Pub Date : 2023-01-06DOI: 10.1590/0103-6513.20220035
Mariana Arboleda-Florez, Carlos Castro-Zuluaga
Paper aims: Several concerns regarding the lack of interpretability of machine learning models obstruct the implementation of machine learning projects as part of the demand forecasting process. This paper presents a methodology to support the introduction of machine learning into the forecasting process of a traditional direct sales company by providing explanations for the otherwise obscure results. We also suggest incorporating human knowledge inside the machine learning pipeline as an essential part of capturing the business logic and integrating machine learning into the existing processes. Originality: Using explainable machine learning methods on real-life company data demonstrates that machine learning techniques are functional beyond the academy and can be introduced to everyday companies’ production. Research method: The project used real-world data from a company and followed a traditional machine learning pipeline to collect, preprocess, select and train a machine learning model, to conclude with the explanation of the model results through the implementation of SHAP Main findings: The results provided insights regarding the contribution of the features to the forecast. We analyzed individual predictions to understand the behavior of different variables, proving helpful when interpreting complex machine learning models. Implications for theory and practice: This study contributes to a discussion about adopting new technology and implementing machine learning models for demand forecasting. The methodology presented in this paper can be used to implement similar projects on interested companies.
{"title":"Interpreting direct sales’ demand forecasts using SHAP values","authors":"Mariana Arboleda-Florez, Carlos Castro-Zuluaga","doi":"10.1590/0103-6513.20220035","DOIUrl":"https://doi.org/10.1590/0103-6513.20220035","url":null,"abstract":"Paper aims: Several concerns regarding the lack of interpretability of machine learning models obstruct the implementation of machine learning projects as part of the demand forecasting process. This paper presents a methodology to support the introduction of machine learning into the forecasting process of a traditional direct sales company by providing explanations for the otherwise obscure results. We also suggest incorporating human knowledge inside the machine learning pipeline as an essential part of capturing the business logic and integrating machine learning into the existing processes. Originality: Using explainable machine learning methods on real-life company data demonstrates that machine learning techniques are functional beyond the academy and can be introduced to everyday companies’ production. Research method: The project used real-world data from a company and followed a traditional machine learning pipeline to collect, preprocess, select and train a machine learning model, to conclude with the explanation of the model results through the implementation of SHAP Main findings: The results provided insights regarding the contribution of the features to the forecast. We analyzed individual predictions to understand the behavior of different variables, proving helpful when interpreting complex machine learning models. Implications for theory and practice: This study contributes to a discussion about adopting new technology and implementing machine learning models for demand forecasting. The methodology presented in this paper can be used to implement similar projects on interested companies.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67578353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210065
J. Martins, M. I. Morandi, D. P. Lacerda, Barbara Pisoni Bender Andrade
Paper aims: The present study aims to identify the limitations of the artifacts used in the decision-making process in the adoption of energy efficiency measures in productive systems, using non-intensive energy companies as a delimitation. Originality: Identifies authors and connections, the relationships between them and how these interactions contribute to the advancement of knowledge on the subject. Regarding energy efficiency, studies show that the real investment in initiatives in the industrial sector is below the full potential and that the artifacts used in the decision-making process have severe limitations when used in a complex and dynamic context. Research method: In this paper a systematic literature review was conducted from the Literature-Grounded Theory. Additionally, social network analysis was used. Main findings: It concludes that the approaches are limited to technical and financial factors and does not consider a systemic and dynamic understanding of different internal and external variables to the organization. Implications for theory and practice: The contribution of this study is that it identifies the initiatives that help in the process of decision-making for the adoption of energy efficiency measures in productive systems. Specifically, the focus of this study is on non-intensive energy companies. Scientific articles published in the main databases of management were selected.
