Business Process Simulation- An...

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185 Annexure I

Transcript of Business Process Simulation- An...

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Annexure I

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Annexure-II

LIST OF AUTOMOBILE MANUFACTURERS IN NORTH INDIA Sr. No. Name of the Automobile

Manufacturer Contact Address

1. Punjab Tractors Ltd. Phase-IV, Industrial Area, SAS Nagar, Mohali-160055, Punjab.

2. Hero Honda Motors Ltd. 69 Km Stone, Delhi-Jaipur Highway, Dharuhera-122100, Distt. Rewari, Haryana.

3. Bajaj Auto Ltd. Plot No. 2, Sector-10, Phase-II E, Pantnagar, Sidcul, Rudrapur, Uttranchal.

4. New Holland Tractors Ltd. Plot No.-3, Udyog Kendra, Greater Noida-201306, Uttar Pradesh.

5. Swaraj Mazda Ltd. Village Asron, P B No.-38, Ropar-141001, Punjab.

6. HMT Tractors Ltd. Tractor Division, Pinjore-134101, Distt. Panchkula, Haryana.

7. International Tractors Ltd. Vill. Chak Gujran, Jalandhar Road, Hoshiarpur-146022, Punjab.

8. Ford India Pvt. Ltd. Plot No.-2, Industrial Area No.-1, Pitampur-454775, Distt. Dhar, M.P.

9. Honda Siel Cars India Ltd. Plot No. A-1, Sector 40/41, Surajpur-Kasna Road, Greater Noida-201203, Uttar Pradesh.

10. Maruti Suzuki India Ltd. Palam-Gurgaon Road, Gurgaon-122015, Haryana.

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11. Escorts Ltd. Plot No.- 2 & 3, Sector-13, Faridabad-121007, Haryana.

12. Honda Motorcycle & Scooter India Pvt. Ltd.

Plot No.- 1, Sector-3, IMT Manesar, Gurgaon-122050, Haryana.

13. TVS Motor Co. Ltd. Bhatian Village, Nalagarh Post & Taluk, Solan-174101, Himachal Pradesh.

14. Suzuki Motorcycle India Pvt. Ltd. Village Kherkidhaula, Badshahpur, NH-8, Link Road, Gurgaon-122050, Haryana.

15. Yamaha Motor Solutions (India) Pvt. Ltd.

A-3, Industrial Area, Noida-Dadri Road, Surajpur-201306, Distt. Gautam Budh Nagar, Uttar Pradesh.

16. General Motors India Pvt. Ltd. Plot No. 72, SIPCOT Industrial Complex, Ranipet-632403.

17. International Cars & Motors Ltd. 25th Mile Stone, NH-70, Una-Amb Road, Industrial Area, Amb, Distt. Una-177203, Himachal Pradesh.

18. Standard Tractors Ltd. Standard Chowk, Barnala-148101, Punjab.

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Annexure-III

List of Vendors of Simulation Softwares used by Automobile

Manufacturers in North India

S. No. Simulation

Software Vendor

Website

1. NX-IDEAS Siemens PLM Software www.plm.automation.siemens.com

2. ProcessModel ProcessModel Inc. www.processmodel.com

3. HyperMesh Altair Corporation www.altairhyperworks.com

4. Nastran MSC Software

Corporation

www.mscsoftware.com

5. ProModel ProModel Corporation www.promodel.com

6. AutoMod Visual8 Simulation

Solutions

www.visual8.com

7. Star-CD CD-adapco www.cd-adapco.com

8. Moldex 3D CoreTech System Co.

Ltd.

www.moldex3d.com

9. Tecnomatix Siemens PLM Software www.plm.automation.siemens.com

10.

CATIA V4

Dassault Systems www.3ds.com

11. ExtendSim Imagine That Inc. www.extendsim.com

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Annexure-V

Output of Factor Analysis: For User Support:

Correlation Matrixa

1.000 .552 .185 -.059 .147 .128 .271 .249 .246 .234 .251.552 1.000 .406 .115 .253 .225 .266 .154 .440 .396 .517.185 .406 1.000 .675 .478 .391 .301 .178 .289 .071 .118-.059 .115 .675 1.000 .598 .481 .302 .229 .284 -.079 .088.147 .253 .478 .598 1.000 .598 .451 .236 .077 -.269 .000.128 .225 .391 .481 .598 1.000 .783 .530 .281 .114 .394.271 .266 .301 .302 .451 .783 1.000 .453 .267 -.026 .328.249 .154 .178 .229 .236 .530 .453 1.000 .238 .352 .369.246 .440 .289 .284 .077 .281 .267 .238 1.000 .128 .606.234 .396 .071 -.079 -.269 .114 -.026 .352 .128 1.000 .558.251 .517 .118 .088 .000 .394 .328 .369 .606 .558 1.000

.000 .001 .162 .007 .016 .000 .000 .000 .000 .000.000 .000 .027 .000 .000 .000 .005 .000 .000 .000.001 .000 .000 .000 .000 .000 .001 .000 .117 .024.162 .027 .000 .000 .000 .000 .000 .000 .095 .071.007 .000 .000 .000 .000 .000 .000 .099 .000 .500.016 .000 .000 .000 .000 .000 .000 .000 .028 .000.000 .000 .000 .000 .000 .000 .000 .000 .334 .000.000 .005 .001 .000 .000 .000 .000 .000 .000 .000.000 .000 .000 .000 .099 .000 .000 .000 .016 .000.000 .000 .117 .095 .000 .028 .334 .000 .016 .000.000 .000 .024 .071 .500 .000 .000 .000 .000 .000

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

Correlation

Sig. (1-tailed)

Q2.4.1 Q2.4.2 Q2.4.3 Q2.4.4 Q2.4.5 Q2.4.6 Q2.4.7 Q2.4.8 Q2.4.9 Q2.4.10 Q2.4.11

Determinant = .002a.

Inverse of Correlation Matrix

1.708 -.742 -.098 .460 -.350 .548 -.536 -.325 -.252 -.254 .300-.742 2.961 -.885 .790 -1.373 .913 -.544 .594 -.681 -1.101 -.683-.098 -.885 2.463 -1.526 .062 -.201 -.118 .112 -.172 -.270 .657.460 .790 -1.526 2.960 -1.311 -.107 .097 -.049 -.735 -.337 .058-.350 -1.373 .062 -1.311 3.468 -2.025 .784 -.355 .974 1.670 .055.548 .913 -.201 -.107 -2.025 4.927 -2.814 -.363 -.307 -1.138 -.638-.536 -.544 -.118 .097 .784 -2.814 3.389 -.418 .355 1.275 -.356-.325 .594 .112 -.049 -.355 -.363 -.418 1.804 -.305 -.856 .043-.252 -.681 -.172 -.735 .974 -.307 .355 -.305 2.359 1.230 -1.498-.254 -1.101 -.270 -.337 1.670 -1.138 1.275 -.856 1.230 3.018 -1.388.300 -.683 .657 .058 .055 -.638 -.356 .043 -1.498 -1.388 3.229

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

Q2.4.1 Q2.4.2 Q2.4.3 Q2.4.4 Q2.4.5 Q2.4.6 Q2.4.7 Q2.4.8 Q2.4.9 Q2.4.10 Q2.4.11

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KMO and Bartlett's Test

.622

1692.77555

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .8461.000 .8251.000 .7551.000 .8431.000 .7851.000 .8701.000 .7751.000 .6611.000 .5791.000 .6561.000 .812

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

Initial Extraction

Extraction Method: Principal Component Analysis.

Anti-image Matrices

.586 -.147 -.023 .091 -.059 .065 -.093 -.105 -.062 -.049 .054-.147 .338 -.121 .090 -.134 .063 -.054 .111 -.097 -.123 -.071-.023 -.121 .406 -.209 .007 -.017 -.014 .025 -.030 -.036 .083.091 .090 -.209 .338 -.128 -.007 .010 -.009 -.105 -.038 .006-.059 -.134 .007 -.128 .288 -.119 .067 -.057 .119 .160 .005.065 .063 -.017 -.007 -.119 .203 -.169 -.041 -.026 -.077 -.040-.093 -.054 -.014 .010 .067 -.169 .295 -.068 .044 .125 -.033-.105 .111 .025 -.009 -.057 -.041 -.068 .554 -.072 -.157 .007-.062 -.097 -.030 -.105 .119 -.026 .044 -.072 .424 .173 -.197-.049 -.123 -.036 -.038 .160 -.077 .125 -.157 .173 .331 -.142.054 -.071 .083 .006 .005 -.040 -.033 .007 -.197 -.142 .310.673a -.330 -.048 .204 -.144 .189 -.223 -.185 -.125 -.112 .128-.330 .600a -.328 .267 -.428 .239 -.172 .257 -.258 -.368 -.221-.048 -.328 .713a -.565 .021 -.058 -.041 .053 -.071 -.099 .233.204 .267 -.565 .652a -.409 -.028 .031 -.021 -.278 -.113 .019-.144 -.428 .021 -.409 .561a -.490 .229 -.142 .341 .516 .016.189 .239 -.058 -.028 -.490 .673a -.689 -.122 -.090 -.295 -.160-.223 -.172 -.041 .031 .229 -.689 .650a -.169 .126 .399 -.108-.185 .257 .053 -.021 -.142 -.122 -.169 .761a -.148 -.367 .018-.125 -.258 -.071 -.278 .341 -.090 .126 -.148 .549a .461 -.543-.112 -.368 -.099 -.113 .516 -.295 .399 -.367 .461 .382a -.445.128 -.221 .233 .019 .016 -.160 -.108 .018 -.543 -.445 .687a

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

Anti-image Covariance

Anti-image Correlation

Q2.4.1 Q2.4.2 Q2.4.3 Q2.4.4 Q2.4.5 Q2.4.6 Q2.4.7 Q2.4.8 Q2.4.9 Q2.4.10 Q2.4.11

Measures of Sampling Adequacy(MSA)a.

