Search Results (26)

In the context of increasingly complex and dynamic maritime logistics, seaports serve as critical nodes for intermodal transport, energy distribution, and global trade. Ensuring the safe and uninterrupted operation of port infrastructure—particularly berths—is vital for maintaining supply chain resilience. This study explores the impact of multiple risk categories on berth efficiency in a seaport, aligning with the growing emphasis on maritime safety and risk-informed decision-making. A two-stage methodology is adopted. In the first phase, the DEA CCR input-oriented model is employed to assess the efficiency of selected berths considered as Decision Making Units (DMUs). In the second phase, the Analytical Hierarchy Process (AHP) is used to categorize and quantify the impact of four major risk classes—operational, technical, safety, and environmental—on berth efficiency. The results demonstrate that operational and safety risks contribute 63.91% of the composite weight in the AHP risk assessment hierarchy. These findings are highly relevant to contemporary efforts in maritime risk modeling, especially for individual ports and port systems with high berth utilization and vulnerability to system disruptions. The proposed integrated approach offers a scalable and replicable decision-support tool for port authorities, port operators, planners, and maritime safety stakeholders, enabling proactive risk mitigation, optimal utilization of available resources in a port, and improved berth performance. Its methodological design is appropriately suited to support further applications in port resilience frameworks and maritime safety strategies, being one of the bases for establishing collision avoidance strategies related to an individual port and/or port system, too. Full article

The construction of ecological civilization is intrinsically connected to green development. The green development of forestry enterprises serves as a key approach to achieving this goal. The research purpose of this paper is to explore the realization path of green development of forestry enterprises. First, an improved CRITIC (Criteria Importance Through Intercriteria Correlation)–entropy weight method was used to construct a reasonable input-output indicator system. Next, a three-stage data envelopment analysis (DEA) model was employed to evaluate the comprehensive technical efficiency of green development across 33 forestry enterprises in China, using panel data from 2017 to 2022. Finally, the study explored various configurational pathways for achieving green development by integrating the Technology–Organization–Environment (TOE) framework with dynamic qualitative comparative analysis (QCA). The findings reveal that green development in forestry enterprises is shaped by the interplay of multiple factors. Four distinct configurations were identified as instrumental in driving high green development. These configurations could be classified into two categories: the environment–organization synergistic development model and the technology–organization dual-driven model. This study provides empirical insights into the complex configurational relationships underlying green development in forestry enterprises, offering valuable guidance for optimizing development strategies. Full article

The objective of this work is to analyze the relevance of governance (corporate and ownership concentration) for the divisional inter-temporal dynamic efficiency in piped natural gas utilities in Brazil. The main innovative contribution of this work is the application of inter-temporal (dynamic) efficiency analysis with network structure in the first stage, in this case, the ‘Dynamic DEA (Data Envelopment Analysis) with network structure: A slacks-based–DNSBM (Dynamic Network Slacks-Based Measure)’, in which two divisional interactions ${\delta }_{ok}^{\ast }$ (technical–operational and economic–financial division) between ${\tau }_o^{t\ast }$ periods and divisional ${\rho }_{ok}^{t\ast }$ periods are reflected in the overall efficiency scores ${\theta }_o^{\ast }$, representing an approach not yet explored by the previous literature on the sector and subject investigated. The database used corresponds to 21 Brazilian natural gas utilities in the form of a balanced data panel, which were collected for the period 2014–2019. The second stage (explanatory) was estimated through the panel with random effects to identify the relationship between governance and efficiency, considering certain context factors. The results show that the average general efficiency was 74.96%, resulting from the interactions between the average efficiency rates of 72.21% of the technical–operational division and 82.03% of the economic–financial division, and suggest that the corporate governance index and ownership (public or private) are not relevant factors for the efficiency results studied. Full article

