An intuitionistic fuzzy entropy-based gained and lost dominance score decision-making method to select and assess sustainable supplier selection

Sustainable supplier selection (SSS) is recognized as a prime aim in supply chain because of its impression on profitability, adorability, and agility of the organization. This work introduces a multi-phase intuitionistic fuzzy preference-based model with which decision experts are authorized to choose the suitable supplier using the sustainability "triple bottom line (TBL)" attributes. To solve this issue, an intuitionistic fuzzy gained and lost dominance score (IF-GLDS) approach is proposed using the developed IF-entropy. To make better use of experts' knowledge and fully represent the uncertain information, the evaluations of SSS are characterized in the form of intuitionistic fuzzy set (IFS). To better distinguish fuzziness of IFSs, new entropy for assessing criteria weights is proposed with the help of an improved score function. By considering the developed entropy and improved score function, a weight-determining process for considered criterion is presented. A case study concerning the iron and steel industry in India for assessing and ranking the SSS is taken to demonstrate the practicability of the developed model. The efficacy of the developed model is certified with the comparison by diverse extant models

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

Application of Interval Fuzzy Logic in Selecting a Sustainable Supplier on the Example of Agricultural Production

The selection of sustainable suppliers (SSS) is the first step in applying a sustainable supply chain and sustainable production. Therefore, it is necessary to select the supplier that best meets the set sustainability criteria. However, the selection of suppliers cannot be done by applying symmetric information, because the company does not have complete information, so asymmetric information should be used when selecting suppliers. Since the SSS applies three main sustainability criteria, environmental, social, and economic criteria, this decision-making problem is solved by applying multi-criteria decision-making (MCDM). In order to solve the SSS for the needs of agricultural production, interval fuzzy logic was applied in this research, and six suppliers with whom agricultural pharmacies in Semberija work were taken into consideration. The application of interval fuzzy logic was performed using the methods PIPRECIA (Pivot pairwise relative criteria importance assessment) and MABAC (Multi-Attributive Border Approximation Area Comparison). Using the PIPRECIA method, the weights of criteria and sub-criteria were determined. Results of this method showed that the most significant are economic criteria, followed by the social criteria. The ecological criteria are the least important. The supplier ranking was performed using the MABAC method. The results showed that supplier A4 best meets the sustainability criteria, while supplier A6 is the worst. These results were confirmed using other MCDM methods, followed by the sensitivity analysis. According to the attained results, agricultural producers from Semberija should buy the most products from suppliers A4, in order to better apply sustainability in production. This paper showed how to decision make when there is asymmetric information about suppliers

Aplicação de métodos de tomada de decisão multicritério para gestão do ciclo de vida: sustentabilidade na cadeia produtiva da carne bovina brasileira