{"title":"Energy efficiency decision-making in non-energy intensive industries: content and social network analysis","authors":"J. Martins, M. I. Morandi, D. P. Lacerda, Barbara Pisoni Bender Andrade","doi":"10.1590/0103-6513.20210065","DOIUrl":"https://doi.org/10.1590/0103-6513.20210065","url":null,"abstract":"Paper aims: The present study aims to identify the limitations of the artifacts used in the decision-making process in the adoption of energy efficiency measures in productive systems, using non-intensive energy companies as a delimitation. Originality: Identifies authors and connections, the relationships between them and how these interactions contribute to the advancement of knowledge on the subject. Regarding energy efficiency, studies show that the real investment in initiatives in the industrial sector is below the full potential and that the artifacts used in the decision-making process have severe limitations when used in a complex and dynamic context. Research method: In this paper a systematic literature review was conducted from the Literature-Grounded Theory. Additionally, social network analysis was used. Main findings: It concludes that the approaches are limited to technical and financial factors and does not consider a systemic and dynamic understanding of different internal and external variables to the organization. Implications for theory and practice: The contribution of this study is that it identifies the initiatives that help in the process of decision-making for the adoption of energy efficiency measures in productive systems. Specifically, the focus of this study is on non-intensive energy companies. Scientific articles published in the main databases of management were selected.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67576641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210055
Diana C. Tascón, G. Mejía, D. Rojas-Sánchez
Paper aims: To provide guidelines on current state of the literature on aspects related to the implementation of Industry 4.0 (I4.0) for operations flexibility in emerging economies, and derived from this, propose a conceptual framework for the analysis of the main topics studied. Originality: Based on previous literature reviews on related topics (I4.0 and flexibility), we recognized an opportunity to focus on developing countries which until now has not been documented. Research method: We carried out a systematic review of the literature together with a topic cluster analysis. Main findings: The study revealed that there is a perceived consensus on how Industry 4.0 technologies can impact flexibility in emerging countries. Cloud computing is by far the most adopted technology despite the fact that there is a wide concern about security issues. The use of other technologies and their impact appears to be incipient. Implications for theory and practice: The study presented here can be used as a starting point for new directions of research in terms of adoption of these technologies and new applications developed and/or customized to the realities of emerging countries.
{"title":"Flexibility of operations in developing countries with Industry 4.0. A systematic review of literature","authors":"Diana C. Tascón, G. Mejía, D. Rojas-Sánchez","doi":"10.1590/0103-6513.20210055","DOIUrl":"https://doi.org/10.1590/0103-6513.20210055","url":null,"abstract":"Paper aims: To provide guidelines on current state of the literature on aspects related to the implementation of Industry 4.0 (I4.0) for operations flexibility in emerging economies, and derived from this, propose a conceptual framework for the analysis of the main topics studied. Originality: Based on previous literature reviews on related topics (I4.0 and flexibility), we recognized an opportunity to focus on developing countries which until now has not been documented. Research method: We carried out a systematic review of the literature together with a topic cluster analysis. Main findings: The study revealed that there is a perceived consensus on how Industry 4.0 technologies can impact flexibility in emerging countries. Cloud computing is by far the most adopted technology despite the fact that there is a wide concern about security issues. The use of other technologies and their impact appears to be incipient. Implications for theory and practice: The study presented here can be used as a starting point for new directions of research in terms of adoption of these technologies and new applications developed and/or customized to the realities of emerging countries.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67576685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210073
A. Anis, R. Islam, N. I. Hafit
Paper aims: Several Barriers impede the robust effectiveness of the supply-chain management implementation for the Malaysian automotive industry. The purpose of the present work is to identify these Barriers and prioritize them. Originality: Originality of the present work lies in identifying the Barriers, putting them into categories and subsequently prioritize them by applying a scientific method such as Analytic Hierarchy Process (AHP). Research Research method: This study has identified five main categories of Barriers through literature reviews. Fourteen practitioners who are involved with the automotive industry helped prioritise those Barriers by applying the AHP. Main Main findings: Five main categories of Barriers are found to be technological, organisational, individual, strategic, and cultural barriers. Organisational barrier is the most critical barrier followed by technological and strategic barriers. Implications for theory and practice: This research provides important feedback to the automotive company managers to take appropriate measures to minimise negative impacts of the barriers identified.