The high carbon emissions and pollution of China’s thermal power industry chain have exacerbated environmental and climate degradation. Therefore, accelerating the green transformation process is of great significance in promoting the sustainable development of enterprises. This study selected 30 listed thermal power enterprises in China as research objects, analyzed their data from 2018 to 2022, set targeted input–output indicators for different stages, and used a two-stage dynamic data envelopment analysis (DEA) model to evaluate and measure the efficiency of the green transformation of Chinese thermal power enterprises. In addition, this study also uses the logarithmic mean Divisia index (LMDI) method to analyze the driving effects of green transformation. The results indicate that in terms of overall efficiency, there is a significant difference in the overall performance of these 30 thermal power enterprises, with a large difference in average efficiency values. Efficiency values are related to enterprise size. In terms of stage efficiency, the average efficiency value of thermal power enterprises in the profit stage was significantly higher than that in the transformation stage, and the profitability of Chinese thermal power enterprises was better. In terms of sub-indicator efficiency, the efficiency of each indicator shows a “U”-shaped trend, and there is a certain correlation between the operating costs and revenue of thermal power enterprises, the market value of green transformation, and related indicators. In addition, the most important factor affecting the efficiency of green transformation is the sewage cost they face, whereas their operational capabilities have the least impact on their green transformation. In this regard, thermal power enterprises should increase their investment in the research and development of key technologies for thermal power transformation and continuously optimize their energy structure. The government will increase financial support for thermal power green transformation enterprises and correspondingly increase emission costs. Full article

Intelligent robots are often used to explore various areas instead of humans. However, when the driving joint is damaged, the actuated robot degenerates to an underactuated robot, and the traditional control method is not suitable for the underactuated robot. In this work, a two-stage control approach for a planar prismatic–rotational (PR) underactuated robot is introduced. Firstly, we establish the dynamic model and describe the underactuated constraint between an underactuated rotational joint and active prismatic joint. Secondly, the trajectory with multiple parameters is planned to ensure that the two joints reach the target position. Based on underactuated constraints and the evaluation function, the differential evolution algorithm (DEA) is used to optimize these parameters. After that, in stage 1, we design the controller to move the active prismatic joint to the desired position. Meanwhile, the underactuated rotational joint is rotating freely. In stage 2, we design the controller for the active prismatic joint to track the planned trajectory. By means of this strategy, both joints reach their target locations simultaneously. The final simulation result demonstrates that this strategy is effective. Full article

Poverty eradication is a crucial element of SDG 1. Whether the financial resources invested by the Government provide a critical impetus for deeply impoverished rural areas needs to be studied by quantitative analysis. Therefore, this study presents a theoretical analytical framework for agricultural production–government poverty reduction. It divides the poverty reduction process into two stages, agricultural production and poverty reduction, from the perspective of sustainable agricultural development. The comprehensive measurement and spatio-temporal evolution analysis of China’s agricultural production and poverty reduction efficiency are conducted using a novel dynamic two-stage DEA model, which incorporates non-expected factors. The study found that (1) China’s agricultural production and poverty reduction efficiency exhibit overall poor performance, characterized by two poles of differentiation. (2) The agricultural production efficiency score is higher in the northern region than in the southern region, while the poverty reduction efficiency score is higher in the eastern region compared to the western region. (3) The coupling and coordination between China’s production efficiency and poverty reduction efficiency are inadequate. Full article

Data Envelopment Analysis (DEA) is one of the fastest growing approaches to solving management problems for the multi-criteria evaluation of the efficiency of homogeneous production systems. The general trend in recent years has been the development of network DEA (NDEA) models, which can consider the complicated structure of Decision Making Units (DMUs) and, therefore, can be more informative from the point of view of management science than traditional DEA models. The aim of this study is the systematization and clarification of general trends in the development of NDEA applications over the past 6 years (2017–2022). This study uses the methodology of a systematic literature review, which includes the analysis of the dynamics of the development of the topic, the selection of the main clusters of publications according to formal (citation, branches of knowledge, individual researchers) and informal (topics) criteria, and the analysis of their content. This review reveals that, most frequently, network structures are used for bank models, supply chain models, models of eco-efficiency of complex production systems, models of innovation processes, and models of universities or their departments and healthcare systems. Two-stage models, where the outputs of the first stage are the inputs of the second (intermediate outputs), are the most commonly used. However, in recent years, there has been a noticeable tendency to complicate DEA models and introduce hierarchical structures into them. Full article

The sustainable development of the Yellow River Basin (YRB) is regarded as a national strategy for China. Previous literature has focused on the green efficiency measurement of YRB, ignoring its evolution process and influential mechanism. This paper tries to disclose the spatial-temporal evolution of green efficiency and its influential mechanism of the YRB region by proposing a novel integrated DEA-Tobit model to fill the gap. Based on the development path of the YRB region, the multi-period two-stage DEA model is adopted to evaluate the green development efficiency (GDE) from provincial and urban dimensions. In addition, the panel Tobit model is developed to investigate the influential factors of the GDE for the YRB region. The GDE in the YRB region shows an unbalanced state where the downstream is best, followed by the middle and upstream. The unbalanced development also exists within the province. Both Henan and Shandong Province achieved the optimal value, while cities in these two provinces show lower green efficiency. The results also show that economic development, technological innovation and foreign capital utilization obviously affect the GDE of the YRB region positively, while industrial structure, urbanization levels and environmental regulation have negative effects. Full article