Sistemas de produção agrícola, como os destinados à bovinocultura de corte, são reconhecidos mundialmente como importantes contribuintes de impactos ambientais, principalmente para o potencial de mudanças climáticas. O aumento da demanda de carne bovina nas últimas décadas tem gerado mais atenção sobre o tema, que se reflete na preocupação do consumidor em obter informações sobre os impactos associados ao produto. Neste estudo, avaliou-se a sustentabilidade de possíveis ações de melhoria para minimizar a pegada de carbono da cadeia produtiva de carne bovina brasileira para exportação, utilizando abordagens estruturadas sobre o pensamento do ciclo de vida, combinadas com métodos de tomada de decisão multicritério e ponderação probabilística. A pegada de carbono das exportações de carne bovina brasileira foi mensurada utilizando Avaliação do Ciclo de Vida e a partir disso identificou-se a etapa da cadeia mais representativa em termos de contribuição para o impacto. As emissões por quilo de carne bovina desossada variaram entre 33,35 a 33,58 kg de CO2-Eq. Os portos de destino influenciaram em menos de 1% nos resultados, pois a fase de produção animal é a mais impactante, contribuindo com 98% dos impactos associados ao produto. Por meio de uma abordagem combinada dos métodos multicritérios TOPSIS e lógica fuzzy foram identificadas possíveis ações de melhoria no desempenho ambiental da fase de produção animal, a partir da ótica dos stakeholders: fertilização das pastagens, suplementação proteinada e integração lavoura-pecuária. Utilizou-se uma combinação da abordagem de Avaliação Sustentável do Ciclo de Vida com modelos multicritério VIKOR e lógica fuzzy para, além de avaliar a eficácia das alternativas na redução dos impactos associados a mudanças climáticas, analisa-las em relação a outros indicadores de critérios ambiental, econômico e social. Comparando com o sistema referência, a rotação de lavoura-pecuária obteve a melhor posição na hierarquização do desempenho entre todos os critérios avaliados. Especificamente para a pegada de carbono, a substituição do sistema de referência pela rotação lavoura-pecuária possibilitaria reduzir aproximadamente 7,7 kg de CO2-Eq., ou seja, 23% do total da pegada de carbono atribuída ao produto, além de combinar a melhor oportunidade de melhoria no desempenho dos demais indicadores avaliados. Visando facilitar o processo de ponderação e integração de indicadores de diferentes critérios para geração de uma pontuação única de sustentabilidade, neste estudo propôs-se um modelo matemático de ponderação a partir da teoria da probabilidade. O modelo proposto demostrou-se uma alternativa viável para a redução da incerteza e risco relatados por pesquisadores sobre a integração de métodos multicritérios com a Avaliação Sustentável do Ciclo de Vida, isentando o julgamento humano do processo de ponderação e possibilitando mensurar a probabilidade de determinada hierarquização de alternativas ocorrer. Além disso, combinado com o método VIKOR e seus critérios de desvios para determinação da melhor alternativa, a ponderação probabilística permitiu classificar se a melhor alternativa possibilitava uma solução ideal ou uma solução estável para o problema. Com base nos resultados desta pesquisa, demonstrou-se que existem ações que, além de minimizar os impactos ambientais associados às exportações de carne bovina brasileira em termos de pegada de carbono, também contribuem significativamente para o aumento da sustentabilidade da produção animal nos aspectos econômico e social.Agricultural systems like beef cattle production are recognized worldwide as important cause of many environmental impacts, especially for the potential of climate change. The increase in beef demand in the last decades has generated even more attention on the subject, which is reflected in the consumer's concern to obtain information on the impacts associated with the product. In this study, it was evaluated the sustainability of possible improvement actions to minimize the carbon footprint of the export chain of Brazilian beef, using structured approaches to life-cycle thinking, combined with multicriteria decision-making methods and weighting probabilistic analysis. The carbon footprint of Brazilian beef exports was measured using the environmental Life Cycle Assessment and the most representative chain stage was identified in terms of contribution to the impact. Emissions per kilogram of product ranged from 33.35 to 33.58 kg of CO2-Eq. The variation of destination ports influenced less than 1% of the results, since the animal production phase is the most impacting, contributing in more than 98% of the impacts associated to the product. Through a combined approach of the TOPSIS multi-criteria methods and fuzzy logic, it was possible to identify possible actions to improve the environmental performance of the animal production phase, from the perspective of the stakeholders: pasture fertilization, protein supplementation and crop-livestock integration. A combination of the Sustainable Life Cycle Assessment approach with VIKOR multicriteria model and fuzzy logic was applied to evaluate the effectiveness of the alternatives in reducing the impacts associated with climate change and to analyze them in comparison to other environmental criteria indicators, besides economic and social ones. Comparing with the reference system, the crop-livestock rotation obtained the best position in the hierarchy of performance among all evaluated criteria. Specifically for the carbon footprint, the replacement of the reference system by crop-livestock rotation would make it possible to reduce approximately 7.7 kg of CO2-Eq., or 23% of the total carbon footprint attributed to the product, in addition to combining opportunity to improve the performance of the other indicators evaluated. Aiming to facilitate the process of weighting and integration of indicators of different criteria to generate a single sustainability score, in this study it was proposed a mathematical model of weighting from the theory of probability. The proposed model demonstrated a viable alternative for the reduction of uncertainty and risk reported by researchers on the integration of multicriteria methods with the Sustainable Life Cycle Assessment, exempting human judgment from the weighting process and making it possible to measure the probability of a certain hierarchy of alternatives occur. In addition, combined with the VIKOR method and its deviation criteria to determine the best alternative, probabilistic weighting allowed to classify whether the best alternative provided an optimal solution or a stable solution to the problem. Based on the results of this research, it has been demonstrated that there are actions that, in addition to minimizing the impacts associated with Brazilian beef exports in terms of carbon footprint, also contribute significantly to increasing the sustainability of animal production in economic and social aspects

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

Application of Industry 4.0 in the Procurement Processes of Supply Chains: A Systematic Literature Review

