Search Results (428)

As the climate problem is getting more and more serious and the “low-carbon revolution” of globalization is emerging, the logistics industry, as a high-end service industry, must also take the road of low-carbon development. Improving logistics carbon emission efficiency (LCEE) is gradually becoming an inevitable choice to maintain sustainable social development. The study uses the Super-SBM (Super-Slack-Based Measure) model to evaluate the urban LCEE from 2013 to 2022, explores the contribution of efficiency changes and technological progress to LCEE through the decomposition of the GML (Global Malmquist–Luenberger) index, and reveals the influence of digital transformation and energy consumption structure on LCEE by using the Spatial Durbin Model, concluding as follows: (1) LCEE declines from east to west, with large regional differences. (2) LCEE has steadily increased over the past decade, with slower growth from east to west. It fell in 2020 due to COVID-19 but has since recovered. (3) LCEE shows a catching-up effect among the three major regions, with technological progress being a key driver of improvement. (4) LCEE has significant spatial dependence. Energy consumption structure has a short-term negative spillover effect, while digital transformation has a positive spillover effect. Full article

In the process of evaluating the quality of a company’s development, the issues related to production capacity and environmental pollution have emerged as significant concerns. Drawing on the methodologies employed in previous related research, this study utilizes the Data Envelopment Analysis with relaxation variables and the Global Malmquist–Luenberger index to measure the green total factor productivity of Chinese heavy-polluting enterprises. The main findings of this study are as follows: (1) It is clearly demonstrated that higher managerial effectiveness has a substantial positive impact on the improvement of a company’s green total factor productivity; (2) the digitalization progress within enterprises serves as a moderating factor in the relationship between managerial effectiveness and green total factor productivity; (3) the extent of financial constraints acts as a mediating variable, intervening in the relationship between managerial efficiency and green total factor productivity; and (4) a threshold effect is detected between managerial effectiveness and the debt repayment pressure faced by enterprises. When the threshold values of managerial effectiveness or the quick ratio are surpassed, the influence of managerial effectiveness on the green total factor productivity of enterprises will undergo a change. Full article

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

As pivotal nodes in maritime logistics networks, ports face mounting pressure to reconcile economic growth with environmental sustainability. Although the SBM-Undesirable model has been extensively applied to assess port environmental efficiency (PEE), most applications assume strong disposability and disregard heterogeneity in technological capacities across different port scales, potentially biasing the assessments. To overcome these limitations, coastal ports are initially categorized into three subgroups based on operational scale criteria. A meta-frontier SBM-Undesirable model incorporating weak disposability is then developed to evaluate PEE. Dynamic characteristics are further explored via the Global Malmquist Index. Results indicate substantial disparities between subgroup frontiers and the meta-frontier. The average group PEE (0.732) exceeded the meta PEE (0.570), implying potential overestimation under homogeneity assumptions. Large-sized ports, with a mean technology gap ratio (TGR) of 0.956, operated near the meta-frontier, whereas medium-sized and small-sized ports, with TGRs of 0.770 and 0.600 respectively, exhibited substantial technological gaps. Total factor productivity (TFP) demonstrated a volatile upward trend, averaging 6.8% annual growth. In large-sized and medium-sized ports, TFP growth was primarily driven by technological innovation, whereas in small-sized ports, it stemmed from combined improvements in technical efficiency and technological level. These insights underscore the necessity of differentiated decarbonization strategies for port management. Full article

In the context of global climate change and the escalating energy crisis, the development of new energy vehicles (NEVs) has become a critical strategy for China to foster green transformation and achieve its carbon neutrality goals. This study focuses on A-share-listed NEV companies in China from 2015 to 2023, specifically those listed on the Shanghai or Shenzhen Stock Exchange and subject to domestic regulatory standards and disclosure requirements. These firms were selected due to the representativeness, availability, and quantifiability of their data. A super-efficient-network SBM model based on undesirable outputs and the Malmquist index were employed to assess the static and dynamic green technology innovation efficiency of 260 NEV enterprises. Additionally, the Tobit regression model was applied to analyze the influencing factors. The findings reveal that the overall green technology innovation efficiency of Chinese NEV enterprises is relatively low and has exhibited a declining trend over the years. Furthermore, the efficiency of enterprises in the western regions surpasses that of those in the eastern and central regions. Key factors, including government support, enterprise scale, and R&D investment, significantly inhibit the green technology innovation efficiency of firms. Based on these findings, this paper recommends prioritizing the innovation of core technologies, addressing regional disparities in development, and implementing tailored policies to enhance the green technology innovation efficiency and economic performance of NEV enterprises. Full article

The scientific evaluation of ecological total factor productivity of cultivated land use (ETFPCLU) is fundamental for advancing sustainable utilization of cultivated land resources and safeguarding national food security and ecological stability. Using the epsilon-based measure and the global Malmquist–Luenberger (EBM–GML) index, this study quantifies and decomposes ETFPCLU across China. Spatial–temporal variations and convergence patterns are systematically investigated via an analytical toolkit comprising the spatial mismatch index, Dagum’s Gini coefficient decomposition, and convergence models. The results indicate that Chinese ETFPCLU increased by an average of 2.1% per year from 2001 to 2022, primarily attributed to technical change (TC), with limited contributions from efficiency change (EC). The spatial mismatch between ETFPCLU and TC, as well as EC, is predominantly characterized by low to medium mismatch types, exhibiting a high degree of spatial distribution similarity; inter-regional differences are the main contributors to regional disparities. Furthermore, except for the central region, significant σ-convergence exists in ETFPCLU across the country and in other regions, alongside absolute β-convergence and conditional β-convergence in the four major regions. The analysis concludes that to enhance ETFPCLU, it is essential to strengthen technological innovation, synergistically improve technological efficiency, formulate ecological protection policies tailored to local conditions, and foster collaboration among regions for cultivated land protection. Full article

Background/Objectives: This study introduces the Multi Group Cost Malmquist Index ($CM{g}_m$), a novel tool for comparing and ranking the cost efficiency of multiple groups of similar decision-making units operating in different contexts. It was applied to Greek public hospitals to assess productivity change between 2009 and 2021, covering the period before the economic recession and after the second lockdown during the COVID-19 pandemic. The study aimed to determine the impact of these external shocks on hospital efficiency and to identify differences in cost productivity based on hospital size and regional location. Methods: Data envelopment analysis was employed to compute the Malmquist indices for productivity change and ranking. Overall, 109 Greek public hospitals were analysed using three models: as a single group, classified by bed capacity, and classified by regional health authority (RHA). Cost productivity was decomposed into its core measures. Results: During the economic crisis, hospitals improved their cost productivity by 13.2%, whereas during the pandemic, it declined by 32.1%, primarily due to cost frontier deterioration resulting from increased healthcare demand and strained resources. Medium-sized hospitals exhibited higher cost efficiency than small and large hospitals. Regional disparities were also observed, with hospitals in the 5^th and 7^th RHAs outperforming those in 1^st and 2^nd RHAs. Conclusions: The findings highlight the pandemic’s disruptive impact on hospital cost productivity compared to the efficiency gains during the economic crisis. It is encouraging, though, that hospitals are recovering again after the lifting of strict lockdown measures. The $CM{g}_m$ is a valuable tool for policymakers, offering insights into hospital performance across multiple groups. Future healthcare policies should prioritise resource optimisation and address regional disparities to enhance system-wide efficiency and resilience in times of crisis. Full article

The purpose of this study is to propose a novel approach for measuring productivity changes in decision-making units (DMUs) over time and evaluating the performance of each DMU under uncertainty in terms of progress, regression, and stagnation. To achieve this, the Malmquist productivity index (MPI) and the data envelopment analysis (DEA) models are extended, and a new productivity index capable of handling uncertain data are introduced through a robust optimization approach. Robust optimization is recognized as one of the most applicable and effective methods in uncertain programming. The implementation and calculation of the proposed index are demonstrated using data from 15 actively traded stocks in the petroleum products industry on the Tehran stock exchange over two consecutive years. The results reveal that a significant number of stocks exhibit an unfavorable trend, marked by a decline in productivity. The findings highlight the efficacy and effectiveness of the proposed robust Malmquist productivity index (RMPI) in measuring and identifying productivity trends for each stock under data uncertainty. Full article

