What effect consumers intention to buy counterfeit luxury brands the moderating role of product involvement and product knowledge evidence from vietnam

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Nguyễn Hạo Nhiên WHAT EFFECT CONSUMERS’ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? THE MODERATING ROLE OF PRODUCT INVOLVEMENT AND PRODUCT KNOWLEDGE: EVIDENCE FROM VIETNAM MASTER OF BUSINESS (Honours) Ho Chi Minh City – Year 2015 Nguyễn Hạo Nhiên WHAT EFFECT CONSUMERS’ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? THE MODERATING ROLE OF PRODUCT INVOLVEMENT AND PRODUCT KNOWLEDGE: EVIDENCE FROM VIETNAM ID: 22130049 MASTER OF BUSINESS (Honours) SUPERVISOR: Dr Ngô Viết Liêm Ho Chi Minh City – Year 2015 WHAT EFFECT CONSUMERS‘ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? i ACKNOWLEDGEMENTS Firstly, I would like to specially thank my supervisor, Dr Ngo Viet Liem, for his guidance Without him, this thesis would not have been finished Secondly, I would also like to thank my thesis committee, Dr Nguyen Dinh Tho, Dr Nguyen Thi Mai Trang, Dr Nguyen Thi Nguyet Que, and Dr Tran Ha Minh Quan, for their insightful comments Their advices helped me improve this thesis significantly Thirdly, I would like to acknowledge all the professors and staffs of International School of Business, University of Economics Ho Chi Minh City for providing me the best opportunities to study and develop deep understanding about research and business Finally, I would like to express my gratitude to my dear family and friends This thesis would have never come true without their encouragements and supports WHAT EFFECT CONSUMERS‘ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? ii TABLE OF CONTENTS ABSTRACT CHAPTER 1: INTRODUCTION 1.1 Research background 1.1.1 The emerging luxury market 1.1.2 Counterfeiting 1.2 Existing studies on counterfeiting 1.3 Research objectives 1.4 Scope of the study 1.5 Research significance 1.6 Research structure CHAPTER 2: LITERATURE REVIEW 2.1 Luxury brands 2.2 Counterfeits 2.3 Counterfeit purchase intention 10 2.4 Value-expressive and social-adjustive function 10 2.5 Product involvement 12 2.6 Product knowledge 13 2.7 Summary 14 CHAPTER 3: RESEARCH METHODOLOGY 17 3.1 Data collection 17 3.2 Measurement 18 3.3 Luxury brands 20 3.4 Measurement validation 20 3.5 Hypotheses tests 22 3.6 Summary 24 CHAPTER 4: DATA ANALYSIS 26 WHAT EFFECT CONSUMERS‘ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? 4.1 Pilot study 26 4.2 Data collection result and demographics 28 4.3 Measurement validation 28 4.3.1 Cronbach‘s alpha 28 4.3.2 Exploratory factor analysis 32 4.3.3 Confirmatory factor analysis 33 4.3.4 Composite reliability and average variance extracted 36 4.3.5 Divergent reliability and Pearson correlation 36 4.3.6 Final scales 37 4.4 Hypotheses tests 39 4.4.1 Model A 39 4.4.2 Model B 41 4.4.3 Model C 42 4.5 Discussion 43 4.6 Summary 45 CHAPTER 5: CONCLUSION 47 5.1 Overview 47 5.2 Managerial implications 47 5.3 Limitations and future research 48 References 51 Appendix A 55 Appendix B 56 Appendix C 57 Appendix D 60 Appendix E 61 Appendix F 67 Appendix G 68 LIST OF TABLES Table 2.1: Summary of definitions .14 Table 2.2: Summary of hypotheses .15 Table 3.1: Measurement scales 19 Table 3.2: Summary of research criteria .24 Table 4.1: In-depth interview results 26 Table 4.2: Demographics 28 Table 4.3: Cronbach‘s alpha .29 Table 4.4: Item-total statistics for product knowledge scale .29 Table 4.5: Item-total statistics for counterfeit purchase intention scale 30 Table 4.6: Cronbach‘s alphas after item reduction 31 Table 4.7: KMO and Bartlett‘s test .32 Table 4.8: Promax rotation with Kaiser Normalization, k=4 .33 Table 4.9: Modification indices covariances .34 Table 4.10: Composite score and average variance extracted .36 Table 4.11: Square root of average variance extracted and