Ayinla, K; Saka, A; Seidu, R and Madanayake, U (2023) The impact of artificial intelligence on construction costing practice. In: Tutesigensi, A and Neilson, C J (eds.) Proceedings of 39th Annual ARCOM Conference, 4-6 September 2023, University of Leeds, Leeds, UK.
Abstract
Cost estimation is a crucial process in the construction sector as the efficiency of the overall project cost serves as one metric in determining project success. Prevailing traditional approach suffers from human subjectivity and bias which affect accuracy. With the development and adoption of Artificial Intelligence (AI) such as the use of machine learning (ML) and deep learning (DL) algorithms, the construction industry is experiencing brisk technological change and new ways of working, particularly in terms of cost predictions and estimations. However, the application of AI is still in its infancy and the industry still prioritises traditional cost modelling approaches in determining early estimates. This research explores the application of the various ML methods for costing and assesses their usage and application in the costing practice via an exploratory critical review. Findings indicate that ML algorithms would improve the accuracy and efficiency of costing practice but cannot replace the professionals and data availability.
| Item Type: | Conference Paper (Paper) |
|---|---|
| Uncontrolled Keywords: | artificial intelligence AI; artificial neural network ANN; construction sector; cost estimating; machine learning ML |
| Index terms: | construction sector, costing, construction industry, modelling, machine learning, estimate, artificial intelligence, bias, technological change, subjectivity, estimation, artificial neural network, project cost, deep learning, accuracy, efficiency, cost estimating, cost prediction, project success |
| Subjects: | industry analysis, project management theory and practice, probability and distributions, professional development, accounting and finance, performance management, economics, artificial intelligence, financial and cost management, analytical methods, modelling and simulation, human factors and perception, innovation studies |
| Topics: | Cost Management, Business Strategy, Research Practice, Project Management, Information Management, Engineering Principles, Digital Applications, Quality Management |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here