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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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Sustainable management of the supply chain based on fuzzy logic
(Bellwether Publishing, Ltd., 2021-01-01)
Companies face a number of management challenges, and decision makers must adopt new approaches that consider sustainable development in their operations. In this context, the article aims to address sustainable supply chain management and propose solutions based on a fuzzy logic. Three distance measurement algorithms are applied to evaluate and classify suppliers in a consumer goods industry. The results demonstrate the usefulness of the algorithms in decision-making and bring a contribution to the sustainable development of companies. Furthermore, it supports future studies on sustainable management, the supply chain, and the application of algorithms to sustainability.
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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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Bibliometric review of research on decision models in uncertainty, 1990-2020
(John Wiley and Sons Ltd, 2022-10-01)
Societies experience intense and frequent changes in diverse environments, which increase uncertainty and complexity in decision-making. The decision-maker looks for alternatives to reduce risks and face these new challenges. In this context, science plays a vital role in proposing new solutions. The article aims to: (i) to carry out a bibliometric review of decision models in uncertainty through scientific mapping and performance analysis between 1990 and 2020; (ii) to know the scientific progress of 17 models that specialists validated. The Web of Science database and the VOSviewer, R, and Python software analyzed 26,835 articles in nine bibliometric indicators. The results revealed a positive trend of the publications in the analyzed models, being the Analytic Hierarchical Process the most used. Other findings showed China as the country with more scientific collaborations. There is enormous potential for future lines of research on the subject.
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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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Fuzzy Algorithm Applied to Factors Influencing Competitiveness: A Case Study of Brazil and Peru Through Affinities Theory
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-11-08)
Innovation plays a crucial role in the economy of nations worldwide. In Latin America, countries foster competitiveness through public and private incentives to support innovation. Moreover, entrepreneurship incentives seek to improve countries’ performance, although factors such as low business growth rates and informality can compromise it. Despite the efforts, there are several difficulties in achieving competitiveness, and few studies in developing countries. Therefore, the article explores the relationship between the factors that influence competitiveness, especially the role of innovation and entrepreneurship in Brazil and Peru. The research uses quantitative-qualitative methodology through modeling and simulation and a case study. The authors use the Affinities Theory to verify the relationship between the indicators that make up the competitiveness landscape and its most significant and attractive factors, adapting the methodology established by the International Institute for Management Development (IMD) World Competitiveness ranking. As a result, this algorithm allows us to know the relationships between five factors of economic attractiveness and four competitiveness indicators. As its main contributions, the study advances the frontier of knowledge about innovation and entrepreneurship, as few studies explore competitiveness in developing countries. Also, it offers a detailed explanation of the application of this algorithm, allowing researchers to reproduce this methodology in other scenarios. Practically, it might support policymakers in formulating development strategies and stimuli for business competitiveness. In addition, academic and business leaders can strengthen university-business collaboration with applied research in innovation and entrepreneurship. One limitation would be the number of countries participating in the research. The authors suggest future lines of research.
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Algorithm Applied to SDG13: A Case Study of Ibero-American Countries
(MDPI, 2023-01-01)
Scientific studies confirm the existence of a crisis caused by climate change, in which global causes produce local effects. Despite climate agreements, greenhouse gas emissions continue to fall short of targets to limit global warming. There is still a need for comparable data for Sustainable Development Goal (SDG) 13—Climate Action. The motivation of the research is to provide data for decision-making and to propose solutions to address the climate crisis. The article aims to propose a Fuzzy Logic algorithm to evaluate the SDG13 indicators and to deepen the discussion on climate change. The research is applied explanatory with a combined approach (quantitative-qualitative) through modeling, simulation, and case studies. As a result, the OWA operator ranks 10 Ibero-American countries to SDG13, indicating Colombia, Peru, and Cuba in the first positions. The main contributions are the reduction of identified knowledge gaps and proposals for action for policy and decision-makers. A limitation of this study would be the number of participating countries. The authors indicate future lines of research.
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Uncovering hidden and cumulative impacts of construction life cycle processes on planetary boundaries through Forgotten Effects Theory
(Elsevier BV, 2026-09-01)
This study applies the Forgotten Effects Theory (FET), a fuzzy-logic-based modelling framework, to analyse how construction life cycle processes generate direct and indirect pressures on multiple planetary boundaries. The approach captures multistage and nonlinear causal relationships derived from expert-based incidence matrices. Results show that mineral extraction, material distribution, and waste disposal strongly influence ocean acidification; construction operations and building use affect biosphere integrity; material production drives land-use change; and demolition contributes to climate change. The analysis revealed substantial hidden effects: the influence of mineral extraction on ocean acidification increased from 0.4 to 0.9 when material production was included as a mediator; the relationship between building use and biosphere integrity increased from 0 to 0.8 through indirect pathways; and the influence of demolition on climate change increased from 0 to 0.8 through waste-disposal mediation. A ±10% sensitivity analysis confirmed the stability of the main incidence hierarchy, with changes below 0.05 for the most relevant coefficients. These findings demonstrate that indirect (“forgotten”) effects can be as influential as direct impacts, significantly intensifying pressures across planetary boundaries. The construction sector is therefore characterised as a cumulative and interconnected system in which impacts propagate and reinforce each other across life cycle stages. These results highlight the limitations of silo-based environmental assessments and underscore the need for integrated, life cycle-oriented sustainability strategies. Policies prioritising upstream interventions, material efficiency and reduced demolition can generate broader systemic benefits. The study demonstrates the potential of FET as a transparent and reproducible modelling approach for linking local construction decisions with global environmental processes, supporting more integrated circular economy strategies and contributing to the achievement of Sustainable Development Goals 11, 12 and 13.
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