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185
Annexure I
186
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.
187
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.
188
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
189
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
190
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.
191
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.
192
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.
193
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.
194
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.
195
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.
196
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.
197
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.
198
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
199
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.
200
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.
201
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.
202
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.
203
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.
204
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.
205
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.
206
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.
207
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.
208
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.
209
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.
210
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.
211
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.
212
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.
213
Annexure VI
214
Annexure VII
215
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]