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Selecting an agricultural technology package based on the flexible and interactive tradeoff method

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The aim of this paper is to solve an agricultural technology packages selection problem by considering multiple dimensions which influence a maize producer’s preferences. The decision-making process is aided by a new multicriteria method for eliciting scale constants in additive models: flexible and interactive tradeoff (FITradeoff). This method works with partial information, obtained from the decision maker (DM), and thus reduces the time that the DM has to spend on the process for eliciting his/her preferences as he/she may avoid answering difficult questions. The decision-making process makes use of a decision support system (DSS), in which the DM interactively gives preference statements in a structured manner. The DSS gives flexibility to the DM, in such way that he/she gives as much information as he/she is willing to. Graphical visualization is provided at each step in order to help the DM’s analyses. Throughout the description of an application, some insights are provided including a discussion of the advantages and features of the FITradeoff method.
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Annals of Operations Research (2022) 314:377–392
https://doi.org/10.1007/s10479-018-3020-y
S.I.: AGRICULTURE ANALYTICS, BIGDATA AND SUSTAINABLE
DEVELOPMENT
Selecting an agricultural technology package based
on the flexible and interactive tradeoff method
Pavel Anselmo Alvarez Carrillo1·Lucia Reis Peixoto Roselli2·
Eduarda Asfora Frej2·Adiel Teixeira de Almeida2
Published online: 22 August 2018
© Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
The aim of this paper is to solve an agricultural technology packages selection problem
by considering multiple dimensions which influence a maize producer’s preferences. The
decision-making process is aided by a new multicriteria method for eliciting scale constants in
additive models: flexible and interactive tradeoff (FITradeoff). This method works with partial
information, obtained from the decision maker (DM), and thus reduces the time that the DM
has to spend on the process for eliciting his/her preferences as he/she may avoid answering
difficult questions. The decision-making process makes use of a decision support system
(DSS), in which the DM interactively gives preference statements in a structured manner.
The DSS gives flexibility to the DM, in such way that he/she gives as much information as
he/she is willing to. Graphical visualization is provided at each step in order to help the DM’s
analyses. Throughout the description of an application, some insights are provided including
a discussion of the advantages and features of the FITradeoff method.
Keywords Multicriteria decision making ·Additive model ·Flexible and interactive
tradeoff ·Partial information
1 Introduction
Decision-making in the context of agricultural production concerns different elements
directly related to cultivating crops such as preparing the land, planting, and conducting
weed and pest control until the harvest is over. Convening for harvesting is closely related
to understanding the properties of a plant (seed variety) and the region in which the crop is
BEduarda Asfora Frej
eafrej@cdsid.org.br
1Department of Economic and Management Sciences, Universidad de Occidente, Culiacan, Mexico
2CDSID - Center for Decision Systems and Information Development, Universidade Federal de
Pernambuco, Av. Acadêmico Hélio Ramos, s/n Cidade Universitária, Recife, PE CEP 50.740-530,
Brazil
123
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... The FITradeoff method can be used in choice problematics (de Almeida et al., 2016), in ranking problematics (Frej et al., 2019), in sorting problematics (Kang et al., 2020), and in portfolio problematics . Thus, the FITradeoff presents a wide variety of real-world applications, such as: energy and environmental applications (de Macedo et al., 2018;Fossile et al., 2020;Frej et al., 2021;Kang et al., 2018;Monte & Morais, 2019), healthcare applications (Dell'Ovo et al., 2017;Camilo et al., 2020), applications regarding public security (Camara e Silva et al., 2019), application in industry context (Frej et al., 2019;Lima et al., 2017;Pergher et al., 2020;Santos et al., 2020;Silva et al., 2019), agricultural context (Carrillo et al., 2018). ...
... Based on the Alpha-Theta Diagram, it is possible to conclude that most of the visualizations have been evaluated with the adequate patterns of behavioral (Diligence or Involvement). Therefore, this study reinforces the holistic evaluation during the FITradeoff decision-making process, which already have been conducted in previous studies (Carrillo et al., 2018;Frej et al., 2017;Pergher et al., 2020;Santos et al., 2020). ...
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Article
This study has been proposed to improve the holistic evaluation in the FITradeoff decision-making process. The study generates recommendations that can support the analyst during the advising process with the decision-maker. A neuroscience tool is applied to conduct a behavioral study. Using an electroencephalogram, the Alpha and Theta activities have been monitored from a sample of twenty-seven management engineering students. The neuroscience experiment is composed of graphical and tabular visualizations. These visualizations represent multi-criteria decision problems, and they are presented in the holistic evaluation phase of the FITradeoff method. As result, the Alpha-Theta Diagram has been obtained, based on frontal Theta and parietal Alpha activities. The Alpha-Theta Diagram is a tool proposed to be applied during the holistic evaluation phase, with the visualizations. Thus, based on the Alpha-Theta Diagram, the visualizations in which the decision-maker presents the adequate pattern of behavioral, with high cognitive effort and high engagement are revealed. Statistical tests show that in most of the visualizations there have been significant cognitive effort and/or engagement of participants. Thus, based on this diagram, recommendations can consider the visualizations that use the adequate patterns of behavioral. As conclusion, the result reinforces which visualization should be used for holistic evaluation during the FITradeoff decision process. For future studies, rigorous investigations should be performed with EEG responses, specially to develop the Alpha-Theta Diagram for participants.
