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The current Special Issue contains six papers focused on Multiple Criteria Decision Making (MCDM) problems and the formal techniques applied to derive consistent rankings of them
Debora Di Caprio; Francisco Santos Arteaga. Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making. Algorithms 2021, 14, 233 .
AMA StyleDebora Di Caprio, Francisco Santos Arteaga. Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making. Algorithms. 2021; 14 (8):233.
Chicago/Turabian StyleDebora Di Caprio; Francisco Santos Arteaga. 2021. "Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making." Algorithms 14, no. 8: 233.
Digital supply chains (DSCs) are collaborative digital systems designed to quickly and efficiently move information, products, and services through global supply chains. The physical flow of products in traditional supply chains is replaced by the digital flow of information in DSCs. This digitalization has changed the conventional supplier selection processes. We propose an integrated and comprehensive fuzzy multicriteria model for supplier selection in DSCs. The proposed model integrates the fuzzy best-worst method (BWM) with the fuzzy multi-objective optimization based on ratio analysis plus full multiplicative form (MULTIMOORA), fuzzy complex proportional assessment of alternatives (COPRAS), and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The fuzzy BWM approach is used to measure the importance weights of the digital criteria. The fuzzy MULTIMOORA, fuzzy COPRAS, and fuzzy TOPSIS methods are used as prioritization methods to rank the suppliers. The maximize agreement heuristic (MAH) is used to aggregate the supplier rankings obtained from the prioritization methods into a consensus ranking. We present a real-world case study in a manufacturing company to demonstrate the applicability of the proposed method.
Madjid Tavana; Akram Shaabani; Debora Di Caprio; Maghsoud Amiri. An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains. Sustainable Operations and Computers 2021, 2, 149 -169.
AMA StyleMadjid Tavana, Akram Shaabani, Debora Di Caprio, Maghsoud Amiri. An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains. Sustainable Operations and Computers. 2021; 2 ():149-169.
Chicago/Turabian StyleMadjid Tavana; Akram Shaabani; Debora Di Caprio; Maghsoud Amiri. 2021. "An integrated and comprehensive fuzzy multicriteria model for supplier selection in digital supply chains." Sustainable Operations and Computers 2, no. : 149-169.
Consider the problem faced by a decision maker (DM) who must select the order in which to evaluate the unknown alternatives displayed by an online search engine. DMs do not know the distribution of the realizations that result from clicking on an alternative and must therefore account for the differences that may exist between the ranking provided by the engine and their subjective potential evaluations. The current paper formalizes the information retrieval incentives of DMs through a combinatorial function that incorporates the position of the results displayed by the search engine and the order in which they are evaluated. This function defines a benchmark framework measuring the ability of search engines to identify the preferences of DMs and the capacity of the latter to assimilate and evaluate the information provided by the engines. We compare the cumulative frequencies derived from the implementation of evaluation models of varying complexity with the average traffic shares and click through rates of the alternatives ranked within the first page of Google results. A seemingly paradoxical result is obtained when simulating the information acquisition behavior of DMs after performing an online search, namely, artificial agents require more complex combinatorial abilities than actual DMs to approximate better the heuristic choices of the latter in online evaluation environments.
Debora Di Caprio; Francisco J. Santos-Arteaga. Combinatorial abilities and heuristic behavior in online search environments. Operations Research Perspectives 2021, 8, 100179 .
AMA StyleDebora Di Caprio, Francisco J. Santos-Arteaga. Combinatorial abilities and heuristic behavior in online search environments. Operations Research Perspectives. 2021; 8 ():100179.
Chicago/Turabian StyleDebora Di Caprio; Francisco J. Santos-Arteaga. 2021. "Combinatorial abilities and heuristic behavior in online search environments." Operations Research Perspectives 8, no. : 100179.
Data envelopment analysis (DEA) is a nonparametric frontier assessment method used to evaluate the relative efficiency of similar decision-making units (DMUs). This method provides benchmarking information regarding the removal of inefficiency. In conventional DEA models, the view of the decision maker (DM) is ignored and the performance of each DMU is solely determined by the observations retrieved. The current paper exploits the structural similarity existing between DEA and multiple objective programming to define a model that incorporates the preferences of DMs in the evaluation process of DMUs. Given the potential unfeasibility of the input and output targets selected by the DM, the model defines an interactive procedure that considers minimum and maximum acceptable objective levels. Given the feasible levels located closer to the targets selected by the DM, a program improving upon the feasible allocations is designed so that the suggested benchmark approximates the requirements fixed by the DM as much as possible. A real-life case study is included to illustrate the efficacy and applicability of the proposed hybrid procedure.
