Print Email Facebook Twitter A multinomial probit model with Choquet integral and attribute cut-offs Title A multinomial probit model with Choquet integral and attribute cut-offs Author Dubey, S.K. (TU Delft Transport and Planning) Cats, O. (TU Delft Transport and Planning) Hoogendoorn, S.P. (TU Delft Transport and Planning) Bansal, Prateek (National University of Singapore) Department Transport and Planning Date 2022 Abstract Several non-linear functions and machine learning methods have been developed for flexible specification of the systematic utility in discrete choice models. However, they lack interpretability, do not ensure monotonicity conditions, and restrict substitution patterns. We address the first two challenges by modeling the systematic utility using the Choquet Integral (CI) function and the last one by embedding CI into the multinomial probit (MNP) choice probability kernel. We also extend the MNP-CI model to account for attribute cut-offs that enable a modeler to approximately mimic the semi-compensatory behavior using the traditional choice experiment data. The MNP-CI model is estimated using a constrained maximum likelihood approach, and its statistical properties are validated through a comprehensive Monte Carlo study. The CI-based choice model is empirically advantageous as it captures interaction effects while maintaining monotonicity. It also provides information on the complementarity between pairs of attributes coupled with their importance ranking as a by-product of the estimation. These insights could potentially assist policymakers in making policies to improve the preference level for an alternative. These advantages of the MNP-CI model with attribute cut-offs are illustrated in an empirical application to understand New Yorkers’ preferences towards mobility-on-demand services. Subject Aggregation functionsAttribute cut-offsChoquet integralProbit modelSemi-compensatory behavior To reference this document use: http://resolver.tudelft.nl/uuid:1d0d68f7-35af-4317-a7b5-52da6a506ea1 DOI https://doi.org/10.1016/j.trb.2022.02.007 ISSN 0191-2615 Source Transportation Research. Part B: Methodological, 158, 140-163 Part of collection Institutional Repository Document type journal article Rights © 2022 S.K. Dubey, O. Cats, S.P. Hoogendoorn, Prateek Bansal Files PDF 1_s2.0_S0191261522000261_main.pdf 1.84 MB Close viewer /islandora/object/uuid:1d0d68f7-35af-4317-a7b5-52da6a506ea1/datastream/OBJ/view