Search Results (216)

Reducing poverty and income inequality is a major objective of contemporary social policy. Considerable financial resources are spent on social protection to support this purpose. Since these resources are limited, their efficient use is important for improving poverty and income inequality outcomes. The aim of this study is to assess the efficiency and productivity of social protection expenditure in eleven Central and Eastern European (CEE) EU Member States through Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI). Three input-oriented DEA models are estimated for 2016–2023, including two poverty-oriented models and one income-distribution-oriented model. The results indicate high efficiency and scale efficiency across countries, but favourable results in both poverty-oriented models are not necessarily accompanied by similar results in the income-distribution-oriented model. MPI decomposition shows that productivity dynamics in the poverty-oriented models reflect mainly technical efficiency changes before the COVID-19 pandemic and technological change thereafter, whereas productivity dynamics in the income-distribution-oriented model reflect mainly technical efficiency changes throughout the period. Full article

Against the backdrop of increasing global food security pressures and tightening resource–environment constraints, enhancing grain production efficiency has become a focal international concern. Based on panel data from 16 cities in Shandong Province, China, spanning 2013 to 2022, this study employs the DEA–Malmquist index, SBM model, and Spatial Durbin model to measure grain production efficiency and analyze its spatiotemporal evolution and influencing factors. The findings reveal that Shandong’s grain production efficiency has generally improved but exhibits a spatial differentiation pattern of “higher in Western Shandong, lower in Eastern Shandong,” with significant positive spatial correlation and agglomeration effects. Mechanization significantly boosts efficiency, while urbanization, excessive fertilizer and pesticide use, and labor surplus exert notable negative impacts. This research clarifies the spatial spillover mechanisms and key constraints of efficiency, providing scientific evidence and practical guidance for optimizing agricultural resource allocation, promoting regional collaborative innovation, and formulating differentiated food security policies in Shandong Province and other regions with similar natural–economic conditions. Full article

The embedded finance paradigm is fundamentally restructuring digital economies by seamlessly integrating financial services into non-financial digital infrastructures. This study dynamically evaluates the productivity frontiers of Sea Limited’s embedded fintech operations (SeaMoney) across six core geographic markets (Indonesia, Thailand, Vietnam, the Philippines, Malaysia, and Brazil) over the 2023–2026 temporal horizon. Employing a rigorous Panel Data Envelopment Analysis (DEA) Malmquist Productivity Index framework, the research measures systemic performance by analyzing Sales & Marketing (S & M) Expenses and the undesirable Non-Performing Loan (NPL) rate as inputs, against Gross Loan Outstanding as the primary credit output. Before model execution, robust isotonicity was empirically validated using Pearson correlation matrices. The empirical findings reveal profoundly robust systemic performance across the global ecosystem, driven primarily by overarching algorithmic innovations captured by the Technical Change (TC) index. However, this technological boundary exhibits a stabilizing deceleration over time, indicative of a maturing ecosystem transitioning from explosive, frontier-shifting innovation to optimized refinement. Furthermore, localized managerial optimization, measured by the Efficiency Change (EC) index, displays significant regional heterogeneity. While markets like Brazil demonstrated aggressive late-stage efficiency spikes, and core Southeast Asian markets (such as Vietnam and the Philippines) maintained highly stable, competitive trajectories, other regions, such as Thailand, experienced notable managerial regression. This regression signals severe internal frictions in optimizing local marketing budgets against rising credit defaults. Managerial Implications: These findings provide critical strategic insights for orchestrators of the multinational e-commerce ecosystem. The empirical evidence suggests that relying exclusively on centralized technological scaling, such as unified platform infrastructure and global AI architectures, is insufficient for sustained operational growth. To maintain a competitive advantage, operations executives must deploy hyper-localized resource-allocation and customer-acquisition frameworks tailored to specific regional market dynamics and consumer behavior. Sustainable scaling in cross-border digital commerce requires a precise dynamic equilibrium: leveraging robust global technological infrastructure while executing highly adaptive, market-specific operational and marketing optimizations to maximize customer lifetime value (CLV), eliminate customer acquisition waste, and streamline localized transaction and engagement cycles. Full article

