UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Trinh Minh Long FACTORS AFFECTING CONSUMER’S ONLINE PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HO CHI MINH CITY MASTER OF BUSINESS (Honors) Ho Chi Minh City – Year 2014 UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Trinh Minh Long FACTORS AFFECTING CONSUMER’S ONLINE PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HO CHI MINH CITY ID: 22120054 MASTER OF BUSINESS (Honors) SUPERVISOR: DR NGUYEN QUYNH MAI Ho Chi Minh City – Year 2014 Running head: FACTORS AFFECTING CONSUMER’S ONLINE PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HCMC Factors Affecting Consumer’s Online Purchase Intention: The Moderating Role of Product Category - An Empirical Study in Ho Chi Minh City Trinh Minh Long long.minh.trinh@gmail.com 0938727169 Dr Nguyen Quynh Mai MBUS Dec, 08th, 2014 ii ACKNOWLEDGEMENTS I would like to express my deepest gratitude to my advisor, Dr Mai Nguyen, for her excellent guidance, caring, patience, and providing me with a great atmosphere for doing research Her guidance helped me in all the time of research and writing of this thesis I could not have imagined having a better advisor and mentor for my Master thesis Besides my advisor, I would like to thank my friends, and other workers in the Engineering Service Department, Software Center of Excellence Department at LogiGear Corporation in Ho Chi Minh City for helping me to collect mussel samples from the field My research would not have been possible without their helps My sincere thanks go to my mom, two elder brothers, and younger sister They were always supporting me and encouraging me with their best wishes Last but not the least, I would like to thank my girlfriend, Dao Ninh She was always there cheering me up and stood by me through the good times and bad iii Table of Contents Chapter 1: Introduction 1.1 Background of the Study 1.2 Problem Statement 1.3 Research Objective 1.4 Research Question 1.5 Research contributions 1.5.1 Theoretical contributions .8 1.5.2 Practical contributions 1.6 Scope of the study .9 1.7 Organization of the Study .11 Chapter 2: Literature Review 12 2.1 Introduction .12 2.2 Behavioral Intention Models 12 2.2.1 Theory of Reasoned Action (TRA) 12 2.2.2 Theory of Planned Behavior (TPB) 14 2.2.3 Technology Acceptance Model (TAM) 15 2.3 Overview of the Preliminary Model .16 2.4 Conceptual Framework and Proposed Hypotheses 18 2.4.1 Perceived usefulness (PU) 19 2.4.2 Perceived ease of use (PEOU) 19 2.4.3 Perceived risk (PR) 20 2.4.4 Brand orientation (BO) 21 iv 2.4.5 Prior online purchase experience (POPE) 22 2.4.6 Product category 23 2.5 Chapter summary 26 Chapter 3: Research Method 27 3.1 Introduction .27 3.2 Research design .27 3.3 Measurement and Questionnaire Design 27 3.3.1 Measurement 27 3.3.2 Questionnaire design 29 3.4 Data Collection Method 30 3.5 Data Analysis Method .31 3.5.1 Descriptive statistics 31 3.5.2 Exploratory factor analysis (EFA) .31 Correlation matrix analysis 32 Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy/Bartlett's Test of Sphericity 32 Factor extraction analysis .32 Rotation analysis 33 3.5.3 Reliability analysis .33 3.5.4 Correlation Analysis 33 3.5.5 Multiple Regression 33 (1) Normality 34 (2) Linearity 34 (3) Independence of error term 34 v (4) Absence of multicollinearity 