Ali Emrouznejad

University of Surrey · Surrey Business School

Several countries have focused on achieving optimal economic growth in the past decades, which has caused diverse environmental concerns among policymakers and managers. The present study aims to introduce new metric using mathematical modeling to examine strategies to promote environmental performance in OECD countries. Thus, we propose a target-o...

Management-led productivity improvements are crucial for achieving sustainable development, and the Malmquist productivity index is known to be useful in relevant contexts. This study aims to extend such index by using non-parametric mathematical modeling of production processes. Specifically, and in the spirit of the existing index, we introduce t...

Accepted by: Aris Syntetos Management-led productivity improvements are crucial for achieving sustainable development, and the Malmquist productivity index is known to be useful in relevant contexts. This study aims to extend such index by using non-parametric mathematical modelling of production processes. Specifically, and in the spirit of the ex...

Data Envelopment Analysis models have evolved over the years, offering formulations that correspond to instances beyond strictly measuring performance. In this chapter, extensions of DEA models will be presented, demonstrating recent developments in DEA formulations. The models that will be analytically described and modelled with GAMS in this chap...

Aside from the classical DEA models for assessing efficiency, special models based on either the DEA technique or similar functioning have been proposed over the years. In this chapter, we will focus on the Benefit-of-the-Doubt model and the Multi-objective Linear Programming in DEA.

The field of production economics has rapidly changed over the last decades. This rapid change is partly due to the Data Envelopment Analysis (DEA) technique, which assesses the comparative performance of a set of units based on inputs and outputs, measuring the efficiency of the transformation procedure. The inputs are consumed in order to produce...

In addition to radial models, non-radial models have also been developed and used in the DEA literature, albeit as latecomers. Historically, radial models have been represented by the CCR (Charnes et al., 1978) and BCC (Banker et al., 1984) models, and non-radial models by the slacks-based measure (SBM) (Tone, 2001a). In this chapter, non-radial mo...

One of the most widely used software for mathematical programming is the General Algebraic Modeling System (GAMS). The software is user-friendly and facilitates the process of going from a mathematical statement of the problem to its solution. The main use of GAMS is for optimisation. One of the features that makes the GAMS software easy to use and...

In most of the analyses employed where DEA is applied, the need to assess productivity for a given period of time is often necessary. Since classical DEA formulations ignore the temporal dimension of data, new DEA formulations and relevant indices have been proposed. Among them, the most important is the Malmquist Productivity Index or MPI. This in...

When input prices are available, cost efficiency, also known as input overall efficiency, or input allocative efficiency (as proposed by Färe et al., 1985) can be estimated. Alternatively, when output prices are available, revenue efficiency, also known as output overall efficiency, or output allocative efficiency (as proposed by Färe et al., 1985)...

Data Envelopment Analysis (DEA) is a widely used mathematical programming approach for assessing the efficiency of decision-making units (DMUs) in various sectors. Inverse DEA is a post-DEA sensitivity analysis approach developed initially for solving resource allocation. The main objective of Inverse DEA is to determine the optimal quantity of inp...

The objective of this special issue is to provide a comprehensive overview of inverse DEA, covering the current state of knowledge, its significance, and the need for further research contributions.

We highlight the state-of-the-art in the eco-efficiency measurement using Data Envelopment Analysis, including Malmquist-Luenberger productivity index. We also consider productivity change over time, provide directions for future studies in the field, and gather the most recent policy suggestions for governments, organisations and sectors for reduc...

Traditionally most cross-selling models in retail banking use demographics information and interactions with marketing as input to statistical models or machine learning algorithms to predict whether a customer is willing to purchase a given financial product or not. We overcome with such limitation by building several models that also use several...

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of th...

As smart meters are becoming widespread around the world, it is a good idea to complement the traditional theory-driven research by machine learning techniques to fully untap the potential of the data collected. Previous studies examining the electricity consumption behavior using traditional research methods, before the smart-meter era, mostly wor...

About this book This book provides a comprehensive and practical introduction to DEA. It explains how this non-parametric technique is used to measure performance and extract efficiency from homogeneous entities within a production procedure. It situates DEA within a growing field of productivity analysis and performance measurement, for which nume...

Data analytics projects can be like throwing darts in the dark. Problem‐centric thinking is vital, argue Vincent Charles, Ali Emrouznejad, Tatiana Gherman, and James Cochran

By introducing the concept of sustainable development, managers and policymakers in many industries have been encouraged to consider environmental and social issues in addition to economic objectives in their planning. Following this concept, sustainable supply chain management has become the main concern of many studies. Among all the strategies t...

