33
Views
2
CrossRef citations to date
0
Altmetric
Theoretical Paper

Optimal multi-period service capacity allocation and pricing allowing for uncertain competitive entry

&
Pages 780-789 | Received 01 Jan 2008, Accepted 01 Jan 2009, Published online: 21 Dec 2017
 

Abstract

A nonlinear programming model is formulated in this paper to determine the optimal scheme of capacity allocation and prices over a multi-period planning horizon for a service provider in the absence and presence of uncertain competitive entry. The model is solved for constant, decreasing, and increasing price sensitivities employing a combination of analytical and numerical methods. The study highlights the importance of advance selling of service prior to its eventual consumption in the spot period and investigates the impact of uncertain competitive entry on the optimal capacity allocation policy and its related profit if the entry is more or less likely or if the rival is more or less influential. The findings of the study reveal that the conclusions drawn from a two-period model are not necessarily generalizable to a model of a multi-period planning horizon.

Acknowledgements

The authors thank the anonymous referees for their valuable comments and suggestions. The authors are also grateful to Dr Rob Blackstock and Dr Jayanta Sarkar for their valuable comments on an earlier version of the paper.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.