scholarly journals Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia Validated with Hybridized Emerging Harris Hawks Optimization (HHO)

2021 ◽  
Author(s):  
Mohammad Abazid ◽  
Hüseyin Gökçekuş ◽  
Tahir Celik
Keyword(s):  
Saudi Arabia ◽  
Construction Projects ◽  
Evaluation Metrics ◽  
Support Vector ◽  
Relative Importance ◽  
Total Quality ◽  
Mean Values ◽  
Performance Accuracy ◽  
Importance Index ◽  
The Mean

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.

scholarly journals Implementation of TQM and the Integration of BIM in the Construction Management Sector in Saudi Arabia

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Mohammad Abazid ◽  
Hüseyin Gökçekuş ◽  
Tahir Çelik
Keyword(s):  
Saudi Arabia ◽  
Time Management ◽  
Construction Projects ◽  
Response Rate ◽  
Relative Importance ◽  
Total Quality ◽  
Mean Values ◽  
Safety Regulations ◽  
Importance Index ◽  
The Mean

Total Quality Management (TQM) is based on the conceptions of managing and enhancing the success of construction projects. When applied, TQM improves execution of time management of project, satisfies clients’ needs, minimizes the expenses and increases the profit of contractor, and fulfils safety regulations on the construction site. This research is aimed at evaluating the impacts of employing the concepts of 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.

Causes of Delay in Budget Hotel Construction Projects

2014 ◽  
Vol 5 (3) ◽  
pp. 49-63 ◽  
Author(s):  
Milind T. Phadtare
Keyword(s):  
Construction Projects ◽  
Business Group ◽  
Relative Importance ◽  
Joint Effort ◽  
Indian Context ◽  
Importance Index ◽  
Project Participants ◽  
Causes Of Delays ◽  
Industry Training

Delay in construction projects is a universal phenomenon. However, the topic is not adequately studied in the Indian context. This paper attempts to identify the causes of delays in construction of budget hotels in India and suggest remedies to avoid some delays. A business group constructing budget hotels across the country is approached for this study. Forty causes of delay have been identified and Relative Importance Index was calculated. The contribution of each category of causes of delay to overall delay in the projects was computed. Remedies such as, joint effort of the participants of the industry, training, coordination between project participants and project timing and scheduling are suggested and validated.

scholarly journals Calibration of the depth invariant algorithm to monitor the tidal action of Rabigh City at the Red Sea Coast, Saudi Arabia

2020 ◽  
Vol 12 (1) ◽  
pp. 1666-1678
Author(s):  
Mohammed H. Aljahdali ◽  
Mohamed Elhag
Keyword(s):  
Remote Sensing ◽  
Saudi Arabia ◽  
Wind Speed ◽  
Red Sea ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
Optical Data ◽  
Mean Values ◽  
Sensing Data ◽  
The Mean

AbstractRabigh is a thriving coastal city located at the eastern bank of the Red Sea, Saudi Arabia. The city has suffered from shoreline destruction because of the invasive tidal action powered principally by the wind speed and direction over shallow waters. This study was carried out to calibrate the water column depth in the vicinity of Rabigh. Optical and microwave remote sensing data from the European Space Agency were collected over 2 years (2017–2018) along with the analog daily monitoring of tidal data collected from the marine station of Rabigh. Depth invariant index (DII) was implemented utilizing the optical data, while the Wind Field Estimation algorithm was implemented utilizing the microwave data. The findings of the current research emphasis on the oscillation behavior of the depth invariant mean values and the mean astronomical tides resulted in R2 of 0.75 and 0.79, respectively. Robust linear regression was established between the astronomical tide and the mean values of the normalized DII (R2 = 0.81). The findings also indicated that January had the strongest wind speed solidly correlated with the depth invariant values (R2 = 0.92). Therefore, decision-makers can depend on remote sensing data as an efficient tool to monitor natural phenomena and also to regulate human activities in fragile ecosystems.

scholarly journals Imprecise Imputation as a Tool for Solving Classification Problems with Mean Values of Unobserved Features

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Lev V. Utkin ◽  
Yulia A. Zhuk
Keyword(s):  
Partial Information ◽  
Probability Distributions ◽  
Classification Problem ◽  
Support Vector ◽  
Classification Problems ◽  
Mean Values ◽  
Numerical Examples ◽  
The Standard Model ◽  
The Mean ◽  
Available Information

A method for solving a classification problem when there is only partial information about some features is proposed. This partial information comprises the mean values of features for every class and the bounds of the features. In order to maximally exploit the available information, a set of probability distributions is constructed such that two distributions are selected from the set which define the minimax and minimin strategies. Random values of features are generated in accordance with the selected distributions by using the Monte Carlo technique. As a result, the classification problem is reduced to the standard model which is solved by means of the support vector machine. Numerical examples illustrate the proposed method.