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Total Variance Explained

4.010 36.452 36.452 4.010 36.452 36.452 2.367 21.517 21.5172.152 19.567 56.018 2.152 19.567 56.018 2.311 21.011 42.5281.225 11.135 67.153 1.225 11.135 67.153 2.160 19.632 62.1601.021 9.282 76.435 1.021 9.282 76.435 1.570 14.275 76.435.853 7.754 84.188.566 5.141 89.330.419 3.807 93.136.291 2.645 95.782.187 1.698 97.480.177 1.613 99.093.100 .907 100.000

Component1234567891011

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

.441 .383 .260 -.661

.623 .419 .466 -.211

.636 -.314 .473 .169

.587 -.551 .215 .387

.594 -.612 .098 -.221

.799 -.267 -.400 -.013

.721 -.196 -.379 -.272

.603 .120 -.533 -.009

.582 .287 .219 .332

.296 .712 -.111 .222

.615 .584 -.117 .281

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

1 2 3 4Component

Extraction Method: Principal Component Analysis.

4 components extracted.a.

Reproduced Correlations

.846b .696 .172 -.152 .199 .155 .324 .179 .204 .229 .279

.696 .825b .449 .154 .206 .203 .248 .180 .515 .385 .514

.172 .449 .755b .713 .578 .400 .294 .092 .440 -.050 .200-.152 .154 .713 .843b .621 .524 .344 .169 .359 -.156 .123.199 .206 .578 .621 .785b .601 .571 .234 .118 -.319 -.066.155 .203 .400 .524 .601 .870b .783 .662 .297 .088 .379.324 .248 .294 .344 .571 .783 .775b .615 .190 .056 .297.179 .180 .092 .169 .234 .662 .615 .661b .265 .321 .500.204 .515 .440 .359 .118 .297 .190 .265 .579b .426 .593.229 .385 -.050 -.156 -.319 .088 .056 .321 .426 .656b .673.279 .514 .200 .123 -.066 .379 .297 .500 .593 .673 .812b

-.145 .014 .093 -.052 -.027 -.054 .070 .041 .005 -.028-.145 -.043 -.038 .047 .022 .017 -.025 -.074 .011 .003.014 -.043 -.039 -.101 -.009 .007 .086 -.150 .121 -.082.093 -.038 -.039 -.023 -.044 -.042 .060 -.075 .078 -.035-.052 .047 -.101 -.023 -.003 -.120 .002 -.041 .051 .066-.027 .022 -.009 -.044 -.003 .000 -.133 -.015 .025 .015-.054 .017 .007 -.042 -.120 .000 -.162 .077 -.082 .032.070 -.025 .086 .060 .002 -.133 -.162 -.027 .031 -.132.041 -.074 -.150 -.075 -.041 -.015 .077 -.027 -.298 .013.005 .011 .121 .078 .051 .025 -.082 .031 -.298 -.116-.028 .003 -.082 -.035 .066 .015 .032 -.132 .013 -.116

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

Reproduced Correlation

Residual a

Q2.4.1 Q2.4.2 Q2.4.3 Q2.4.4 Q2.4.5 Q2.4.6 Q2.4.7 Q2.4.8 Q2.4.9 Q2.4.10 Q2.4.11

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 24 (43.0%) nonredundant residuals with absolute values greater than 0.05.a.

Reproduced communalitiesb.

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Rotated Component Matrix a

.170 -.052 .113 .895

.025 .297 .444 .734

.094 .831 .105 .209

.244 .868 .031 -.169

.490 .629 -.327 .207

.847 .364 .139 .016

.829 .203 .023 .214

.733 -.021 .351 .015

.072 .402 .622 .160

.060 -.198 .771 .135

.279 .064 .840 .157

Q2.4.1Q2.4.2Q2.4.3Q2.4.4Q2.4.5Q2.4.6Q2.4.7Q2.4.8Q2.4.9Q2.4.10Q2.4.11

1 2 3 4Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 7 iterations.a.

Component Transformation Matrix

.632 .552 .415 .353-.214 -.533 .743 .344-.706 .537 -.031 .460-.238 .350 .525 -.738

Component1234

1 2 3 4

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

For Financial & Technical Features:

Correlation Matrixa

1.000 .380 .340 .197 .238 .211 .134 -.226 -.092 .004 .199 .045 .027 .156.380 1.000 .835 .633 -.031 .350 .155 .257 .083 .170 .127 .466 .032 .336.340 .835 1.000 .496 -.117 .257 .123 .231 .011 .225 .048 .488 .009 .361.197 .633 .496 1.000 .261 .505 .434 .121 .076 .014 .068 .366 .059 .208.238 -.031 -.117 .261 1.000 .320 .536 -.016 .158 -.215 .165 -.342 .121 -.312.211 .350 .257 .505 .320 1.000 .555 .289 .072 .223 .121 .325 .192 .046.134 .155 .123 .434 .536 .555 1.000 .493 .442 .177 .104 -.032 .021 -.172-.226 .257 .231 .121 -.016 .289 .493 1.000 .687 .485 .398 .381 .145 -.048-.092 .083 .011 .076 .158 .072 .442 .687 1.000 .158 .351 .106 .228 .098.004 .170 .225 .014 -.215 .223 .177 .485 .158 1.000 .376 .293 .199 .117.199 .127 .048 .068 .165 .121 .104 .398 .351 .376 1.000 .482 .529 .048.045 .466 .488 .366 -.342 .325 -.032 .381 .106 .293 .482 1.000 .275 .287.027 .032 .009 .059 .121 .192 .021 .145 .228 .199 .529 .275 1.000 .445.156 .336 .361 .208 -.312 .046 -.172 -.048 .098 .117 .048 .287 .445 1.000

.000 .000 .000 .000 .000 .013 .000 .062 .472 .000 .225 .324 .004.000 .000 .000 .304 .000 .005 .000 .082 .002 .017 .000 .298 .000.000 .000 .000 .025 .000 .020 .000 .430 .000 .214 .000 .438 .000.000 .000 .000 .000 .000 .000 .021 .102 .405 .127 .000 .164 .000.000 .304 .025 .000 .000 .000 .397 .004 .000 .003 .000 .022 .000.000 .000 .000 .000 .000 .000 .000 .116 .000 .022 .000 .001 .223.013 .005 .020 .000 .000 .000 .000 .000 .002 .041 .297 .365 .002.000 .000 .000 .021 .397 .000 .000 .000 .000 .000 .000 .008 .211.062 .082 .430 .102 .004 .116 .000 .000 .004 .000 .039 .000 .051.472 .002 .000 .405 .000 .000 .002 .000 .004 .000 .000 .000 .026.000 .017 .214 .127 .003 .022 .041 .000 .000 .000 .000 .000 .211.225 .000 .000 .000 .000 .000 .297 .000 .039 .000 .000 .000 .000.324 .298 .438 .164 .022 .001 .365 .008 .000 .000 .000 .000 .000.004 .000 .000 .000 .000 .223 .002 .211 .051 .026 .211 .000 .000

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

Correlation

Sig. (1-tailed)

Q2.5.1 Q2.5.2 Q2.5.3 Q2.5.4 Q2.5.5 Q2.5.6 Q2.5.7 Q2.5.8 Q2.5.9 Q2.5.10 Q2.5.11 Q2.5.12 Q2.5.13 Q2.5.14

Determinant = .000a.

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Inverse of Correlation Matrix

2.342 -1.081 -.565 .968 .016 -.514 -.964 2.016 -.360 -.020 -1.299 .289 .557 -.270-1.081 5.543 -3.220 -2.304 .359 -.667 1.683 -1.755 .027 .425 -.378 .971 .213 -.109-.565 -3.220 4.594 .494 -.893 1.092 -.543 -.568 .656 -.617 1.463 -1.781 -.012 -.590.968 -2.304 .494 3.415 -.797 -.122 -1.718 1.731 -.182 -.063 .063 -1.364 .347 -.462.016 .359 -.893 -.797 3.723 -1.033 -.982 .691 -.271 1.047 -1.767 2.317 -.593 1.026-.514 -.667 1.092 -.122 -1.033 2.697 -.983 -.613 .751 -.515 1.312 -1.569 -.540 -.096-.964 1.683 -.543 -1.718 -.982 -.983 4.083 -2.159 -.508 -.253 .657 .802 .102 .2492.016 -1.755 -.568 1.731 .691 -.613 -2.159 6.132 -2.671 -1.023 -.988 -.861 .298 .831-.360 .027 .656 -.182 -.271 .751 -.508 -2.671 3.088 .656 -.280 .311 -.068 -.913-.020 .425 -.617 -.063 1.047 -.515 -.253 -1.023 .656 2.006 -1.123 .972 -.031 -.155-1.299 -.378 1.463 .063 -1.767 1.312 .657 -.988 -.280 -1.123 4.092 -2.544 -1.279 .502.289 .971 -1.781 -1.364 2.317 -1.569 .802 -.861 .311 .972 -2.544 4.429 -.022 .165.557 .213 -.012 .347 -.593 -.540 .102 .298 -.068 -.031 -1.279 -.022 2.387 -1.338-.270 -.109 -.590 -.462 1.026 -.096 .249 .831 -.913 -.155 .502 .165 -1.338 2.426

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

Q2.5.1 Q2.5.2 Q2.5.3 Q2.5.4 Q2.5.5 Q2.5.6 Q2.5.7 Q2.5.8 Q2.5.9 Q2.5.10 Q2.5.11 Q2.5.12 Q2.5.13 Q2.5.14

KMO and Bartlett's Test

.537

2419.34791

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .5331.000 .8331.000 .8041.000 .6821.000 .8581.000 .5511.000 .8311.000 .9101.000 .5821.000 .4481.000 .7081.000 .6691.000 .7861.000 .556

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

Initial Extraction

Extraction Method: Principal Component Analysis.

