Would predicting peoples’ choices get any easier if we understood behaviour? Inaugural Professorial lecture by Stephane Hess, Professor of Choice Modelling Institute for Transport Studies, University of Leeds 25 June 2014 Abstract: day to day human activity is characterised by decisions on activities and consumption. These have direct impacts on the demand for services and goods and the use of public infrastructure. Accurate estimates of consumers’ valuations and predictions of future choices are thus needed to make appropriate provisions to adjust supply and guide demand. Mathematical models of choice are a key tool in this process. However, many of the leading choice modellers are economists, mathematicians and engineers, hardly the kind of people we would describe as being experts in behaviour. Drawing on the growing media exposure for behavioural economics in popular books such as Predictably Irrational, or the TV and radio appearances by Nobel Prize winner Daniel Kahneman, most recently on Desert Island Discs, this inaugural lecture asks the question whether our models would be better at predictions if we understood behaviour. Biography: Stephane Hess is Professor of Choice Modelling in the Institute for Transport Studies and Director of the Choice Modelling Centre, both at the University of Leeds. He is also Honorary Professor in Choice Modelling in the Institute for Transport and Logistics Studies at the University of Sydney. His main research interests lie in the use of advanced discrete choice models for the analysis of human decision making, with theoretical and applied contributions across a number of fields, including transport, health and environmental economics. He is the founding editor in chief of the Journal of Choice Modelling, and the founder and steering committee chair of the International Choice Modelling Conference. www.its.leeds.ac.uk/people/s.hess www.cmc.leeds.ac.uk www.its.leeds.ac.uk/research/themes/choicemodelling/

2. With a little help from my friends

3. Daddy, what do you really do at work?

4. … other questions I’ll try to answer
• Why do we want to understand and predict choices?
• Why is this especially important and challenging
now?
• How do we do it?
• Who is doing this, and are we the right people?
• Do we do it the right way?
• What can we learn from behavioural economics?
• What are the challenges and opportunities?

5. Why do we want to understand and predict
choices?
Why is this especially important and
challenging now?

6. Need understanding and prediction of
demand

7. Some big decisions are needed

8. Making choices in a difficult climate

9. Life is more and more digital

10. … and more international

11. How do we do it?
Who is doing this?
Are we the right people?
Do we do it the right way?

12. First we observe choices, then …
Valuation of
individual
components and
overall valuation
Forecasting of
choices/demand
in specific
scenarios

13. (A selection of the) leading modellers

14. We often treat choices in isolation …
Short term
vs medium term
vs long term
Transport
vs energy
vs health
….

15. … and generally look at individual people

16. Reality is more complicated

17. Are we modelling the right things?
Transport dominates,
but main emphasis on
short term choices
Other fields are
catching up
Long term
choices under-
researched

18. There are other experts on behaviour!

19. The BBC’s love of Daniel Kahneman

20. System 1 vs system 2 – fast vs slow

21. A new dawn?
• “… synthesize a new
behavioral science of
pleasure [extending] into
areas of individual
sensation of well-being and
choice in the context of
social network information
and approval …”

22. Do these theories apply in real world
behaviour?
Or in hypothetical choices?

23. Modelling not just for the sake of it
vs.

24. Zero cost: Ariely chocolate experiments
$0.15  73% $0.01  27%
$0.14  31% $0.00  69%

25. … an example from real life
£0 to £5 £5 to £8

26. … and it happens in SP too
Option with lowest
toll chosen
Willingness to pay higher
toll for reduced slowed
down time
No zero toll option 40.6% AUD 13.2/hr
Zero toll option available 74.7% AUD 11.9/hr

27. Framing & mental accounts
time vs cost
(p/min)
safety vs time
(min/ 1000 inj)
safety vs cost
(£/ 1000 inj)
direct valuation 11.07 42.75 3.34
inferred 7.81 30.15 4.73
bias in inferred -29.47% -29.47% 41.79%

28. Anchoring: real life cost referencing

29. … similar effects in value of time work
Base model:
22.28DKK/hr
With anchor
(at mean):
26.95DKK/hr
Route 1
45 minutes
25 DKK
Choose route 1
Route 2
37 minutes
31 DKK
Choose route 2

30. Choice sets can influence the choices
Online only Print only
Print &
online
16% 0% 84%
68% removed 32%

31. … we tend to ignore this in modelling
WTP
large vs compact, only
one fuel type available $1,638
large vs compact petrol,
large hybrid available $5,963
large vs compact hybrid,
large petrol available $14,731
… predictably
irrational?

32. Losses are more painful than gains

33. … but reality is complex
Date Toll Vehicles per day
August 2005 (opening) AUD 3.5 20K
October 2005 AUD 3.5 23K
November 2005 (free month) free 50.5K (+27.5K)
December 2005 AUD 3.5 26.5K (-24K)
March 2006 (half toll) AUD 1.75 34K (+7.5K)
July 2006 AUD 3.5 30K (-4K)

34. Does it matter?
What are the challenges and opportunities?

35. Does a richer individual representation
make much overall difference?

36. Observation/understanding vs prediction

37. Is SP (or other experimental) data valid?
Thurstone (1930s):
hypothetical
choices
Wallis and Friedman (1942):
“The responses are valueless
because the subject cannot
know how he would react.”

38. Best (& big) data often not accessible to us

39. What should we do next?

40. Lots of exciting things are happening already

41. Let’s not kill RUM yet!
HowmuchIregretmydecision
Distance travelled on a roller
coaster

42. Build bridges

44. Questions