34 (5) Absence of heteroscedasticity 34 (6) Absence of outlier and influential observations .34 3.6 Chapter summary 35 Chapter 4: Research Results 36 4.1 Introduction .36 4.2 Profile of Respondents 36 4.3 Descriptive statistics .38 Perceived usefulness (PU) 39 Perceived ease of use (PEOU) .39 Perceived risk (PR) .40 Brand orientation (BO) 40 Prior online purchase experience (POPE) 41 Online purchase intention (OPI) 41 4.4 Factor analysis .42 4.5 Reliability Test 45 4.6 Correlation Analysis .47 4.7 Multiple Regression 47 4.7.1 Assumption for Multiple Regression 47 4.7.2 Hypotheses Test 48 4.7.3 The Moderating Effect .51 4.7.4 Summary of Model Analysis .54 4.8 Chapter summary 56 Chapter 5: Discussion and Conclusion 57 vi 5.1 Introduction .57 5.2 Discussion .57 5.2.1 Relationship between perceived usefulness and consumer’s online purchase intention 58 5.2.2 Relationship between perceived ease of use and consumer’s online purchase intention 59 5.2.3 Relationship between perceived risk and consumer’s online purchase intention 60 5.2.4 Relationship between brand orientation and consumer’s online purchase intention 62 5.2.5 Relationship between prior online purchase experience and consumer’s online purchase intention .63 5.2.6 The moderating effect of product category .64 5.3 Implications .65 5.3.1 Theoretical 65 5.3.2 Practical .66 5.4 Limitations 68 5.5 Recommendations 69 5.6 Conclusion 70 References 72 APPENDIX A1 i APPENDIX A2 v APPENDIX B ix APPENDIX C x APPENDIX D xi vii APPENDIX E xiii APPENDIX F xv APPENDIX G xviii APPENDIX H xxi viii List of tables Table 3.1: Measurements and Sources 28 Table 4.1: Respondents’ Demographic Profile 37 Table 4.2: Online purchasing characteristics 38 Table 4.3: Means and standard deviations of items measuring perceived usefulness 39 Table 4.4: Means and standard deviations of items measuring perceived ease of use 40 Table 4.5: Means and standard deviations of items measuring perceived risk 40 Table 4.6: Means and standard deviations of items measuring brand orientation 41 Table 4.7: Means and standard deviations of items measuring prior online purchase experience .41 Table 4.8: Means and standard deviations of items measuring online purchase intention 42 Table 4.9: KMO and Bartlett's Test .43 Table 4.10: Rotated Component Matrix a 44 Table 4.11: Total Variance Explained 45 Table 4.12: Reliability Statistics 46 Table 4.13: Pearson Correlation Coefficient 47 Table 4.14: Model Summary 49 Table 4.15: ANOVAa .49 Table 4.16: Result of Multiple Regression Analysisa 50 Table 4.17: Correlation between Moderator, Dependent and Independent Variables 52 Table 4.18: Model Summaryc with Moderator .52 Table 4.19: Result of Regression Analysisa with Moderator 53 Table 4.20: Product category differences in online shopping (books: n=89; electronics: n = 106; clothing: n=124) .54 Table 5.1: Summary of Hypotheses Results 58 x APPENDIX C SPSS OUTPUT: DEMOGRAPHIC INFORMATION Gender Age Marital Status Male Female 16 - 20 21 - 25 26 - 30 31 - 35 > 35 Single Married High school - year school College Graduate Education Bachelor Degree/Professional Qualification Postgraduate < 5.000.000 VND 5.000.000 - 10.000.000 VND > 10.000.000 - 15.000.000 VND Monthly Income > 15.000.000 - 20.000.000 VND > 20.000.000 - 25.000.000 VND > 25.000.000 VND IT - related Occupation