• 沒有找到結果。

The structural model studies the fit and explanatory power of the entire model. In reference to Bagozzi and Yi (1988), Joreskog and Sorbom (1996), and Bentler (1990), seven indicators were selected to evaluate the fitness of the entire model, including the ratio of the chi-square value to the degree of freedom (χ2/d.f.),

吋usted goodness-of-fit index (AGFI), nonned fit index (NFI), non-nonned fit index (1'心甘FI), comparative fix index (CFI), relative fix index (RFI), and root mean square error of approximation (RMSEA). Results are summarized in Table 4.According to Table 4, Bagozzi and Yi (1988) believed that the ratios of the chi-square value to the degree of freedom (X2/d.f.) less than 3 are preferable (Cannines and McIver, 1981; Chin and Todd, 1995; Hair et al., 2005). All the ratios ofthe chi-square value to the degree offreedom (χ2/d.f.) in this study are

46

Fit indices

χ2/d.f

AGFI NFI NNFI

CFI

RFI

RMSEA

The Impacts o[Supply Chain Relational Benefit on lnler-organizational Knowledge Sharing - Cross Validalion o[ SEM

Table 4

Fit indices for Structural Models

Suggested Reference Measurement Structural

value result model

三三 3.00 8agozzi and Yi (1988); Hair el al 1.825 2.30 (2005)

0.80 DolI el al. (J 994); Hair el al. (2005) 0.80 0.80

0.90 DolI el al. (J 994); Hair el al. (2005) 0.90 。.90

0.90 8entler and 80nnett (J 980); 8entler 。 94 0.91 (J 990); Hair el al. (2005)

。 90 8entler and 80nnett (J 980); 8entler 0.95 0.92 (J 990); Hair el al. (2005)

0.90 8entler and 80nnett (J 980); 8entler 0.95 0.92 (1990); Hair el al. (2005)

三豆 0.08 Hair el al. (2005) 0.061 0.073

less than 3 (2.30). This indicates that even though the sample was small, the model was still acceptable. Our other indicators also fall into the suggested ranges, as follows: AGFI ~ 0.80 (0.80), NFI ~ 0.90 (0.90), NNFI 三 0.90 (0別), CFI 主

0.90 (0.92), RFI 三 0.90 (0.92), and RMSEA 三 0.08 (0.073). In general, the model fit the data well.

As demonstrated in Table 2 and Figure 5, based on the SEM-estimated path relationships among the dimensions with standardized coefficients (in Term 1), five out of nine hypotheses in the studies are significant atα= O.肘, and four hypotheses are significant atα= 0.01. The following structural path coefficients are slgm日cant: confidence benefits

relationship commitment (0.277), confidence benefits

trust (0.352), trust

relationship commitment (0.141), relationship commitment

willingness to share knowledge (0.316)

,

and trust

willingness to share knowledge (0.204).

In addition, in the SEM structural results in Term 2, the ratio of chi-square to the degree of freedom (χ2/d.f.) is smaller than 3 (2.43). This suggests that the model was acceptable even if the sample was too small. The values of other indicators are within the acceptable range, as follows: AGFI 主 0.80 (0.80), NFI 三 0.90 (0.90),

Chiao Da Managemenl ReνiewVol. 30No. 2, 2010 47

NNFI 主 0.90 (0.91), CFI 三 0.90 (0.92), RFI 三 0.90 (0.92), and RMSEA 三 0.08

(0.079). In general, the model in Term 2 日t the data well. In Term 2, we estimate the path among different dimensions based on SEM; the path values of standardized coefficients were used to test the nine hypotheses in the study. Five hypotheses are significant at α= 0.05, and four are significant atα= 0.01. The path values in Term 2 are described in Tab 5.

Figure 2 Test results

r---~

Relationship Benefit '

Confidence Benefits

i

[Social Benefit

|?令

'.Q~:

抖的,

Special T

t B e n e f i t s l h d r

*: p < 0.05, **: P < 0.01

4.5

Cross-Validity

R'9l.355

Relationship Commitment

Trust

R'9l.229

。 204**

R'=o.192

Knowledge Sharing

In addition to the measurements' basic reliability and validity, we applied the cross-validity to increase the validity and test whether the two models had consistent path relationship 伊 value). We sequentially conducted the Term 1 and Term 2 SEM analyses, and then substituted the derived chi-square values and degree of 企eedom of the two SEM models in the F-test to calculate the F-value.