Anti-image Matrices

.427 -.083 -.053 .121 .002 -.081 -.101 .140 -.050 -.004 -.136 .028 .100 -.048-.083 .180 -.126 -.122 .017 -.045 .074 -.052 .002 .038 -.017 .040 .016 -.008-.053 -.126 .218 .032 -.052 .088 -.029 -.020 .046 -.067 .078 -.088 -.001 -.053.121 -.122 .032 .293 -.063 -.013 -.123 .083 -.017 -.009 .005 -.090 .043 -.056.002 .017 -.052 -.063 .269 -.103 -.065 .030 -.024 .140 -.116 .141 -.067 .114-.081 -.045 .088 -.013 -.103 .371 -.089 -.037 .090 -.095 .119 -.131 -.084 -.015-.101 .074 -.029 -.123 -.065 -.089 .245 -.086 -.040 -.031 .039 .044 .010 .025.140 -.052 -.020 .083 .030 -.037 -.086 .163 -.141 -.083 -.039 -.032 .020 .056-.050 .002 .046 -.017 -.024 .090 -.040 -.141 .324 .106 -.022 .023 -.009 -.122-.004 .038 -.067 -.009 .140 -.095 -.031 -.083 .106 .498 -.137 .109 -.006 -.032-.136 -.017 .078 .005 -.116 .119 .039 -.039 -.022 -.137 .244 -.140 -.131 .051.028 .040 -.088 -.090 .141 -.131 .044 -.032 .023 .109 -.140 .226 -.002 .015.100 .016 -.001 .043 -.067 -.084 .010 .020 -.009 -.006 -.131 -.002 .419 -.231-.048 -.008 -.053 -.056 .114 -.015 .025 .056 -.122 -.032 .051 .015 -.231 .412.369a -.300 -.172 .342 .006 -.204 -.312 .532 -.134 -.009 -.420 .090 .236 -.113-.300 .627a -.638 -.530 .079 -.172 .354 -.301 .007 .127 -.079 .196 .059 -.030-.172 -.638 .621a .125 -.216 .310 -.125 -.107 .174 -.203 .337 -.395 -.003 -.177.342 -.530 .125 .587a -.223 -.040 -.460 .378 -.056 -.024 .017 -.351 .122 -.161.006 .079 -.216 -.223 .431a -.326 -.252 .145 -.080 .383 -.453 .571 -.199 .341-.204 -.172 .310 -.040 -.326 .568a -.296 -.151 .260 -.221 .395 -.454 -.213 -.038-.312 .354 -.125 -.460 -.252 -.296 .604a -.432 -.143 -.088 .161 .189 .033 .079.532 -.301 -.107 .378 .145 -.151 -.432 .536a -.614 -.292 -.197 -.165 .078 .215-.134 .007 .174 -.056 -.080 .260 -.143 -.614 .567a .264 -.079 .084 -.025 -.333-.009 .127 -.203 -.024 .383 -.221 -.088 -.292 .264 .523a -.392 .326 -.014 -.070-.420 -.079 .337 .017 -.453 .395 .161 -.197 -.079 -.392 .424a -.598 -.409 .159.090 .196 -.395 -.351 .571 -.454 .189 -.165 .084 .326 -.598 .510a -.007 .050.236 .059 -.003 .122 -.199 -.213 .033 .078 -.025 -.014 -.409 -.007 .529a -.556-.113 -.030 -.177 -.161 .341 -.038 .079 .215 -.333 -.070 .159 .050 -.556 .518a

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

Anti-image Covariance

Anti-image Correlation

Q2.5.1 Q2.5.2 Q2.5.3 Q2.5.4 Q2.5.5 Q2.5.6 Q2.5.7 Q2.5.8 Q2.5.9 Q2.5.10 Q2.5.11 Q2.5.12 Q2.5.13 Q2.5.14

Measures of Sampling Adequacy(MSA)a.

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Total Variance Explained

3.927 28.047 28.047 3.927 28.047 28.047 3.154 22.527 22.5272.293 16.379 44.426 2.293 16.379 44.426 2.399 17.137 39.6642.108 15.054 59.480 2.108 15.054 59.480 2.315 16.539 56.2031.423 10.168 69.648 1.423 10.168 69.648 1.882 13.444 69.648.993 7.096 76.744.897 6.406 83.150.774 5.528 88.679.477 3.405 92.084.375 2.680 94.764.236 1.687 96.451.187 1.334 97.785.146 1.040 98.825.088 .632 99.457.076 .543 100.000

Component1234567891011121314

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

.304 -.214 .448 .441

.740 -.428 .279 -.159

.678 -.503 .208 -.221

.655 -.105 .488 -.052

.125 .621 .555 .386

.624 .206 .343 .024

.508 .649 .361 -.146

.614 .444 -.404 -.417

.425 .535 -.326 -.091

.464 .059 -.447 -.173

.507 .231 -.444 .447

.662 -.341 -.332 -.063

.378 .066 -.409 .686

.351 -.538 -.219 .308

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

1 2 3 4Component

Extraction Method: Principal Component Analysis.

4 components extracted.a.

Reproduced Correlations

.533b .371 .310 .418 .323 .310 .113 -.273 -.171 -.148 .103 .098 .220 .260

.371 .833b .809 .674 -.080 .465 .222 .218 .009 .221 .082 .553 .028 .380

.310 .809 .804b .610 -.197 .385 .126 .201 -.029 .230 .037 .565 -.014 .395

.418 .674 .610 .682b .267 .554 .449 .180 .068 .089 .068 .311 .005 .164

.323 -.080 -.197 .267 .858b .406 .610 -.032 .170 -.220 .133 -.338 .126 -.293

.310 .465 .385 .554 .406 .551b .572 .326 .262 .144 .223 .227 .126 .040

.113 .222 .126 .449 .610 .572 .831b .515 .459 .138 .182 .005 -.013 -.295-.273 .218 .201 .180 -.032 .326 .515 .910b .668 .563 .407 .415 .140 -.063-.171 .009 -.029 .068 .170 .262 .459 .668 .582b .390 .443 .213 .267 -.095-.148 .221 .230 .089 -.220 .144 .138 .563 .390 .448b .370 .446 .244 .176.103 .082 .037 .068 .133 .223 .182 .407 .443 .370 .708b .377 .696 .289.098 .553 .565 .311 -.338 .227 .005 .415 .213 .446 .377 .669b .320 .469.220 .028 -.014 .005 .126 .126 -.013 .140 .267 .244 .696 .320 .786b .398.260 .380 .395 .164 -.293 .040 -.295 -.063 -.095 .176 .289 .469 .398 .556b

.009 .030 -.221 -.085 -.099 .021 .047 .079 .152 .096 -.053 -.193 -.104.009 .026 -.041 .049 -.115 -.067 .039 .074 -.051 .045 -.087 .003 -.044.030 .026 -.114 .080 -.129 -.003 .031 .040 -.004 .011 -.076 .023 -.033-.221 -.041 -.114 -.006 -.049 -.015 -.059 .008 -.074 .000 .055 .053 .044-.085 .049 .080 -.006 -.085 -.075 .017 -.011 .005 .032 -.004 -.005 -.019-.099 -.115 -.129 -.049 -.085 -.017 -.037 -.190 .079 -.102 .098 .066 .005.021 -.067 -.003 -.015 -.075 -.017 -.022 -.018 .039 -.078 -.037 .034 .123.047 .039 .031 -.059 .017 -.037 -.022 .020 -.078 -.008 -.034 .004 .015.079 .074 .040 .008 -.011 -.190 -.018 .020 -.232 -.093 -.107 -.039 .194.152 -.051 -.004 -.074 .005 .079 .039 -.078 -.232 .006 -.153 -.045 -.059.096 .045 .011 .000 .032 -.102 -.078 -.008 -.093 .006 .106 -.167 -.241-.053 -.087 -.076 .055 -.004 .098 -.037 -.034 -.107 -.153 .106 -.046 -.182-.193 .003 .023 .053 -.005 .066 .034 .004 -.039 -.045 -.167 -.046 .046-.104 -.044 -.033 .044 -.019 .005 .123 .015 .194 -.059 -.241 -.182 .046

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

Reproduced Correlation

Residuala

Q2.5.1 Q2.5.2 Q2.5.3 Q2.5.4 Q2.5.5 Q2.5.6 Q2.5.7 Q2.5.8 Q2.5.9 Q2.5.10 Q2.5.11 Q2.5.12 Q2.5.13 Q2.5.14

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 42 (46.0%) nonredundant residuals with absolute values greater than 0.05.a.