Sustainable industrial transition requires productivity evidence that separates real efficiency improvement from scale expansion, capital deepening, and reporting change. This study develops a reproducible frontier-productivity diagnostic for provincial leading industry policy, using official 2013–2023 sector panels for 23 two-digit manufacturing sectors in Shandong Province and a matched 2019–2023 benchmark against Jiangsu. The framework combines input-oriented Banker–Charnes–Cooper (BCC) data envelopment analysis (DEA), Simar–Wilson bootstrap bias correction, Malmquist total factor productivity change (TFPCH) decomposition, producer price index (PPI) deflation diagnostics, scale-productivity classification, and targeted sensitivity tests. Bootstrap correction lowers mean BCC efficiency from 0.77 to 0.69 in Shandong and from 0.79 to 0.70 in Jiangsu. Uniform provincial PPI deflation leaves constant-returns-to-scale (CRS) Malmquist estimates almost unchanged, whereas asymmetric deflation creates measurable sensitivity. Direct sector-cluster resampling places Shandong’s aggregate TFPCH at 1.016 with a 95% interval of 0.995–1.045, supporting a near-stationary interpretation rather than a broad upgrading surge; Jiangsu’s corresponding estimate is 0.976 with a 95% interval of 0.955–0.997. The study does not measure environmental performance directly. It shows how frontier-productivity evidence should be stress-tested and paired with environmental indicators before it is used in sustainability-oriented industrial policy. Full article

The sustainability of olive oil cooperatives is a critical issue for the stability and competitiveness of the Mediterranean agri-food sector in an environment of increasing environmental pressures, structural constraints, and changing market conditions. This study assesses the performance and sustainability of 33 Greek olive oil cooperatives over the period 2020–2024 using a non-radial Maximum Distance from the Frontier (MDF) DEA model and the Malmquist Productivity Index. The empirical results highlight strong structural heterogeneity in performance, with average technical efficiency under constant returns to scale remaining relatively low (mean CRS efficiency = 0.49) and scale efficiency averaging 0.77, indicating that a large share of cooperatives operates far from the best-practice frontier and below optimal production scale. The diachronic evolution of productivity appears moderate and unstable, driven mainly by improvements in relative efficiency rather than technological progress. The Malmquist analysis reveals an average technological change index below unity (mean TECHCH = 0.84), reflecting the slow diffusion of modern processing and standardization technologies across the sector. By integrating static and dynamic efficiency analyses, the study provides a comprehensive assessment of productivity dynamics and sustainability challenges in Greek olive oil cooperatives. The findings contribute to a deeper understanding of structural inequalities and highlight the economic foundations of sustainability in cooperative agri-food systems, offering directions for the transition toward more sustainable and competitive production patterns. Full article

This study evaluates the efficiency of fiscal support policies for village-level collective economies in S Province, a frontier region of China, over the analytical period of 2018–2023, which includes the policy implementation years (2019–2022) plus one pre-policy and one post-policy year. Integrating theories of collaborative governance, resource alertness, and inclusive rural development, we construct an efficiency measurement framework to assess policy performance across 13 regions. Static efficiency is measured using DEA-BCC and super-efficiency SE-DEA models, while dynamic total factor productivity (TFP) is analyzed via the DEA–Malmquist index. The entropy-weighted method is employed to ensure robust indicator weighting. The findings reveal the following: (1) The average super-efficiency is 0.855, indicating relatively high expenditure efficiency but significant regional disparities and room for improvement. (2) The TFP declined by an average of 9.7% over the analytical period (2018–2023), primarily due to technological regression, despite stable technical efficiency. Based on the TFP performance, regions are categorized into high-, middle-, and low-efficiency tiers. Accordingly, we propose policy recommendations including efficiency-driven funding allocation, long-term support mechanisms combining technological innovation and management empowerment, regionally differentiated strategies, and strengthened multi-stakeholder collaboration. This study provides empirical evidence for optimizing fiscal policies to promote the sustainable development of rural collective economies and advance inclusive rural development in frontier regions. Full article

