The effect of communication media on dimensions of brand equily

UNIVERSITY OF ECONOMICS HO CHI MINH CITY International School of Business Cao Thi Hang THE EFFECT OF COMMUNICATION MEDIA ON DIMENSIONS OF BRAND EQUITY ID:22110016 MASTER OF BUSINESS (Honours) SUPERVISOR: Le Nguyen Hau Ho Chi Minh City – Year 2014 Abstract This study is aimed to explore the relative impact of social media and traditional media on customer-based brand equity dimensions in three groups of product market such as foods (Cocacola, Nescafe, Vinamilk), banking (ACB, Techcombank, Vietcombank) and electronics (Samsung, Sony, Toshiba) It then tests the impact of dimension of customer-based brand equity on purchase intention The study was conducted through two steps including preliminary research and formal research Preliminary research employed focus group discussion while formal research is quantitative research technique with a sample of 228 cases The Model used in this study based on the previous researches and qualitative study to identify factors in brand value chain The results show that both of traditional media and social media have a strong impact on dimensions of brand equity (brand awareness, brand association) Social media have a stronger impact on brand awareness and brand association compared to traditional media Additionally, brand awareness have no direct relationship with purchase intention In this research, there is no difference between firm created social media and user generated social media, these concept combined with each other Chapter 1: Introduction 1.1 Background 1.2 Research problem .11 1.3 Research objectives 12 1.4 Scope 12 1.5 Research Structure .13 Chapter 2: Literature Review .14 2.1 Theoretical background 14 2.1.1 The concept of Social Media Marketing .14 2.1.2 Traditional Communication 15 2.1.3 Brand Equity and Customers-based Brand Equity .16 2.1.4 Concept of Brand Value Chain 19 2.2 A Brief Review of Previous Study 20 2.3 Research hypotheses and Model .21 Chapter 3: Research Method 25 3.1 Study Design .25 3.1.1 Research Method 25 3.1.2 Research process 26 3.2 Scale Development .28 3.2.1 Firm created social media 28 3.2.2 User generated Social Media 29 3.2.3 Traditional Media 30 3.2.4 Brand Awareness 30 3.2.5 Brand Association .31 3.2.6 Brand Attitude .31 3.3.7 Purchase Intention .32 3.3 Pilot Study (N=100) 33 3.3.1 Firm created Social Media 34 3.3.2 User generated Social Media 35 3.3.3 Traditional media 35 3.3.4 Brand awareness 35 3.3.5 Brand associations 35 3.3.6 Brand attitude 36 3.3.7 Purchase intention .36 3.4 Main Study 37 3.4.1 Brand name for research .37 3.4.2 Sample size and sample method 38 3.4.3 Data collection Method .38 Chapter Research Result 40 4.1 Reliability Analysis 40 4.2 EFA analysis .41 4.2.1 EFA group 42 4.2.2 EFA group 43 4.2.3 EFA group 45 4.3 CFA Analysis 47 4.3.1 Social Media .47 4.3.2 Brand Association .49 4.3.3 Brand Awareness 49 4.3.4 Research Model 50 4.4 Research Model Testing 52 4.4.1 The saturated model 52 4.4.2 Testing Theoretical Model 56 4.4.3 Testing Competitive model 59 4.4.4 BOOTSTRAP analysis for Theoretical Model (Refined) 62 4.4.5 Hypothesis testing .63 Chapter 5: Conclusions, Implication and Limitation .66 References .69 Appendix .73 LIST OF FIGURES Figure 2.1: Brand Value Chain Figure 2.2 Research Model Figure 3.1: Research Process Figure 