Essays on supplier responsiveness and buyer firm value - Nyenrode ...

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Table 2.20 represented the reliability for the constructs in our model. The values are above 0.7, and for exploratory scales lower values of construct reliability are acceptable. In light of the exploratory nature of the supplier brand value scale as it created by us we have decided to keep it in the model. Therefore, as per Table 2.20 our constructs are reliable (Hair et al., 2006,p. 612). Table 2.20 Construct Reliability Construct Name Construct Reliability 1.Supplier Responsiveness 0.72 2.Idiosyncratic Relational Risk 0.71 3.Strategic Supplier Brand Value 0.54 4.Buyer Satisfaction 0.74 In the fourth step, we assessed our model; the results of this process are presented in Table 2.21. One of the first tests to check for model fit in this stage is the χ 2 test. The χ 2 tests whether the estimated covariance index is equal to the observed covariance index. Ideally our estimated model should be exactly the same as our predicted model, showing no difference between the χ 2 mean value for the null and estimated models. The null hypothesis is that there is no difference between the observed and estimated matrices. The χ 2 shows that the matrices are different in our model as the null hypothesis is supported at the 0.001 level (Hair et al., 2006). This means that our predicted model does fit the observed model. Although the χ 2 statistic is a powerful indicator, it alone is not enough to indicate the model fit (Joreskog & Sorbom, 1984). This is because of χ 2 sensitivity to sample size. For example, as the sample size increases above 200, the χ 2 test tends to show significance because an increased sample size inflated the χ 2 values. As it approaches or moves away from 100, it tends to indicate insignificance (Hair et al., 2006). Since our sample size is 164, we rely on the χ 2 indicator as one test of whether our model shows a relationship between the variables in the model. Our findings are consistent with the recommendations of Hair et al. (2006), who specified that the models should be insignificant. However, Hair et al. (2006) also state that SEM has no single fit statistic that best describes the overall model fit or strength of its predictions. Therefore, below we use a number of absolute and relative fit measures to assess our confirmatory factor model. GFI is a widely accepted absolute fit measure. A model is considered acceptable when it has a GFI value of ≥.9. Our model meets this limit with a value of 0.951 as shown in Table 2.21. RMSEA is sometimes called a badness-of-fit measure and is an absolute fit measure. RMSEA measures how good a model fits the whole population rather than just the sample. It is typically a good indicator for larger samples. The RMSEA is used to avoid a Type II error, which occurs when a model that actually fits the data is rejected. Acceptable values for RMSEA are between .05 and .08; less than .05 indicates a good fit. By this standard, our current model is acceptable with a RMSEA of 0.068. The second category of fit indices are incremental fit measures. These indices compare our proposed model with the null model (Hair et al., 2006). The 62
incremental fit index (IFI) is one from the range of incremental fit measures. Our model has an incremental fit index (IFI) value of .966 indicating a good fit. The next incremental fit index that we use is the comparative fit index (CFI) and it is specifically meant for samples with small sizes (Hair et al., 2006). We surpass the minimum level of 0.9 with our model score of 0.965, which is considered a good fit. Moreover, the Tucker Lewis index (TLI) has a value of 0.942 and that is above the minimal level of 0.90. Since our model meets the criteria of the goodness of fit measures, we accept the measurement model. Table 2.21 Measurement Model Indices Goodness of fit index Recommended Values Values χ 2 /degrees of freedom ≤ 3.00 1.76 Tucker Lewis Index (TLI) ≥ 0.90 0.94 Goodness-of-Fit Index ≥ 0.90 0.95 (GFI) Incremental Fit Index (IFI) ≥ 0.90 0.96 Comparative Fit Index ≤ 0.90 0.96 (CFI) Root Mean Square Error of Approximation (RMSEA) ≤ 0.08 0.06 In Table 2.22, we examine the standardized residual covariance. Table 2.22 presents the results of the difference between the sample and implied covariances. Each residual covariance has been divided by an estimate of its standard error (Jöreskog & Sörbom, 1984). The remaining 9 items in Table 2.22 standardized residual covariances have a standard normal distribution, as none of the items has a value that exceeds two in absolute value. Table 2.22 Standardized Residual Covariances 1 2 3 4 5 6 7 8 9 IM 0 Sales -0.08 0 Fair -0.39 0.00 0 RP 0.78 0.12 -0.09 0.75 AssBrand -0.76 -0.15 0.19 -0.39 0 CCC 0.00 0.12 0.71 1.00 -0.52 0 CF 0.29 0.18 1.07 -0.39 -0.95 -0.85 0 CustNPD -0.13 0.52 0.20 0.10 0.55 -0.43 -0.63 0 SIQ 0.44 -0.29 -0.89 1.61 -0.93 -0.21 0.38 -0.03 0 63
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ISBN 978-90-8980-055-8 © M. Abrahi
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Examination Committee Supervisor: P
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2.3 DEVELOPMENT OF THE CONCEPTUAL M
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5.1 RESEARCH FINDINGS 114 5.2 OVERA
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List of Tables Table 2.1 Representa
Page 12 and 13: PREFACE Oscar Wilde once said, “I
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Page 16 and 17: Figure 1.1 Mckinsey Survey Results
Page 18 and 19: 1.4 Scope PhD thesis This thesis fo
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Page 26 and 27: Table 2.1 highlights several promin
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Page 30 and 31: Therefore, there is a convergence i
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Page 44 and 45: Table 2.2 Modified Items of the MAR
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Page 53 and 54: Table 2.7 Component Matrix Buyer Sa
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iii) iv) Indeed, there may not be m
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uyer firm performance through a ser
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specifically highlighted the import
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5.5 Practical Implications From a m
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Summary in English This dissertatio
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is that, when developing marketing
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isk by 0.98 standard deviations. Su
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collectivist culture and a Confucia
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Overwegende dat Verhoef en Leeflang
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van de waarde te communiceren dat d
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erkennen dat dit niet altijd een mo
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ij de vraag of cultureel risico voo
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Businessweek. (2012). S&P/BusinessW
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-industry-09012011.html Grewal, R.,
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Langerak, F. (2001). Effects of mar
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Quelch, J. (2007). How to brand an
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Verhoef, P. C., & Leeflang, P. S. H
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1. The name of the company where yo
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9.The supplier seems to have good i
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17. The supplier takes a very long
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25. If the supplier were to find ou
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33.Does your strategic supplier als
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41.To what degree do those specific
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Supplier Brand Value 51.How likely
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Appendix B Scatter Plot Diagrams fo
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