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Dr. Francisco Javier Santos-Arteaga
Faculty of Economics and Management, Free University of Bolzano

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0 Decision Theory
0 Economic Growth
0 Innovation
0 Operations Research
0 Multiple criteria decision making

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Multiple criteria decision making
Decision Theory
Operations Research

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Editorial
Published: 08 August 2021 in Algorithms
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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

ACS Style

Debora Di Caprio; Francisco Santos Arteaga. Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making. Algorithms 2021, 14, 233 .

AMA Style

Debora Di Caprio, Francisco Santos Arteaga. Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making. Algorithms. 2021; 14 (8):233.

Chicago/Turabian Style

Debora Di Caprio; Francisco Santos Arteaga. 2021. "Special Issue on Algorithms and Models for Dynamic Multiple Criteria Decision Making." Algorithms 14, no. 8: 233.

Research article
Published: 13 June 2021 in Cornell Hospitality Quarterly
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The academic literature analyzing the behavior and interactions among commensals at a table generally resorts to experimental settings with volunteer decision makers or focuses on receipts issued at actual restaurants. The experimental approach widens the potential scope of the phenomena that can be analyzed but is subject to observer effects, with decision makers being aware of the fact that their actions are being monitored. The approach using receipts is not subject to observer effects but limited in its scope by lacking interactions with the commensals and the data that can be collected. In the current article, we make extensive use of a data set collected by restaurant personnel following specific instructions. They gathered information on a number of decisions made at the table throughout the whole meal without the commensals being aware that they are being monitored. As a result, we are able to examine empirically the importance that the choices of the first-person ordering (the leader) may have for the decisions made by the other commensals at the table. In particular, we study the similarity of orders—in terms of dishes, drinks, and prices—between the table leader and the other commensals. Our results reveal that table leaders, both male and female, have a considerable influence on the choices made by other commensals under a variety of different scenarios. We also describe the differences arising when males and females act as table leaders, as well as the influence that specific payment arrangements have on the ordering behavior of the commensals.

ACS Style

Guenter Schamel; Francisco Javier Santos-Arteaga. Metrics on Restaurant Ordering Behavior. Cornell Hospitality Quarterly 2021, 62, 386 -404.

AMA Style

Guenter Schamel, Francisco Javier Santos-Arteaga. Metrics on Restaurant Ordering Behavior. Cornell Hospitality Quarterly. 2021; 62 (3):386-404.

Chicago/Turabian Style

Guenter Schamel; Francisco Javier Santos-Arteaga. 2021. "Metrics on Restaurant Ordering Behavior." Cornell Hospitality Quarterly 62, no. 3: 386-404.

Article
Published: 23 April 2021 in Artificial Intelligence Review
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In an overwhelming demand scenario, such as the SARS-CoV-2 pandemic, pressure over health systems may outburst their predicted capacity to deal with such extreme situations. Therefore, in order to successfully face a health emergency, scientific evidence and validated models are needed to provide real-time information that could be applied by any health center, especially for high-risk populations, such as transplant recipients. We have developed a hybrid prediction model whose accuracy relative to several alternative configurations has been validated through a battery of clustering techniques. Using hospital admission data from a cohort of hospitalized transplant patients, our hybrid Data Envelopment Analysis (DEA)—Artificial Neural Network (ANN) model extrapolates the progression towards severe COVID-19 disease with an accuracy of 96.3%, outperforming any competing model, such as logistic regression (65.5%) and random forest (44.8%). In this regard, DEA-ANN allows us to categorize the evolution of patients through the values of the analyses performed at hospital admission. Our prediction model may help guiding COVID-19 management through the identification of key predictors that permit a sustainable management of resources in a patient-centered model.