4.1: CFA for Social Media Figure 4.2: CFA for Brand Association Figure 4.3: CFA for Brand Awareness Figure 4.4: Theoretical Model Figure 4.4: Competitive model Figure 4.5: SEM for The saturated model Figure 4.6: CFA for Theoretical Model Figure 4.7: CFA for Theoretical Model (Refined) Figure 4.8: CFA for Competitive model LIST OF TABLES Table 3.1: The measurement of scales Table 3.2: Firm created Social Media Scale Table 3.3: User generated Social Media Scale Table 3.4: Traditional Media Scale Table 3.5: Brand awareness Scale Table 3.6: Brand Association Scale Table 3.7: Brand Attitude Scale Table 3.8: Purchase Intention Scale Table 3.9: Reliability analysis of all items (Pilot test) Table 3.10: Reliability analysis Brand awareness, Brand association and Purchase intention (after deleted unsatisfied items) Table 4.1: Cronbach’s alpha of all items (Main study) Table 4.2: Pattern Matrixa Table 4.3: Pattern Matrixa Table 4.4: Pattern Matrix – after deleted variance with unsatisfied Table 4.5: Factor Matrixa Table 4.6: Covariance Table 4.7: SEM for Scale - Covariances: (Group number - Default model) Table 4.8: Composite reliability and Variance extracted for Scale Table 4.9: Briefly result of scale measuring Table 4.10: SEM statistics Table 4.11: Theoretical Model - Covariance Table 4.12: SEM statistics for Theoretical Model (Refined) Table 4.13: Theoretical Model (Refined) - Regression Weights (Unstandardized) Table 4.14 - SEM statistics Competitive model Table 15 - Competitive model - Regression Weights Table 4.16: Bootstrap Result Table 4.17: Bootstrap Result CHAPTER 1: INTRODUCTION 1.1 Background The rapid growth in the popularity of social media platforms (such as Youtube, social network, etc.) in recent years has raised the question of whether this phenomenon has reduced marketers’ control of brand management (Berthon et al 2007) Moreover, consumers are increasingly using social media sites to search for information and turning away from traditional media, such as television, radio, and magazines (Mangold and Faulds 2009); cited in Schivinski & Dąbrowski (2013) According to Burmann and Arnhold, 2008, the Internet and Web 2.0 have empowered proactive consumer behavior in the information and purchase process Based on the latest survey of the development of the Internet, social media, digital and mobile phones in Asia, Vietnam known as "the most interesting markets in Asia" The percentage of Internet users over total population is 34% (higher than the world average is 33%) In 2012, Vietnam has added 1.59 million new users (wearesocial.net, 2012) Additional, social networking, digital devices and mobile phone VN is growing astonishingly, internet users in Vietnam increased by 5% since late 2011 35% of mobile Internet users access social media content over the phone This is also one of facilities which helps social media of enterprise reach more target customers (wearesocial.net, 2012) The strong development of social networks create trends in the advertising in Social networks Advertising on social networks become a trend in over the world, they predicted that advertising on social networks will bring more than $ billion in revenue in 2015 This makes the enterprise pay attention to this channel of communication, and social media plays an important role in marketing strategy (wearesocial.net, 