Reproduced communalitiesb.

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Rotated Component Matrix a

.419 -.422 .311 .288

.907 .079 .051 .030

.889 .085 -.076 -.011

.719 .015 .405 -.012-.128 -.159 .897 .106.463 .187 .541 .093.169 .408 .790 -.110.150 .930 .146 .040-.071 .678 .275 .204.193 .587 -.139 .217.025 .381 .132 .738.580 .380 -.267 .342-.010 .106 .053 .878.431 -.105 -.342 .492

Q2.5.1Q2.5.2Q2.5.3Q2.5.4Q2.5.5Q2.5.6Q2.5.7Q2.5.8Q2.5.9Q2.5.10Q2.5.11Q2.5.12Q2.5.13Q2.5.14

1 2 3 4Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 6 iterations.a.

Component Transformation Matrix

.745 .479 .288 .364-.549 .457 .699 -.029.336 -.566 .617 -.431-.172 -.491 .220 .825

Component1234

1 2 3 4

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

For General Features:

Correlation Matrix a

1.000 .253 .011 -.016 -.083 .049 -.071 -.185 -.432 -.242.253 1.000 .677 .397 .223 .096 .169 .120 .040 .365.011 .677 1.000 .636 .148 .229 .368 .278 .259 .383-.016 .397 .636 1.000 .227 .309 .268 .131 .233 .313-.083 .223 .148 .227 1.000 .386 .013 -.064 -.104 .053.049 .096 .229 .309 .386 1.000 .418 -.126 -.214 .049-.071 .169 .368 .268 .013 .418 1.000 .490 .428 .484-.185 .120 .278 .131 -.064 -.126 .490 1.000 .616 .571-.432 .040 .259 .233 -.104 -.214 .428 .616 1.000 .745-.242 .365 .383 .313 .053 .049 .484 .571 .745 1.000

.000 .424 .394 .082 .205 .119 .001 .000 .000.000 .000 .000 .000 .054 .002 .022 .252 .000.424 .000 .000 .007 .000 .000 .000 .000 .000.394 .000 .000 .000 .000 .000 .015 .000 .000.082 .000 .007 .000 .000 .413 .142 .041 .190.205 .054 .000 .000 .000 .000 .018 .000 .206.119 .002 .000 .000 .413 .000 .000 .000 .000.001 .022 .000 .015 .142 .018 .000 .000 .000.000 .252 .000 .000 .041 .000 .000 .000 .000.000 .000 .000 .000 .190 .206 .000 .000 .000

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

Correlation

Sig. (1-tailed)

Q3.1.3 Q3.1.4 Q3.1.5 Q3.1.6 Q3.1.7 Q3.1.8 Q3.1.9 Q3.1.10 Q3.1.11 Q3.1.12

Determinant = .009a.

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Inverse of Correlation Matrix

1.484 -.610 .313 -.159 .283 .098 -.234 -.095 .763 .091-.610 2.982 -1.953 .121 -.518 .771 -.084 .309 1.244 -1.600.313 -1.953 3.180 -1.149 .295 -.429 -.233 -.413 -.587 .723-.159 .121 -1.149 1.904 -.177 -.430 .205 .198 -.511 -.040.283 -.518 .295 -.177 1.378 -.686 .355 -.157 -.023 .096.098 .771 -.429 -.430 -.686 2.453 -1.404 .584 1.559 -.860-.234 -.084 -.233 .205 .355 -1.404 2.363 -.757 -.902 .010-.095 .309 -.413 .198 -.157 .584 -.757 2.031 -.391 -.562.763 1.244 -.587 -.511 -.023 1.559 -.902 -.391 4.471 -2.633.091 -1.600 .723 -.040 .096 -.860 .010 -.562 -2.633 3.658

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

Q3.1.3 Q3.1.4 Q3.1.5 Q3.1.6 Q3.1.7 Q3.1.8 Q3.1.9 Q3.1.10 Q3.1.11 Q3.1.12

KMO and Bartlett's Test

.599

1308.55545

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .5691.000 .7821.000 .7741.000 .5651.000 .5121.000 .7741.000 .5431.000 .6471.000 .8501.000 .747

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

Initial Extraction

Extraction Method: Principal Component Analysis.

Anti-image Matrices

.674 -.138 .066 -.056 .138 .027 -.067 -.032 .115 .017-.138 .335 -.206 .021 -.126 .105 -.012 .051 .093 -.147.066 -.206 .314 -.190 .067 -.055 -.031 -.064 -.041 .062-.056 .021 -.190 .525 -.068 -.092 .045 .051 -.060 -.006.138 -.126 .067 -.068 .726 -.203 .109 -.056 -.004 .019.027 .105 -.055 -.092 -.203 .408 -.242 .117 .142 -.096-.067 -.012 -.031 .045 .109 -.242 .423 -.158 -.085 .001-.032 .051 -.064 .051 -.056 .117 -.158 .492 -.043 -.076.115 .093 -.041 -.060 -.004 .142 -.085 -.043 .224 -.161.017 -.147 .062 -.006 .019 -.096 .001 -.076 -.161 .273.576a -.290 .144 -.095 .198 .052 -.125 -.055 .296 .039-.290 .478a -.634 .051 -.255 .285 -.032 .125 .341 -.485.144 -.634 .634a -.467 .141 -.153 -.085 -.162 -.156 .212-.095 .051 -.467 .741a -.109 -.199 .096 .101 -.175 -.015.198 -.255 .141 -.109 .478a -.373 .197 -.094 -.009 .043.052 .285 -.153 -.199 -.373 .354a -.583 .262 .471 -.287-.125 -.032 -.085 .096 .197 -.583 .638a -.346 -.278 .004-.055 .125 -.162 .101 -.094 .262 -.346 .781a -.130 -.206.296 .341 -.156 -.175 -.009 .471 -.278 -.130 .598a -.651.039 -.485 .212 -.015 .043 -.287 .004 -.206 -.651 .652a

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

Anti-image Covariance

Anti-image Correlation

Q3.1.3 Q3.1.4 Q3.1.5 Q3.1.6 Q3.1.7 Q3.1.8 Q3.1.9 Q3.1.10 Q3.1.11 Q3.1.12

Measures of Sampling Adequacy(MSA)a.

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Total Variance Explained

3.407 34.066 34.066 3.407 34.066 34.066 2.919 29.194 29.1942.090 20.899 54.964 2.090 20.899 54.964 2.179 21.788 50.9821.266 12.662 67.626 1.266 12.662 67.626 1.664 16.644 67.626.997 9.970 77.596.726 7.263 84.859.483 4.827 89.686.448 4.476 94.162.272 2.720 96.882.201 2.006 98.888.111 1.112 100.000

Component12345678910

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

-.227 .479 .537.526 .516 .490.730 .413 .266.615 .432 .016.170 .498 -.485.231 .600 -.600.690 -.024 -.256.661 -.452 .076.706 -.593 -.018.821 -.267 .025

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

1 2 3Component

Extraction Method: Principal Component Analysis.

3 components extracted.a.

Reproduced Correlations

.569b .391 .175 .076 -.060 -.087 -.306 -.326 -.454 -.300

.391 .782b .727 .554 .109 .137 .225 .152 .057 .307

.175 .727 .774b .632 .201 .258 .426 .316 .265 .496

.076 .554 .632 .565b .312 .392 .410 .212 .177 .390-.060 .109 .201 .312 .512b .629 .230 -.150 -.167 -.005-.087 .137 .258 .392 .629 .774b .299 -.164 -.183 .014-.306 .225 .426 .410 .230 .299 .543b .447 .506 .567-.326 .152 .316 .212 -.150 -.164 .447 .647b .733 .665-.454 .057 .265 .177 -.167 -.183 .506 .733 .850b .737-.300 .307 .496 .390 -.005 .014 .567 .665 .737 .747b

-.138 -.164 -.092 -.023 .136 .235 .141 .022 .059-.138 -.050 -.157 .115 -.041 -.056 -.031 -.016 .058-.164 -.050 .004 -.053 -.029 -.057 -.038 -.007 -.113-.092 -.157 .004 -.085 -.083 -.142 -.081 .056 -.077-.023 .115 -.053 -.085 -.243 -.216 .085 .063 .058.136 -.041 -.029 -.083 -.243 .119 .039 -.032 .035.235 -.056 -.057 -.142 -.216 .119 .043 -.078 -.083.141 -.031 -.038 -.081 .085 .039 .043 -.117 -.094.022 -.016 -.007 .056 .063 -.032 -.078 -.117 .008.059 .058 -.113 -.077 .058 .035 -.083 -.094 .008

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

Reproduced Correlation

Residual a

Q3.1.3 Q3.1.4 Q3.1.5 Q3.1.6 Q3.1.7 Q3.1.8 Q3.1.9 Q3.1.10 Q3.1.11 Q3.1.12

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 30 (66.0%) nonredundant residuals with absolute values greater than 0.05.a.

Reproduced communalitiesb.

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Rotated Component Matrix a

-.549 .481 -.192.046 .882 .043.308 .798 .206.249 .596 .384-.057 .091 .707-.045 .115 .871.616 .206 .348.774 .140 -.167.907 .025 -.166.808 .305 .018

Q3.1.3Q3.1.4Q3.1.5Q3.1.6Q3.1.7Q3.1.8Q3.1.9Q3.1.10Q3.1.11Q3.1.12

1 2 3Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 6 iterations.a.

