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    The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage
    (Emerald, 2020-08-04)
    Purpose: This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach: In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based partial and general coverage of suppliers makes the number of orders of products more realistic. In this model, the weights of suppliers are determined by fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, as a multi-criteria decision analysis method, in the objective function. Also, the authors consider the parameters related to delays as triangular fuzzy numbers. Findings: A small-sized numerical example is provided to clearly show the proposed model. The exact epsilon constraint method is used to solve this given multi-objective combinatorial optimization problem. Subsequently, the sensitivity analysis is conducted to testify the proposed model. The obtained results demonstrate the validity of the proposed multiple objectives mixed integer mathematical programming model and the efficiency of the solution approach. Originality/value: In real-life situations, supplier selection parameters are uncertain and incomplete. Hence, the fuzzy set theory is used to tackle uncertainty. In this paper, a multi-objective supplier selection problem is formulated taking into consideration the coverage of suppliers and suppliers’ weights. Integrating coverage of suppliers to select and allocate the order to them can be mentioned as the main contribution of this study. The proposed model considers the delay from suppliers as fuzzy parameters.
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    A contribution of fuzzy logic to sustainable tourism through a case analysis in Brazil
    (IOS Press, 2020-09-08)
    Society is increasingly concerned about environmental, social and economic issues. According to the World Tourism Organization, over the past six decades, tourism has experienced a continuous expansion and diversification to become one of the fastest-growing economic sectors in the world. Furthermore, studies affirm the complexity of the tourism sector and the fact that sustainable development depends on various topics that are not correctly identified by managers and policymakers. For these reasons, this paper aims to reflect on the effects of tourism and to propose alternatives that can be sustainably managed. In terms of results, knowledge gaps have been identified and, through a case analysis in Brazil, the forgotten effects of tourism activity that can have an impact on sustainable development have been exposed. Also, an algorithm has been presented to manage uncertainty and facilitate decision-making.
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    Applying CBA to Decide the Best Excavation Method: Scenario During the Covid-19 Pandemic
    (Pontificia Universidad Católica del Perú. Facultad de Arte y Diseño, 2021)
    On January 30 of 2020, The World Health Organization declared the pandemic crisis as the first public emergency with international importance. Because of this, many building projects were paralyzed since then and the building industry experienced changes that have brought the inclusion of new tools to achieve the objectives of the projects. The purpose of the present paper is to present the application of Choosing By Advantages (CBA) methodology to select the best alternative in the material removal system in the execution of basements in a project that was paralyzed by the health emergency COVID 19. CBA is a lean tool used to make decisions with clarity and transparency and in this case is used to consider the constraints of COVID-19 protocol to guide in decisions making. This methodology was applied to a case study for a building project in the basement construction phase that restarts its activities in the excavations. For that, an expert panel was formed to analyze and decide the best alternative solution. Finally, the selected alternative was implemented on-site, validating the methodology. It is concluded that CBA is an excellent tool to transparently document the selection process of the removal system. Additionally, this methodology allows including activities regarding the COVID-19 protocol, without affecting the project's productivity.
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    Life-cycle cost analysis for an incremental seismic rehabilitation project
    (SAGE Publications Inc., 2021-11-01)
    Incremental seismic rehabilitation (ISR) consists of a set of discrete rehabilitation actions in order to decrease initial costs and to avoid long-lasting disruptions. Nevertheless, there are few cases of incrementally retrofitted buildings and few studies about its economic feasibility. The objective of this work is to evaluate the differences between incremental and single-stage rehabilitation in terms of economic losses during the building’s life span. For this purpose, this work analyzes three rehabilitation proposals to improve seismic performance of typical school buildings. Based on P58 FEMA (Federal Emergency Management Agency) methodology, expected repair costs and benefits were calculated for each rehabilitation intervention. Results confirm the potential of ISR for improving essential buildings.