2012) Potential of communication via social media will be increased strongly in the future because internet in Vietnam gets more impressed development in near time For example, Da Nang installed nearly 400 Wi-Fi post cover through this province, ensuring 10,000 peoples can access at the same time in September 2013 In Vietnam, Da Nang city is the fourth city with free Wi-Fi coverage, after Hoi An, Ha Long and Hue (vnexpress.net, 2013) Ho Chi Minh City tended to set up free Wifi on bus for attracting more people use bus Along with the development of internet with high speed internet and increase quickly of mobile devices that makes Social Media become popular more than any marketing tool Additionally, consumers are turning away from traditional media such as TV, radio, or magazines and increasingly using social media to search for information (Mangold and Faulds, 2009) The advantage of social media is two-way interoperability on widespread but rarely the communication tools can reach before that Therefore, brand communication not only created solely by company, but also generated by users on Social Media communication This creates opportunities for enterprise social activities not only widely but also deeply Social media not only allows companies convey the message to the target customers but also build stronger relationships with them There are different effects between firm-created and users-generated in Social Media This research will examine effect size of social media and traditional media on dimensions of brand equity Social media include firm-created and user-generated in Social Media Then, this study will test the impact of dimensions of brand equity on purchase intention 10 Appendix 6: CFA for Theoretical Model (Refined) Table 1: Theoretical Model (Refined) – CMIN Model Default model Saturated model Independence model NPAR 48 190 19 CMIN 279.271 000 2692.892 DF 142 171 P 000 CMIN/DF 1.967 000 15.748 Table 2: Theoretical Model (Refined) – Baseline Comparisons Model Default model Saturated model Independence model NFI Delta1 896 1.000 000 RFI rho1 875 000 IFI Delta2 946 1.000 000 TLI rho2 934 000 CFI 946 1.000 000 Table 3: Theoretical Model (Refined) – RMSEA Model Default model Independence model RMSEA 065 255 LO 90 054 246 HI 90 077 263 PCLOSE 015 000 Table 4: Theoretical Model (Refined) - Covariance: (Group number - Default model) Parameter M.I Par Change e26 < > SOC 4.475 -.132 e26 < > e24 5.852 150 e22 < > SOC 5.030 -.162 e22 < > e24 4.906 160 e13 < > e26 5.438 118 e13 < > e23 7.812 203 e10 < > TRA 5.451 -.155 e10 < > e23 7.002 -.228 e10 < > e22 4.232 143 e7 < > e23 4.292 -.156 e8 < > e23 6.732 171 84 Parameter M.I Par Change e8 < > e13 8.394 134 e8 < > e10 9.682 -.170 e3 < > TRA 14.655 302 e3 < > SOC 5.401 -.204 e3 < > e7 4.571 159 e3 < > e9 5.598 173 e4 < > e11 5.267 -.134 e5 < > e22 7.182 -.146 e5 < > e10 10.837 -.183 e19 < > e4 4.060 -.103 e18 < > e22 9.152 -.189 e18 < > e3 4.018 -.153 e17 < > e26 5.175 -.121 e17 < > e23 4.487 -.162 e17 < > e4 18.326 -.227 e17 < > e5 13.413 182 e16 < > e24 4.499 -.125 e16 < > e10 5.042 -.128 e16 < > e17 5.381 116 e15 < > e10 4.830 121 e15 < > e11 4.353 113 e15 < > e12 4.950 -.106 e14 < > e11 4.626 -.124 e14 < > e8 4.494 095 e14 < > e4 6.169 122 85 Table 5: Theoretical Model (Refined) - Regression Weights: (Group number - Default