correlations .37 Table 4.12: Modified scales 37 Table 4.13: Summary of research criteria results 38 Table 4.14: Hierarchical multiple regression – Model A 40 Table 4.15: Hierarchical multiple regression – Model B 41 Table 4.16: Hierarchical multiple regression – Model C 42 Table 4.17: Hypothesis test results .45 LIST OF FIGURES Figure 2.1: Conceptual model .16 Figure 3.1: Research process 17 Figure 4.1: Modified confirmatory factor analysis model 35 Figure 4.2: Moderation effect of product involvement on the relationship between valueexpressive function and counterfeit purchase intention 40 Figure 4.3: Moderation effect of product knowledge on the relationship between socialadjustive function and counterfeit purchase intention 43 WHAT EFFECT CONSUMERS‘ INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? ABSTRACT In recent years, luxury market is growing fast worldwide—particularly in Asia However, along with the growth is the emerging threat from counterfeits Despite many works on counterfeiting, more works are needed to investigate the impacts of psychological aspects on counterfeit purchasing intention Furthermore, the interaction effects of the psychological factors and two important constructs in consumer behavioral studies— product involvement and product knowledge—were also examined to further understand the problem In order to achieve the research objectives, five respondents took part in in-depth interviews to check the wordings of a 25-item questionnaire The revised questionnaire was used in the main survey 248 respondents participated in the survey, and 201 usable answers were retained Tests were conducted to examine the validity and reliability of the measurement scales, which resulted in the elimination of an item The hypotheses were then tested with hierarchical multiple regression method The results from the tests indicated that social-adjustive function significantly affected counterfeit purchase intention (p < 001) On the contrary, the effect of valueexpressive function was found to be positive (β = 078) but insignificant (p = 271) Regarding to the moderation effects, the interaction between product involvement and value-expressive function negatively and significantly affected counterfeit purchase intention (p = 029), while the impacts of the interaction between product involvement and social-adjustive function turned out to be insignificant (p = 268) The results also claimed that social-adjustive function was found to be negatively moderated by product knowledge (p = 042) It can be inferred from the findings that luxury brands focusing on communicating the social-adjustive functions are more likely to face the risk of counterfeiting than those focusing on the value-expressive functions In order to reduce customers‘ intention to buy counterfeits, two marketing combinations—value-expressive function focused combined with campaigns strengthening product involvement, and social-adjustive focused combined with campaigns strengthening product knowledge—are advised to be taken into consideration seriously, while other combinations have not been proven to be effective yet and require further investigation Chapter INTRODUCTION This chapter tends to introduce the situation and characteristics of luxury brands, as well as their war against counterfeits Chapter also summarizes previous studies on the subject, as well as the gaps should be filled Research objectives, research questions and research scope are stated Research structure is also described 1.1 Research background This section investigates the growing market of luxury brands and products worldwide, especially in Asian countries It also gives an overview of battle against counterfeiting of luxury brands 1.1.1 The emerging luxury market In recent years, the market for luxury products is expanding faster and faster Though there are