A new approach to the measurement of the quantitative effects of inherent and environmental factors on the composition of the milk of individual cows and of herds, with particular reference to lactose content

1968 ◽  
Vol 35 (1) ◽  
pp. 91-105 ◽  
Author(s):  
J. P. Walsh ◽  
J. A. F. Rook ◽  
F. H. Dodd
Keyword(s):  
Quantitative Estimation ◽  
Relative Importance ◽  
New Approach ◽  
Mean Values ◽  
Stage Of Lactation ◽  
Bulk Milk ◽  
Wide Range ◽  
The Mean ◽  
The Difference ◽  
Effect Of Age

Summary(1) A tentative scheme is proposed for the quantitative estimation of the effects of various factors on one major milk constituent, lactose, from analyses of the milk of individual cows within herds. The potential lactose content in the milk of individual cows is predicted from the observed potassium-to-lactose ratio in the milk, and the difference between the predicted potential and the actual lactose content is partitioned into fractions that are attributed to effects due to age, inter-quarter difference and changes with stage of lactation. The scheme was applied to 2 commercial herds, one (herd A) producing milk of low and the other (herd B) milk of normal SNF content.(2) Lactation mean values for fat, SNF and lactose contents of the milk of individual cows showed a wide range of the same order in each of the 2 herds. Of the mean difference in SNF percentage of 0·30 between the herds, 0·14, or 47%, was due to a difference in lactose content.(3) The predicted potential milk lactose content of the cows in the 2 herds ranged from 5·04 to 5·66 (g/100 g milk water). Herd mean values were 5·394 for herd A and 5·244 for herd B.(4) Herd mean values for the effect on the lactose content (g/100 g milk water) of age, of changes with stage of lactation and of inter-quarter difference were −0·127, −0·080, and 0·073 respectively in herd A, and −0·197, −0·058 and −0·078, respectively, in herd B.(5) The relative importance of the various factors in accounting for differences between the herds in the lactose content of their bulk milk were: predicted potential lactose content 61%, effect of age 28%, effect of changes with stage of lactation 9% and effect of inter-quarter difference 2%.(6) The errors attached to the estimation of potential milk lactose content and the effects of age, of changes with stage of lactation and of inter-quarter difference are discussed.

scholarly journals Assessment of Delay Factors in Saudi Arabia Railway/ Metro Construction Projects

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Raja Khan Mohammed Gopang ◽  
◽  
Qadir Buxalias Imran ◽  
Sasitharan Nagapan ◽  
◽  
...  
Keyword(s):  
Saudi Arabia ◽  
Construction Industry ◽  
Construction Projects ◽  
Railway Construction ◽  
Design Changes ◽  
Importance Index ◽  
Control Procedures ◽  
Labor Skills ◽  
Spearman’S Correlation ◽  
Delay Factor

Railway construction industry has devoted vast amount of resources into advancing the management and technology of railway construction, yet most project in this industry often failed to comply with the set deadlines and budget limits. This study was conducted to recognize the critical factors that are causing delays in the construction of Riyadh Metro project, Saudi Arabia. From a thorough literature review, thirty-six (36) factors causing delays were identified which were then distributed to qualified industry experts in a survey questionnaire. A total of 105 respondents were gathered during the data collection. The datawas then evaluated statistically by utilizing different calculation tools that are frequency adjusted importance index for the delay factor ranking, and Spearman's correlation coefficient for the link between two different set of data. The result of this research identified the top five main delay factors to the railway construction projects which are “Client's decision-making process and changes in control procedures”, “Design Errors (including ambiguities and discrepancies of details/specifications)”, “Labor skills level”, “Design changes by Client or Consultant” and lastly, “Issues regarding permissions/ approvals from other stakeholders”.Finally, this study is hoped to help the railway construction industry in bettering itself by highlighting which issues should be focused on to counter the delays and reduce downtimes.

scholarly journals Challenges and Barriers of Building Information Modeling Adoption in the Saudi Arabian Construction Industry

2020 ◽  
Vol 14 (1) ◽  
pp. 98-110
Author(s):  
Mohammed A. Al-Hammadi ◽  
Wei Tian
Keyword(s):  
Saudi Arabia ◽  
Construction Industry ◽  
Construction Projects ◽  
Building Information Modeling ◽  
Saudi Arabian ◽  
Information Modeling ◽  
Relative Importance ◽  
Kingdom Of Saudi Arabia ◽  
Current State ◽  
Building Information