Debora Di Caprio; Ali Ebrahimnejad; Mojtaba Ghiyasi; Francisco J. Santos-Arteaga. Integrating fuzzy goal programming and data envelopment analysis to incorporate preferred decision-maker targets in efficiency measurement. Decisions in Economics and Finance 2020, 43, 673 -690.
AMA StyleDebora Di Caprio, Ali Ebrahimnejad, Mojtaba Ghiyasi, Francisco J. Santos-Arteaga. Integrating fuzzy goal programming and data envelopment analysis to incorporate preferred decision-maker targets in efficiency measurement. Decisions in Economics and Finance. 2020; 43 (2):673-690.
Chicago/Turabian StyleDebora Di Caprio; Ali Ebrahimnejad; Mojtaba Ghiyasi; Francisco J. Santos-Arteaga. 2020. "Integrating fuzzy goal programming and data envelopment analysis to incorporate preferred decision-maker targets in efficiency measurement." Decisions in Economics and Finance 43, no. 2: 673-690.
We formalize the information acquisition and choice structure of a decision maker (DM) when the main characteristics defining the alternatives are not directly observed but numerical evaluations of unknown quality are provided by external raters. The DM observes the overall numerical value assigned by the raters to an alternative and defines an uncertain interval within which the evaluation observed is contained. The width of the interval is determined by the subjective perception and evaluation differences existing between the DM and the raters transmitting the information. We analyze the incentives of the DM to improve upon an evaluation contained within an uncertain interval by retrieving further information from the raters of other alternatives. Different scenarios will be developed based on the ability of the DM to fully assimilate uncertainty and the introduction of heuristic approximations to account for the potential frictions arising from uncertainty. One of the main qualities of the current framework is its capacity to formalize interactions among alternatives determined by interval width differences across their characteristics, providing an analytical advantage over the operational complexity involved in the use of fuzzy and intuitionistic fuzzy sets. The same remark applies to the formalization of the interactions across attributes that must be considered when defining sequential decision processes or dynamical systems while dealing with multiple sources of uncertainty. Numerical simulations are provided to compare the different scenarios developed and describe the main consequences derived from ignoring the uncertainty inherent to the evaluations received. In particular, we illustrate the ranking consequences derived from increasing the spread of the evaluation uncertainty, an effect that can be easily combined with the risk attitude exhibited by DMs. The inclusion of both these features bridges the gap between economics, psychology and multiple criteria decision making, whose techniques do not generally account for these differences among DMs.
Francisco J. Santos-Arteaga; Madjid Tavana; Debora Di Caprio. A new model for evaluating subjective online ratings with uncertain intervals. Expert Systems with Applications 2019, 139, 112850 .
AMA StyleFrancisco J. Santos-Arteaga, Madjid Tavana, Debora Di Caprio. A new model for evaluating subjective online ratings with uncertain intervals. Expert Systems with Applications. 2019; 139 ():112850.
Chicago/Turabian StyleFrancisco J. Santos-Arteaga; Madjid Tavana; Debora Di Caprio. 2019. "A new model for evaluating subjective online ratings with uncertain intervals." Expert Systems with Applications 139, no. : 112850.
Consider a decision maker (DM) who must rank a set of alternatives and select one of them when searching online using a recommender engine such as Amazon or TripAdvisor. These websites provide numerical and linguistic reviews of the available alternatives offered by groups of unknown raters. The evaluations assigned by the raters to the characteristics of the different alternatives may or may not coincide with the evaluations that would be assigned by the DM if he were to actually observe the alternative. Hence, the value assigned by the DM to a characteristic must account for the uncertainty regarding the distribution of its realizations, the frictions inherent to the evaluations of the raters and the subjective quality of the perception determining his own evaluation. We formalize the incentives of the DM to select an alternative using a value function that incorporates these sources of uncertainty within a multi-criteria decision making environment. In addition, we implement this perception-based evaluation scenario within a data envelopment analysis (DEA) framework in order to study numerically the effects that perception differentials have on the ranking and selection behavior of the DM.
