1. What is the role of recognition in decision making? Ben Newell University College London & Centre for Economic Learning & Social Evolution Acknowledgements: David Shanks, Nicola Weston, Tim Rakow Funding: ESRC, Leverhulme Trust

2. Role of recognition in a cue- learning task Previous work examined empirical evidence for building blocks of fast & frugal heuristics (e.g., search, stopping, decision rules) in menu-based tasks Natural extension – examine evidence for fundamental ‘building block’ – the use of recognition

3. What do we mean by recognition? Distinction between the truly novel and the previously experienced E.g. nonwords – “prache”, “elbonics” Repetition of nonwords makes them recognisable How much ‘weight’ is placed on simple recognition?

5. Status of Recognition Information Proportion of trials on which recognized company chosen Proportion of trials on which advice is purchased Special RH = RLRH = RL < NR Consistent with other cues RH > RLNR = RH < RL RH = Recognition High (recognition best predictor of company performance) RL = Recognition Low (recognition poorest predictor of company performance) NR = No Recognition (Free advisor informational equivalent of RH)

6. Choices in accord with recognition Predictions: “special” RH = RL = 1.0; “consistent” RH > RL

7. Advice Purchase Predictions: “special” RH = RL (=0) < NR; “consistent” NR = RH < RL

8. Compensatory use of cues Evidence for compensatory cue use in all conditions, most in RL

9. Conclusions Recognition information not ascribed “special status” in cue learning task Treated as ‘just another cue’ in the environment (cf.,PROBEX Juslin & Persson 2002) What about inferences from memory – do these rely on a ‘different sort of recognition’?

10. Recognition, Availability, Familiarity……. Powerful influences on inferences from memory Availability Heuristic (Kahneman & Tversky) “Overnight Fame” effect (Jacoby) Recognition Heuristic (Goldstein & Gigerenzer) No RecognitionRecognition + Availability (ease of recall) Recognition

11. Recognition Heuristic Adaptive, non-compensatory, “all or nothing” use of recognition – “no other information is searched for” Cities task with football team information When is such a rule applied? What are the consequences…..?

12. “Paying for the name…….”

13. Paying for the name….. Hoyer & Brown (1990) – 3 brands of peanut butter, – “Aware group”:1 known, 2 unknown brands – 5 trials, opportunity to sample after each choice Support for use of brand recognition in choice of peanut butter (DVD’s, computers, cars…….??) % of participants choose known brand Explicit (sole) use of brand awareness ‘heuristic’ Trial 193.5%60% Trial 574.5%17%

14. Paying for the name….. Hoyer & Brown (1990) contd…. Comparison with “No Awareness” group Significantly more sampling of brands in No Awareness group AND Awareness/quality-difference manipulation showed: Reliance on Brand Awareness heuristic led to decreased search and final choice of inferior alternative % of participants chose high quality brand when in an ‘unknown brand’ jar Brand Awareness20% No Awareness59%

15. “A good name is better than riches” (?) Borges et al. (1999) – can “ignorance” beat the stock market? 180 German lay-people recognition of German stocks 6 month return on DAX 30: Dec 1996 – Jun 1997 Result replicated in 6 out of 8 tests Conclusion – ignorance can beat the stock market or big firms do well in strong bull (up) markets? Market IndexRec > 90%Rec < 10% +34%+47%+13%

16. “A good name is better than riches” (?) Boyd (2001) – test in a down or ‘bear market’ 184 US students recognition of 111 companies randomly selected from Standard & Poor’s 500 6 month return: June 2000 – December 2000 No evidence to support use of recognition heuristic in a ‘bear’ market Borges et al result a ‘big firm’ effect? Market IndexRec > 90%Rec < 10% -4.54%-14.75%+16.27%

17. “A good name is better than riches” (?) Rakow (2002) – further test in a strong market 53 UK students recognition of 30 companies in Italian Mib 30 8 week return: October – December 2002 Compared recognition portfolios, anti-recognition portfolios and expert portfolio with market index Only 7 out of 53 recognition portfolios outperformed market index How robust is recognition heuristic as an investment tool? Market IndexExpertRecognition Portfolio Anti-Recognition Portfolio +21.0% +13.3%+26.2%

18. When will recognition be accurate…? It depends on the domain….. f(n) = 2(n / N) (N - n / N -1)  + (N – n / N) (N – n – 1 / N – 1) ½ + (n / N) (n – 1 / N – 1)  f(n) = proportion correct inferences  = recognition validity  =knowledge validity N = reference class of objects n = recognized objects (fast and frugal?)

19. Deliberate or automatic? Automatic ‘feeling of familiarity’ + deliberate application of heuristic? “I recognise it so I’ll choose it” – deliberate selection and use of a heuristic from the toolbox? (cf., Kahneman & Frederick, 2002) Recognition + “relevance check”. Enron?

20. Conclusions Cue learning: recognition treated like other cues in the environment Consumer research:Exploitation of reliance on recognition Stock market investment: ‘big firm’ rather than recognition effect – how generalisable?

21. Where to next? Further tests of use of recognition in memory-based inference Cost/benefit effects on use of recognition Discussion of adaptive/maladaptive use of recognition Further specification of the domains in which the ‘recognition heuristic’ applies