Background: The Building Information Modeling (BIM) revolution can provide a solution for problems in the Saudi Arabian construction industry and improve its outcomes. Though this technology is increasingly and rapidly adopted in advanced countries, developing countries such as Saudi Arabia and the Gulf Cooperation Council countries (GCC) are still in the early stages of BIM adoption. Objective: This study investigates the current state of BIM technology adoption by exploring and analyzing the critical challenges and barriers to BIM technology utilization in the construction sectors. Methods: The quantitative approach is adopted via a survey questionnaire distributed to participants in the field of construction projects in the Architecture, Engineering, and Construction (AEC) industry. A total of 228 questionnaires are collected and analyzed using the statistical packaging for social science software. Results: Findings show that several significant barriers negatively affect the utilization of BIM. The major barriers to BIM adoption are related to the lack of demand, lack of experts, and poor awareness of BIM benefits, which have relative importance indexes of (RII = 89.910), (RII = 88.475), and (RII = 87.130), respectively. Meanwhile, unspecified data responsibilities, difficulty of learning BIM, lack of data sharing, and sufficient current technology constitute the lowest-ranking barriers with their relative importance indexes of (RII = 71.704), (RII = 70.807), (RII = 66.413), and (RII = 65.874), respectively. Conclusion: The findings of this study are highly significant and can become more helpful and interesting if further research can measure the methodologies to implement BIM technology in the Kingdom of Saudi Arabia.

scholarly journals Factors Affecting Contractors’ Bidding Decisions for Construction Projects in Saudi Arabia

Buildings ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 33 ◽  
Author(s):  
Mohammad Alsaedi ◽  
Sadi Assaf ◽  
Mohammad Hassanain ◽  
Abdullatif Abdallah
Keyword(s):  
Saudi Arabia ◽  
Construction Projects ◽  
Critical Factors ◽  
Start Time ◽  
Design Quality ◽  
Factors Affecting ◽  
Importance Index ◽  
Efficiency And Effectiveness ◽  
Major Factors ◽  
Level Of Agreement

One of the critical decisions taken by contractors is whether or not to bid for a project. This is due to the complexity and uncertainty surrounding this decision, which is influenced by many factors. Given the above challenge, this study aimed to uncover the critical factors affecting the contractors’ bidding decisions in Saudi Arabia-based construction projects. A questionnaire survey, which consisted of 31 factors, was distributed to first-, second- and third-grade contractors. In total, 67 responses were obtained. Median and relative importance index (RII) techniques were adopted for ranking the most critical factors. Based on the received responses, the top six critical factors were “size of the job”, “type of the job”, “company’s strength in the industry”, “designer/design quality”, “rate of return”, and “project cash flow”. The least significant factors were “job start time” and “labor environment (union/nonunion/cooperative)”. The findings of this study show a level of agreement among all contractors about the critical factors. The findings would benefit contractors and subcontractors by increasing their understanding of the major factors affecting the bidding decision process. Contractors armed with such valuable information will be better able to enhance their bidding decision-making process in terms of efficiency and effectiveness.

Relative Importance of Factors Affecting Construction Hazards in the Design Phase

2013 ◽  
Vol 330 ◽  
pp. 862-866
Author(s):  
Seyyed Shahab Hosseinian ◽  
Zahra Jabbarani Torghabeh ◽  
Aziruddin Ressang
Keyword(s):  
Construction Projects ◽  
Relative Importance ◽  
Design Phase ◽  
Construction Sites ◽  
Index Method ◽  
Safety Level ◽  
Factors Affecting ◽  
Importance Index ◽  
Construction Accidents ◽  
Construction Hazards

dentifying the root causes of construction accidents has indicated that not only contractors but designers and architectures are capable of influencing construction workers safety. The aim of this study is to investigate and prioritize factors affecting construction hazards in the design phase. To achieve the aim of this study, a questionnaire survey was distributed among respondents randomly selected from construction sites within Malaysia. Relative Importance Index method was used to prioritize factors in order of level of effect on construction hazards. The results indicated that Lack of designers safety knowledge, Lack of designers knowledge about construction processes and Late involvement of constructors in the design process have the highest level of effect while Lack of safety organizations which evaluates the safety level of design and Few application of components' prefabrication have the lowest level of effect on hazards in the design phase of construction projects.

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