Madjid Tavana

La Salle University · School of Business

Most real-life decisions are made with less than perfect information and there is often some opportunity to acquire additional information to increase the quality of the decision. In this paper, we define and study the sequential information acquisition process of a rational decision maker (DM) when allowed to acquire any finite amount of informati...

We introduce a novel decision support framework that allows decision makers (DMs) to assess the informativeness of a ranking of alternatives provided by different experts and to extrapolate additional evaluations based on the distributional bias and entropy inherent to those received from the experts. In the proposed framework, expert analysts rank...

The prioritization of advanced-technology projects at the National Aeronautic and Space Administration (NASA) is a difficult task. This difficulty is due to the multiple and often conflicting objectives in addition to the inherent technical complexities and valuation uncertainties involved in the assessment process. As such, a systematic and transp...

The robotization and digitalization of businesses are slow and demanding processes requiring significant investments in human capital and infrastructures. The ability of firms to adapt their production and innovation structures conditions the successful implementation of robotics and centralized computing across their value chains. At the same time...

Data envelopment analysis (DEA) is a well-established method for measuring efficiency among a comparable group of decision-making units (DMUs). DMUs comprise entities with time-related activities—i.e., inputs and outputs. The concept of DMU is not reserved only for business entities; it can also be a project or product. This study focuses on the la...

Socially responsible procurement includes diversity and inclusion, and many companies have found diverse sourcing plays a substantial role in their success. Supplier diversity and inclusion initiatives can significantly impact innovation, reputation, employee engagement, and organizational retention. This paper presents a novel fuzzy general best–w...

The concept of returns to scale (RTS) or local scale elasticities in data envelopment analysis (DEA)—stemming from variable returns to scale (VRS) technology—has been recently criticized because of its misbehavior in the case of decreasing returns to scale (DRS). Here, the instrument should imply a downsizing force for improving productivity. In cl...

This study introduces a novel approach named the fuzzy KEmeny Median Indicator Ranks Accordance (KEMIRA) method tailored for Multi-Attribute Decision Making (MADM) while capturing and processing the uncertainties inherent in complex problems. We explore preferential voting to enhance MADM models, rewriting it as a Linear Programming (LP) problem wi...

This paper studies a linear programming (LP) and a multiple attribute decision-making (MADM) model with hesitant fuzzy numbers (HFNs) for solving group decision-making problems under uncertainty. We introduce a new type of HFN whose flexibility allows for its direct application to standard LP and MADM methods while facing credibility considerations...

The current paper analyzes the efficiency displayed by 24 European Union (EU) countries when fostering labor productivity and the value added via ICT investments. In particular, a dynamic slacks-based measure data envelopment analysis (SBM-DEA) model is applied to analyze the evolution of efficiency through the period 2006–2013. The ranking resulti...

We analyze the effects of digitalization and the knowledge acquired through vertical and institutional cooperation across the value chain on the introduction of patents and technological, namely, product and process, innovations in large, and small and medium-sized enterprises (SMEs). We study the case of Spain as a digitally competitive economy di...

Circular supplier evaluation aims at selecting the most suitable suppliers with zero waste. Sustainable circular supplier selection also considers socio-economic and environmental factors in the decision process. This study proposes an integrated method for evaluating sustainable suppliers in intelligent circular supply chains using fuzzy inference...

The Best-Worst Method (BWM) is a relatively new and popular method for obtaining criteria weights in multi-criteria decision-making. The BWM uses very few comparisons and produces consistent comparisons, leading to more reliable criteria weights. Despite its popularity and reliability, the decision criteria in the BWM are considered independent of...

Designing resilient supply chain networks for vaccine development and distribution requires reliable and robust infrastructure. This stud develops a novel two-stage decision support framework for configuring multi-echelon Supply Chain Networks (SCNs), resilient supplier selection, and order allocation under uncertainty. Resilient supplier selection...

This special issue shall advance knowledge regarding the interrelationship between Circular Economy (CE) and Open Innovation (OI). It aims to promote the businesses' transition to new models of sustainable development. Several governments are taking action to develop green policies (i.e., The European Green Deal, the United Nations 2030 Agenda, etc...