model) Estimate S.E C.R P AWA < - SOC 263 086 3.068 002 AWA < - TRA 249 098 2.542 011 ASS < - SOC 204 066 3.071 002 ASS < - TRA 214 075 2.847 004 ASS < - AWA 360 066 5.420 *** PUR < - ASS 906 093 9.765 *** USE3 < - SOC 1.000 USE2 < - SOC 953 060 15.843 *** TRA3 < - TRA 1.000 TRA2 < - TRA 1.041 075 13.801 *** TRA1 < - TRA 1.017 079 12.898 *** AWA3 < - AWA 1.000 AWA2 < - AWA 990 082 12.118 *** AWA1 < - AWA 918 081 11.406 *** AWA4 < - AWA 925 073 12.725 *** Parameter ASS1 < - ASS 1.000 ASS2 < - ASS 1.087 074 14.690 *** ASS3 < - ASS 1.060 087 12.141 *** ASS4 < - ASS 1.010 091 11.162 *** ASS5 < - ASS 840 091 9.264 *** ASS6 < - ASS 930 090 10.321 *** PUR1 < - PUR 1.000 PUR3 < - PUR 1.125 118 9.501 *** < - SOC 729 077 9.508 *** USE1 < - SOC 979 063 15.495 *** FIR3 Label Table 6: Theoretical Model (Refined) - Standardized Regression Weights: (Group number - Default model) 86 Parameter Estimate AWA < - SOC 289 AWA < - TRA 242 ASS < - SOC 250 ASS < - TRA 233 ASS < - AWA 401 PUR < - ASS 883 USE3 < - SOC 857 USE2 < - SOC 859 TRA3 < - TRA 805 TRA2 < - TRA 871 TRA1 < - TRA 806 AWA3 < - AWA 821 AWA2 < - AWA 763 AWA1 < - AWA 726 AWA4 < - AWA 797 ASS1 < - ASS 748 ASS2 < - ASS 802 ASS3 < - ASS 818 ASS4 < - ASS 755 ASS5 < - ASS 638 ASS6 < - ASS 701 PUR1 < - PUR 754 PUR3 < - PUR 711 FIR3 < - SOC 593 USE1 < - SOC 845 87 88 Appendix 7: SEM for Competitive Model Table 1: Competitive Model - Regression Weights: (Group number - Default model) Estimate S.E C.R P AWA < - SOC 259 086 3.027 002 AWA < - TRA 252 098 2.575 010 ASS < - SOC 163 064 2.554 011 ASS < - TRA 233 073 3.183 001 ASS < - AWA 400 066 6.040 *** PUR < - ASS 921 105 8.741 *** PUR < - AWA 081 076 1.068 285 ATT4 < - ASS 974 088 11.027 *** TRA3 < - TRA 1.000 TRA2 < - TRA 1.038 075 13.833 *** TRA1 < - TRA 1.015 079 12.926 *** AWA3 < - AWA 1.000 AWA2 < - AWA 989 082 12.126 *** AWA1 < - AWA 917 080 11.401 *** AWA4 < - AWA 931 072 12.842 *** Parameter ASS1 < - ASS 1.000 ASS2 < - ASS 1.076 072 14.870 *** ASS3 < - ASS 1.022 085 11.958 *** ASS4 < - ASS 976 089 10.981 *** ASS5 < - ASS 813 089 9.151 *** ASS6 < - ASS 926 089 10.466 *** ATT1 < - ASS 976 085 11.497 *** Label 89 Parameter Estimate S.E C.R P PUR1 < - PUR 1.000 PUR3 < - PUR 1.080 106 10.189 *** < - SOC 729 077 9.501 *** USE1 < - SOC 980 063 15.507 *** USE2 < - SOC 953 060 15.802 *** USE3 < - SOC 1.000 FIR3 Label Table 2: Competitive Model - Standardized Regression Weights: (Group number Default model) Parameter Estimate AWA < - SOC 286 AWA < - TRA 246 ASS < - SOC 200 ASS < - TRA 254 ASS < - AWA 446 PUR < - ASS 878 PUR < - AWA 086 ATT4 < - ASS 732 TRA3 < - TRA 806 TRA2 < - TRA 870 TRA1 < - TRA 806 AWA3 < - AWA 820 AWA2 < - AWA 762 AWA1 < - AWA 724 90 Parameter Estimate AWA4 < - AWA 801 ASS1 < - ASS 747 ASS2 < - ASS 793 ASS3 < - ASS 788 ASS4 < - ASS 729 ASS5 < - ASS 618 ASS6 < - ASS 697 ATT1 < - ASS 760 PUR1 < - PUR 770 PUR3 < - PUR 697 FIR3 < - SOC 593 USE1 < - SOC 847 USE2 < - SOC 858 USE3 < - SOC 857 Table 3: Competitive Model - CMIN Model Default model Saturated model Independence model NPAR CMIN DF P CMIN/DF 53 360.924 178 000 2.028 231 000 21 3084.420 210 000 14.688 Table 4: Competitive Model - Baseline Comparisons Model Default model NFI Delta1 RFI rho1 IFI Delta2 TLI rho2 CFI 883 862 937 925 936 91 NFI Delta1 Model Saturated model Independence model RFI rho1 IFI Delta2 1.000 000 TLI rho2 1.000 000 000 