Component Transformation Matrix

.806 .543 .235-.564 .585 .583-.178 .603 -.778

Component123

1 2 3

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

For Modelling Assistance:

Correlation Matrix a

1.000 .472 .405 .159 .487 .510 .535.472 1.000 .699 .117 .200 .185 .239.405 .699 1.000 .323 .345 .329 .335.159 .117 .323 1.000 .725 .505 .299.487 .200 .345 .725 1.000 .735 .576.510 .185 .329 .505 .735 1.000 .881.535 .239 .335 .299 .576 .881 1.000

.000 .000 .004 .000 .000 .000.000 .000 .026 .000 .001 .000.000 .000 .000 .000 .000 .000.004 .026 .000 .000 .000 .000.000 .000 .000 .000 .000 .000.000 .001 .000 .000 .000 .000.000 .000 .000 .000 .000 .000

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

Correlation

Sig. (1-tailed)

Q3.2.1 Q3.2.2 Q3.2.3 Q3.2.4 Q3.2.5 Q3.2.6 Q3.2.7

Determinant = .009a.

Inverse of Correlation Matrix

1.986 -.680 -.027 .667 -.957 -.166 -.392-.680 2.266 -1.457 .071 .103 .411 -.134-.027 -1.457 2.268 -.512 .049 .002 -.273.667 .071 -.512 2.644 -1.946 -.909 .930-.957 .103 .049 -1.946 3.924 -1.710 .298-.166 .411 .002 -.909 -1.710 7.249 -5.138-.392 -.134 -.273 .930 .298 -5.138 5.409

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

Q3.2.1 Q3.2.2 Q3.2.3 Q3.2.4 Q3.2.5 Q3.2.6 Q3.2.7

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KMO and Bartlett's Test

.701

1308.46621

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .5681.000 .8641.000 .7461.000 .5271.000 .8121.000 .8611.000 .687

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

Initial Extraction

Extraction Method: Principal Component Analysis.

Anti-image Matrices

.504 -.151 -.006 .127 -.123 -.012 -.036-.151 .441 -.284 .012 .012 .025 -.011-.006 -.284 .441 -.085 .006 9.96E-005 -.022.127 .012 -.085 .378 -.188 -.047 .065-.123 .012 .006 -.188 .255 -.060 .014-.012 .025 9.96E-005 -.047 -.060 .138 -.131-.036 -.011 -.022 .065 .014 -.131 .185.788a -.320 -.013 .291 -.343 -.044 -.120-.320 .618a -.643 .029 .035 .101 -.038-.013 -.643 .703a -.209 .017 .000 -.078.291 .029 -.209 .629a -.604 -.208 .246-.343 .035 .017 -.604 .752a -.321 .065-.044 .101 .000 -.208 -.321 .704a -.821-.120 -.038 -.078 .246 .065 -.821 .685a

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

Anti-image Covariance

Anti-image Correlation

Q3.2.1 Q3.2.2 Q3.2.3 Q3.2.4 Q3.2.5 Q3.2.6 Q3.2.7

Measures of Sampling Adequacy(MSA)a.

Total Variance Explained

3.660 52.282 52.282 3.660 52.282 52.282 2.980 42.575 42.5751.406 20.081 72.363 1.406 20.081 72.363 2.085 29.789 72.363.929 13.270 85.634.494 7.059 92.693.255 3.644 96.337.173 2.468 98.805.084 1.195 100.000

Component1234567

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

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Component Matrixa

.707 .262

.516 .773

.636 .584

.625 -.370

.835 -.339

.867 -.332

.807 -.190

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

1 2Component

Extraction Method: Principal Component Analysis.

2 components extracted.a.

Reproduced Correlations

.568b .567 .603 .345 .501 .525 .520

.567 .864b .780 .036 .169 .190 .269

.603 .780 .746b .181 .333 .357 .402

.345 .036 .181 .527b .647 .664 .575

.501 .169 .333 .647 .812b .836 .738

.525 .190 .357 .664 .836 .861b .762

.520 .269 .402 .575 .738 .762 .687b

-.095 -.198 -.186 -.015 -.016 .015-.095 -.081 .080 .032 -.005 -.029-.198 -.081 .141 .012 -.029 -.067-.186 .080 .141 .078 -.159 -.276-.015 .032 .012 .078 -.102 -.162-.016 -.005 -.029 -.159 -.102 .119.015 -.029 -.067 -.276 -.162 .119

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

Reproduced Correlation

Residual a

Q3.2.1 Q3.2.2 Q3.2.3 Q3.2.4 Q3.2.5 Q3.2.6 Q3.2.7

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 13 (61.0%) nonredundantresiduals with absolute values greater than 0.05.

a.

Reproduced communalitiesb.

Rotated Component Matrix a

.447 .607

.007 .929

.211 .837

.725 .034

.884 .175

.907 .198

.779 .284

Q3.2.1Q3.2.2Q3.2.3Q3.2.4Q3.2.5Q3.2.6Q3.2.7

1 2Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 3 iterations.a.

Component Transformation Matrix

.836 .549-.549 .836

Component12

1 2

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

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For Visual Aspects:

Correlation Matrixa

1.000 .641 .267 .349 .312 .302 .517 .327 .356 -.066 -.436.641 1.000 .648 .549 .345 .503 .416 .229 .232 .043 -.372.267 .648 1.000 .657 .299 .376 .200 -.015 -.006 -.009 -.195.349 .549 .657 1.000 .634 .634 .499 .194 .191 .013 -.141.312 .345 .299 .634 1.000 .693 .546 .260 .244 .238 .079.302 .503 .376 .634 .693 1.000 .659 .379 .368 .189 .033.517 .416 .200 .499 .546 .659 1.000 .565 .575 .405 .083.327 .229 -.015 .194 .260 .379 .565 1.000 .863 .197 .145.356 .232 -.006 .191 .244 .368 .575 .863 1.000 .389 .103-.066 .043 -.009 .013 .238 .189 .405 .197 .389 1.000 .520-.436 -.372 -.195 -.141 .079 .033 .083 .145 .103 .520 1.000

.000 .000 .000 .000 .000 .000 .000 .000 .138 .000.000 .000 .000 .000 .000 .000 .000 .000 .239 .000.000 .000 .000 .000 .000 .000 .404 .461 .443 .001.000 .000 .000 .000 .000 .000 .001 .001 .412 .010.000 .000 .000 .000 .000 .000 .000 .000 .000 .095.000 .000 .000 .000 .000 .000 .000 .000 .001 .292.000 .000 .000 .000 .000 .000 .000 .000 .000 .085.000 .000 .404 .001 .000 .000 .000 .000 .001 .008.000 .000 .461 .001 .000 .000 .000 .000 .000 .045.138 .239 .443 .412 .000 .001 .000 .001 .000 .000.000 .000 .001 .010 .095 .292 .085 .008 .045 .000

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

Correlation

Sig. (1-tailed)

Q4.1.1 Q4.1.2 Q4.1.3 Q4.1.4 Q4.1.5 Q4.1.6 Q4.1.7 Q4.1.8 Q4.1.9 Q4.1.10 Q4.1.11

Determinant = .001a.

Inverse of Correlation Matrix

3.130 -1.833 .299 .438 -.798 1.186 -1.687 .663 -1.035 .956 .480-1.833 3.833 -1.542 -.185 .596 -1.352 .742 -1.119 1.025 -1.119 .874.299 -1.542 2.717 -1.576 .306 .119 .344 .242 .099 -.090 -.191.438 -.185 -1.576 3.446 -1.278 -.220 -1.020 .572 -.630 .851 .034-.798 .596 .306 -1.278 2.659 -1.390 .345 -.522 .805 -.749 -.0581.186 -1.352 .119 -.220 -1.390 3.366 -1.560 .486 -.780 .823 -.284-1.687 .742 .344 -1.020 .345 -1.560 3.840 -1.398 .693 -1.510 .086.663 -1.119 .242 .572 -.522 .486 -1.398 5.796 -5.055 2.199 -1.321

-1.035 1.025 .099 -.630 .805 -.780 .693 -5.055 6.127 -2.397 1.114.956 -1.119 -.090 .851 -.749 .823 -1.510 2.199 -2.397 2.928 -1.334.480 .874 -.191 .034 -.058 -.284 .086 -1.321 1.114 -1.334 2.279

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

Q4.1.1 Q4.1.2 Q4.1.3 Q4.1.4 Q4.1.5 Q4.1.6 Q4.1.7 Q4.1.8 Q4.1.9 Q4.1.10 Q4.1.11

KMO and Bartlett's Test

.626

2023.26955

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .7371.000 .7311.000 .6681.000 .7851.000 .6611.000 .7231.000 .7621.000 .8161.000 .8631.000 .6021.000 .795

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

Initial Extraction

Extraction Method: Principal Component Analysis.

