Alqershy, M T and Kishore, R (2023) Construction claims prediction using ann models: A case study of the Indian construction industry. International Journal of Construction Management, 23(6), pp. 1097-1108. ISSN 1562-3599
Abstract
Claims are a major concern in every construction project. With the increasing complexity and size of the construction projects in India, the number and frequency of claims, also bound to increase, which adversely affects the construction environment. So, an early prediction of these claims is crucial to avoid their costly negative impacts. This paper aimed to develop artificial neural network models to predict the frequency of claims in construction projects. Based on a comprehensive literature review, a total of 39 factors causing claims were identified first, and then refined by Delphi interview with 10 experts. Subsequently, a questionnaire was further developed and disseminated to different owners, contractors, and consultants' organizations working in the Indian construction sector, which received 206 valid replies. The questionnaire data were then utilized to develop and validate the construction claims frequency prediction models. For this, an artificial neural network approach was used to construct the models. These models will help the construction professionals in predicting the frequency of occurrence for different types of claims throughout the course of the project and enable them to select the best strategy available to avoid or mitigate their occurrence at an early stage.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial neural networks; causes of claims; construction claims; types of claims |
| Index terms: | owner, case study, construction industry, India, construction professional, literature review, strategy, prediction model, artificial neural network, interview, construction claim, construction sector, complexity, construction project, questionnaire |
| Subjects: | systems engineering, industry analysis, sociology, payment, professional development, production management, Geography, management, prediction and forecasting, data analysis and analytics, modelling and simulation, data collection methods |
| Topics: | Business Strategy, Engineering Principles, Information Management, Research Practice, Project Management, Geographical Context, Stakeholder Management, Contract Administration |
| Descriptive scope: | 5 PCTEA |
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