A novel artificial intelligent approach: comparison of machine learning tools and algorithms based on optimization DEA Malmquist productivity index for eco-efficiency evaluation

An integrated approach of discrete event simulation and a non-radial super efficiency data envelopment analysis for performance evaluation of an emergency department

DEA environmental assessment of coal fired power plants: Methodological comparison between radial and non-radial models

The concept of congestion, which is mainly applied in economics, refers to a situation where inputs are overinvested. Many studies have focused on congestion measurement by means of data envelopment analysis (DEA). However, most of the previous investigations only considered the framework of desirable outputs. In fact, firms in the real world unavoidably generate undesirable outputs (such as pollutants or wastes) along with desirable outputs. Therefore, a new scheme is required for measuring congestion in the simultaneous presence of both desirable and undesirable outputs. This paper develops a nonradial efficiency measure for including undesirable outputs into the environmental performance. Based on the proposed model, a new definition and a new approach are presented to deal with congestion in the simultaneous presence of desirable and undesirable outputs. Then, this paper uses the presented method to study the pollutants (waste gas emission and waste discharge) of 31 administrative regions of China. The finding indicates that 7 industries pay attention to the reduction of their pollutants accompanying improvement of their commercial targets. Consequently, they do not show congestion in any input.

Undesirable factors in integer-valued DEA: Evaluating the operational efficiencies of city bus systems considering safety records

Data Envelopment Analysis (DEA) model usually does not consider the interaction between the decision making units (DMU). The interaction can be represented in the form of two consecutive stages in which the outputs from the precedent stage will be the inputs for the latter stage. The two consecutive stage DEA model can be represented as Non-separable DEA (NS-DEA) which integrates both desirable and undesirable output. The undesirable output unlike desirable output, indicates a higher efficiency if the output is lower or not productive. The different orientation between desirable and undesirable output may affect the efficiency score especially if it was formed in two consecutive stages. Thus, this research attempts to address four different types of dependence relationship which can occur in the formation of two consecutive stage DEA models and to investigate the impact towards the overall efficiency of the DMUs. The finding shows that the determination of positive or negative correlation between the two stages which combines both desirable and undesirable output, are more likely to be influenced by the orientation of the first precedent stage.

This study employs four data envelopment analysis (DEA) models to evaluate the performance efficiency of 21 OECD countries and assess whether the undesirable outputs are over-produced relative to desirable outputs. In evaluating the performance of OECD countries via super-efficiency models, this study focuses on two aspects. First, employing the concept of the Sharpe ratio, we propose another method to deal with undesirable outputs (the unemployment rate, inflation, and air pollution) in DEA. This approach can reveal the relative importance of desirable outputs and undesirable outputs, detect whether undesirable outputs are over-produced, and obtain more accurate efficiency scores. Second, we examine whether knowledge capital can improve a country’s efficiency scores. Our empirical results support the above arguments. In addition, research and development (R&D) expenditures, the proxy variable for knowledge capital, can indeed improve countries’ efficiency scores, implying that the endogenous growth theory is supported in OECD countries. Evidently, whether the undesirable outputs are included in the DEA models and are properly treated is crucial in the evaluation of efficiency values.

The conventional data envelopment analysis (DEA) models make an assumption of non-negativity in the inputs and outputs data of the decision making units (DMUs) under analysis. In this paper, we present a non-radial measure of efficiency of DMUs by establishing a multi-period additive DEA model taking into consideration both desirable and undesirable inputs and outputs with positive and non-positive values. The proposed efficiency model possesses the requisite features of translation invariance and unit independence, obligatory when dealing with negative values in the data set. Furthermore, this paper contributes with the proposal of a multi-period additive super-efficiency DEA model to discriminate the performance of efficient decision making units. Finally, we present an efficiency evaluation 37 countries worldwide on economic parameters to demonstrate the applicability and efficacy of the proposed models.

