1887
Volume 2022 Number 2
  • EISSN: 2223-506X

Abstract

This study aims to examine the causes of delay in construction projects, particularly in the case of infrastructure projects in Qatar. The most critical delay causes were analyzed in the perception of the project’s three participants: clients, contractors, and consultants. A literature review was conducted to highlight possible delay causes in other countries. There were gaps in detecting the causes of delay due to the lack of studies on Qatar infrastructure projects. The deductive approach has been used in this study for the quantitative method. It provides a new framework or theory for identifying the causes of delay. The quantitative method used a questionnaire that was created through Survey Monkey. The number of participants was one hundred thirty-three. The questionnaire included forty-one questions in four sections, one sheet for participant information, nine questions about personal data, thirty questions about delay causes, and two questions about delay effects. The data analysis was conducted on a questionnaire to rank the causes of delays by the Relative Importance Index (RII) method. Further analysis was undertaken to interpret the data by regression analysis. The results showed that client changing orders during construction was the most significant delay cause in Qatar infrastructure projects. The research aim was achieved by meeting its objectives. Several recommendations were suggested to reduce delays’ influence on Qatar's infrastructure projects. Research limitations were identified for this study.

Loading

Article metrics loading...

/content/journals/10.5339/connect.2022.spt.5
2022-10-09
2024-04-24
Loading full text...

Full text loading...

/deliver/fulltext/connect/2022/2/connect.2022.spt.5.html?itemId=/content/journals/10.5339/connect.2022.spt.5&mimeType=html&fmt=ahah

References

  1. Sambasian M, Soon YW. Causes and effects of delays in Malaysian construction industry. International Journal of project management. 2007 Jul 1; 25:(5):517-26.
    [Google Scholar]
  2. Olawale YA, Sun M. Cost and time control of construction projects: inhibiting factors and mitigating measures in practice. Construction management and economics. 2010 May 1; 28:(5):509-26.
    [Google Scholar]
  3. Frimpong Y, Oluwoye J, Crawford L. Causes of delay and cost overruns in construction of groundwater projects in a developing countries; Ghana as a case study. International Journal of project management. 2003 Jul 1; 21:(5):321-6.
    [Google Scholar]
  4. Assaf SA, Al-Hejji S. Causes of delay in large construction projects. International journal of project management. 2006 May 1; 24:(4):349-57.
    [Google Scholar]
  5. Chan DW, Kumaraswamy MM. A comparative study of causes of time overruns in Hong Kong construction projects. International Journal of project management. 1997 Feb 1; 15:(1):44-63.
    [Google Scholar]
  6. Kometa ST, Olomolaiye PO, Harris FC. Attributes of UK construction clients influencing project consultants' performance. Construction Management and economics. 1994 Sep 1; 12:(5):433-43.
    [Google Scholar]
  7. Alaghbari W, Kadir MRA, Salim A, Ernawati MK. The significant factors causing a delay of building construction projects in Malaysia. Engineering, Construction and Agricultural Management. 2007; 14:(2):192-206.
    [Google Scholar]
  8. Al‐Kharashi A, Skitmore M. Causes of delays in Saudi Arabian public sector construction projects. Construction Management and Economics. 2009 Jan 1; 27:(1):3-23.
    [Google Scholar]
  9. Al-Hammadi S, Nawab MS. Project Time Overruns in Saudi Arabian Construction Industry. International Journal of Scientific and Engineering Research. 2016; 7:(2):555-60.
    [Google Scholar]
  10. Senouci A, Ismail A, Eldin N. Time delay and cost overrun in Qatari public construction projects. Procedia engineering. 2016 Jan 1;164:368-75.
    [Google Scholar]
  11. Cumming G, Finch S. Inference by eye: confidence intervals and how to read pictures of data. American psychologist. 2005 Feb; 60:(2):170-180.
    [Google Scholar]
  12. Soyer E, Hogarth RM. The illusion of predictability: How regression statistics mislead experts. International Journal of Forecasting. 2012 Jul 1; 28:(3):695-711.
    [Google Scholar]
  13. Lee KJ, Wiest MM, Carlin JB. Statistics for clinicians: An introduction to linear regression. Journal of paediatrics and child health. 2014 Dec; 50:(12):940-3.
    [Google Scholar]
  14. Holiday DB, Ballard JE, McKeown BC. PRESS-related statistics: regression tools for cross-validation and case diagnostics. Medicine and science in sports and exercise. 1995 Apr 1; 27:(4):612-20.
    [Google Scholar]
  15. Field A. Discovering statistics using SPSS–SAGE Publications Ltd. London, UK. 2009.
  16. Nunkoo R, Seetanah B, Jaffur ZR, Moraghen PG, Sannassee RV. Tourism and economic growth: A meta-regression analysis. Journal of Travel Research. 2020 Mar; 59:(3):404-23.
    [Google Scholar]
  17. Curran-Everett D. Explorations in statistics: regression. Advances in Physiology Education. 2011 Dec; 35:(4):347-52.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journals/10.5339/connect.2022.spt.5
Loading
/content/journals/10.5339/connect.2022.spt.5
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error