Non-IT - related to 12 months to years Internet experience to years years or more Hours spent Less than hour – hours on the Internet – hours (daily) More than hours None Frequency - times of purchase - times > times Books Product Electronics category Clothing Frequency Percent Valid Percent Cumulative Percent 162 50.8 50.8 50.8 157 49.2 49.2 100.0 26 8.2 8.2 8.2 139 43.6 43.6 51.7 109 34.2 34.2 85.9 41 12.9 12.9 98.7 1.3 1.3 100.0 240 75.2 75.2 75.2 79 24.8 24.8 100.0 20 6.3 6.3 6.3 42 13.2 13.2 7.2 20.4 213 66.8 66.8 87.1 41 97 86 63 38 13 22 171 148 27 87 204 42 70 200 57 112 60 90 89 106 124 12.9 30.4 27.0 19.7 11.9 4.1 6.9 53.6 46.4 8.5 27.3 63.9 2.2 13.2 21.9 62.7 17.9 35.1 18.8 28.2 27.9 33.2 38.9 12.9 30.4 27.0 19.7 11.9 4.1 6.9 53.6 46.4 8.5 27.3 63.9 2.2 13.2 21.9 62.7 17.9 35.1 18.8 28.2 27.9 33.2 38.9 100.0 30.4 57.4 77.1 89.0 93.1 100.0 53.6 100.0 8.8 36.1 100.0 2.2 15.4 37.3 100.0 17.9 53.0 71.8 100.0 27.9 61.1 100.0 xi APPENDIX D SPSS OUTPUT: DESCRIPTIVE STATISTICS Descriptive Statistics N Perceived Usefulness Use online shopping enables me to search and buy something more quickly Overall, I believe “online shopping” is useful and advantageous Use online shopping makes it easier for me to obtain goods Use online shopping enables me to save my money Use online shopping helps me to make better purchase decisions (efficiency and effectiveness) Perceived Ease of Use It will be IMPOSSIBLE to make an online transaction without expert help It is easy for me to learn how to use online shopping, even as the first time It is easy for me to become skillful at using online shopping Use online shopping not requires a lot of mental effort Perceived Risk I think online shopping would put my privacy at risk I am worried that product quality may not meet my expectations I think paying with a credit card to shop online is risky Brand Orientation Once I find a brand I like through web-shopping, I stick with it It is important for me to buy products/services from the web retailer with well-known brand names If I buy products/services from a web-retailer that I am familiar with, I would prefer to buy well—known brand name Prior Online Purchase Experience After doing an online shopping, I know reliable retailer's web sites After doing an online shopping, I become more skillful I am experienced with the use of the retailer's web site Online Purchase Intention Minimum Maximum Mean Std Deviation 319 4.03 774 319 3.61 804 319 3.61 853 319 3.18 959 319 3.14 1.007 319 4.23 743 319 3.93 861 319 3.87 860 319 3.62 979 319 3.69 911 319 3.55 943 319 3.48 967 319 3.95 840 319 3.73 1.004 319 3.64 885 319 4.02 707 319 3.90 761 319 3.73 754 xii I think it would be very good to purchase products through Internet in addition to traditional methods I will keep using online shopping in the future I intend to shop online in the future I would strongly recommend others to use online shopping I would frequently use “online shopping” 319 3.90 791 319 319 1 5 3.85 3.84 808 795 319 3.63 848 319 3.47 903 xiii APPENDIX E SPSS OUTPUT: FACTOR ANALYSIS E.1 Independent Variables KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Approx Chi-Square Bartlett's Test of df Sphericity Sig Total Variance Explained Component Initial Eigenvalues Total % of Variance Cumulative % 809 1680.179 153 000 Extraction