The notion of hypothetical bias (HB) constitutes, arguably, the most fundamental issue in relation to the use of hypothetical survey methods. Whether or to what extent choices of survey participants and subsequent inferred estimates translate to real-world settings continues to be debated. While HB has been extensively studied in the broader context of contingent valuation, it is much less understood

This study proposes a joint modelling approach to simulate episode timing decisions of skeletal activities -- activities that typically take precedence in the scheduling process -- using copulas. The analyses focus on examining the correlation between activity start time and duration while exploring the timing behaviour over a 20-year period between 1996 and 2016 in the Greater Toronto and Hamilton

In many cases, ordinal data, for example rating objects on a scale from 1 to 5, is observed only for those objects that have been chosen from a set of discrete alternatives, with no ratings for unchosen objects. An example is customer ratings of goods sold by online retailers. The joint modelling of choice and rating is made difficult by the missing ratings for unchosen alternatives. A method of jointly

Econometric modelling of choice now constitutes a major cross-over between multiple fields of research in which quantitative valuation of human preferences is of interest. The methods are pervasively used by consumer, environmental and health economists as well as transportation researchers and beyond. This work analyses the scholarly literature on econometric discrete choice modelling developed in

Preference heterogeneity is one of the central behavioral concepts in applied econometrics. Its centrality is particularly evident in the choice modeling literature, notably in its widespread application to environmental and health economics, marketing, and transport. Despite conceptual and empirical advances in modeling preference heterogeneity, the generalizability of preference heterogeneity to

This article proposes a two recursive equation model to correct for endogeneity in latent class Probit models. Concretely, it is assumed that there exists an endogenous and continuous variable defined as a predictor, while unobserved heterogeneity is conceptualized as a vector of parameters that varies across individuals following a discrete distribution. A Maximum Likelihood Estimator is provided

The National Disability Insurance Scheme (NDIS) is an ambitious Australian welfare program, with the goal of supporting 460,000 people living with a disability. To promote individual choices, the NDIS allocates personalised budgets based on the goals of Participants (or their nominated Carers). This paper examines (a) the heterogeneity of personal preferences for support services in the disability

Fear of Crime (FoC) has social and economic consequences and can impact both physical and mental health. Consequently, strategies to reduce FoC are imperative to national and local policy makers. We use the stated preference method choice experiments to elicit preferences for multiple FoC mitigation attributes in a nightlife setting among adolescents and their parents in 10 Danish cities. We find the

In assignment models a key role is played by the path choice model, which computes the set of decisions made by the user before (and during) the routing on the network according to perceived paths and related costs. The path choice is a component of the assignment models. This paper considers the effects of an interference term in addition to the effect of the traditional covariance term in the choice

This paper proposes simple and computationally efficient forecasting algorithms for random utility maximization-based multiple discrete-continuous (MDC) choice models with additively separable utility functions, such as the Multiple Discrete-Continuous Extreme Value (MDCEV) model. The algorithms build on simple yet insightful, analytical explorations with the Karush Kuhn-Tucker (KKT) conditions of

Case 1 best-worst scaling, also known as best-worst scaling or MaxDiff, is a popular method for examining the relative ratings and ranks of a series of items in various disciplines in academia and industry. The method involves a survey respondent indicating the “best” and “worst” from a sample of items across a series of trials. Many methods exist for calculating scores at the individual and aggregate

Simulation models are an undeniable tool to help researchers and designers forecast effects of definite policies regarding pedestrian social and collective movement behaviour. Considering both the environment's details and the complexity of human behaviour in choosing paths simultaneously is the main challenge in micro-simulation pedestrian dynamics models. This paper aims to present a novel comprehensive

This paper investigates the activity behavior of residents of Paraisópolis, the second largest slum of São Paulo (Brazil). The study used data from a survey and one week of GPS traces of a sample of residents. Location data was the basis to infer individual stays and points of interest. Stays were clustered into 6 classes, based on spatial, temporal, repetition and sequence variables characterizing

Determining appropriate utility specifications for discrete choice models is time-consuming and prone to errors. With the availability of larger and larger datasets, as the number of possible specifications exponentially grows with the number of variables under consideration, the analysts need to spend increasing amounts of time on searching for good models through trial-and-error, while expert knowledge