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    The strengthening of corporate governance based on applied fuzzy logic
    (John Wiley and Sons Ltd, 2022-09-01)
    Despite advances in research on corporate governance, there are still knowledge gaps. The article aims to broaden the debate on strengthening corporate governance and propose a tool to facilitate decision‐making. The research is novel because of the engagement of 117 master's students from a business school, contributing to competency‐based learning on Good Corporate Governance (GCG). This is applied research with the explanatory objective and quantitative approach through modeling and simulation. The OWA Operator assesses GCG principles' adequacy and reveals a ranking of 28 enterprises listed on the Lima Stock Exchange in corporate governance, increasing transparency and reducing risks. The results indicate that six enterprises would be solid in the GCG, and the corporate governance should consider strategic capability, fair dealing, transparency, and good social responsibility practices. The main contributions are reducing the identified knowledge gaps and proposing actions to strengthen governance. The authors suggest promising lines of research.
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    Socio-economic and health management of pandemics based on forgotten effects theory
    (Taylor & Francis, 2022-04-04)
    Intense and frequent changes increase uncertainty and complexity in decision-making. The COVID-19 pandemic exacerbates this situation. Therefore, the decision-maker seeks to reduce risks and meet these challenges. The manuscript aims to identify cause-effect relationships between variables affecting countries and changes caused by the COVID-19 pandemic and propose an algorithm to facilitate decision-making by identifying forgotten effects. The authors use thematic analysis to synthesize the semi-systematic literature review findings. The applied research uses a quantitative approach through modeling and simulation. The results highlight that the pandemic effects are associated with causes such as health care, political and economic stability, social justice, and the level of corruption. Decision-makers must prioritize the management of these variables guided by science. The main contribution is to show an algorithm that identifies forgotten effects in pandemics' socio-economic and health management, preventing future crises. In addition, the study advances the frontier of knowledge by addressing identified gaps and contributes to academia and policy makers. The most critical limitation is the number of variables included in this research. Future investigations could include analyses on the impact of climate change and sustainable development of nations and country-specific studies on the forgotten effects of the COVID-19 pandemic.
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    Financial literacy and risky credit behavior: The moderating effect of minimalist lifestyle
    (Springer Publishing Company, 2024-11-01)
    The minimalist lifestyle represents an opportunity to make more conscious consumption decisions that lead to higher well-being. In spite of its growing popularity among the younger generations, this lifestyle has received little attention from scholars. To address this limitation, the influence of the minimalist lifestyle on the financial decision-making process was examined. Particularly, the study investigated the moderating effect of the minimalist lifestyle on the relationship between financial literacy and risky credit behavior among 308 adults in Lima, Peru. Using partial least squares structural modeling, the results revealed that the adoption of the minimalist lifestyle strengthened the negative association between financial literacy and risky credit behavior. In other words, the minimalist lifestyle allowed the individual’s level of financial literacy to have a higher effect on risky behavior related to consumer credit only among individuals from Generation Y. What’s more, the application of artificial neural network allowed the identification of financial knowledge and financial behavior as the most important mitigators of risky credit behavior among Generation Y and Generation X individuals, respectively.
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    Ética y factores que afectan las decisiones judiciales
    (Poder Judicial del Peru, 2026-06-30)
    La ética es el estudio sobre los medios que tiene el ser humano para lograr alcanzar el bien. En su aplicación de la administración de justicia, se espera que cada magistrado se desempeñe con ética al momento de tomar las decisiones judiciales porque impactan directamente sobre los bienes jurídicos de las partes del proceso, de ahí la necesidad de que el juez actúe objetivamente y libre de cualquier sesgo. No obstante, la toma de decisiones está expuesta a factores que vulneran su objetividad y que no siempre son identificados a tiempo, por ello se requiere llevar a cabo una labor preventiva desde la política jurisdiccional para salvaguardar la neutralidad. En ese sentido, el presente artículo de investigación de tipo mixto describe la opinión de un grupo de jueces respecto a la objetividad de las decisiones judiciales, así como el resultado de la revisión de los factores que potencialmente podrían afectarlas, basados en estudios de investigación científica. Los resultados evidencian que los factores extra- legales que afectan las decisiones judiciales son de tres tipos: biológicos, emocionales y sesgos cognitivos. Del estudio cuantitativo se apreció que el 100 % de los participantes consideraron que sus sentencias son completamente objetivas y que no han recibido ninguna capacitación sobre los factores extralegales que afectan las decisiones judiciales; sin embargo, el 18 % reconoce que las fuentes principales de error son los problemas familiares, el cumplimiento de metas, los prejuicios personales y la presión mediática.
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