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Anti-image Matrices

.320 -.153 .035 .041 -.096 .113 -.140 .037 -.054 .104 .067-.153 .261 -.148 -.014 .059 -.105 .050 -.050 .044 -.100 .100.035 -.148 .368 -.168 .042 .013 .033 .015 .006 -.011 -.031.041 -.014 -.168 .290 -.139 -.019 -.077 .029 -.030 .084 .004-.096 .059 .042 -.139 .376 -.155 .034 -.034 .049 -.096 -.010.113 -.105 .013 -.019 -.155 .297 -.121 .025 -.038 .084 -.037-.140 .050 .033 -.077 .034 -.121 .260 -.063 .029 -.134 .010.037 -.050 .015 .029 -.034 .025 -.063 .173 -.142 .130 -.100-.054 .044 .006 -.030 .049 -.038 .029 -.142 .163 -.134 .080.104 -.100 -.011 .084 -.096 .084 -.134 .130 -.134 .342 -.200.067 .100 -.031 .004 -.010 -.037 .010 -.100 .080 -.200 .439.606a -.529 .103 .134 -.277 .365 -.487 .156 -.236 .316 .180-.529 .653a -.478 -.051 .187 -.376 .194 -.237 .212 -.334 .296.103 -.478 .695a -.515 .114 .039 .106 .061 .024 -.032 -.077.134 -.051 -.515 .754a -.422 -.065 -.280 .128 -.137 .268 .012-.277 .187 .114 -.422 .718a -.464 .108 -.133 .199 -.268 -.024.365 -.376 .039 -.065 -.464 .724a -.434 .110 -.172 .262 -.103-.487 .194 .106 -.280 .108 -.434 .723a -.296 .143 -.450 .029.156 -.237 .061 .128 -.133 .110 -.296 .531a -.848 .534 -.363-.236 .212 .024 -.137 .199 -.172 .143 -.848 .552a -.566 .298.316 -.334 -.032 .268 -.268 .262 -.450 .534 -.566 .326a -.516.180 .296 -.077 .012 -.024 -.103 .029 -.363 .298 -.516 .529a

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

Anti-image Covariance

Anti-image Correlation

Q4.1.1 Q4.1.2 Q4.1.3 Q4.1.4 Q4.1.5 Q4.1.6 Q4.1.7 Q4.1.8 Q4.1.9 Q4.1.10 Q4.1.11

Measures of Sampling Adequacy(MSA)a.

Total Variance Explained

4.435 40.321 40.321 4.435 40.321 40.321 3.405 30.952 30.9522.262 20.568 60.888 2.262 20.568 60.888 2.784 25.307 56.2591.444 13.128 74.016 1.444 13.128 74.016 1.953 17.756 74.016.790 7.183 81.199.659 5.988 87.187.359 3.259 90.446.346 3.142 93.589.314 2.857 96.446.174 1.582 98.028.149 1.351 99.379.068 .621 100.000

Component1234567891011

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

.639 -.299 -.489

.724 -.446 -.089

.530 -.520 .340

.755 -.317 .339

.716 .040 .384

.807 .032 .264

.823 .285 -.051

.594 .500 -.462

.609 .539 -.449

.279 .654 .309-.091 .743 .485

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

1 2 3Component

Extraction Method: Principal Component Analysis.

3 components extracted.a.

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Reproduced Correlations

.737b .639 .328 .411 .257 .377 .466 .456 .448 -.169 -.517

.639 .731b .586 .658 .466 .547 .474 .248 .241 -.117 -.440

.328 .586 .668b .680 .490 .501 .271 -.103 -.110 -.088 -.270

.411 .658 .680 .785b .658 .689 .514 .133 .137 .108 -.139

.257 .466 .490 .658 .661b .681 .581 .267 .285 .344 .151

.377 .547 .501 .689 .681 .723b .660 .373 .390 .328 .079

.466 .474 .271 .514 .581 .660 .762b .655 .678 .400 .112

.456 .248 -.103 .133 .267 .373 .655 .816b .838 .350 .093

.448 .241 -.110 .137 .285 .390 .678 .838 .863b .384 .127-.169 -.117 -.088 .108 .344 .328 .400 .350 .384 .602b .611-.517 -.440 -.270 -.139 .151 .079 .112 .093 .127 .611 .795b

.001 -.061 -.062 .055 -.075 .051 -.129 -.092 .102 .081.001 .063 -.108 -.121 -.044 -.058 -.019 -.009 .160 .068-.061 .063 -.023 -.191 -.125 -.071 .088 .104 .079 .075-.062 -.108 -.023 -.024 -.055 -.015 .061 .054 -.095 -.001.055 -.121 -.191 -.024 .013 -.035 -.007 -.041 -.106 -.071-.075 -.044 -.125 -.055 .013 -.001 .006 -.022 -.139 -.045.051 -.058 -.071 -.015 -.035 -.001 -.090 -.103 .005 -.029-.129 -.019 .088 .061 -.007 .006 -.090 .025 -.153 .051-.092 -.009 .104 .054 -.041 -.022 -.103 .025 .006 -.025.102 .160 .079 -.095 -.106 -.139 .005 -.153 .006 -.090.081 .068 .075 -.001 -.071 -.045 -.029 .051 -.025 -.090

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

Reproduced Correlation

Residual a

Q4.1.1 Q4.1.2 Q4.1.3 Q4.1.4 Q4.1.5 Q4.1.6 Q4.1.7 Q4.1.8 Q4.1.9 Q4.1.10 Q4.1.11

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 34 (61.0%) nonredundant residuals with absolute values greater than 0.05.a.

Reproduced communalitiesb.

Rotated Component Matrix a

.356 .518 -.585

.677 .257 -.454

.769 -.154 -.230

.877 .092 -.088

.748 .230 .220

.762 .353 .132

.528 .683 .130

.063 .899 .056

.070 .922 .093

.157 .336 .681-.075 .054 .887

Q4.1.1Q4.1.2Q4.1.3Q4.1.4Q4.1.5Q4.1.6Q4.1.7Q4.1.8Q4.1.9Q4.1.10Q4.1.11

1 2 3Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 5 iterations.a.

Component Transformation Matrix

.790 .609 -.072-.338 .531 .777.511 -.589 .626

Component123

1 2 3

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

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For Efficiency: Correlation Matrix a

1.000 .411 .157 .269 .328 .339 .119 .230 .391.411 1.000 .590 .182 .490 .195 -.049 .026 .490.157 .590 1.000 .240 .301 .319 .291 .134 .367.269 .182 .240 1.000 .329 .345 .229 .348 .398.328 .490 .301 .329 1.000 .312 .156 .190 .529.339 .195 .319 .345 .312 1.000 .575 .349 .396.119 -.049 .291 .229 .156 .575 1.000 .612 .261.230 .026 .134 .348 .190 .349 .612 1.000 .293.391 .490 .367 .398 .529 .396 .261 .293 1.000

.000 .004 .000 .000 .000 .024 .000 .000.000 .000 .001 .000 .001 .208 .330 .000.004 .000 .000 .000 .000 .000 .012 .000.000 .001 .000 .000 .000 .000 .000 .000.000 .000 .000 .000 .000 .004 .001 .000.000 .001 .000 .000 .000 .000 .000 .000.024 .208 .000 .000 .004 .000 .000 .000.000 .330 .012 .000 .001 .000 .000 .000.000 .000 .000 .000 .000 .000 .000 .000

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

Correlation

Sig. (1-tailed)

Q4.2.1 Q4.2.2 Q4.2.3 Q4.2.4 Q4.2.5 Q4.2.6 Q4.2.7 Q4.2.8 Q4.2.9

Determinant = .041a.

Inverse of Correlation Matrix

1.455 -.599 .331 -.117 -.024 -.360 .113 -.214 -.161-.599 2.564 -1.337 .252 -.579 -.011 .794 -.061 -.510.331 -1.337 1.969 -.240 .141 -.097 -.728 .237 -.018-.117 .252 -.240 1.384 -.206 -.250 .261 -.377 -.289-.024 -.579 .141 -.206 1.611 -.131 -.070 -.011 -.455-.360 -.011 -.097 -.250 -.131 1.860 -1.016 .236 -.191.113 .794 -.728 .261 -.070 -1.016 2.531 -1.179 -.144-.214 -.061 .237 -.377 -.011 .236 -1.179 1.833 -.142-.161 -.510 -.018 -.289 -.455 -.191 -.144 -.142 1.830

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

Q4.2.1 Q4.2.2 Q4.2.3 Q4.2.4 Q4.2.5 Q4.2.6 Q4.2.7 Q4.2.8 Q4.2.9

KMO and Bartlett's Test

.706

876.06736

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .3661.000 .7921.000 .4341.000 .3651.000 .5381.000 .5841.000 .7771.000 .6571.000 .613

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

Initial Extraction

Extraction Method: Principal Component Analysis.

