A stochastic approach to professional services firms' revenue optimization

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

11 Scopus Citations
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Author(s)

  • K. K. Lai
  • Ming Wang
  • L. Liang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)971-982
Journal / PublicationEuropean Journal of Operational Research
Volume182
Issue number3
Publication statusPublished - 1 Nov 2007

Abstract

Regarding professional service time as perishable goods, it should be possible to directly migrate the successful airline revenue management techniques to professional services firms (PSFs) for their analogous business characters. However, there are salient differences between airlines and PSFs should be highlighted-the network structure of length-of-continuance and capacity allocation of multifunctional staff. Customers booking to be served from a first continuance time to a last continuance time in consecutive time continuance. Multifunctional professionals should be properly allocated to maximize the benefit. The arrival demands and lengths of service are stochastic in nature. In this paper, we propose a network optimization model for PSFs revenue management under an uncertain environment. Multifunctional staff's capacity allocation is emphasized. The network optimization is in a stochastic programming formulation so as to capture the randomness of the unknown demand (unknown number of arrivals and unknown length of stays). A novel approach of robust optimization techniques is applied to solve the problem. We also discuss strategies for PSFs revenue management to take into account cancellations, early ends, extended continuance and overbooking. We show our proposed model can be modified to adopt these strategic considerations. © 2006 Elsevier B.V. All rights reserved.

Research Area(s)

  • Professional service, Revenue management, Stochastic programming

Citation Format(s)

A stochastic approach to professional services firms' revenue optimization. / Lai, K. K.; Wang, Ming; Liang, L.

In: European Journal of Operational Research, Vol. 182, No. 3, 01.11.2007, p. 971-982.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal