Search Results (39)

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

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 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

Global economic change and technological development have made the digital economy a key force for economic growth. With its innovation, penetration, and integration, the digital economy has penetrated into all aspects of the manufacturing industry, bringing opportunities and challenges to the manufacturing industry. Based on the development level of China’s digital economy and manufacturing industry data from 2001 to 2023, using DEA–BCC–Malmquist, this paper studies the impact of the digital economy on the total factor productivity of the manufacturing industry. It is found that the development of the digital economy impacted the total factor productivity of the manufacturing industry, in which cost and innovation research and development played an intermediary effect, and the digital economy has shown a more positive push in technology-intensive and labor-intensive industries than in capital-intensive ones. Based on the findings, this research is designed to empower the manufacturing sector to capitalize on emerging digital economy opportunities while advancing sustainable development goals. Full article

Passenger transportation in Japan’s main metropolitan areas is operated by the JR companies, which were privatized and divested from Japan National Railways (JNR) in 1987 and by 16 major private railway companies with large-scale operations. Although their core business is transportation, the major private railway companies have adopted a strategy of diversification, and they engage, e.g., in real estate and distribution businesses. This study examines the relationship between the degree of business diversification and the production efficiency of Japan’s major private railway companies from the perspective of a future business model. To this aim, this study applies data envelopment analysis combined with the Malmquist index to the data of the railway companies from 1987 to 2019. We focus on four phases of activities: cost, operational resource, operational output, and total revenue. This study is the first to analyze the diversified management of Japanese railroad companies by evaluating their production efficiency and its changes over time. The results of the analysis reveal that, while all companies’ earnings have generally increased, the less diversified they are, the more they struggle to optimize personnel and other overhead expenses and resources, lowering production efficiency. Full article

Multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems exhibit enormous computational costs for high-dimensional problems. To address this problem, we propose a novel approach for reducing the dimensionality of MIMO systems. The method leverages the Takenaka–Malmquist basis and incorporates the strictly complex-valued relevant vector machine (SCRVM). We refer to this method as covariance-free maximum likelihood (CoFML). The proposed method avoids the explicit computation of the covariance matrix. CoFML solves multiple linear systems to obtain the required posterior statistics for covariance. This is achieved by exploiting the preconditioning matrix and the matrix diagonal element estimation rule. We provide theoretical justification for this approximation and show why our method scales well in high-dimensional settings. By employing the CoFML algorithm, we approximate MIMO systems in parallel, resulting in significant computational time savings. The effectiveness of this method is demonstrated through three well-known examples. Full article

The exponential growth of the agricultural industry in the Amazon region has brought about notable economic advancements. However, this growth has substantially cost the region’s ecosystems, manifesting in increased deforestation and biodiversity degradation within the Amazon forest. This article is dedicated to assessing the eco-efficiency of agricultural production in Amazon Biome municipalities. It places particular emphasis on identifying critical determinants through the utilization of the classic Data Envelopment Analysis (DEA) model for efficiency computation, super-efficiency models for distinctive characterization, bootstrap computational techniques for robust resampling, and the Malmquist index for calculating annual eco-efficiency indices of each Decision-Making Unit (DMU). An exploration of the correlation between efficiency and meteorological attributes of the municipalities is conducted. The findings of this study reveal the following significant points: Eco-efficient municipalities within the Amazon Biome can serve as benchmarks for other DMUs striving to attain optimal input–output levels, most municipalities in the Amazon Biome operate close to the productive frontier due to the prevalent technology employed in their agricultural activities, the nature of the technological frontier’s return suggests that small and large DMUs possess eco-efficiency potential, and the current dataset does not yield conclusive evidence regarding a direct correlation between the variables. Leveraging this information, strategic pathways can be formulated to drive economic development in tandem with the sustainability of Amazon Biome municipalities. These strategies promise to foster social, economic, and environmental benefits for the populace while providing valuable insights to inform future research within this thematic domain. Full article

