Mahmoud Allahham, Abdel-Aziz Ahmad Sharabati, Heba Hatamlah, A. Y. B. Ahmad, Samar Sabra, Mohammad Khalaf Daoud
{"title":"大数据分析和人工智能促进医院绿色供应链整合和可持续发展","authors":"Mahmoud Allahham, Abdel-Aziz Ahmad Sharabati, Heba Hatamlah, A. Y. B. Ahmad, Samar Sabra, Mohammad Khalaf Daoud","doi":"10.37394/232015.2023.19.111","DOIUrl":null,"url":null,"abstract":"This paper examines how big data analytics and AI improve hospital supply chain sustainability. Hospitals are recognizing the need for eco-friendly operations due to environmental issues and rising healthcare needs. It analyzes data from 68 UK hospitals using a conceptual model and partial least squares regression-based structural equation modeling. The research begins by examining hospital supply networks' environmental impact. Energy use, trash, and transportation emissions are major issues. It then explains how big data analytics and AI can transform these implications. This study prioritizes big data analytics for inventory management, demand forecasting, and procurement. Hospitals can reduce inventory, waste, and supply shortages using data-driven insights, saving money and the environment. AI also boosts hospital supply chain logistics and transportation efficiency, according to the study. Fuel consumption, carbon emissions, and delivery routes are optimized by AI. Predictive maintenance preserves medical equipment. In conclusion, hospital supply chains benefit greatly from big data analytics and AI. Hospitals can improve the healthcare business, reduce their environmental impact, and preserve resources for future generations. Healthcare leaders, politicians, and researchers seeking data-driven solutions for sustainable hospital supply chains gain valuable insights.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":"69 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big Data Analytics and AI for Green Supply Chain Integration and Sustainability in Hospitals\",\"authors\":\"Mahmoud Allahham, Abdel-Aziz Ahmad Sharabati, Heba Hatamlah, A. Y. B. Ahmad, Samar Sabra, Mohammad Khalaf Daoud\",\"doi\":\"10.37394/232015.2023.19.111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper examines how big data analytics and AI improve hospital supply chain sustainability. Hospitals are recognizing the need for eco-friendly operations due to environmental issues and rising healthcare needs. It analyzes data from 68 UK hospitals using a conceptual model and partial least squares regression-based structural equation modeling. The research begins by examining hospital supply networks' environmental impact. Energy use, trash, and transportation emissions are major issues. It then explains how big data analytics and AI can transform these implications. This study prioritizes big data analytics for inventory management, demand forecasting, and procurement. Hospitals can reduce inventory, waste, and supply shortages using data-driven insights, saving money and the environment. AI also boosts hospital supply chain logistics and transportation efficiency, according to the study. Fuel consumption, carbon emissions, and delivery routes are optimized by AI. Predictive maintenance preserves medical equipment. In conclusion, hospital supply chains benefit greatly from big data analytics and AI. Hospitals can improve the healthcare business, reduce their environmental impact, and preserve resources for future generations. Healthcare leaders, politicians, and researchers seeking data-driven solutions for sustainable hospital supply chains gain valuable insights.\",\"PeriodicalId\":53713,\"journal\":{\"name\":\"WSEAS Transactions on Environment and Development\",\"volume\":\"69 10\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"WSEAS Transactions on Environment and Development\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37394/232015.2023.19.111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"WSEAS Transactions on Environment and Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37394/232015.2023.19.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
Big Data Analytics and AI for Green Supply Chain Integration and Sustainability in Hospitals
This paper examines how big data analytics and AI improve hospital supply chain sustainability. Hospitals are recognizing the need for eco-friendly operations due to environmental issues and rising healthcare needs. It analyzes data from 68 UK hospitals using a conceptual model and partial least squares regression-based structural equation modeling. The research begins by examining hospital supply networks' environmental impact. Energy use, trash, and transportation emissions are major issues. It then explains how big data analytics and AI can transform these implications. This study prioritizes big data analytics for inventory management, demand forecasting, and procurement. Hospitals can reduce inventory, waste, and supply shortages using data-driven insights, saving money and the environment. AI also boosts hospital supply chain logistics and transportation efficiency, according to the study. Fuel consumption, carbon emissions, and delivery routes are optimized by AI. Predictive maintenance preserves medical equipment. In conclusion, hospital supply chains benefit greatly from big data analytics and AI. Hospitals can improve the healthcare business, reduce their environmental impact, and preserve resources for future generations. Healthcare leaders, politicians, and researchers seeking data-driven solutions for sustainable hospital supply chains gain valuable insights.
期刊介绍:
WSEAS Transactions on Environment and Development publishes original research papers relating to the studying of environmental sciences. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of these particular areas. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with sustainable development, climate change, natural hazards, renewable energy systems and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.