Designing and developing sustainable circular supply chain networks for electric vehicle (EV) lithium‐ion battery recycling and production requires complex environmental sustainability and economic viability assessment. EVs use a lot of data for battery management and delivering optimum performance, and the Internet of Things (IoT) plays a major ro...

Most companies operate to maximize profits and increase their market shares in competitive environments. Since the proper location of the facilities conditions their market shares and profits, the competitive facility location problem (CFLP) has been extensively applied in the literature. This problem generally falls within the class of NP-hard pro...

Information and Communication Technologies (ICTs) have been extensively adopted by firms worldwide due to the significant positive effect on their performance. This fact contrasts with the uncertainty faced by decision makers when entering a country and selecting local firms with which to interact. Consider selecting Decision Making Units (DMUs) ac...

Circular supply chain (CSC) networks improve sustainability and create socially responsible enterprises through recycling, harvesting, and refurbishing. This study develops a Lagrangian relaxation (LR) algorithm for solving location-inventory-routing (LIR) problems with heterogeneous vehicles in multi-period and multi-product sustainable CSC networ...

The twenty-two papers in this special section focus on fuzzy decision systems for sustainable transport. Sustainable transport has gained widespread recognition by countries, local governments, cities, and transport authorities around the world to bring about positive change for the environment, ensure wider accessibility, and reduce carbon emissio...

Despite the widespread use of interpretive structural modeling (ISM) in business research, little is known about its overall scientific productivity and impact on business research. This study presents a comprehensive review of the published ISM research and its latest editions in business using text mining. A two-tier review (narrative and systema...

Purpose New business practices and the globalization of markets force firms to take innovation as the fundamental pillar of their competitive strategy. Research and Development (R&D) plays a vital role in innovation. As technology advances and product life cycles become shorter, firms rely on R&D as a strategy to invigorate innovation. R&D project...

Many companies face challenges in reducing their supply chain costs while increasing sustainability and customer service levels. A comprehensive framework for a sustainable closed-loop supply chain (CLSC) network is a practical solution to these challenges. Hence, for the first time, this study considers an integrated multi-objective mixed-integer...

The papers in this special section focus on industrial information integration in space applications. With continuous growth in the complexity, scale, and dynamics of space systems, information integration (II) becomes an essential strategy for managing system complexity and tackling dynamic changes and uncertainties in space missions. Space II (SI...

Flow shop scheduling deals with the determination of the optimal sequence of jobs processing on machines in a fixed order with the main objective consisting of minimizing the completion time of all jobs (makespan). This type of scheduling problem appears in many industrial and production planning applications. This study proposes a new bi-objective...

Economic-environmental performance or eco-efficiency is a topic of great interest due to the “green movement.” Data Envelopment Analysis (DEA) is a non-parametric method for measuring the eco-efficiencies in comparable Decision-Making Units (DMUs) under various technology assumptions, e.g., constant or variable returns to scale. In the case of vari...

Waste collection management plays a crucial role in controlling pandemic outbreaks. Electric waste collection systems and vehicles can improve the efficiency and effectiveness of sanitary processes in municipalities worldwide. The waste collection routing optimization involves designing routes to serve all customers with the least number of vehicle...

Artificial intelligence (AI) promises breakthroughs in space operations, from mission design planning to satellite data processing and navigation systems. Advances in AI and space transportation have enabled AI technologies in spacecraft tracking control and synchronization. This study assesses and evaluates three alternative spacecraft tracking co...

Multiple Criteria Decision-Making (MCDM) methods do not account for the potentially strategic evaluations of experts. Once the ranking is delivered, Decision Makers (DMs) select the first alternative without questioning the credibility of the evaluations received from the experts. We formalize the selection problem of a DM who must choose from a se...

Railway transportation is the backbone of the economy significantly influences mobility and life quality in many developed and developing countries. Railway infrastructure investment problems are inherently complex and involve multiple and often conflicting criteria in an uncertain socio-economic environment. This study presents an integrated rough...