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Anti-image Matrices

.687 -.161 .116 -.058 -.010 -.133 .031 -.080 -.060-.161 .390 -.265 .071 -.140 -.002 .122 -.013 -.109.116 -.265 .508 -.088 .044 -.027 -.146 .066 -.005-.058 .071 -.088 .723 -.092 -.097 .074 -.149 -.114-.010 -.140 .044 -.092 .621 -.044 -.017 -.004 -.154-.133 -.002 -.027 -.097 -.044 .538 -.216 .069 -.056.031 .122 -.146 .074 -.017 -.216 .395 -.254 -.031-.080 -.013 .066 -.149 -.004 .069 -.254 .546 -.042-.060 -.109 -.005 -.114 -.154 -.056 -.031 -.042 .546.763a -.310 .196 -.083 -.016 -.219 .059 -.131 -.099-.310 .604a -.595 .134 -.285 -.005 .312 -.028 -.236.196 -.595 .612a -.145 .079 -.051 -.326 .125 -.010-.083 .134 -.145 .785a -.138 -.156 .139 -.237 -.182-.016 -.285 .079 -.138 .842a -.076 -.035 -.006 -.265-.219 -.005 -.051 -.156 -.076 .768a -.468 .128 -.104.059 .312 -.326 .139 -.035 -.468 .559a -.547 -.067-.131 -.028 .125 -.237 -.006 .128 -.547 .664a -.078-.099 -.236 -.010 -.182 -.265 -.104 -.067 -.078 .871a

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

Anti-image Covariance

Anti-image Correlation

Q4.2.1 Q4.2.2 Q4.2.3 Q4.2.4 Q4.2.5 Q4.2.6 Q4.2.7 Q4.2.8 Q4.2.9

Measures of Sampling Adequacy(MSA)a.

Total Variance Explained

3.509 38.985 38.985 3.509 38.985 38.985 2.814 31.270 31.2701.617 17.968 56.953 1.617 17.968 56.953 2.312 25.683 56.953.938 10.424 67.377.748 8.306 75.683.633 7.036 82.719.608 6.753 89.472.447 4.971 94.442.296 3.285 97.727.205 2.273 100.000

Component123456789

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

.575 -.188

.606 -.652

.607 -.257

.592 .122

.665 -.309

.688 .332

.550 .688

.543 .602

.760 -.186

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

1 2Component

Extraction Method: Principal Component Analysis.

2 components extracted.a.

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Reproduced Correlations

.366b .471 .397 .317 .441 .333 .187 .199 .472

.471 .792b .536 .279 .605 .201 -.115 -.063 .582

.397 .536 .434b .327 .483 .332 .157 .175 .509

.317 .279 .327 .365b .356 .448 .410 .395 .427

.441 .605 .483 .356 .538b .355 .153 .175 .563

.333 .201 .332 .448 .355 .584b .607 .573 .462

.187 -.115 .157 .410 .153 .607 .777b .713 .291

.199 -.063 .175 .395 .175 .573 .713 .657b .301

.472 .582 .509 .427 .563 .462 .291 .301 .613b

-.061 -.241 -.048 -.113 .006 -.068 .031 -.081-.061 .054 -.098 -.115 -.006 .066 .089 -.092-.241 .054 -.087 -.182 -.013 .134 -.040 -.142-.048 -.098 -.087 -.027 -.103 -.181 -.047 -.030-.113 -.115 -.182 -.027 -.043 .003 .015 -.034.006 -.006 -.013 -.103 -.043 -.032 -.224 -.065-.068 .066 .134 -.181 .003 -.032 -.101 -.030.031 .089 -.040 -.047 .015 -.224 -.101 -.008-.081 -.092 -.142 -.030 -.034 -.065 -.030 -.008

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

Reproduced Correlation

Residuala

Q4.2.1 Q4.2.2 Q4.2.3 Q4.2.4 Q4.2.5 Q4.2.6 Q4.2.7 Q4.2.8 Q4.2.9

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 20 (55.0%) nonredundant residuals with absolute valuesgreater than 0.05.

a.

Reproduced communalitiesb.

Rotated Component Matrix a

.572 .198

.877 -.151

.639 .163

.397 .456

.716 .157

.347 .681

.021 .881

.068 .808

.717 .313

Q4.2.1Q4.2.2Q4.2.3Q4.2.4Q4.2.5Q4.2.6Q4.2.7Q4.2.8Q4.2.9

1 2Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 3 iterations.a.

Component Transformation Matrix

.796 .606-.606 .796

Component12

1 2

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

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For Testability:

Correlation Matrix a

1.000 .722 .275 -.123 .066 -.020 .010 .161.722 1.000 .428 .142 .075 -.036 -.032 -.107.275 .428 1.000 .403 -.197 -.162 .018 -.005-.123 .142 .403 1.000 .264 .025 -.111 -.108.066 .075 -.197 .264 1.000 .466 .199 .264-.020 -.036 -.162 .025 .466 1.000 .728 .492.010 -.032 .018 -.111 .199 .728 1.000 .582.161 -.107 -.005 -.108 .264 .492 .582 1.000

.000 .000 .019 .137 .371 .434 .003.000 .000 .009 .107 .277 .296 .037.000 .000 .000 .000 .003 .383 .470.019 .009 .000 .000 .339 .032 .036.137 .107 .000 .000 .000 .000 .000.371 .277 .003 .339 .000 .000 .000.434 .296 .383 .032 .000 .000 .000.003 .037 .470 .036 .000 .000 .000

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

Correlation

Sig. (1-tailed)

Q4.3.23 Q4.3.24 Q4.3.25 Q4.3.26 Q4.3.27 Q4.3.28 Q4.3.29 Q4.3.30

Determinant = .035a.

Inverse of Correlation Matrix

2.823 -2.125 -.182 .718 -.163 .118 .447 -.882-2.125 2.945 -.627 -.289 -.232 -.191 -.264 .933-.182 -.627 1.926 -.973 .623 .520 -.515 -.254.718 -.289 -.973 1.768 -.671 -.276 .495 .064-.163 -.232 .623 -.671 1.703 -.749 .305 -.326.118 -.191 .520 -.276 -.749 2.923 -1.912 -.193.447 -.264 -.515 .495 .305 -1.912 2.890 -.872-.882 .933 -.254 .064 -.326 -.193 -.872 1.937

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

Q4.3.23 Q4.3.24 Q4.3.25 Q4.3.26 Q4.3.27 Q4.3.28 Q4.3.29 Q4.3.30

KMO and Bartlett's Test

.507

922.51428

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .9011.000 .8651.000 .8971.000 .9081.000 .8941.000 .8001.000 .8431.000 .673

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

Initial Extraction

Extraction Method: Principal Component Analysis.

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Anti-image Matrices

.354 -.256 -.033 .144 -.034 .014 .055 -.161-.256 .340 -.111 -.056 -.046 -.022 -.031 .164-.033 -.111 .519 -.286 .190 .092 -.093 -.068.144 -.056 -.286 .566 -.223 -.053 .097 .019-.034 -.046 .190 -.223 .587 -.151 .062 -.099.014 -.022 .092 -.053 -.151 .342 -.226 -.034.055 -.031 -.093 .097 .062 -.226 .346 -.156-.161 .164 -.068 .019 -.099 -.034 -.156 .516.437a -.737 -.078 .321 -.075 .041 .157 -.377-.737 .480a -.263 -.127 -.104 -.065 -.090 .391-.078 -.263 .455a -.527 .344 .219 -.218 -.131.321 -.127 -.527 .324a -.387 -.122 .219 .035-.075 -.104 .344 -.387 .498a -.336 .137 -.179.041 -.065 .219 -.122 -.336 .621a -.658 -.081.157 -.090 -.218 .219 .137 -.658 .563a -.369-.377 .391 -.131 .035 -.179 -.081 -.369 .589a

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

Anti-image Covariance

Anti-image Correlation

Q4.3.23 Q4.3.24 Q4.3.25 Q4.3.26 Q4.3.27 Q4.3.28 Q4.3.29 Q4.3.30

Measures of Sampling Adequacy(MSA)a.

Total Variance Explained

2.442 30.530 30.530 2.442 30.530 30.530 2.201 27.518 27.5182.018 25.227 55.757 2.018 25.227 55.757 1.855 23.189 50.7071.314 16.424 72.181 1.314 16.424 72.181 1.423 17.782 68.4891.008 12.596 84.778 1.008 12.596 84.778 1.303 16.289 84.778.567 7.086 91.864.284 3.551 95.415.198 2.473 97.888.169 2.112 100.000

Component12345678

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

-.011 .800 -.451 -.241-.153 .883 -.134 -.210-.238 .670 .250 .573-.086 .306 .896 .069.548 .151 .421 -.627.886 .065 .106 -.022.835 .109 -.104 .351.757 .131 -.169 .235

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

1 2 3 4Component

Extraction Method: Principal Component Analysis.

4 components extracted.a.

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Reproduced Correlations

.901b .819 .288 -.174 .076 -.001 .040 .116

.819 .865b .474 .149 .124 -.088 -.091 -.027

.288 .474 .897b .490 -.283 -.154 .050 .000-.174 .149 .490 .908b .333 .037 -.107 -.160.076 .124 -.283 .333 .894b .554 .210 .216-.001 -.088 -.154 .037 .554 .800b .728 .656.040 -.091 .050 -.107 .210 .728 .843b .746.116 -.027 .000 -.160 .216 .656 .746 .673b

-.097 -.013 .051 -.010 -.019 -.030 .046-.097 -.046 -.007 -.050 .052 .059 -.080-.013 -.046 -.086 .086 -.008 -.032 -.004.051 -.007 -.086 -.069 -.013 -.004 .052-.010 -.050 .086 -.069 -.088 -.011 .047-.019 .052 -.008 -.013 -.088 .000 -.164-.030 .059 -.032 -.004 -.011 .000 -.164.046 -.080 -.004 .052 .047 -.164 -.164

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

Reproduced Correlation

Residual a

Q4.3.23 Q4.3.24 Q4.3.25 Q4.3.26 Q4.3.27 Q4.3.28 Q4.3.29 Q4.3.30

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 12 (42.0%) nonredundant residuals withabsolute values greater than 0.05.

a.

