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1 results

  • 22 - Modelling Context-Dependent Behaviour

  • from Part IV - Systems and Culture
  • Edited by Ganna Pogrebna, The Alan Turing Institute, Thomas T. Hills, University of Warwick
  • Book:
    The Cambridge Handbook of Behavioural Data Science
    Published online:
    29 May 2026
    Print publication:
    18 June 2026, pp 396-406

  • Summary

    Context-dependent behaviour is a central feature of human and algorithmic decision-making. Unlike context-free models, which assume stable preferences or uniform mechanisms across environments, context-dependent models account for how behaviour shifts depending on external, social, temporal or emotional surroundings. This chapter reviews conceptual frameworks and computational techniques used to capture context-dependence in behavioural data science. We explore psychological theories such as framing and cue-dependence, formal models including multi-level regression, contextual bandits and conditional generative models and the role of context in real-world domains such as health, finance and human–machine interaction. We provide a taxonomy of modelling approaches, examine challenges in data acquisition and generalisability and present a worked example using environmental nudges in energy consumption. The chapter concludes with future directions for context-sensitive modelling, highlighting its importance for ethical, fair and adaptive behavioural data systems.