This study analyses the effects of public hospital mergers in Portugal, particularly the creation of hospital centers, on productivity levels. Grounded in the theoretical frameworks of New Public Management and Efficiency Theory, a Data Envelopment Analysis (DEA) approach, combined with the Malmquist Productivity Index, was used to evaluate performance. Results for the 2013–2015 period show no statistically significant difference in productivity levels between merged hospitals (hospital centers) and non-merged hospitals (hospital units). However, for hospitals merged in 2007, there is evidence of significant productivity gains in the post-merger period (2008–2014). These findings partially support the assumptions of New Public Management and Efficiency Theory concerning efficiency improvements through hospital mergers in the public sector. Full article

The property-liability insurance market in Taiwan has implemented three-stage deregulation on rate-making since 2002. This research investigates whether the rating liberalization brought about improvements in efficiency and productivity of the property-liability insurance market. Using data on property-liability insurers in Taiwan over 2001 to 2019 and employing data envelopment analysis, we show that technical, cost, and revenue efficiencies have improved after rating liberalization. Post-liberalization productivity has improved as well, and the decomposition of productivity change demonstrates that change in technology contributes most to productivity improvement at the inception of liberalization, and the contribution of efficiency improvement follows when rating controls are further released. Further analyses reveal that technical and revenue efficiency rose in the third stage of liberalization and cost efficiency improved in the second and third stages. Our findings suggest that the removal of price controls creates an operating environment with less restrictions and thus favors progress in efficiency of the property-liability insurance market. Full article

The energy market in the European Union is dominated by large energy companies. However, the liberalization of this market, the removal of market barriers, and the encouragement of small companies to enter the market are creating new conditions and changing the structure of companies. In addition to large energy companies, a significant number of small entities are also emerging. The aim of this research is to analyze the relationship between the size of energy companies and their technical efficiency. This analysis was carried out for the period 2019–2023. In order to assess the efficiency of the researched energy companies, the Data Envelopment Analysis (DEA) method was employed. The analyzed enterprises were divided into three groups: small (IA), medium (IB), and large (II). The following economic categories were adopted as the division criteria: 1. net sales revenue; 2. operating costs; 3. fixed assets. The findings of our study suggest that small and medium-sized energy companies can exhibit levels of efficiency that are comparable to those of larger enterprises. This result suggests that companies of different sizes can coexist in the energy market. The results obtained are not completely conclusive, as statistically significant differences in technical efficiency (TE) were recorded in 2021 and 2022 but only between small enterprises (IA) and medium-sized enterprises (IB). This study highlights the potential of small energy companies to contribute effectively to Poland’s energy sector and suggests that supporting their development could enhance energy security and market competition. However, many energy companies—regardless of size—exhibited low levels of efficiency, underlining the need for deeper investigation into the sources of inefficiency. Full article

Background: This study examined shifts in the productivity and efficiency of Opioid Substitution Treatment (OST) units in Greece from 2019 to 2022. OST units address withdrawal symptoms in individuals discontinuing psychoactive substances. They also offer mental health care, primary healthcare, psychosocial support, and other integrated services, aiming to provide holistic addiction treatment and promote social reintegration. Methods: We assessed the contributions of 54 OST units addressing opioid addiction using non-parametric Malmquist Data Envelopment Analysis (DEA). Data were collected from all OST units operating in Greece during this period, with a focus on key external factors such as the COVID-19 pandemic and rising global trends in stimulant and synthetic opioid use. Results: The analysis revealed a productivity decline in 2020, followed by improvements in the next two years. However, technical efficiency declined, suggesting a decrease in resource utilization. Conclusions: This dip in efficiency likely reflects the impact of emerging drug trends, particularly stimulants and synthetic opioids, which lack standardized treatment protocols. These findings highlight the urgent need for new treatment options to address evolving addiction trends. The study also underscored the need for improved data collection and monitoring to optimize resource allocation and enhance operational efficiency in OST units. Strengthening evidence-based policies and expanding access with low-threshold treatment services could improve patient outcomes and the overall effectiveness of OST programs. Full article