CFI 1.000 000 000 Table 5: Competitive Model - RMSEA Model RMSEA LO 90 HI 90 PCLOSE Default model 067 057 077 003 Independence model 246 238 253 000 Table 6: Competitive Model - Covariances: (Group number - Default model) Parameter M.I Par Change e26 < > SOC 5.380 -.135 e22 < > SOC 6.292 -.172 e13 < > e23 6.388 180 e10 < > TRA 5.563 -.157 e10 < > e23 8.642 -.250 e7 < > e23 4.339 -.155 e8 < > e23 6.823 170 e8 < > e13 8.264 132 e8 < > e10 9.646 -.170 e3 < > SOC 5.405 -.204 e3 < > TRA 14.650 302 e3 < > e7 4.601 159 e3 < > e9 5.596 173 e4 < > e11 5.383 -.135 e5 < > e22 6.792 -.135 92 Parameter M.I Par Change e10 10.681 -.182 e21 < > SOC 4.089 -.136 e21 < > e26 11.960 175 e21 < > e23 8.785 229 e20 < > e26 4.241 097 e20 < > e23 4.058 -.144 e20 < > e22 17.006 229 e20 < > e10 4.468 128 e20 < > e8 6.005 -.113 e20 < > e9 5.471 121 e19 < > e22 4.313 -.117 e19 < > e4 5.110 -.114 e19 < > e5 4.025 095 e18 < > e22 9.682 -.185 e17 < > e26 6.934 -.133 e17 < > e23 4.029 -.154 e17 < > e4 18.178 -.229 e17 < > e5 15.110 197 e17 < > e21 4.730 -.128 e16 < > e24 5.696 -.144 e16 < > e10 5.303 -.135 e16 < > e21 6.074 -.130 e16 < > e17 12.431 186 e15 < > e12 4.924 -.105 e14 < > e11 4.994 -.128 e14 < > e8 4.533 095 e14 < > e9 4.569 -.107 e5 < > 93 Appendix 8: BOOTSTRAP Analysis – Theoretical model (Refined) Table 1: Theoretical Model (Refined) Bootstrap Standardized Regression Weights: (Group number - Default model) Parameter SE SE-SE Mean Bias SE-Bias AWA < - SOC 106 003 286 -.004 005 AWA < - TRA 111 004 239 -.003 005 ASS < - SOC 105 003 240 -.011 005 ASS < - TRA 100 003 238 005 004 ASS < - AWA 075 002 406 005 003 PUR < - ASS 052 002 883 000 002 USE3 < - SOC 024 001 858 001 001 USE2 < - SOC 032 001 858 -.001 001 TRA3 < - TRA 041 001 804 000 002 TRA2 < - TRA 037 001 872 001 002 TRA1 < - TRA 036 001 803 -.003 002 AWA3 < - AWA 043 001 820 -.001 002 AWA2 < - AWA 043 001 763 000 002 AWA1 < - AWA 055 002 728 002 002 AWA4 < - AWA 035 001 797 000 002 ASS1 < - ASS 038 001 749 002 002 ASS2 < - ASS 030 001 803 001 001 ASS3 < - ASS 040 001 815 -.003 002 ASS4 < - ASS 046 001 753 -.002 002 ASS5 < - ASS 062 002 632 -.006 003 ASS6 < - ASS 047 001 699 -.001 002 PUR1 < - PUR 047 001 752 -.001 002 94 Parameter SE SE-SE Mean Bias SE-Bias PUR3 < - PUR 064 002 706 -.005 003 FIR3 < - SOC 058 002 589 -.005 003 USE1 < - SOC 031 001 847 002 001 Table 2: Theoretical Model (Refined) - Bootstrap ML Parameter BOOTSTRAP Estimate SE SE SE-SE Mean Bias SE-Bias AWA < - SOC 0.289 0.064 0.106 0.003 0.286 -0.004 0.005 AWA < - TRA 0.242 0.065 0.111 0.004 0.239 -0.003 0.005 ASS < - SOC 0.25 0.064 0.105 0.003 0.24 -0.011 0.005 ASS < - TRA 0.233 0.065 0.1 0.003 0.238 0.005 0.004 ASS < - AWA 0.401 0.061 0.075 0.002 0.406 0.005 0.003 PUR < - ASS 0.883 0.031 0.052 0.002 0.883 0.002 USE3 < - SOC 0.857 0.034 0.024 0.001 0.858 0.001 0.001 USE2 < - SOC 0.859 0.034 0.032 0.001 0.858 -0.001 0.001 TRA3 < - TRA 0.805 0.039 0.041 0.001 0.804 0.002 TRA2 < - TRA 0.871 0.033 0.037 0.001 0.872 0.001 0.002 TRA1 < - TRA 0.806 0.039 0.036 0.001 0.803 -0.003 0.002 AWA3 < - AWA 0.821 0.038 0.043 0.001 0.82 -0.001 0.002 AWA2 < - AWA 0.763 0.043 0.043 0.001 0.763 0.002 AWA1 < - AWA 0.726 0.046 0.055 0.002 0.728 0.002 0.002 AWA4 < - AWA 0.797 0.040 0.035 0.001 0.797 0.002 ASS1 < - ASS 0.748 0.044 0.038 0.001 0.749 0.002 0.002 ASS2 < - ASS 0.802 0.040 0.03 0.001 0.803 0.001 0.001 