Debora Di Caprio; Francisco J. Santos-Arteaga. A novel perception-based DEA method to evaluate alternatives in uncertain online environments. Computers & Industrial Engineering 2019, 131, 327 -343.
AMA StyleDebora Di Caprio, Francisco J. Santos-Arteaga. A novel perception-based DEA method to evaluate alternatives in uncertain online environments. Computers & Industrial Engineering. 2019; 131 ():327-343.
Chicago/Turabian StyleDebora Di Caprio; Francisco J. Santos-Arteaga. 2019. "A novel perception-based DEA method to evaluate alternatives in uncertain online environments." Computers & Industrial Engineering 131, no. : 327-343.
We define a novel information acquisition model that accounts explicitly for the influence of positive and negative anticipated emotions in the evaluation and selection incentives of decision makers (DMs). The model focuses on the value assigned by the DMs to the information being acquired and its capacity to prevent regrettable decisions within a forward-looking sequential environment. We introduce a novel definition of value of information accounting for the two main uses that DMs can derive from it, namely, verifying the optimality or suboptimality of a potential decision and preventing the regret that may arise from a suboptimal decision. In particular, DMs would regret a decision whenever rejecting [accepting] an alternative that should have actually been accepted [rejected]. Our formal information acquisition model allows to account for the subjective relative importance assigned by the DMs to the verification and regret value of information. Moreover, we illustrate how the incentives defining the sequential information retrieval process of DMs are determined by the relative width of the domains on which the different characteristics describing the alternatives are defined.
Debora Di Caprio; Francisco J. Santos-Arteaga; Madjid Tavana. The role of anticipated emotions and the value of information in determining sequential search incentives. Operations Research Perspectives 2019, 6, 100106 .
AMA StyleDebora Di Caprio, Francisco J. Santos-Arteaga, Madjid Tavana. The role of anticipated emotions and the value of information in determining sequential search incentives. Operations Research Perspectives. 2019; 6 ():100106.
Chicago/Turabian StyleDebora Di Caprio; Francisco J. Santos-Arteaga; Madjid Tavana. 2019. "The role of anticipated emotions and the value of information in determining sequential search incentives." Operations Research Perspectives 6, no. : 100106.
In this paper, a new non-linear mixed-integer mathematical programming problem is proposed to model a stochastic multi-product closed-loop supply chain (CLSC). The radio frequency identification (RFID) system is implemented in the supply chain to decrease product losses and the overall lead time of transportation while computing the profit derived from internet and conventional sales. The resulting traceable CLSC improves upon the existing literature by allowing us to: (1) boost the incorporation of traceability assumptions in mathematical programming problems so as to enhance the efficiency and visibility of a supply chain, (2) analyze the strategic effects that different internet sale formats have on customers’ evaluations and acquisition choices, and (3) account for the environmental and socio-economical dimension by explicitly formalizing employment-based incomes as part of the profit function. Two meta-heuristic algorithms are introduced to solve the proposed optimization problem, namely, the greedy randomized adaptive search procedure (GRASP) and particle swarm optimization (PSO). Twelve test problems of different sizes are generated and solved using these algorithms. The computational results show that GRASP outperforms PSO in terms of both profit and CPU time values. Finally, a case study in the network marketing industry is presented and managerial implications outlined to show the validity of the proposed model and shed more light on its practical implications.
Vahid Hajipour; Madjid Tavana; Debora Di Caprio; Majid Akhgar; Yasaman Jabbari. An optimization model for traceable closed-loop supply chain networks. Applied Mathematical Modelling 2019, 71, 673 -699.
AMA StyleVahid Hajipour, Madjid Tavana, Debora Di Caprio, Majid Akhgar, Yasaman Jabbari. An optimization model for traceable closed-loop supply chain networks. Applied Mathematical Modelling. 2019; 71 ():673-699.
Chicago/Turabian StyleVahid Hajipour; Madjid Tavana; Debora Di Caprio; Majid Akhgar; Yasaman Jabbari. 2019. "An optimization model for traceable closed-loop supply chain networks." Applied Mathematical Modelling 71, no. : 673-699.
Madjid Tavana; Amir-Reza Abtahi; Debora DI Caprio; Reza Hashemi; Reza Yousefi Zenouz. An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences 2018, 64, 21 -37.
AMA StyleMadjid Tavana, Amir-Reza Abtahi, Debora DI Caprio, Reza Hashemi, Reza Yousefi Zenouz. An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences. 2018; 64 ():21-37.
