 | ICMC2026: International Choice Modelling Conference 2026 Sheraton Grand Mirage Resort Gold Coast, Australia, July 20-22, 2026 |
| Submission link | https://easychair.org/conferences/?conf=icmc20260 |
| Abstract registration deadline | January 15, 2026 |
| Submission deadline | January 15, 2026 |
2026 International Choice Modelling Conference (ICMC)
Gold Coast, Australia | 20 - 22 July, 2026
Conference Theme: "Connections"
Call for Submissions
The 9th International Choice Modelling Conference (ICMC) will be hosted by The University of Queensland on the Gold Coast from Monday 20 to Wednesday 22 July, 2026.
The ICMC brings together the global community of researchers, practitioners, and policymakers working at the frontiers of choice modelling. The Conference is the preeminent event for interdisciplinary engagement on the theory and practice of modelling individual choice behaviour.
"Connections" is the broad theme for the 2026 Conference – and the theme speaks to the importance of intellectual, disciplinary, and practical linkages:
- Connections across disciplines, such as economics, marketing, psychology, and transport;
- Connections between universities, government, and industry; and
- Connections between theory and application, academic and practitioner, model and impact.
We invite submissions from across the spectrum of disciplines and sectors.
Key Dates
| Call for Submissions Opens | Early October 2025 |
| Abstract Submission Deadline | 15 January 2026 |
| Acceptance Notifications | 15 February 2026 |
| Optional Short-Form Paper Deadline | 01 May 2026 |
| Conference Dates | 20 - 22 July 2026 |
Submission Format
The submission process for the 2026 ICMC will follow a two-stage model – designed to encourage both early contributions and deeper scholarly engagement, per below.
Stage 1 – Extended Abstract Submission (Required)
Submit a short abstract of 2-3 pages (approx. 1,000 words). Abstracts should clearly describe the research question, method, key results (if available), and contribution. Abstracts will be peer-reviewed for relevance and quality and will form the basis for acceptance for presentation at the conference. Upon acceptance, authors may be invited to submit a short-form paper version for pre-publication consideration in a special issue of the affiliated journal: the Journal of Choice Modelling – per Stage 2 below.
Stage 2 – Short-Form Paper Submission (Optional)
After abstract acceptance (Stage 1), authors for a subset of abstracts will be invited to submit a short-form paper of up to 20 pages of text plus supplementary material (tables and figures, references, etc.) for pre-publication consideration in a special issue of the Journal of Choice Modelling. This second stage – the submission of short-form papers – is optional at the discretion of invited abstract authors. Authors will subsequently be invited to convert accepted short-form papers into full papers for expedited review at the Journal of Choice Modelling.
Research Themes and Topics
We welcome submissions addressing theoretical, methodological, empirical, and applied questions in any area of choice modelling and related methods. The following themes are offered as guidance.
1. Methodological Advances in Choice Modelling
Research on the development and refinement of discrete as well as continuous choice models, the interface with data science (i.e. machine learning), innovations in estimation, simulation techniques, model diagnostics, and general advances in model architecture.
Indicative domain: Econometrics, statistical modelling, simulation methods, machine learning in choice.
2. Experimental Design and Survey Methodology
Research focused on the design and delivery of stated preference surveys, including experimental efficiency, attribute framing, response quality, and survey complexity. Contributions that enhance the rigour of choice data collection are welcome. We also welcome submissions on new types of experiments, including using immersive technologies, and capturing psychometric processes.
Indicative domain: Survey design, experimental methods, conjoint design, psychometrics.
3. Advances in Revealed Preference Data
Innovative approaches to using revealed preference data to understand decision-making, including naturally occurring choice data from transport ticketing and mobility apps to online shopping, financial transactions, and behavioural traces. Submissions exploring novel frameworks for modelling large-scale RP datasets and unstructured RP data.
Indicative domain: Revealed preference, big data, digital trace data.
4. Hybrid and Integrated Data Approaches
Methodological innovations that integrate multiple data types – stated preference, revealed preference, sensor data, behavioural tracking, biometrics – or link choice models to broader systems (e.g., agent-based or dynamic simulation models).
Indicative domain: Data integration, hybrid modelling, sensor analytics, agent-based systems.
5. Behavioural and Psychological Insights
Integration of behavioural science into choice models, including attention, emotion, heuristics, habit, preference evolution, and bounded rationality. These contributions seek to explain the why behind choices – generalising and extending traditional utility-maximising frameworks.
Indicative domain: Behavioural economics, psychology, decision science, cognitive modelling.
6. Machine Learning and Generative Artificial Intelligence
Machine Learning (ML) models such as decision trees, support vector machines, artificial neural networks, and generative artificial intelligence (GenAI) offer alternative, often non-parametric, approaches to explaining and predicting choice. These methods can uncover complex, non-linear patterns in high-dimensional data and may complement or even challenge traditional utility-based models.
Indicative domain: Artificial intelligence, predictive modelling, non-parametric methods, interpretable ML, emerging GenAI modelling frameworks.
7. Applications in Transport and Travel Behaviour
Empirical and theoretical contributions on transport mode, route, or trip timing choice; shared mobility; mobility as a service; travel demand modelling; congestion pricing; emissions reductions; and infrastructure evaluation. Both stated and revealed preference approaches are welcome.
Indicative domain: Transport economics, travel behaviour research, infrastructure planning.
8. Environmental and Sustainability Applications
Valuation of environmental goods and ecosystem services; modelling sustainable behaviours; and preference studies on climate, conservation, and circular economy initiatives. These studies often support or have implications for policy design or resource allocation in environmental domains.
Indicative domain: Environmental economics, ecological policy, sustainability science.
9. Health and Wellbeing Applications
Research on choice behaviour in health and wellbeing domains, including patient preferences, technology adoption, public health policy, and health service design. Applications of choice models to inform both clinical and policy decisions are encouraged.
Indicative domain: Health economics, public health, health services research.
10. Marketing and Consumer Choice
Studies of consumer behaviour, brand preference, pricing, bundling, digital products, and ethical consumption. Submissions may include choice experiments/conjoint analysis, willingness-to-pay estimation, and market segmentation using discrete choice techniques.
Indicative domain: Marketing science, consumer research, digital strategy, pricing.
11. Policy, Ethics, and Fairness
Examinations of the societal impacts of choice modelling, including fairness, ethics in experimental design, inclusiveness, and transparency. Submissions may address the normative dimensions of model use in policy and algorithmic decision-making.
Indicative domain: Public policy, ethical design, social equity, researcher responsibility.
The Spirit of "Connections"
In keeping with our conference theme, we particularly encourage submissions that:
- Bridge disciplines, such as crossovers between psychology and economics, or marketing and health
- Foster collaboration between academics, industry professionals, and government partners
- Translate theory into practice, offering actionable insights or decision-support
- Reflect global diversity, with attention to cross-cultural, international, or regional perspectives