Metaverse comes from the meta-universe, and it is the integration of physical and digital space into a virtual universe. Metaverse technologies will change the transportation system as we know it. Preparations for the transition of the transportation systems into the world of metaverse are underway. This study considers four alternative metaverses:...

Clustering is an ideal tool for working with big data and searching for structures in the data set. Clustering aims at maximizing the similarity between the data within a cluster and minimizing the similarity between the data between different clusters. This study presents a new and improved Particle Swarm Optimization (PSO) algorithm using pattern...

We design an information retrieval algorithm that mimics the stochastic behavior of decision-makers (DMs) when evaluating the alternatives displayed by an online search engine. The algorithm consists of a decision tree that incorporates all the 1,024 decision nodes that may arise from the information retrieval process of DMs. We calibrate the behav...

Industry 4.0 technologies are causing a paradigm shift in supply chain process management. The digital transformation of the supply chains provides enormous benefits to organizations by empowering collaboration among multiple internal and external organizations and systems. This study presents a narrative review explaining the existing knowledge on...

This paper presents the problem of batching and scheduling jobs belonging to incompatible job families on unrelated-parallel machines. More specifically, we investigate cost-efficient approaches for solving batching and scheduling problems concerning the desired lower bounds on batch sizes (〖LB〗_b), which indirectly has a considerable impact on the...

We present an equilibrium model where the demand side of the market determines the strategic incentives of firms when considering the introduction of technologically superior products (TSPs) and the subsequent dynamic evolution of the market configuration. Market demand is built on conventional features defining the behavior of decision-makers (DMs...

Increasing consumer goods and products has inspired environmental activists and policymakers to demand eco-friendly packaging from retailers and manufacturers. At the same time, consumer attitudes about sustainable packaging have changed significantly. In response to these changing consumer sentiments, the packaging value chain is changing, and bus...

Supply chain collaboration plays an important role in profit maximization. Contract coordination is a successful strategy for collaboration and profit-sharing in supply chains. The study of contract coordination in supply chains under uncertainty and stochastic environmental conditions has attracted the attention of many researchers. We propose a s...

Every second counts for patients with life-threatening injuries, and trauma centers deliver timely emergency care to patients with traumatic injuries. Quality assessment and improvement are some of the most fundamental concerns in trauma centers. In this study, a comprehensive organizational resilience approach is proposed to evaluate performance i...

Cascade disasters can destroy urban infrastructures, kill thousands of people, and permanently displace millions of people. The paramount goal of disaster relief programs is to save lives, reduce financial loss, and accelerate the relief process. This study proposes a bi-level two-echelon mathematical model to minimize pre-disaster costs and maximi...

The formalization and solution of supplier selection problems (SSPs) based on sustainable (economic, environmental, and social) indicators have become a fundamental tool to perform a strategic analysis of the whole supply chain process and maximize the competitive advantage of firms. Over the last decade, sustainability issues have been often consi...

Developing sustainable municipal waste management systems requires an in-depth analysis and synthesis of economic, environmental, and social sustainable development indicators. However, despite its profound impact on organizational performance, social sustainability has received little attention in previous studies compared to economic and environm...

This study analyzes the effects that the position of the alternatives ranked by a search engine and the relative impatience of users have on their information retrieval behavior. We design a stochastic information retrieval algorithm calibrated to mimic the click-through rates (CTRs) of users observed in real-life environments. We introduce two ver...

This book discusses an emerging area in computer science, IT, and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision making for cross-platforms that contain heterogeneous data assoc...

In this race for productivity, the most successful leaders in the banking industry are those with high-efficiency and a competitive edge. Data envelopment analysis is one of the most widely used methods for measuring efficiency in organizations. In this study, we use the ideal point concept and propose a common weights model with fuzzy data and non...

The Analytical Hierarchy Process (AHP) is a reliable, rigorous, and robust method for eliciting and quantifying subjective judgments in multi-criteria decision-making (MCDM). Despite the many benefits, the complications of the pairwise comparison process and the limitations of consistency in AHP are challenges that have been the subject of extensiv...