ACS Style

Ignacio Revuelta; Francisco J. Santos-Arteaga; Enrique Montagud-Marrahi; Pedro Ventura-Aguiar; Debora Di Caprio; Frederic Cofan; David Cucchiari; Vicens Torregrosa; Gaston Julio Piñeiro; Nuria Esforzado; Marta Bodro; Jessica Ugalde-Altamirano; Asuncion Moreno; Josep M. Campistol; Antonio Alcaraz; Beatriu Bayès; Esteban Poch; Federico Oppenheimer; Fritz Diekmann. A hybrid data envelopment analysis—artificial neural network prediction model for COVID-19 severity in transplant recipients. Artificial Intelligence Review 2021, 1 -32.

AMA Style

Ignacio Revuelta, Francisco J. Santos-Arteaga, Enrique Montagud-Marrahi, Pedro Ventura-Aguiar, Debora Di Caprio, Frederic Cofan, David Cucchiari, Vicens Torregrosa, Gaston Julio Piñeiro, Nuria Esforzado, Marta Bodro, Jessica Ugalde-Altamirano, Asuncion Moreno, Josep M. Campistol, Antonio Alcaraz, Beatriu Bayès, Esteban Poch, Federico Oppenheimer, Fritz Diekmann. A hybrid data envelopment analysis—artificial neural network prediction model for COVID-19 severity in transplant recipients. Artificial Intelligence Review. 2021; ():1-32.

Chicago/Turabian Style

Ignacio Revuelta; Francisco J. Santos-Arteaga; Enrique Montagud-Marrahi; Pedro Ventura-Aguiar; Debora Di Caprio; Frederic Cofan; David Cucchiari; Vicens Torregrosa; Gaston Julio Piñeiro; Nuria Esforzado; Marta Bodro; Jessica Ugalde-Altamirano; Asuncion Moreno; Josep M. Campistol; Antonio Alcaraz; Beatriu Bayès; Esteban Poch; Federico Oppenheimer; Fritz Diekmann. 2021. "A hybrid data envelopment analysis—artificial neural network prediction model for COVID-19 severity in transplant recipients." Artificial Intelligence Review , no. : 1-32.

Journal article
Published: 14 January 2021 in Operations Research Perspectives
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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.

ACS Style

Debora Di Caprio; Francisco J. Santos-Arteaga. Combinatorial abilities and heuristic behavior in online search environments. Operations Research Perspectives 2021, 8, 100179 .

AMA Style

Debora Di Caprio, Francisco J. Santos-Arteaga. Combinatorial abilities and heuristic behavior in online search environments. Operations Research Perspectives. 2021; 8 ():100179.

Chicago/Turabian Style

Debora Di Caprio; Francisco J. Santos-Arteaga. 2021. "Combinatorial abilities and heuristic behavior in online search environments." Operations Research Perspectives 8, no. : 100179.

Journal article
Published: 13 November 2020 in Technological and Economic Development of Economy
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We present a formal and empirical framework that links the technological capacity of a country, reflected in its National System of Innovation, with the financial constraints it faces. The paper is divided into two sections. The first one introduces a stochastic growth model based on the relative level of technological development of countries, which determines their productivity and capacity to finance innovation activities. The second section describes the empirical conditioning observed in the innovation outputs of countries determined by their financial constraints and time period relative to the economic crisis of 2008. We classify a panel sample of European Union countries according to their technological development level and find that financial stability constraints negatively affect the less developed ones, a relationship that weakens as their innovation capacity increases. We also observe that financial stability becomes significant among technologically developed countries when reacting to the exogenous shock triggered by the crisis, while laggards remain constrained through the entire 2000–2018 sample period.

ACS Style

Francisco Javier Santos-Arteaga; Madjid Tavana; Celia Torrecillas; Debora Di Caprio. INNOVATION DYNAMICS AND FINANCIAL STABILITY: A EUROPEAN UNION PERSPECTIVE. Technological and Economic Development of Economy 2020, 26, 1366 -1398.

