Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches
The wireless use of radio frequency waves for data acquisition and transfer is known as Radio Frequency Identification (RFID). RFID-based systems have been applied in various fields, including building construction and maintenance. This study aims to evaluate the RFID tools for realizing the sustain...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor and Francis Group
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/114664/ http://psasir.upm.edu.my/id/eprint/114664/1/114664.pdf |
| _version_ | 1848866559713345536 |
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| author | Kineber, Ahmed Farouk Oke, Ayodeji Emmanuel Elshaboury, Nehal Elseknidy, Mohamed Alhusban, Mohammad Zamil, Ahmad Altuwaim, Ayman |
| author_facet | Kineber, Ahmed Farouk Oke, Ayodeji Emmanuel Elshaboury, Nehal Elseknidy, Mohamed Alhusban, Mohammad Zamil, Ahmad Altuwaim, Ayman |
| author_sort | Kineber, Ahmed Farouk |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The wireless use of radio frequency waves for data acquisition and transfer is known as Radio Frequency Identification (RFID). RFID-based systems have been applied in various fields, including building construction and maintenance. This study aims to evaluate the RFID tools for realizing the sustainability of construction projects. The literature was reviewed to obtain secondary data, complemented by a quantitative method involving the administration of a questionnaire to 107 experts in Nigeria using a random sampling method. It was followed by data analysis using the Exploratory Factor Analysis (EFA) approach. Finally, the structural equation modeling-artificial neural network model was applied to prioritize the major constructs. The EFA results demonstrated that RFID deployment areas may be divided into two main categories: hardware and system. The results affirmed the effectiveness of the system tools for RFID implementation in the building industry. Additionally, the hybrid model revealed that system and hardware predictors rank first and second in the RFID implementation areas. The outcomes of this study are important to understanding tools and methodologies related to the fuzziness of RFID for prospective workforces. Furthermore, it is envisaged that the identified RFID tools would enhance the sustainability of building projects. This study lays the foundation for the enhancement of decision-making in building projects. Although these studies have been confined to Nigeria, the findings apply to other developing countries, especially those with similar construction processes and operations. |
| first_indexed | 2025-11-15T14:22:32Z |
| format | Article |
| id | upm-114664 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:22:32Z |
| publishDate | 2024 |
| publisher | Taylor and Francis Group |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1146642025-01-22T07:54:27Z http://psasir.upm.edu.my/id/eprint/114664/ Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches Kineber, Ahmed Farouk Oke, Ayodeji Emmanuel Elshaboury, Nehal Elseknidy, Mohamed Alhusban, Mohammad Zamil, Ahmad Altuwaim, Ayman The wireless use of radio frequency waves for data acquisition and transfer is known as Radio Frequency Identification (RFID). RFID-based systems have been applied in various fields, including building construction and maintenance. This study aims to evaluate the RFID tools for realizing the sustainability of construction projects. The literature was reviewed to obtain secondary data, complemented by a quantitative method involving the administration of a questionnaire to 107 experts in Nigeria using a random sampling method. It was followed by data analysis using the Exploratory Factor Analysis (EFA) approach. Finally, the structural equation modeling-artificial neural network model was applied to prioritize the major constructs. The EFA results demonstrated that RFID deployment areas may be divided into two main categories: hardware and system. The results affirmed the effectiveness of the system tools for RFID implementation in the building industry. Additionally, the hybrid model revealed that system and hardware predictors rank first and second in the RFID implementation areas. The outcomes of this study are important to understanding tools and methodologies related to the fuzziness of RFID for prospective workforces. Furthermore, it is envisaged that the identified RFID tools would enhance the sustainability of building projects. This study lays the foundation for the enhancement of decision-making in building projects. Although these studies have been confined to Nigeria, the findings apply to other developing countries, especially those with similar construction processes and operations. Taylor and Francis Group 2024-09-12 Article PeerReviewed text en cc_by_4 http://psasir.upm.edu.my/id/eprint/114664/1/114664.pdf Kineber, Ahmed Farouk and Oke, Ayodeji Emmanuel and Elshaboury, Nehal and Elseknidy, Mohamed and Alhusban, Mohammad and Zamil, Ahmad and Altuwaim, Ayman (2024) Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches. Cogent Engineering, 11 (1). art. no. 2402052. pp. 1-15. ISSN 2331-1916 https://www.tandfonline.com/doi/full/10.1080/23311916.2024.2402052 10.1080/23311916.2024.2402052 |
| spellingShingle | Kineber, Ahmed Farouk Oke, Ayodeji Emmanuel Elshaboury, Nehal Elseknidy, Mohamed Alhusban, Mohammad Zamil, Ahmad Altuwaim, Ayman Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title | Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title_full | Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title_fullStr | Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title_full_unstemmed | Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title_short | Exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| title_sort | exploring radio frequency identification tools for sustainable construction projects: a hybrid structural equation modeling and deep neural network approaches |
| url | http://psasir.upm.edu.my/id/eprint/114664/ http://psasir.upm.edu.my/id/eprint/114664/ http://psasir.upm.edu.my/id/eprint/114664/ http://psasir.upm.edu.my/id/eprint/114664/1/114664.pdf |