Managing equipment rentals: Unreliable fleet, impatient customers, and finite commitment capacity

Mohammad Firouz, Linda Li and Burcu B. Keskin

Production and Operations Management, 2022, vol. 31, issue 11, 3963-3981

Abstract: In this paper, we discuss fleet size decisions of an equipment rental firm. The availability of the rental equipment depends on the fleet size of the firm and has a direct impact on its profitability. In our setting, we allow for partial backordering, reneging, and finite commitment capacity. Moreover, we explicitly consider the breakdown possibility of the available equipment fleet. We develop an efficient recursive algorithm to solve the underlying two‐dimensional stochastic single‐player model. Our algorithm determines the global optimal fleet size of the firm for the same reneging and equipment return rates. Our extensive managerial insights quantify the behavior of various performance measures in the single‐player model with regard to repair performance of the firm, customer impatience level, traffic intensity, and equipment rental revenue. We demonstrate that by applying our model to a real case, there is a potential of more than a 4% (400,000 USD) increase in total daily profits. Extending our model to a two‐player game, we propose an approximation heuristic to derive closed‐form solutions to estimate equilibrium fleet sizes under complete information. Using our heuristic as the initial solution, we develop a simulation model to determine the exact equilibrium fleet sizes and draw a detailed comparison between the two‐player and single‐player models.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.1111/poms.13796

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:31:y:2022:i:11:p:3963-3981

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1937-5956

Access Statistics for this article

Production and Operations Management is currently edited by Kalyan Singhal

More articles in Production and Operations Management from Production and Operations Management Society
Bibliographic data for series maintained by Wiley Content Delivery ().