Chicago/Turabian StyleMadjid Tavana; Amir-Reza Abtahi; Debora DI Caprio; Reza Hashemi; Reza Yousefi Zenouz. 2018. "An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations." Socio-Economic Planning Sciences 64, no. : 21-37.
Dynamic data envelopment analysis (DEA) models are built on the idea that single period optimization is not fully appropriate to evaluate the performance of decision making units (DMUs) through time. As a result, these models provide a suitable framework to incorporate the different cumulative processes determining the evolution and strategic behavior of firms in the economics and business literatures. In the current paper, we incorporate two distinct complementary types of sequentially cumulative processes within a dynamic slacks-based measure DEA model. In particular, human capital and knowledge, constituting fundamental intangible inputs, exhibit a cumulative effect that goes beyond the corresponding factor endowment per period. At the same time, carry-over activities between consecutive periods will be used to define the pervasive effect that technology and infrastructures have on the productive capacity and efficiency of DMUs. The resulting dynamic DEA model accounts for the evolution of the knowledge accumulation and technological development processes of DMUs when evaluating both their overall and per period efficiency. Several numerical examples and a case study are included to demonstrate the applicability and efficacy of the proposed method.
Francisco J. Santos Arteaga; Madjid Tavana; Debora Di Caprio; Mehdi Toloo. A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution. European Journal of Operational Research 2018, 278, 448 -462.
AMA StyleFrancisco J. Santos Arteaga, Madjid Tavana, Debora Di Caprio, Mehdi Toloo. A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution. European Journal of Operational Research. 2018; 278 (2):448-462.
Chicago/Turabian StyleFrancisco J. Santos Arteaga; Madjid Tavana; Debora Di Caprio; Mehdi Toloo. 2018. "A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution." European Journal of Operational Research 278, no. 2: 448-462.
We develop a novel method that uses single-valued neutrosophic sets (NSs) to handle independent multi-source uncertainty measures affecting the reliability of experts’ assessments in group multi-criteria decision-making (GMCDM) problems. NSs are characterized by three independent membership magnitudes (falsity, truth and indeterminacy) and can be employed to model situations characterized by complex uncertainty. In the proposed approach, the neutrosophic indicators are defined to explicitly reflect DMs’ credibility (voting power), inconsistencies/errors inherent to the assessing process, and DMs’ confidence in their own evaluation abilities. In contrast with most of the existing studies, single-valued NSs are used not only to formalize the uncertainty affecting DMs’ priorities, but also to aggregate them into group estimates without the need to define neutrosophic decision matrices or aggregation operators. Group estimates are synthesized into crisp evaluations through a two-step deneutrosophication process that converts (1) single-valued NSs in fuzzy sets (FSs) using the standard Euclidean metric and (2) FSs in representative crisp values using defuzzification. Theoretical and practical implications are discussed to highlight the flexibility of the proposed approach. An illustrative example shows how taking into account the uncertainty inherent to the experts’ evaluations may deeply affect the results obtained in a standard fuzzy environment even when dealing with very simple ranking problems.
Mariya A. Sodenkamp; Madjid Tavana; Debora Di Caprio. An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets. Applied Soft Computing 2018, 71, 715 -727.
AMA StyleMariya A. Sodenkamp, Madjid Tavana, Debora Di Caprio. An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets. Applied Soft Computing. 2018; 71 ():715-727.
Chicago/Turabian StyleMariya A. Sodenkamp; Madjid Tavana; Debora Di Caprio. 2018. "An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets." Applied Soft Computing 71, no. : 715-727.
User acceptance of technology is essential to determine its success. The current paper incorporates the main properties of the technology acceptance models (TAMs) developed by management scholars into a pre-commitment signaling duopolistic framework, where two competing firms must decide the level of technological improvement of the products being introduced. As a result, the corresponding equilibria of the duopolistic technological games will be determined by demand-based factors, providing a novel approach and complementing the current supply-based economic and operational research models developed in the literature. The proposed model will be simulated numerically to illustrate the strategic optimality of the update process of smartphone and tablet characteristics defined by Apple and Samsung as the market developed.
Madjid Tavana; Debora Di Caprio; Francisco J. Santos-Arteaga. STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION. Technological and Economic Development of Economy 2018, 24, 1466 -1498.