still disagreements in estimating luxury market size due to different methods, researchers all agree on the fast increase of the market (Heine & Phan, 2011; Ho, Moon, Kim, & Yoon, 2012; Truong, McColl, & Kitchen, 2008) According to Truong et al (2008), this fast increase of the luxury market is due to two main reasons: Firstly, the economy has been better recently with improved business environment, resulting in lower unemployment rates (which lead to higher income and consumption) and lower production costs (which understandably lead to production expansion) Secondly, the market of luxury products now does not contain only wealthy consumers, but also lower-class ones Truong et al (2008) summarize that the low-class consumers nowadays tend to purchase luxury products to imitate the high-class, to gain good feelings for the purpose of self-rewarding, or simply due to the high-quality This results in a new kind of luxury brand—which Truong et al (2008) call the masstige—a portmanteau of mass market and prestige market, indicating that the luxury market is now open to the mass Moreover, Cavender and Kincade (2013) also state the role of lower entry barriers Thanks to globalization, the level of managing and conducting business raises consequently, which enables potential players to join the luxury- Appendix C Cronbach‘s alpha Value-expressive function Reliability Statistics Cronbach's Alpha N of Items 880 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted VE1 VE2 VE3 VE4 10.87 10.69 10.49 11.17 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 699 776 770 717 861 833 834 855 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 568 668 761 672 835 790 748 788 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 709 716 465 740 732 852 17.593 17.186 16.201 17.545 Social-adjustive function Reliability Statistics Cronbach's Alpha N of Items 835 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted SA1 SA2 SA3 SA4 12.79 12.27 12.84 12.92 16.746 16.520 15.528 15.844 Product knowledge Reliability Statistics Cronbach's Alpha N of Items 817 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted PK1 PK2 PK3 10.25 10.24 9.76 18.988 18.045 20.223 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted PK1 PK2 PK3 PK4 10.25 10.24 9.76 10.09 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 709 716 465 687 740 732 852 745 18.988 18.045 20.223 17.782 Product knowledge after deleting PK3 Reliability Statistics Cronbach's Alpha N of Items 852 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted PK1 PK2 PK4 6.56 6.56 6.40 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 727 774 675 793 743 843 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 677 625 686 771 743 712 823 784 756 770 929 931 929 924 926 927 922 924 925 925 10.227 9.218 9.512 Product involvement Reliability Statistics Cronbach's Alpha N of Items 933 10 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted PI1 PI2 PI3 PI4 PI5 PI6 PI7 PI8 PI9 PI10 42.47 42.48 42.66 42.48 42.14 42.46 42.22 42.08 42.04 42.28 124.070 127.291 124.475 119.221 121.734 125.059 118.212 119.984 120.218 116.864 Counterfeit purchase intention Reliability Statistics Cronbach's Alpha N of Items Reliability Statistics Cronbach's Alpha N of Items 896 Item-Total Statistics Scale Mean if Item Scale Variance if Deleted Item Deleted CP1 CP2 CP3 5.83 5.85 6.28 10.575 10.698 12.184 Corrected ItemTotal Correlation Cronbach's Alpha if Item Deleted 850 870 674 802 786 952 Appendix D Exploratory factor analysis KMO and Bartlett’s test KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett's Test of Sphericity Approx Chi-Square 868 3.270E3 df 276 Sig .000 Factor loading, Promax rotation with Kaiser Normalisation, k=4 Structure Matrix Component PI7 PI8 PI10 PI9 PI4 PI5 PI6 PI3 PI1 PI2 VE2 VE3 VE1 VE4 SA3 SA4 SA2 SA1 CP2 CP1 CP3 PK2 PK1 PK4 866 846 822 820 813 