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Akinradewo, O, Aigbavboa, C and Oke, A (2020) Accuracy of road construction preliminary estimate: examining the influencing factors. Built Environment Project and Asset Management, 10(05), 657–71.

  • Type: Journal Article
  • Keywords: Construction industry; Ghana; Project estimate; Project performance; Road projects;
  • ISBN/ISSN: 2044-124X
  • URL: https://doi.org/10.1108/BEPAM-11-2019-0101
  • Abstract:
    Preparation of preliminary estimate is difficult owing to the lack of full project details in the early phases of the construction project. This paper seeks to assess the estimation techniques used for road projects and the critical factors affecting their accuracy in the Ghanaian construction industry.Design/methodology/approach Quantitative research design was adopted and questionnaire was designed to retrieve data. The target population were engineers and quantity surveyors who were contacted using an e-questionnaire through their professional bodies owing to location constraints. Retrieved data were analysed using descriptive and exploratory factor analysis. In order to compare the opinions of the respondents, the Mann–Whitney U-test was employed.Findings The survey revealed that subjective, parametric, comparative and analytical estimations are in use in Ghana. The most critical factors influencing the accuracy of estimation techniques are improper project planning, insufficient preliminary site investigation and usage of shortcuts, among others.Research limitations/implications This study was limited to Accra, Ghana, due to time and distance constraint.Practical implications For accuracy of preliminary estimates to be improved, estimators being the custodian of the estimate are expected to be devoid of errors such as arithmetic calculation errors, inaccurate quantity measurement and error of omission. The usage of estimating software can eliminate these human errors.Originality/value The study will assist policymakers and stakeholders in aligning mitigative actions for factors influencing preliminary estimate of road projects with defined clusters rather than basic ranks. With attention focussed on the characteristics of each cluster, accuracy of preliminary estimate can be improved.

Alshihre, F, Chinyio, E, Nzekwe-Excel, C and Daniel, E I (2020) Improving clients’ satisfaction in construction projects: the case of Saudi Arabia. Built Environment Project and Asset Management, 10(05), 709–23.

Hu, W and Panthi, K (2020) Project status reporting system for pipeline relocation programs. Built Environment Project and Asset Management, 10(05), 693–708.

Leo-Olagbaye, F and Odeyinka, H A (2020) An assessment of risk impact on road projects in Osun State, Nigeria. Built Environment Project and Asset Management, 10(05), 673–91.

Oshodi, O S, Awuzie, B O, Akotia, J, Ademiloye, A S and Ngowi, A (2020) A bibliometric analysis of recycled concrete research (1978–2019). Built Environment Project and Asset Management, 10(05), 725–36.

Zanni, M, Ruikar, K and Soetanto, R (2020) Systematising multidisciplinary sustainable building design processes utilising BIM. Built Environment Project and Asset Management, 10(05), 637–55.