AMA StyleMadjid Tavana, Debora Di Caprio, Francisco J. Santos-Arteaga. STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION. Technological and Economic Development of Economy. 2018; 24 (4):1466-1498.
Chicago/Turabian StyleMadjid Tavana; Debora Di Caprio; Francisco J. Santos-Arteaga. 2018. "STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION." Technological and Economic Development of Economy 24, no. 4: 1466-1498.
Mohammad Izadikhah; Madjid Tavana; Debora Di Caprio; Francisco J. Santos-Arteaga. A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs. Expert Systems with Applications 2018, 99, 213 -230.
AMA StyleMohammad Izadikhah, Madjid Tavana, Debora Di Caprio, Francisco J. Santos-Arteaga. A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs. Expert Systems with Applications. 2018; 99 ():213-230.
Chicago/Turabian StyleMohammad Izadikhah; Madjid Tavana; Debora Di Caprio; Francisco J. Santos-Arteaga. 2018. "A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs." Expert Systems with Applications 99, no. : 213-230.
Madjid Tavana; Francisco J. Santos-Arteaga; Debora DI Caprio. The value of information as a verification and regret-preventing mechanism in algorithmic search environments. Information Sciences 2018, 448-449, 187 -214.
AMA StyleMadjid Tavana, Francisco J. Santos-Arteaga, Debora DI Caprio. The value of information as a verification and regret-preventing mechanism in algorithmic search environments. Information Sciences. 2018; 448-449 ():187-214.
Chicago/Turabian StyleMadjid Tavana; Francisco J. Santos-Arteaga; Debora DI Caprio. 2018. "The value of information as a verification and regret-preventing mechanism in algorithmic search environments." Information Sciences 448-449, no. : 187-214.
Purpose The purpose of this paper is to provide a theoretical framework for predicting the next period financial behavior of bank mergers within a statistical-oriented setting. Design/methodology/approach Bank mergers are modeled combining a discrete variant of the Smoluchowski coagulation equation with a reverse engineering method. This new approach allows to compute the correct merging probability values via the construction and solution of a multi-variable matrix equation. The model is tested on real financial data relative to US banks collected from the National Information Centre. Findings Bank size distributions predicted by the proposed method are much more adherent to real data than those derived from the estimation method. The proposed method provides a valid alternative to estimation approaches while overcoming some of their typical drawbacks. Research limitations/implications Bank mergers are interpreted as stochastic processes focusing on two main parameters, that is, number of banks and asset size. Future research could expand the model analyzing the micro-dynamic taking place behind bank mergers. Furthermore, bank demerging and partial bank merging could be considered in order to complete and strengthen the proposed approach. Practical implications The implementation of the proposed method assists managers in making informed decisions regarding future merging actions and marketing strategies so as to maximize the benefits of merging actions while reducing the associated potential risks from both a financial and marketing viewpoint. Originality/value To the best of the authors’ knowledge, this is the first study where bank merging is analyzed using a dynamic stochastic model and the merging probabilities are determined by a multi-variable matrix equation in place of an estimation procedure.
Zahra Banakar; Madjid Tavana; Brian Huff; Debora DI Caprio. A bank merger predictive model using the Smoluchowski stochastic coagulation equation and reverse engineering. International Journal of Bank Marketing 2018, 36, 634 -662.
AMA StyleZahra Banakar, Madjid Tavana, Brian Huff, Debora DI Caprio. A bank merger predictive model using the Smoluchowski stochastic coagulation equation and reverse engineering. International Journal of Bank Marketing. 2018; 36 (4):634-662.
Chicago/Turabian StyleZahra Banakar; Madjid Tavana; Brian Huff; Debora DI Caprio. 2018. "A bank merger predictive model using the Smoluchowski stochastic coagulation equation and reverse engineering." International Journal of Bank Marketing 36, no. 4: 634-662.
Consider a decision maker (DM) who must select an alternative to evaluate when using an online recommender engine that displays multiple evaluations from unknown raters regarding the different characteristics of the available alternatives. The evaluations of the raters do not necessarily coincide with those that would be provided by the DM, who must consider the differences existing between the ratings observed and his subjective perception and subsequent potential evaluations. We formalize the incentives of the DM to observe and evaluate an alternative through a function that accounts for these differences in a multi-criteria decision making setting. The resulting perception-based framework is implemented in a data envelopment analysis (DEA) scenario to analyze the effects of perception differentials on the evaluation and ranking behavior of DMs.
