A stochastic approach to professional services firms' revenue optimization

被引:7
|
作者
Lai, K. K. [1 ]
Wang, Ming [1 ]
Liang, L. [1 ]
机构
[1] City Univ Hong Kong, Dept Management Sci, Hong Kong, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
revenue management; professional service; stochastic programming;
D O I
10.1016/j.ejor.2006.09.038
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:971 / 982
页数:12
相关论文
共 50 条
  • [21] Re-solving Extended Expected Marginal Seat Revenue Model Using Stochastic Approach
    Petricek, Martin
    Chalupa, Stepan
    Mace, Jan
    Straka, Ivo
    QUALITY-ACCESS TO SUCCESS, 2022, 23 (186): : 151 - 155
  • [22] Stochastic Linear Programming Approach for Portfolio Optimization Problem
    Dao Minh Hoang
    Tran Ngoc Thang
    Nguyen Danh Tu
    Nguyen Viet Hoang
    2021 IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLIED NETWORK TECHNOLOGIES (ICMLANT II), 2021, : 135 - 138
  • [23] A Stochastic Knapsack Game: Revenue Management in Competitions
    Lu, Yingdong
    APPLICATIONS AND APPLIED MATHEMATICS-AN INTERNATIONAL JOURNAL, 2021, 16 (01): : 1 - 11
  • [24] Governance and growth of professional service firms
    Guzak, James Richard
    Rasheed, Abdul A.
    SERVICE INDUSTRIES JOURNAL, 2014, 34 (04) : 295 - 313
  • [25] Customer heterogeneity in revenue management for railway services
    Hetrakul P.
    Cirillo C.
    Journal of Revenue and Pricing Management, 2015, 14 (1) : 28 - 49
  • [26] Optimal Sizing of a BESS Providing Multiple Services to the System: a Stochastic Approach
    Siface, Dario
    2020 17TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET, EEM, 2020,
  • [27] Revenue management model for on-demand IT services
    Liu, Tieming
    Methapatara, Chinnatat
    Wynter, Laura
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2010, 207 (01) : 401 - 408
  • [28] A MATHEMATICAL APPROACH TO REVENUE MANAGEMENT
    Stanciu-Gorun, Lucian
    PROCEEDINGS OF THE 13TH INTERNATIONAL MANAGEMENT CONFERENCE: MANAGEMENT STRATEGIES FOR HIGH PERFORMANCE (IMC 2019), 2019, : 675 - 683
  • [29] An interactive approach to stochastic programming-based portfolio optimization
    Koksalan, Murat
    Sakar, Ceren Tuncer
    ANNALS OF OPERATIONS RESEARCH, 2016, 245 (1-2) : 47 - 66
  • [30] Stochastic structural topology optimization: discretization and penalty function approach
    Evgrafov, A
    Patriksson, M
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2003, 25 (03) : 174 - 188