PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO)
Version 1
: Received: 16 March 2021 / Approved: 17 March 2021 / Online: 17 March 2021 (17:01:02 CET)
How to cite:
Abazid, M.; Gökçekuş, H.; Celik, T. Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO). Preprints2021, 2021030455. https://doi.org/10.20944/preprints202103.0455.v1
Abazid, M.; Gökçekuş, H.; Celik, T. Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO). Preprints 2021, 2021030455. https://doi.org/10.20944/preprints202103.0455.v1
Abazid, M.; Gökçekuş, H.; Celik, T. Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO). Preprints2021, 2021030455. https://doi.org/10.20944/preprints202103.0455.v1
APA Style
Abazid, M., Gökçekuş, H., & Celik, T. (2021). Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO). Preprints. https://doi.org/10.20944/preprints202103.0455.v1
Chicago/Turabian Style
Abazid, M., Hüseyin Gökçekuş and Tahir Celik. 2021 "Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO)" Preprints. https://doi.org/10.20944/preprints202103.0455.v1
Abstract
This research is aimed at evaluating two different scenarios, firstly, appraising the impacts of employing the concepts of Total Quality Management (TQM) to the construction projects in Saudi Arabia. The results of the study were obtained through utilization of a descriptive analytical approach, where 300 questionnaires were distributed to engineering firms and companies with a response rate of 200 questionnaires, hence achieving the study sample for this research. The data gathered was analyzed by applying the Statistical Package for Social Science (SPSS) program and calculating the Relative importance index (RII) and the mean values. From the research conducted, the outcomes showed that the management’s ability to commit using TQM while applying BIM obtained a relative importance of (0.717), while the relative importance for the management’s ability to commit using TQM without the application of BIM is (0.552). The results showed that construction projects in Saudi Arabia still sustain setbacks from applying TQM concepts and suffer from the lack of administrative, scientific and technical applications. In a second scenario, a hybridized support vector regression (SVR) Harris-hawks optimization (HHO) (i.e., SVR-HHO) were used to predict the TQM. The performance accuracy of the models was checked through three different evaluation metrics namely; mean square error (MSE), correlation co-efficient (CC) and Nash-Sutcliffe efficiency (NSE). the hybridized emerging SVR-HHO outperformed the other two data driven approaches in both the training and testing stages based on the employed evaluation metrics. Overall, the obtained results showed that both the machine learning and metaheuristic approaches were capable of predicting TQM.
Keywords
Total Quality Management; construction projects; Saudi Arabia; Harris-hawks optimization; support vector regression
Subject
Engineering, Automotive Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
