大数据通过需求预测对供应链绩效的影响

Pastor Arguelles JR., Z. Pólkowski
{"title":"大数据通过需求预测对供应链绩效的影响","authors":"Pastor Arguelles JR., Z. Pólkowski","doi":"10.54489/ijcim.v3i1.232","DOIUrl":null,"url":null,"abstract":"By enabling more precise demand forecasting, the use of big data has changed the field of supply chain management. Companies may more accurately predict customer demand by gathering and analyzing enormous amounts of data from many sources, including customer behaviors and market trends, and then adjusting their production and inventory levels accordingly. By ensuring that goods and services are accessible when and where they are required, this improves customer happiness in addition to the efficiency and cost-effectiveness of the supply chain. The data collected from both primary and secondary sources to achieve the research objectives. The data collected from hospitality industry and evaluated through SmartPLS software to investigate the hypothesized model. An online survey through a questionnaire was the data collection tools used for attaining data. A survey analysis was conducted on the individuals employed to the supply chain departments. In addition, the findings revealed a positive significant of big data on supply chain performance through demand forecasting. Overall, the impact of big data on supply chain performance through demand forecasting is significant and continues to drive innovation and improvement in the hospitality sector.","PeriodicalId":104992,"journal":{"name":"International Journal of Computations, Information and Manufacturing (IJCIM)","volume":"193 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Impact of Big Data on Supply Chain Performance through Demand Forecasting\",\"authors\":\"Pastor Arguelles JR., Z. Pólkowski\",\"doi\":\"10.54489/ijcim.v3i1.232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By enabling more precise demand forecasting, the use of big data has changed the field of supply chain management. Companies may more accurately predict customer demand by gathering and analyzing enormous amounts of data from many sources, including customer behaviors and market trends, and then adjusting their production and inventory levels accordingly. By ensuring that goods and services are accessible when and where they are required, this improves customer happiness in addition to the efficiency and cost-effectiveness of the supply chain. The data collected from both primary and secondary sources to achieve the research objectives. The data collected from hospitality industry and evaluated through SmartPLS software to investigate the hypothesized model. An online survey through a questionnaire was the data collection tools used for attaining data. A survey analysis was conducted on the individuals employed to the supply chain departments. In addition, the findings revealed a positive significant of big data on supply chain performance through demand forecasting. Overall, the impact of big data on supply chain performance through demand forecasting is significant and continues to drive innovation and improvement in the hospitality sector.\",\"PeriodicalId\":104992,\"journal\":{\"name\":\"International Journal of Computations, Information and Manufacturing (IJCIM)\",\"volume\":\"193 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computations, Information and Manufacturing (IJCIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54489/ijcim.v3i1.232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computations, Information and Manufacturing (IJCIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54489/ijcim.v3i1.232","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

通过实现更精确的需求预测,大数据的使用改变了供应链管理领域。通过收集和分析来自多个来源的大量数据,包括客户行为和市场趋势,公司可以更准确地预测客户需求,然后相应地调整生产和库存水平。通过确保货物和服务在需要的时间和地点都可以获得,除了提高供应链的效率和成本效益外,还可以提高客户的满意度。从主要和次要来源收集的数据,以实现研究目标。从酒店业收集的数据,并通过SmartPLS软件进行评估,以调查假设模型。通过问卷的在线调查是用于获取数据的数据收集工具。对供应链部门的员工进行了调查分析。此外,研究结果还揭示了大数据通过需求预测对供应链绩效的积极影响。总体而言,通过需求预测,大数据对供应链绩效的影响是巨大的,并将继续推动酒店业的创新和改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Impact of Big Data on Supply Chain Performance through Demand Forecasting
By enabling more precise demand forecasting, the use of big data has changed the field of supply chain management. Companies may more accurately predict customer demand by gathering and analyzing enormous amounts of data from many sources, including customer behaviors and market trends, and then adjusting their production and inventory levels accordingly. By ensuring that goods and services are accessible when and where they are required, this improves customer happiness in addition to the efficiency and cost-effectiveness of the supply chain. The data collected from both primary and secondary sources to achieve the research objectives. The data collected from hospitality industry and evaluated through SmartPLS software to investigate the hypothesized model. An online survey through a questionnaire was the data collection tools used for attaining data. A survey analysis was conducted on the individuals employed to the supply chain departments. In addition, the findings revealed a positive significant of big data on supply chain performance through demand forecasting. Overall, the impact of big data on supply chain performance through demand forecasting is significant and continues to drive innovation and improvement in the hospitality sector.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Big Data Analytics in Healthcare: Exploring the Role of Machine Learning in Predicting Patient Outcomes and Improving Healthcare Delivery Technology Acceptance Model and Attitude of Consumers towards Online Shopping with Special Reference to UAE Impact of Big Data on Supply Chain Performance through Demand Forecasting Impact of Information Security on Online Operations: The Mediating Role of Risk Management Improving Heart Disease Prediction Accuracy Using a Hybrid Machine Learning Approach: A Comparative study of SVM and KNN Algorithms
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1