AMA Style

Francisco Javier Santos-Arteaga, Madjid Tavana, Celia Torrecillas, Debora Di Caprio. INNOVATION DYNAMICS AND FINANCIAL STABILITY: A EUROPEAN UNION PERSPECTIVE. Technological and Economic Development of Economy. 2020; 26 (6):1366-1398.

Chicago/Turabian Style

Francisco Javier Santos-Arteaga; Madjid Tavana; Celia Torrecillas; Debora Di Caprio. 2020. "INNOVATION DYNAMICS AND FINANCIAL STABILITY: A EUROPEAN UNION PERSPECTIVE." Technological and Economic Development of Economy 26, no. 6: 1366-1398.

Article
Published: 20 September 2020 in Decisions in Economics and Finance
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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.

ACS Style

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 Style

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 (2):673-690.

Chicago/Turabian Style

Debora 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.

Article
Published: 18 September 2020 in Health Care Management Science
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The main applications of Data Envelopment Analysis (DEA) to medicine focus on evaluating the efficiency of different health structures, hospitals and departments within them. The evolution of patients after undergoing a medical procedure or their response to a given treatment are not generally studied through this programming technique. In addition to the difficulty inherent to the collection of this type of data, the use of a technique that is mainly applied to evaluate the efficiency of decision making units representing industrial and production structures to analyze the evolution of human patients may seem inappropriate. In the current paper, we illustrate how this is not actually the case and implement a decision engineering approach to model kidney transplantation patients as decision making units. As such, patients undergo three different phases, each composed by specific as well as interrelated variables, determining the potential success of the transplantation process. DEA is applied to a set of 12 input and 6 output variables – retrieved over a 10-year period – describing the evolution of 485 patients undergoing kidney transplantation from living donors. The resulting analysis allows us to classify the set of patients in terms of the efficiency of the transplantation process and identify the specific characteristics across which potential improvements could be defined on a per patient basis.

ACS Style

Francisco Javier Santos Arteaga; Debora Di Caprio; David Cucchiari; Josep M Campistol; Federico Oppenheimer; Fritz Diekmann; Ignacio Revuelta. Modeling patients as decision making units: evaluating the efficiency of kidney transplantation through data envelopment analysis. Health Care Management Science 2020, 24, 55 -71.

AMA Style

Francisco Javier Santos Arteaga, Debora Di Caprio, David Cucchiari, Josep M Campistol, Federico Oppenheimer, Fritz Diekmann, Ignacio Revuelta. Modeling patients as decision making units: evaluating the efficiency of kidney transplantation through data envelopment analysis. Health Care Management Science. 2020; 24 (1):55-71.

Chicago/Turabian Style

Francisco Javier Santos Arteaga; Debora Di Caprio; David Cucchiari; Josep M Campistol; Federico Oppenheimer; Fritz Diekmann; Ignacio Revuelta. 2020. "Modeling patients as decision making units: evaluating the efficiency of kidney transplantation through data envelopment analysis." Health Care Management Science 24, no. 1: 55-71.

Review
Published: 01 August 2020 in Energies
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The managerial and environmental studies conducted in the energy research area reflect its substantial importance, particularly when optimizing and modifying consumption patterns, transitioning to renewable sources away from fossil ones, and designing plans and systems. The aim of this study is to provide a systematic review of the literature allowing us to identify which research subjects have been prioritized in the fields of energy and sustainability in recent years, determine the potential reasons explaining these trends, and categorize the techniques applied to analyze the uncertainty faced by decision-makers. We review articles published in highly ranked journals through the period 2003–2020 and apply text analytics to cluster their main characteristics; that is, we rely on pre-processing and text mining techniques. We analyze the title, abstract, keywords, and research methodology of the articles through clustering and topic modeling and illustrate what methods and fields constitute the main focus of researchers. We demonstrate the substantial importance of fuzzy-related methods and decision-making techniques such as the Analytical Hierarchy Process and Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). We also show that subjects such as renewable energy, energy planning, sustainable energy, energy policy, and wind energy have gained relevance among researchers in recent years.

