Research Article
Dynamic Modeling and Simulation of How Information Sharing Influences Supply Chain Performance
Table 1
The validity and reliability.
| Item | Factor loadings | Variance of common factor | Cronbach’α□ | Factor 1 | Factor 2 | Factor 3 |
| SC performance | Cost | 0.678 | 0.192 | 0.269 | 0.569 | 0.893 | Customer satisfaction | 0.746 | 0.19 | 0.006 | 0.593 | Shared benefits | 0.78 | 0.151 | 0.198 | 0.67 | Information sharing quantity | Information sharing quality | Accurate information | 0.318 | 0.733 | 0.107 | 0.65 | Timely information | 0.427 | 0.601 | 0.288 | 0.626 | Effective decision information | 0.654 | 0.388 | 0.258 | 0.645 | Information sharing coverage | Diversified information | 0.24 | 0.64 | 0.17 | 0.498 | Deepened information content | 0.079 | 0.826 | 0.132 | 0.707 | Partner trust (cooperation strategy consistency) | 0.721 | 0.334 | 0.089 | 0.639 | Integration degree of SC | Dynamic allocation of resources | −0.062 | 0.242 | 0.852 | 0.788 | Network partnership | 0.522 | 0.105 | 0.679 | 0.744 | Information decision | 0.445 | 0.195 | 0.724 | 0.76 | Eigenroot value (before rotation) | 5.602 | 1.16 | 1.124 | — | Cumulative variance interpretation rate (%) (before rotation) | 46.686 | 56.353 | 65.721 | — | Cumulative variance interpretation rate (%) (after rotation) | 28.270 | 48.740 | 65.721 | — | KMO | 0.853 | — | Bartlett’ test | 498.198 | | df | 66 | | | 0 | |
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