Environmental efficiency of the Indian cement industry: An interstate analysis

DEA approach for unified efficiency measurement: Assessment of Japanese fossil fuel power generation

Environmental efficiency and economic growth of China: A Ray slack-based model analysis

Returns to Scale and Damages to Scale with Strong Complementary Slackness Conditions in DEA Assessment: Japanese Corporate Effort on Environment Protection

The purpose of this paper is to develop an output oriented methodology with constant return to scale (CRS) assumption for calculating productivity changes by using double frontier (optimistic and pessimistic) data envelopment analysis (DEA) simultaneously for two-stage processes. Measuring the productivity changes with Malmquist productivity index (MPI) via double frontiers DEA with single process has been defined by Wang and Lan (2011) as a geometrically average of optimistic and pessimistic point of views to generate an aggregate MPI. In order to develop and modify the previous studies, in this paper we have proposed a method to modify Wang and Lan (2011) aggregate MPI and also extend it to two-stage process which we refer to the double frontiers two-stage DEA (DFTDEA). It should be mentioned that the proposed model of this paper measures the MPI's distance functions for two individual stages and whole process for both DEA different points of view by the traditional DEA models and supposed relational models in output oriented CCR models, respectively. Therefore, the identified double frontiers two-stage DEA (DFTDEA-based MPI) is more realistic and comprehensive than the conventional optimistic or pessimistic DEA-based MPI individually. Subsequently, the proposed approach is examined to five Iranian commercial banks over the five-year period, 2009-2013.

This study proposes a new use of data envelopment analysis (DEA) for assessing economic success and environmental protection, so measuring the level of sustainability. The new approach is referred to as “DEA environmental assessment,” and it can measure the performance of various entities that use inputs to produce not only desirable outputs but also undesirable outputs. DEA models are generally classified into radial or non-radial category. This study proposes a new “intermediate” approach between them. As an illustrative application, this study is interested in empirical assessment on energy usage and social sustainability of 21 Asian nations from 2008 to 2014. The energy usage, usually classified into primal (e.g., oil and coal) and secondary (i.e., electricity) categories, is essential in developing the economy, but the development simultaneously produces various pollutions (e.g., carbon emission). They have been developing their economic prosperities in a short period, but simultaneously suffering from such pollutions. All Asian nations are classified into four or five groups based upon their unified efficiency measures under natural disposability, where economic performance is the first priority and environmental performance is the second, along with managerial disposability with the opposite priority to the natural disposability. An implication found in this study is that among Asian nations, Japan and New Zealand belong to the first tier in terms of developing their social sustainability. Japan’s economy started to turn down after 2012 and faced a pitfall in recent years. Meanwhile, New Zealand has developed its economy by exporting agriculture products and is surrounded by natural beauty. Thus, the two nations are ranked as the top tier under the four types of unified efficiency measures. Beside these expected findings, this study has found that large nations such as China and India have not badly performed if we consider the size of their economies. This is a surprising result because they are large carbon emitters in the world and thereby they have been often criticized by international communities. Their problem is that the living standard of people is low because of the size of population. The empirical findings are useful in developing the energy and industrial policies of Asian nations.

Multi-valued measures in DEA in the presence of undesirable outputs

One of the major concerns in healthcare management is the optimal allocation of staffing and resources. The global crisis created by the COVID-19 Pandemic has created extreme strains both on the staffing and the resources available to the healthcare systems. It has geometrically added to the number of patients seeking health services. In addition, the Pandemic has dramatically increased the rate of mortality in the hospitals in an unprecedented way. Therefore, in this research, in order not to sacrifice the quality of the services provided, we have used Data Envelopment Analysis (DEA) model to determine the efficiency of the emergency departments in the hospitals and the possible improvements that could be made to them. As traditional DEA models do not seek to reduce the undesirable outputs and increase the undesirable inputs, in addition to determining the efficiency of decision making units (DMU) despite some undesirable input components, the effect of these units on performance is investigated. To this end, considering the problem assumptions, first, a set of proper production possibilities is defined. Finally, a new method is introduced to determine the system’s performance in the presence of some undesirable input components. The impact of undesirable components on determining efficiency is specified, and a real example is provided consisting of emergency rooms in 30 hospitals, in which five desirable inputs and four desirable outputs along with one undesirable input are considered. The example is solved using the presented model, and the efficiency scores are determined.