人工智能在未来建筑项目有效执行过程中的应用

Roozbeh Shakibaei
{"title":"人工智能在未来建筑项目有效执行过程中的应用","authors":"Roozbeh Shakibaei","doi":"10.9734/jemt/2024/v30i61215","DOIUrl":null,"url":null,"abstract":"The construction industry currently constitutes 13% of the global gross domestic product (GDP), with projections indicating an 85% increase in value to $15.5 trillion by 2030. The widespread adoption of information technology (IT) has significantly enhanced the integration of disparate data in construction project environments. Consequently, the construction sector including full construction value chain, is undergoing a transformative phase. The increasing investment in artificial intelligence (AI) makes it impossible to keep pace with its rapid advancements. Hence, this study aims to examine the role of AI in facilitating the effective execution of construction projects in the future. This research employs a document analysis approach and scrutinizes 20 relevant papers from both domestic and international scientific databases. Methodologically, this study adopts an applied research approach, and based on the method of data collection, it is considered a descriptive survey method. Therefore, a questionnaire was designed and distributed among 100 experts and practitioners familiar with AI concepts in Tehran for data collection to conduct a census-style field study. Subsequently, Smart PLS software was employed for data analysis. The findings not only validate the model's reliability, validity and fit but also present solutions and pertinent issues related to challenges concerning AI future role in enhancing project execution efficacy.","PeriodicalId":502721,"journal":{"name":"Journal of Economics, Management and Trade","volume":"26 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence in the Effective Execution Process of Construction Projects in the Future\",\"authors\":\"Roozbeh Shakibaei\",\"doi\":\"10.9734/jemt/2024/v30i61215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The construction industry currently constitutes 13% of the global gross domestic product (GDP), with projections indicating an 85% increase in value to $15.5 trillion by 2030. The widespread adoption of information technology (IT) has significantly enhanced the integration of disparate data in construction project environments. Consequently, the construction sector including full construction value chain, is undergoing a transformative phase. The increasing investment in artificial intelligence (AI) makes it impossible to keep pace with its rapid advancements. Hence, this study aims to examine the role of AI in facilitating the effective execution of construction projects in the future. This research employs a document analysis approach and scrutinizes 20 relevant papers from both domestic and international scientific databases. Methodologically, this study adopts an applied research approach, and based on the method of data collection, it is considered a descriptive survey method. Therefore, a questionnaire was designed and distributed among 100 experts and practitioners familiar with AI concepts in Tehran for data collection to conduct a census-style field study. Subsequently, Smart PLS software was employed for data analysis. The findings not only validate the model's reliability, validity and fit but also present solutions and pertinent issues related to challenges concerning AI future role in enhancing project execution efficacy.\",\"PeriodicalId\":502721,\"journal\":{\"name\":\"Journal of Economics, Management and Trade\",\"volume\":\"26 10\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economics, Management and Trade\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/jemt/2024/v30i61215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economics, Management and Trade","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/jemt/2024/v30i61215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

目前,建筑业占全球国内生产总值(GDP)的 13%,预计到 2030 年,建筑业产值将增长 85%,达到 15.5 万亿美元。信息技术(IT)的广泛应用极大地促进了建筑项目环境中不同数据的整合。因此,包括整个建筑价值链在内的建筑行业正在经历一个转型阶段。对人工智能(AI)的投资不断增加,使其无法跟上快速发展的步伐。因此,本研究旨在探讨人工智能在未来促进建筑项目有效执行方面的作用。本研究采用文献分析法,仔细研究了国内外科学数据库中的 20 篇相关论文。在方法上,本研究采用应用研究方法,并根据数据收集方法,将其视为描述性调查方法。因此,本研究设计了一份调查问卷,并在德黑兰 100 名熟悉人工智能概念的专家和从业人员中进行了数据收集,以开展普查式的实地研究。随后,采用 Smart PLS 软件进行数据分析。研究结果不仅验证了模型的可靠性、有效性和拟合性,还针对人工智能未来在提高项目执行效率方面的作用所面临的挑战提出了解决方案和相关问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in the Effective Execution Process of Construction Projects in the Future
The construction industry currently constitutes 13% of the global gross domestic product (GDP), with projections indicating an 85% increase in value to $15.5 trillion by 2030. The widespread adoption of information technology (IT) has significantly enhanced the integration of disparate data in construction project environments. Consequently, the construction sector including full construction value chain, is undergoing a transformative phase. The increasing investment in artificial intelligence (AI) makes it impossible to keep pace with its rapid advancements. Hence, this study aims to examine the role of AI in facilitating the effective execution of construction projects in the future. This research employs a document analysis approach and scrutinizes 20 relevant papers from both domestic and international scientific databases. Methodologically, this study adopts an applied research approach, and based on the method of data collection, it is considered a descriptive survey method. Therefore, a questionnaire was designed and distributed among 100 experts and practitioners familiar with AI concepts in Tehran for data collection to conduct a census-style field study. Subsequently, Smart PLS software was employed for data analysis. The findings not only validate the model's reliability, validity and fit but also present solutions and pertinent issues related to challenges concerning AI future role in enhancing project execution efficacy.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信