Manufacturing productivity in ASEAN has become increasingly important as the region joins global value chains and recovers from COVID-19 disruptions. However, it remains uncertain whether output growth results from true productivity improvements or from changes in factor utilization. This study analyses the efficiency and productivity trends in six ASEAN countries, namely Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam, from 2000 to 2022. It employs an input-oriented Data Envelopment Analysis (DEA) under both constant and variable returns to scale to assess technical, pure technical, and scale efficiency, while the Malmquist Productivity Index (MPI) decomposes total factor productivity into efficiency and technological change. Results show significant variation among countries and over time. Singapore and Malaysia consistently stay near the regional production frontier, whereas Indonesia, Thailand, and Vietnam lag in efficiency despite strong output and investment growth. Productivity shifts mainly stem from technological advances rather than efficiency gains, especially slowing during the pandemic. Scale inefficiency remains a key performance issue, particularly for Indonesia and Singapore, worsening after 2020. These insights indicate that ASEAN manufacturing competitiveness hinges not only on capital investment but also on converting inputs into productivity improvements. This study offers a comparative analysis of ASEAN manufacturing efficiency and productivity performance. Full article

Improving productivity under resource and environmental constraints is a key challenge for sustainability-oriented transformation in manufacturing. Using panel data from 30 Chinese provinces during the period 2010–2024, this study examines how regional digital innovation capability is associated with manufacturing total factor productivity at the provincial level. A multidimensional digital innovation index is constructed using the entropy-weighting method, while manufacturing total factor productivity (TFP) is measured using the DEA–Malmquist index. In this study, conventional manufacturing TFP is treated as a productivity-oriented proxy within a sustainability-oriented transformation context, rather than as a direct measure of environmental performance. The empirical framework applies a two-way fixed-effects model and is complemented by supplementary instrumental-variable estimation, mediation analysis, and threshold regression to examine transmission channels and nonlinear effects. The results indicate that digital innovation capability is positively associated with manufacturing TFP, with stronger associations observed in regions that have more developed digital and innovation foundations. Decomposition results show that the gains are mainly related to technological progress rather than short-term efficiency improvements, suggesting that digitalization is reflected primarily through innovation-led upgrading. Mechanism tests further show that improvements in R&D efficiency, data element allocation, and human capital structure play important mediating roles. A significant threshold effect is also observed: When the share of digital-skilled labor exceeds a critical level, the productivity return from digital innovation increases markedly. These findings underscore the role of digital innovation and digital maturity in supporting manufacturing productivity upgrading within a sustainability-oriented transformation context and imply that policy should prioritize coordinated investment in digital infrastructure, data governance, and digital skills development. Full article

This study examines the efficiency and productivity of public education expenditure in 20 countries using Data Envelopment Analysis (DEA) and the Malmquist Productivity Index over the period 2011–2023. Focusing on science and mathematics performance at the primary and lower-secondary levels, the results show that higher public spending does not necessarily lead to better educational outcomes, highlighting the importance of efficient resource allocation. The DEA estimates reveal substantial cross-country heterogeneity in efficiency, while the Malmquist results indicate positive total factor productivity growth across all countries, driven mainly by technical progress rather than efficiency catch-up. Countries such as Morocco, Japan, Turkey, and Iran exhibit sustained productivity improvements, particularly in 2019–2023. Persistent disparities in efficiency and productivity are closely associated with differences in education policies, governance, and socio-economic contexts. Overall, the findings stress the need for efficiency-oriented education reforms to enhance performance and promote sustainable growth. Full article

