Wednesday 19th June 2019
PREFERENCE & EMOTIONS
8.30 Registration
9.00 Introduction
9.30-10.30 John Prescott – Explaining preferences
Theoretical background
• Psychology of consumer preferences
• Influences: exposure, familiarity, attention, learning mechanisms
10.30-11.00 BREAK
11.00-12.00 John Prescott – Measuring preferences: methods and case studies
• Explicit and implicit measures of preferences
• Rating scales: applications and limitations
• Implicit methods: Implicit association task (IAT), priming
12.00-13.00 Erminio Monteleone – Interpreting individual differences in liking
Hands on: Interpretation of preference mapping
13.00-14.00 LUNCH
14.00-15.00 Sara Spinelli – Explaining emotions
Theoretical background
• What are emotions
• Emotions and decision-making
• Emotions and language
15.00-15.30 BREAK
15.30-17.00 Sara Spinelli – Measuring emotions: methods and case studies
• Explicit measurements: verbal and visual self-reports Standardised and product specific questionnaires; examples: EsSense Profile, GEOS, EmoSemio, PrEmo
• Implicit measurements: Implicit Association and Emotive; Projection Test
• Measuring emotions through physiological measures (ANS)
• Measuring emotions from the brain: applied consumer neuroscience
Emotions in product development
• Emotions in the product experience: from the product to the packaging (and back)
• Sensory and branding: the impact of expectations on emotions
17.00-18.00 Sara Spinelli & John Prescott – Designing a study: emotions, liking, preference
Hands on:
Implicit association task test
Questionnaire design and translation
Multi-country studies
Thursday 20th June 2019
EXPECTATIONS & INDIVIDUAL DIFFERENCES
9.00-10.30 John Prescott – Explaining expectations
Theoretical background
• Expectations as a psychological construct
• Sources of expectations: memory, associations
• Types of expectations: sensory-based, hedonic or affect-based, credencebased expectations
10.30-11.00 BREAK
11.00-12.00 Gastón Ares – Measuring expectations: methods and case studies
Hands on:
Expectation test
Conjoint analysis: Evaluation of how extrinsic characteristics influence consumer expectations
12.00-13.00 Erminio Monteleone – Analysing expectations
• Assimilation and contrast effects
• The role of expectations in consumer driven product development
• Measuring expectations to gain an insight into product performance
13.00-14.00 LUNCH
14.00-15.00 John Prescott – Explaining individual differences
Theoretical background
• Segmenting for liking, taste responsiveness, psychological traits and attitudes, physiological measures
15.00-15.30 BREAK
15.30-16.30 Gastón Ares – Measuring individual difference
• Segmentation and cluster analysis
• Hierarchical cluster analysis
• K-means cluster analysis
• Selecting the number of clusters
• Comparing clusters and segments
16.30.00-18.00 R-Lab
Gastón Ares
- R-basics: How to import data and launch an analysis
- Hands on Conjoint Analysis using R:
Relative importance of intrinsic and extrinsic characteristics on consumer perception - Cluster Analsyis using R
Friday 21st June 2019
CONTEXT AND PRODUCT CHARACTERISATION
9.30-10.30 John Prescott – Explaining context
Theoretical background
• What is a context?
• Context has many meanings
• Context and individual differences
10.30-11.00 BREAK
11.00-12.00 Sara Spinelli – Studying context: methods and case studies
• Context and product experience: Natural/naturalistic/Lab context
• Central Location Test vs Home Test
• Evoked context: written scenarios, videos, pictures, immersive settings, virtual reality. Pros and cons
• Appropriateness of situational contexts
• Contexts and expectations
• Context and emotions
12.00-13.00 Gastón Ares & Sara Spinelli – Interpreting context appropriateness: exercises
13.00-14.00 LUNCH
14.00-15.00 Gastón Ares – Explaining sensory differences and similarities
Novel methods for sensory characterisation in product development
• Based on global differences (holistic)
• Sorting and Projective Mapping/Napping®
Hands-on: projective mapping test
15.00-15.30 BREAK
15.30-16.30 Gastón Ares – Measuring product perception: methods and case studies
• Application of check-all-that-apply (CATA) and rate-all-that-apply (RATA)
• Questionnaire design
• When does the addition of a rating task improves the performance of CATA?
• Insights for product optimization: Penalty-lift and penalty analysis based on the ideal product
16.30.00-18.00 R-Lab
Gastón Ares
Analysing product perception
- Application of CATA questions including sensory, emotional and wellbeing-related terms
- Hands on: CATA analysis using R
- Multiple Factor Analysis using R:
Application to projective mapping data under blind and informed conditions