{"title":"Prioritisation of barriers for supply chain management implementation in the Malaysian automotive industry","authors":"A. Anis, R. Islam, N. I. Hafit","doi":"10.1590/0103-6513.20210073","DOIUrl":"https://doi.org/10.1590/0103-6513.20210073","url":null,"abstract":"Paper aims: Several Barriers impede the robust effectiveness of the supply-chain management implementation for the Malaysian automotive industry. The purpose of the present work is to identify these Barriers and prioritize them. Originality: Originality of the present work lies in identifying the Barriers, putting them into categories and subsequently prioritize them by applying a scientific method such as Analytic Hierarchy Process (AHP). Research Research method: This study has identified five main categories of Barriers through literature reviews. Fourteen practitioners who are involved with the automotive industry helped prioritise those Barriers by applying the AHP. Main Main findings: Five main categories of Barriers are found to be technological, organisational, individual, strategic, and cultural barriers. Organisational barrier is the most critical barrier followed by technological and strategic barriers. Implications for theory and practice: This research provides important feedback to the automotive company managers to take appropriate measures to minimise negative impacts of the barriers identified.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67576937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210111
Mary Fernanda de Sousa de Melo, R. Piao, Willerson Lucas Campos-Silva, Diogo Palheta Nery
Paper aims: This study aims to analyze the relationship between the corporate social responsibility (CSR) strategy and competitiveness, considering the moderating effect of the governance mode on CSR actions. Originality: This study sheds some light on a tendency towards the proactivity in terms of CSR of Brazilian Multinationals. They also present collaborative governance mode more frequently to conduct CSR actions. Research method: In order to reach the research objective, a survey research was carried out in 144 Brazilian Multinationals and SmartPLS was used to conduct partial least square-structural equation modeling analysis. Main findings: The results indicated that there is a positive relationship between CSR and competitiveness. Regarding the CSR governance mode, the adoption of different governance modes depending on the characteristics of the CSR action developed.
{"title":"Corporate social responsibility and competitiveness: a study of Brazilian multinationals","authors":"Mary Fernanda de Sousa de Melo, R. Piao, Willerson Lucas Campos-Silva, Diogo Palheta Nery","doi":"10.1590/0103-6513.20210111","DOIUrl":"https://doi.org/10.1590/0103-6513.20210111","url":null,"abstract":"Paper aims: This study aims to analyze the relationship between the corporate social responsibility (CSR) strategy and competitiveness, considering the moderating effect of the governance mode on CSR actions. Originality: This study sheds some light on a tendency towards the proactivity in terms of CSR of Brazilian Multinationals. They also present collaborative governance mode more frequently to conduct CSR actions. Research method: In order to reach the research objective, a survey research was carried out in 144 Brazilian Multinationals and SmartPLS was used to conduct partial least square-structural equation modeling analysis. Main findings: The results indicated that there is a positive relationship between CSR and competitiveness. Regarding the CSR governance mode, the adoption of different governance modes depending on the characteristics of the CSR action developed.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67577363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210097
Blanka Bártová, V. Bína, Lucie Váchová
Paper aims: This research aims to analyze the primary studies published in recent years focusing on defect detection or classification in manufacturing and extract information about frequently used data mining (DM) methods, their accuracy, strengths, and limitations. Originality: Industrial production is now undergoing a dynamic transformation in the context of Industry 4.0, where implementation of data mining is a frequently discussed topic, and such an overall summary is missing. Research method: In this study, the PRISMA-driven systematic literature review is combined with the approach defined by Kitchenham (2004). Main findings: The most frequently used data mining methods for defect detection are Bayesian network (BN) and Support vector machine (SVM). Besides previously mentioned methods, the Decision trees (DT) and Clustering are often used for defect classification. Neural Networks (NN) use is common for both defect detection and classification. DT, together with the Genetic algorithm (GA) and SVM, achieved the highest average accuracy. Recently, authors often combine different DM methods, and also methods for data dimensionality reduction are often used. Implications for theory and practice: This study contributes to the quality management literature by extending a summary of recently used DM methods for defect detection and classification. This summary can help researchers choose a suitable method and build models for achieving its research purpose.
