Neutrosophic CEBOM-MACONT model for sustainable management of end-of-life tires

Šimić, Vladimir; Dabić-Miletić, Svetlana; Tirkolaee, Erfan Babaee; Stević, Željko; Deveci, Muhammet; Senapati, Tapan

doi:10.1016/j.asoc.2023.110399

Cited by 15 publications

(2 citation statements)

References 80 publications

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“…Even though market factors suggest concentrating on WT treatments that involve their reuse, statistics reveal that more than 90 % of them are designed for energy production or material recovery [13]. According to the ETRMA data [14], WTs were collected and used for material recycling and energy recovery in 2019 in Europe [3]. Despite insufficient reusing, economic sustainability is supported regarding the cost of new raw material procurement, energy demands, and illegal dumping.…”

Section: Actual Trends In Waste Tire Managementmentioning

confidence: 99%

Smart and Sustainable Waste Tire Management: Decision-Making Challenges and Future Directions

Dabić-Miletić

Šimić

2023

Decis. Mak. Adv.

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The vehicle number has grown significantly in recent decades, resulting in a significant increase in the number of waste tires globally. The environment and public health are seriously endangered by the growing amount of waste tires. As a result, considerable effort is being put into the search for viable alternatives for sustainable management. Even though numerous treatments for waste tires have already been tested and proved successful, their continued industrial implementation remains difficult in both everyday life and research efforts. Finding practical, cost-effective, and ecologically friendly ways to manage waste tires is one of the biggest environmental challenges of the 21st century. By focusing on smart tire waste management, this study examines some of the most important decision-making challenges that support social and environmental sustainability. The main topics of this research are the examination of certain fundamental problems and challenges, as well as some key management strategies for this environmentally unfavorable type of increasing waste. This comprehensive analysis not only identifies significant gaps but also establishes the foundation for addressing some of the most significant decision-making issues in waste tire management by providing recommendations for further research in this important and vulnerable area of academic and practical analysis.

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Section: Actual Trends In Waste Tire Managementmentioning

confidence: 99%

Smart and Sustainable Waste Tire Management: Decision-Making Challenges and Future Directions

Dabić-Miletić

Šimić

2023

Decis. Mak. Adv.

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“…Consequently, multi-criteria decision-making (MCDM) approaches have gained traction, demonstrating promise in providing policymakers and managers with flexible and adaptable tools [31][32][33][34][35][36][37][38][39]. These approaches use predetermined parameters to classify and select one or more elements from a set of alternatives [40][41][42][43][44][45][46], and the chosen parameters are subsequently assessed based on their effectiveness in fulfilling their respective functions and determining the suitability of alternative options [47][48][49][50][51][52].…”

Section: Literature Reviewmentioning

confidence: 99%

Strategies for Enhancing Industry 4.0 Adoption in East Africa: An Integrated Spherical Fuzzy SWARA-WASPAS Approach

Qiu¹,

Bouraima²,

Kiptum³

et al. 2023

JII

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Developed countries have successfully implemented various Industry 4.0 (I4.0) initiatives, showcasing their ability to reap the benefits of this new industrial revolution. Active pursuit of excellence in Industry 4.0 is evident in these nations. However, in Africa, many countries still lack a clear understanding of Industry 4.0, with some remaining trapped in Industry 1.0 and others facing challenges in transitioning to Industry 2.0. Moreover, a significant number of these African countries continue to grapple with limited access to reliable electricity. To address the issue, this study examines seven strategies identified as criteria for enhancing the adoption of Industry 4.0 within the East African Community (EAC). These strategies are derived from observations of Industry 4.0 initiatives implemented in developed countries. Subsequently, the criteria are used to evaluate and rank the level of Industry 4.0 adoption in two specific East African countries. To tackle the challenges of complex group decision-making, the study integrates the Weighted Aggregated Sum Product Assessment (WASPAS) technique with the Step-Wise Weight Assessment Ratio Analysis (SWARA) within a spherical fuzzy (SF) framework. The SF-SWARA approach is applied to determine the weight and importance of the criteria, while SF-WASPAS is employed to rank the countries based on the criteria weighted by SF-SWARA. According to the findings, it was revealed that education and training, research, development, and innovation, as well as public-private partnerships and policy innovation, are the three most influential strategies for significantly improving the adoption of Industry 4.0 within the East African community. Furthermore, the results indicate that Rwanda stands out as the leading country in terms of implementing these strategies to enhance the adoption of Industry 4.0 technology. To verify the reliability and suitability of the proposed methodology, a sensitivity analysis was conducted, which affirmed the stability and practicality of the suggested approach.

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Enhanced TODIM based on VIKOR method for multi-attribute decision making with Type-2 neutrosophic number and applications to green supplier selection

Wang

Cai

2023

Soft Comput

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Neutrosophic CEBOM-MACONT model for sustainable management of end-of-life tires

Cited by 15 publications

References 80 publications

Smart and Sustainable Waste Tire Management: Decision-Making Challenges and Future Directions

Smart and Sustainable Waste Tire Management: Decision-Making Challenges and Future Directions

Strategies for Enhancing Industry 4.0 Adoption in East Africa: An Integrated Spherical Fuzzy SWARA-WASPAS Approach

Enhanced TODIM based on VIKOR method for multi-attribute decision making with Type-2 neutrosophic number and applications to green supplier selection

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