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Keywords = DEA-SBM model

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17 pages, 319 KiB  
Article
Research on Pathways to Improve Carbon Emission Efficiency of Chinese Airlines
by Liukun Zhang and Jiani Zhao
Sustainability 2025, 17(15), 6826; https://doi.org/10.3390/su17156826 - 27 Jul 2025
Viewed by 249
Abstract
As an energy-intensive industry, the aviation sector’s carbon emissions have drawn significant attention. Against the backdrop of the “dual carbon” goals, how to enhance the carbon emission efficiency of airlines has become an urgent issue to be addressed for both industry development and [...] Read more.
As an energy-intensive industry, the aviation sector’s carbon emissions have drawn significant attention. Against the backdrop of the “dual carbon” goals, how to enhance the carbon emission efficiency of airlines has become an urgent issue to be addressed for both industry development and low-carbon targets. This paper constructs an evaluation system for the carbon emission efficiency of airlines and uses the SBM-DDF model under the global production possibility set, combined with the bootstrap-DEA method, to calculate the efficiency values. On this basis, the fuzzy-set qualitative comparative analysis method is employed to analyze the synergistic effects of multiple influencing factors in three dimensions: economic benefits, transportation benefits, and energy consumption on improving carbon emission efficiency. The research findings reveal that, first, a single influencing factor does not constitute a necessary condition for achieving high carbon emission efficiency; second, there are four combinations that enhance carbon emission efficiency: “load volume-driven type”, “scale revenue-driven type”, “high ticket price + technology-driven type”, and “passenger and cargo synergy mixed type”. These discoveries are of great significance for promoting the construction of a carbon emission efficiency system by Chinese airlines and achieving high-quality development in the aviation industry. Full article
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21 pages, 1566 KiB  
Article
Environmental Degradation and Its Implications for Forestry Resource Efficiency and Total Factor Forestry Productivity in China
by Fuxi Wu, Rizwana Yasmeen, Xiaowei Xu, Heshan Sameera Kankanam Pathiranage, Wasi Ul Hassan Shah and Jintao Shen
Forests 2025, 16(7), 1166; https://doi.org/10.3390/f16071166 - 15 Jul 2025
Viewed by 329
Abstract
Environmental costs (carbon emissions) have come with China’s economic rise, and its forestry sector now faces difficulties in maintaining both its profit and the health of its ecosystems. This study assesses the impact of carbon emissions on forestry efficiency and total factor productivity [...] Read more.
Environmental costs (carbon emissions) have come with China’s economic rise, and its forestry sector now faces difficulties in maintaining both its profit and the health of its ecosystems. This study assesses the impact of carbon emissions on forestry efficiency and total factor productivity (TFFP) in China’s 31 provinces between 2001 and 2021. Using the data envelopment analysis (DEA) model through the slack-based measure (SBM framework) and Malmquist–Luenberger index (MLI), we examine the efficiency and productivity growth of forestry, both with and without accounting for carbon emissions. The study reveals that when carbon emissions are not taken into account, traditional measures of productivity tend to overstate both efficiency and total factor forestry productivity (TFFP) growth, resulting in an average of 7.7 percent higher efficiency and 1.6 percent of additional TFFP growth per year. If we compare the regions, coast provinces with stricter technical regulations have improved efficiency in usage, but places like Tibet and Qinghai, with more vulnerable ecosystems, endure harsher consequences. Regardless of incorporating bad output into the TFFP estimation, China’s growth in forestry productivity primarily depends on efficiency change (EC) rather than technological change (TC). Full article
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32 pages, 2492 KiB  
Article
A Study on the Correlation Between Urbanization and Agricultural Economy Based on Efficiency Measurement and Quantile Regression: Evidence from China
by Hong Ye, Yaoyao Ding, Rong Zhang and Yuntao Zou
Sustainability 2025, 17(13), 5908; https://doi.org/10.3390/su17135908 - 26 Jun 2025
Viewed by 331
Abstract
The impact of urbanization on the agricultural economy has long attracted scholarly attention. Taking China as a case, this study investigates the relationship between urbanization and agricultural development under the dual progress of urbanization and the rural revitalization strategy. Based on panel data [...] Read more.
