Artificial Intelligence (AI)-Based Technology Adoption in the Construction Industry: A Cross National Perspective Using the Technology Acceptance Model
Author:
Affiliation:
1. Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Suji-gu, Yongin-si 16890, Gyeonggi-do, Republic of Korea
2. School of Computing and Engineering, University of East London, London E15 4LZ, UK
Abstract
Funder
the Ministry of Land, Infrastructure and Transport
Korean government
Publisher
MDPI AG
Subject
Building and Construction,Civil and Structural Engineering,Architecture
Link
https://www.mdpi.com/2075-5309/13/10/2518/pdf
Reference128 articles.
1. Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges;Abioye;J. Build. Eng.,2021
2. Building the future of the construction industry through artificial intelligence and platform thinking;Oprach;Digit. Welt,2019
3. Chui, M. (2017). Artificial Intelligence the Next Digital Frontier, McKinsey and Company Global Institute.
4. Mohamed, M.A., and Mohamad, D. (2021). AIP Conference Proceedings, AIP Publishing.
5. Heo, S., Han, S., Shin, Y., and Na, S. (2021). Challenges of data refining process during the artificial intelligence development projects in the architecture, engineering and construction industry. Appl. Sci., 11.
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Exploring The Role of Digital Literacy in University Students' Engagement with AI through the Technology Acceptance Model;Sakarya University Journal of Education;2024-07-22
2. A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle;Buildings;2024-07-11
3. Investigating influencing factors of learning satisfaction in AI ChatGPT for research: University students perspective;Heliyon;2024-06
4. Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective;Heliyon;2024-06
5. Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study;Heliyon;2024-04
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3