Reza Farzipoor Saen

Reza Farzipoor Saen
Sultan Qaboos University | SQU · Department of Operations Management and Business Statistics

Phd
Doing research, teaching, and service at my current university.

About

248
Publications
59,212
Reads
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6,191
Citations
Citations since 2016
106 Research Items
4600 Citations
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Introduction
Reza Farzipoor Saen has published over 204 refereed papers in ABDC and ABS-ranked journals. His h indices in Google Scholar and Scopus are 47 and 38, respectively. He has 24 years of industrial and consultation experience. Reza is on the list of the top 2% of scientists in the world, ranked by Stanford University (2020; 2021; 2022). Reza is a member of the editorial board of Production and Operations Management (Financial Times listed) and Senior Editor of Journal of Business Logistics (ABS 3).
Additional affiliations
January 1997 - August 2021
Islamic Azad University Karaj Branch
Position
  • Professor (Full)
Description
  • Reza Farzipoor Saen has published over 203 refereed papers in many prestigious journals.
Education
January 1997 - September 2002

Publications

Publications (248)
Article
The main objective of this study is to propose a network data envelopment analysis (NDEA) model and a deep learning approach for forecasting the sustainability of healthcare supply chains (HSCs). Technological advances manifested in approaches such as deep learning, artificial intelligence (AI), and Blockchain are of substantial importance througho...
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Arising from the recent COP26 climate change conference, many governments have emphasised carbon neutrality targets for environmental sustainability by increasing renewable energy efficiency. This study develops a common set of weights (CSW) model for the additive model in data envelopment analysis using goal programming to analyse the energy effic...
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Supply chain operations reference (SCOR) is an appropriate method for assessing supply chains. SCOR defines supply chains' stages as follows: plan, source, make, deliver, and return. To examine these phases in terms of economic, social, and environmental aspects, the SCOR model is incorporated into the sustainable supply chain management (SSCM) con...
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The widespread outbreak of a new Coronavirus (COVID-19) strain has reminded the world of the destructive effects of pandemic and epidemic diseases. Pandemic outbreaks such as COVID-19 are considered a type of risk to supply chains (SCs) affecting SC performance. Healthcare SC performance can be assessed using advanced Management Science (MS) and Op...
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Management Decision (MD) was first published on January 1st of 1967, making it the oldest and longest-running scholarly publication focused specifically on the area of management studies. The purpose of this article is to investigate the publication trends across the Journal’s life by using a bibliometric analysis. In particular, we used the Scopus...
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This paper proposes a robust window data envelopment analysis (RWDEA) approach for assessing the dynamic performance of decision making units (DMU) in the presence of panel and uncertain data. To present the RWDEA method, generalized data envelopment analysis (GDEA) model, window analysis (WA) method, and robust optimization (RO) approach are taken...
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The transport industry is one of the main contributors to environmental pollution. Assessing the efficiency of this industry helps organizations to enhance their awareness of performance and develop managerial strategies. The need for sustainable development in the transportation industry requires efficiency analysis. Data envelopment analysis (DEA...
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In the globalization era, assessing the resilience and sustainability of suppliers is a key issue in supply chains (SCs). The literature survey shows data envelopment analysis (DEA) and analytic hierarchy process (AHP) are the two most effective approaches for evaluating suppliers. To take full advantage of these powerful approaches, we propose a n...
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Sustainability has become a critical issue in supplier selection problems. Also, risk management in supply chains has become an important issue in supply chain management (SCM). The literature shows that there is no data envelopment analysis (DEA) research to evaluate suppliers by considering both sustainability factors and risk factors. This paper...
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Appraising sustainable supply chain performance is of great importance in today’s world. Businesses, for attaining competitive advantages, call for some methods to appraise their sustainable supply chains. Applying valid performance evaluation methods along with using accurate accounting data leads to valid and reliable results. A performance appra...
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Given international regulations, countries try to improve their sustainability. The objective of this paper is to assess the sustainability of Islamic countries and to present optimal strategies to promote their sustainability. In developing Islamic countries, increasing level of production requires clean technologies to achieve or promote their le...