Road freight transport, an essential component of the logistics sector, faces challenges: high cost, low efficiency, and environmental impact. The need has become urgent to achieve a synergistic balance between low-carbon and high-efficiency development. This study used a three-stage DEA–Malmquist index model to analyze the road freight efficiency of Wuhan and 16 other cities in China from 2015 to 2020, and we compared Wuhan’s performance with its peers. In addition, grey correlation analysis was used to evaluate the low-carbon development of urban road freight transport in Wuhan. Through the calculation of the degree of synergy between low-carbon development and freight transport efficiency, this study provides insights into the synergistic development of low-carbon and efficient road freight transport in Wuhan. The key findings show that the total factor productivity of road freight transport in Wuhan was generally on a downward trend from 2015 to 2020, and was lower than that of the average of the 17 selected Chinese cities. The carbon emissions of road freight transport in Wuhan inversely related to its scale efficiency. This study also points out that the synergy between low-carbon development and the economic efficiency of road freight transport in Wuhan is not high and needs to be further integrated and optimized. Full article

Improving carbon emission performance (CEP) is the key to realizing the goal of “carbon peaking and carbon neutrality” for China. Using a panel dataset of 282 cities at prefecture level and above in China from 2003 to 2017, this study employs the Global Malmquist–Luenberger (GML) index to measure CEP. Moreover, this study investigates the effect and transmission mechanisms of urbanization on CEP based on the extended STIRPAT model. The results show a significant positive “U-shaped” relationship between urbanization and CEP. When urbanization exceeds the inflection point, urbanization is conducive to improve CEP in Chinese cities. The mechanism analysis illustrates that human capital has a positive impact on CEP, while technological innovation inhibits it. The findings of this study can provide a scientific basis for local governments to formulate different strategies to improve China’s high-quality development through human capital accumulation and low cost and scale of low-carbon technologies. Full article

The paper studies the productivity change of the commercial banks in the CEE countries over the post-crisis period 2013–2018. The productivity change is measured by the Malmquist Productivity Index and its sub-components, applying two approaches—the asset-oriented and profit-oriented intermediation approaches. The analysis uses data from a balanced panel of 181 commercial banks in 11 CEE countries. We find that commercial banks’ productivity, measured with the asset-oriented intermediation approach, decreased in most of the CEE countries over 2013–2018, with a decline ranging, on average, from 1% to 6.9%, driven mainly by a decline in technical efficiency. Nevertheless, estimates using the profit-intermediation approach point to productivity growth in commercial banks in all CEE countries, ranging, on average, from 0.5% to 6.3%. The empirical findings imply the need for the CEE commercial banks to further digital transformation and cost rationalization. Full article

This study undertakes a comprehensive analysis of vegetable production efficiency in China using input–output data from 30 provinces spanning 2011 to 2017. By incorporating environmental pollution costs as undesirable outputs alongside vegetable output value, we employ Data Envelopment Analysis (DEA) with the Banker, Charnes, and Cooper (BCC) model and the Malmquist index model. Our assessment reveals both annual and inter-period efficiency changes. The findings highlight a modest overall efficiency in China’s vegetable production and significant regional disparities. Technical progress emerges as a pivotal determinant of total factor productivity (TFP). Recognizing these dynamics, we propose policy recommendations that prioritize technical innovation, sustainable practices, rural infrastructure enhancement, and specialized cultivation methods. Implementing these recommendations could bolster China’s position in international trade negotiations due to increased exports and potentially drive broader environmental policy reforms. As vegetable production becomes more efficient and sustainable, there might be a shift in labor needs, potentially leading to migration patterns or changes in employment structures. These insights contribute to the sustainable development of China’s vegetable industry, offering a broader understanding of the dynamics of agricultural efficiency in the context of environmental sustainability. Full article

China’s raw milk production is confronted with problems such as high production costs, stringent environmental constraints, weak industrial interest linkages, etc. The extensive and inefficient operation mode seriously restricts the further development of China’s dairy industry. How to increase the production efficiency of raw milk and realize the transition from “a country with high milk production” to “a country with high-efficiency milk production” has become the key to further developing China’s dairy industry. In order to explore the upgrading path of the raw milk industry in China, this study used the DEA-Malmquist model to estimate the production efficiency of raw milk in China and analyze its spatial and temporal distribution characteristics based on raw milk production input and output data at four scales (i.e., free-range, small-scale, medium-scale, and large-scale) from 2004 to 2020. It then adopted the SFA model to explore the relationship between raw milk input and output factors and the driving factors of production efficiency. Finally, robustness was discussed according to the existing research differences. The study draws several valuable conclusions. First, the production efficiency of raw milk in China from 2004 to 2020 fluctuated upward and showed specific regular regional distribution characteristics, but the spatial–temporal differences were minor. Second, raw milk production efficiency is significantly influenced by various factors, including the proportion of concentrate to roughage consumption, medical and epidemic prevention investment, the price of raw milk, the wage level, and fixed assets. Third, the spatial–temporal distribution and driving factors of raw milk production efficiency are less robust, so efficiency analysis and improvement measures should fully consider analytical methods, scale heterogeneity, indicator systems, and temporal heterogeneity. Full article