ASS3 < - ASS 0.818 0.038 0.04 0.001 0.815 -0.003 0.002 ASS4 < - ASS 0.755 0.044 0.046 0.001 0.753 -0.002 0.002 ASS5 < - ASS 0.638 0.051 0.062 0.002 0.632 -0.006 0.003 ASS6 < - ASS 0.701 0.047 0.047 0.001 0.699 -0.001 0.002 PUR1 < - PUR 0.754 0.044 0.047 0.001 0.752 -0.001 0.002 PUR3 < - PUR 0.711 0.047 0.064 0.002 0.706 -0.005 0.003 FIR3 < - SOC 0.593 0.054 0.058 0.002 0.589 -0.005 0.003 95 USE1 < - SOC 0.845 0.036 0.031 0.001 0.847 0.002 0.001 Table 3: Theoretical Model (Refined) Bootstrap - Standardized Regression Weights: (Group number - Default model) Parameter Estimate Lower Upper P AWA < - SOC 289 119 466 007 AWA < - TRA 242 067 432 023 ASS < - SOC 250 085 439 014 ASS < - TRA 233 062 378 028 ASS < - AWA 401 273 520 007 PUR < - ASS 883 787 955 005 USE3 < - SOC 857 810 893 006 USE2 < - SOC 859 793 905 006 TRA3 < - TRA 805 726 863 006 TRA2 < - TRA 871 803 926 007 TRA1 < - TRA 806 743 857 005 AWA3 < - AWA 821 743 884 006 AWA2 < - AWA 763 692 829 004 AWA1 < - AWA 726 616 800 010 AWA4 < - AWA 797 730 849 006 ASS1 < - ASS 748 669 799 009 ASS2 < - ASS 802 746 842 008 ASS3 < - ASS 818 750 877 003 ASS4 < - ASS 755 664 823 005 ASS5 < - ASS 638 536 735 003 96 Parameter Estimate Lower Upper P < - ASS 701 615 768 005 PUR1 < - PUR 754 677 831 004 PUR3 < - PUR 711 594 803 004 FIR3 < - SOC 593 490 684 003 USE1 < - SOC 845 788 890 007 ASS6 Table 4: BOOTSTRAP Standardized Parameter AWA AWA ASS ASS ASS PUR USE3 USE2 TRA3 TRA2 TRA1 AWA3 AWA2 AWA1 AWA4 ASS1 ASS2 ASS3 ASS4 ASS5 ASS6 PUR1 PUR3 FIR3 USE1 < < < < < < < < < < < < < < < < < < < < < < < < < - SOC TRA SOC TRA AWA ASS SOC SOC TRA TRA TRA AWA AWA AWA AWA ASS ASS ASS ASS ASS ASS PUR PUR SOC SOC ML Estimate 0.289 0.242 0.25 0.233 0.401 0.883 0.857 0.859 0.805 0.871 0.806 0.821 0.763 0.726 0.797 0.748 0.802 0.818 0.755 0.638 0.701 0.754 0.711 0.593 0.845 P 0.002 0.011 0.002 0.004 *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** *** SE 0.106 0.111 0.105 0.1 0.075 0.052 0.024 0.032 0.041 0.037 0.036 0.043 0.043 0.055 0.035 0.038 0.03 0.04 0.046 0.062 0.047 0.047 0.064 0.058 0.031 BOOTSTRAP SE-SE Mean Bias 0.003 0.286 -0.004 0.004 0.239 -0.003 0.003 0.24 -0.011 0.003 0.238 0.005 0.002 0.406 0.005 0.002 0.883 0.001 0.858 0.001 0.001 0.858 -0.001 0.001 0.804 0.001 0.872 0.001 0.001 0.803 -0.003 0.001 0.82 -0.001 0.001 0.763 0.002 0.728 0.002 0.001 0.797 0.001 0.749 0.002 0.001 0.803 0.001 0.001 0.815 -0.003 0.001 0.753 -0.002 0.002 0.632 -0.006 0.001 0.699 -0.001 0.001 0.752 -0.001 0.002 0.706 -0.005 0.002 0.589 -0.005 0.001 0.847 0.002 SE-Bias 0.005 0.005 0.005 0.004 0.003 0.002 0.001 0.001 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.001 0.002 0.002 0.003 0.002 0.002 0.003 0.003 0.001 Appendix 8: Figure 97 Figure 1: CFA for Social Media 98 ... factors in brand value chain The results show that both of traditional media and social media have a strong impact on dimensions of brand equity (brand awareness, brand association) Social media have... media on dimensions of brand equity Social media include firm-created and user-generated in Social Media Then, this study will test the impact of dimensions of brand equity on purchase intention... media have strong effects on marketing performance However, the authors reveal that the effect of traditional media is stronger than the effect of social media There have been a number of researchers