Reviewing the Roles of AI-Integrated Technologies in Sustainable Supply Chain Management: Research Propositions and a Framework for Future Directions

Sustainability, Год журнала: 2024, Номер 16(14), С. 6186 - 6186

Опубликована: Июль 19, 2024

In the post-pandemic era, uncertain global market and rising social-environmental issues drive organizations to adapt their supply chain strategies more dynamic, flexible models, leveraging advanced technologies like AI, big data analytics, decision support systems. This review paper aims examine current research on AI-integrated in sustainable management (SSCM) inform future directions. We adopted bibliometric text analysis, targeting 170 articles published between 2004 2023 from Scopus database following PRISMA (Preferred Reporting Items for Systematic Reviews Meta-Analyses) protocol. confirm that have demonstrated capability enable SSCM across various sectors. generated ten topics using Latent Dirichlet Allocation (LDA) method proposed 20 propositions. The results show processes primarily address sustainability, focusing environmental economic issues. However, there is still a technological gap tackling social working conditions fair dealing. Thus, we dynamic framework of AI help researchers practitioners synthesize optimize models

Язык: Английский

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An integrated best–worst method and fuzzy TOPSIS for resilient-sustainable supplier selection

Decision Analytics Journal, Год журнала: 2024, Номер 11, С. 100488 - 100488

Опубликована: Июнь 1, 2024

Achieving a balance between economic, environmental, and social factors in supplier selection while prioritizing business continuity poses considerable challenge. It is imperative to guarantee that selected suppliers adhere sustainability resilience requirements supporting the company's economic advancement. This study addresses this challenge through novel approach combines Best-Worst Method (BWM) with Fuzzy Technique Order of Preference by Similarity Ideal Solution (F-TOPSIS). Integrating these methodologies reduces burden pairwise comparisons, common using multi-criteria decision-making, thereby streamlining evaluation process. To assess effectiveness proposed model, we implemented our method on an actual case e-commerce conducted sensitivity analysis results. The findings suggest offers improved consistency rankings across criteria compared traditional BWM. also makes simplicity accuracy, ensuring are equipped handle disruptions uncertainties. aligns practical theoretical rigor which more accessible manageable for practitioners real-world settings.

Язык: Английский

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A novel fuzzy general best–worst method for considering diversity and inclusion in supplier selection programs

Annals of Operations Research, Год журнала: 2024, Номер unknown

Опубликована: Май 23, 2024

Язык: Английский

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A Strategic and Social Analytics Model for Sustainable Packaging in the Cosmetic Industry

Supply Chain Analytics, Год журнала: 2024, Номер 8, С. 100090 - 100090

Опубликована: Ноя. 1, 2024

Язык: Английский

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Preference mining and fuzzy inference for hotel selection based on aspect-based sentiment analysis from user-generated content

Journal of the Operational Research Society, Год журнала: 2024, Номер unknown, С. 1 - 18

Опубликована: Дек. 13, 2024

Язык: Английский

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