The impact of urbanization on the agricultural economy has long attracted scholarly attention. Taking China as a case, this study investigates the relationship between urbanization and agricultural development under the dual progress of urbanization and the rural revitalization strategy. Based on panel data from 31 mainland provinces, this paper measures agricultural economic efficiency using the global slack-based measure (SBM) model and employs quantile regression to systematically analyze the influence of various urbanization factors across different levels of agricultural efficiency. A Tobit regression model is further adopted for robustness checks. The results show that representative urbanization factors, such as the proportion of urban population and the prevalence of higher education, exert significant negative impacts on agricultural efficiency, particularly in regions with higher efficiency levels. Freight volume has a significantly negative effect in regions with medium and low efficiency, while freight turnover negatively impacts medium- to high-efficiency areas. In contrast, improvements in healthcare services and digital infrastructure are found to consistently enhance agricultural efficiency. Although the corporatization of agriculture is often regarded as a key outcome of urbanization, its efficiency-improving effect is not statistically significant in most models and is mainly concentrated in high-efficiency regions. Overall, the improvement in China’s agricultural economic efficiency relies more on direct support from the rural revitalization strategy, while rapid urbanization has failed to bring substantial benefits and has even led to structural negative effects. These adverse outcomes may stem from the rapid occupation of suburban farmland, increased logistics costs due to the relocation of agricultural activities, and the ineffective absorption of surplus rural labor. This study highlights the need for future urbanization policies in China to pay greater attention to the coordinated development of the agricultural economy. The methods and findings of this research also provide reference value for other developing regions facing similar urbanization-agriculture dynamics. Full article
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27 pages, 426 KiB  
Article
The Influence of Customer ESG Performance on Supplier Green Innovation Efficiency: A Supply Chain Perspective
by Shengen Huang, Yalian Zhang, Tianji Cheng and Xin Guo
Sustainability 2025, 17(12), 5519; https://doi.org/10.3390/su17125519 - 16 Jun 2025
Viewed by 607
Abstract
The present study examines the impact of customer firms’ environmental, social, and governance (ESG) performance on suppliers’ green innovation efficiency, grounded in stakeholder theory and innovation diffusion theory. The DEA-SBM model is employed to measure green innovation efficiency and analyze transmission mechanisms through [...] Read more.
The present study examines the impact of customer firms’ environmental, social, and governance (ESG) performance on suppliers’ green innovation efficiency, grounded in stakeholder theory and innovation diffusion theory. The DEA-SBM model is employed to measure green innovation efficiency and analyze transmission mechanisms through knowledge spillovers, financing constraints, and the moderating roles of executives’ green cognition and digitization. This analysis is based on panel data from 3134 customer–supplier pairs of China’s A-share listed firms from 2014 to 2023. The findings indicate that high ESG performance by customer firms has a substantial impact on suppliers’ green innovation efficiency, with a 1% increase in customer ESG score resulting in a 1.38% improvement in supplier efficiency. The phenomenon under scrutiny is hypothesized to be precipitated by knowledge spillovers and mitigated by reduced financing constraints. The hypothesis further posits that supplier firm executives’ green cognition and customer digitization will amplify the effect. A heterogeneity analysis reveals stronger effects in technology-intensive firms and regions with higher governmental environmental oversight. These findings underscore the pivotal function of ESG-driven supply chain collaboration in propelling sustainable industrialization. It is imperative that policymakers prioritize cross-regional ESG benchmarking and digital infrastructure to amplify green spillovers. Conversely, firms must integrate ESG metrics into supplier evaluation systems and foster executive training on sustainability. This research provides empirical evidence for the optimization of green innovation policies and the achievement of China’s dual carbon goals through the coordination of supply chain governance. Full article
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25 pages, 2402 KiB  
Article
Research on Different Energy Transition Pathway Analysis and Low-Carbon Electricity Development: A Case Study of an Energy System in Inner Mongolia
by Boyi Li, Richao Cong, Toru Matsumoto and Yajuan Li
Energies 2025, 18(12), 3129; https://doi.org/10.3390/en18123129 - 14 Jun 2025
Viewed by 553
Abstract
To achieve carbon neutrality targets in the power sector, regions with rich coal and renewable energy resources are facing unprecedented pressure. This paper explores the decarbonization pathway in the power sector in Inner Mongolia, China, under different energy transition scenarios based on the [...] Read more.