The equation for the F-test is as follows:

:d /

F= ~生i

%2/

/ df2

48 The Impacts ofSupply Chain Relational Benefit on Jnter-organizational Knowledge Sharing-Cross Validation ofSEM

Table 5

Hypotheses testing Hypotheses

H1a H1a: The higher the confidence benefits" in the supply chain, the higher the inter-organizationalrelationship commitment."

Hlb H1b: The higher the social benefits" in the supply chain, the higher the inter-organizational "relationship commitment."

Hlc Hlc: The higher the special treatment benefits" in the supply chain, the higher the inter-organizational relationship commitment. "

H2a H2a: The higher the confidence benefits" in the supply chain, the higher the inter-organizationaltrust. "

H2b H2b: The higher the social benefits" in the supp1y chain, the higher the inter-organizationa1trust."

H2c H2c: The higher the specia1 treatment benefits" in the supp1y chain, the higher the inter-organizationa1trust. "

H3 H3: The higher the trust" in supp1y chain members, the higher the inter-organizationa1 "re1ationship commitment."

H4 H4: The higher the "re1ationship commitment" in the supply

Chiao Da Management ReviewVol. 30 No. 2. 2010

Special Treatment Benefits 0.164 Commitment

Confidence Benefits Trust 0.352**

Social Benefits Trust 0.152

Special Treatment Benefits 0.016 Trust

Trust Commitment 0.141 *

Commitment •Kn owledge 0.316**

Sharing

Trust •Kn owledge Sharing 0.204**

χ2/d. f. of measurement model 2.30

No significant differen心e in the whole model (F = 0.931)

50 The lmpacts ofSu,月IyChain Relational Benejìt on lnter-organizational Knowledge Sharing - Cross Validation of SEM

5. Conclusions

With the emergence of supply chain management philosophy, companies are concerned about internal knowledge sharing as well as knowledge sharing among supply chain members. Based on the principles of the social exchange theory, we studied how supply chain relationship benefits affect inter-organizational knowledge sharing.

The SEM tests reveal that six out of ten hypotheses in this study are supported by empirical data. The empirical results include the following: (1) The higher the confidence benefits of the supply chain relationship benefits, the higher the inter-organizational relationship commitment. (2) The higher the confidence benefits of the supply chain relationship benefits, the higher the inter-organizational trust. (3) The higher trust among supply chain members, the higher the willingness to share knowledge with other organizations. (4) The higher the supply chain relationship commitment, the higher the willingness to share knowledge with other organizations. (5) The higher the trust among supply chain meinbers, the higher the willingness to share knowledge with other orgamzations.

Based on the social exchange theory, we believe that the interaction among supply chain members is also a social relationship. The inter-organizational relationship benefit is an internal variable of social exchange, and knowledge sharing is a social exchange of “knowledge." Our results help the academic in understanding what kind of relationship benefits to focus on and maintain, in order to promote the willingness and actions of knowledge sharing among supply chain members. Such a perspective has long been ignored by the academics.

It is necessary to cross-examine the model in the process of model design.

The existence of a relationship between single dimensions does not imply that such a relationship also exists in the entire mode1. As a result, we need further analysis. Even though previous studies seem to have proved the pair-wise relationships, this is the first time a complete model has been studied, domestically or abroad. Therefore the examination is necessary. In addition, since the entire model was not exposed before, in order to avoid shortcomings of a

Chiao Da Managemen/ ReviewVol. 30 No. 2, 2010 51

single dimension, we conducted the inter-temporal cross-validity test to verify that the results are not a special phenomenon in a single period

Empirically, our results help companies access the dimensions of relationship benefits (confidence benefits, social benefits, and special treatment benefits) in knowledge sharing among supply chain members. As a result, supply chain members can create greater relationship comrnitments and trust to e曲ance

the willingness of knowledge sharing among supply chain members. The empirical results show that with respect to knowledge sharing among supply chain members, companies care more about the

confidence benefits" than the

social benefits" and

special treatment benefits" in the relationship benefits. This sheds light on many companies. In other words, special treatment benefits (such as price discount) do not significantly make supply chain members more willing to share knowledge. The long-term trust relationship remains the most effective means; it significantly increases the willingness to share knowledge with supply chain members.

Finally, our subjects of this study were large manufacturing companies in Taiwan. The generalization with other industries or small and medium enterprises requires more future empirical studies. In addition, to increase the explanatory power of models, future researchers can introduce variables based on relevant theories (such as the trading cost theory) to improve the prediction power of inter-organizational willingness to share knowledge.

6.Acknowledgements

This research was supported by National Science Council, Taiwan, Republic of China, under the contract number NSC 98-2410-H-265-002.

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