The impact of information on transportation systems with strategic customers

Author:

Logothetis Dimitrios1ORCID,Economou Antonis1ORCID

Affiliation:

1. Department of Mathematics National and Kapodistrian University of Athens Panepistemiopolis Athens Greece

Abstract

AbstractNowadays, a transportation station has the possibility to provide its potential passengers with information regarding the arrival times of the successively arriving facilities, the congestion in the station and the space availability of future facilities. Such information influences the behavior of the passengers who think strategically and consequently the throughput and the welfare that are generated by the system. In the present work, we consider a general model of a transportation station where strategic customers arrive according to a Poisson process, the arriving instants of the transportation facilities form a renewal process and the capacities of successively arriving facilities are finite. Customers decide whether to stay or balk based on their expected waiting costs and the probability of being served, conditioning on the information provided. The information may include the capacity of the next facility, the elapsed time from the previous visit of the facility and/or the number of waiting customers in the station. We derive the customer equilibrium strategies and compare the equilibrium throughput and social welfare, under various information structures. We then determine the ideal level of information that should be provided according to the operational and economic parameters of a given system. Providing the elapsed time from the previous visit of the facility is of utmost importance for infrequent transportation visits. On the other hand, revealing the number of waiting customers is the most advantageous piece of information in the case of frequent facility's visits and small mean capacity.

Funder

Hellenic Foundation for Research and Innovation

Publisher

SAGE Publications

Subject

Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research

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