ACS Style

Madjid Tavana; Akram Shaabani; Francisco Javier Santos-Arteaga; Iman Raeesi Vanani. A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics. Energies 2020, 13, 3947 .

AMA Style

Madjid Tavana, Akram Shaabani, Francisco Javier Santos-Arteaga, Iman Raeesi Vanani. A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics. Energies. 2020; 13 (15):3947.

Chicago/Turabian Style

Madjid Tavana; Akram Shaabani; Francisco Javier Santos-Arteaga; Iman Raeesi Vanani. 2020. "A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics." Energies 13, no. 15: 3947.

Conference paper
Published: 22 January 2020 in Advances in Intelligent Systems and Computing
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The current paper presents a heuristic evaluation mechanism describing the online search behavior of decision makers (DMs) as determined by the credibility of the rankings displayed by search engines. We formalize the incentives of DMs to observe and evaluate alternatives through a pairwise comparison function that accounts for both the ranking positions displayed and the credibility of the search engine. The resulting evaluation framework is implemented to analyze the effects that ranking credibility has on the online search behavior of DMs. In particular, we compare the cumulative frequencies derived from the implementation of the pairwise heuristic evaluation mechanism with the average traffic shares of the different items ranked within a Google result page.

ACS Style

Debora Di Caprio; Francisco J. Santos-Arteaga. A Novel Heuristic Mechanism to Formalize Online Behavior Through Search Engine Credibility. Advances in Intelligent Systems and Computing 2020, 235 -240.

AMA Style

Debora Di Caprio, Francisco J. Santos-Arteaga. A Novel Heuristic Mechanism to Formalize Online Behavior Through Search Engine Credibility. Advances in Intelligent Systems and Computing. 2020; ():235-240.

Chicago/Turabian Style

Debora Di Caprio; Francisco J. Santos-Arteaga. 2020. "A Novel Heuristic Mechanism to Formalize Online Behavior Through Search Engine Credibility." Advances in Intelligent Systems and Computing , no. : 235-240.

Journal article
Published: 01 January 2020 in International Journal of Strategic Decision Sciences
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The following article considers the results from two different studies, a European one involving over 20,000 respondents and an American one closing on 1,000, to illustrate how online platforms such as Facebook and Google can be defined as regrettable necessities. We define regrettable necessities as those whose consumption provides a direct disutility to consumers. That is, other than the standard utility derived from the access to a given service, a direct disutility in terms of privacy losses and preference manipulation results from their use. In addition, users acknowledge this fact and are aware of the disutility suffered, though not necessarily of its intensity, highlighting the fundamental strategic role played by these platforms in current voting environments.

ACS Style

Pietro Frigato; Francisco J. Santos-Arteaga. Facebook and Google as Regrettable Necessities. International Journal of Strategic Decision Sciences 2020, 11, 21 -34.

AMA Style

Pietro Frigato, Francisco J. Santos-Arteaga. Facebook and Google as Regrettable Necessities. International Journal of Strategic Decision Sciences. 2020; 11 (1):21-34.

Chicago/Turabian Style

Pietro Frigato; Francisco J. Santos-Arteaga. 2020. "Facebook and Google as Regrettable Necessities." International Journal of Strategic Decision Sciences 11, no. 1: 21-34.

Journal article
Published: 01 January 2020 in IZA Journal of Development and Migration
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This article seeks to explain the contradiction between the promises of welfare gains derived from the economic models recommending the removal of immigration restrictions and the realities experienced by countries attempting to apply restrictions to immigration flows. A formal model is built in which the strategic reaction of countries considers not only the benefits derived from migration but also the (economic and non-economic) costs that migration can generate in the host country. Strategic reactions drive what may be called the “paradox of adverse interest”: the fewer potential gains associated with liberalization of migration, the easier it becomes for nations to reach an unrestrictive agreement. The existence of two asymmetries (between the bargaining power of receiving and sending countries, and between the private nature of most of migration’s benefits and the social nature of its main costs) can hinder the agreement when the countries involved exhibit a high wage differential. Results suggest that permissive international agreements on migration are easier to reach in regional contexts, among countries with proximate economic conditions and levels of income.

