food decisions: causes of biases
TRANSCRIPT
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Prof. Dr. Michael Siegrist
Food decisions: Causes of biases
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Experiential system Analytic system
1. Holistic 1. Analytic
2. Affective: pleasure-pain oriented 2. Logical: reason oriented (what is sensible)
3. Associationistic connections 3. Logical connections
4. Behavior mediated by ÒvibesÓ from past experiences
4. Behavior mediated by conscious appraisal of events
5. Encodes reality in concrete images, metaphors, and narratives
5. Encodes reality in abstract symbols, words, and numbers
6. More rapid processing: oriented toward immediate action
6. Slower processing: oriented toward delayed action
7. Self-evidently valid: Òexperiencing is believingÓ 7. Requires justification via logic and evidence
Two Modes of Thinking
Slovic et al. 2004
16.10.16 Prof. Dr. Michael Siegrist 2
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
In the food domain various heuristics help us to make quick decisions
Heuristics may result in biased decisions
The importance of heuristics
16.10.16 Prof. Dr. Michael Siegrist 3
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
People often rely on heuristics to make
judgments or decisions (e.g., availability,
representativeness, affect heuristic)
A general feature of heuristic judgment is
attribute substitution (Kahneman and
Frederick, 2005)
A target attribute (not readily accessible) is
substituted by an heuristic attribute (which
comes easier to mind)
Heuristics
16.10.16 Prof. Dr. Michael Siegrist 4
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Affect heuristic
16.10.16 Prof. Dr. Michael Siegrist 5
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
S�tterlin & Siegrist (2015)
16.10.16 Prof. Dr. Michael Siegrist 6
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Affect evoked by the nutrition information and perceived healthiness of breakfast cereals using the label Òfruit sugarÓ vs.
ÒsugarÓ in the nutrition table.
Fruit sugar Sugar
M (SD) [N] M (SD) [N]
Affect evoked by
the information 43.81 (20.05) [127] 36.14 (18.72) [124]
Perceived
healthiness 39.61 (21.52) [127] 32.51 (19.32) [124]
Note. Ratings of affect could range from 0 (very negative) to
100 (very positive). Ratings of perceived healthiness could range from 0 (not healthy at all) to 100 (very healthy).
Experimental Manipulation
Perceived Healthiness
Experimental Manipulation
Perceived Healthiness
Affect
a
b
7.10* (2.58)
1.31 (1.85)
0.75* (0.05)
7.67
* (2
.45)
16.10.16 Prof. Dr. Michael Siegrist 7
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Natural is better heuristic
16.10.16 Prof. Dr. Michael Siegrist 8
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Factors that Influence Perception of Naturalness
Rozin, 2005
16.10.16 Prof. Dr. Michael Siegrist 9
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Factors that Influence Perception of Naturalness
Evans et al., 2013
0 10 20 30 40 50 60 70 80 90 100
Orange juice
Orange juice with 2% fruit powder
Orange juice with 4% fruit powder
Orange juice with 6% fruit powder
Naturalness
16.10.16 Prof. Dr. Michael Siegrist 10
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
With E-Number (M,
SD) (N=121)
No E-Number (M, SD)
(N=123)
t-value
(E 100) Curcumin, natural food color (orange-yellow)
65.10 (32.26) 75.89 (26.42) 2.86**
(E 220) Sulfur dioxide, blocks browning reactions in dry fruits
39.55 (33.29) 46.72 (33.93) 1.66*
(E 620) Glutamic acid, flavor enhancer
30.62 (29.11) 37.89 (33.58) 1.81*
Food Additives: The Symbolic Power of
E-Numbers
16.10.16 Prof. Dr. Michael Siegrist 11
As how artificial or natural do you evaluate the following food additives?
(0=artificial, 100=natural)
** p < .01; * p < .05, one-tailed
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
The production of beef (red meat) is important for agriculture. Most meat is produced in intensive animal husbandry. This production method has
negative impacts on the environment and it is associated with animal suffering. Heavy consumption of red meat results in a significantly higher risk
to get colon cancer.
By means of biotechnology in-vitro meat is to be produced. In doing so, red meat is produced in the laboratory. This production method is more
environmentally friendly and it is associated with less animal suffering compared with traditional meat production. Heavy consumption of in-vitro
meat results in a significantly higher risk to get colon cancer. The risk is
comparable with the one of the consumption of red meat from traditional meat production
Risk of Traditional Versus
Cultured Meat
16.10.16 Prof. Dr. Michael Siegrist 12
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Traditional Meat
Cultured Meat t-value
How artificial (0) or natural (100) do you assess this meat?
62.65 (25.45) 17.96 (21.46) 15.06*
How unacceptable (0) or acceptable (100) do you perceive
the risk associated with this meat?
