Presentation by Jorieke Manders and Paul Ghijsen at the IPSERA 2011 meeting in Maastricht

1. Supply chain flexibility and customer
satisfaction revisted
Results from higher order construct
considerations and Rasch analyses
Jorieke Manders and Paul Ghijsen,
IPSERA, Maastricht, april 12th 2011

2. Overview
• Introduction
• Framework and problem statement
• Results of further analyses on supply chain
flexibility and customer satisfaction
• Conclusion
2

3. Introduction
• To cope with uncertainty, a fast changing environment and
globalisation firms aim for flexibility (Upton 1994; 1995, Zhang
et al. 2002a; 2002b; 2006).
• To achieve the level of flexibility in relation to satisfy
customers, firms must look beyond the organizational
boundaries (supply chain- or value chain perspective)
(Day 1994; Schmenner and Tatikonda 2005; Slack 2005b)
• Starting point: Value chain model Zhang et al. (2002),
Zhang, Vonderembse and Lim/Cao (2002, 2003, 2005,
2006 en 2009).
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4. Framework 2010 and problem statement
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5. Study 2010
• Which capabilities of
flexibility have an
effect on customer
satisfaction when
used in combination?
5

6. Results study 2010
Relationship Coefficient t-value p-value Conclusion R²
Product Modification Flexibility => Customer Satisfaction 0.208 2.543 0.006 H1 supported 0.478
New Product Flexibility => Customer Satisfaction -0.139 1.406 0.082 H2 not supported
Volume Flexibility => Customer Satisfaction 0.108 1.121 0.133 H3 not supported
Mix Flexibility => Customer Satisfaction 0.052 0.573 0.284 H4 not supported
Physical Distribution Flexibility => Customer Satisfaction 0.200 2.741 0.004 H5 supported
Demand Management Flexibility => Customer Satisfaction 0.105 0.925 0.179 H6 not supported
Strategy Development Flexibility => Customer Satisfaction 0.408 3.572 0.000 H7 supported
p < 0,05 and t > 1,98
• From a comprehensive view only product modification-,
physical distribution and strategy development flexibility show
a significant impact.
• No indication of multicollineairity. The condition index
becomes higher but remains under the value of 30 (28,7)
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7. Comments
• Is it possible to make an index of the degree of flexibility to benchmark
between organizations (IBEC)?
• Why not expand this study with the relationship between flexibility and
more countable data like profit, turnover, etcetera (IBEC).
• There are different sectors in the sample, so control the effect of these
sector in the sample (IPSERA) and/or maybe you can add the sector as a
dummy coded variable in the model (AoM)
• Why not model the higher level construct as such? (IPSERA)
• Consider the different dimensions of customer satisfaction and the
difference between customer satisfaction on the short and long term in
relation to the flexibility dimensions (IPSERA and AoM).
• Go for a more detailed and rigid approach with more than only the
managers perspective about flexibility and customer satisfaction (AoM).
• Standard deviations decrease as the questionnaire progress.
Further analyses?! (IPSERA and AoM)
• Check for multicollineairity (IPSERA and AoM)
• Work out the check for non respons bias
and common method bias (IPSERA and AoM)
• Increase the number of surveyed companies (IPSERA and AoM)
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8. Further
analyses
higher order
construct
level
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9. Results higher order construct level
Relationship Coefficient t-value p-value Conclusion R²
Product Development Flexibility => Customer 0.141 1.723 0.044 H1 Not supported 0.457
Satisfaction
Manufacturing Flexibility => Customer Satisfaction 0.127 1.029 0.153 H2 Not supported
Logistics Flexibility => Customer Satisfaction 0.224 2.671 0.005 H3 supported
Spanning Flexibility => Customer Satisfaction 0.412 4.043 0.000 H4 supported
p < 0,05 and t > 1.98
