# Alireza AmirteimooriIslamic Azad University of Rasht · Department of Applied Mathematics

Alireza Amirteimoori

Full Professor

## About

145

Publications

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1,561

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Citations since 2017

## Publications

Publications (145)

Purpose
Data envelopment analysis (DEA) is a significant method for measuring the relative efficiency of decision making units (DMUs) that use the least inputs, produce the most desirable outputs and emit the least undesirable outputs in order to maximize their profits. In DEA, detecting an optimal scale size (OSS) is also vital and could be more a...

In the nonparametric data envelopment analysis literature, scale elasticity is evaluated in two alternative ways: using either the technical efficiency model or the cost efficiency model. This evaluation becomes problematic in several situations, for example (a) when input proportions change in the long run, (b) when inputs are heterogeneous, and (...

One of the most complicated decision making problems for managers in supply chain is the evaluation of supply chain performance which can be done in different ways. Though several studies have been developed on supply chain performance evaluation based on balanced scorecard (BSC), a few studies focused on relationships among four perspectives of BS...

Purpose. The purpose of this study is to sensitivity analysis analyze the returns to scale in two-stage network based on DEA models. The main focus of the firms has always been to obtain the maximum output with the least available resources, which points to the improvement of the firm’s performance and the importance of returns to scale and technic...

In this research, inverse data envelopment analysis (IDEA) approaches are proposed to measure inputs changes for output perturbations made while the convexity assumption is relaxed. Actually, inverse free disposal hull (IFDH) techniques under constant returns to scale (CRS) assumption are introduced from two perspectives, optimistic and pessimistic...

The problem of determining an optimal benchmark to inefficient decision-making units (DMUs) is an important issue in the field of performance analysis. Previous methods for determining the projection points of inefficient DMUs have only focused on one objective and other features have been ignored. This paper attempts to determine the best projecti...

Paying heed to organizational performance evaluation in recent years has led to the development of frameworks and methodologies such as the Balanced Scorecard, EFQM Model, performance-based costing, etc. that have offered numerous advantages. However, the subject of multiple stakeholders and data, multiple and innumerable headquarters in the public...

Conventional data envelopment analysis (DEA) models are often extended for constant or variable returns to scale assumptions based on the under-investigated technology. It is assumed that all inputs and outputs are real-valued data. However, in many practical applications, proportionality or convexity axioms require to be modified. This study attem...

In production theory, industrial units do business in such a way that they use minimum amount of resources to produce maximum amount of products. So, inefficient units decrease their inputs level and increase their outputs level to meet the efficient frontier. By changing inputs and outputs, achieving an optimal scale size (OSS) in industrial units...

Managerial ability plays a vital role in the performance of business enterprises; however, such efforts are not directly observable. This study estimates managerial ability within the insurance sector of the economy based on two data sets from two different Asian countries. We estimate insurer-wise efficiency using Data Envelopment Analysis (DEA) a...

In classic data envelopment analysis models, two-stage network structures are studied in cases in which the input/output data set are deterministic. In many real applications, however, we face uncertainty. This paper proposes a two-stage network DEA model when the input/output data are stochastic. A stochastic two-stage network DEA model is formula...

The majority of data envelopment analysis (DEA) research studies evaluate the sustainability of processes with real-valued factors and individual role, while the investigation of sustainability of networks with bounded, discrete, and joint measures is necessary in many applications. Therefore, the purpose of this study is the examination of sustain...

Probability theory is a branch of mathematical science that deals with the mathematical analysis of random events. Probability is commonly used to describe the mind’s attitude to statements that we are not sure of. Statements usually take the form of “Will a particular event occur?” and the attitude of our minds will be of the form “How confident a...

Most real-life production processes are multi-stage in nature. Characterization of such processes via concepts such as technical efficiency is considered important to firm managers for the stage-specific analysis of their business decisions in improving their performance. Therefore, it is imperative to estimate the efficiency of a firm not only for...

In traditional DEA models, the technologies are developed using the premise that inputs and outputs are precisely measured and are, therefore, deterministic. However, in practical situations, the general production processes are often stochastic. The stochastic production relationship in a DEA setting may arise in different situations, for example,...