{"title":"A PRISMA-driven systematic review of data mining methods used for defects detection and classification in the manufacturing industry","authors":"Blanka Bártová, V. Bína, Lucie Váchová","doi":"10.1590/0103-6513.20210097","DOIUrl":"https://doi.org/10.1590/0103-6513.20210097","url":null,"abstract":"Paper aims: This research aims to analyze the primary studies published in recent years focusing on defect detection or classification in manufacturing and extract information about frequently used data mining (DM) methods, their accuracy, strengths, and limitations. Originality: Industrial production is now undergoing a dynamic transformation in the context of Industry 4.0, where implementation of data mining is a frequently discussed topic, and such an overall summary is missing. Research method: In this study, the PRISMA-driven systematic literature review is combined with the approach defined by Kitchenham (2004). Main findings: The most frequently used data mining methods for defect detection are Bayesian network (BN) and Support vector machine (SVM). Besides previously mentioned methods, the Decision trees (DT) and Clustering are often used for defect classification. Neural Networks (NN) use is common for both defect detection and classification. DT, together with the Genetic algorithm (GA) and SVM, achieved the highest average accuracy. Recently, authors often combine different DM methods, and also methods for data dimensionality reduction are often used. Implications for theory and practice: This study contributes to the quality management literature by extending a summary of recently used DM methods for defect detection and classification. This summary can help researchers choose a suitable method and build models for achieving its research purpose.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67577388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210132
F. G. Camargo
Paper aims : the combination of the quality indices, a novel model called “Dynamic Growth Allocation Model (DGAM)”, Fuzzy Decision Making Theory (FDM), Analytical Hierarchy Process (AHP) and the Evolutive Particle Swarm Optimization (EPSO) is proposed. Originality : the multi-objective optimization (with uncertainty) of the Argentine energy transition is not sufficiently studied. This combined methodology in this problem was not published and it had good, relatively easy and fast results. Research method : the optimization indices (EROI, CO2, IC and RP), the methodology used (DGAM, FDM, AHP and EPSO) and its results are analyzed. Main findings : (i) the nuclear energy allowed the renewable transition; (ii) the fossil dismantling and the investment in biomass and wind are needed; (iii) the EROI depends on the good load factor, useful life and performance. Implications for theory and practice : It is sought a minimum Renewable Participation (RP) of 20% of Argentina with a sustainable energy matrix.
{"title":"Fuzzy multi-objective optimization of the energy transition towards renewable energies with a mixed methodology","authors":"F. G. Camargo","doi":"10.1590/0103-6513.20210132","DOIUrl":"https://doi.org/10.1590/0103-6513.20210132","url":null,"abstract":"Paper aims : the combination of the quality indices, a novel model called “Dynamic Growth Allocation Model (DGAM)”, Fuzzy Decision Making Theory (FDM), Analytical Hierarchy Process (AHP) and the Evolutive Particle Swarm Optimization (EPSO) is proposed. Originality : the multi-objective optimization (with uncertainty) of the Argentine energy transition is not sufficiently studied. This combined methodology in this problem was not published and it had good, relatively easy and fast results. Research method : the optimization indices (EROI, CO2, IC and RP), the methodology used (DGAM, FDM, AHP and EPSO) and its results are analyzed. Main findings : (i) the nuclear energy allowed the renewable transition; (ii) the fossil dismantling and the investment in biomass and wind are needed; (iii) the EROI depends on the good load factor, useful life and performance. Implications for theory and practice : It is sought a minimum Renewable Participation (RP) of 20% of Argentina with a sustainable energy matrix.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67577736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20220054
Ana Carolina de Oliveira, W. Silva, D. Morais
Paper aims : The aim of this study was to propose a hybrid approach to develop and prioritize the indicators which should be used to monitor the development of plastering supply chains while using lean manufacturing practices. Originality : This approach proposed the integration of a Balanced Scorecard (BSC) - a multi-perspective tool for performance evaluation and strategic planning, and FITradeoff for the ranking problematic – a multicriteria method that features a robust axiomatic structure and uses partial information. Research method : The results showed that the approach provided a set of indicators to assist the company’s manager to monitor and improve the company’s competitiveness and sustainability. Main findings : The results showed that the approach was able to provide a set of KPIs to assist the company’s manager to monitor and improve the plastering company management in terms of competitiveness and sustainability. Implications for theory and practice : The results allowed evaluation of important issues for the strategic, economic, and environmental stability in complex business environments.
