Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/223364
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dc.titleEFFECTIVENESS OF INVESTMENT ON INFORMATION TECHNOLOGY INTELLIGENCE FOR CONSTRUCTION SAFETY AND RISK MANAGEMENT
dc.contributor.authorCHEN YANFEI
dc.date.accessioned2010-06-02T03:18:58Z
dc.date.accessioned2022-04-22T20:31:32Z
dc.date.available2019-09-26T14:14:10Z
dc.date.available2022-04-22T20:31:32Z
dc.date.issued2010-06-02T03:18:58Z
dc.identifier.citationCHEN YANFEI (2010-06-02T03:18:58Z). EFFECTIVENESS OF INVESTMENT ON INFORMATION TECHNOLOGY INTELLIGENCE FOR CONSTRUCTION SAFETY AND RISK MANAGEMENT. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/223364
dc.description.abstractWith the advancement in information technology (IT), many IT risk assessment tools have been produced which provide better hazard identification levels, efficient analysis and recommendations for control measures. The research hypotheses are whether investment on these tools renders efficiency and are Singapore contractors ready to adopt the use of IT risk assessment tools. A survey questionnaire was sent to 300 contractors regarding a recently completed project on the resources spent on safety items, including IT intelligence, and the usage of IT intelligence for risk management. From the responses, 93.3% of them use Microsoft Office Excel spreadsheet for risk assessment work. 83.3% of them are aware that IT intelligence tools are effective in safety and risk management but 46.7% do not think that an investment in IT risk assessment tools will be effective. One-sample t-test results are generated. For factors on the use of Microsoft Office tools in safety and risk management, they are the company practice and culture of using the tools for most work, and the availability of such tools at every workplace. The identified significant requirements for IT risk assessment tools are the ability in hazard identification, ability to apply for big projects, and ease in the understanding of procedures. Based on these factors, five regression models are produced for IT Intelligence Investment, out of which three are accepted in explaining the investment inclination levels for IT risk assessment tools. Better understanding can then be drawn on the likelihood of investment by different types of contractor firms.
dc.language.isoen
dc.sourcehttps://lib.sde.nus.edu.sg/dspace/handle/sde/1083
dc.subjectBuilding
dc.subjectProject and Facilities Management
dc.subjectTeo Ai Lin Evelyn
dc.subject2009/2010 PFM
dc.subjectConstruction IT risk assessment
dc.subjectConstruction IT risk management
dc.typeDissertation
dc.contributor.departmentBUILDING
dc.contributor.supervisorTEO AI LIN EVELYN
dc.description.degreeBachelor's
dc.description.degreeconferredBACHELOR OF SCIENCE (PROJECT AND FACILITIES MANAGEMENT)
Appears in Collections:Bachelor's Theses

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