Performance measurement for incineration plants using multi-activity network data envelopment analysis: The case of Taiwan

Innovation Efficiency, Productive Performance and Undesirable Outputs across European Regions: Are there any missing links?

We introduce an analytical methodological framework that links knowledge generation efficiency with economic efficiency and the corresponding environmental impact for 199 European Regions during 2000-2018, using a benchmarking approach and especially a chain network DEA technique. A clear trade-off between knowledge generation efficiency and productive performance emerges. European regions which exhibit high innovation efficiency enjoy higher overall performance compared to their counterparts. In a second stage, we investigate the convergence patterns of the examined regions with respect to all the three facets of the estimated efficiency where the coexistence of multi-type convergence clubs is revealed.

Efficiency evaluation of sewage treatment plants in Delhi, India, using tolerance-based data envelope analysis

Correct and effective performance evaluation of wastewater treatment plants is a tough task because of the complex biological, physico-chemical, and biochemical processes and associated variables affecting their performance. Conventionally, the efficiency of sewage treatment plants (STPs) are obtained using some index relating pollutant removal efficiency with energy used or costs. These indicators consider only one variable at a time. This leads to incorrect assessment of efficiency, which in turn could adversely affect decision-making of the regulatory authorities. The data envelope analysis (DEA) method utilizes a Linear programming technique which can handle multiple input/output variables without requiring the cost function. This makes it an appropriate tool for assessing the relative efficiency of treatment plants. The present study assess the efficiency of 30 STPs in Delhi, India, using the tolerance-based DEA model utilizing the variable return of scale (VRS). The uncertainty was incorporated into the model using the tolerance measure. The model is solved using the "Add on" option in spreadsheet toolbox of excel solver. Results reveal that out of the 30 plants considered for the study, 6 are performing well (20%). Further, it was observed that a slight change in the input data leads to instability of the efficiency results. Lastly, the ranking is used to determine the treatment plant with best efficiency under all scenarios for the larger period of the year. Such studies will help in chalking out the best management practices that could be adopted by other regulatory authorities.

A Nash bargaining game data envelopment analysis model for measuring efficiency of dynamic multi-period network structures

Purpose

A Nash bargaining game data envelopment analysis (NBG-DEA) model is proposed to measure the efficiency of dynamic multi-period network structures. This paper aims to propose NBG-DEA model to measure the performance of decision-making units with complicated network structures.

Design/methodology/approach

As the proposed NBG-DEA model is a non-linear mathematical programming, finding its global optimum solution is hard. Therefore, meta-heuristic algorithms are used to solve non-linear optimization problems. Fortunately, the NBG-DEA model optimizes the well-formed problem, so that it can be solved by different non-linear methods including meta-heuristic algorithms. Hence, a meta-heuristic algorithm, called particle swarm optimization (PSO) is proposed to solve the NBG-DEA model in this paper. The case study is Industrial Management Institute (IMI), which is a leading organization in providing consulting management, publication and educational services in Iran. The sub-processes of IMI are considered as players where their pay-off is defined as the efficiency of sub-processes. The network structure of IMI is studied during multiple periods.

Findings

The proposed NBG-DEA model is applied to measure the efficiency scores in the IMI case study. The solution found by the PSO algorithm, which is implemented in MATLAB software, is compared with that generated by a classic non-linear method called gradient descent implemented in LINGO software.

Originality/value

The experiments proved that suitable and feasible solutions could be found by solving the NBG-DEA model and shows that PSO algorithm solves this model in reasonable central process unit time.

Testing the Bioeconomic Options of Transitioning to Solid Recovered Fuel: A Case Study of a Thermal Power Plant in Slovakia

This paper deals with the state and perspectives of bioenergy development in the context of exploiting the potential of available natural resources. We analyse the economic benefits of transitioning to alternative biofuel within the research task in cooperation with the Vojany black coal power plant. Within the applied methodology, a non-parametric data envelopment analysis method was used to confirm the most economically efficient types of fuels used in the combustion process. The assumption of fuel efficiency was confirmed by testing fuel combustion combinations directly in the power plant. The transition to 100% combustion of solid recovered fuel creates the potential for sustainable production of the analysed power plant and compliance with the current emission values of basic pollutants and new stricter limits, which will be binding in the EU from August 2021. The proposed solutions were analysed by Monte Carlo simulation. An estimate of the economic results achieved by the power plant was simulated, assuming a complete transition to solid recovered fuel. The results of the study support the feasibility of creating a circular waste management market, with the Vojany black coal power plant as the largest user of solid recovered fuel in Slovakia and abroad.