To analyze the performance of firms (decision-making units, DMUs) in the literature, several economic concepts such as economies of scale (returns to scale, RTS), economies of scope, marginal rates of technical substitutions, etc., have been used. Banker et al. (2004) studied RTS in different DEA models. In this chapter, however, we concentrate on...

Following the seminal work of Farrell (1957), Charnes et al. (1978) introduced DEA as a deterministic and nonparametric efficiency evaluation tool. DEA is a linear programming-based technique that has been widely accepted as a competing methodology to evaluate the relative efficiency of entities or decision-making units, DMUs (Charles et al., 2016,...

Benchmarking is an efficiency performance measurement procedure that allows firms to compare their performance to the top competitors. In this chapter, benchmarking (as an efficiency performance measurement tool using a specific indicator) and key performance indicators are first briefly introduced. Then, we introduce efficiency and productivity an...

This book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs. It focuses on the application of theories and interpretations of the mathematical programs, which are combined wit...

In the current study, the general fuzzy data envelopment analysis (GFDEA) approach is presented for stock evaluation under data ambiguity and linguistic variables. It should be explained that to propose GFDEA method, data envelopment analysis (DEA), possibilistic programming approach (PPA), general fuzzy measure (GFM), and chance-constrained progra...

Sustainability performance analysis is a critical and significant aspect for organizations due to growing challenges in competitive industries. Finding the most productive scale size (MPSS) is also necessary for reorganizing. Conventional data envelopment analysis (DEA) models analyze the performance from the optimistic viewpoint. However, evaluati...

Purpose
As returns to scale (RTS) describes the long run connection of the changes of outputs relative to increases in the inputs, the purpose of this study is to answer the following questions: If the proportionate changes exist in the inputs, what is the rate of changes in outputs with respect to the inputs’ variations in the two-stage networks o...

This paper proposes an approach to maintaining unit efficiency (cost efficiency) under any fluctuation in input costs. It can accommodate situations where the level of influence over costs ranges from minimal to considerable. For this purpose, a two-step procedure is applied: First, finding the convex cone. It is formed by the intersection of conve...

Traditional efficiency studies on network data envelopment analysis (DEA) consider decision-making units as black boxes that use a set of crisp inputs to produce a set of crisp outputs and that ignore intermediate measures and reverse flows. In real applications, however, we are faced with network systems with reverse flows in an uncertain environm...

Conventional data envelopment analysis (DEA) models cannot deal with negative and uncertain values. Accordingly, the main objective of current study is to present a novel robust data envelopment analysis (RDEA) approach that is capable to be used in the presence of negative values and uncertain data. Notably, to propose RDEA approach, range directi...

In some processes and systems, undesirable inputs and outputs may be presented along with desirable measures. Undesirable factors play a significant role to calculate the accurate efficiency of Decision Making Units (DMUs). Furthermore, analyzing the impact of a throughput on another throughput in economics and production management gives useful in...

As a useful performance evaluation and decision-making tool, data envelopment analysis (DEA) has been proven to be an excellent data-oriented efficiency analysis method when there are multiple inputs and outputs. However, when working with large datasets, DEA requires more time to solve and calculate the optimal values for each decision-making unit...

Returns to scale and scale elasticity are two important issues in the field of economics and operations research. Recently, estimating returns to scale and scale elasticity using tools such as data envelopment analysis (DEA) has attracted considerable attention among researchers. The existing approaches to calculate scale elasticity in DEA context,...

In real applications of data envelopment analysis (DEA), there are cases in which undesirable outputs are produced along with desirable outputs in such a way that the total sum of the produced undesirable outputs over the production units must be fixed and constant. In this case, a trade-off between the decision making units (DMUs) is needed to bal...

The selection-based problem is a type of decision-making issue which involves opting for a single option among a set of available alternatives. In order to address the selection-based problem in data envelopment analysis (DEA), various integrated mixed binary linear programming (MBLP) models have been developed. Recently, an MBLP model has been pro...