To achieve carbon neutrality targets in the power sector, regions with rich coal and renewable energy resources are facing unprecedented pressure. This paper explores the decarbonization pathway in the power sector in Inner Mongolia, China, under different energy transition scenarios based on the Long-Range Energy Alternatives Planning System (LEAP) model. This includes renewable energy expansion, carbon capture and storage (CCS) applications, demand response, and economic regulation scenarios. Subsequently, a combination of the Logarithmic Mean Divisia Index (LMDI) and Slack-Based Measure Data Envelopment Analysis (SBM-DEA) model was developed to investigate the influencing factors and power generation efficiency in low-carbon electricity. The results revealed that this region emphasizes first developing renewable energy and improving the carbon and green electricity market and then accelerating CCS technology. Its carbon emissions are among the lowest, at about 77.29 million tons, but the cost could reach CNY 229.8 billion in 2060. We also found that the influencing factors of carbon productivity, low-carbon electricity structures, and carbon emissions significantly affected low-carbon electricity generation; their cumulative contribution rate is 367–588%, 155–399%, and −189–−737%, respectively. Regarding low-carbon electricity efficiency, the demand response scenario is the lowest at about 0.71; other scenarios show similar efficiency values. This value could be improved by optimizing the energy consumption structure and the installed capacity configuration. Full article
(This article belongs to the Special Issue Energy Transition and Environmental Sustainability: 3rd Edition)
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24 pages, 3629 KiB  
Article
Coupling Coordination Development Between Cultivated Land and Agricultural Water Use Efficiency in Arid Regions: A Case Study of the Turpan–Hami Basin
by Yue Kong, Abdugheni Abliz, Dongping Guo, Xianhe Liu, Jialin Li and Buasi Nurahmat
Agriculture 2025, 15(11), 1153; https://doi.org/10.3390/agriculture15111153 - 27 May 2025
Viewed by 348
Abstract
The coupling coordination relationship between cultivated land and water resources in arid regions is crucial for ecological security and sustainable food production. This study explores the interaction between these resources to optimize the allocation of water–land resources, ecological resources, and agricultural resources and [...] Read more.
The coupling coordination relationship between cultivated land and water resources in arid regions is crucial for ecological security and sustainable food production. This study explores the interaction between these resources to optimize the allocation of water–land resources, ecological resources, and agricultural resources and promote synergistic development. Taking the Turpan–Hami Basin as a case study, this research analyzed the utilization efficiency of cultivated land and agricultural water resources from 2000 to 2023 using a super-efficiency SBM-DEA model. A coupling coordination degree model was constructed to evaluate their coordinated development level, with spatial autocorrelation and other methods used to examine spatiotemporal patterns. Key findings include: (1) The overall utilization efficiency of both resources was relatively low, with mean values of 0.516 and 0.596, showing a fluctuating upward trend and significant spatial heterogeneity; (2) The mean coupling coordination degree (CCD) ranked as follows: Barkol Kazakh Autonomous County (0.587) > Yiwu County (0.563) > Gaochang District (0.494) > Shanshan County (0.437) > Tuokexun County (0.417) > Yizhou District (0.342), with an annual growth rate of 4.6%; (3) Regional disparities were dominated by intra-regional differences (42.0%), followed by transvariation density (30.64%). This study provides scientific evidence for optimizing resource allocation in arid regions. Full article
(This article belongs to the Section Agricultural Water Management)
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20 pages, 940 KiB  
Article
The Impact of Digital Village Construction on the Comprehensive Efficiency of Eco-Agriculture: An Empirical Study Based on Panel Data from 53 Counties in Fujian Province
by Wenqi Lian, Zexi Xue, Gaiyan Ma and Fangfang Zeng
Sustainability 2025, 17(9), 3840; https://doi.org/10.3390/su17093840 - 24 Apr 2025
Cited by 1 | Viewed by 496
Abstract
This study is based on panel data from 53 counties in eight prefectural-level cities in Fujian Province, spanning from 2012 to 2022. It employs the entropy method, DEA-SBM model, fixed-effects spatial Durbin model, and spatial autoregressive model to investigate the impact of digital [...] Read more.
