A Systematic Review of Construction Scheduling Methods: Trends, gaps, and potential research areas

Conference paper


Ayeni, R., Udeaja, C., Fong, D. and Chen, Y. (2021). A Systematic Review of Construction Scheduling Methods: Trends, gaps, and potential research areas. IDoBE International Conference, London South Bank University, London. London 22 - 23 Nov 2021 London South Bank University.
AuthorsAyeni, R., Udeaja, C., Fong, D. and Chen, Y.
TypeConference paper
Abstract

Construction projects are subject to diverse and complex challenges. However, most construction scheduling methods (CSM) do not adequately consider these complex challenges or the various causes of duration overruns in construction projects. Also, most CSM cannot efficiently process the vast data and the relationship between these factors or variables. It is essential to understand how these factors contribute to project duration overrun, their relationships, and how this information can improve construction project duration estimates. Therefore, to develop a reliable CSM, it is vital to understand the existing approaches to CSM, the gaps and trends. In this study, a total of 148 documents were extracted from Scopus database using Article Title, Abstract, and Keywords in the domain of CSM. The documents were retrieved using a bibliometric search. The search results were analysed using a scientometric approach, and the results were discussed. The bibliometric search suggests that the collected works on literature in the domain of CSM, in general, is increasing. Also, besides identifying influential journals, authors and countries, the study was crucially able to identify the gaps and trends in CSM. The findings show that the application of artificial intelligence (AI), contract time determination system (CTDS), BIM-based scheduling methods are approaches that can be explored further for reliable construction project time estimation. The results will be later discussed in detail as part of ongoing research.

KeywordsConstruction Scheduling Methods (CSM), Scientometric Analysis, Bibliometric, Bibliographic Coupling, Artificial Intelligence
Year2021
PublisherLondon South Bank University
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Print22 Nov 2021
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Deposited08 Dec 2022
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