The concept of strong sustainability suggests that natural capital is irreplaceable and emphasizes that human natural consumption cannot exceed the carrying capacity of the ecological environment. In the realistic context of tightening resource constraints and ecological degradation, how to explore the optimal economic and well-being output under certain ecological constraints has become an important topic in sustainability research. Ecological well-being performance (EWP) can comprehensively reflect the efficiency of natural resources and ecological inputs into the well-being level and has become an important tool for sustainable development research. Based on strong sustainability, this paper constructs an EWP evaluation index system. It decomposes EWP into two stages: ecological economy and economic well-being, which opens the “black box” of the ecological well-being conversion process. PCA-DEA, the network super-efficiency Epsilon-based measure (Network SEBM) model, and Geodetector are used to dynamically measure the EWP in the Three Gorges Reservoir Area (TGRA) from 2010 to 2020 and analyze its spatial and temporal characteristics and influencing factors. The results show that (1) temporally, the EWP in the TGRA shows an increasing trend from 2010 to 2020, but the overall level is low. Spatially, it shows a high pattern in the east and low in the west, and spatial differences are gradually decreasing; (2) ecological economic efficiency is significantly lower than economic well-being efficiency, and ecological economic efficiency is the main reason limiting the improvement in EWP in the TGRA. The ecological well-being situation of the TGRA is not optimistic; (3) there is an overall problem of excessive ecological input and insufficient per-capita GDP and well-being output in the TGRA, and decisions should be made according to local conditions; (4) the level of economic development has an EWP level that plays a dominant role and also has a greater relationship with the policy system, socioeconomic conditions, and natural environment. Full article

As human society is entering an era of scarce natural resources, realizing the welfare level of human society is a fundamental requirement to improve sustainable development, while being restrained by the ecological environment. In this paper, we divided ecological welfare performance (EWP) into an ecological economic system and an economic welfare system from the perspective of ecological welfare, and predicted the EWP in the Yellow River Basin Urban Agglomerations (YRBUAs) using the US-NSBM model in two stages. We further explored the dynamic change trend and spatial convergence characteristics in the YRBUAs using the Dagum Gini coefficient, the kernel density estimation method, and the spatial convergence models. The results indicate that there are great spatial variations in EWP in the YRBUAs, where the spatial variation in the downstream is higher than that in the upstream, and the spatial distribution pattern in large- and medium-sized cities is higher than that in small cities. The DEA efficiency could not be realized overall throughout the study period, but it shows an improving trend. At the same time, absolute β convergence and conditional β convergence were observed in the YRBUAs, both overall and between the UAs. This paper provides a basis for analyzing the spatial pattern of EWP and for promoting the coordinated development of urban agglomerations in the YRBUAs, thus serving as a reference for the sustainable development of ecologically sensitive regions in countries across the world. Full article

Low temperature during cold acclimation (CA) leads to the accumulation of detrimental reactive oxygen species (ROS) in plant tissues, which are scavenged by antioxidants, such as ascorbate and glutathione. However, there is a lack of studies examining the dynamics of antioxidants throughout CA, deacclimation (DEA), and reacclimation (REA) in winter wheat. Six winter wheat genotypes were selected to assess the effect of CA, DEA, and REA on the concentrations of ascorbate and glutathione in leaf and crown tissues under two CA temperature treatments. Higher levels of total, reduced, and oxidised ascorbate were determined in leaves, whereas crowns accumulated higher concentrations of nicotinamide adenine dinucleotide (NAD⁺) after CA, DEA, and REA. Constant low temperature (CLT) during CA led to higher contents of ascorbate and glutathione in both tissues at all stages of acclimation, in comparison with prolonged higher low temperature (PHLT). The concentrations of antioxidants increased after CA, tended to decrease after DEA, and returned to CA levels after REA. Significant positive correlations between freezing tolerance (FT) and antioxidants were only determined under the CA at CLT treatment, thus, affirming the negative effect of PHLT during CA on the FT of winter wheat. Full article