This study is based on panel data from 53 counties in eight prefectural-level cities in Fujian Province, spanning from 2012 to 2022. It employs the entropy method, DEA-SBM model, fixed-effects spatial Durbin model, and spatial autoregressive model to investigate the impact of digital village construction on the comprehensive efficiency of eco-agriculture in Fujian. The results are as follows: (1) During the study period, the comprehensive efficiency of eco-agriculture in 53 counties of Fujian showed a fluctuating upward trend. (2) The level of digital village construction in Fujian exhibited notable regional variation, with the following ranked order: Central region > Southern region > Eastern region > Western region > Northern region. (3) A significant spatial positive effect was observed on eco-agricultural efficiency, with H-H and L-L spatial correlation patterns. (4) Digital village construction significantly improved the comprehensive efficiency of eco-agriculture in Fujian, but no spatial spillover effect was observed. Based on these findings, this study recommends strengthening technological innovation, enhancing regional exchanges, and tailoring policies to local conditions. This study applies the theory of technology diffusion in spatial economics to eco-agriculture, aiming to explore the specificity of digital technology spillover and the inhibitory effects of “blocked data-sharing channels” and the “digital divide” on such spillover. Full article
(This article belongs to the Section Sustainable Agriculture)
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22 pages, 2215 KiB  
Article
Impact of Shrinking Cities on Carbon Emission Efficiency in China
by Tianshu Yu, Ling Li and Tao Li
Sustainability 2025, 17(8), 3664; https://doi.org/10.3390/su17083664 - 18 Apr 2025
Viewed by 441
Abstract
The issue of urban carbon emission efficiency (CEE) has become a critical problem for global sustainable development, particularly in China, where the phenomenon of shrinking cities has emerged after rapid urbanization. Using panel data from 283 Chinese prefecture-level cities (2000–2016), we examine how [...] Read more.
The issue of urban carbon emission efficiency (CEE) has become a critical problem for global sustainable development, particularly in China, where the phenomenon of shrinking cities has emerged after rapid urbanization. Using panel data from 283 Chinese prefecture-level cities (2000–2016), we examine how urban shrinkage affects CEE through both direct and spatial spillover effects. Our findings show that urban shrinkage significantly improves CEE both directly and indirectly; when a city shrinks, it increases the local CEE by 0.0132%, while the contraction of adjacent cities enhances the local CEE by 0.0312%, leading to a total improvement of 0.0445%. However, the overall CEE in shrinking cities remains lower than the nationwide average, with values consistently below 0.5. The main determinants of CEE are GDP per capita and population size, which show significant direct positive effects but opposing regional spillover effects. These findings offer important insights for urban development policies and sustainable city management in the context of population decline. Full article
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19 pages, 5342 KiB  
Article
Spatio-Temporal Analysis of the Redundancies of Construction Land in the Beijing-Tianjin-Hebei Region (2000–2020)
by Ting Zhang, Rui Shen, Yongqing Xie, Haowen Gao and Weitong Lv
ISPRS Int. J. Geo-Inf. 2025, 14(4), 173; https://doi.org/10.3390/ijgi14040173 - 16 Apr 2025
Viewed by 407
Abstract
Excessive redundancy of construction land in county-level units within the Beijing-Tianjin-Hebei region has become a significant obstacle to achieving high-quality development. The objective of this study is to discover the spatial and temporal patterns of redundancy of construction land, with a view to [...] Read more.
