pfsg conference2012 may [read-only] - ifst...essense profile consumer defined cata predetermined...
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Brief Intense Often focused on a referent
WHATis emotion? King & Meiselman
(2010)
Example: The chocolate made her happy
Activated Pleasant
Pleasant Unpleasant
Unactivated Unpleasant
Unactivated Pleasant
Low Activation
High ActivationActivated Unpleasant
450450
Larsen & Diener (1992)
Engagement
EMOTIONMODEL
Multidimensional
Liking data is not enough
Emotional quality of products is important for: – Differential advantage – Purchase decision
WHY measure
emotion?
EsSense Profile (King & Meiselman., 2010)
Overall acceptability (9 point scale)
Emotion terms (5 point scale)– 39 terms; most positive – Selected from published psychological emotion list
Reference:King, S. C., & Meiselman, H. L. (2010). Development of a method to measure consumer emotions associated with foods. Food Quality and Preference, 21 (2), 168-177
Samples
Subjects
Methodologies
11 UK Commercial Blackcurrant Squashes
Labeled as P1- 113
No Added Sugar
2 NicheAdded Sugar
6Added Sugar
Group 1n=100
METHODS &MATERIALS
Group 2n=100
EsSense Profile
Consumer defined CATA
Methodologies
EsSense Profile Consumer defined CATAPredetermined psychological
list
Consumer self generated & defined
list (1:1 Rep Grid Interview; n=29)5 point scale
(Quantitative data) Check-All-That-Apply(Qualitative data)
9 – point scale to measure liking
METHODS &MATERIALS
EsSense Profile (39) C-defined CATA (36) 25
POSITIVE(+ve)
AdventurousActive AffectionateCalmEnergetic EnthusiasticFreeFriendlyGladGoodGood-naturedHappyInterested Joyful Loving Merry Nostalgic Peaceful Pleasant
3 NEGATIVE
(-ve) Bored Disgusted Worried
11 UNCLEAR
(+/-ve)Aggressive Daring Eager Guilty Mild PoliteSteady Tame Understanding Wild
16 POSITIVE
(+ve)Approval At ease Attentive Comforted Curious Desire GoodHappyInterested Pleasant Pleased Refreshed Reminiscence SatisfactionTrust Warm
19NEGATIVE
(-ve)Angry Annoyed Bored Cautious Confused DisappointmentDiscontented Disgusted DispleasureNot refreshed Regret Resentment Sceptical Shocked Sickly Uncomfortable UnhappyUnpleasant Worried
1 UNCLEAR
(+/-ve)Guilty pleasure
PleasedSatisfied SecureTender Warm Whole
EMOTION LEXICONS
25POSITIVE
(+ve)AdventurousActive AffectionateCalmEnergetic EnthusiasticFreeFriendlyGlad
GoodGood-natured
HappyInterested Joyful Loving Merry
Nostalgic Peaceful
Pleasant
3 NEGATIVE
(-ve)
Bored DisgustWorried
11 UNCLEAR
(-/+ve)Aggressive Daring Eager
Guilty Mild PoliteSteady Tame Understanding Wild
16 POSITIVE
(+ve) Approval At ease Attentive Comforted Curious Desire
GoodHappyInterested Pleasant Pleased Refreshed
Reminiscence SatisfiedTrust
Warm
19 NEGATIVE
(-ve) Angry Annoyed
Bored Cautious Confused DisappointmentDiscontented
Disgust DispleasureNot refreshed Regret Resentment Sceptical Shocked Sickly Uncomfortable UnhappyUnpleasant
Worried
1 UNCLEAR
(+/-ve)
Guilty pleasure
PleasedSatisfiedSecureTender
Warm Whole
Reminiscence
EsSense Profile (39) C-defined CATA (36)
EMOTION LEXICONS
DATA ANALYSIS
Quantitativedata
Qualitativedata
EsSense Profile C-defined CATA
ANOVA and Tukeys Multiple Comparison test
to determine which products differed from each other
Principal Component Analysis (PCA)
Emotion mean datato determine product positioning
Consumer liking as supplementary variable.
Chi square testto determine which products differed from
each other
Multiple Correspondence Analysis
(MCA)Individual responses to CATA question
Products as supplementary variableto determine product positioning
ANOVA &
Tukeys Multiple Comparison liking scores
RESULTS: EsSense Profile Liking data
11 UK commercial blackcurrant juice
squashes (Labelled as P1 – P11)
No Added Sugar
Niche Added Sugar
Added Sugar
Product Liking scores
Group
4 4.1 A3 4.3 AB10 5.0 BC8 5.3 CD6 5.5 CDE5 6.0 DEF2 6.0 DEF1 6.3 EFG9 6.5 FG7 6.7 FG11 6.8 G
Incr
ease
d in
Lik
ingSimilar
low liking scores
Similar high liking
scores
Do products with similar liking scores induce different emotional responses??
