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TQM Model of Elements-Deployment Table Developed from Quality ...

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on the plus side, “9.2 Management Review is implemented”, “9.5<br />

Businesses Results is improved”, and on the minus side, “4.5<br />

Customer Satisfaction Degree is improved”.<br />

Factor 2: It is named "Product and service process factor", because the <strong>TQM</strong><br />

element existed that on the plus side, “3.3 Customer-relationships are<br />

constructed”, “2.6 Long term pr<strong>of</strong>it is ensured”, and on the minus side,<br />

“5.5 the GWQM process is established”, “6.1 Qualities, Environmental<br />

regulations, and standards are focused”.<br />

Factor 3: It was named "Relationship factor" because the <strong>TQM</strong> element exist that<br />

on the plus side, “3.3 Customer-relationships is constructed”, and on<br />

the minus side, the elements such as the customer, employee, and<br />

stockholder are concentrated, as “6.1 Qualities and Environmental<br />

regulations are focused”, “6.4 Processes Management and<br />

Improvement are proceeded”, “8.1 Basis <strong>of</strong> Human Resources<br />

Developments is established”, “9.4 Stockholders-relationship is<br />

improved”<br />

.<br />

(4) Accumurateive Contributiion Ratio is 0.976, caluculated by Factor 1, Factor 2,<br />

among <strong>of</strong> 3 factors that Factor model could be explained by these 2<br />

fctors.<br />

(B) Application <strong>of</strong> Principal Component Analysis<br />

(1) Selection <strong>of</strong> analysis method<br />

The matrix <strong>of</strong> <strong>Table</strong> side ☓ <strong>Table</strong> top <strong>of</strong> 48☓233 and 49☓49 for the time<br />

series comparison by the Principal Factor Analysis Method is prepared and<br />

analized, but the Correlation Coefficient Matrix fall the rank falling (omission).<br />

The reason is in the cause that there are a lot <strong>of</strong> 0 and no quite effective data in<br />

the element <strong>of</strong> the matrix. Moreover, because the number <strong>of</strong> rows was able to be<br />

used up to 256 rows, the Principal Component Analysis Method was adopted, and<br />

the matrix <strong>of</strong> 48☓49 was prepared and used.<br />

(2) Extraction and interpretation <strong>of</strong> Principal Component<br />

The Cumulative Contribution Ratio becomes 7.53% by 5 Principal<br />

Components as the <strong>Table</strong> 6.3 after the results <strong>of</strong> studies <strong>of</strong> the number <strong>of</strong><br />

Principal Component by the Eigenvalue.<br />

The Principal Component name was interpreted <strong>from</strong> the Principal Component<br />

Scorebook and the Principal Component Score Scatter Diagram with <strong>TQM</strong> <strong>Elements</strong><br />

<strong>Deployment</strong> <strong>Table</strong> and 5 Principal Components as follows.<br />

175

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