{"title":"Developing and prioritizing lean key performance indicators for plastering supply chains","authors":"Ana Carolina de Oliveira, W. Silva, D. Morais","doi":"10.1590/0103-6513.20220054","DOIUrl":"https://doi.org/10.1590/0103-6513.20220054","url":null,"abstract":"Paper aims : The aim of this study was to propose a hybrid approach to develop and prioritize the indicators which should be used to monitor the development of plastering supply chains while using lean manufacturing practices. Originality : This approach proposed the integration of a Balanced Scorecard (BSC) - a multi-perspective tool for performance evaluation and strategic planning, and FITradeoff for the ranking problematic – a multicriteria method that features a robust axiomatic structure and uses partial information. Research method : The results showed that the approach provided a set of indicators to assist the company’s manager to monitor and improve the company’s competitiveness and sustainability. Main findings : The results showed that the approach was able to provide a set of KPIs to assist the company’s manager to monitor and improve the plastering company management in terms of competitiveness and sustainability. Implications for theory and practice : The results allowed evaluation of important issues for the strategic, economic, and environmental stability in complex business environments.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67578264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20220028
W. Quintero
{"title":"Digital competences of the industrial engineer in industry 4.0 a systematic vision","authors":"W. Quintero","doi":"10.1590/0103-6513.20220028","DOIUrl":"https://doi.org/10.1590/0103-6513.20220028","url":null,"abstract":"","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67578681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.1590/0103-6513.20210059
Ygor Logullo, Vinícius Bigogno-Costa, Amanda Cecília Simões da Silva, M. Belderrain
Paper Aims: This paper aims to develop an approach to support group decision making combining methods and tools to a holistic MCDA process. Originality : Authors have been using Value-Focused Thinking (VFT) for structuring problems with different MCDA methods, but there is a lack of a process that defines a clear transition from VFT to those methods. Here we propose a process to fill this gap. Research method : Rich Picture and VFT structure the problem and elicit objectives that become criteria within a decision hierarchy. Analytic Hierarchy Process (AHP) with ratings supports preference elicitation and sensitivity analysis in the judgment weights of decision-makers. Main findings : VFT is effective for eliciting the decision structure to AHP; using weight distribution of stakeholders may affect the results, and the multimethodology approach developed here can deal with group decision making. Implications for theory and practice : The approach developed is effective in complex environments (complex problems and multiple stakeholders) because it focuses on values and defines a process to bring those values into a multicriteria method. Furthermore, sensitivity analysis with the judgment weights of the different stakeholders may be useful in negotiation.
{"title":"A prioritization approach based on VFT and AHP for group decision making: a case study in the military operations","authors":"Ygor Logullo, Vinícius Bigogno-Costa, Amanda Cecília Simões da Silva, M. Belderrain","doi":"10.1590/0103-6513.20210059","DOIUrl":"https://doi.org/10.1590/0103-6513.20210059","url":null,"abstract":"Paper Aims: This paper aims to develop an approach to support group decision making combining methods and tools to a holistic MCDA process. Originality : Authors have been using Value-Focused Thinking (VFT) for structuring problems with different MCDA methods, but there is a lack of a process that defines a clear transition from VFT to those methods. Here we propose a process to fill this gap. Research method : Rich Picture and VFT structure the problem and elicit objectives that become criteria within a decision hierarchy. Analytic Hierarchy Process (AHP) with ratings supports preference elicitation and sensitivity analysis in the judgment weights of decision-makers. Main findings : VFT is effective for eliciting the decision structure to AHP; using weight distribution of stakeholders may affect the results, and the multimethodology approach developed here can deal with group decision making. Implications for theory and practice : The approach developed is effective in complex environments (complex problems and multiple stakeholders) because it focuses on values and defines a process to bring those values into a multicriteria method. Furthermore, sensitivity analysis with the judgment weights of the different stakeholders may be useful in negotiation.","PeriodicalId":34960,"journal":{"name":"Production","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67576489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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