799 765 742 738 676 236 226 166 229 304 236 294 169 027 070 054 354 417 348 287 165 335 088 197 263 259 106 138 160 880 868 836 836 374 380 440 391 073 109 071 221 290 186 315 158 266 169 252 279 262 217 187 298 395 501 357 388 881 838 811 738 236 268 162 303 316 381 209 -.037 204 -.016 098 153 104 -.099 -.142 102 116 147 037 051 252 141 205 260 941 933 834 021 042 022 312 185 368 223 489 283 418 420 329 442 271 224 112 297 411 374 295 153 -.039 -.003 088 905 877 828 Extraction Method: Principal Component Analysis Rotation Method: Promax with Kaiser Normalization Appendix E Confirmatory factor analysis Original model Regression weights VE1 VE2 VE3 VE4 < < < < - value-expressive function value-expressive function value-expressive function value-expressive function Estimate 1.000 1.081 1.202 1.031 S.E C.R P 093 101 095 11.682 11.854 10.898 *** *** *** Label SA1 SA2 SA3 SA4 PK1 PK2 PK4 CP1 CP2 CP3 PI1 PI2 PI3 PI4 PI5 PI6 PI7 PI8 PI9 PI10 < < < < < < < < < < < < < < < < < < < < - social-adjustive function social-adjustive function social-adjustive function social-adjustive function Product knowledge Product knowledge Product knowledge Counterfeit purchase intention Counterfeit purchase intention Counterfeit purchase intention Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Estimate 1.000 1.089 1.304 1.238 1.000 1.113 1.010 1.000 1.000 728 1.000 886 986 1.267 1.191 990 1.355 1.233 1.208 1.417 S.E C.R P 131 142 142 8.306 9.206 8.714 *** *** *** 087 090 12.788 11.282 *** *** 045 059 22.276 12.354 *** *** 105 110 123 116 104 122 118 120 134 8.463 8.975 10.303 10.276 9.476 11.119 10.425 10.038 10.607 *** *** *** *** *** *** *** *** *** Label Standardized regression weights VE1 VE2 VE3 VE4 SA1 SA2 SA3 SA4 PK1 PK2 PK4 CP1 CP2 CP3 PI1 PI2 PI3 PI4 PI5 PI6 PI7 PI8 PI9 PI10 < < < < < < < < < < < < < < < < < < < < < < < < - value-expressive function value-expressive function value-expressive function value-expressive function social-adjustive function social-adjustive function social-adjustive function social-adjustive function Product knowledge Product knowledge Product knowledge Counterfeit purchase intention Counterfeit purchase intention Counterfeit purchase intention Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Product involvement Estimate 749 837 851 782 622 732 869 784 833 865 749 942 965 691 676 642 685 799 796 727 872 810 776 826 Modification Indices Covariances M.I Par Change M.I Par Change e24 < > CPI 5.968 0.305 e15 < > CPI 9.323 -0.411 e24 < > VEF 5.743 0.193 e15 < > e24 11.192 -0.284 e22 < > CPI 5.305 -0.263 e15 < > e21 e22 < > PK 11.132 -0.279 e15 < > e20 19.3 0.348 e22 < > e23 64.906 0.575 e15 < > e19 6.129 -0.194 e21 < > CPI 4.828 0.223 e15 < > e17 38.327 0.547 e21 < > PK 4.022 -0.149 e13 < > e23 4.053 0.106 e21 < > e24 13.767 0.234 e12 < > e23 7.567 -0.152 e21 < > e23 6.871 -0.165 e11 < > SAF 7.617 0.223 e20 < > PK 4.314 0.177 e11 < > e14 5.918 0.294 e19 < > e24 7.068 0.192 e11 < > e13 4.019 -0.131 e19 < > e23 7.997 -0.203 e10 < > e22 6.632 -0.191 e19 < > e21 25.801 0.296 e10 < > e18 5.924 0.192 e19 < > e20 8.571 -0.198 e10 < > e16 5.667 0.201 e18 < > PK 10.256 0.285 e10 < > e13 5.203 0.124 e18 < > e22 9.155 -0.211 e9 < > e20 14.065 0.273 e17 < > CPI 4.37 -0.271 e8 < > e24 5.803 -0.202 e17 < > PK 4.88 0.21 e8 < > e11 6.026 0.253 e17 < > e24 11.867 -0.281 e7 < > VEF 4.45 -0.154 e17 < > e21 10.853 -0.218 e6 < > e19 6.051 0.191 e17 < > e20 7.691 0.212 e5 < > e24 4.057 0.203 e17 < > e19 5.405 -0.175 e5 < > e19 5.28 -0.213 e16 < > PK 4.751 0.208 e5 < > e8 4.1 -0.215 e16 < > e22 7.889 -0.211 e3 < > SAF 4.652 0.138 e16 < > e18 9.006 0.239 e1 < > e5 9.682 0.332 CMIN Model Default model Saturated model Independence model NPAR 58 300 24 CMIN 525.735 000 3421.605 DF 242 276 P 000 CMIN/DF 2.172 000 12.397 RMR, GFI Model Default model Saturated model Independence model RMR 153 000 846 GFI 817 