Green innovation, which combines “innovation-driven” and “green development,” is one of the most powerful ways to overcome resource and environmental constraints and enhance manufacturing industry sustainability. Based on the innovation value chain perspective, the green innovation process of manufacturing industry is decomposed into two stages: green scientific and technological R&D and achievement transformation. Then, using the three-stage DEA and Malmquist index model to measure the green innovation performance of China’s manufacturing industry, and compare its regional heterogeneity from the dual perspectives of static efficiency and dynamic productivity. In addition, this paper further discusses the improvement path of green innovation performance of China’s manufacturing industry. The findings are as follows: (1) The green innovation efficiency of manufacturing industry in China is at a comparatively low degree and has great potential for improvement. Moreover, it shows apparent regional heterogeneity: The green innovation efficiency in the eastern region is higher than that in the western region, and both are higher than that in the center region, confirming the phenomenon of “central collapse”. (2) The green innovation productivity of China’s manufacturing industry shows a “W-type” dynamic evolution tendency, with green technological progress as the key driving factor, while the green technical efficiency does not clearly exhibit a “catch-up effect”. Additionally, it shows significant regional heterogeneity: green innovation productivity in the western region is higher than that in the central and eastern regions, indicating a potential “backwardness advantage”. (3) The eastern region of China is located in combination IV, which indicates that it has a high rate of green innovation efficiency but a low rate of green innovation productivity; the central region is located in combination III, which indicates that it has a low rate of both green innovation efficiency and productivity; and the western region is located in combination II, which indicates that it has a low rate of green innovation efficiency but a high rate of green innovation productivity. Last but not least, this paper puts forward three kinds of paths for the improvement of the green innovation performance of China’s manufacturing industry: unilateral breakthrough, step-by-step and stimulating jumping type. Full article

The Paris Agreement marks global response to climate change after 2020 and China has proposed the dual carbon goals, carbon peaking and carbon neutrality, in response. This paper analyses the contribution to dual carbon goals by analyzing the impact of environmental regulations (ERs) on green technology innovation (GTI) in China. First, considering variances in energy consumption structure across provinces and industries, industrial CO₂ emission is calculated and set as an undesirable output of industrial GTI. Then, industrial green technology innovation efficiencies (GTIE) of 29 provinces in China between 2005–2017 are calculated using a non-oriented two-stage network SBM-DEA model assuming variable returns to scale. Last, dynamic evolution and regional differences of industrial GTIE during green technology R&D, green technology commercialization, and overall GTI stages are respectively observed, and the influences from different types of ERs, command-based (CER), market-based (MER), and voluntary (VER), on industrial GTIE are analyzed. We identify China is overall experiencing relatively low but gradually increasing industrial GTIE and Industrial GTIE present gradient changes across provinces with increasingly prominent regional difference. It is found that influences of types of ERs on industrial GTIE present dynamic effect, threshold effect, lag effect and regional differences. Full article

This study employs the two-stage dynamic data envelopment analysis model to examine sustainability and corporate performances of the 29 largest multinational enterprises in the transport manufacturing industry from 2015 to 2019. The results show that, on average, sustainability has a positive relation to corporate performance and sustainability performance is better than corporate performance for all multinational enterprises (MNEs). In addition, we also found that corporate social responsibility (CSR) acts as a moderator in the relationship between sustainability and corporate performances. Overall, the American group leads the others in sustainability performance, followed by Asia and Europe. On the other hand, Europe has the highest score in terms of corporate performance. In terms of size, the results show that it is positively related to corporate performance. In contrast, leverage has a negative relationship with corporate performance. The findings of this research can assist inefficient MNEs in identifying areas for advancement by learning from their peers and provide perspective and insights into the plans for MNEs’ strategies and decisions in the future. Full article

The development of innovation at a regional level in a transition economy is characterised by complex multidirectional processes of generating and commercialising innovation, indicating the need for systematic research and rethinking of the existing methods of managing such territorial entities to stimulate innovation. For the successful introduction and implementation of innovative solutions, the deployment of appropriate amounts of intellectual, material and financial resources as well as their concentration in space and time is important. This article aims to develop a model for assessing the effectiveness of regional innovation systems (RISs) during the shift from the transition economy to the market economy. The authors developed a two-stage data envelopment analysis (DEA) model connected with patent activities and the output of innovative goods and services. The model’s application made it possible to build maps describing the rating of regions concerning the performance indicator and to identify the availability of unutilised resources. For example, we identified efficient and inefficient regions in terms of producing innovative products, which is especially important for developing additional measures for developing the institutional environment of regions with considerable resources but very low utilisation efficiency. The data obtained will allow for more effective management of the structural elements of RISs as well as the detection of changes in the dynamics of key development indicators by identifying the size of efficiency reserves and the causes of their occurrence at the individual subject level. Full article