ACS Style

José Antonio Alonso; Francisco Javier Santos Arteaga. International migratory agreements: the paradox of adverse interest. IZA Journal of Development and Migration 2020, 11, 1 .

AMA Style

José Antonio Alonso, Francisco Javier Santos Arteaga. International migratory agreements: the paradox of adverse interest. IZA Journal of Development and Migration. 2020; 11 (1):1.

Chicago/Turabian Style

José Antonio Alonso; Francisco Javier Santos Arteaga. 2020. "International migratory agreements: the paradox of adverse interest." IZA Journal of Development and Migration 11, no. 1: 1.

Journal article
Published: 27 July 2019 in Expert Systems with Applications
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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.

ACS Style

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 Style

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.

Chicago/Turabian Style

Francisco 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.

Journal article
Published: 17 June 2019 in Journal of the Operational Research Society
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ACS Style

Hiwa Farughi; Madjid Tavana; Sobhan Mostafayi; Francisco Javier Santos Arteaga. A novel optimization model for designing compact, balanced, and contiguous healthcare districts. Journal of the Operational Research Society 2019, 71, 1740 -1759.

AMA Style

Hiwa Farughi, Madjid Tavana, Sobhan Mostafayi, Francisco Javier Santos Arteaga. A novel optimization model for designing compact, balanced, and contiguous healthcare districts. Journal of the Operational Research Society. 2019; 71 (11):1740-1759.

Chicago/Turabian Style

Hiwa Farughi; Madjid Tavana; Sobhan Mostafayi; Francisco Javier Santos Arteaga. 2019. "A novel optimization model for designing compact, balanced, and contiguous healthcare districts." Journal of the Operational Research Society 71, no. 11: 1740-1759.

Journal article
Published: 28 May 2019 in Computers & Industrial Engineering
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We define a fuzzy multi-objective multi-period network DEA model customized to evaluate the dynamic performance of oil refineries in the presence of undesirable outputs. In particular, we use a standard fuzzy operator to define the efficiency levels so as to integrate multiple objectives and periods of time within a unique maximization framework. Managers and decision makers are provided with a model characterized by its operational simplicity that allows for the straightforward implementation of standard spreadsheet software. The model is applied to a real-life case study, where the capacity of refineries to optimize their performance through the refining process is analyzed together with the introduction of value-added products that preserve and enhance the environmental dimensions of the refining process. The inclusion of a real-life case study aims at illustrating the efficacy and applicability of the proposed method relative to those of more conventional models. Moreover, the range of the time period covered allows us to analyze the evolution of efficiency beyond the standard two-period Malmquist framework generally considered in the literature dealing with the behavior of refineries.

ACS Style

Madjid Tavana; Kaveh Khalili-Damghani; Francisco J. Santos Arteaga; Amineh Hosseini. A fuzzy multi-objective multi-period network DEA model for efficiency measurement in oil refineries. Computers & Industrial Engineering 2019, 135, 143 -155.

AMA Style

Madjid Tavana, Kaveh Khalili-Damghani, Francisco J. Santos Arteaga, Amineh Hosseini. A fuzzy multi-objective multi-period network DEA model for efficiency measurement in oil refineries. Computers & Industrial Engineering. 2019; 135 ():143-155.

Chicago/Turabian Style

Madjid Tavana; Kaveh Khalili-Damghani; Francisco J. Santos Arteaga; Amineh Hosseini. 2019. "A fuzzy multi-objective multi-period network DEA model for efficiency measurement in oil refineries." Computers & Industrial Engineering 135, no. : 143-155.

Monograph
Published: 05 April 2019 in The Dark Places of Business Enterprise
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ACS Style

Pietro Frigato; Francisco J. Santos-Arteaga. The Dark Places of Business Enterprise. The Dark Places of Business Enterprise 2019, 1 .

