Artificial intelligence (AI) implementation in improving construction site workflow performance
In a wide variety of industries, Artificial Intelligence (AI) is having a significant influence on both productivity and economic expansion. Studies found that Malaysia's AI issues are limited AI expertise in the construction industry, risks of privacy violation due to AI, and confronting cultu...
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| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2024
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| Online Access: | http://eprints.uthm.edu.my/12156/1/P16941_6aa138a88adfb080e79bb3b9de9794a8.pdf%2013.pdf http://eprints.uthm.edu.my/12156/ https://doi.org/10.30880/rmtb.2024.05.01.086 |
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| _version_ | 1833419721083453440 |
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| author | Roslan, Nurul Azreen Izzatie Zainal, Rozlin Abd Rahim, Mohd Hilmi Izwan Kasim, Narimah |
| author_facet | Roslan, Nurul Azreen Izzatie Zainal, Rozlin Abd Rahim, Mohd Hilmi Izwan Kasim, Narimah |
| author_sort | Roslan, Nurul Azreen Izzatie |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | In a wide variety of industries, Artificial Intelligence (AI) is having a significant influence on both productivity and economic expansion. Studies found that Malaysia's AI issues are limited AI expertise in the construction industry, risks of privacy violation due to AI, and confronting cultural obstacles on the construction site. Therefore, the objectives of this research are to identify the influencing factors in the use of AI in improving workflow performance in construction site, to identify the challenges in improving construction site workflow performance and to measure relationships between main influencing factors in the use of AI with main challenges of AI in improving construction site workflow performance. This study specifically targeted G7, a contractor company situated in Johor Bahru, as the respondent. It used a quantitative approach to accomplish all of its objectives. This research examines the 226 viewpoints of Grade 7 contractors in Johor Bahru. The participants received a questionnaire via both face-to-face meetings and a link to a Google form sent via WhatsApp and email. Out of the total number of respondents, 101 individuals, making up 45% of the total, have provided feedback in the questionnaire. The data was analysed for all purposes using SPSS software, including descriptive statistics with frequency and crosstabs. This study identified that the main factors and main challenges respectively management of risks and limited AI expertise in the construction industry were reported with the highest frequency. Meanwhile, the correlation between the main factors and with main challenges with strongest relationship is return on investment with sluggish electrical supply. All of these findings give guidelines and information for contractors to improve overall performance, less risk, and increase efficiency. This study opens the door to more focused interventions and calculated methods to address the intricacies present in improving construction site workflow building projects, which will eventually benefit industry stakeholders |
| format | Conference or Workshop Item |
| id | my.uthm.eprints-12156 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | en |
| publishDate | 2024 |
| record_format | eprints |
| spelling | my.uthm.eprints-121562025-04-14T04:31:14Z http://eprints.uthm.edu.my/12156/ Artificial intelligence (AI) implementation in improving construction site workflow performance Roslan, Nurul Azreen Izzatie Zainal, Rozlin Abd Rahim, Mohd Hilmi Izwan Kasim, Narimah T Technology (General) In a wide variety of industries, Artificial Intelligence (AI) is having a significant influence on both productivity and economic expansion. Studies found that Malaysia's AI issues are limited AI expertise in the construction industry, risks of privacy violation due to AI, and confronting cultural obstacles on the construction site. Therefore, the objectives of this research are to identify the influencing factors in the use of AI in improving workflow performance in construction site, to identify the challenges in improving construction site workflow performance and to measure relationships between main influencing factors in the use of AI with main challenges of AI in improving construction site workflow performance. This study specifically targeted G7, a contractor company situated in Johor Bahru, as the respondent. It used a quantitative approach to accomplish all of its objectives. This research examines the 226 viewpoints of Grade 7 contractors in Johor Bahru. The participants received a questionnaire via both face-to-face meetings and a link to a Google form sent via WhatsApp and email. Out of the total number of respondents, 101 individuals, making up 45% of the total, have provided feedback in the questionnaire. The data was analysed for all purposes using SPSS software, including descriptive statistics with frequency and crosstabs. This study identified that the main factors and main challenges respectively management of risks and limited AI expertise in the construction industry were reported with the highest frequency. Meanwhile, the correlation between the main factors and with main challenges with strongest relationship is return on investment with sluggish electrical supply. All of these findings give guidelines and information for contractors to improve overall performance, less risk, and increase efficiency. This study opens the door to more focused interventions and calculated methods to address the intricacies present in improving construction site workflow building projects, which will eventually benefit industry stakeholders 2024-06-30 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/12156/1/P16941_6aa138a88adfb080e79bb3b9de9794a8.pdf%2013.pdf Roslan, Nurul Azreen Izzatie and Zainal, Rozlin and Abd Rahim, Mohd Hilmi Izwan and Kasim, Narimah (2024) Artificial intelligence (AI) implementation in improving construction site workflow performance. In: RESEARCH IN MANAGEMENT OF TECHNOLOGY AND BUSINESS. https://doi.org/10.30880/rmtb.2024.05.01.086 |
| spellingShingle | T Technology (General) Roslan, Nurul Azreen Izzatie Zainal, Rozlin Abd Rahim, Mohd Hilmi Izwan Kasim, Narimah Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title | Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title_full | Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title_fullStr | Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title_full_unstemmed | Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title_short | Artificial intelligence (AI) implementation in improving construction site workflow performance |
| title_sort | artificial intelligence (ai) implementation in improving construction site workflow performance |
| topic | T Technology (General) |
| url | http://eprints.uthm.edu.my/12156/1/P16941_6aa138a88adfb080e79bb3b9de9794a8.pdf%2013.pdf http://eprints.uthm.edu.my/12156/ https://doi.org/10.30880/rmtb.2024.05.01.086 |
| url_provider | http://eprints.uthm.edu.my/ |