Innovative Changes in Quantity Surveying Practice through BIM, Big Data, Artificial Intelligence and Machine Learning

Journal article

Seidu, RD, Young, BE, Clack, J, Adamu, Z and Robinson, H (2020). Innovative Changes in Quantity Surveying Practice through BIM, Big Data, Artificial Intelligence and Machine Learning. Applied Science University Journal of Natural Science.. 4 (1), pp. 37-47. https://doi.org/10.18576/asuj/040105
AuthorsSeidu, RD, Young, BE, Clack, J, Adamu, Z and Robinson, H
Abstract

Like many construction industry professions, quantity surveying (QS) has been around for many years and has undergone many changes to reflect developments within the wider industry and society. The proliferation of computers into the design process starting from the 1980’s leading up to the rise of Building Information Modelling has particularly led to significant changes in the design and construction landscape. In the UK for instance, the proliferation of BIM and possible demise of traditional Bill of Quantities, with the concurrent rise of smart buildings/cities with exploitation of Big Data (BD), artificial intelligence (AI) and Machine Learning (ML). It implies that QS practices need to reflect on emerging products and services that can promote construction quality and productivity as well as their own professional development. With the decline of traditional QS roles and increased focus on speed of construction, there may be opportunities for different roles for quantity surveyors when dealing with data-driven needs of advanced clients such as BIM managers and Project managers. Additionally, there is need to improve the market value for traditional QS practices when dealing with less innovative clients with less time constraints, which inadvertently contributes to a skills gap which will allow practices to charge more for the traditional services. This study is an exploratory research based on secondary data, which is aim at understanding BIM adoption and related technical advancements that represent innovative and emerging roles for QS professionals to meet the growing demands in the industry. The findings will ignite and support the need for changes in practice, professional education as well as attitudinal behaviour required toward the UK’s Construction 2025 goals.

This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Applied Science University Journal of Natural Sciences following peer review. The definitive publisher-authenticated version Seidu et al (2020) Innovative Changes in Quantity Surveying Practice through BIM, Big Data, Artificial Intelligence and Machine Learning, is available online at: DOI:10.18576/asuj/040105

KeywordsQuantity Surveying; Building Information Model; Innovation; Productivities; Construction
Year2020
JournalApplied Science University Journal of Natural Science.
Journal citation4 (1), pp. 37-47
PublisherNatural Sciences Publishing Corporation
ISSN1764-2210
Digital Object Identifier (DOI)https://doi.org/10.18576/asuj/040105
Publication dates
Print01 Jan 2020
Publication process dates
Accepted23 Oct 2019
Deposited16 Jul 2020
Accepted author manuscript
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Open
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Boonyanan, A., Robinson, H., Naoum, S. and Fong, D. (2011). Team Relationship and Knowledge Management in Construction Projects in Thailand Part 1: Network Relationship Analysis Using UCINET Software. Journal of Architectural/Planning Research and Studies. 8 (2), pp. 139-152. https://doi.org/10.56261/jars.v8i2.168617
Relationship and knowledge management among construction development project members in Thailand: the clients' perspective
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