• From a comprehensive view logistics and spanning flexibility
show a significant impact.
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10. Persons - map - items
Rasch
analyses
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11. Followed routing in Rasch analyses
• The construct validity
• Separation
• The way the response scale is used
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12. Construct validity and separation
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13. The way the response scale is used
|CATEGORY OBSERVED|OBSVD SAMPLE|INFIT OUTFIT||STRUCTURE|CATEGORY|
|LABEL SCORE COUNT %|AVRGE EXPECT| MNSQ MNSQ||CALIBRATN| MEASURE|
|-------------------+------------+------------++---------+--------+
| 1 1 70 2| -.61 -.89| 1.26 1.39|| NONE |( -3.49)| 1
| 2 2 509 14| .11 .09| 1.02 1.05|| -2.30 | -1.43 | 2
| 3 3 897 24| .54 .58| .95 .98|| -.22 | -.01 | 3
| 4 4 1689 45| 1.01 1.03| 1.00 1.04|| .17 | 1.43 | 4
| 5 5 570 15| 1.56 1.49| .92 .95|| 2.34 |( 3.52)| 5
+------------------------------------------------------------------
CATEGORY PROBABILITIES: MODES - Structure measures at intersections
P ++---------+---------+---------+---------+---------+---------++
R 1.0 + 5555555+
O | 555555 |
B |111 555 |
A | 11 5 |
B .8 + 11 55 +
I | 1 5 |
L | 1 5 |
I | 1 222 5 |
T .6 + 1 22 22 5 +
Y | 1 2 2 5 |
.5 + 12 2 44444 5 +
O | 21 2 4 * |
F .4 + 2 1 2 4 5 44 +
| 22 1 2 4 5 4 |
R | 2 1 33*33 5 4 |
E | 2 1 33 4 2 33 5 44 |
S .2 + 22 1 33 4 2 * 4 +
P | 22 3*1 4 *5 33 44 |
O |222 33 ** 5 2 33 444 |
N | 3333 44 11*55 222 333 444444 |
S .0 +*******************555555 11111111***************************+
E ++---------+---------+---------+---------+---------+---------++
-50 -30 -10 10 30 50 70
Person [MINUS] Item MEASURE
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14. Results lower and higher order construct
level analyses based on Rasch measures
Relationship Coefficient t-value p-value Conclusion R²
Product Modification Flexibility => Customer Satisfaction 0.147 1.308 0.195 H1 not supported 0.326
New Product Flexibility => Customer Satisfaction -0.035 -0.310 0.757 H2 not supported
Volume Flexibility => Customer Satisfaction 0.085 0.785 0.451 H3 not supported
Mix Flexibility => Customer Satisfaction 0.028 0.245 0.028 H4 not supported
Physical Distribution Flexibility => Customer Satisfaction 0.222 2.278 0.025 H5 supported
Demand Management Flexibility => Customer Satisfaction 0.232 2.131 0.036 H6 supported
Strategy Development Flexibility => Customer Satisfaction 0.295 2.695 0.009 H7 supported
p < 0,05 and t > 1,98
Relationship Coefficient t-value p-value Conclusion R²
Product Development Flexibility => Customer Satisfaction 0.110 0.985 0.328 H1 Not supported 0.340
Manufacturing Flexibility => Customer Satisfaction 0.057 0.506 0.614 H2 Not supported
Logistics Flexibility => Customer Satisfaction 0.379 3.645 0.000 H3 supported
Spanning Flexibility => Customer Satisfaction 0.296 2.852 0.006 H4 supported
p < 0,05 and t > 1.98
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15. Conclusion
• Flexibility with
respect to
logistics
flexibility and
spanning
flexibility are
important for
increasing
customer
satisfaction.
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16. Questions, comments
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17. 17

18. Methodology
• Pilot study
• Survey (Dutch Manufacturing companies > 100 employees)
Population 7000, 1000 companies asked
• Dillman’s Tailored Design method
• Questionnaire (Zhang et al. 2002, 2003, 2005, 2006)
• Responses (83 usable)
senior managers, including presidents/CEO, vice presidents,
(general) managers, directors, production managers, logistics
managers and others, i.e. purchasing managers, marketing
managers, supply chain managers and -specialists
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19. Results study 2010
Collinearity diagnostics
Condition index - Variance proportions
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