The design of cooperative applications combining several unmanned aerial and aquatic vehicles is now possible thanks to the considerable advancements in wireless communication technology and the low production costs for small, unmanned vehicles. For example, the information delivered over the air instead of inside an optical fiber causes it to be far simpler for an eavesdropper to intercept and improperly change the information. This article thoroughly analyzes the cybersecurity industry’s efficiency in addressing the rapidly expanding requirement to incorporate compelling security features into wireless communication systems. In this research, we used a combination of DEA window analysis with the Malmquist index approach to assess the efficiency of the cybersecurity industry. We used input and output factors utilizing financial data from 2017–2020 sources from a US market. It was found that U1—Synopsys and U9—Fortinet exhibited the best performances when relating Malmquist and DEA window analysis. By evaluating ten big companies in the cybersecurity industry, we indicate that U2—Palo Alto Networks and U6—BlackBerry Ltd. companies needed significant improvements and that four other companies were generally more efficient. The findings of this study provide decision-makers a clear image and it will be the first study to evaluate and predict the performance of cyber security organizations, providing a valuable reference for future research. Full article

Vietnam’s textile and garment enterprises make an important contribution to the country with the second largest export turnover. The existence and development of textile and garment enterprises have a significant influence on the socioeconomic development of Vietnam. Currently, Vietnam’s textile and garment industry is facing difficulties caused by the COVID-19 pandemic, along with competition from foreign direct investment (FDI) enterprises. Therefore, it is imperative for managers to assess competitiveness by measuring their past and current performance indicators. This study assesses the performance of Vietnam’s 10 textile and garment enterprises from 2017 to 2020 by combining the DEA–Malmquist productivity index (MPI) and epsilon-based measure (EBM) model. The proposed model considered three inputs (total assets, cost of goods sold, and liabilities) and two outputs (total revenue and gross profit). In addition to showing the best-performing companies from certain aspects during the period (2017–2020), the results show that the EBM method combined with the Malmquist model in the field can be successfully applied. This study is a reference for companies in the textile and garment industry to identify their position to improve their operational efficiency and overcome their weaknesses. Full article

Nowadays, public health issues are increasingly in the spotlight, and the role played by foreign direct investment (FDI) cannot be ignored, especially in developing countries. Scholars have discussed the influencing mechanism of FDI on public health from both positive and negative aspects, but there is little literature focused on the impact of FDI’s green technology spillovers. This paper explores the impact of spontaneous green technology progress induced by FDI, i.e., FDI’s green technology spillover effect, on the public health status of China. It constructs a theoretical model based on the cost discovery theory and uses the Global Malmquist–Luenberger Method to calculate the green technology spillover index; then, it empirically researches the impact of this spillover effect on public health based on the Grossman health product function, using Chinese provincial data from 2007 to 2019. After a series of robustness tests, this paper also discusses the regional heterogeneity and the influencing mechanism. The main conclusions are as follows: Firstly, there is a significant negative correlation between FDI’s green technology spillover and infant mortality, indicating that the spillover effect significantly promotes China’s public health. Secondly, the results of regional heterogeneity show that the spillover effect of green technology presents a decreasing trend from east to west regions. The threshold effect test results also show that, when the level of economic development is extremely low or exceeds a specific threshold, FDI’s green technology spillover will have a positive impact on public health. Finally, FDI’s green technology spillover improves public health by controlling environmental pollution and optimizing industrial activities, but it does not worsen public health by increasing income inequality. The conclusions of this paper provide empirical support and policy suggestions for rationally and effectively utilizing FDI to promote China’s public health in the future. Full article