ActiveAdventurousAffectionate
Bored Calm
Daring
Disgusted
Eager
Energetic
EnthusiasticFree
FriendlyGlad
Good
Good‐ natured
Happy
InterestedJoyful
Loving
Merry
Peaceful
Pleased
PleasantPoliteSatisfiedSecure
Steady
Tame
Tender
UnderstandingWarm
Whole
Worried
Liking
‐1
‐0.75
‐0.5
‐0.25
0
0.25
0.5
0.75
1
‐1 ‐0.75 ‐0.5 ‐0.25 0 0.25 0.5 0.75 1
F2 (5
.58 %)
F1 (83.70 %)
Variables (axes F1 and F2: 89.28 %)Correlation circle:29/ 39 emotion terms were found significant in blind assessment
22 +ve & 3+/- ve3 –ve
‘Tam
e’
RESULTS: EsSense Profile
PCA:
1
2
3
4
56 7
8
9
10
11
‐5
‐80 ‐64 ‐48 ‐32 ‐16 0 16 32 48 64
Biplot (axes F1 and F2: 89.28 %)
Liking
NEGATIVE POSITIVEHigh liking Low liking
RESULTS: EsSense Profile
Low liking scores:
2
4More ‘Tame’
High liking scores:
No Added Sugar
Niche Added Sugar
Added Sugar
15
Less 'Adventurous’ & Less ‘Daring’
Q: Do products with similar liking scores induce different emotional responses?
A: Yes. There is a significant difference for some emotions.
11975
10
2
43
The difference in mean data is ≤ 0.5 point over a 5 point scale.
RESULTS: EsSense Profile
Product Liking scores
Group
3 4.06 A10 4.26 A4 4.62 AB8 4.81 AB6 4.83 AB2 5.45 BC5 6.0 CD9 6.36 D11 6.57 D1 6.61 D7 6.62 D
RESULTS: C-Defined CATALiking data
11 UK commercial blackcurrant juice
squashes (Labelled as P1 – P11)
No Added Sugar
Niche Added Sugar
Added Sugar
Similar low liking
scores
Similar high liking
scores
Incr
ease
d in
Lik
ing
Do products with similar liking scores inducedifferent emotional responses??
No Added Sugar
NicheAdded Sugar
Added Sugar
PLEASANT UNPLEASANT
LOW
AC
TIVA
TIO
NH
IGH
High liking Low liking
MCA:
RESULTS: C-Defined CATA
Activated Pleasant
Pleasant Unpleasant
Unactivated Unpleasant
Unactivated Pleasant
Low Activation
High ActivationActivated Unpleasant
450450
Larsen & Diener (1992)
Engagement
EMOTIONMODEL
Multidimensional
No Added Sugar
NicheAdded Sugar
Added Sugar
Higher activated pleasant emotion
Interested Discontent
Higher activated
unpleasant emotion
MCA:
Desire
Angry
RESULTS: C-Defined CATA
Low liking scores:
High liking scores:
No Added Sugar
NicheAdded Sugar
Added Sugar
1
Q: Do products with similar liking scores induce different emotional responses?
A: Yes. Key examples:
11975
1043 More ‘Attentive’
34More
‘Refreshed’
5More
‘Bored’
9Less ‘Reminiscence’Less ‘Warm’
Frequency count for ‘Refreshed’
33 consumers 18 consumers
43
Furthermore, consumers with same liking have different emotional responses .
RESULTS: C-Defined CATA
More consumers have selected
pleasant/ positive emotions
Same liking scores of 7 but
Different emotions
MCA: Product 7 (Highest Liking)
RESULTS: C-Defined CATA
ID16
ID33
EsSense Profile C-Defined CATA
Liking data is not enough
Emotions can be explained using degree of pleasantness and activation as illustrated by Larsen and Diener (1992)
KEY FINDINGS
Similar product/ emotion plot
EsSense Profile C-Defined CATA
Easy and straightforward to use
Better discrimination
Reported more negative emotions
Time consuming and limited statistical analysis
Limited number of negative emotion terms
PROS AND CONS
OTHER WORK...
Condition 1:Product
Condition 2:Packaging
Condition 3:Informedtasting
Can sensory properties evoke emotions?? YES!! Emotion data were also collected under different
conditions:
Take home message
Products with similar liking scores can induce different emotional responses
Exploiting emotional responses
is crucial to connect people to brandvia sensory experience
REMINDER: POSTER
Measuring emotional response to food products
Eaton C1, Bealin-Kelly F2 & Hort J11Sensory Science Centre, University of Nottingham, UK.2SABMiller, Woking, UK.
Poster Board 1, Training room 1.
ACKNOWLEDGEMENTSupervisors: Dr Joanne Hort (UoN)Dr Carolina Chaya (UPM)
Acknowledge: Dr Ben Lawlor (GSK)Dr Tracey Hollowood(Sensory Dimensions)Prof Hal MacFie (Consultant) & all the volunteers who have taken part in my study!
Sponsor:
Thank you for your attentionAny Questions?
ContactsMay Ng : [email protected] Dr. Joanne Hort : [email protected]
• Reference:• Larsen, R. J., & Diener, E. (1992). Promises and problems with the ircumplex
model of emotion. Review of Personality and Social Psychology, 13, 25-59.
• Reference:• King, S. C., & Meiselman, H. L. (2010). Development of a method to measure
consumer emotions associated with foods. Food Quality and Preference, 21 (2), 168-177
Multiple Correspondence Analysis Popular technique to explore the relationships among
multiple categorical variable Data input: Individual CATA questions and 11 products
Methods & Materials
C-defined CATA Process of terms generation & selection Stage1: Terms elicitation
- 1:1 Rep Grid Interview (n=29)- Subjects presented with triads of products
289 365 972
Please indicate how two products differ in the same way from the third
Refreshing, premium,
guilty pleasure etc
etc
Stage 2: Defining constructs-Every subject has his/ her own list of constructs -Product assessment using individual constructs
109 Selection of terms based on word frequency table