Sustainable low-carbon logistics serves as a key driver for economic development in China’s eastern coastal regions. This study evaluates the efficiency of low-carbon logistics across 12 provinces from 2013 to 2022, incorporating both environmental and economic dimensions. The analysis begins with Pearson’s correlation tests to examine relationships between input and output variables, followed by a three-stage Data Envelopment Analysis (DEA) model to compute efficiency scores. After adjustment, overall comprehensive technical efficiency slightly declined from 0.811 to 0.799, while pure technical efficiency improved from 0.919 to 0.931 and scale efficiency decreased from 0.885 to 0.859. Provinces such as Hebei and Liaoning demonstrate high and stable development, whereas Beijing and Hainan are constrained by declining scale efficiency. Expanding the research scope from individual provinces to the entire eastern coastal region, this study combines a three-stage DEA model with the Malmquist index to provide both static and dynamic analysis. A scientifically constructed indicator system incorporates carbon emissions, highlighting the synergy between economic and environmental performance. A key finding is the identification of scale diseconomies as a significant constraint on regional low-carbon logistics efficiency. The results suggest that policymakers should adopt tailored strategies, prioritize targeted environmental investments, and enhance cross-regional collaboration. For corporate managers, we emphasize shifting from scale-driven expansion to technology-enabled refinement, with a focus on advancing precision in operations. These insights offer a valuable reference for promoting sustainable, high-quality, and low-carbon logistics development in other regions. Full article

With the acceleration of global urbanization, water resources, as a core element supporting the economic and social development of cities, have seen their green configuration efficiency become a significant bottleneck restricting the sustainable development of cities. In order to alleviate the contradiction between water resources supply and demand, and to optimize the water supply issue brought about by rapid urbanization, based on the DEA–Malmquist index method, this study systematically measured the dynamic evolution characteristics of the green configuration efficiency of water resources in the Yellow River areas of Gansu Province, China from 2012 to 2022, and analyzed the key factors affecting these efficiencies. The research findings show that from 2012 to 2022, the Yellow River areas in Gansu Province demonstrated DEA effectiveness, while the majority of the remaining areas experienced varying degrees of fluctuation and increase in the efficiency of green water resource allocation, with an overall average increase rate of 4.28%. By decomposition of the Malmquist green configuration efficiency index, it was found that from 2012 to 2022, the green configuration efficiency of water resources in the Yellow River areas of Gansu Province showed an overall trend of fluctuating upward first and then decreasing. The Yellow River areas of Gansu Province all showed technological progress to varying degrees, but due to the limitation of the decline in the technical efficiency index, some areas failed to achieve the efficient utilization of green allocation of water resources. Based on the research conclusions, countermeasures and suggestions for improving the efficiency of green water resource allocation in various regions of Gansu Province are put forward. Full article

Background: Ports play a strategic role in the efficiency and sustainability of European transport corridors; however, empirical evidence on their performance remains limited, particularly for Eastern European countries. This study aims to assess the technical efficiency and productivity dynamics of Romanian ports along the Danube corridor in a context of structural change and evolving cargo flows. Methods: Technical efficiency is estimated using an output-oriented Data Envelopment Analysis (DEA) model under variable returns to scale, followed by bias correction and determinant analysis employing the Simar–Wilson bootstrap procedure. Productivity change is examined separately using the Malmquist Productivity Index based on original DEA distance functions. Results: The analysis reveals substantial heterogeneity in efficiency levels across ports, with bias-corrected estimates indicating that efficiency differentials are structural rather than statistical. Cargo specialization emerges as the main determinant of efficiency, while location effects are found to be asymmetric. Efficiency levels are largely stable over time, and productivity change is modest, being driven exclusively by efficiency change, with no evidence of technological progress. Conclusions: These findings suggest that the performance of ports along the Romanian Danube corridor is shaped primarily by structural and organizational factors rather than temporal dynamics, underlining the importance of targeted policy interventions focusing on traffic consolidation, port specialization, and coordinated spatial and hinterland planning to enhance inland port performance within European transport corridors. Full article