... The FITradeoff method has been made use of in a wide range of practical applications. Thus, it was used in medical applications (Dell'Ovo et al., 2020;Camilo et al. 2020), in energy applications (Fossile et al., 2020;de Macedo, de Miranda-Mota and Sola, 2018;Kang, Frej and de Almeida, 2018), in environmental applications (Monte and Morais, 2019;Carrillo et al., 2018), in a security application (Camara e Silva et al., 2019), and in industry applications (Frej, de Almeida and Costa, 2017;Santos et al., 2020;Pergher et al., 2020; Silva, Costa and Frej, de Almeida and Costa, 2019;Lima, Viegas and Costa, 2017;de Gusmão and Pereira Medeiros, 2016). In order to test the performance of the FITradeoff method, Mendes et al. (2020) performed simulation studies considering several scenarios, including different number of criteria and alternatives. ...
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This paper presents a practical case involving a shopping mall location problem in the northeast countryside of Brazil. In this problem, conflicting objectives have been expressed in terms of seven criteria. Then, ten cities of the northeastern countryside have been selected to compose the space of actions. The problem plays a special role since Brazil is a big country that requires investments in the countryside. Thus, the shopping mall aims to stimulate economic growth in the respective region. In the study, this multi-objective problem is solved using the FITradeoff method. In FITradeoff, the combination of the paradigms of holistic evaluation and elicitation by decomposition in preference modeling are well explored, bringing different perspectives for the decision-maker during the decision process.
... Several applications using the FITradeoff Method, and consequently it DSS, are already present in the literature. Carrillo et al. (2018) used the method to select better technologies for the agricultural sector. Monte and Morais (2019) used the method to support water management. ...
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The technology can support multi-criteria decision-making processes, allowing managers to identify efficient solutions to complex problems in a structured and rational way. Specially, in time of crises, the use of Decision Support System (DSS) is useful since these situations demand greater accuracy in the decision-making process. Therefore, this study shows the usefulness of the Decision Support System constructed for the FITradeoff method in a practical context involving a decision-making in time of crisis. In special, in this study, the applicability of the FITradeoff DSS is discussed to solve an important problem involving a Brazilian Company. The FITradeoff DSS was employed for a compliance-program problem, in which a company sought to improve its performance in relation to the program. This problem is particularly significant in Brazil where the search for compliance programs has been increasing since the adoption of the anticorruption law. Thus, twenty-eight alternatives were created, and these alternatives were evaluated against five criteria. As a result, most of the alternatives in the top of the ranking are related to Internal Communication aspect. Hence, the DM considered that these alternatives are sufficient to direct the efforts to execute the Compliance Program, and in special this theme can be the focus in this company. Furthermore, in view of recurring crises around the world, companies must identify ways to ensure their internal processes support the sustainability of their business. For decision making in times of crisis, the DSS of the FITradeoff method is an effective tool allowing decision makers to handle complex decisions.
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Chapter
It has been claimed in the literature that decision-making methods have not been modulated (transformed) by results obtained in behavioral studies as much as has been expected and that further modulation would be an important advancement in decision-making. This paper summarizes the modulation provided by the Flexible and Interactive Tradeoff (FITradeoff) method from behavioral studies performed using neuroscience tools. Modulations of the FITradeoff method have been conducted in two ways: modulations in the preference modelling process and modulations in the FITradeoff Decision Support System (DSS). For modulation in FITradeoff preference modeling, several recommendations were provided to support analysts during their advising process with decision-makers. For modulation in the FITradeoff DSS, several improvements were implemented in the design of the DSS. The modulation of the FITradeoff method was supported by neuroscience experiments. These experiments investigated decision-makers’ (DMs) behavior when they interacted with a holistic evaluation and elicitation by decomposition in the FITradeoff method. The modulation of the FITradeoff method promoted the inclusion of some features through the combination of the two paradigms of preference modeling, completely transforming the decision-making process, and its DSS.
Chapter
The study demonstrates the flexible functioning of the FITradeoff method that integrates the Holistic Evaluation with the Elicitation by Decomposition. For that purpose, the new features of the FITradeoff method in which integrates the two paradigms of preference modeling have been explored to solve a real multi-criteria decision problem. In this paper, a truck acquisition problem, at a midsize carrier faced with an uncertain and turbulent scenario due to the Coronavirus pandemic, was solved using the FITradeoff method. In this problem, seven criteria were considered to represent the Decision-Maker objectives. Also, six trucks (alternatives) have been examined by the Decision-Maker (Financial Director). The FITradeoff DSS supported the company as to obtain, through the combination of Holistic Evaluation and Elicitation by Decomposition, a ranking of all the trucks based on the preferences expressed during the decision process to ensure lower costs and higher profits in the long run, also guaranteeing a quicker (more efficient) resolution of the problem.KeywordsFITradeoff methodElicitation processHolistic evaluationMulti-criteria decision making/Aiding (MCDM/A)Truck acquisition
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