Sustainable Green Growth in Developing Economies

The Belt and Road Initiative (BRI) initiated by Chinese government could be regarded as a systematic framework for promoting economic cooperation and development among the countries along the Belt and Road and China. This paper attempts to analyze economic and environmental performance in 61 developing countries along Belt and Road. An additive total factor productivity growth measure allows aggregating contributions of individual countries along the BRI to construct a reasonable measure. Both desirable and undesirable outputs are considered. The growth in the total factor productivity is decomposed with respect to the economic and environmental contributions. The annual average growth rate of green productivity is 3.1% and the disparity of economic and environmental performance could be observed among countries. Some countries show robust economic growths while environmental performance slows down green growth. This indicates that developing economies should pay attention to environmental impacts and promote sustainable development by sharing emission reduction technologies.

Measuring paper industry's ecological performance in an imprecise and vague scenario: a fuzzy DEA-based analytical framework

PurposeProductivity improvement is key to sustainability performance improvements of organizations. In a real-world scenario, the nature of inputs and outputs is likely to be imprecise and vague, leading to complexity in comparing firms' efficiency measurements. Implementation of fuzzy-logic based measurement systems is a method for dealing with such cases. This paper presents a fuzzy weight objective function to solve Data Envelopment Analysis (DEA) CCR model for measuring paper mills' performance in India for 15 years.Design/methodology/approachAn integrated methodology is proposed to solve DEA models having fuzzy weights. The fuzzy DEA methodology is an extended version of the DEA approach that researchers have used for performance measurement purposes in imprecise and vague scenarios. The ecological performance of the paper industry is evaluated, considering some desirable and undesirable outputs. The effect of non-discretionary input on the performance of a paper mill is also analyzed.FindingsAnalysis suggests that the productivity of the paper industry is improving consistently throughout the period. The comparative evaluation of methods suggests that a diverse cluster of DMUs and integration of DEA with the fuzzy logic increases the diversity in the efficiency score while DEA-DE imitates the results of CCR DEA.Originality/valueProposed a fuzzy DEA-based analytical framework for measuring the paper industry's ecological performance in an imprecise and vague scenario. The model is tested on data from the paper industry in a developing country context and comparative performance analysis using DEA, fuzzy DEA and DE algorithm is done.

Initial Allocation Model of CO2 Emission Allowances Based on the Equity-Efficiency Tradeoff

Reasonably and fairly allocating carbon intensity reduction targets among Chinese provinces is a key problem in effectively controlling and reducing CO2 emissions. This study establishes the ZSG-DDF model combining the Zero-Sum Gains DEA and the Directional Distance Function to study the CO2 emission allowance allocations from the perspective of maximum efficiency. This model can discriminate desirable and undesirable outputs and solve the problem of total CO2 emission amount control. Then, we add the equity principle to the constraint conditions, namely, the proportion of carbon emission allowance approaching the proportion of GDP. Finally, we establish a CO2 emission allocation scheme based on the equity-efficiency tradeoff while considering the relationship between economic development and carbon emissions as well as achieving maximum efficiency. We use this new model to allocate CO2 emission allowance during the Chinese 13th Five-Year Plan, and compare it with the other two allocation schemes, including National allocations during the 13th Five-Year Plan, allocation scheme from the perspective of efficiency maximization. The results have a certain significance for government departments to formulate the allocation scheme of CO2 emission allowance.

Benchmarking Sustainable Manufacturing: A DEA-Based Method and Application

In past decades, many manufacturing enterprises have followed the business model of productivity maximization, in which achieving maximum profit using limited resources is the business goal. Although this industrial strategy may make profit, it can be detrimental to the long-term social welfare. Industrial regulations require that enterprise should be responsible for the natural environment and the health of their employees while achieving their business goals. This presents a complex problem involving the trade-off between ecology and economy so that an efficient strategic decision support method is needed. Since the value-added process of a manufacturing company encompasses both desirable and undesirable outputs, in this study we use a data envelopment analysis-based model to measure performance sustainability. In it, energy, water, and manpower are considered as input resources, meanwhile CO2 emissions, wasted water, chemical compounds, and laborers’ injuries are considered as bad outputs. The proposed approach is applied to a global chemical manufacturing company to benchmark the sustainability of its production sites located in Asia. Based on the benchmarking results, the theoretical and practical implications are discussed.

Ecological Evaluation of Industrial Parks Using a Comprehensive DEA and Inverted-DEA Model

Data envelopment analysis (DEA) and inverted data envelopment analysis (inverted-DEA) are used so that the desirable and undesirable outputs of decision-making units (DMUs) exist simultaneously. We developed a new approach based on the concept of utilizing both DEA and inverted-DEA to enhance the discrimination power of DMUs with undesirable outputs. DMUs are ranked by the Z-score method and classified based on the efficiency scores of DEA and inverted-DEA. Then, the characteristics of the DMUs are analyzed based on the classification result. This paper performs an efficiency evaluation of 21 industrial parks in China in 2017 using this new approach. The overall evaluation results indicate that the proposed new approach increases the discrimination ability in this empirical study.