Data envelopment analysis (DEA) technique is commonly utilized for efficiency assessment in a variety of fields for both theoretical and applicational purposes. In classic cost efficiency measurement models, the input and output data and input prices should be known for each decision-making unit (DMU). However, in real-life markets the input prices...

The concept of returns to scale and scale elasticity has been frequently studied in the framework of data envelopment analysis. Returns to scale is a qualitative characterization to the frontier points of the technology set and its estimation using tools such as data envelopment analysis (DEA) has attracted considerable attention among researchers....

Data envelopment analysis (DEA) is a model for measuring the efficiency of decision-making units (DMUs). The majority of DEA models suffer from drawbacks, in particular, changes in the weights of inputs and outputs. Consequently, the efficiency of DMUs is measured with different weights and so it is important to establish how to evaluate all DMUs u...

The problem of constructing a common equilibrium efﬁcient frontier with fixed-sum inputs or outputs is studied in this paper. To do this, all decision making units are classified into different classes based on their size score and in each class, a common equilibrium efficient frontier is constructed. In the developed procedure, we consider undesir...

Purpose
The purpose of this paper is introducing an alternative model to measure the relative efficiency of observations with undesirable products. Describing the reference set and benchmarking.
Design/methodology/approach
In this paper, an alternative definition of weak disposability assumption is introduced to handle undesirable outputs. Actuall...

Sustainability is an essential ingredient for long‐term success of firms, and its assessment has a significant impact on decision making and sustainability management. In the current paper, a data envelopment analysis‐based approach is proposed to assess the sustainability of systems over several periods when undesirable outputs are present in the...

One of the most serious problems in electricity supply chain management is excessive energy consumption in oil and gas fields and power plant sections and the control wasted energy or power losses in transmission and distribution lines. The resource allocation and utilization to environmental preservation of pollution gas emissions play a fundament...

Purpose
Merger and acquisitions (M&A) is a process of restructuring two or more companies into one, a process that occurs frequently in many companies. Previous studies on M&A mainly paid attention to the potential gains from a merger, while ignored the problem of how to select the partners to merge. This paper aims to select the best partner from...

Purpose
The paper analyzes the relative performance of provincial gas distribution companies with different types of inputs and outputs. A data envelopment analysis (DEA)-based model is developed to construct an equilibrium efficient frontier in the presence of multi-type input/output variables.
Design/methodology/approach
A DEA-based model is dev...

While the conventional DEA based production plans aim to minimize all the inputs consumption and maximize all the outputs production, there are many real world production systems may also generate undesirable by-products. One methodological difficulty associated with the previous DEA-based production planning models is how to incorporate undesirabl...

Regular network data envelopment analysis (DEA) models deal with evaluating the performance of a set of decision-making units with a two-stage construction in the context of a deterministic data set. In the real world, however, observations may display a stochastic behavior. To the best of our knowledge, despite the existing research done with diff...

Data envelopment analysis (DEA) is a mathematical programming approach with widespread applications in productivity and efficiency analysis. Compared with traditional DEA models, two-stage DEA models show the performance of each process and make available more information for decision making. In an article by Kao and Liu, models were proposed for c...

Data envelopment analysis (DEA) is a data-oriented procedure to evaluate the relative performances of a set of homogenous decision making units (DMUs) with multiple incommensurate inputs and outputs. Performance measurement using tools such as DEA needs to construct an empirical production technology set. In this analysis, DMUs are partitioned into...

In the real world, there are processes whose structures are like a parallel-series mixed network. Network data envelopment analysis (NDEA) is one of the appropriate methods for assessing the performance of processes with these structures. In the paper, mixed processes with two parallel and series components are considered, in which the first compon...

Data envelopment analysis (DEA) is a powerful mathematical programming methodology for evaluating the relative efficiency of decision-making units (DMUs) with multiple outputs and multiple inputs. In the classic DEA, it has been implicitly assumed that all DMUs perform in a unique technology set and the traditional DEA cannot measure the relative p...

