The constrained multinomial logit: A semi-compensatory choice model

被引:85
|
作者
Martinez, Francisco [1 ]
Aguila, Felipe [1 ]
Hurtubia, Ricardo [1 ]
机构
[1] Univ Chile, Santiago, Chile
关键词
Discrete choice; Logit models; Constrained behavior; Consumer's utilities; RANDOM UTILITY-MODELS;
D O I
10.1016/j.trb.2008.06.006
中图分类号
F [经济];
学科分类号
02 ;
摘要
The traditional formulation of logit models applied to transport demand assumes a compensatory (indirect) utility function in which the consumers' strategy assumes a trade-off between attributes. Several authors have criticized this approach because it fails to recognize attribute thresholds in consumer behavior, or a more generic domain where such a compensatory strategy is contained, In this paper, a mixed strategy is proposed, which combines the compensatory strategy valid in the interior of the choice domain with cutoff factors that restrain choices to the domain edge. The proposed model combines the multinomial logit model with a binomial logit factor that represents soft cutoffs. This approach extends previous contributions in several ways and allows multiple dimensions for cutoff factors. In addition to considering individual behavior, it introduces system constraints Such as capacity and inter-agent interactions (choice externalities). This extension yields a non-linear problem, which is solved by analyzing the fixed point problem. Additionally, a set of evaluation tools, a social utility of the constrained problem, and a measure of the shadow price of each constraint, are proposed. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:365 / 377
页数:13
相关论文
共 50 条
  • [31] Multinomial Logit Model-Based Parking Choice in a Mall at City
    Liang, Wei
    Hu, Jianming
    Zhang, Yi
    Wang, Ziwei
    [J]. PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 320 - 323
  • [32] Correction to: Optimal pricing for a multinomial logit choice model with network effects
    Nako Iwaji
    Kimitoshi Sato
    [J]. Journal of Revenue and Pricing Management, 2024, 23 : 119 - 120
  • [33] Coopetition Between TTA and OTA Based on Multinomial Logit Choice Model
    Hui-Li Yan
    Hao Xiong
    [J]. Journal of the Operations Research Society of China, 2021, 9 : 741 - 756
  • [34] Robust product line pricing under the multinomial logit choice model
    Qi, Wei
    Luo, Xinggang
    Liu, Xuwang
    Zhang, Zhong-Liang
    [J]. CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS, 2022, 30 (03): : 273 - 282
  • [35] Network Revenue Management Under a Spiked Multinomial Logit Choice Model
    Cao, Yufeng
    Kleywegt, Anton J.
    Wang, He
    [J]. OPERATIONS RESEARCH, 2022, 70 (04) : 2237 - 2253
  • [36] Assortment Optimization under the Multinomial Logit Model with Random Choice Parameters
    Rusmevichientong, Paat
    Shmoys, David
    Tong, Chaoxu
    Topaloglu, Huseyin
    [J]. PRODUCTION AND OPERATIONS MANAGEMENT, 2014, 23 (11) : 2023 - 2039
  • [37] Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint
    Rusmevichientong, Paat
    Shen, Zuo-Jun Max
    Shmoys, David B.
    [J]. OPERATIONS RESEARCH, 2010, 58 (06) : 1666 - 1680
  • [38] Using Clustering Methods in Multinomial Logit Model for Departure Time Choice
    Zargari, Shahriar Afandizadeh
    Safari, Farshid
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2020, 2020
  • [40] Learning to Rank under Multinomial Logit Choice
    Grant, James A.
    Leslie, David S.
    [J]. JOURNAL OF MACHINE LEARNING RESEARCH, 2023, 24