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Efficiency measurement is a key and strategic factor in improving an organization’s performance and increasing their competitive advantage. Nevertheless, measuring efficiency in settings with multicomponent production technologies is a major issue with the existing approaches in the literature. The main contribution of the current paper is to devel...
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The transport industry is one of the main contributors to environmental pollution. Assessing the efficiency of this industry helps organizations to enhance their awareness of performance and develop managerial strategies. The need for sustainable development in the transportation industry requires efficiency analysis. Data envelopment analysis (DEA...
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The transport industry is one of the main contributors to environmental pollution. Sustainable supply chain management (SSCM) is an essential subject in the transportation industry. Today, one of the important goals of organizations is to evaluate the sustainability of supply chain (SC) because assessing the efficiency of SCs helps organizations to...
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Sustainability assessment of organizations in terms of technical efficiency (TE) and service effectiveness (SE) for non-storage goods has always been an interesting topic for managers and scholars. This paper develops a novel non-radial network data envelopment analysis (NDEA) model to assess the performance of railways in terms of overall efficien...
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One of the common methods for classifying inventory items is ABC classification approach. In many cases, the data might be stochastic. In the current study, using stochastic data envelopment analysis model, we present a new approach to categorize inventory items given stochastic data and nature of criteria. Then, a new stochastic mixed integer prog...
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Purpose The objective of this study is to present a binary-valued data envelopment analysis (DEA) theory. The authors’ proposed approach, for the first time, combines binary-valued and integer-valued theories concurrently in the DEA context. To do so, new production possibility sets (PPSs) with some distinguished features are developed. Design/met...
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Sustainability in the supply chain means considering environmental, social, and economic practices. Conventional data envelopment analysis (DEA) models deal with desirable, discretionary, and nonnegative data. However, there might be undesirable outputs, nondiscretionary factors, and negative data. On the other hand, some criteria can be considered...
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Although Data Envelopment Analysis (DEA) assumes that inputs and outputs take non-negative real values, in some realworld cases, data are integer-valued. In some situations, rounding a fractional value to the closest integer can lead to a misleading evaluation of efficiency and in some cases may lead to an infeasible projection point. To date, vari...
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The objective of this paper is to assess the sustainability of supply chains by proposing a dynamic network data envelopment analysis (DNDEA) model in the presence of interval data, due to the fact that in many real-world applications, the condition of convexity in the production technology might be violated. To prevent this issue, a DNDEA model ba...
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Window Data Envelopment Analysis (WDEA) is a popular, effective, and applicable methods for dynamic performance assessment of peer decision making units (DMUs). WDEA is a non-parametric panel method that operates based on the principle of moving averages and establishes efficiency measures by treating each DMU in different periods as a separate DMU...
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Purpose The objective of this research is to put forward a novel closed-loop circular economy (CE) approach to forecast the sustainability of supply chains (SCs). We provide a practical and real-world CE framework to improve and fill the current knowledge gap in evaluating sustainability of SCs. Besides, we aim to propose a real-life managerial for...
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Sustainable Supply Chain Management (SSCM) involves the integrating of environmental, social and economic concerns into supply chain management activities with emphasis on the managers' efforts in the context of reducing the negative social and environmental impacts. Evaluating sustainable supply chain performance and efficiency is a significant to...
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Sustainable supply chain management (SSCM) is one of the most significant topics. Today, assessing sustainability and choosing the best supply chain is an important goal for companies. One of the techniques that can be used for evaluating the sustainability of supply chains is data envelopment analysis (DEA). This study contributes to the knowledge...
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Purpose This paper discusses how learning-by-doing (LBD) criterion can be used to evaluate the sustainability of supply chains. This paper assesses the impacts of teamwork on the LBD criterion. Besides, the effect of the internship of new labors on the LBD criterion is discussed. Design/methodology/approach The repeat of a task leads to a gradual...
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Purpose Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the...