Excessive redundancy of construction land in county-level units within the Beijing-Tianjin-Hebei region has become a significant obstacle to achieving high-quality development. The objective of this study is to discover the spatial and temporal patterns of redundancy of construction land, with a view to providing insights for promoting efficient land use. The study employs the SBM-DEA model, Markov transfer probability matrix analysis, and multiple regression analysis to analyze the spatial change characteristics, spatial differentiation, and influencing factors of construction land redundancy in this Beijing-Tianjin-Hebei county unit during the period of 2000–2020. The study shows that the Beijing-Tianjin-Hebei county unit has a serious oversupply of land and, combined with the reasons for redundancy in each sub-region, the degree of spatial redundancy has already formed a spatial lock-in effect. The degree of redundancy of construction land is affected by a variety of factors such as location, scale, economy, and facilities. Furthermore, the study puts forward suggestions for improving land use efficiency in Beijing-Tianjin-Hebei county units by adjusting the construction land supply and demand relationship, mechanisms to facilitate the flow of development factors, and strengthening land use supervision. These measures aim to reduce redundancy of construction land and support sustainable high-quality development in the region. Full article
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25 pages, 6600 KiB  
Article
Spatial Correlation Network Characteristics of Comprehensive Transportation Green Efficiency in China
by Qifei Ma, Sujuan Li and Zhenchao Zhang
Future Transp. 2025, 5(2), 40; https://doi.org/10.3390/futuretransp5020040 - 1 Apr 2025
Viewed by 419
Abstract
Accurately characterizing the structural features of the spatial correlation network of comprehensive transportation green efficiency (CTGE) is essential for achieving balanced regional transportation development and eliminating regional disparities. This study employs the slacks-based measure-data envelopment analysis (SBM-DEA) model to assess the CTGE of [...] Read more.
Accurately characterizing the structural features of the spatial correlation network of comprehensive transportation green efficiency (CTGE) is essential for achieving balanced regional transportation development and eliminating regional disparities. This study employs the slacks-based measure-data envelopment analysis (SBM-DEA) model to assess the CTGE of China. Furthermore, the standard deviational ellipse (SDE) model and social network analysis (SNA) method are adopted to delineate the spatiotemporal evolution patterns and spatial correlation network characteristics of CTGE, based on input–output data from the transportation industry across 30 provinces (municipalities and autonomous regions) between 2003 and 2020. The findings reveal that China’s CTGE exhibits a fluctuating trend of an initial decline followed by subsequent increase, with a national average of 0.555 and an average of 0.722 in eastern regions, 0.434 in central regions, and 0.478 in western regions. This demonstrates that China’s CTGE maintains an overall low level while showing significant regional disparities. The spatial center of gravity of China’s CTGE has shifted from a southwestern to a northeastern trajectory, with a generally concentrated spatial distribution pattern. Furthermore, China’s CTGE demonstrates a distinct “core-edge” hierarchical structure, with regions occupying varied roles and statuses within the network. The central and western regions are positioned at the network periphery, predominantly receiving spillover effects from other regions, while the eastern region, driven by its strong spillover effect, serves as the network’s “engine”. The most significant contribution of this study lies in developing a more comprehensive CTGE evaluation framework and precisely identifying the structural positions and functional roles of different regions within the network, which holds substantial theoretical and practical value for advancing sustainable development in China’s transportation sector. Full article
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26 pages, 303 KiB  
Article
Is It Feasible for China’s Resource-Based Cities to Achieve Sustainable Development? A Natural Resource Dependence Perspective
by Siyu Li, Tian Xia, Yongrok Choi and Hyoungsuk Lee
Land 2025, 14(4), 710; https://doi.org/10.3390/land14040710 - 26 Mar 2025
Cited by 1 | Viewed by 601
Abstract
Theoretically, regions with rich natural resources often tend to develop resource-based industries more intensively, resulting in resource-dependent land development. China’s resource-dependent cities exhibit certain exceptions. Natural resource dependence (NRD) plays a relatively positive role in the total factor productivity change (TFPCH) in these [...] Read more.
