An economic modelling approach for public sector construction workload planning

LI, X., OGIER, J. and CULLEN, J. (2006). An economic modelling approach for public sector construction workload planning. Construction management and economics, 24 (11), 1137-1147.

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Link to published version:: https://doi.org/10.1080/01446190600798960
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    Abstract

    The effectiveness of public sector construction workload planning can be enhanced through employing an economic modelling approach to predict the impact of different workloads on tender price changes. The main problem associated with existing methods used for predicting tender price index (TPI) for construction projects is a lack of robustness when the market becomes unstable. This is due to limited consideration of market conditions in these methods. An economic modelling approach has been developed and applied for public sector construction workload planning in the States of Guernsey where forward planning was required. The developed model overcomes the problem of existing methods—lack of robustness—by correlating TPI of construction projects to demand over capacity ratio of the industry, which represents the industry's economic condition. The model generates the price changes under different planning options associated with different workloads over a five-year planning period. The information is valuable to the public sector in estimating actually required investment. This ensures the feasibility of the plan and the possibility of contribution to the stability of the construction market. The model development and application process developed in this research can be used to assist a planning process for an industry where a demand, capacity and price relationship is applied.

    Item Type: Article
    Uncontrolled Keywords: modelling, construction workload planning, tender price index, demand, capacity
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Sheffield Business School Research Institute > People, Work and Organisation
    Identification Number: https://doi.org/10.1080/01446190600798960
    Page Range: 1137-1147
    Depositing User: Ann Betterton
    Date Deposited: 06 Jun 2008
    Last Modified: 13 Jun 2017 12:44
    URI: http://shura.shu.ac.uk/id/eprint/738

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