A Bayesian BWM-Based Approach for Evaluating Sustainability Measurement Attributes in the Steel Industry

Sahebi, Iman Ghasemian; Toufighi, Seyed Pendar; Arab, Alireza

doi:10.1007/978-3-030-89795-6_13

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…A multicriteria decision-making method called the "Best-Worst Method" (BWM) determines the appropriate weights for a collection of criteria based solely on the preferences of one decision-maker (DM). The Bayesian best-worst method, a modified and revised edition of the BWM for group decision-making, is an MCDM methodology in which the opinions of various experts are aggregated, applying a probabilistic approach to enable more accurate decision-making regarding the integrated ranking of the criteria under consideration [83]. The Bayesian BWM is stochastic since comparisons are accomplished pairwise by applying the multinomial distribution and the Dirichlet distribution is utilized to compute global weights [84].…”

Section: Baysian Best-worst Methodsmentioning

confidence: 99%

Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy

Shakur,

Lubaba,

Debnath

et al. 2024

Logistics

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Background: Fast-moving consumer goods (FMCG) supply chains are experiencing various challenges due to the interactions between consumers and decision-makers during physical distribution, manufacturing, wholesale and retail. One possible strategy to address these challenges for smoothing the supply chain (SC) and logistics operations is to adopt Industry 4.0 (I4.0) based technologies in the FMCG business processes. In this regard, digitalization and automation of the FMCG supply chain can be strengthened by the alluring properties of I4.0 technologies. Methods: This study identified nine significant challenges through a literature review and expert validation. Later, the challenges were evaluated using a novel multicriteria decision-making (MCDM) framework, the Bayesian best worst method (BWM). Results: The findings indicated that “requirement for substantial investment and resources”, “incompatible technological infrastructure” and “poorly structured value chain” are the most significant challenges to implementing I4.0 in the FMCG industry. Conclusions: The study is expected to significantly contribute to improving the FMCG supply chain’s resilience, sustainability, visibility, traceability and responsiveness. Additionally, the research can provide industrial practitioners valuable insights into implementing I4.0 in FMCG and similar sectors and thus promote SC sustainability and resilience in those industries.

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Section: Baysian Best-worst Methodsmentioning

confidence: 99%

Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy

Shakur,

Lubaba,

Debnath

et al. 2024

Logistics

View full text Add to dashboard Cite

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A neutrosophic enhanced best–worst method for performance indicators assessment in the renewable energy supply chain

Masoomi,

Sahebi,

Arab

et al. 2023

Soft Comput

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The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America

et al. 2022

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This study aims to help managers develop a proper strategy and policy for their company’s future. After the global COVID-19 pandemic, developed countries decided to change their production and relocate and re-industrialize. The U.S.’s big electronics and automobile companies are not an exception to this rule. The lithium batteries are the main instrument of mobile phone and electric vehicles. The leading lithium battery supplier for the U.S mobile phone companies is China. Argentina, Bolivia, and Chile (in South America) have some of the largest lithium mines in the world; these countries are known as the lithium triangle. Among the 86 million tonnes of lithium resources worldwide, 49.9 million tonnes exist in this area. The researchers in this study surveyed the best country for constructing a battery for companies in the U.S. Because of the growth of electric vehicles and their use of the lithium battery, the world is facing astronomical prices for lithium. To emphasize this issue and help managers create good policy, this study combined multiple methods. The improved suitability-feasibility-acceptability (SFA) strategy is integrated with the Bayesian best-worst method (BBWM) and measurement of alternatives and rankings according to compromise solution (MARCOS) multicriteria methods to determine the best destination. For comparison, based on the SFA strategy, seven criteria are introduced: commercially viable reserves, national minimum wage, corporate income tax, accessibility to mining companies, accessibility to the waterway, population, and political stability index. The Bayesian BWM analysis reveals that the foremost factor is corporate income tax, whereas MARCOS’s findings indicate that Chile is the best country to construct the lithium battery industry. To verify the proposed approach, a comparison analysis also is performed.

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A Bayesian BWM-Based Approach for Evaluating Sustainability Measurement Attributes in the Steel Industry

Cited by 3 publications

References 23 publications

Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy

Exploring the Challenges of Industry 4.0 Adoption in the FMCG Sector: Implications for Resilient Supply Chain in Emerging Economy

A neutrosophic enhanced best–worst method for performance indicators assessment in the renewable energy supply chain

The Suitability-Feasibility-Acceptability Strategy Integrated with Bayesian BWM-MARCOS Methods to Determine the Optimal Lithium Battery Plant Located in South America

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