1) The document summarizes research on the relationship between experience, learning orientation, innovativeness, and performance in the beef production industry. 2) A cluster analysis of survey responses from over 1500 beef producers in Illinois identified three clusters characterized by their experience levels and commitment to learning. 3) Producers in the cluster with the highest learning orientation and lowest experience reported higher innovativeness and satisfaction with performance compared to the other clusters.

1. EXPERIENCE, LEARNING, AND INNOVATIVNESS IN
BEEF PRODUCTION: RESULTS FROM A CLUSTER
ANALYSIS
Dr. Eric T. Micheels
Department of Bioresource Policy, Business & Economics
Presentation at the 19th International Farm Management Congress
21-26 July 2013,
Warsaw University of Life Sciences
Warsaw, Poland
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2. Motivation

Big area of interest – performance in agriculture
• Performance driven by hard and soft skills
• Learning (Lourenzani et al., 2005; Shadbolt, 2005)
• Innovations that lead to increased productivity
• Experience (Nuthall, 2009; Wilson et al., 2001)
• Better judgment when making decisions
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3. Previous Research

Experience and Performance
• Older managers seek more info (Taylor, 1975)
• Managers of large farms that seek more info have
better rates of performance (Wilson et al., 2001)
• Experience related to short-term and long-term
efficiency (Hansson, 2008)
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4. Previous Research

Learning and Performance
• Learning may be only source of SCA (Slater and
Narver, 1995)
• Learning important in order to use new technologies
(Napier and Nell, 2007)
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5. Research Question

Stakeholders see experience as advantageous
• Lenders, landlords, employees
• However, experience may lead to rigidity (Boeker,
1997; Koberg et al., 2000)

Question: Is experience related to willingness to
learn (i.e. to challenge assumptions)?
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6. Cluster Analysis

Attempt to create homogeneous subgroups
from heterogeneous data

Grouping variables
• Managerial experience (in years)
• Learning orientation (summated scale)
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7. Data

Survey of 1500+ beef producers in Illinois in
2007
• Respondents were, on average:
• 68 years of age
• Had over 32 years of experience
• Managed farms with over 69 head of cattle
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8. Methods

Non-hierarchical, two-stage method to identify
clusters
• Clustered firms on experience and commitment to
learning
• Results showed three clusters

ANOVA to test for differences across clusters
• Innovativeness
• Satisfaction with performance
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9. Descriptive Statistics Across Clusters
Cluster 1
Cluster 2
Cluster 3
Experience (years)
25.85
51.83
23.01
Learning Orientation
31.17
35.99
40.91
Herd Size
64.17
76.84
70.92
Acres Operated
908.87
1069.03
882.50
Operator Age
69.44
62.97
70.52
Education*
3.97
3.49
4.03
Number of cases
113
76
96
* 1 = some high school, 2 = High school grad, 3 = Some college, 4 = Vocational/Tech degree, 5 = college grad, 6
= Graduate degree
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10. Learning
Orientation Items
Cluster 1 Cluster 2 Cluster 3 Average
Difference
E=25.85
E=51.83
E=23.01
L=31.17
L=35.99
L=40.91
…learning as a key to
improvement.
4.29
4.75
5.33
4.76
1.04
… learning is an
investment, not an
expense.
Learning is seen as …
necessary to guarantee
survival.
We challenge assumptions
….
There is… agreement on
our organizational vision….
All employees are
committed to the goals of
this farm.
Employees view
themselves as partners…
Personnel … realize [how]
they perceive the market
4.31
4.91
5.53
4.88
1.22
4.33
4.96
5.50
4.89
1.17
3.76
4.21
5.01
4.30
1.25
3.59
4.02
4.69
4.08
1.10
3.81
4.57
5.11
4.45
1.30
3.62
4.51
5.02
4.33
3.46
4.07
4.71
4.04
(High-Low)
1.40
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1.25

11. Cluster 1
Cluster 2
Cluster 3
E=25.85
E=51.83
E=23.01
L=31.17
L=35.99
L=40.91
22.07
23.47
25.57
29.779***
Technical innovation
accepted
4.15
4.50
4.91
15.741***
Seldom seek innovative
ideas#
4.31
4.51
5.10
14.183***
Innovation accepted
4.12
4.59
4.93
22.336***
Penalized for new ideas#
5.01
5.17
5.46
5.240*
Innovation is risky#
4.48
4.70
5.17
10.759**
Innovativeness
Items
Innovativeness (Summated)
F-Statistic
Note: Items with an # were negatively phrased and were reverse coded.
F-statistics: ***,**,* signify significance at the 0.001, 0.01, and 0.05 levels,
respectively
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12. Satisfaction with
Cluster 1
Cluster 2
Cluster 3
E=25.85
E=51.83
E=23.01
L=31.17
L=35.99
L=40.91
Performance (Summated)
21.90
23.51
24.64
7.610**
Return on farm assets
met expectations#
3.59
3.78
3.84
1.000
Satisfaction with overall
performance
3.70
4.13
4.45
11.962**
Return on production
investments
3.79
4.18
4.31
6.700*
Cash flow was
satisfactory#
3.72
3.74
3.85
0.313
Return on marketing
investments
3.80
4.05
4.26
5.361*
We receive higher prices
than competitors
3.44
3.74
3.96
5.972*
Performance
F-Statistic
Note: Items with an # were negatively phrased and were reverse coded.
F-statistics: ***,**,* signify significance at the 0.001, 0.01, and 0.05 levels, respectively
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13. Conclusions

Differences observed between clusters on
innovativeness and performance
• Firms that value learning also state they are willing
to accept new ideas
• Value of demonstration farms (Pangborn et al.,
2011) and learning groups (Clark et al., 2005;
Terblanche and Willemse, 2011)
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14. Implications for managers

Value in broadening the network
• Success may accrue to those that set an uncommon
table (Don Floyd, CEO of 4H)
• Especially beginning farmers
• Value in coopetition
• Source of learning
• Important to recognize areas where cooperation has
higher NPV than competition
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15. Thank you for your attention!
Eric T. Micheels
Assistant Professor
Department of Bioresource Policy,
Business & Economics
University of Saskatchewan
3D14 Agriculture
Saskatoon, SK S7N 5A8
Email: eric.micheels@usask.ca
Twitter: @ericmicheels
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