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    <title>EconStor Community: Journal of Choice Modelling</title>
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    <title>Approximation of bayesian efficiency in experimental choice designs</title>
    <link>http://hdl.handle.net/10419/66849</link>
    <description>Title: Approximation of bayesian efficiency in experimental choice designs
&lt;br/&gt;
&lt;br/&gt;Authors: Bliemer, Michiel C. J.; Rose, John M.; Hess, Stephane
&lt;br/&gt;
&lt;br/&gt;Abstract: This paper compares different types of simulated draws over a range of number of draws in generating Bayesian efficient designs for stated choice (SC) studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and Gaussian quadrature methods are able to replicate the true levels of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analysed here (Halton, Sobol, and Modifed Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the Gaussian quadrature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of SC designs.</description>
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  <item rdf:about="http://hdl.handle.net/10419/66848">
    <title>Accounting for taste heterogeneity in purchase channel intention modeling: An example from Northern California for book purchases</title>
    <link>http://hdl.handle.net/10419/66848</link>
    <description>Title: Accounting for taste heterogeneity in purchase channel intention modeling: An example from Northern California for book purchases
&lt;br/&gt;
&lt;br/&gt;Authors: Tang, Wei Laura; Mokhtarian, Patricia L.
&lt;br/&gt;
&lt;br/&gt;Abstract: This study uses latent class modeling (LCM) to explore the effects of channel-specific perceptions, along with other variables, on purchase channel intention. Using data on book purchases collected from an Internet-based survey of two university towns in Northern California, we develop a latent class model with two segments (final N=373). Age turns out to be the only observed determinant of class membership, and in the intention model, the mostly-younger segment is more cost-sensitive and the mostly-older segment appears to be more conveni¬ence-sensitive. The results clearly demonstrate the effects on purchase intention of channel-specific perceptions, purchase experience, context and sociodemographics. Comparing the LCM to the unsegmented model and to models deterministically segmented on age indicates that the LCM is slightly better from the statistical perspective, but arguably weaker from the conceptual perspective. However, a model that interacts age with the explanatory variables in the conventional unsegmented model outperforms all the others (though not overwhelmingly so), including the LCM. Thus, our results suggest that using LCM as an initial stage in model exploration allows us to more intelligently specify a model where the taste heterogeneity is (potentially) specified deterministically in the end, which often yields a more parsimonious model, and may in fact fit the data better.</description>
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    <title>Freight transport distance and weight as utility conditioning effects on a stated choice experiment</title>
    <link>http://hdl.handle.net/10419/66847</link>
    <description>Title: Freight transport distance and weight as utility conditioning effects on a stated choice experiment
&lt;br/&gt;
&lt;br/&gt;Authors: Masiero, Lorenzo; Hensher, David A.
&lt;br/&gt;
&lt;br/&gt;Abstract: Within a freight transport context, the origin-destination distance and the weight of the shipment play an important role in the decision of the most preferred transport service and in the way logistics managers evaluate the transport service's attributes. In particular, the attributes commonly used in order to describe a freight transport service in a stated choice framework are cost, time, punctuality and risk of damages, respectively. This paper investigates the role of origin-destination distance and weight of freight transport services introducing a conditioning effect, where the standard utility function is conditioned on the freight transport distance. We refer to this model form as a heteroskedastic panel multinomial logit (panel HMNL) model. This model form outperforms the underlying unconditioned model and suggests that an appropriate conditioning effect leads to an improved understanding of the derived measures, such as measures for marginal rates of substitution.</description>
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    <title>Route choice modeling: Past, present and future research directions</title>
    <link>http://hdl.handle.net/10419/66846</link>
    <description>Title: Route choice modeling: Past, present and future research directions
&lt;br/&gt;
&lt;br/&gt;Authors: Prato, Carlo Giacomo
&lt;br/&gt;
&lt;br/&gt;Abstract: Modeling route choice behavior is problematic, but essential to appraise travelers' perceptions of route characteristics, to forecast travelers' behavior under hypothetical scenarios, to predict future traffic conditions on transportation networks and to understand travelers' reaction and adaptation to sources of information. This paper reviews the state of the art in the analysis of route choice behavior within the discrete choice modeling framework. The review covers both choice set generation and choice process, since present research directions show growing interest in understanding the role of choice set size and composition on model estimation and flow prediction, while past research directions illustrate larger efforts toward the enhancement of stochastic route choice models rather than toward the development of realistic choice set generation methods. This paper also envisions future research directions toward the improvement in amount and quality of collected data, the consideration of the latent nature of the set of alternatives, the definition of route relevance and choice set efficiency measures, the specification of models able to contextually account for taste heterogeneity and substitution patterns, and the adoption of random constraint approaches to represent jointly choice set formation and choice process.</description>
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