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Explaining human decision-making by combining choice and process data

Project description

A new toolkit for decision-making research

Decision-making is integral to human activity, influencing personal lives and global challenges like climate change, sustainable energy and public health. Yet, many behavioural models focus on predicting outcomes rather than elucidating the decision-making process itself. Often, valuable neurophysiological data is overlooked, and current methods fail to simulate realistic future scenarios. In this context, the ERC-funded IMMERSION project addresses these gaps by developing innovative methods to combine choice and process data. The project includes empirical studies aimed at understanding decision-making in transportation, enhancing the design of future systems. IMMERSION equips researchers with a powerful toolkit to extract profound insights from complex behavioural data.

Objective

Decision-making is a core element of human activity, and the decisions we make can have significant consequences for ourselves, others, and the world we live in. Thus, the ability to explain and predict decision-making is vital for improving individual and societal outcomes, especially when addressing global challenges like climate change, sustainable energy, ageing populations, and public health. Mathematical models of decision-making can help us to understand and predict human behaviour.

Despite significant progress, several scientific challenges persist in the applicability of advanced behavioural models to real-world problems. Many models focus on predicting decision outcomes rather than explaining the decision process itself. Information contained in neurophysiological process data that emerge during decision-making are often ignored, and methods for collecting behavioural data fail to create realistic impressions of scenarios representing the future.

IMMERSION aims to advance the study of human decision-making by developing new innovative methods for combining choice and process data. This includes new models for integrating choice and process data, new statistical inference procedures tailored to such models, and new methods for collecting rich behavioural data in immersive experiments. The proposed research will create a paradigm shift in behavioural research with impacts on many application domains. IMMERSION will equip researchers with a new powerful toolkit for extracting deep behavioural insights from rich data using advanced models.

The proposed research includes substantial empirical work applying IMMERSION’s methodological innovations to real-world problems with implications for the human-centric design of future transport systems. This work includes case studies to explain and predict human decision-making in the contexts of transportation infrastructure development, pedestrian-autonomous vehicle interactions and pedestrian wayfinding.

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-STG

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Host institution

DANMARKS TEKNISKE UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 500 000,00
Address
ANKER ENGELUNDS VEJ 101
2800 KONGENS LYNGBY
Denmark

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Region
Danmark Hovedstaden Københavns omegn
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 500 000,00

Beneficiaries (1)

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