The analytic hierarchy process (AHP) introduced by Thomas Saaty (1980) is a modern tool for dealing with complex decision-making and may help the decision maker to set priorities to make the best decision. Due to its simplicity, ease of use, and great flexibility, the AHP has been studied extensively and used in mearly all applications related to m...

In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (D...

Global warming, climate change, and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution, greenhouse effect, poor working conditions, child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The pu...

Determining energy productivity change during a time interval is an important issue in many production lines. Data Envelopment Analysis (DEA) approach is a well-known technique utilized to measure productivity change and widely used by researchers to analyze the performance of decision making units. In this regard, the modified Enhanced Russell Mea...

Data Envelopment Analysis (DEA), provides an empirical estimation of the production frontier, based on an observed sample of decision making units (DMUs). Except for the single input-single output case, the asymptotic distribution of the DEA estimator can only be approximated through bootstrapping approaches. Therefore, bootstrapping techniques hav...

This paper surveys the increasing use of statistical approaches in non-parametric efficiency studies. Data Envelopment Analysis (DEA) and Free Disposable Hull (FDH) are recognized as standard non-parametric methods developed in the field of operations research. Kneip et al. (Econom Theory, 14:783–793, 1998) and Park et al. (Econom Theory, 16:855–87...

Data and process storytelling are important skills that data scientists can acquire and exhibit. And although the audience is different for each story, it is sensible to treat the two sets of skills as intimately intertwined rather than separately applied.

Special Issue of JMSE: New advances in DEA and its applications under big data Guest editors: Prof. Dr. Guoliang Yang & Prof. Dr. Ali Emrouznejad

Mutual fund (MF) is one of the applicable and popular tools in investment market. The aim of this paper is to propose an approach for performance evaluation of mutual fund by considering internal structure and financial data uncertainty. To reach this goal, the robust network data envelopment analysis (RNDEA) is presented for extended two-stage str...

Conventional DEA performs like a “black box” and provides no information about sub-processes. In some cases, such as banks, providing services made up of interactive and interdependent processes. Also, in real-world applications, inputs could be shared among these sub-processes. Moreover, due to the characteristics of some variables, such as number...

Data Envelopment Analysis (DEA) methods have been widely used in many fields, including operations research, optimization, operations management, industrial engineering, accounting, management, and economics. This chapter starts with an introduction to common DEA-based models in the envelopment and multiplier forms to illustrate the importance of t...

Because port operations have rapidly been extending, air pollution resulted from ports has been increased and become a persistent concern for environmentalist and policy makers. The objective of this paper is to measure the environmental efficiency of ports in Korea. The main characteristic of the environmental efficiency assessment problem is that...

Data Envelopment Analysis (DEA) is a mathematical programming model that calculates the relative efficiency of homogenous Decision Making Units (DMUs). The conventional DEA models used to calculate the efficiency require the exact amount of inputs and outputs; in real business situations, however, it is often impossible to determine the exact numer...

Uncertainty is an important issue to consider when evaluating entities in both public and private sectors. On the other hand, many operations have more than one stage process when some inputs are fed to the system to produce a number of intermediate measures. The intermediate measures are then transformed into final products in the subsequent stage...

Sustainable development has gained significant attention in the literature due to the increased global awareness of environmental sustainability during the last decade. Sustainable development has three aspects, including economic, social, and environmental. The challenge of sustainable development is to establish a balance between these three aspe...

This paper evaluates the stock performance of Islamic banks relative to their conventional counterparts during the initial phase of the COVID-19 crisis (from December 31, 2019, to March 31, 2020). Using 426 banks from 48 countries, we find that stock returns of Islamic banks were about 10–13% higher than those of conventional banks after controllin...

Background: Paying particular attention to sustainable food consumption in low-income households is essential for increasing human health. Due to the growing population globally, this concept will likely become more serious soon. Methods: Following the importance of optimizing food consumption for sustainability, in this study, a novel methodolo...

The airline industry is one of the major industries having a significant role in the economic development of a country, on both domestic and international sides. Hence, it is important to have the airlines performing efficiently, as much as possible. To this end, it seems necessary to continuously evaluate the performance of the airlines to find an...

Data envelopment analysis (DEA) model has been applied for evaluating bank branches and recognizing efficient and inefficient branches can help bank managers to provide appropriate strategies to improve the inefficient branches' performance. Conventional DEA models are based on the ‘black box’ approach. However, the process of providing services in...