Theoretically, regions with rich natural resources often tend to develop resource-based industries more intensively, resulting in resource-dependent land development. China’s resource-dependent cities exhibit certain exceptions. Natural resource dependence (NRD) plays a relatively positive role in the total factor productivity change (TFPCH) in these cities, primarily attributable to their relatively mature technological efficiency. However, while such positive impacts exist, their overall effect remains limited. Many resource-based cities in China still face challenges in achieving sustainable growth. This raises a key question: why have some resource-based cities failed to achieve sustainable development? In order to explore the root cause of this problem, this paper systematically analyses the impact of resource dependence on TFPCH, and its governance mechanism based on the balanced panel data of 112 resource cities in China from 2003 to 2021, using the Super-SBM-DEA-Malmquist index method in the first stage, and the OLS model in the second stage. The main findings of this paper are as follows: First, NRD has a significantly positive impact on TFPCH, especially in growing and regenerating cities. The empirical results further validate the applicability of the resource blessing theory in China. Second, government regulation has a dampening effect on TFPCH in resource cities, which suggests that in the future development of resource cities, government intervention should be moderately reduced, and more emphasis should be placed on stimulating the city’s own autonomous mobility and endogenous development drive. Third, heterogeneity analyses show that this promotional effect is mainly realized through the improvement of technical efficiency. Fourth, the analysis of the moderation effect shows that research and development (R&D) intensity plays a positively moderating role in the sustainable development of resource-based cities. Through a stepwise approach, this paper reveals why resource-based cities cannot achieve sustainable development. The level of R&D in some resource-based cities remains relatively low, while it is the key factor for the applicability of the resource blessing (RB) hypothesis in China’s resource city. The findings not only provide new perspectives for theoretical research, but also important policy recommendations for the sustainable governance of land use in resource-based cities worldwide. Full article
(This article belongs to the Section Land Use, Impact Assessment and Sustainability)
23 pages, 1504 KiB  
Article
Environmental Regulation and Green Investment Efficiency: Threshold and Spatial Spillover Analysis for China
by Lixin Dai and Ruyue Zhang
Sustainability 2025, 17(7), 2934; https://doi.org/10.3390/su17072934 - 26 Mar 2025
Cited by 2 | Viewed by 820
Abstract
To achieve the mutual coordination and sustainable development of ecology and the economy, China has been consistently strengthening its environmental regulations while simultaneously bolstering the green investments of heavily polluting enterprises. This study utilizes panel data from heavily polluting enterprises between 2017 and [...] Read more.
To achieve the mutual coordination and sustainable development of ecology and the economy, China has been consistently strengthening its environmental regulations while simultaneously bolstering the green investments of heavily polluting enterprises. This study utilizes panel data from heavily polluting enterprises between 2017 and 2022. Firstly, it employs the SBM-DEA method to quantify the green investment efficiency of the sampled enterprises. Secondly, it constructs panel threshold and spatial autoregressive models to investigate how environmental regulations impact the efficiency of green investments by these enterprises. The findings indicate that the green investment efficiency of heavily polluting enterprises in China is low. The relationship between environmental regulations and green investment efficiency exhibits double threshold effects and spatial spillover effects, forming an inverted “N” shape. After incorporating internal control factors, the threshold effect persists, displaying an inverted “N” shape, but with a broader promotion interval. These findings are crucial for formulating government policies on environmental regulation intensity, optimizing the efficiency of corporate green investment, and advancing the practice of sustainable development. Full article
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26 pages, 13816 KiB  
Article
Evaluating Territorial Space Use Efficiency: A Geographic Data Envelopment Model Considering Geospatial Effects
by Minrui Zheng, Yin Ma, Xinqi Zheng, Xvlu Wang, Li Li, Feng Xu, Xiaoyuan Zhang, Fuping Gan, Jianchao Wang and Zhengkun Zhu
Land 2025, 14(3), 635; https://doi.org/10.3390/land14030635 - 17 Mar 2025
Viewed by 538
Abstract
Accurately evaluating territorial space use efficiency is a prerequisite for promoting the realization of high-quality development. Existing efficiency evaluation models all treat decision making units (DMUs) as independent individuals, ignoring geospatial effects between geographical spaces, which leads to unreliable results. This study proposes [...] Read more.
