Evidence Domain

Behavioural Science

What it studies

How people actually decide and act, as opposed to how rational models say they should: heuristics, defaults, social norms, friction, habit formation and choice architecture. In the workplace it explains the gap between policy and behaviour, and between stated preference and revealed behaviour.

Why it matters

Every workplace concept is a bet on behaviour — that people will share, book honestly, move between settings, follow norms. Behavioural science explains why those bets fail (defaults beat intentions, friction beats preference, norms beat rules) and how to design the choice architecture so they don't.

Questions it answers
  • Why does reported preference diverge from observed behaviour?
  • Why do rules fail where defaults succeed?
  • How do social norms establish, decay and transfer in shared space?
  • Which frictions determine whether a setting gets used?
Evidence sources
  • Behavioural economics and judgment-and-decision-making literature
  • Field experiments and natural experiments in organisational settings
  • Booking and usage data analysed as revealed behaviour
  • Norm and default research (with replication-crisis caveats applied)
Design and policy implications

Booking rules designed as choice architecture (auto-release, defaults, friction placement); norms launched with visible modelling rather than policy documents; setting placement that makes desired behaviour the low-friction path; interventions tested rather than assumed.

Related methods
Common misuse

Nudge theatre: cosmetic interventions borrowed from pop-science books, deployed untested, credited with effects never measured. Parts of the nudge literature have replicated poorly; workplace applications should be treated as hypotheses to test, not established levers.

Further research

Effect sizes and replication in organisational (rather than consumer) contexts are the live questions; the honest position is that behavioural interventions in workplaces need local testing.