the average house price, which stimulated factor input and economic growth but decreased TFP. This study provides empirical evidence of the causal relationships between property taxes and growth patterns, indicating that transitional economies should avoid narrow tax bases during property tax reform for intensive growth.

Urbanization and aging populations are threatening the sustainability of rural development around the world. Improving the happiness of rural residents is closely related not only to rural development but also to the harmony and stability of a country. Sustainable development has become an important strategy for China’s rural areas. Although withdrawal from rural homesteads is an important issue in rural land policy, few researchers have examined the determinants of the subjective well-being of farmers following withdrawal. The current paper investigated 315 rural residents under three models of the “withdrawal from homestead” policy in Jinjiang City, Fujian Province, China. The application of the orderly probit model revealed how satisfaction with economic, social, environment, cultural, and policy factors impacted their subjective well-being. The pooled results showed that satisfaction with cultural and policy factors had no significant impact; however, the other aspects significantly promoted their subjective well-being. The empirical model with interaction terms indicated the significant positive impact of economic, environmental, and social factors on subjective well-being under the index replacement model, while only environment and social factors exerted a significant positive impact under the asset replacement and monetary compensation models. Corresponding policy implications are discussed.

Ecological security patterns are an effective tool by which to balance economic development with ecological protection. This study used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model in conjunction with circuit theory to evaluate ecosystem quality from four dimensions: background conditions, topography, landscape structure, and ecological resistance. Our objective was to identify ecological “pinch points” in order to create an ecological security pattern that would be sustainable under a range of land use functions. We selected as the research target the Xia-Zhang-Quan metropolitan area in China due to the extensive soil erosion and general degradation of ecosystems caused by its rapid socio-economic development. Our analysis identified 17 ecological source sites covering 11,512 km², which accounts for 45.36% of the total area. The inter-source corridor includes 31 key corridors and 10 potential corridors covering 3305 km. The average ecosystem quality of this area was estimated at 0.65 at an optimal granularity of 400 m. The distribution of resistance values in the study area was relatively concentrated with the land divided into an ecological buffer zone (34.6%), an environmentally sensitive zone (10.9%), and a blocking zone (9.2%). Our analysis also revealed various corridors based on the regional and functional characteristics of ecological elements and improvement strategies at the pinch points to help restore the function of ecological sources. Protection of these corridors will help to maintain regional ecological security patterns and optimize the structure of ecological spaces with the aim of achieving sustainable development.