Measuring Multidimensional Preferences in Non-consumer Choice: Results of a Conjoint Analysis with Farmers Christian D. Schade, Wei-Shiun Chang, Christine Lauritzen The Institute for Entrepreneurial Studies and Innovation Management Humboldt-Universität zu Berlin Ravello (Italy): June 18 - 21, 2013 1
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Measuring Multidimensional Preferences in Non- consumer Choice: Results of a Conjoint Analysis with Farmers Christian D. Schade, Wei-Shiun Chang, Christine.
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Measuring Multidimensional Preferences in Non-consumer Choice: Results of a Conjoint
Analysis with Farmers
Christian D. Schade, Wei-Shiun Chang, Christine Lauritzen
The Institute for Entrepreneurial Studies and Innovation Management
Humboldt-Universität zu Berlin
Ravello (Italy): June 18 - 21, 2013
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Outline
• Introductiono Motivation
• Theoretical background
o Previous Literature
o Methodology
• Experiment Design
• Findingso Preferences of farmers
o Cluster analysis on farmers’
preferences
o Prediction of cluster
memberships
• Conclusion and Limitations
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Motivation
"It is not from the benevolence of the butcher, the brewer, or the baker
that we expect our dinner, but from their regard to their own interest.”
~ Adam Smith (1776) in The Wealth of
Nations
• Elicitation of farmers‘ preferences of farming as producers from two
general objectives ( the example of strawberry and cumcumber)o Short-term monetary self-regard aspect
• 19 Farmers from Uelzen, Germany, Session run with 20-station mobile lab
in Uelzen, December 2012
• 35 Students from Georg August Universität, sessions run with
mobile lab in Göttingen, January 2013
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General statistics of participants
Student Farmer Pooled
Age 24.06 (3.886) 30.68 (7.853) 25.91 (6.029)
Female ratio 0.286 0.156 0.250
Parents in farming 0.592 (0.497)
Farming as career 0.939 (0.242)
Organic-favored 0.305
Farm ownership ratio 0.842
Years of possession (farm) 5.684 (7.111)
# of employee 4.579 (2.341)
Farm size (hectares) 272.6 (220.0)
Risk aversion (turning
point)
6.182 (1.646)a 6.000 (1.732) 6.140 (1.652)
# of obs 49 19 68
Parentheses are standard deviation. a: sample size=44 for students, 13 for farmers, 57 for
pooled
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Average ranking of situation
Situation Description Ave. ranking Std. dev.
A I60,000, V10, EH, FL3.176 (1.050)
B I20,000, V30, EH, FL6.750 (1.164)
C I20,000, V10, EL, FL7.265 (0.971)
D I20,000, V30, EL, FH5.750 (1.250)
E I20,000, V10, EH, FH1.676 (1.112)
F I60,000, V30, EH, FH4.117 (1.399)
G I60,000, V30, EL, FL5.162 (1.532)
H I60,000, V10, EL, FH2.103 (1.161)
I: net income; V: volatility; E: negative externality; F: Fertility
作者
E, H, A 用同樣的顏色 加匡起來 從 situation 到ave. ranking. B, C, D用另一個顏色框起來然後用動畫,EHA的框先出來, 然後BCD的框再出來
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Data analyses
• Conjoint analysis to analyze relative importance of attributes
• Cluster analysis to analyze preference heterogeneity among
farmers
• Probit regressions to predict cluster memberships
Y o Dependent variables
• Cluster 1 vs other clusters (Y=1 if cluster 1, otherwise =0)• Cluster 2 vs other clusters (Y=1 if cluster 2, otherwise =0)• Cluster 3 vs other clusters (Y=1 if cluster 3, otherwise =0)
o Independent variables • For students: age, gender, risk propensity, career plan (to be a
farmer), parents in agri-business, farm type inclination (organic vs conventional farm)
• For farmers: age, gender, risk propensity, ownership, years of possession, # of employee in farm, farm size
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Findings 1 (conjoint analysis): Fertility is most important factor, followed by volatility, income and externality.