Abstract
The construction industry has a crucial impact on the economy. Data analytics provides a unique opportunity to improve construction decision-making, enhance construction productivity, and reduce construction cost overruns. Although data analytics have tremendous potential to improve strategic decision-making in the construction industry as an ever-increasing volume of data becomes available, it has not been fully exploited on a larger scale in the construction industry due to a lack of proper training and educational materials. Two powerful construction analytics techniques (i.e., forecasting and investment valuation) are introduced that can potentially help address several grand challenges in the construction industry. Advanced forecasting techniques can improve cost estimation accuracy and assist engineers in avoiding a bid loss or a profit loss. Investment valuation techniques assist engineers in identifying the appropriate time to invest, quantifying the investment risks in projects, and determining the optimum value of an investment for maximizing the returns on investments. This book provides theoretical explanations, hands-on practice problems with R code scripts, and exercises for learning the construction industry’s most advanced and valuable data analytics techniques.
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Shahandashti, M., Abediniangerabi, B., Zahed, E., Kim, S. (2023). Introduction to Construction Analytics. In: Construction Analytics. Springer, Cham. https://doi.org/10.1007/978-3-031-27292-9_1
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DOI: https://doi.org/10.1007/978-3-031-27292-9_1
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