Fully Automated Vehicles (AVs) have been widely expected to revolutionise the future travel experience. Recent studies have shown that their impact may also reach beyond the travel episode, and lead their users to alter other activities performed during the day – their daily lifestyles. This study is among the first to empirically investigate the changes that travellers expect in their daily activities

This paper introduces mixl, a new R package for the estimation of advanced choice models. The estimation of such models typically relies on simulation methods with a large number of random draws to obtain stable results. mixl uses inherent properties of the log-likelihood problem structure to greatly reduce both the memory usage and runtime of the estimation procedure for specific types of mixed multinomial

Quantal response equilibrium choice (QREC) models are structural behavioral models that account for bounded rationality and strategic interactions in analyses of games where each player’s payoff is a vector. We revisit the question of how market competition affects pro-social behavior and fit a QREC model to data from an incentivized laboratory experiment, where participants make decisions on medical

Over the last decade, immigration flows among developing countries have grown at a faster pace than immigration to advanced economies. Despite the documented welfare benefits of immigration, adverse policies and negative public opinion toward immigrants appear to be as common in developing countries as in developed ones. In such a context, understanding natives' attitudes toward immigrants may help

In this paper, we analyze the implications for the economic valuation of the provision of public goods, considering respondents’ perceptions of the institution(s) that provide the service. The specific behavioral mechanism whereby institutional distrust (ID) shows itself is through the activation of screening of choice options (choice set formation). However, ID-induced choice set formation might be

This paper argues that choice modelling is a useful approach for all social sciences, while at the same time disciplines such as sociology and political science can contribute significantly to the future development of choice modelling. So far choice modelling has mainly been applied in disciplines that investigate types of consumption choices, be it marketing to investigate preferences for new products

We propose a structural econometric model that incorporates altruism towards other household members into the willingness to pay for a public good. The model distinguishes preferences for public good improvements for oneself from preferences for improvements for other household members. We test for three different types of altruism - ‘pure self-interest’, ‘pure altruism’ and ‘public-good-focused non-pure

Activity travel pattern of pilgrims in a religious setting is a complex process. Extant literature on religious tourism has taken minimal efforts in addressing such complexity, which has led to a paucity of information on preferred activity participation destinations and trip chain sequences of pilgrims. So, the present research objective is two-fold. First, to examine the causal effects of socio-demographics

To appropriately weight dimensions of quality of life instruments for health economic evaluations, population and patient preferences need to be elicited. Two commonly used elicitation methods for this purpose are discrete choice experiments (DCE) and case 2 best-worst scaling (BWS). These methods differ in terms of their cognitive burden, which is especially relevant when eliciting preferences among

Background and objectives Additional funding will be needed to meet the growing demand for health and social care in the UK. What is the most acceptable way to raise it? Options range from taxation to mandatory insurance, voluntary insurance and user charges. We sought to analyse the preferences of the UK general public. Methods An online quantitative survey embedded within a DCE was undertaken with

We consider anchoring on visual cues in a contingent-behavior study of the effects of offshore wind power projects on beach use on the East Coast of the United States. In an internet-based survey of beachgoers, we show respondents visual simulations of wind power projects at three offshore distances and vary the order in which respondents see the visuals -- so some see near visuals first and some see

The decoy effect reveals a potential violation of the regularity assumption, which is a building block of canonical discrete choice models. This effect has been detected in various choice contexts, but the susceptibility to it and its subjective valuation have been scarcely studied before. This paper proposes, illustrates and assesses two methodologies aimed to fill this gap: systematic taste variations

An examination of model validation practices in the peer-reviewed transportation literature published between 2014 and 2018 reveals that 92% of studies reported goodness-of-fit statistics, and 64.6% reported some sort of policy-relevant inference analysis. However, only 18.1% reported validation performance measures, out of which 78% (14.2% of all studies) consisted of internal validation and 22% (4%

The emergence of the ‘gig’ economy is disrupting industries, reshaping the organisation of work and the terms and conditions under which work is carried out. In effect, the terms and conditions of ‘gig’ work mean that minimum standards, for example minimum wages, that are attached to work in advanced capitalist economies like Australia, regularly do not apply to ‘gig’ work. This study explores the