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While interests in Industry 4.0 technologies such as cloud computing and the Internet of Things (IoT) are growing, an ongoing challenge is to properly evaluate the performance of the providers of such technologies. Methods have been developed and applied to assess the efficiency of cloud service providers (CSPs) for Industry 4.0. However, most exis...
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The objective of this study is to present a new stochastic two-stage data envelopment analysis (DEA) model for assessing the sustainability of supply chains. Unlike the conventional DEA models, which consider each decision making unit as a black box, two-stage DEA models consider the intermediate products. The main contribution of the current paper...
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This study develops a double frontier fuzzy network data envelopment analysis (FNDEA) model for assessing the sustainable supply chains. The proposed FNDEA model evaluates the optimistic and pessimistic sustainability of supply chains. The α-cut approach is used to solve the proposed models. The main contribution of this paper is to develop a novel...
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Supply chain finance (SCF) as a crucial approach plays a key role in improving commitment, trust, financial flows, and profitability in a supply chain (SC). Many industrial organisations finance their SC through two resources: internal financing (buyer) and external financing (bank). The main objective of this paper is to develop an advanced data e...
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Blood supply chains (BSCs) play a strategic and crucial role in healthcare systems especially in unexpected situations such as earthquakes and pandemic outbreaks. Nevertheless, measuring the sustainability and resilience of BSCs is a major challenge for many decision-makers in healthcare systems. To this end, this paper presents an advanced network...
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Data envelopment analysis (DEA) is a widely used technique for the performance evaluation of decision making units. Cost efficiency is one of the important factors for the financial evaluation of a system. Financial factors are important as they can be used in sustainable supply chain management. There are many cost efficiency models in DEA. In thi...
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The construction industry routinely extracts vast quantities of materials and releases deleterious pollutant emissions to the biosphere. In this study, we propose an integrated data envelopment analysis (DEA) and life cycle assessment (LCA) method to measure the performance of eco-friendly building materials in green construction management. Initia...
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Presence of input congestion is one of the key issues that results in lower efficiency and performance in Decision Making Units (DMUs). So, determination of congestion is of prime importance, and removing it improves performance of DMUs. One of the most appropriate methods for detecting congestion is Data Envelopment Analysis (DEA). Since the outpu...
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One of the most important issues in microeconomics is congestion. In general, an increase in inputs will result in an increase in outputs. However, in some cases, it does not happen. Hence, in these situations congestion occurs. The existence of the congestion reduces efficiency of Decision Making Units (DMUs), so determination of congestion is hig...
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Sustainable supplier selection is one of the most critical activities for establishing an effective sustainable supply chain and is typically a multi-criteria decision-making problem. One of the important ways for evaluating sustainable suppliers is to use data envelopment analysis (DEA) models. There are many DEA models for ranking decision making...
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This paper proposes a novel model of inverse data envelopment analysis (IDEA) based on the slack‐based measure (SBM) approach. The developed inverse SBM model can maintain relative efficiency of decision making units (DMUs) with new input and output. This model can also measure the input and output volumes when a decision maker (DM) increases effic...
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Owing to the increasing importance of sustainable supply chain management (SSCM), it has received much attention from both corporate and academic over the past decade. SSCM performance evaluation plays a crucial role in organizations success. One of the practical techniques that can be used for SSCM performance assessment is network data envelopmen...
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Data envelopment analysis (DEA) technique is widely applied for performance assessment of decision making units (DMUs). The revenue efficiency (RE) evaluation is one of the controversial subject matters that can be performed through DEA context. The amount of productions and its prices are crucial factors in the RE. The classical DEA models conside...
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Assessing the efficiency of a supply chain (SC) is of great importance for managers and policy makers. For this aim, we propose a network data envelopment analysis (NDEA) model to reflect the internal structure of networks in efficiency evaluation. For many of the real-world performance evaluation problems, data of inputs and outputs are available,...
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Purpose The purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS). Design/methodology/approach This study proposes a new stochastic super-efficiency DEA (S...
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This paper reviews the milestone approaches for handling uncertainty in data envelopment analysis (DEA). This paper presents the detailed classifications of robust data envelopment analysis (RDEA). RDEA is appropriate for measuring the efficiencies of decision making units (DMUs) in the presence of the data and distributional uncertainties. This pa...