Sums of Squared Loadings Total % of Cumulative Variance % Rotation Sums of Squared Loadings Total % of Cumulative Variance % 4.633 25.740 25.740 4.633 25.740 25.740 2.637 14.648 14.648 1.939 10.771 36.511 1.939 10.771 36.511 2.338 12.989 27.637 1.731 9.615 46.126 1.731 9.615 46.126 2.136 11.865 39.502 1.589 8.829 54.955 1.589 8.829 54.955 2.010 11.167 50.670 1.119 6.215 61.171 1.119 Extraction Method: Principal Component Analysis 6.215 61.171 1.890 10.501 61.171 Rotated Component Matrixa 730 706 705 655 605 Component PU5 PU3 PU2 PU4 PU1 PEOU3 811 PEOU1 687 PEOU4 685 PEOU2 561 POPE1 808 POPE3 312 752 POPE2 396 706 BO2 853 BO1 809 BO3 719 PR2 PR1 PR3 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a Rotation converged in iterations E.2 Dependent Variable 845 813 692 xiv KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Approx Chi-Square Bartlett's Test of df Sphericity Sig .819 1037.999 10 000 Total Variance Explained Component Initial Eigenvalues Total % of Variance Cumulative % 3.496 69.918 69.918 563 11.261 81.179 482 9.635 90.814 346 6.912 97.727 114 2.273 100.000 Extraction Method: Principal Component Analysis Component Matrixa Component OPI2 910 OPI1 881 OPI5 814 OPI3 789 OPI4 779 Extraction Method: Principal Component Analysis a component extracted Extraction Sums of Squared Loadings Total % of Variance Cumulative % 3.496 69.918 69.918 xv APPENDIX F SPSS OUTPUT: RELIABILITY ANALYSIS F.1 All Items Reliability Statistics Cronbach's Alpha Cronbach's Alpha Based on Standardized Items N of Items 854 865 23 Item-Total Statistics Scale Mean if Scale Variance Item Deleted if Item Deleted PU1 81.58 85.131 PU2 82.43 85.385 PU3 82.47 84.847 PU4 81.99 86.352 PU5 81.99 84.516 PEOU1 81.67 85.799 PEOU2 81.38 87.715 PEOU3 81.98 87.846 PEOU4 81.74 84.821 PR1 82.13 92.846 PR2 81.92 91.958 PR3 82.06 92.220 BO1 81.97 87.109 BO2 81.88 88.447 BO3 81.66 87.805 POPE1 81.88 86.567 POPE2 81.71 84.120 POPE3 81.59 85.374 OPI1 81.77 83.147 OPI2 81.76 82.327 OPI3 81.71 83.930 OPI4 81.98 84.352 OPI5 82.13 83.381 Corrected Item-Total Correlation 561 421 425 421 581 452 394 270 517 -.001 055 036 355 228 333 472 649 603 688 735 635 558 579 Squared Cronbach's Multiple Alpha if Item Correlation Deleted 389 844 329 849 361 848 352 848 493 843 370 847 294 849 349 855 448 845 375 865 407 862 222 863 417 851 415 856 284 851 439 847 620 841 574 843 800 840 826 838 546 841 519 844 601 842 F.2 Specific items Reliability Statistics Perceived usefulness Perceived Ease of use Perceived Risks Brand Orientation Prior online purchase experience Online Purchase Intention Inter-Item Correlation Matrix Cronbach's Cronbach's Alpha Based N of Items Alpha on Standardized Items 751 757 715 716 692 693 729 729 813 814 890 891 xvi PU1 PU2 PU3 PU4 PU5 PEOU1 PEOU2 PEOU3 PEOU4 PU1 1.000 332 398 373 442 PU2 332 1.000 450 264 394 PEOU1 1.000 387 370 459 PEOU2 387 1.000 281 348 PR1 PR1 PR2 PR3 BO1 POPE1 POPE2 POPE3 OPI1 OPI2 OPI3 OPI4 OPI5 PU4 373 264 265 1.000 502 PEOU3 370 281 1.000 477 PR3 572 1.000 391 BO2 1.000 574 409 574 1.000 436 POPE1 1.000 546 539 POPE2 546 1.000 693 OPI1 1.000 838 600 541 614 OPI2 838 1.000 641 577 660 OPI3 600 641 1.000 559 520 Item-Total Statistics Scale Mean if Scale Variance Item Deleted if Item Deleted PU1 PU2 PU3 PU4 PU5 PEOU1 PEOU2 PEOU3 13.55 14.40 14.43 13.96 13.96 11.71 11.42 