Influential Factors in Estimating and Tendering for Construction Work
1 Department of Surveying, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, 43000 Kajang, Selangor, Malaysia
2 Asia Pacific Logistics Center, Eppendorf Asia Pacific Sdn Bhd, 47600 Subang Jaya, Selangor, Malaysia
3 Department of Quantity Surveying, Faculty of Built Environment, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
4 Department of Real Estate, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
5 Department of Construction Management, Faculty of Technology Management and Business, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Johor, Malaysia
a Corresponding author : email@example.com
Cost estimation, bid/no bid decision, estimating accuracy, and cost overrun are the four main cost estimating issues (MCEI) investigated by many previous researchers from different parts of the world for decades. Factors relating to client characteristics, consultant and design parameters, contractor attributes, project characteristics, contract procedures and procurement methods, and external market conditions  are examined for their influences on those four MCEI separately. However, very little attention is paid on the comparison of factors rankings across those four MCEI. Results from comparing those factors rankings improve the understandings on cost estimating issues. Thus, this study aims to compare the factors rankings across the four MCEI and evaluate the degree of agreement between the four sets of ranks for their influential factors. Four previous studies, each examining factors affecting each of the four MCEI are selected through literature survey for analysis. Influential factors from each previous study are assigned to their related categories: client, consultant, contractor, project, contract, and environment. Kendall’s coefficient of concordance is used to assess interjudge reliability. The computed correlation indicates a moderate degree of association between the four sets of ranks. It is found that the four MCEI are influenced by different factors with different ranks and hence should be treated as different MCEI and be managed differently.
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