1.000 264 AGFI 773 PGFI 659 200 243 RFI rho1 825 IFI Delta2 911 1.000 000 TLI rho2 897 Baseline Comparisons Model Default model Saturated model Independence model NFI Delta1 846 1.000 000 000 000 CFI 910 1.000 000 RMSEA Model Default model Independence model RMSEA 077 239 LO 90 068 232 HI 90 086 246 PCLOSE 000 000 7.233 -0.185 Modified model Regression weights VE1 VE2 VE3 VE4 SA1 SA2 < < < < < < - VEF VEF VEF VEF SAF SAF Estimate 1.000 1.082 1.203 1.031 1.000 1.088 S.E C.R P 093 101 095 11.683 11.854 10.897 *** *** *** 131 8.308 *** Label SA3 SA4 PK1 PK2 PK4 CP1 CP2 CP3 PI1 PI2 PI3 PI4 PI5 PI6 PI7 PI8 PI9 < < < < < < < < < < < < < < < < < - SAF SAF PK PK PK CPI CPI CPI PI PI PI PI PI PI PI PI PI Estimate 1.304 1.238 1.000 1.112 1.009 1.000 999 728 1.000 923 988 1.320 1.192 1.019 1.375 1.202 1.181 S.E .142 142 C.R 9.210 8.717 P *** *** 087 089 12.831 11.296 *** *** 045 059 22.289 12.356 *** *** 111 087 132 124 111 131 125 127 8.339 11.392 10.035 9.643 9.189 10.528 9.605 9.281 *** *** *** *** *** *** *** *** Label Standardized regression weights VE1 VE2 VE3 VE4 SA1 SA2 SA3 SA4 PK1 PK2 PK4 CP1 CP2 CP3 PI1 PI2 PI3 PI4 PI5 PI6 PI7 PI8 PI9 PI10 < < < < < < < < < < < < < < < < < < < < < < < < - VEF VEF VEF VEF SAF SAF SAF SAF PK PK PK CPI CPI CPI PI PI PI PI PI PI PI PI PI PI Estimate 749 837 851 782 622 731 869 784 834 865 749 942 965 691 660 653 670 813 779 731 865 771 741 833 CMIN Model Default model Saturated model Independence model NPAR 61 300 24 CMIN 391.168 000 3421.605 DF 239 276 P 000 CMIN/DF 1.637 000 12.397 RMR, GFI Model Default model Saturated model Independence model RMR 144 000 846 GFI 863 1.000 264 AGFI 828 PGFI 688 200 243 RFI rho1 868 IFI Delta2 952 1.000 000 TLI rho2 944 Baseline Comparisons Model Default model Saturated model Independence model NFI Delta1 886 1.000 000 000 000 CFI 952 1.000 000 RMSEA Model Default model Independence model RMSEA 056 239 LO 90 046 232 HI 90 066 246 PCLOSE 146 000 Appendix F Pearson correlation test Correlations ValueExpressive Pearson Correlation SocialAdjustive 496** 271** 254** 078 Sig (2-tailed) SocialAdjustive ProductKnowledge ProductInvolvement CounterfeitPurchase Intention CounterfeitPurchas ProductKnowled eIntention ge ProductInvolvement ValueExpressive 000 000 000 271 N 201 201 201 201 201 Pearson Correlation 496** 388** 311** 248** Sig (2-tailed) 000 000 000 000 N 201 201 201 201 Pearson Correlation 271 ** 201 388 ** Sig (2-tailed) 000 000 N 201 201 Pearson Correlation Sig (2-tailed) 254** N 438 ** 020 000 780 201 201 201 311** 438** 058 000 000 000 201 201 201 201 201 Pearson Correlation Sig (2-tailed) 078 248** 020 058 271 000 780 416 N 201 201 201 201 ** Correlation is significant at the 0.01 level (2tailed) .416 201 Appendix G Hierarchical multiple regression tests Model A Model Summaryd Change Statistics Model R R Square Adjusted R Square 078a 078b 173c 006 006 030 001 -.004 015 Std Error of the Estimate R Square Change F Change df1 df2 Sig F Change 1.62697 1.63107 1.61557 006 000 024 1.220 000 4.819 1 199 198 197 271 984 029 a Predictors: (Constant), ValueExpressive b Predictors: (Constant), ValueExpressive, PIcategorized c Predictors: (Constant), ValueExpressive, PIcategorized, VExPI d Dependent Variable: CounterfeitPurchaseIntention ANOVAd Model Sum of Squares df Mean Square F Sig 3.230 3.230 2.647 1.220 271a 607 546b 2.019 113c Regression Residual 526.761 199 Total 529.991 200 3.231 1.616 Residual 526.760 198 2.660 Total 529.991 200 Regression 15.808 5.269 Residual 514.183 197 2.610 Regression 529.991 Total a Predictors: (Constant), ValueExpressive 200 b Predictors: (Constant), ValueExpressive, PIcategorized c Predictors: (Constant), ValueExpressive, PIcategorized, VExPI d Dependent Variable: CounterfeitPurchaseIntention Coefficientsa Unstandardized Coefficients Model B Standardized Coefficients Beta Std Error t Sig (Constant) 2.655 