AMA Style

Pietro Frigato, Francisco J. Santos-Arteaga. The Dark Places of Business Enterprise. The Dark Places of Business Enterprise. 2019; ():1.

Chicago/Turabian Style

Pietro Frigato; Francisco J. Santos-Arteaga. 2019. "The Dark Places of Business Enterprise." The Dark Places of Business Enterprise , no. : 1.

Journal article
Published: 04 April 2019 in Computers & Industrial Engineering
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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.

ACS Style

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 Style

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.

Chicago/Turabian Style

Debora 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.

Journal article
Published: 14 March 2019 in Operations Research Perspectives
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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.

ACS Style

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 Style

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.

Chicago/Turabian Style

Debora 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.

Journal article
Published: 15 November 2018 in Journal of Wine Economics
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We empirically examine the strategic importance of the choices of the first person ordering, that is, the leader, for the decisions made and money spent by other commensals at a restaurant table. Our aim is to study the similarity of orders—in terms of dishes, drinks, and prices—among the table leader and the other commensals. The empirical results reveal that table leaders, both male and female, exert a considerable influence on the choices made by other diners. We analyze the differences arising when males and females act as table leaders. (JEL Classifications: D12, D91)

ACS Style

Guenter Schamel; Francisco Javier Santos-Arteaga. Leader Effects and Gender Differences in Sequential Restaurant Ordering Environments. Journal of Wine Economics 2018, 13, 461 -468.

AMA Style

Guenter Schamel, Francisco Javier Santos-Arteaga. Leader Effects and Gender Differences in Sequential Restaurant Ordering Environments. Journal of Wine Economics. 2018; 13 (4):461-468.

Chicago/Turabian Style

Guenter Schamel; Francisco Javier Santos-Arteaga. 2018. "Leader Effects and Gender Differences in Sequential Restaurant Ordering Environments." Journal of Wine Economics 13, no. 4: 461-468.

Original article
Published: 22 October 2018 in Expert Systems
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The quality of its players is one of the most significant features determining the failure or success of a sports team. The wide array of factors contributing to the performance of the players together with the inherent financial limitations of the clubs have transformed the selection of players into a complex problem. The current paper presents an integrated approach that combines multiple‐criteria decision‐making analysis and mathematical programming to support the decision maker through the building process of a soccer team. First, the fuzzy analytic network process is applied to evaluate the significance of the different performance criteria for each position in the field. The score attained by the different players in each potential position is computed using PROMETHEE II. A biobjective integer programming model has been designed to evaluate the transfer status of the players. Finally, data envelopment analysis is used to identify the most efficient Pareto solution determining the status of each player. In order to demonstrate the applicability of the proposed approach, the position in the field and transfer status of 60 players being considered by a real soccer team have been determined.

ACS Style

Mohammad Mahdi Nasiri; Mojtaba Ranjbar; Madjid Tavana; Francisco J. Santos Arteaga; Reza Yazdanparast. A novel hybrid method for selecting soccer players during the transfer season. Expert Systems 2018, 36, e12342 .

AMA Style

Mohammad Mahdi Nasiri, Mojtaba Ranjbar, Madjid Tavana, Francisco J. Santos Arteaga, Reza Yazdanparast. A novel hybrid method for selecting soccer players during the transfer season. Expert Systems. 2018; 36 (1):e12342.

Chicago/Turabian Style

Mohammad Mahdi Nasiri; Mojtaba Ranjbar; Madjid Tavana; Francisco J. Santos Arteaga; Reza Yazdanparast. 2018. "A novel hybrid method for selecting soccer players during the transfer season." Expert Systems 36, no. 1: e12342.

Journal article
Published: 12 September 2018 in European Journal of Operational Research
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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.

ACS Style

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 Style

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 (2):448-462.

Chicago/Turabian Style

Francisco 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.