Evaluation of carsharing network's growth strategies through discrete event simulation

  • Authors:
  • Ahmed El Fassi;Anjali Awasthi;Marco Viviani

  • Affiliations:
  • CIISE, Concordia University, 1515 Sainte-Catherine West, Montréal, Canada EV7 640;CIISE, Concordia University, 1515 Sainte-Catherine West, Montréal, Canada EV7 636;Business Development and Public Relations, Communauto Inc. 1117, Sainte-Catherine West, Bur. 806, Montréal, Canada H3B 1H9

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2012

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Abstract

Carsharing organizations are nowadays faced with the emergence of new markets due to the growing popularity of their services. To keep up with the growing demand, they have to constantly adapt their network and balance their stations' capacities by implementing new strategies. These strategies involve creation of new carsharing stations, increasing the capacity of stations, merging or demerging carsharing stations etc. Currently, the decision makers rely on an intuitive strategy selection process which often results in inadequate decisions being made representing an immediate loss in resources, time and market penetration. This paper presents a discrete event simulation based decision support tool that assists the decision makers in selecting best network growth strategies to implement for meeting adequately the demand growth while maximizing the members' satisfaction level and minimizing the number of vehicles used. Our discrete event simulation model allows modeling the activities at any given set of carsharing stations, regardless of their number and capacities. A benchmarking comparison of different potential strategies is done. An application of the proposed model on a region of Communauto's Montreal (Quebec, Canada) carsharing network is provided.