Manufacturing is a major source of energy consumption and, therefore, a significant contributor to emissions and greenhouse gases. This paper is concerned with evaluating different scheduling policies in a job shop system where energy-efficient scheduling is incorporated with multiple other scheduling criteria. In the production systems being inves...

Composite indices are used by national and international organisations, as well as governments and corporations, to track various performance aspects of a country's economy and its people, evaluate progress, and engage constructively in policy dialogue; and they have long proven useful as communication tools and inputs into decision-making and poli...

Data envelopment analysis (DEA) model has been widely applied for estimating efficiency scores of decision making units (DMUs) and is especially used in many applications in transportation. In this paper, a novel common weight credibility DEA (CWCDEA) model is proposed to evaluate DMUs considering uncertain inputs and outputs. To develop a credibil...

Big Data is a major source of change in today’s world. It is without doubt a source of immense economic and social value with the potential to impact individuals, organisations and society alike in ways that are yet to be fully explored. On the other hand, Blockchain is poised to play the role of foundation technology to store Big Data, ensuring th...

The Industry 4.0 (I4.0) revolution has led to rapid digital transformation, automation of manufacturing processes and efficient decision-making in business operations. Despite the potential benefits of I4.0 technologies in operations management reported in the extant literature, there has been a paucity of empirical research examining the intention...

The field of service operations management has a plethora of research opportunities to capitalise on, which are nowadays heightened by the presence of big data. In this research, we review and analyse the current state-of-the-art of the literature on big data for service operations management. To this aim, we use the Scopus database and the VOSview...

Studies have shown that the sensible operation of big data may yield powerful insights that can improve the organisations’ strategic decision-making process and contribute to achieving an enhanced competitive advantage. In this manuscript, we explore the promise of big data in redefining strategy in service operations management (SOM) by means of i...

Due to the urban expansion and population increasing, bus network design is an important problem in the public transportation. Functional aspect of bus networks such as the fuel consumption and depreciation of buses and also spatial aspects of bus networks such as station and terminal locations or access rate to the buses are not proper conditions...

As risks of all sorts, from economic and financial crises to terrorism acts and pandemics, keep on characterising and affecting all aspects of life globally, at the individual and societal level, national and international organisations, as well as governments, need to be constantly adapting and collaborating through international diplomacy to purs...

Auditing energy usage of farming operations is a key step towards agricultural sustainability. The current systems of tomato production use a considerable quantity of energy. As a result, improving energy efficiency is a crucial stage in decreasing energy consumption in tomato production. Data envelopment analysis (DEA) model is an established meth...

Data envelopment analysis (DEA) is one of the widely used methods to measure the efficiency scores of decision making units (DMUs). Conventional DEA is unable to consider both uncertainty in data and decision makers’ (DMs) judgments in the evaluations. This study, to address the shortcomings of the conventional DEA, proposes a new best worst method...

Performance evaluation enables decision makers (DMs) to have a better view about the weaknesses and strengths of leading units to improve efficiencies as a crucial goal. Data envelopment analysis (DEA) is the most popular technique to measure performance efficiency of decision making units (DMUs). However, conventional DEA is unable to consider unc...

Allocating a fixed cost among a set of peer decision-making units (DMUs) is one of the most important applications of data envelopment analysis. However, almost all existing studies have addressed the fixed cost allocation (FCA) problem within a traditional framework while ignoring the existence of undesirable outputs. Undesirable outputs are neith...

In response to the limitation of classical Data Envelopment Analysis (DEA) models, the super efficiency DEA models, including Andersen and Petersen (Manag Sci 39(10): 1261–1264, 1993)’s model (hereafter called AP model) and Li et al. (Eur J Oper Res 255(3): 884–892, 2016)’s cooperative-game-based model (hereafter called L–L model), have been propos...

One of the most important effects that railways have on the environment is noise pollution, notably in Europe. The purpose of this study is to evaluate the environmental efficiency of railways in 22 European countries, considering two factors; a country’s response in retrofitting their wagon fleet with more silent braking technology and the number...

The problem of assessment of Decision Making Units (DMUs) by using Data Envelopment Analysis (DEA) may not be straightforward due to the data uncertainty. Several studies have been developed to incorporate uncertainty into input/output values in the DEA literature. On the other hand, while traditional DEA models focus more on crisp data, there exis...

The significant positive and negatives effects of transportation systems (TSs) on the sustainability of cities and human life draw much attention from both researchers and managers. Constructing bus rapid transit (BRT) networks, or adding new lines to the existing ones, is one of the cheapest and easiest solutions to improve the performance of the...

