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Feldman, G, Shah, H, Chapman, C, Pärn, E A and Edwards, D J (2017) A systematic approach for enterprise systems upgrade decision-making: Outlining the decision processes. Journal of Engineering, Design and Technology, 15(06), 778-802.

Kwofie, T E, Adinyira, E and Fugar, F (2017) Theoretical and practical implications for engendering project team communication effectiveness in mass housing project delivery in Ghana. Journal of Engineering, Design and Technology, 15(06), 826-44.

Nani, G, Mensah, I and Adjei-Kumi, T (2017) Duration estimation model for bridge construction projects in Ghana. Journal of Engineering, Design and Technology, 15(06), 754-77.

  • Type: Journal Article
  • Keywords: Ghana; artificial neural network; duration; bridge projects
  • ISBN/ISSN:
  • URL: https://doi.org/10.1108/JEDT-04-2017-0029
  • Abstract:
    Purpose A major concern for construction professionals at the rural road agency in Ghana is the problem of fixing contract duration for bridge construction projects in rural areas. The purpose of the study was to develop a tool for construction professionals to forecast duration for bridge projects. Design/methodology/approach In all, 100 questionnaires were distributed to professionals at the Department of Feeder Roads to ascertain their views on the work items in a bill of quantities (BOQ) that impact significantly on the duration of bridge construction projects. Historical data for 30 completed bridge projects were also collected from the same Department. The data collected were executed work items in BOQ and actual durations used in completing the works. The qualitative data were analysed using the relative importance index and the quantitative data, processed and analysed using both the stepwise regression method and artificial neural network (ANN) technique. Findings The identified predictors, namely, in-situ concrete, weight of prefabricated steel components, gravel sub-base and haulage of aggregates, used as independent variables resulted in the development of a regression model with a mean absolute percentage error (MAPE) of 25 per cent and an ANN model with a feed forward back propagation algorithm with an MAPE of 26 per cent at the validation stage. The study has shown that both regression and ANN models are appropriate for predicting the duration of a new bridge construction project. Research limitations/implications The predictors used in the developed models are limited to work items in BOQs only of completed bridge construction projects as well as the small sample size. Practical implications The study has developed a working tool for practitioners at the agency to forecast contract duration for bridge projects prior to its commencement. Originality value The study has quantified the relationship between the work items in BOQs and the duration of bridge construction projects using the stepwise regression method and the ANN techniques.

Oke, A E, Ibironke, O T and Bayegun, O A (2017) Appraisal of reward packages in construction firms: A case of quantity surveying firms in Nigeria. Journal of Engineering, Design and Technology, 15(06), 722-37.

Riaz, Z, Parn, E A, Edwards, D J, Arslan, M, Shen, C and Pena-Mora, F (2017) BIM and sensor-based data management system for construction safety monitoring. Journal of Engineering, Design and Technology, 15(06), 738-53.

Yap, J B H and Lock, A (2017) Analysing the benefits, techniques, tools and challenges of knowledge management practices in the Malaysian construction SMEs. Journal of Engineering, Design and Technology, 15(06), 803-25.