1. Proceedings
  2. I3M
  3. 2018
  4. MAS
  5. 10.46354/i3m.2018.mas.003

Linear regression and agent-based modeling approach for equipment market value predict

  • a Lingzi Wu , 
  • b Mostafa Ali , 
  • c Estacio Pereira ,
  • d Simaan M. AbouRizk 
  • a,b,c,d Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Canada T6G 2W2
Cite as
Wu L., Ali M., Pereira E., AbouRizk S.M. (2018). Linear regression and agent-based modeling approach for equipment market value predict. Proceedings of the 17th International Conference on Modeling & Applied Simulation (MAS 2018), pp. 15-21. DOI: https://doi.org/10.46354/i3m.2018.mas.003

Abstract

The acquisition, ownership, and operation costs of construction equipment represent a considerable portion of a general contractor’s budget. The ability to accurately estimate the current market value of equipment is vital for successful fleet management. Although market valuation models have been built, they do not consider the impact of human behavior on selling price. Understanding basic auction mechanisms and the relationships between human behavior and selling price would improve the credibility and accuracy of equipment market value estimation—particularly for construction equipment, which is often sold at auction. This research proposes a hybrid linear regression and simulation modeling approach to uncover patterns in historical equipment resale data and to use these data, in consideration of human behavior, to simulate a typical North American equipment auction. Feasibility of the proposed approach is demonstrated through a case
study.

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