In linear-in-income logit, a case with no income effect, the expectation ofthe compensating variation and the expectation of the equivalent variation are identical and provided by the logsum formula. The statistical properties of the estimator of this measure of welfare change are investigated. Under regularity conditions, the estimator of the measure obtained from maximum likelihood estimators of

Discrete choice experiments (DCEs) are used to provide evidence for policymaking and nonmarket valuation in health. A perennial issue with the stated preference data used in DCEs is hypothetical bias; that is, hypothetical responses in experiments may differ from real-world behavior. A randomized DCE tested whether an incentive-compatible preference elicitation reduced hypothetical bias. Adult smokers

Choice modelling techniques have established themselves as a key analysis tool in health economics and have been used to understand patient and practitioner preferences across a wide variety of settings. A key interest in recent years has been the incorporation of ever more flexible levels of heterogeneity in preferences across individual decision makers, and in particular a growing interest in the

Modelling people's behaviour is a complex task, not only because of their intrinsic complexity but also because of their interaction with the environment and other individuals. The traditional format for discrete choice experiments involves the use of text and images. However, there is a growing tendency for using tools that offer a more realistic representation of complex and dynamic attributes in

Discrete choice analysis is a popular method of estimating heterogeneous customer preferences. Although model accuracy can be increased by including more choice data, this option is untenable when the obtaining of choice data from target customers is costly and time-consuming.. We thus propose a method for choice data generation for commercial products whose expected money value is a key factor in

This study focuses on the menus typically found in the marketplace (e.g., restaurants and Internet vendors), where the consumer may choose one or more from dozens of options or menu items, each at a posted price or fee. We show that modeling choices out of the typical menu leads to the “curse of dimensionality,” which transpires in two ways. First, the choice set (all possible menu selections) grows

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the estimation of statistical Discrete Choice Models based on the random utility framework. In this article, we provide new ways of dealing with large datasets

In this study, we apply the multiple discrete–continuous extreme value (MDCEV) model with triple constraints to identify the value of leisure time during weekends and long holidays. Our approach models the economic behavior of leisure trips with the triple constraints of budget, duration of weekend, and duration of holiday. The econometric model is developed to construct an estimation using the observed

Theatrical productions are supposed to be perishable good, since the tickets for a particular play cannot be inventoried and sold after a time of play. In the revenue management of a perishable good price discrimination is widely used. Since the theatre audience is heterogeneous in terms of visit purpose, ability to perceive quality, willingness-to-pay, the strategy of price discrimination is developed

It is an enduring question how to combine revealed preference (RP) and stated preference (SP) data to analyze individual choices. While the nested logit (NL) model is the classical way to address the question, this study presents multitask learning deep neural networks (MTLDNNs) as an alternative framework, and discusses its theoretical foundation, empirical performance, and behavioral intuition. We

Estimating installed-base effects for product adoption in the presence of unobserved heterogeneity is challenging since the typical solution of including fixed effects leads to inconsistent estimates in models with installed base. Narayanan and Nair (2013) highlight this problem and propose a bias correction method as a solution to the problem. This research note proposes an alternative solution: Borrowing

Machine Learning (ML) approaches are increasingly being investigated as an alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These approaches have the potential to provide valuable insights into choice modelling research questions. However, the research and the methodologies used are fragmented. Whilst systematic reviews on RUMs for mode choice prediction have long existed

This paper tests for the existence of loss aversion, reference dependence and diminishing sensitivity in a discrete choice experiment (DCE). A status quo alternative is introduced in a DCE of nurses' job choices and modeled as an individual-specific third alternative representing the respondent's current job. This provides a feasible method for including a status quo, which changes the reference point

In a referendum in March 2016, the British public voted by a margin of 52 per cent to 48 per cent to leave the European Union. Unfortunately, the referendum question provides little information on the sort of relationship Britons desire with the EU. The purpose of this study is to use stated choice experiments (CEs) to understand and quantify what aspects of the relationship between Britain and the

Wildlife is widely becoming an important vehicle for rural development in most third-world countries across the globe. With wildlife, as with other conservation and development policies, policymakers are usually not informed about the needs and wants of poor rural households and roll out programmes that are not tailor made to suit their desires, which often results in policy failure. We use a survey-based

