Impact of environmental concerns on the capacity-pricing problem in the car rental business

摘要

One of the main decisions that a car rental company has to make regards the definition of the fleet size and mix, i.e., the capacity to meet demand. This demand is highly unpredictable and price-sensitive; thus, the definition of the prices charged influences capacity decisions. Moreover, capacity decisions are also linked to other company strategies to meet demand, such as offering upgrades or transferring empty cars between stations. Typically, these problems are tackled focusing on the maximization of profits, disregarding the environmental impacts associated with these decisions. There is a growing need for models and analytical tools that can support decisions considering the trade-off between profit and environmental impact in mobility. Therefore, this work incorporates environmental concerns into the capacity-pricing problem for car rental, proposing a bi-objective model to tackle the trade-off between profit and environmental impact. The Life Cycle Assessment method is applied not only to vehicles but also to fuel to define environmental parameters accurately. Four types of vehicles are considered: internal combustion engine vehicles, hybrids, hybrids plug-in, and electric vehicles. Solving multi-objective models is a computationally challenging problem, which requires efficient and applicable methods. These methods can support policy and business decisions in a real-world context, running different scenarios and evaluating solutions under varying conditions. Due to its efficiency in solving bi-objective models, an Epsilon-constraint method is developed and applied in diverse situations to retrieve managerial insights. The results obtained enable quantifying the feasible trade-offs, overall showing that, on average, with a decrease of 14.44% in financial results, it is possible to obtain a decrease of 63.41% in environmental impact. Additional insights are also retrieved related to the fleet, fuel, prices and demand.