In conventional data envelopment analysis (DEA) models, data are usually considered as continuous measures while the role of measures from input and/or output aspects is known. However, there are situations in the real world that a measure can play either input or output roles, a flexible measure, while it can only take integer values (e.g., nurse...

In this study, we develop a marginal chance-constrained data envelopment analysis (DEA) model in the presence of nondiscretionary inputs and hybrid outputs for the first time. We call it a stochastic nondiscretionary DEA model (SND-DEA), and it is developed to measure and compare the relative efficiency of forest management units under different en...

Data Envelopment Analysis includes a wide range of mathematical models and is used for assessing the relative efficiency of a set of homogenous Decision Making Units (DMUs). Multiplicative DEA models achieve a set of weights for input and output variables for each DMU. Based on these weights, relative efficiency of each DMU is evaluated. Determinin...

Purpose
The purpose of this paper is to propose a modified model in multi-stage processes when there are intermediate measures between the stages and in this sense, the new efficiency scores are more accurate. Conventional data envelopment analysis (DEA) models disregard the internal structures of peer decision-making units (DMUs) in evaluating th...

Regular Network Data Envelopment Analysis (NDEA) models for calculating the efficiency of decision-making units (DMUs) with two-stage construction requires the data set to be deterministic. In the real world, however, there are many observations that have stochastic behavior. This paper proposes a two-stage network DEA model with stochastic data. T...

The conventional data envelopment analysis suggests each decision-making unit selecting its most desirable weight. Applying these weights lets the units achieve their maximum performance. But, the performance of different units is achieved with different sets of weights. So, comparison and ranking of units on a common basis seems such an impossible...

Data envelopment analysis (DEA) is a technique to evaluate the relative efficiency of a set of decision making units (DMUs) which is applicable in different systems such as engineering, ecology, and so forth. In real-world situations, there are instances in which production processes of systems must be analyzed in multiple periods while desirable a...

In conventional data envelopment analysis (DEA) models, the efficiency of decision making units (DMUs) is evaluated while data are precise and continuous. Nevertheless, there are occasions in the real world that the performance of DMUs must be calculated in the presence of vague and integer-valued measures. Therefore, the current paper proposes fuz...

Supply chain performance evaluation is an essential aspect for decision-makers in order to make better and profitable decisions and survive in the competitive environment. Furthermore, considering desirable and undesirable outputs that are usually produced in supply chain processes simultaneously is significant and effective for obtaining rational...

In performance measurement of the firms using tools such as data envelopment analysis (DEA) models, weak efficient units are almost appeared as reference points in the models. To avoid zero weights or equivalently non-zero slacks in DEA assessment, weights restrictions are used frequently. In DEA literature, two-stage procedures are developed to de...

The “Dynamic-network” version of cost efficiency measurement in Data Envelopment Analysis (DEA) is proposed in this paper. The classical DEA models ignore operations of individual processes within a system; moreover, they compute efficiency at the same time. Therefore, we suggest a relational model to estimate cost efficiency in static network stru...

The purpose of this paper is to measure the relative performance of forest management units, and to analyze the impact of the external non-discretionary (ND) factors on these units’ technical efficiency. Toward this end, data envelopment analysis (DEA) technique in variable returns to scale environment with both discretionary and ND factors has bee...

Mergers and Acquisitions (M&A) is a process whereby two or more companies merge into one company to improve their efficiency and strengthen their market positions. Previous studies about best partner selection for M&A simply consider one factor independently among several relevant factors. In this paper, DEA is applied to support decision making fo...

Recently, network data envelopment analysis (NDEA) models have been developed to evaluate the efficiency of decision making units (DMUs) with internal structures. The network structures range from a simple two-stage process to a complex system. Looking through the literature on two-stage network structures, we see that Li et al. (2012) extended a m...

In the prior literature on performance measurement of firms with fixed-sum outputs, an equilibrium-efficient frontier is constructed. This paper shows that a single equilibrium-efficient frontier needs a significant trade-off between efficient and inefficient firms, and this may be impossible in practical applications. We develop a data envelopment...