Quantum probability, first developed in theoretical physics, has recently been successfully used in cognitive psychology to model data from experiments that previously resisted effective modelling by classical methods. This has led to the development of choice models based on quantum probability, which have greater flexibility than standard models due to the implementation of complex numbers through

Researchers using discrete choice experiments (DCE) are often faced with the difficult decision of selecting which are the key attributes that must be included into their analysis. Previous literature on methods for attribute selection is not particularly well documented, frequently leaving researchers with a wide choice of attributes that could lead to complex choice tasks. Moreover, selecting attributes

This paper i) compares parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian logit models and ii) applies these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV) services. Specifically, we compare the multivariate normal, the finite mixture of normals and the Dirichlet process mixture of normals (DP-MON)

Individual-specific posterior distributions are an attractive tool for disentangling the tastes for each person in the sample. However, there exists some risks and certain limitations regarding their use. This study reviews and summarizes the theoretical literature about the individual-specific posterior distributions derived from the Mixed Logit model, focusing on their properties, limitations and

The proneness of stated preference methods to different biases has increased the popularity of incentivized choice experiments (ICE). ICEs, however, are not free from challenges. One such challenge when using ICEs in market valuation is that some product alternatives may not be available to incentivize experiments. In this context, withholding information about product availability could be considered

The aim of the study is to examine the potential effect of attitudes towards physical activity on bus utility in the context of a rural area where studies have shown that the level and opportunity for physical activity are generally low. The need to analyze attitudes remains a strong motivation for the application of integrated choice and latent variable models. As such, we integrated attitudes towards

This paper proposes the use of Most Typical (MT) and Most Ideal (MI) levels when an adaptive choice-based conjoint (ACBC) survey can only obtain a small sample size n from a small population size N. This situation arises when expert decision makers are surveyed from among important small populations such as executives of large companies or political leaders, for which the expert decision maker assumption

This paper presents an agent-based model of team reasoning in a social dilemma game. Starting from the conundrum of empirically high levels of cooperation in dilemma games, contradicting traditional utility maximisation assumptions of game theory, Bacharach (1999, 2006) developed a theory of team reasoning. The idea behind team reasoning is that agents do not try to maximise their own utility but make

Combining choice modelling with social network analysis, we show how the stochastic actor-oriented model for the co-evolution of networks and behavior (SAOM) can be used as a powerful statistical framework to empirically analyze network-related choices. We discuss the underlying assumptions of SAOMs and show that they can be interpreted to represent a random utility maximization model (RUM). Network-related

In linear regressions, the ecological fallacy—the erroneous belief that aggregate-level coefficients coincide with individual-level coefficients—arises when individual outcomes depend on the group environment. This paper suggest that such “group effects” determine also the circumstances under which the ecological fallacy vanishes from basic discrete-choice models. In particular, when controlling for

Endogeneity arises in discrete choice models due to several factors and results in inconsistent estimates of the model parameters. In adaptive choice contexts such as choice-based recommender systems and adaptive stated preferences (ASP) surveys, endogeneity is expected because the attributes presented to an individual in a specific menu (or choice situation) depend on the previous choices of the same

In this paper, we estimate the relative value of different employment characteristics when choosing between apprenticeship and job offers. Further, we test assumptions derived from sociological rational choice theory on preference heterogeneity by individual and context characteristics. For this purpose, we analyse data from two discrete choice experiments, one focusing on the choice of an apprenticeship

Abstract One of the central topics in crime research, and one in which discrete choice modelling has been relatively recently introduced, is the study of where offenders choose to commit crime. Since the introduction of this approach in 2003, it has become relatively popular and used in over 25 published studies covering a range of crime types and study areas. However, in most of these analyses the

Abstract The huge increase in higher education coverage in many developing countries has gone hand-in-hand with an additional supply of private colleges and with the enrolment of low to middle-class students, previously excluded from a historically elitist education segment. The larger diversity of both “suppliers and consumers”, unseen a few years ago, calls for methodological approaches that recognize

Artificial Neural Networks (ANNs) are increasingly used for discrete choice analysis, being appreciated in particular for their strong predictive power. However, many choice modellers are critical – and rightfully so – about using ANNs, for the reason that they are hard to diagnose. That is, for analysts it is hard to see whether a trained (estimated) ANN has learned intuitively reasonable relationships