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Purpose The objective of this paper is to propose a new data envelopment analysis (DEA) model for assessing sustainability of suppliers with partial impacts between inputs, desirable outputs and undesirable outputs. Design/methodology/approach This paper examines partial impacts of inputs on desirable and undesirable outputs and applies weak dispo...
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It is indeed a real pleasure to announce the publication of this special issue, Sustainable Operation in Manufacturing Enterprise (SOME), for Annals of Operations Research. Overall , many papers were received for this special issue, and based on reviewer reports the best papers are included in this issue. This special issue is focused primarily on...
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Purpose The aim of this paper is to classify suppliers into some clusters based on sustainability factors. However, there might be some unqualified suppliers and we should identify and remove those suppliers before clustering. Design/methodology/approach First, using fuzzy screening system, the authors identify and remove the unqualified suppliers...
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Data envelopment analysis (DEA) is one of the techniques for assessing sustainability of supply chains. There have been raising interests in incorporating sustainability in supply chain operations. The objective of this article is to develop a dynamic network DEA (DNDEA) model for calculating both optimistic and pessimistic efficiency and effective...
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To survive, organizations should inevitably work based on sustainability principles in an ever-increasing changes of markets. Appropriate flexibility and responsiveness are particularly important when considering sustainability issue and market changes in clustering problem. One of the uses of clustering can be allocation of resources and equipment...
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Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMU o ) and other decision-making units (DMUs) are...
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Appropriate supplier selection due to its direct impact on profitability and maintaining the competitive status of an organization is one of the vital decisions for each company. Data envelopment analysis (DEA) is a proper tool for measuring the sustainability of suppliers. Classic DEA models suppose that inputs and outputs are deterministic; conse...
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To assess sustainability of power plants, this paper presents a novel hybrid method. To this end, self‐organizing map method of artificial neural networks is employed. Then, a double frontier data envelopment analysis is developed to rank power plants in each cluster of decision‐making units. Because outputs of power plants might be uncertain, a ro...
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Recently, sustainable supply chain management has attracted the attention of scholars and practitioners. Data envelopment analysis (DEA) is a useful tool for evaluating sustainability of suppliers. Ranking a system of voting is an important topic in DEA. Many firms apply voting systems to rank candidates. Generally, these kinds of methods rank cand...
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Cap-and-trade is regarded as the most effective approach to control and reduce greenhouse gas emission. How to perform the reallocation in a fair way is very critical to control total amount of emissions and improve trade mechanism. It has been proved that data envelopment analysis (DEA) is an effective way for reallocation. The objective of the pr...
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Nowadays, forward-thinking companies move beyond conventional structures of organizations and consider all parties of the supply chain. The objective of this paper is to present an adaptive network data envelopment analysis (DEA) model to evaluate overall and divisional efficiency of sustainable supply chains in the presence of desirable and undesi...
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Transportation industry is one of the major contributors to the environmental pollution. Analyzing efficiency of this industry helps people and societies to enhance their awareness of its performance and develop managerial strategies. The need for sustainable development in transportation industry requires efficiency analysis over time. Malmquist p...
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Full-text available
Given the fierce competition between large companies, the sustainable supply chain has been recognized as a key component of corporate responsibility in recent years. Classification of suppliers can facilitate the selection of a suitable supplier for management, which saves time and costs for the company. Data envelopment analysis (DEA) has become...
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Purpose To manage cash flow in supply chains, the purpose of this paper is to propose inverse data envelopment analysis (DEA) model. Design/methodology/approach This paper develops an inverse range directional measure (RDM) model to deal with positive and negative values. The proposed model is developed to estimate input and output variations su...
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In the conventional data envelopment analysis (DEA) approach, decision making units (DMUs) are regarded as black boxes that transform sets of inputs into sets of outputs without considering the internal interactions taking place within each DMU. Two-stage DEA models are designed to overcome this shortfall. However, the existing two-stage DEA models...