With the applications of blockchain technology in various fields, the research on blockchain has attracted much attention. Different from the researches focusing on specific applications of blockchain technology in a certain field, this study devotes to capturing the attitudes of investors regarding different risk criteria in blockchain technology...

Economic crisis and uncertainty in global status quo affect stock markets around the world. This fact imposes improvement in the development of volatility models. However, the comparison among volatility models cannot be made based on a single‐error measure as a model can perform better in one‐error measure and worst in another. In this paper, we p...

In this paper, we reformulate the conventional DEA models as an imprecise DEA problem and propose a novel method for evaluating the DMUs when the inputs and outputs are fuzzy and/or ordinal or vary in intervals. For this purpose, we convert all data into interval data. In order to convert each fuzzy number into interval data, we use the nearest wei...

The emissions trading system allows organizations to transact emission permits to fit their production practice. This paper develops a new nonparametric methodology for performance evaluation of organizations (or decision-making units, DMUs) considering carbon emission permit trading. Explicit production axioms are discussed, and a new production t...

Although there is a growing number of research articles investigating the performance in the banking industry, research on Chinese banking efficiency is rather focused on discussing rankings to the detriment of unveiling its productive structure in light of banking competition. This issue is of utmost importance considering the relevant transformat...

Data Envelopment Analysis (DEA) has been widely applied in measuring the efficiency of Decision-Making Units (DMUs). The conventional DEA has three major drawbacks: a) it does not consider Decision Makers’ (DMs) preferences in the evaluation process, b) DMUs in this model are flexible in weighting the criteria to reach the maximum possible efficien...

This paper proposes a new slacks-based measure network data envelopment analysis (SBM-NDEA) model with undesirable outputs to evaluate the performance of production processes that have complex structure containing both series and parallel processes. We demonstrate the proposed approach by evaluating Chinese commercial banks during 2012-2016. The op...

This paper presents a novel approach for performance appraisal and ranking of decision-making units (DMUs) with two-stage network structure in the presence of imprecise and vague data. In order to achieve this goal, two-stage data envelopment analysis (DEA) model, adjustable possibilistic programming (APP), and chance-constrained programming (CCP)...

Smart meters that allow information to flow between users and utility service providers are expected to foster intelligent energy consumption. Previous studies focusing on demand-side management have been predominantly restricted to factors that utilities can manage and manipulate, but have ignored factors specific to residential characteristics. T...

The continuous development of energy management systems, coupled with a growing population, and increasing energy consumption, highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavioral change. Using a data mining segmentation technique, 2,505 Northern Ireland house...

Classical data envelopment analysis models have been applied to extract efficiency when time series data are used. However, these models do not always yield realistic results, especially when the purpose of the study is to identify the peers of the decision making unit (DMU) under investigation. This is due to the fact that apart from the spatial d...

Purpose The aim of this research study is to develop a queue assessment model to evaluate the inflow of walk-in outpatients in a busy public hospital of an emerging economy, in the absence of appointment systems, and construct a dynamic framework dedicated towards the practical implementation of the proposed model, for continuous monitoring of the...

Data Envelopment Analysis (DEA) is the most popular mathematical approach to assess efficiency of decision-making units (DMUs). In complex organizations, DMUs face a heterogeneous condition regarding environmental factors which affect their efficiencies. When there are a large number of objects, non-homogeneity of DMUs significantly influences thei...

The continuous development of sophisticated energy management systems, coupled with a growing population, and increasing energy consumption highlights the necessity to develop a deep understanding of household energy consumption behavior and interventions that facilitate behavior change. Using the data mining segmentation technique, 2,505 Northern...

Data Envelopment Analysis (DEA) is a linear programming methodology for measuring the efficiency of Decision Making Units (DMUs) to improve organizational performance in the private and public sectors. However, if a new DMU needs to be known its efficiency score, the DEA analysis would have to be re-conducted, especially nowadays, datasets from man...

Data envelopment analysis (DEA) is a well-known non-parametric technique primarily used to estimate radial efficiency under a set of mild assumptions regarding the production possibility set and the production function. The technical efficiency measure can be complemented with a consistent radial metrics for cost, revenue and profit efficiency in D...

This paper investigates the problem of efficiency measurement for parallel systems with two components based on Stackelberg game theory, while some inputs/outputs are fuzzy numbers. Conventional DEA models treat DMUs as “Black Boxes”. While in this paper, we propose a new parallel fuzzy DEA model to calculate the efficiency scores for each DMU’s wh...