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Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model

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  • Haghani, Milad
  • Sarvi, Majid
  • Shahhoseini, Zahra

Abstract

Mixed logit has been recognised and widely practised by researchers as a highly flexible modelling tool that can address the main shortcomings of the standard logit. Despite the potential to be generalised, the random-coefficient modelling has rarely been integrated with more advanced GEV-type models, possibly due to the unavailability of such estimation options in most econometric software. This particular generalisation has been recommended by a number of econometricians for analysing choice problems in which capturing taste variation and specific non-IIA patterns of substitution are both of modeller's concern. This way, the analyst will be able to limit the number of explanatory variables to the ones whose distributions of coefficients offer behavioural interpretations about taste variation, and leave the imposition of the desired substitution pattern to the GEV core.

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  • Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.
  • Handle: RePEc:eee:eejocm:v:16:y:2015:i:c:p:58-68
    DOI: 10.1016/j.jocm.2015.09.006
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    as
    1. Hensher, David A., 2012. "Accounting for scale heterogeneity within and between pooled data sources," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(3), pages 480-486.
    2. Abbe, E. & Bierlaire, M. & Toledo, T., 2007. "Normalization and correlation of cross-nested logit models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 795-808, August.
    3. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    4. Koppelman, Frank S. & Wen, Chieh-Hua, 2000. "The paired combinatorial logit model: properties, estimation and application," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 75-89, February.
    5. Antonini, Gianluca & Bierlaire, Michel & Weber, Mats, 2006. "Discrete choice models of pedestrian walking behavior," Transportation Research Part B: Methodological, Elsevier, vol. 40(8), pages 667-687, September.
    6. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    7. Hänseler, Flurin S. & Bierlaire, Michel & Farooq, Bilal & Mühlematter, Thomas, 2014. "A macroscopic loading model for time-varying pedestrian flows in public walking areas," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 60-80.
    8. Bierlaire, M. & Bolduc, D. & McFadden, D., 2008. "The estimation of generalized extreme value models from choice-based samples," Transportation Research Part B: Methodological, Elsevier, vol. 42(4), pages 381-394, May.
    9. Daly, Andrew & Bierlaire, Michel, 2006. "A general and operational representation of Generalised Extreme Value models," Transportation Research Part B: Methodological, Elsevier, vol. 40(4), pages 285-305, May.
    10. Mariel, Petr & Ayala, Amaya de & Hoyos, David & Abdullah, Sabah, 2013. "Selecting random parameters in discrete choice experiment for environmental valuation: A simulation experiment," Journal of choice modelling, Elsevier, vol. 7(C), pages 44-57.
    11. Greene, William H. & Hensher, David A. & Rose, John, 2006. "Accounting for heterogeneity in the variance of unobserved effects in mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 75-92, January.
    12. Hensher, David A. & Rose, John M. & Greene, William H., 2008. "Combining RP and SP data: biases in using the nested logit ‘trick’ – contrasts with flexible mixed logit incorporating panel and scale effects," Journal of Transport Geography, Elsevier, vol. 16(2), pages 126-133.
    13. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    14. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    15. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
    16. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    17. Robin, Th. & Antonini, G. & Bierlaire, M. & Cruz, J., 2009. "Specification, estimation and validation of a pedestrian walking behavior model," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 36-56, January.
    18. Hetrakul, Pratt & Cirillo, Cinzia, 2013. "Accommodating taste heterogeneity in railway passenger choice models based on internet booking data," Journal of choice modelling, Elsevier, vol. 6(C), pages 1-16.
    19. Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
    20. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    21. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    22. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    23. Bliemer, Michiel C.J. & Rose, John M., 2013. "Confidence intervals of willingness-to-pay for random coefficient logit models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 199-214.
    24. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    25. Hou, Lei & Liu, Jian-Guo & Pan, Xue & Wang, Bing-Hong, 2014. "A social force evacuation model with the leadership effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 93-99.
    26. Shiwakoti, Nirajan & Sarvi, Majid & Rose, Geoff & Burd, Martin, 2011. "Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1433-1449.
    27. Hoogendoorn, S. P. & Bovy, P. H. L., 2004. "Pedestrian route-choice and activity scheduling theory and models," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 169-190, February.
    28. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
    29. Frode Alfnes, 2004. "Stated preferences for imported and hormone-treated beef: application of a mixed logit model," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 31(1), pages 19-37, March.
    30. Zheng, Yaochen & Chen, Jianqiao & Wei, Junhong & Guo, Xiwei, 2012. "Modeling of pedestrian evacuation based on the particle swarm optimization algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4225-4233.
    31. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
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    2. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    3. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    4. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    5. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    6. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    7. Shahhoseini, Zahra & Sarvi, Majid, 2019. "Pedestrian crowd flows in shared spaces: Investigating the impact of geometry based on micro and macro scale measures," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 57-87.
    8. Milad Haghani & Majid Sarvi & Zahra Shahhoseini & Maik Boltes, 2016. "How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-24, November.
    9. Hassanpour, Sajjad & Rassafi, Amir Abbas & González, Vicente A. & Liu, Jiamou, 2021. "A hierarchical agent-based approach to simulate a dynamic decision-making process of evacuees using reinforcement learning," Journal of choice modelling, Elsevier, vol. 39(C).
    10. Haghani, Milad & Sarvi, Majid, 2019. "Laboratory experimentation and simulation of discrete direction choices: Investigating hypothetical bias, decision-rule effect and external validity based on aggregate prediction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 134-157.
    11. Haghani, Milad & Sarvi, Majid, 2017. "Social dynamics in emergency evacuations: Disentangling crowd’s attraction and repulsion effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 475(C), pages 24-34.
    12. Haghani, Milad & Sarvi, Majid, 2017. "Stated and revealed exit choices of pedestrian crowd evacuees," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 238-259.
    13. Haghani, Milad & Sarvi, Majid, 2018. "Crowd behaviour and motion: Empirical methods," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 253-294.
    14. Vásquez Lavin, Felipe & Barrientos, Manuel & Castillo, Álvaro & Herrera, Iván & Ponce Oliva, Roberto D., 2020. "Firewood certification programs: Key attributes and policy implications," Energy Policy, Elsevier, vol. 137(C).

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