12.03 PU5 442 394 417 502 1.000 PEOU4 459 348 477 1.000 PR2 1.000 572 326 BO1 BO2 BO3 PU3 398 450 1.000 265 417 7.035 6.473 6.158 6.995 6.624 3.909 4.547 3.653 326 391 1.000 BO3 409 436 1.000 POPE3 539 693 1.000 OPI4 541 577 559 1.000 617 OPI5 614 660 520 617 1.000 Corrected Item-Total Correlation 525 492 524 458 609 528 426 491 Squared Cronbach's Multiple Alpha if Item Correlation Deleted 283 706 265 718 303 707 282 727 393 677 289 636 193 695 263 665 xvii PEOU4 PR1 PR2 PR3 BO1 BO2 BO3 POPE1 POPE2 POPE3 OPI1 OPI2 OPI3 OPI4 OPI5 11.78 7.24 7.03 7.18 7.68 7.60 7.37 7.92 7.75 7.63 14.85 14.84 14.79 15.06 15.21 3.780 2.391 2.420 2.774 2.450 2.097 2.813 1.824 1.643 1.774 7.822 7.594 8.263 8.018 7.602 577 536 593 403 588 604 477 590 704 701 787 832 674 669 709 338 340 374 168 360 378 228 348 522 517 782 814 468 471 523 606 562 491 727 601 580 726 817 699 707 854 843 878 880 872 xviii APPENDIX G SPSS OUTPUT: MULTIPLE REGRESSION ANALYSIS Model Summaryb Model R R Square Adjusted R Square Std Error of the Estimate 737a 544 536 47077 a Predictors: (Constant), POPE, PR, BO, PEOU, PU b Dependent Variable: OPI R Square Change 544 Change Statistics F Change df1 df2 ANOVAa Model Sum of df Mean Square Squares Regression 82.657 16.531 Residual 69.369 313 222 Total 152.026 318 a Dependent Variable: OPI b Predictors: (Constant), POPE, PR, BO, PEOU, PU Coefficientsa Model Unstandardized Standardized Coefficients Coefficients B Std Beta Error (Const.) 239 259 PU 472 049 427 PEOU 115 048 105 PR -.088 036 -.094 BO 100 037 106 POPE 342 052 312 a Dependent Variable: OPI t Sig .926 9.665 2.392 -2.464 2.700 6.560 355 000 017 014 007 000 74.591 F Sig F Change 313 000 2.043 Sig .000b 74.591 95.0% Confidence Interval for B Lower Upper Bound Bound -.269 748 376 568 020 209 -.158 -.018 027 173 239 444 DurbinWatson Correlations Zeroorder 638 421 -.127 270 596 Partial 479 134 -.138 151 348 Part 369 091 -.094 103 250 Correlations OPI PU PEOU Pearson Correlation PR BO POPE OPI PU PEOU Sig (1-tailed) PR BO POPE Residuals Statisticsa OPI 1.000 638 421 -.127 270 596 000 000 012 000 000 PU 638 1.000 338 -.045 189 481 000 000 209 000 000 PEOU 421 338 1.000 -.027 163 483 000 000 314 002 000 PR -.127 -.045 -.027 1.000 029 -.043 012 209 314 305 225 BO 270 189 163 029 1.000 220 000 000 002 305 000 POPE 596 481 483 -.043 220 1.000 000 000 000 225 000 Collinearity Statistics Toler VIF ance 747 750 996 938 643 1.339 1.334 1.004 1.066 1.556 xix Minimum Maximum 1.8016 5.1180 -1.27817 1.52101 Predicted Value Residual Std Predicted -3.797 Value Std Residual -2.715 a Dependent Variable: OPI Mean Std Deviation 3.7373 50983 00000 46706 N 319 319 2.708 000 1.000 319 3.231 000 992 319 xx xxi APPENDIX H SPSS OUTPUT: MULTIPLE REGRESSION ANALYSIS WITH MODERATOR H.1 Pearson Correlation Correlations Pearson Correlation Sig (2-tailed) N Pearson Correlation DELECS Sig (2-tailed) N Pearson Correlation CPU Sig (2-tailed) N Pearson Correlation CPEOU Sig (2-tailed) N Pearson Correlation CPR Sig (2-tailed) N Pearson Correlation CBO Sig (2-tailed) N Pearson Correlation CPOPE Sig (2-tailed) N Pearson Correlation COPI Sig (2-tailed) N DCLO DCLO DELECS -.563** 000 319 319 -.563** 000 319 319 -.021 092 711 101 319 319 -.054 -.013 332 823 319 319 050 016 374 780 319 319 -.060 -.053 288 345 319 319 -.039 078 488 164 319 319 -.097 102 083 