Browsing by Author "Cantillo, Victor"

Now showing 1 - 5 of 5
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    A discrete choice model incorporating thresholds for perception in attribute values
    (PERGAMON-ELSEVIER SCIENCE LTD, 2006) Cantillo, Victor; Heydecker, Benjamin; Ortuzar, Juan de Dios
    In this paper we formulate a discrete choice model that incorporates thresholds in the perception of changes in attribute values. The model considers multiple options and allows for changes in several attributes. We postulate that if thresholds exist they could be random, differ between individuals, and even be a function of socio-economic characteristics and choice conditions. Our formulation allows estimation of the parameters of the threshold probability distribution starting from information about choices.
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    Accounting for stochastic variables in discrete choice models
    (2015) Diaz, Federico; Cantillo, Victor; Arellana, Julian; Ortúzar Salas, Juan de Dios; CEDEUS (Chile)
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    Implications of thresholds in discrete choice modelling
    (TAYLOR & FRANCIS LTD, 2006) Cantillo, Victor; Ortuzar, Juan De Dios
    Individual choices are affected by complex factors and the challenge consists of how to incorporate these factors in order to improve the realism of the modelling work. The presence of limits, cut-offs or thresholds in the perception and appraisal of both attributes and alternatives is part of the complexity inherent to choice-making behaviour. The paper considers the existence of thresholds in three contexts: inertia (habit or reluctance to change), minimum perceptible changes in attribute values, and as a mechanism for accepting or rejecting alternatives. It discusses the more relevant approaches in modelling these types of thresholds and analyses their implications in model estimation and forecasting using both synthetic and real databanks. It is clear from the analysis that if thresholds exist but are not considered, the estimated models will be biased and may produce significant errors in prediction. Fortunately, there are practical methods to attack this problem and some are demonstrated.
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    Modeling discrete choices in the presence of inertia and serial correlation
    (INFORMS, 2007) Cantillo, Victor; Ortuzar, Juan de Dios; Williams, Huw C. W. L.
    The concept of habit or inertia in the context of (reluctance to) change in travel behavior has an important bearing on transport policy (e.g., how to break car use habits) and has remained an unresolved issue in demand modeling. Another major problem in modeling the response to policy measures is the potential correlation or dependence between the choices made by a given individual over time (i.e., serial correlation). The two phenomena are closely related. This paper discusses the effects of considering inertia and serial correlation on travel choices. We formulate a fairly general discrete choice model that incorporates randomly distributed inertia thresholds and allow for serial correlation. The inertia thresholds may also be a function of an individual's socioeconomic characteristics and choice conditions. The model can be applied with panel data as well as with mixed revealed and stated preference data. We applied it to real and simulated data, confirming that if these phenomena exist in the population but are not considered, serious errors in model estimation and prediction may arise, especially in the case of large policy impacts.
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    Thresholds and indifference in stated choice surveys
    (PERGAMON-ELSEVIER SCIENCE LTD, 2010) Cantillo, Victor; Amaya, Johanna; Ortuzar, J. de D.
    One typical aim of choice experiment designs is utility balance, that is, the alternatives defined within each choice set should have similar choice probabilities; otherwise, choice is too easy and little information about preferences may be obtained. Therefore, in a good design respondents may often find themselves close to indifference and thus perception thresholds may be an issue. We propose a discrete choice model to examine the behaviour of individuals with indifference thresholds, i.e. that would make them perceive two or more alternatives as almost identical in stated choice (SC) experiments. Such thresholds may be stochastic, differ among the population and even be a function of socio-economic characteristics and choice conditions. Two estimate this model we need SC data including an "indifference option", so that respondents are not forced to choose when finding that the two alternatives are equally attractive. Our formulation allows estimating the parameters of a threshold probability distribution using information about choices. As an illustration, the model is applied both to synthetic and real data; results clearly show that when indifference thresholds exist, using models without them can lead to errors in estimation and prediction. (C) 2009 Elsevier Ltd. All rights reserved.