Against the backdrop of global energy transition and sustainable development, advancing the new energy industry has become a critical pathway for optimizing energy structures and achieving the dual carbon goals. However, while China’s new energy sector has experienced rapid growth, it has also exposed a series of challenges, including insufficient innovation momentum, irrational resource allocation, and low conversion rates of R&D outcomes. To delve into the root causes and propose improvement pathways, this study selected 76 listed new energy enterprises from 2021 to 2023 as samples. It comprehensively employed the DEA-BCC model, Malmquist productivity index, and Tobit regression model to conduct empirical analysis across three dimensions: static, dynamic, and influencing factors. The findings revealed: firstly, during the study period, overall static efficiency remained low, with only about 32.90% of enterprises operating efficiently. Efficiency decomposition indicated that low and unstable pure technical efficiency constrained overall efficiency gains. In contrast, while scale efficiency was relatively high, its growth was sluggish, and some enterprises exhibited significant scale irrelevance. Secondly, dynamic total factor productivity exhibited fluctuating growth primarily driven by technological progress. However, declining technical efficiency—particularly the deterioration of scale efficiency—indicated that while the new energy industry advanced technologically and expanded in scale, its management capabilities had not kept pace. This mismatch among the three factors trapped the industry in a “high investment, low efficiency” dilemma. Thirdly, regression analysis of influencing factors indicated that corporate governance and market competitiveness were pivotal to innovation efficiency: the proportion of independent directors and revenue growth rate exerted significant positive impacts, while equity concentration showed a significant negative effect. Firm size had a weaker influence, and government support did not demonstrate a significant positive impact. Accordingly, this paper proposes pathways to enhance innovation efficiency in new energy enterprises, including optimizing corporate governance structures, formulating differentiated subsidy policies, and improving the innovation ecosystem. The findings of this study not only provide empirical references for the innovative development of the new energy industry but also offer theoretical support for relevant policy formulation. Full article

With increasing emphasis on ecological conservation and food security, cultivated land issues have become more prominent. This study focuses on Jilin Province and uses nine prefecture-level administrative units and prefectures as the basic analytical units. Using continuous data for 2000–2023, this study analyzes the spatiotemporal evolution of cultivated land use efficiency (CLUE). By 2023, most regions had achieved ecological safety (ES), examined through their coupling and coordination. The Super-Efficiency SBM-DEA model and the Malmquist–Luenberger (ML) index were used to evaluate the static and dynamic changes in CLUE. A DPSIR–PLS-SEM integrated framework was applied to identify causal mechanisms influencing ES, while the TOPSIS method was employed to assess overall evolutionary trends. In addition, the coupling coordination degree (CCD) model combined with kernel density estimation (KDE) was used to characterize the interaction between CLUE and ES and their spatial evolution. Results indicated the following: (1) From 2000 to 2023, overall CLUE in Jilin Province showed an upward trend with fluctuations, while regional disparities narrowed and spatial distribution became more balanced. (2) The composite ES index increased from 0.3009 to 0.7900, accompanied by a marked expansion of areas classified as secure. (3) The CCD improved from a basic level to a high-quality coordination level, indicating enhanced synergistic development. Higher coordination was observed in central and eastern regions, whereas western and peripheral areas lagged. This study integrates multi-dimensional modeling approaches to systematically assess the coupled dynamics on cultivated land use efficiency and ecological safety, providing insights for land management and policy formulation. Full article

The global shift towards sustainable energy and stringent climate policies has underscored the need for decarbonizing energy systems, electrifying transportation, and transforming supply chains. In this context, China’s new energy vehicle (NEV) industry, as the largest global producer and consumer of automobiles, is pivotal in advancing energy substitution and achieving carbon reduction goals. This study investigates the energy efficiency and supply chain transformation within China’s NEV sector, leveraging panel data from 12 representative provinces over the period 2017–2023. Employing a robust analytical framework that integrates the DEA-BCC model, Malmquist index, and Tobit regression, the study provides a dynamic and regionally differentiated assessment of NEV industry efficiency. The results reveal significant improvements in total factor energy efficiency, predominantly driven by technological progress. R&D intensity, infrastructure development, and environmental regulation are identified as key enablers of efficiency, while excessive government intervention tends to hinder performance. The findings offer valuable empirical insights and policy recommendations for optimizing China’s NEV industry in the context of energy system transformation and sustainable industrial development. Full article