069 319 319 CPU CPEOU -.021 -.054 711 332 319 319 092 -.013 101 823 319 319 338** 000 319 319 338** 000 319 319 -.045 -.027 418 628 319 319 189** 163** 001 004 319 319 481** 483** 000 000 319 319 638** 421** 000 000 319 319 CPR CBO CPOPE COPI 050 -.060 -.039 -.097 374 288 488 083 319 319 319 319 016 -.053 078 102 780 345 164 069 319 319 319 319 ** ** -.045 189 481 638** 418 001 000 000 319 319 319 319 -.027 163** 483** 421** 628 004 000 000 319 319 319 319 029 -.043 -.127* 610 449 023 319 319 319 319 029 220** 270** 610 000 000 319 319 319 319 -.043 220** 596** 449 000 000 319 319 319 319 -.127* 270** 596** 023 000 000 319 319 319 319 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) H.2 Multiple Hierarchical Regression Analysis Result ANOVAa Model Sum of df Mean Square F Sig Squares Regression 83.613 11.945 54.299 000b Residual 68.413 311 220 Total 152.026 318 Regression 86.804 17 5.106 23.565 000c Residual 65.222 301 217 Total 152.026 318 a Dependent Variable: OPI b Predictors: (Constant), DELECS, CPEOU, CPR, CBO, CPU, DCLO, CPOPE c Predictors: (Constant), DELECS, CPEOU, CPR, CBO, CPU, DCLO, CPOPE, DELECS_CPOPE, DELECS_CBO, DCLO_CPR, DCLO_CPU, DELECS_CPEOU, DCLO_CBO, DELECS_CPR, DELECS_CPU, DCLO_CPEOU, DCLO_CPOPE xxii Model Summaryc Model R 742a 756b R Square Adjusted R Square 550 571 540 547 Std Error of Change Statistics the Estimate R Square F df1 df2 Change Change 46902 46549 550 021 54.299 1.473 DurbinWatson Sig F Change 311 10 301 000 149 2.041 a Predictors: (Constant), DELECS, CPEOU, CPR, CBO, CPU, DCLO, CPOPE b Predictors: (Constant), DELECS, CPEOU, CPR, CBO, CPU, DCLO, CPOPE, DELECS_CPOPE, DELECS_CBO, DCLO_CPR, DCLO_CPU, DELECS_CPEOU, DCLO_CBO, DELECS_CPR, DELECS_CPU, DCLO_CPEOU, DCLO_CPOPE c Dependent Variable: OPI Coefficientsa Model (Constant) CPU CPEOU CPR CBO CPOPE DCLO DELECS (Constant) CPU CPEOU CPR CBO CPOPE DCLO DELECS DCLO_CPU DCLO_CPEOU DCLO_CPR DCLO_CBO DCLO_CPOPE DELECS_CPU DELECS_CPR DELECS_CPEOU DELECS_CBO DELECS_CPOPE Unstandardized Standardized Coefficients Coefficients B Std Error Beta 3.718 051 466 049 421 119 048 109 -.088 036 -.095 104 037 110 335 052 307 -.032 066 -.023 095 069 065 3.727 052 533 094 483 133 102 122 029 067 031 095 072 101 186 104 170 -.034 067 -.024 094 070 064 -.060 125 -.031 -.022 126 -.013 -.150 090 -.096 045 094 029 279 128 173 -.085 124 -.045 -.168 090 -.107 002 130 001 -.011 096 -.006 053 146 024 H.3 Regression Analysis with Books selected t 73.613 9.523 2.470 -2.476 2.781 6.438 -.486 1.379 71.089 5.664 1.301 431 1.328 1.796 -.505 1.345 -.484 -.178 -1.667 477 2.186 -.686 -1.861 017 -.111 362 Sig .000 000 014 014 006 000 627 169 000 000 194 667 185 074 614 180 629 859 096 634 030 493 064 987 912 717 Collinearity Statistics Tolerance VIF 739 741 989 920 638 663 655 1.353 1.350 1.011 1.087 1.566 1.507 1.526 196 161 275 247 158 632 628 339 255 428 399 229 325 431 292 437 325 5.093 6.197 3.641 4.054 6.316 1.582 1.592 2.948 3.925 2.336 2.507 4.371 3.073 2.322 3.425 2.289 3.078 xxiii Model Summaryb Model R R Adjusted Std Error of the Change Statistics DurbinSquare R Square Estimate R Square F df1 df2 Sig F Watson Change Change Change a 731 534 506 49884 534 19.029 83 000 1.824 a Predictors: (Constant), POPE, PR, BO, PEOU, PU b Dependent Variable: OPI ANOVAa Model Sum of Squares df Mean Square F Sig Regression 