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Presentation Ipsera 12 4 2011 Xx

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

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


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  • 1. Supply chain flexibility and customer satisfaction revisted Results from higher order construct considerations and Rasch analysesJorieke 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). 3
  • 4. Framework 2010 and problem statement 4
  • 5. Study 2010• Which capabilities of flexibility have an effect on customer satisfaction when used in combination? 5
  • 6. Results study 2010Relationship Coefficient t-value p-value Conclusion R²Product Modification Flexibility => Customer Satisfaction 0.208 2.543 0.006 H1 supported 0.478New Product Flexibility => Customer Satisfaction -0.139 1.406 0.082 H2 not supportedVolume Flexibility => Customer Satisfaction 0.108 1.121 0.133 H3 not supportedMix Flexibility => Customer Satisfaction 0.052 0.573 0.284 H4 not supportedPhysical Distribution Flexibility => Customer Satisfaction 0.200 2.741 0.004 H5 supportedDemand 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 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) 6
  • 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) 7
  • 8. Furtheranalyseshigher orderconstructlevel 8
  • 9. Results higher order construct levelRelationship Coefficient t-value p-value Conclusion R²Product Development Flexibility => Customer 0.141 1.723 0.044 H1 Not supported 0.457SatisfactionManufacturing Flexibility => Customer Satisfaction 0.127 1.029 0.153 H2 Not supportedLogistics Flexibility => Customer Satisfaction 0.224 2.671 0.005 H3 supportedSpanning Flexibility => Customer Satisfaction 0.412 4.043 0.000 H4 supportedp < 0,05 and t > 1.98 • From a comprehensive view logistics and spanning flexibility show a significant impact. 9
  • 10. Persons - map - itemsRaschanalyses 10
  • 11. Followed routing in Rasch analyses• The construct validity• Separation• The way the response scale is used 11
  • 12. Construct validity and separation 12
  • 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 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 70 Person [MINUS] Item MEASURE 13
  • 14. Results lower and higher order constructlevel 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 14
  • 15. Conclusion• Flexibility with respect to logistics flexibility and spanning flexibility are important for increasing customer satisfaction. 15
  • 16. Questions, comments 16
  • 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 18
  • 19. Results study 2010Collinearity diagnosticsCondition index - Variance proportions 19