Artificial Intelligence Capabilities for Demand Planning Process

Logistics Pub Date : 2024-05-10 DOI:10.3390/logistics8020053
C. D. de Mattos, Fernanda Caveiro Correia, K. Kissimoto
{"title":"Artificial Intelligence Capabilities for Demand Planning Process","authors":"C. D. de Mattos, Fernanda Caveiro Correia, K. Kissimoto","doi":"10.3390/logistics8020053","DOIUrl":null,"url":null,"abstract":"Background: Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review of the existing literature, the main objective of this study is to analyze how AI is being applied and adopted in the demand planning process, identifying the resources needed to build the capacity of AI in the demand process, as well as the mechanisms and practices contributing to AI capability’s advancement and formation. Methodology: The approach was qualitative, and case studies of three different companies were conducted. Results: This study identified crucial resources necessary for fostering AI capabilities in demand planning. Our study extends the literature on AI capability in several ways. First, we identify the resources that are important in the formation of the capacity to implement AI in the context of demand planning. Conclusions: This study’s practical contributions underscore the multifaceted nature of AI implementation for demand planning, emphasizing the importance of resource allocation, human capital development, collaborative relationships, organizational alignment, and relational capital and AI.","PeriodicalId":507203,"journal":{"name":"Logistics","volume":" 41","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/logistics8020053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review of the existing literature, the main objective of this study is to analyze how AI is being applied and adopted in the demand planning process, identifying the resources needed to build the capacity of AI in the demand process, as well as the mechanisms and practices contributing to AI capability’s advancement and formation. Methodology: The approach was qualitative, and case studies of three different companies were conducted. Results: This study identified crucial resources necessary for fostering AI capabilities in demand planning. Our study extends the literature on AI capability in several ways. First, we identify the resources that are important in the formation of the capacity to implement AI in the context of demand planning. Conclusions: This study’s practical contributions underscore the multifaceted nature of AI implementation for demand planning, emphasizing the importance of resource allocation, human capital development, collaborative relationships, organizational alignment, and relational capital and AI.
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
需求规划流程的人工智能功能
背景:技术进步,特别是人工智能(AI)技术的进步,正在彻底改变运营管理,尤其是供应链管理领域。本文深入探讨了人工智能在供应链背景下的需求规划流程中的应用。在对现有文献进行全面回顾的基础上,本研究的主要目的是分析人工智能在需求计划流程中的应用和采纳情况,确定在需求流程中建立人工智能能力所需的资源,以及促进人工智能能力提升和形成的机制和实践。研究方法:采用定性方法,对三家不同的公司进行了案例研究。研究结果本研究确定了在需求规划中培养人工智能能力所需的关键资源。我们的研究从几个方面扩展了有关人工智能能力的文献。首先,我们确定了在需求规划中形成实施人工智能能力的重要资源。结论:本研究的实际贡献强调了在需求规划中实施人工智能的多面性,强调了资源分配、人力资本开发、协作关系、组织调整以及关系资本与人工智能的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Simulation-Based Optimization of Truck Appointment Systems in Container Terminals: A Dual Transactions Approach with Improved Congestion Factor Representation Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects Enhancing Supplier Selection for Sustainable Raw Materials: A Comprehensive Analysis Using Analytical Network Process (ANP) and TOPSIS Methods Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management An Examination of Human Fast and Frugal Heuristic Decisions for Truckload Spot Pricing
×
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