Assessing the Efficiency of Sustainable Cities Using an Empirical Approach

Sustainability is a multidisciplinary discipline posing a difficult problem as a result of its integrated assessment. From a broad perspective, it considers the impact of human activities (using different resources) and natural conditions on local environments. Urban development has been identified as one of the most important reasons for environmental and social degradation. To address the complexity of sustainability and its impact, policymakers need to be equipped with the right toolkit to foresee the integrated effect of projects and plans on urban sustainability more effectively in their policy design. In this paper, we propose a tool to assess the sustainable performance of urban areas through a common framework of indicators which provides an integrated measurement based on the relative efficiency of key input variables on desirable and undesirable outputs. Using Data Envelopment Analysis (DEA), we propose a procedure for determining the relative efficiency of relevant urban areas, proposing this method as a candidate for integrated sustainability measurement. The selection of variables is based on dimensions which can be addressed from a political perspective for achieving more desirable outputs, or reducing the undesirable ones, controlling for key resources as much as possible. Our analysis takes a comprehensive scope including an environmental and socioeconomic perspective. This will be useful to identify weaknesses and strengths to improve the integrated performance of cities. Our array of indicators, based on standardized key performance indicators (KPIs) will enable policymakers to gather an insightful impact of their proposals in urban sustainability carrying out a global sustainability impact assessment through DEA. The main goal is to gather the urban experience of transforming cities into smarter cities and putting technological progress at the service of their societies.

A Novel Stochastic Two-Stage DEA Model for Evaluating Industrial Production and Waste Gas Treatment Systems

In recent decades, the high-speed development in China has caused serious air pollution in China. The present paper proposes a stochastic data envelopment analysis (DEA) model based on a general two-stage structure with comprehensively considering the randomness in both desirable and undesirable outputs to calculate the environmental efficiency of the industry system. The new proposed model is more applicable to practical system, and is applied to evaluate the performance of production and waste gas treatment in the industrial sector for China’s regions along the “One Belt and One Road” in 2015. The results show that about half of the regions along “One Belt and One Road” in China are inefficient, where the performance on waste gas treatment is significantly worse than that of industrial production. Further, the managers should take different strategies for efficiency improvement in different areas because of the obvious differences in efficiency scores, in which the regions in the southeast area should pay more attention to improving waste gas treatment efficiency while that in the northwest area need to focus on industrial production efficiency.

Evaluation of Sustainable Urban Development under Environmental Constraints: A Case Study of Jiangsu Province, China

Sustainable development is a long-term solution for urban development and a guideline for urban development. Only by better coordination around the population, resources, and environment can the city achieve sustained and steady development. In order to evaluate the efficiency of sustainable urban development under environmental constraints, this paper takes 13 prefecture-level cities in Jiangsu Province as an example. To address the infeasibility problem in the Malmquist-Luenberger (M-L) index, a modified M-L index analysis method based on the new directional distance function (DDF) is adopted. Combined with the consideration of desirable and undesirable outputs, a linear programming model for sustainable urban development evaluation is constructed to provide a scientific decision-making basis for sustainable development of the city. The results show that the growth of sustainable urban development efficiency is not only related to desirable outputs but also affected by undesirable outputs. Technical change is the main driver of most sustainable urban development efficiency growth. However, efficiency changes also affect the sustainable development potential of cities to a certain extent. Through the modified M-L index analysis, we analyze the characteristics of different regions of Jiangsu Province, the changes in efficiency and the impact of technological innovation on sustainable urban development, and give policy recommendations to promote sustainable urban development.

Performance evaluation of portfolios with fuzzy returns

The existing literature on DEA (Data Envelopment Analysis) for evaluating fuzzy portfolios usually takes risk as an input and return as an output. This assumption is actually not congruent with the real investment process, where the input is the initial wealth and the output is the corresponding terminal wealth. As for the risk and return, which are essentially two indicators derived from the terminal wealth, both should be regarded as outputs. In addition, few studies have employed the diversification model (nonlinear DEA) to estimate the fuzzy portfolio efficiency (PE), despite the fact that there are many studies available within the framework of classical probability theory. Further, the relationship between DEA and diversification models needs to be defined. In this paper, we take the initial wealth as an input, while the return and risk of terminal wealth are taken as desirable and undesirable outputs, respectively. We construct different evaluation models under the fuzzy portfolio framework. The relationships among the evaluation model based on a real frontier, the diversification model and the DEA model are investigated. We show the convergence of the diversification and DEA models under the fuzzy theory framework. Some simulations as well as empirical analysis are presented to further verify the effectiveness of the proposed models. Finally, we check the robustness of the evaluation results by using the bootstrap re-sampling approach.

Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach

Transport is recognized as a major energy consumer and environment pollutant. Recently scholars have paid considerable attention to the evaluation of transport energy and environmental efficiency (EEE). In this paper, the non-radial Data Envelopment Analysis (DEA) model was employed to evaluate EEE on a macro level—i.e., of European road, rail and air sectors. The evaluation was conducted under the joint production framework, which considers energy and non-energy inputs, and desirable and undesirable outputs for the last ten years period. To rank decision-making units and check the aptness of this non-radial DEA model in transport EEE evaluation, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been proposed. An empirical study has been conducted for as many European countries as possible, depending on availability of data. Based on the non-radial DEA model, it could be said that the level of EEE is improving for the road sector, while many evaluated countries have low EEE for the rail transport sector. Additionally, results have indicated that the TOPSIS method is more suitable than the non-radial DEA model in transport EEE evaluation and for identification of best practices.