The standard random utility model assumes a fully rational and compensatory choice behaviour. However, various research studies have proven that non-compensatory /semi-compensatory choice behaviour is more realistic. This paper proposes a semi-compensatory framework for the discrete choice model that combines probabilistic choice set formation along with implicit choice constraints in choice making. It combines the Independent Availability Logit (IAL) with Implicit Constrained Multinomial Logit model (CMNL). The model is applied to investigate the mode choice behaviour of the Ottawa-Gatineau regions of Canada’s capital by using the household travel survey data. The explanatory power and elasticity measures of the proposed model are compared with IAL and MNL models. It is found that the IAL-CMNL model outperforms both IAL and MNL models and can reproduce the choice set formation process more effectively. The empirical investigation shows that the IAL-CMNL model results in relatively higher tolerance and softer constraints for cut-off violations compared to the IAL model. Elasticity calculations and outcomes of this research highlight the importance of capturing choice set formation and constrained choice behaviour in the choice modelling.

中文翻译：

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具有概率选择集的半补偿选择模型：在概率选择集形成中结合隐式选择集

标准随机效用模型假定完全理性和补偿性的选择行为。然而，各种研究表明，非补偿/半补偿的选择行为更为现实。本文提出了一种离散选择模型的半补偿框架，该模型将概率选择集的形成与选择中的隐式选择约束相结合。它结合了独立可用性 Logit (IAL) 和隐式约束多项 Logit 模型 (CMNL)。该模型利用家庭旅行调查数据，用于调查加拿大首都渥太华-加蒂诺地区的出行方式选择行为。将所提出模型的解释力和弹性度量与 IAL 和 MNL 模型进行了比较。发现IAL-CMNL模型优于IAL和MNL模型，可以更有效地再现选择集的形成过程。实证研究表明，与 IAL 模型相比，IAL-CMNL 模型对截止违规产生了相对更高的容忍度和更软的约束。本研究的弹性计算和结果强调了在选择建模中捕获选择集形成和受约束的选择行为的重要性。