The fourth industrial revolution has significantly changed the traditional way of managing supply chains. The applications of Industry 4.0 (I4.0) technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) in different processes of supply chains have assisted companies to improve their performance. Procurement can be considered a critical process in supply chain management since it can provide novel opportunities for supply chains to improve their efficiency and effectiveness. However, I4.0 applications can be costly and may not be reasonably affordable. Therefore, the benefits of implementing these technologies should be clarified for procurement managers before investing in the digitalization of the procurement process. Despite the importance of this issue, few papers have attempted to address the effects of I4.0 technologies and smart systems in procurement. To fill this gap, a Systematic Literature Review (SLR) on the applications of I4.0 technologies in procurement has been used in this study. By reviewing 70 papers through appropriate keywords, a conceptual framework is developed to classify different value propositions provided by the different applications of I4.0 technologies in procurement processes. Results reveal nine value propositions that can provide a better understanding for the procurement department to analyze the benefits of implementing the related I4.0 technologies in different activities. Finally, findings and future study opportunities are concluded

Desenvolvimento de método multicritério linguístico para avaliação de desempenho e priorização de recursos

Performance indicators are information collected at regular intervals to track the performance of organizations. With scarce resources and a high number of performance indicators, it is difficult to improve all organizational aspects simultaneously. At the same time, several types of indicators have a subjective character with measurement expressed in words with present uncertainty. Management tools and multicriteria decision support methodologies (MCDM) have been used to evaluate the performance of organizations. However, there are limitations in traditional MCDM: independence of criteria and disregard for the collaborative environment. The main objective of this dissertation was to develop a linguistic multicriteria method for collaborative environments with performance evaluation based on subjective information aiming to prioritize resource allocation to generate greater impact on the organization. The proposed method was developed based on a systematic literature review and the adaptation of existing methodologies. It consists of assessing language performance, determining importance based on 2- Tuple Language Weight in determining language importance and capturing influence through DEMATEL 2-Tuple, all being operationalized in a 2-Tuple computational environment. The proposed method introduces the concept of 'Impact' which combines importance (perceived utility) and influence (causality) as different quantities acting on the same system or collaborative environment. The main steps of the method are Structuring, Evaluation, Processing, Result, and Revaluation. To verify the proposed method, the problem reported by Singh et al. (2018) with the contribution of data from Meksavang et al. (2019) referring to the same study, were adapted for application. As a result of the application, it was identified which priority Performance Indicators (PIs), with the highest potential impact, to develop a group of ecologically correct meat suppliers with economic viability, and it was observed that considering the comparative limitations, the suggestions of prioritization captured by the proposed method are in line with the method selection suggestions developed by Singh et al. (2018) and Meksavang et al. (2019) verifying that the steps developed by the proposed method are adequately structured and feasible.Indicadores de desempenho (IDs) são informações coletadas em intervalos regulares para acompanhar o desempenho de organizações. Com recursos escassos e um número elevado de IDs, torna-se difícil aperfeiçoar todos os aspectos organizacionais simultaneamente. Concomitantemente, diversos tipos de IDs têm caráter subjetivo com mensuração expressa em palavras com incerteza presente. Ferramentas da administração e metodologias multicritério de apoio à tomada de decisão (MCDM) têm sido utilizadas para avaliar o desempenho das organizações.Porém há limitações na MCDM tradicional: a independência dos critérios e a desconsideração ao ambiente colaborativo. O principal objetivo desta dissertação foi desenvolver um método multicritério linguístico para ambientes colaborativos com avaliação de desempenho a partir de informações subjetivas visando priorizar alocação de recursos para gerar maior impacto na organização. O método proposto foi desenvolvido com base em uma revisão sistemática de literatura e na adaptação de metodologias existentes. Consiste na avaliação de desempenho linguística, na determinação da importância com base no Peso Linguístico 2-Tuple na determinação da importância linguística e na captação da influência por meio do DEMATEL 2-Tuple, sendo todos operacionalizados em um ambiente computacional 2-Tuple. O método proposto introduz o conceito de „Impacto’ que combina a importância (utilidade percebida) e influência (causalidade) como grandezas diferentes atuantes em um mesmo sistema, ou ambiente colaborativo. As principais etapas do método são: Estruturação, Avaliação, Processamento, Resultado e Reavaliação. Para verificação do método proposto o problema relatado por Singh et al. (2018) com a contribuição dos dados do trabalho de Meksavang et al. (2019) referentes ao mesmo estudo, foram adaptados para aplicação. Como resultado da aplicação identificou-se quais os IDs prioritários, com maior impacto potencial, para desenvolver um grupo de fornecedores de gado ecologicamente corretos com viabilidade econômica, e observou-se que, consideradas as limitações comparativas, as sugestões de priorização captadas pelo método proposto estão alinhadas com as sugestões de seleção dos métodos elaborados por Singh et al. (2018) e Meksavang et al. (2019) verificando que os passos desenvolvidos pelo método proposto são adequadamente estruturados e exequíveis