23.676 4.735 19.029 000b Residual 20.654 83 249 Total 44.330 88 a Dependent Variable: OPI b Predictors: (Constant), POPE, PR, BO, PEOU, PU Coefficientsa Model Unstandardized Standardized Coefficients Coefficients B Std Beta Error PU 533 101 506 PEOU 133 110 110 PR 029 072 030 BO 095 077 106 POPE 186 111 171 a Dependent Variable: OPI t Sig 5.286 1.214 402 1.239 1.676 000 228 689 219 098 95.0% Confidence Interval for B Lower Upper Bound Bound 333 734 -.085 351 -.114 172 -.057 247 -.035 408 Correlations Zero- Partial Part order 690 502 396 430 132 091 -.052 044 030 425 135 093 554 181 126 Collinearity Statistics Tolera VIF nce 614 1.629 686 1.459 978 1.022 774 1.292 538 1.858 H.4 Regression Analysis with Electronics selected Model Summaryb Model R R Square Adjusted Std Error of Change Statistics DurbinR Square the Estimate R Square F df1 df2 Sig F Watson Change Change Change a 703 494 469 43728 494 19.555 100 000 1.926 a Predictors: (Constant), POPE, BO, PR, PEOU, PU b Dependent Variable: OPI ANOVAa Model Sum of df Mean Square F Sig Squares Regression 18.696 3.739 19.555 000b Residual 19.121 100 191 Total 37.818 105 a Dependent Variable: OPI b Predictors: (Constant), POPE, BO, PR, PEOU, PU Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig 95.0% Confidence Interval for B Correlations Collinearity Statistics xxiv B Std Error (Constant) 965 422 PU 448 076 PEOU 135 075 PR -.139 056 BO 084 061 POPE 239 097 a Dependent Variable: OPI Beta 475 146 -.178 100 216 2.289 5.861 1.801 -2.467 1.387 2.469 024 000 075 015 169 015 Lower Bound 128 296 -.014 -.250 -.036 047 Upper Bound 1.802 599 284 -.027 205 432 Zeroorder Partial 621 391 -.113 160 492 506 177 -.239 137 240 Part Toler ance VIF 417 128 -.175 099 176 769 770 976 975 661 1.300 1.299 1.024 1.026 1.514 H.5 Regression Analysis with Clothing selected Model Summary Model R R Square Adjusted R Std Change Statistics Square Error of R Square Change F df1 df2 Sig F Change the Change Estimat e a 788 621 605 46438 621 38.657 118 000 a Predictors: (Constant), CPOPE, CPR, CBO, CPU, CPEOU ANOVAa Model Sum of Squares 41.682 25.447 67.129 Regression Residual Total df Mean Square 118 123 8.336 216 F Sig .000b 38.657 a Dependent Variable: COPI b Predictors: (Constant), CPOPE, CPR, CBO, CPU, CPEOU Coefficientsa Model Unstandardized Standardized Coefficients Coefficients B (Constant) Std Error -.043 042 CPU 473 082 CPEOU 111 CPR t Sig Correlations Collinearity Statistics Beta Zero-order Partial Part Tolerance VIF -1.021 309 369 5.770 000 616 469 327 785 1.273 074 099 1.505 135 452 137 085 748 1.337 -.121 060 -.117 -2.030 045 -.197 -.184 -.115 973 1.028 CBO 140 061 134 2.303 023 253 207 131 954 1.048 CPOPE 465 074 433 6.285 000 674 501 356 677 1.477 a Dependent Variable: COPI ... PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY - AN EMPIRICAL STUDY IN HCMC Factors Affecting Consumer’s Online Purchase Intention: The Moderating Role of Product Category - An Empirical. ..UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Trinh Minh Long FACTORS AFFECTING CONSUMER’S ONLINE PURCHASE INTENTION: THE MODERATING ROLE OF PRODUCT CATEGORY. .. influencing consumers’ online purchase intention in Ho Chi Minh City - To examine the moderating effect of product category on the relationship between the factors and consumers’ online purchase intention