Presentation Ipsera 12 4 2011 Xx

Supply chain flexibility and customer satisfaction revisted

Results from higher order construct considerations and Rasch analyses

Jorieke MandersJorieke Manders andand Paul GhijsenPaul Ghijsen, , IPSERA, Maastricht, IPSERA, Maastricht, april april 1212th 2011th 2011

Overview

• Introduction

• Framework and problem statement

• Results of further analyses on supply chain flexibility and customer satisfaction

• Conclusion

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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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Framework 2010 and problem statement

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Study 2010

• Which capabilities of flexibility have an effect on customer satisfaction when used in combination?

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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 supportedStrategy Development Flexibility => Customer Satisfaction 0.408 3.572 0.000 H7 supported

• 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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p < 0,05 and t > 1,98

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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Furtheranalyseshigher order construct level

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Results higher order construct level

• From a comprehensive view logistics and spanning flexibility show a significant impact.

Relationship Coefficient t-value p-value Conclusion R²Product Development Flexibility => Customer Satisfaction

0.141 1.723 0.044 H1 Not supported 0.457

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

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p < 0,05 and t > 1.98

Raschanalyses

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Persons - map - items

Followed routing in Rasch analyses

• The construct validity

• Separation

• The way the response scale is used

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Construct validity and separation

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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 intersectionsP ++---------+---------+---------+---------+---------+---------++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 70Person [MINUS] Item MEASURE

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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

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

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p < 0,05 and t > 1,98

p < 0,05 and t > 1.98

Conclusion

• Flexibility with respect to logistics flexibility and spanning flexibility are important for increasing customer satisfaction.

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Questions, comments

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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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Results study 2010 Collinearity diagnostics

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Condition index - Variance proportions