This paper deals with imprecise data in data envelopment analysis (DEA). We construct a new pair of mathematical programming models by using the concepts of ‘inf’ and ‘sup’ to calculate the exact values of the lower- and upper-bound efficiency scores in the presence of interval and ordinal data. The method proposed in this study is motivated by the...

The supplier selection for medical equipment is one of the major challenges for hospitals in healthcare supply chains. The primary reason for measuring medical equipment supplier efficiency is to achieve the highest level of overall performance and productivity in healthcare supply chains. This study presents an integrated quality and resilience en...

Data envelopment analysis (DEA) is a linear programming method for measuring the performance and efficiency of units called decision-making units (DMUs). In many real-world performance measurement problems, the input and output data are not precisely known. Furthermore, the data may include dual-role factors that can be considered an input and outp...

The tourism and hospitality industry significantly impacts socio-economic development and cultural growth in developing countries. This study develops an integrated multicriteria decision-making and optimization model for partner selection in public-private partnership (PPP) projects in the hospitality industry. The proposed model uses a weighted i...

This study analyzes the effects that the position of the alternatives ranked by a search engine and the relative impatience of users have on their information retrieval behavior. We design a stochastic information retrieval algorithm calibrated to mimic the click-through rates (CTRs) of users observed in real-life environments. We introduce two ver...

Linear programming (LP) has long proved its merit as the most flexible and most widely used technique for resource allocation problems in various fields. To solve an LP problem, we have traditionally considered crisp values for the parameters, which are unrealistic in real-world decision-making under uncertainty. The fuzzy set theory has been used...

Manufacturing companies are under constant pressure to optimize the economic sus-tainability of their production systems. Production planning and optimization is a well-established strategy for considering resource constraints and improving economic produc-tivity. This study proposes an integrated fuzzy goal planning and the theory of constraints f...

Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents...

Many cities are struggling to keep pace with limited budgets and rapid growth. Economic development models involving public-private partnerships (P3s) can help drive economic revitalization. The choice of partners plays a vital role in the success or failure of sustainable P3 initiatives. In this study, we propose a novel integrated sustainable pri...

Data envelopment analysis (DEA) is a mathematical approach for evaluating the efficiency of decision-making units that convert multiple inputs into multiple outputs. Traditional DEA models measure technical (radial) efficiencies by assuming the input and output status of each performance measure is known, and the data associated with the performance...

Degenerate optimal weights and uncertain data are two challenging problems in conventional data envelopment analysis (DEA). Cross-efficiency and robust optimization are commonly used to handle such problems. We develop two DEA adaptations to rank decision-making units (DMUs) characterized by uncertain data and undesirable outputs. The first adaptat...

Choosing the right supplier has a significant impact on the efficiency and productivity of a supply chain (SC). Different supplier selection models and approaches have been developed for reverse SCs. The lean, agile, resilient, and green (LARG) strategy is an innovative paradigm for supply chain competitiveness and sustainability. This study propos...

In this paper, we study the scheduling problem for a customized production system consisting of a flow shop production line with a parallel assembly stage that produces various products in two stages. In the first stage of the production line, parts are produced using a flow shop production line, and in the second stage, products are assembled on o...

The electric power industry is uniquely vulnerable to natural and human-made risks such as natural disasters, climate change, and cybersecurity. This study proposes a vulnerability assessment framework to identify and assess the risks associated with the electric power supply chain in the United Kingdom and study the causal relationship among them...

The location-inventory-routing modeling is an integrated and comprehensive approach to the interconnected location planning, inventory management, and vehicle routing problems in supply chain management. Supplier selection and order allocation are critical operational and strategic decisions in green supply chains. Green supply chain management is...

We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation to solve the flexible flow shop scheduling problems with sequence-based setup time, transportation time, and probable rework. A constructive heuristic is used to generate the initial solution, and clustering is applied to improve the solution. The propos...