In this paper, for performance measurement of decision making units (DMUs) with interval data, it is suggested to integrate the efficiencies obtained from optimistic and pessimistic views in the form of an interval. The upper bound of efficiency interval from the optimistic view is obtained based on the most favourable position of each DMU using a...

In this paper, for performance measurement of decision making units (DMUs) with interval data, it is suggested to integrate the efficiencies obtained from optimistic and pessimistic views in the form of an interval. The upper bound of efficiency interval from the optimistic view is obtained based on the most favourable position of each DMU using a...

Various extension using data envelopment analysis (DEA) are available in the literature for performance measurement in public sector. The existence of multiple non- discretionary factors in DEA based public sector models leads to overestimation of the efficiency. This paper proposes a two-step procedure to handle non-discretionary factors in DEA mo...

This paper studies the problem of evaluating the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a large decision-making unit (DMU). The paper develops a data envelopment analysis (DEA) approach for measuring the efficiency of decision processes which can be divided into two stages. In these proc...

In multidimensional input/output space, the behavior of the firms can be analyzed by using efficient frontier or supporting surfaces of production technology. To this end, mathematicians are interested to use marginal rates of substitutions. The piecewise linear frontier of data envelopment analysis (DEA) technology is not differentiable at the ext...

In this study, the relative performance of Mazandaran Wood and Paper Company as a major supplier of paper products in Iran was measured. Network Data Envelopment Analysis (DEA) models with parallel structure were used to evaluate and measure its performance. GAMS software version 23.4 was used for data analysis. Results indicated that this company...

Data envelopment analysis (DEA) is an approach to measure the relative efficiency of a set of decision-making units (DMUs) which uses multiple inputs to produce multiple outputs. In real world situations, due to uncertainty, DEA is sometimes faced with imprecise inputs and/or outputs. Therefore, performance measurement must often be performed under...

In standard data envelopment analysis (DEA) models, inefficient decision-making units (DMUs) should change their inputs and outputs arbitrarily to meet the efficient frontier. However, in many real applications of DEA, because of some limitations in resources and DMU's ability, these variations cannot be made arbitrarily. Moreover, in some situatio...

Operational research (OR) includes a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency. OR involves the construction of mathematical models that attempt to describe the system. Because of the computational and statistical nature of most of these fields, OR also has strong ties to...

Energy, due to its increasing usage in various broad areas has been maintained as a vital factor in economic growth and development of societies. Meanwhile, natural gas is considered as one of the most important energy sources. Therefore, the efficiency and the productivity of the gas companies are crucial to be assessed. Numerous examples from ind...

Data Envelopment Analysis (DEA) has gained a wide range of applications in measuring the relative performance of a set of comparable operational units with multiple in-commensurate inputs and outputs. One research issue which has received widespread attention in the rapidly growing field of DEA deals with the problem of determining marginal rates o...

Marginal rates of substitution are important quantities for analysts and managers. The current paper focuses on estimating these quantities in the presence of nondiscretionary factors in performance measurement of a group of production units. We propose a DEA framework to verify how an efficient unit would perform in two different environments and...

Analysis of efficiency of agricultural processes leads to increased production efficiency. This study was conducted to identify and analyze factors affecting performance of greenhouse owners in Somesara, Iran. Questionnaires were used to collect data. Appropriate management in production and use of financial and accounting specialists were the high...

A new research issue in the context of production theory is production without explicit inputs. In such systems, input consumption
is not important to the decision-maker and the focus is on output production. In the presence of desirable and undesirable
outputs, modelling undesirable outputs is an important problem. This paper discusses the problem...

The non-parametric Data Envelopment Analysis (DEA) literature on network-structured performance analysis normally considers desirable intermediate measures. These measures are the outputs from the first stage and are used as inputs to the second stage. In many real situations, the intermediate measures consist of desirable and undesirable outputs....

Data envelopment analysis (DEA) has been widely used to measure the performance of the
operational units that convert multiple inputs into multiple outputs. In many real world
scenarios, there are systems that have a two-stage network process with shared inputs used
in both stages of productions. In this paper, the problem of evaluating the efficie...