Reproduced communalitiesb.

Rotated Component Matrix a

.067 .942 -.097 -.006-.078 .898 .221 .056.068 .376 .752 -.431-.123 -.083 .886 .318.220 .079 .087 .912.786 -.055 -.006 .423.918 -.023 .001 .011.814 .057 -.077 .044

Q4.3.23Q4.3.24Q4.3.25Q4.3.26Q4.3.27Q4.3.28Q4.3.29Q4.3.30

1 2 3 4Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 7 iterations.a.

Component Transformation Matrix

.903 -.087 -.124 .403

.141 .885 .444 .012-.129 -.385 .795 .451.386 -.248 .394 -.796

Component1234

1 2 3 4

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

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For I/O Capabilities:

Correlation Matrix a

1.000 .753 .613 .306 .456 .297 -.095 -.143 -.482.753 1.000 .717 .316 .310 .295 -.066 -.285 -.610.613 .717 1.000 .551 .302 .195 -.137 -.559 -.529.306 .316 .551 1.000 .568 .233 -.012 -.489 -.273.456 .310 .302 .568 1.000 .491 .098 .031 -.037.297 .295 .195 .233 .491 1.000 .393 .148 -.022-.095 -.066 -.137 -.012 .098 .393 1.000 .349 .232-.143 -.285 -.559 -.489 .031 .148 .349 1.000 .597-.482 -.610 -.529 -.273 -.037 -.022 .232 .597 1.000

.000 .000 .000 .000 .000 .056 .008 .000.000 .000 .000 .000 .000 .136 .000 .000.000 .000 .000 .000 .001 .011 .000 .000.000 .000 .000 .000 .000 .419 .000 .000.000 .000 .000 .000 .000 .051 .305 .269.000 .000 .001 .000 .000 .000 .006 .354.056 .136 .011 .419 .051 .000 .000 .000.008 .000 .000 .000 .305 .006 .000 .000.000 .000 .000 .000 .269 .354 .000 .000

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

Correlation

Sig. (1-tailed)

Q5.1.1 Q5.1.2 Q5.1.3 Q5.1.4 Q5.1.5 Q5.1.6 Q5.1.7 Q5.1.8 Q5.1.9

Determinant = .007a.

Inverse of Correlation Matrix

3.039 -1.306 -.848 .240 -.856 .028 .278 -.750 .639-1.306 3.751 -1.665 .224 .039 -.331 -.047 -.588 1.196-.848 -1.665 3.538 -.784 .263 -.087 -.052 1.353 -.556.240 .224 -.784 2.653 -1.495 .073 -.300 1.168 -.119-.856 .039 .263 -1.495 2.468 -.686 .235 -.577 -.292.028 -.331 -.087 .073 -.686 1.673 -.575 -.137 .013.278 -.047 -.052 -.300 .235 -.575 1.412 -.566 .002-.750 -.588 1.353 1.168 -.577 -.137 -.566 3.166 -1.471.639 1.196 -.556 -.119 -.292 .013 .002 -1.471 2.578

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

Q5.1.1 Q5.1.2 Q5.1.3 Q5.1.4 Q5.1.5 Q5.1.6 Q5.1.7 Q5.1.8 Q5.1.9

KMO and Bartlett's Test

.704

1357.29736

.000

Kaiser-Meyer-Olkin Measure of SamplingAdequacy.

Approx. Chi-SquaredfSig.

Bartlett's Test ofSphericity

Communalities

1.000 .7941.000 .8731.000 .7671.000 .8961.000 .7341.000 .6781.000 .4881.000 .8161.000 .714

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

Initial Extraction

Extraction Method: Principal Component Analysis.

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Anti-image Matrices

.329 -.115 -.079 .030 -.114 .006 .065 -.078 .082-.115 .267 -.125 .023 .004 -.053 -.009 -.050 .124-.079 -.125 .283 -.083 .030 -.015 -.010 .121 -.061.030 .023 -.083 .377 -.228 .016 -.080 .139 -.017-.114 .004 .030 -.228 .405 -.166 .068 -.074 -.046.006 -.053 -.015 .016 -.166 .598 -.243 -.026 .003.065 -.009 -.010 -.080 .068 -.243 .708 -.127 .001-.078 -.050 .121 .139 -.074 -.026 -.127 .316 -.180.082 .124 -.061 -.017 -.046 .003 .001 -.180 .388.780a -.387 -.259 .085 -.312 .012 .134 -.242 .228-.387 .765a -.457 .071 .013 -.132 -.021 -.171 .385-.259 -.457 .779a -.256 .089 -.036 -.023 .404 -.184.085 .071 -.256 .661a -.584 .035 -.155 .403 -.046-.312 .013 .089 -.584 .605a -.338 .126 -.206 -.116.012 -.132 -.036 .035 -.338 .712a -.374 -.059 .006.134 -.021 -.023 -.155 .126 -.374 .579a -.268 .001-.242 -.171 .404 .403 -.206 -.059 -.268 .592a -.515.228 .385 -.184 -.046 -.116 .006 .001 -.515 .727a

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

Anti-image Covariance

Anti-image Correlation

Q5.1.1 Q5.1.2 Q5.1.3 Q5.1.4 Q5.1.5 Q5.1.6 Q5.1.7 Q5.1.8 Q5.1.9

Measures of Sampling Adequacy(MSA)a.

Total Variance Explained

3.740 41.556 41.556 3.740 41.556 41.556 2.899 32.206 32.2061.952 21.691 63.247 1.952 21.691 63.247 1.935 21.504 53.7101.068 11.867 75.114 1.068 11.867 75.114 1.926 21.403 75.114.813 9.032 84.146.482 5.357 89.503.394 4.373 93.876.210 2.332 96.209.194 2.159 98.368.147 1.632 100.000

Component123456789

Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Extraction Method: Principal Component Analysis.

Component Matrix a

.781 .173 .394

.834 .047 .417

.869 -.104 -.010

.667 .125 -.660

.516 .600 -.327

.337 .750 .043-.160 .678 .049-.574 .592 .369-.706 .400 -.237

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

1 2 3Component

Extraction Method: Principal Component Analysis.

3 components extracted.a.

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Reproduced Correlations

.794b .824 .657 .283 .378 .410 .012 -.200 -.575

.824 .873b .716 .287 .323 .335 -.081 -.297 -.669

.657 .716 .767b .574 .390 .215 -.210 -.564 -.653

.283 .287 .574 .896b .635 .290 -.054 -.552 -.265

.378 .323 .390 .635 .734b .610 .308 -.061 -.047

.410 .335 .215 .290 .610 .678b .457 .267 .052

.012 -.081 -.210 -.054 .308 .457 .488b .512 .372-.200 -.297 -.564 -.552 -.061 .267 .512 .816b .554-.575 -.669 -.653 -.265 -.047 .052 .372 .554 .714b

-.071 -.044 .023 .078 -.113 -.107 .057 .093-.071 .001 .029 -.013 -.040 .015 .012 .059-.044 .001 -.023 -.088 -.020 .073 .005 .124.023 .029 -.023 -.068 -.057 .042 .064 -.008.078 -.013 -.088 -.068 -.119 -.210 .092 .010-.113 -.040 -.020 -.057 -.119 -.064 -.118 -.074-.107 .015 .073 .042 -.210 -.064 -.162 -.141.057 .012 .005 .064 .092 -.118 -.162 .043.093 .059 .124 -.008 .010 -.074 -.141 .043

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

Reproduced Correlation

Residual a

Q5.1.1 Q5.1.2 Q5.1.3 Q5.1.4 Q5.1.5 Q5.1.6 Q5.1.7 Q5.1.8 Q5.1.9

Extraction Method: Principal Component Analysis.

Residuals are computed between observed and reproduced correlations. There are 21 (58.0%) nonredundant residuals with absolute valuesgreater than 0.05.

a.

Reproduced communalitiesb.

Rotated Component Matrix a

.860 .184 .146

.922 .060 .135

.718 -.162 .475

.178 -.033 .929

.221 .501 .659

.274 .722 .285-.131 .686 -.009-.291 .683 -.515-.732 .401 -.131

Q5.1.1Q5.1.2Q5.1.3Q5.1.4Q5.1.5Q5.1.6Q5.1.7Q5.1.8Q5.1.9

1 2 3Component

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

Rotation converged in 5 iterations.a.

Component Transformation Matrix

.827 -.067 .558-.039 .984 .176.560 .168 -.811

Component123

1 2 3

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

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Annexure VI

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Annexure VII

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Annexure-VIII

COPYRIGHT NOTICE

Copyright (C) 2010 Ashu Gupta, Dr. Rajesh Verma, Dr. Kawaljeet Singh

This program is free software; you can redistribute it and/or modify it under the

terms of the GNU General Public License as published by the Free Software

Foundation; either version 3, or (at your option) any later version of the License.

This program is distributed in the hope that it will be useful, but WITHOUT

ANY WARRANTY; without even the implied warranty of

MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the

GNU General public License for more details.

Contact Details:

Ashu Gupta, Sr. Lecturer, Apeejay Institute of Management, Jalandhar, Punjab, India. e-mail: [email protected] Dr. Rajesh Verma, Assistant Professor, Lovely Professional University, Phagwara, Punjab, India. e-mail: [email protected] Dr. Kawaljeet Singh, Director, University Computer Centre, Punjabi University, Patiala, Punjab, India. e-mail: [email protected]