Journal of Choice Modelling

Papers
(The median citation count of Journal of Choice Modelling is 2. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-06-01 to 2025-06-01.)
ArticleCitations
On the impact of decision rule assumptions in experimental designs on preference recovery: An application to climate change adaptation measures71
Editorial Board65
Predicting choices of street-view images: A comparison between discrete choice models and machine learning models61
Modelling household online shopping and home delivery demand using latent class & ordinal generalized extreme value (GEV) models47
Cube model: Predictions and account for best–worst choice situations with three choice alternatives28
Estimating decision rule differences between ‘best’ and ‘worst’ choices in a sequential best worst discrete choice experiment25
Capturing trade-offs between daily scheduling choices25
A Bayesian generalized rank ordered logit model23
Evaluating the predictive abilities of mixed logit models with unobserved inter- and intra-individual heterogeneity22
Decision field theory: An extension for real-world settings20
Editorial Board19
Testing for saliency-led choice behavior in discrete choice modeling: An application in the context of preferences towards nuclear energy in Italy16
Longitudinal investigation of skeletal activity episode timing decisions – A copula approach15
Australian community preferences for hotel quarantine options within the Logit Mixed Logit Model framework14
The impact of violations of expected utility theory on choices in the face of multiple risks14
Optimal sequential strategy to improve the precision of the estimators in a discrete choice experiment: A simulation study13
Utilising activity space concepts to sampling of alternatives for mode and destination choice modelling of discretionary activities13
Weibit choice models: Properties, mode choice application and graphical illustrations12
Editorial Board12
A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices12
Estimating a model of forward-looking behavior with discrete choice experiments: The case of lifetime hunting license demand12
Editorial Board12
Building a life-course intertemporal discrete choice model to analyze migration biographies11
A hierarchical Bayesian logit model for spatial multivariate choice data11
Editorial Board10
Models of moral decision making: Theory and empirical applications in various domains10
Separating generalizable from source-specific preference heterogeneity in the fusion of revealed and stated preferences9
Modeling preference heterogeneity using model-based decision trees9
A consistent moment equations for binary probit models with endogenous variables using instrumental variables9
Preference estimation from point allocation experiments9
Editorial Board9
Editorial Board9
Outside good utility and substitution patterns in direct utility models8
Joint analysis of preferences and drop out data in discrete choice experiments8
Predicting strategic medical choices: An application of a quantal response equilibrium choice model7
Control Function Approach for Addressing Endogeneity in Transport Models: A Case Study on the London–Amsterdam Route7
A micro-econometric framework for Participatory Value Evaluation6
Real payment priming to reduce potential hypothetical bias6
One or two-step? Evaluating GMM efficiency for spatial binary probit models6
Exploring the choice landscape: Anchoring and framing effects on search behavior in complex choices6
The interdependence between hospital choice and waiting time — with a case study in urban China5
Climate change adaptation preferences of winemakers from the Rioja wine appellation5
Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods5
mixl: An open-source R package for estimating complex choice models on large datasets5
Integrating a choice experiment into an agent-based model to simulate climate-change induced migration: The case of the Mekong River Delta, Vietnam5
Exploring the subscribing behavior of customized bus passengers: Active users versus inactive users5
Capturing the effect of multiple social influence sources on the adoption of new transport technologies and services5
Analysis of attribute importance in multinomial logit models using Shapley values-based methods5
Attribute range effects: Preference anomaly or unexplained variance?5
Characterizing the impact of discrete indicators to correct for endogeneity in discrete choice models4
New misspecification tests for multinomial logit models4
Latent class choice model with a flexible class membership component: A mixture model approach4
An assessment of the current use of hybrid choice models in environmental economics, and considerations for future applications4
A Bayesian instrumental variable model for multinomial choice with correlated alternatives4
Departure time choices and a modeling framework for a guidance system4
How to ask twenty questions and win: Machine learning tools for assessing preferences from small samples of willingness-to-pay prices4
Context-aware Bayesian mixed multinomial logit model4
Editorial Board4
Distribution-free estimation of individual parameter logit (IPL) models using combined evolutionary and optimization algorithms4
The effect of perceived risk of false diagnosis on preferences for COVID-19 testing: Evidence from the United States3
Editorial Board3
Cost vector effects in discrete choice experiments with positive status quo cost3
An Experience-Based Choice Model (EBCM): Formulation, identification, behavioural insights and well-being assessment3
A control-function correction for endogeneity in random coefficients models: The case of choice-based recommender systems3
Who is watching out for me? Quantifying fear of crime mitigation attributes using a choice experiment approach among adolescents and their parents3
A day in the life with an automated vehicle: Empirical analysis of data from an interactive stated activity-travel survey3
Modeling the relationship between food purchasing, transport, and health outcomes: Evidence from Concepcion, Chile3
Quantum utility and random utility model for path choice modelling: Specification and aggregate calibration from traffic counts3
A hierarchical agent-based approach to simulate a dynamic decision-making process of evacuees using reinforcement learning3
Special issue on choice modelling in health - Editorial2
Level overlap and level color coding revisited: Improved attribute attendance and higher choice consistency in discrete choice experiments2
Editorial Board2
Case 2 best-worst scaling: For good or for bad but not for both2
To pool or not to pool: Accounting for task non-attendance in subgroup analysis2
The value of consideration data in a discrete choice experiment2
Seen but not considered? Awareness and consideration in choice analysis2
Resampling estimation of discrete choice models2
Preferences for online grocery shopping during the COVID-19 pandemic — the role of fear-related attitudes2
A two recursive equation model to correct for endogeneity in latent class binary probit models2
Choice models with stochastic variables and random coefficients2
Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields2
Location choice of residential housing supply: An application of the multiple discrete-continuous extreme value (MDCEV) model2
What factors influence HIV testing? Modeling preference heterogeneity using latent classes and class-independent random effects2
Separation-based parameterization strategies for estimation of restricted covariance matrices in multivariate model systems2
Travel behaviour and game theory: A review of route choice modeling behaviour2
Distortions in willingness-to-pay for public goods induced by endemic distrust in institutions2
Attitudes and Latent Class Choice Models using Machine Learning2
0.03858208656311