59.35 (25.87) 25.18 (26.38) 10.40*
Risk of Traditional Versus Cultured Meat
16.10.16 Prof. Dr. Michael Siegrist 13
* p < .001
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Risk of Traditional Versus Cultured Meat
16.10.16 Prof. Dr. Michael Siegrist 14
Experimental Manipulation
Acceptability of Risk
Experimental Manipulation
Acceptability of Risk
Naturalness
a
b
-34.17* (3.28)
-44.69* (2.97)
-4.83 (3.66)
AcAc
-4.83 (3.66)
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Participants were invited to a
sensory experiment
Evaluate a Òmousse au
chocolatÓ
Three groups
No information
Natural Vanilla
Artificial Vanillin
Impact of Symbolic Information:
Sensory Experience
16.10.16 Prof. Dr. Michael Siegrist 15
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
The Same Product, but Different Information
Condition 1: Control
(n = 47)
Condition 2: Natural vanilla
(n = 47)
Condition 3: Artificial vanilla
(n = 45)
M SD M SD M SD
Expectation 76.09 13.77 74.67 13.97 69.5 17.40
Liking (hedonic rating) 68.04ab
18.47 72.58a 16.64 61.64
b 23.07
Willingness to buy 4.00ab
1.22 4.40a .86 3.55
b 1.33
Note. Means with different letters are significantly different (p<.05)
16.10.16 Prof. Dr. Michael Siegrist 16
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Self-made foods taste better heuristic
16.10.16 Prof. Dr. Michael Siegrist 17
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Participants 60 students (32 females, 28 males, age: M = 24, SD = 3)
recruited in cafeterias and libraries
asked to participate Òin a taste testÓ
Procedure Self-prepared: Participant mixed all ingredients
together (recipe)
Other-prepared: RA mixed everything together
(but participant saw the recipe)
Milkshake 120 g of raspberries, 100 ml of milk (2.5% fat),
80 ml of cream, and 10 g of sugar 444 kcal
Study: Self prepared vs other-prepared
Dohle, Rall, Siegrist (2014) Food Quality and Preference
Prof. Dr. Michael Siegrist 18 16.10.16
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
0
50
100
150
200
250
self-prepared other-prepared
Co
nsu
mp
tio
n (
g)
Consumption
Note. Error bars indicate the standard errors of the means. p = .032 (one-tailed). Dohle, Rall, Siegrist (2014)
Food Quality and Preference
Prof. Dr. Michael Siegrist 19 16.10.16
Participants in the self-prepared
group
- liked the milkshake better
- perceived it as more natural
compared with participants in the
other-prepared group
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Food disgust is a food-rejection emotion
Protects against the ingestion of potentially harmful
agents
Disgust may also pose a problem for the acceptance of
novel foods, however
Disgust Heuristic
16.10.16 Prof. Dr. Michael Siegrist 20
Source: http://blogs.cfr.org/patrick/2013/05/16/theres-
a-fly-in-my-soup-can-insects-satisfy-world-food-
needs/
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
High value protein
Favourable fatty acid composition
High vitamin and mineral content
Low production requirements
(little water, space)
Efficient feed conversation
Small environmental
food print
16.10.16 Prof. Dr. Michael Siegrist 21
Insects as ÔMini-LivestockÕ (De Foliart, 1995)
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Survey results suggest that introducing insects in a processed
form may result in an increased
acceptance of food
Experiment
Control group: Tortilla chips
Experimental group: Tortilla chips with
cricket flour
Results suggest that participants in the
experimental group are more willing to eat
unprocessed foods compared with
participants in the control group
16.10.16 Prof. Dr. Michael Siegrist 22
Acceptance of Insects
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
Consumers decisions are often the result of the experiential
system Heuristics like the affect heuristic play an important role
Consumers value naturalness
Risks associated with novel foods are less acceptable compared
with the same risks of traditional foods
Self-preparation of foods influences liking
Disgust is an important barrier for the acceptance of novel foods
There are large differences between experts and laypeople
regarding risk prioritization of food hazards
Conclusions
16.10.16 Prof. Dr. Michael Siegrist 23
| | Department Health Sciences and Technology (D-HEST) Consumer Behavior CB
S�tterlin B, Siegrist M (2015) Simply adding the word "fruit" makes sugar
healthier: The misleading effect of symbolic information on the perceived
healthiness of food. Appetite 95:252-261.
Rozin P (2005) The meaning of "natural". Psychological Science
16:652-658.
Dohle, S., Rall, S. & Siegrist, M. (2014). I cooked it myself: Preparing
food increases liking and consumption. Food Quality and Preference,
33(1), 14-16.
Hartmann, C. & Siegrist, M. (2016). Becoming an insectivore: Results of
an experiment. Food Quality and Preference, 51, 118Ð122.
Literatur
16.10.16 Prof. Dr. Michael Siegrist 24