794 research outputs found

    Environmental Factors and Adoption of Green Supply Chain Management among SMEs in Nigeria: Moderating Role of Environmental Uncertainty

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    Environmental regulations and policies have been recognised as significant factors influencing the adoption of Green Supply Chain Management. However, the importance of these factors in influencing sustainable practices within supply chains has been emphasized in recent research as global environmental challenges continue to worsen. As a result, adopting Green Supply Chain Management practices is crucial for ensuring sustainable supply chain operations in Nigeria, as SMEs significantly contribute to economic growth and development in the country. Therefore, this study examines the effect of environmental factors on the adoption of GSCM in the Nigerian SMEs. To measure all the variables, validated items were adapted from prior studies. Thus, 412 copies of questionnaires were retrieved from the selected managers/owners of SMEs after testing for the validity and reliability of instruments through a pilot study. The findings of the study indicated that the environmental factor is a very good predictive faction for the GSCM adoption of SMEs business in Nigeria, most especially in the area of customer demand, environmental regulation, environmental uncertainty, and supplier relationships. Furthermore, the introduction of environmental uncertainty as a moderating effect influence the relationship between an environmental factor and the adoption of GSCM practices in the area of environmental regulation and supplier relationship. The study findings are useful for decision-makers in the SMEs sector so they may build methods to enhance the adoption of GSCM. These findings are also useful for academicians’ future research endeavors. Managers can use those environmental factors concretely as a reference for the companies that intend to support the United Nation SDG-2030 agenda and to find new business opportunities for the implementation of sustainable development. The findings have a number of managerial implications that could contribute to SMEs for planning and development a GSCM strategy through the internal of the green supply chain perspective. This study's recommendations can help Nigeria's SME sector achieve its sustainable development goals and lead global climate change and environmental protection initiatives

    Evaluation of Factors Affecting Innovation Productivity by Pythagorean Fuzzy AHP Method

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    Purpose: In this study, it is aimed to rank the factors affecting the innovation productivity of enterprises. Methodology: The Pythagorean Fuzzy Analytical Hierarchy Process (AHP) method, which gives successful results in modelling uncertainty and uses Pythagorean fuzzy sets, is used to rank the factors affecting innovation productivity according to their importance. Findings: In the application part of study firstly, the factors affecting the innovation productivity were determined and as a result of expert evaluations, the steps of the method were applied and the factors were ranked according to their importance. Finally, the most important factors were determined by performing a sensitivity analysis. When the results obtained from the study are examined, it has been determined that the factor of preparing the technology roadmap affects the innovation productivity the most, while the sector and market structure affect the innovation productivity the least among the determined factors. Originality: It is the first study in the literature in which the factors affecting innovation productivity are determined and ranked according to their importance

    A Conceptual Research on the Contribution of Integrated Management Systems to the Circular Economy

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    Companies worldwide strive to become more sustainable, and, in this context, the circular economy (CE) gains importance as alternative system as opposed to the linear economy. Since executive mangers around the world work with management systems (MSs) to guide and improve organizational operations, this work aims to explore how integrated MSs (IMS) as business tools can contribute to the adoption of CE principles at the corporate level. To achieve this objective, a systematic literature review is performed, which results in a synthesis sample of 18 academic papers. The findings reveal how MSs contribute to CE adoption and, therefore, demonstrate that managers can use IMS to foster CE implementation. In addition, the findings highlight the importance of institutional intervention in the transition from a linear towards a circular designed economy. The paper contributes to academia by linking the concepts of IMS and CE, synthesizing the current academic knowledge at hand, and proposing a comprehensive research agenda that sets the path for future academic investigations. In a practical perspective, the paper contributes also to managers since it emphasizes how IMS can be used to incorporate circular business thinking into operations management

    Natural and Technological Hazards in Urban Areas

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    Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events

    Climate change: strategies for mitigation and adaptation

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    The sustainability of life on Earth is under increasing threat due to human-induced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change

    Exploring the transition from techno centric industry 4.0 towards value centric industry 5.0: a systematic literature review

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    This systematic literature review synthesises the literature on human centric IN 4.0 and IN 5.0 while exploring driving forces behind the transition from technocentric IN 4.0 to value centric IN 5.0 using the principles of the multiple level perspective (MLP). Works that discuss contextual, regime and niche level factors which impact on the transition were explored. The Covid- 19 pandemic and Climate change are identified as key contextual, ‘Landscape’, factors impacting the transition while Trust, Mass personalisation and Autonomy are highlighted as key Regime factors. In terms of Niche innovations, Advanced Extended reality technologies, Cobots/ Advanced Robotics, and Advanced AI are often connected with landscape or regime issues. Drawing on MLP theory, the study demonstrates that the transition from IN 4.0 towards IN 5.0 is occurring through a reconfiguration pattern. The paper further emphasises aspects that both practitioners and academics need to be cognisant of in order to affect a transition from IN 4.0 to IN 5.0

    Multicriteria Decision Making in Sustainable Tourism and Low-Carbon Tourism Research: A Systematic Literature Review

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    Multicriteria Decision Making (MCDM) is increasingly being utilized as an analytical research tool for sectors that require decision-making with specific objectives and constraints, such as the tourism industry. Sustainable tourism, which examines the balance of numerous aspects, including stakeholders’ interests, is the critical feature propelling the increased usage of MCDM. This paper explores the use of Multicriteria Decision Making (MCDM) methods applied in studies of sustainable tourism and its derivative term, low-carbon tourism, using a systematic literature review (SLR) search from the Scopus database. The analysis has identified 189 relevant studies published between 1987 to April 2022. After selection, screening, and synthesizing processes, we selected 135 pertinent studies, which were analysed in general descriptive data, citation impacts, geographical categorization, categorization of the methodologies’ objectives, and possible trajectories of similar research in the future. We find that highly cited authors and articles are related to sustainable tourism indicators\u27 development and case studies. Furthermore, most relevant studies are concentrated in Asia and Europe rather than other regions. We also categorize the reviewed studies into six classifications depending on each method\u27s intended usage and further suggest four contexts for the studies’ future trajectory

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
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