Analysis of the dynamic electricity revenue inefficiencies of Taiwan's municipal solid waste incineration plants using data envelopment analysis

Due to insufficient land and energy resources, municipal solid waste incineration plants are used in many countries as a means of addressing the growing volumes of generated municipal solid waste and to recover energy resources. Taiwan's government allows the private sector to offer municipal solid waste treatment services and electricity to the public. Revenue from the sale of electricity is an important source of income for municipal solid waste incineration plants. Although several studies have examined the technical efficiency of municipal solid waste incineration plants, previous studies have not measured or deconstructed the dynamic electricity revenue inefficiency of incineration plants. For our purposes, this paper presents a data envelopment analysis model that measures and deconstructs the electricity revenue inefficiency while taking into account the slacks and dynamic factors in measuring technical inefficiency levels within the context of assessing MSW incineration plants in Taiwan. This study applied the proposed model to analyze the electricity revenue inefficiency of the municipal solid waste incineration plants in Taiwan over the period of 2013-2018. In this study, we found that the main source of electricity revenue inefficiency is the technical waste from electricity production. Our empirical analysis reveals that the electricity technical, revenue and allocative efficiencies of public plants are lower than those of private plants.

Evaluating provincial eco-efficiency in China: an improved network data envelopment analysis model with undesirable output

In this study, an improved matrix-type network data envelopment analysis (NDEA) model with undesirable output was developed to evaluate the eco-efficiency of China's 30 provinces. The proposed model considered three linked but independent subsystems of the economy-society-environment cyclic system. Additionally, to allocate the weights of the NDEA model among the three subsystems (environment, economy, and society) of the eco-environment, a new relative reduction of the input-based method was proposed. The results show that, from 2003 to 2016, the average eco-efficiency of China's 30 provinces was low, ranging in [0.59, 0.73]. Qinghai and Hainan ranked first and second, respectively, in average eco-efficiencies, while both Shaanxi and Xinjiang had the lowest average eco-efficiencies. Affected by the low social subsystem efficiency, the eco-efficiency of 18 provinces decreased, but the range of the decrease was smaller than that of the increase in 11 other provinces in which the eco-efficiency improved. The average efficiency of the environmental subsystem is the highest among the three subsystems benefiting from reducing the emissions of "three industrial wastes," while economic subsystem owns the lowest average efficiency due to the input redundancy of total fixed assets and energy consumption. Compared with variables' projection, for most provinces, the undesirable output of the three industrial wastes should be reduced by more than 88.0%, while the positive outputs of atmospheric quality and per capita years of education should be increased by at least 61.0%.

Evaluating the eco-efficiency of China's industrial sectors: A two-stage network data envelopment analysis

Because the industrial process always results in pollutant emissions, pollution treatment has become necessary for the sustainable development of industry. This paper aims to evaluate the eco-efficiency of China's industrial sectors between 2007 and 2015 by using the directional distance function (DDF) of network data envelopment analysis (DEA), which contains a two-stage structure that divides industrial processes into three linked subprocesses, i.e., the production, wastewater and waste gas treatment processes. The results show that (1) from 2007 to 2015, the eco-efficiency and all process efficiencies of China's industries achieved considerable improvement. This finding indicates that China's industries have already achieved a win-win situation in the development of environmental protection and economic growth over the past few years. (2) During the sampling period, the highest performance was observed during the waste gas treatment process, followed by the wastewater treatment and production processes. During the same period, the performance of wastewater treatment exhibited the fastest growth, followed by the performance of production and waste gas treatment. (3) The eco-efficiencies of China's industrial subsectors exhibited significant industrial differences: the eco-efficiency of the mining industry was the lowest due to a decline in its performance during the waste gas treatment process, while due to the excellent performance during the production wastewater treatment process, the eco-efficiencies of the electricity, gas production and supply industries were the highest.

European Countries: Does common legislation guarantee better hazardous waste performance for European Union member states?

The study of efficiency in hazardous waste management has been proved to be a driving factor for sustainable development (SD). This study focuses on a performance assessment of European countries, most of them European Union (EU) member states and candidate countries that share a common legislative framework through European regulations, in order to provide a general understanding of hazardous waste performance. In this paper, we use Data Envelopment Analysis (DEA) to examine the efficiency of 32 countries in Europe by using novel input/output environmental parameters to study the efficiency of the different waste management operations from an environmental point of view. This analysis contrasts the efficiency in the management of total waste versus hazardous waste and studies three operations with hazardous wastes: incineration and incineration with energy recovery, disposal and recovery. Results show that there are differences in the achievement of efficiency, not only among countries, but also among the different waste management operations analysed.

A two-stage DEA approach for environmental efficiency measurement

The slacks-based measure (SBM) model based on the constant returns to scale has achieved some good results in addressing the undesirable outputs, such as waste water and water gas, in measuring environmental efficiency. However, the traditional SBM model cannot deal with the scenario in which desirable outputs are constant. Based on the axiomatic theory of productivity, this paper carries out a systematic research on the SBM model considering undesirable outputs, and further expands the SBM model from the perspective of network analysis. The new model can not only perform efficiency evaluation considering undesirable outputs, but also calculate desirable and undesirable outputs separately. The latter advantage successfully solves the "dependence" problem of outputs, that is, we can not increase the desirable outputs without producing any undesirable outputs. The following illustration shows that the efficiency values obtained by two-stage approach are smaller than those obtained by the traditional SBM model. Our approach provides a more profound analysis on how to improve environmental efficiency of the decision making units.