Debora DI Caprio; Francisco Javier Santos-Arteaga. Implementing Data Envelopment Analysis in an Uncertain Perception-Based Online Evaluation Environment. Communications in Computer and Information Science 2018, 299 -309.
AMA StyleDebora DI Caprio, Francisco Javier Santos-Arteaga. Implementing Data Envelopment Analysis in an Uncertain Perception-Based Online Evaluation Environment. Communications in Computer and Information Science. 2018; ():299-309.
Chicago/Turabian StyleDebora DI Caprio; Francisco Javier Santos-Arteaga. 2018. "Implementing Data Envelopment Analysis in an Uncertain Perception-Based Online Evaluation Environment." Communications in Computer and Information Science , no. : 299-309.
Madjid Tavana; Debora DI Caprio; Francisco J. Santos-Arteaga. An extended stochastic VIKOR model with decision maker's attitude towards risk. Information Sciences 2018, 432, 301 -318.
AMA StyleMadjid Tavana, Debora DI Caprio, Francisco J. Santos-Arteaga. An extended stochastic VIKOR model with decision maker's attitude towards risk. Information Sciences. 2018; 432 ():301-318.
Chicago/Turabian StyleMadjid Tavana; Debora DI Caprio; Francisco J. Santos-Arteaga. 2018. "An extended stochastic VIKOR model with decision maker's attitude towards risk." Information Sciences 432, no. : 301-318.
Data envelopment analysis (DEA) is a useful management tool for measuring the relative efficiency of decision making units (DMUs) which consumes multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally indispensable in classical DEA models, real-world problems often involve random and/or rough input and output data. We present a chance-constrained DEA model with random and rough (random-rough) input and output data and propose a deterministic equivalent model with quadratic constraints to solve the model. The main contributions of this paper are fourfold: (3.1) we propose a DEA model for problems characterized by random-rough variables; (3.2) we transform the proposed chance-constrained model with random-rough variables into a deterministic equivalent non-linear form that could be simplified as a deterministic model with quadratic constraints; (3.3) we perform sensitivity analysis to investigate the stability and robustness of the proposed model; and (3.4) we use a numerical example to demonstrate the feasibility and richness of the obtained solutions.
Rashed Khanjani Shiraz; Madjid Tavana; Debora Di Caprio. Chance-constrained data envelopment analysis modeling with random-rough data. RAIRO - Operations Research 2018, 52, 259 -284.
AMA StyleRashed Khanjani Shiraz, Madjid Tavana, Debora Di Caprio. Chance-constrained data envelopment analysis modeling with random-rough data. RAIRO - Operations Research. 2018; 52 (1):259-284.
Chicago/Turabian StyleRashed Khanjani Shiraz; Madjid Tavana; Debora Di Caprio. 2018. "Chance-constrained data envelopment analysis modeling with random-rough data." RAIRO - Operations Research 52, no. 1: 259-284.
Madjid Tavana; Mohammad Izadikhah; Debora Di Caprio; Reza Farzipoor Saen. A new dynamic range directional measure for two-stage data envelopment analysis models with negative data. Computers & Industrial Engineering 2018, 115, 427 -448.
AMA StyleMadjid Tavana, Mohammad Izadikhah, Debora Di Caprio, Reza Farzipoor Saen. A new dynamic range directional measure for two-stage data envelopment analysis models with negative data. Computers & Industrial Engineering. 2018; 115 ():427-448.
Chicago/Turabian StyleMadjid Tavana; Mohammad Izadikhah; Debora Di Caprio; Reza Farzipoor Saen. 2018. "A new dynamic range directional measure for two-stage data envelopment analysis models with negative data." Computers & Industrial Engineering 115, no. : 427-448.
Madjid Tavana; Amir-Reza Abtahi; Debora Di Caprio; Maryam Poortarigh. An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking. Neurocomputing 2018, 275, 2525 -2554.
AMA StyleMadjid Tavana, Amir-Reza Abtahi, Debora Di Caprio, Maryam Poortarigh. An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking. Neurocomputing. 2018; 275 ():2525-2554.
Chicago/Turabian StyleMadjid Tavana; Amir-Reza Abtahi; Debora Di Caprio; Maryam Poortarigh. 2018. "An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking." Neurocomputing 275, no. : 2525-2554.