094 2.654 327 085 331 078 8.117 1.105 8.019 000 ValueExpressive 094 088 078 1.063 289 PIcategorized 005 238 001 (Constant) ValueExpressive 1.954 457 308 131 (Constant) ValueExpressive 256 271 000 020 984 4.272 000 2.353 020 1.783 1.373 PIcategorized VExPI -.385 a Dependent Variable: CounterfeitPurchaseIntention 666 422 2.061 041 175 -.519 -2.195 029 Model B Model Summaryd Change Statistics Model R R Square Adjusted R Square Std Error of the Estimate R Square Change F Change df1 df2 Sig F Change 248a 250b 262c 061 063 069 057 053 054 1.58098 1.58391 1.58298 061 001 006 13.038 265 1.234 1 199 198 197 000 607 268 a Predictors: (Constant), SocialAdjustive b Predictors: (Constant), SocialAdjustive, PIcategorized c Predictors: (Constant), SocialAdjustive, PIcategorized, SAxPI d Dependent Variable: CounterfeitPurchaseIntention ANOVAd Sum of Squares df Mean Square F Sig Regression 32.589 000a 497.402 32.589 2.500 13.038 Residual 199 Total 529.991 200 Regression 33.254 16.627 6.628 002b Residual 496.737 198 2.509 Total 529.991 200 Regression 36.345 12.115 4.835 003c Residual 493.646 197 2.506 529.991 Total a Predictors: (Constant), SocialAdjustive 200 Model b Predictors: (Constant), SocialAdjustive, PIcategorized c Predictors: (Constant), SocialAdjustive, PIcategorized, SAxPI d Dependent Variable: CounterfeitPurchaseIntention Coefficientsa Unstandardized Coefficients Model B Standardized Coefficients Beta Std Error (Constant) 1.683 SocialAdjustive (Constant) t Sig .000 248 4.432 3.611 4.453 088 256 3.628 000 -.118 229 -.036 -.515 607 1.248 559 2.234 027 435 136 3.197 002 309 1.701 380 086 382 SocialAdjustive 320 PIcategorized (Constant) SocialAdjustive 348 000 000 1.735 .710 PIcategorized SAxPI -.198 a Dependent Variable: CounterfeitPurchaseIntention 780 218 910 364 178 -.299 -1.111 268 Model C Model Summaryc Change Statistics Model R R Square Adjusted R Square Std Error of the Estimate R Square Change F Change df1 df2 Sig F Change 267a 302b 072 091 062 077 1.57648 1.56387 072 019 7.625 4.206 198 197 001 042 a Predictors: (Constant), PKcategorized, SocialAdjustive b Predictors: (Constant), PKcategorized, SocialAdjustive, SAxPK c Dependent Variable: CounterfeitPurchaseIntention ANOVAc Sum of Squares df Mean Square F Sig Regression 37.901 001a 492.090 18.950 2.485 7.625 Residual 198 Total 529.991 200 Regression 48.188 16.063 6.568 000b Residual 481.803 197 2.446 Model 529.991 200 Total a Predictors: (Constant), PKcategorized, SocialAdjustive b Predictors: (Constant), PKcategorized, SAxPK (Constant) 1.677SocialAdjustive, 379 c Dependent Variable: CounterfeitPurchaseIntention SocialAdjustive 359 092 PKcategorized -.354 242 288 -.108 748 Coefficientsa 588 (Constant) SocialAdjustive 612 153 Standardized Coefficients 490 Coefficients 803 Beta.371 PKcategorized Unstandardized 1.218 Model B SAxPK -.391 Std Error 191 a Dependent Variable: CounterfeitPurchaseIntention -.601 4.429 3.905 000 -1.462 1.272 145 205 3.990 000 1.516 131 t -2.051 Sig .042 000 1.685 Moderation effects of product knowledge on the relationship between social-adjustive function and counterfeit purchase intention Moderation effects of product involvement on the relationship between valueexpressive function and counterfeit purchase intention ... Hạo Nhiên WHAT EFFECT CONSUMERS? ?? INTENTION TO BUY COUNTERFEIT LUXURY BRANDS? THE MODERATING ROLE OF PRODUCT INVOLVEMENT AND PRODUCT KNOWLEDGE: EVIDENCE FROM VIETNAM ID: 22130049 MASTER OF BUSINESS... involvement The level of product involvement reflects two aspects: (1) the importance of the product in consumer‘s life, and (2) the interest of the consumer in the product, or the amount of pleasure the. .. benefits they might gain from buying counterfeits On the other hand, the moderation effect of product involvement on the relationship between social-adjustive function and counterfeit purchase intention