Enhancing the green production efficiency of cotton contributes significantly to achieving carbon neutrality and agricultural sustainability. Based on county-level panel data from 2002 to 2020 and daily average temperature and precipitation data from 53 meteorological stations in Xinjiang, this study employs a non-desirable output super-efficiency slack-based measure model, the Malmquist index, and Moran’s index to analyze the temporal and spatial changes in the green production efficiency of cotton across counties in Xinjiang. From a dynamic evolution perspective, without considering non-desirable outputs, the overall cotton production efficiency at the county level exhibits an upward trend; however, when non-desirable outputs are taken into account, the green production efficiency of cotton shows a declining trend, with a general convergence trend among counties (cities). From 2002 to 2020, the overall green production efficiency of cotton in Xinjiang counties decreased from 0.531 to 0.442, with an annual average decline rate of −0.882%. Spatially, as temperatures rise in northern Xinjiang and rainfall increases in the west, high-value areas for cotton green production efficiency have shifted northward and westward, transforming the spatial distribution pattern from “high in the south and low in the north” to “high in the north and low in the south”. The spatial clustering effect among counties is significant, exhibiting a “clustered distribution” pattern. To improve the green production efficiency of cotton, it is recommended to promote ecological protection efforts, disseminate advanced agricultural technologies, implement differentiated strategies, leverage spatial clustering effects, and strengthen theoretical and technological research. Full article

A critical natural solution to combat global warming and reduce carbon emission is the forest carbon sink (FCS). Owing to variations in geographic location, policy formulation, and economic development, Chinese provinces exhibit significant disparities in forest carbon sink efficiency (FCSE). Therefore, evaluating and enhancing FCSE and optimizing resource allocation have emerged as pressing issues. This study develops a pioneering analytical framework for the systematic estimation and optimization of FCS resources. It measures FCSE, considering both dynamic and static aspects and adopting a spatial–temporal perspective, utilizing the Malmquist Index and Super Efficiency Slacks-Based Measure to analyze the primary factors influencing FCSE. The Autoregressive Integrated Moving Average method forecasts carbon sink goals for typical regions for the years 2030, 2045, and 2060. To effectively enhance FCSE and rationally optimize FCS resource allocation, this study constructs the Inverse Data Envelopment Analysis. The study’s findings indicate significant disparities in the extremes of the average FCSE across Chinese regions, with a mean value difference of 2.2188. Technological change is the primary driver of advancements in FCSE. To achieve the 2060 carbon sink goal, each input indicator requires a substantial increase. Drawing on insights into the FCS landscape, the study delineates regional disparities and offers a scientific foundation for policymakers to devise strategies and address sustainability concerns regarding FCS. Full article

This study evaluated the efficiency performance of the world’s top ten seed-producing companies from 2016 to 2022, exploring the interplay between asset scale, technological innovation, and resource allocation in the context of the third global wave of seed industry mergers and growing external uncertainties. Against the backdrop of rising sustainability demands and low-carbon transitions, optimizing firm-level efficiency has become central in balancing economic performance with environmental responsibility. Using Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI), in this study, we conducted a comprehensive static and dynamic assessment of firm efficiency. The results reveal considerable heterogeneity across firms and over time. Corteva’s overall technical efficiency (OTE) rose from 0.57 in 2018 to 0.91 in 2022, reflecting successful post-merger integration and digital innovation. DLF achieved an OTE = 1.00 in 2020 and 2022, indicating stable specialization on an optimal scale. In contrast, Bayer’s OTE dropped from 0.72 in 2016 to 0.36 in 2022, underscoring the challenges of resource integration after large-scale mergers. In terms of productivity dynamics, Corteva exhibited a sharp EFFCH surge to 1.7041 in 2018–2019, reflecting a phase of rapid efficiency recovery following its post-merger restructuring. Syngenta also demonstrated strong managerial improvement, with its EFFCH reaching 1.3759 in 2017–2018 and maintaining positive momentum thereafter. Over the entire period, Syngenta recorded the highest cumulative growth in efficiency (up 40.76%), while Bayer showed a significant decline (−28.33%), highlighting contrasting integration outcomes. On the technological front, DLF stood out with a TECHCH increase of 34.67%, suggesting that innovation remained the key driver of long-term productivity gains, particularly among firms that avoided aggressive mergers. These findings emphasize the importance of aligning technological investment with scalable and resilient operational structures to achieve sustainable efficiency. This study offers empirical guidance for policymakers and strategic planners seeking to strengthen the seed industry’s role in green transformation, while also providing a framework applicable to other capital-intensive sectors undergoing structural transition. Full article