A data-driven model for sustainable and resilient supplier selection and order allocation problem in a responsive supply chain: A case study of healthcare system

Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 124, С. 106511 - 106511

Опубликована: Июнь 8, 2023

Язык: Английский

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AI-Driven Supply Chain Transformation in Industry 5.0: Enhancing Resilience and Sustainability

Journal of the Knowledge Economy, Год журнала: 2024, Номер unknown

Опубликована: Июнь 13, 2024

Язык: Английский

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A Smart and Agile Dry Port-Seaport Logistic Network Considering Industry 5.0: A Multi-stage Data-driven Approach

Socio-Economic Planning Sciences, Год журнала: 2025, Номер unknown, С. 102141 - 102141

Опубликована: Янв. 1, 2025

Язык: Английский

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A hybrid machine learning-based decision-making model for viable supplier selection problem considering circular economy dimensions

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Янв. 25, 2025

Язык: Английский

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Sustainable evaluation of the raw material providers based on industry 5.0 and circular economy aspects: a new stochastic method

OPSEARCH, Год журнала: 2025, Номер unknown

Опубликована: Фев. 4, 2025

Язык: Английский

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Sustainable supplier selection and order allocation problem considering the agility and resilience dimensions: a novel multi-stage data-driven decision-making approach

International Journal of Systems Science Operations & Logistics, Год журнала: 2025, Номер 12(1)

Опубликована: Фев. 5, 2025

Язык: Английский

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Viable supplier selection problem based on Industry 5.0 and circular economy aspects: a hybrid decision-making approach

International Journal of Systems Science Operations & Logistics, Год журнала: 2025, Номер 12(1)

Опубликована: Фев. 25, 2025

Язык: Английский

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Two-stage approach for COVID-19 vaccine supply chain network under uncertainty using the machine learning algorithms: A case study

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 135, С. 108837 - 108837

Опубликована: Июнь 17, 2024

Язык: Английский

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Delays to distributed ledgers: examining the rationale for leveraging blockchain technology in construction sector

Global Knowledge Memory and Communication, Год журнала: 2025, Номер unknown

Опубликована: Янв. 2, 2025

Purpose India’s construction sector faces substantial challenges with project delays and cost overruns. According to the Ministry of Statistics Programme Implementation, an astounding 431 out 1,820 projects reported overruns, whereas 848 experienced in 2023. These overruns often push costs 30%–40% beyond initial estimates. Blockchain technology (BCT) offers a promising solution by enhancing transparency, streamlining processes through automation optimising supply chains industry. This study aims explore adoption landscape BCT within sector, drivers behind its acceptance future directions for implementation. Design/methodology/approach uses mixed-methods’ research design that combines both quantitative qualitative data collection analysis techniques investigate current use blockchain, perceived rationale direction blockchain construction. A survey professionals experience was conducted. In addition, exhaustive literature review content were conducted using reputable electronic databases such as Scopus, Web Science IEEE Xplore, reinforcing study’s empirical foundation. The analysed descriptive inferential statistics determine relative importance items MS-Excel SPSS. Findings Despite regulatory challenges, is on rise, 90% respondents expressing strong interest. Stakeholders see improved transparency accountability key adoption, emphasising blockchain’s capacity support veracity trust projects. Notable benefits include enhanced communication, reduction, chain management precise execution monitoring. Overcoming constraints bridging knowledge gaps will be essential fully realising all players Originality/value findings provide valuable insights professionals, researchers policymakers interested adopting BCT. By clarifying transformative potential this emphasises imperatives further study, innovation collaborative endeavours aimed at addressing industry facilitating digital integration.

Язык: Английский

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A Multi-stage Machine Learning Model to Design a Sustainable-Resilient-Digitalized Pharmaceutical Supply Chain

Socio-Economic Planning Sciences, Год журнала: 2025, Номер unknown, С. 102165 - 102165

Опубликована: Фев. 1, 2025

Язык: Английский

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