Accurately evaluating territorial space use efficiency is a prerequisite for promoting the realization of high-quality development. Existing efficiency evaluation models all treat decision making units (DMUs) as independent individuals, ignoring geospatial effects between geographical spaces, which leads to unreliable results. This study proposes a geographic data envelopment analysis (GeoDEA) model, integrating a spatially constrained multivariate clustering model with generalized data envelopment analysis (DEA). The GeoDEA model reconstructs evaluation and reference sets considering spatial adjacency, cluster numbers, and socio-economic indicators and then applies a slack-based measure (SBM) super-efficient formula. It is verified that the efficiency value evaluated using the GeoDEA model is higher than that of the traditional DEA model, but it is also more consistent with cognition and more reliable. This is mainly explained by the fact that the GeoDEA model takes into account the geospatial effect and selects DMUs with relatively close geographic distance and higher levels of development as the reference frontier for efficiency evaluation. The GeoDEA model optimizes the traditional DEA model and avoids the problem that the efficiency of DMU is underestimated when the geographical background and development mode of DMU are very different from the reference frontier. It enhances the reliability of the evaluation of territorial space use efficiency. Full article
(This article belongs to the Section Land Use, Impact Assessment and Sustainability)
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19 pages, 2120 KiB  
Article
Toward Integrated Marine Renewables: Prioritizing Taiwan’s Offshore Wind Projects for Wave Energy Compatibility Through a Cross-Efficiency Data Envelopment Analysis Approach
by Yen-Hsing Hung and Fu-Chiang Yang
Sustainability 2025, 17(5), 2151; https://doi.org/10.3390/su17052151 - 2 Mar 2025
Viewed by 941
Abstract
Offshore wind energy has become a critical component of global efforts to transition toward low-carbon and sustainable energy systems, and although Taiwan’s advantageous geographical position has accelerated its progress in this domain, many of Taiwan’s upcoming offshore wind projects remain in a pre-construction [...] Read more.
Offshore wind energy has become a critical component of global efforts to transition toward low-carbon and sustainable energy systems, and although Taiwan’s advantageous geographical position has accelerated its progress in this domain, many of Taiwan’s upcoming offshore wind projects remain in a pre-construction phase, raising questions about their viability for complementary wave energy integration. To address this challenge, this study proposes a hybrid Cross-Efficiency Slacks-Based Measure (CE-SBM) Data Envelopment Analysis (DEA) model. Thirteen announced offshore wind projects were evaluated using spatial and resource-related input variables and energy-centric output variables. The self-efficiency results from the SBM stage highlighted several projects—most notably Zhu Ting, Wo Neng, and Chu Tin—as highly effective in resource utilization under their own weighting schemes. However, the subsequent cross-efficiency analysis added a consensus-based perspective, revealing a clear performance hierarchy and identifying inefficiencies in projects such as Greater Changhua Northeast and Winds of September. These findings underscore the value of combining DEA-based models with slacks-based and cross-efficiency features to guide multifaceted energy development. By prioritizing projects with robust efficiency profiles, policymakers and stakeholders can expedite Taiwan’s broader adoption of integrated wind–wave energy systems, ultimately fostering a more reliable and sustainable marine energy portfolio. Full article
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24 pages, 567 KiB  
Article
Intergovernmental Competition and Agricultural Science and Technology Innovation Efficiency: Evidence from China
by Daohan Yu and Fang Wang
Agriculture 2025, 15(5), 530; https://doi.org/10.3390/agriculture15050530 - 28 Feb 2025
Viewed by 811
Abstract
Against the backdrop of global challenges to food security and China’s push to modernize its agriculture, it is critical to understand how government strategies affect innovation efficiency. This study examines how three modes of intergovernmental competition—fiscal spending competition (strategically increasing public spending to [...] Read more.
Against the backdrop of global challenges to food security and China’s push to modernize its agriculture, it is critical to understand how government strategies affect innovation efficiency. This study examines how three modes of intergovernmental competition—fiscal spending competition (strategically increasing public spending to attract resources), tax competition (providing incentives to promote investment), and promotion competition (officials prioritizing short-term projects for promotion)—affect the efficiency of agricultural science and technology innovations across China’s provinces. Utilizing panel data (2000–2021) and a Slack-Based Measure Data Envelopment Analysis (DEA-SBM) model, we find that fiscal spending competition suppresses efficiency, particularly in western regions where infrastructure investments crowd out R&D. Tax competition enhances efficiency, yet its impact is attenuated in central China due to low industrial upgrading. Promotion competition impedes long-term innovation, as frequent official turnover prioritizes short-term projects. Regional heterogeneity highlights eastern China’s market-driven advantages versus central/western regions’ structural constraints. Policy implications advocate for spatially differentiated governance, including R&D tax rebates in the east and cross-regional innovation alliances. This study contributes to fiscal decentralization theory by revealing the nonlinear effects of competition modes on agricultural innovation. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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