Search Results (6)

Research on the urban circular economy (CE) in developing regions often overlooks cross-sectoral interactions, social dimensions, data uncertainty, circularity metrics, and nonlinear trends, underscoring the need for integrated adaptive assessment. To address these gaps, we propose an integrated framework combining a nonlinear autoregressive with exogenous inputs (NARX) neural network and a fuzzy dynamic network slack-based measure (DNSBM) model to evaluate and improve urban CE performance across economic, environmental, and social dimensions in 107 cities of the Yangtze River Economic Belt (YREB) from 2011 to 2023. The results show a steady increase in aggregate efficiency and robustness across α-cut levels, alongside marked regional and stage heterogeneity. Downstream cities perform better because of more effective resource coordination, whereas upstream cities show greater potential for improvement. The main constraint is the social health dimension, reflecting persistent underinvestment in public health. ANN-based slack adjustment enhances efficiency estimation accuracy. Most cities need to reduce redundant inputs, curb pollution emissions, and increase health investment. This study contributes a closed-loop, multidimensional framework that captures temporal dynamics, data uncertainty, and cross-sectoral feedback and supports performance optimization and region-specific sustainability pathways. 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

This study evaluates the impact of industrial energy efficiency on agricultural development in the 31 member countries of the Organization for Economic Cooperation and Development (OECD) from 2015 to 2019. Using dynamic network slack-based measures (DN-SBM) and dynamic network total factor productivity (DN-TFP) indicators, dynamic cross-period information is used to assess the changes in efficiency and productivity of the industrial and agricultural sectors. The empirical results show that the industrial sector of the OECD is more efficient than the agricultural sector, and while some countries have low efficiency, productivity tends to improve. The study has three contributions: 1. Using the concept of the water–energy–food (WEF) nexus as a framework and combining its elements with variables to evaluate the efficiency performance of OECD countries; 2. using a dynamic two-stage DN-SBM model to objectively assess the overall efficiency value and provide improvement suggestions for different stages; 3. a comprehensive analysis of efficiency and productivity; the results can serve as a reference for OECD countries when formulating policies Full article

Industry is an important force in China’s economic development; however, with the transformation and upgrading of the industrial structure, a large number of resources have flowed to the tertiary industry, and the funding problem has become one of the main disadvantages restricting China’s industrial enterprises’ sustainable development. This paper aims to point out the problems and improvement directions of financing efficiency of China’s industrial listed enterprises. Based on the two-stage dynamic network SBM (DNSBM) model, this paper evaluates the financing efficiency of 450 of China’s industrial listed enterprises from 2011 to 2017. The results show that: (1) the overall financing efficiency of China’s industrial listed enterprises is low, the funds are not used effectively, and there is great room for improvement; (2) the overall financing efficiency of state-owned enterprises (SOEs) is lower than that of non-state-owned enterprises (NSOEs), the average fund raising efficiency of SOEs is greater than the fund using efficiency, but the opposite is true for NSOEs; (3) the overall financing efficiency of the main-board-listed enterprises is the lowest, and that of the growth enterprise market (GEM) is the highest, the most obvious gap is in the second stage of fund using, but this gap is gradually narrowing; and (4) the overall financing efficiency of China’s industrial enterprises has obvious regional characteristics, the fund raising efficiency value in each region is not much different, while the fund using is significantly different. To improve financing efficiency, enterprises must improve their financing channels, choose the best financing method, maintain a reasonable debt-financing ratio, improve management level and profitability, increase enterprise value, enhance the debt-paying ability, and attract more capital at a low cost. In addition, the government should also provide corresponding financing support policies for different types of enterprises. Full article

In recent years, China’s electronics and communication equipment manufacturing (ECEM) industry has overgrown, and the government should assess the innovation performance of the industry for its sustainable development. However, most previous studies on the innovation efficiency of the ECEM industry have ignored the link and carry-over variables. This paper uses the number of patent applications as a link variable to consider the stage of innovation activities. It divides the innovation activities of the electronics industry into two stages: technology development and results in transformation. To consider the dynamics of innovation activities, this paper uses capital stock as a period carry-over variable and evaluates the change of innovation efficiency over time. In this paper, the DNSBM model is used to measure the innovation efficiency of the ECEM industry in 26 Chinese provinces from 2013–2019. This model includes both stage link variables and period carry-over variables, thus allowing for overall efficiency and stage efficiency and period efficiency. The results show that the overall innovation efficiency values in the Chinese ECEM industry are low, there are considerable differences between the two-stage efficiency values in the east, central and western regions, and the overall efficiency values show a slow upward trend. Full article

Environmental pollution and the associated societal health issues have attracted recent research attention. While most research has focused on the effect of air pollution on human health and local economies, few articles have discussed the environment, health, and economic development in in an integrated analysis. This paper used a Dynamic Network SBM Model to evaluate production and health efficiencies in Chinese cities and found that the production efficiency scores were slightly higher than the health efficiency scores, with the two-stage efficiency scores in most cities having significant fluctuations. Labor, fixed assets, energy, GDP, and lung disease and mortality reduction efficiencies in the first stage were generally high; however, the medical input efficiencies in the second stage were low, indicating that there was there significant room for improvement in many cities. Full article