Testing a model of customer - Based brand equity in the Vietnamese banking servic (Viết bằng Tiếng Anh)

nt .488 .884 SQ2 - Bank X 's employees are well dressed and appear neat .560 .881 SQ4 - Bank [X]' s physical facilities are visually appealing .469 .886 SQ5 - Bank [X] provides its services at the time it promises to do so .510 .883 SQ6 - When I have problems, bank [X] is sympathetic and reassuring. .610 .878 SQ7 - I receive prompt service from bank [X]'s employees .663 .876 SQ8 - Bank [X] bank employees are always willing to help me .659 .876 SQ9 - I feel safe in my transaction with the bank [X] .535 .882 SQ10 - Bank [X]' s employees are polite .671 .875 SQ11 - Bank [X]'s employees know the bank product and service very well .589 .879 SQ12 - Bank [X] employees have necessary knowledge to answer my questions .596 .879 SQ13 - Bank [X]' s employees know what my needs are and how the bank's products can satisfy them .594 .879 SQ14 - Bank [X]'s employees give me personal attention .595 .879 Price scale ( α = .888 ) PC1 - Interest rates of bank [X] are very competitive .756 .856 PC2 - Service fees of bank [X] are very competitive .725 .868 PC3 - Bank [X] offers me price deals .764 .854 PC4 - Bank [X] offers me very reasonable price .785 .848 Brand promise scale ( α = .793) PR1 - Bank [X] creates meaningful promises for me .581 .775 PR2 - Bank [X] lives up to its promises .717 .626 PR3 - Bank [X] creates positive associations and image .612 .743 Brand differentiation scale ( α = .834) DF1 - Bank [X] differs from other banks in a positive way .698 .768 DF2 - Bank [X] is unique compared to other banks .722 .741 DF3 - Bank [X] offers advantages that other banks can not .667 .800 42 Brand trust & credibility quality scale (α = .691) TR1 - Bank [X] communicates openly and honestly .384 .765 TR2 - Bank [X] is trustworthy and credible .566 .527 TR3 - I have great faith in bank [X] .589 .494 Rational evaluations scale (α = .818 ) RE1 - Bank [X] provides good value for money .634 .787 RE2 - Bank [X] greatly meets expectations .703 .717 RE3- Overall, I am very satisfied with bank [X] .679 .743 Emotional evaluations scale (α = .848) EE1 - When thinking of bank [X], I get a positive and warm feeling .728 .778 EE2 - Bank [X] means a lot to me .732 .773 EE3 - I am proud to be a customer of bank [X] .690 .813 Customer-brand relationship scale (α = .844 ) RL1 - The next time I am going to transact with a bank, I am going to bank [X] again .615 .823 RL2 - I will recommend bank [X] to others .595 .830 RL3 - Overall, I find Bank [X] better than other banks .677 .805 RL4 - I am very interested in bank [X] .698 .800 RL5 - It is important for me to maintain the relationship with bank [X] in the future. .680 .805 4.3.2 Exploratory factor analysis All variables retained were then put into EFA. The purpose of this step was to continuously purify the instrument and to identify the components that explain for the correlation between variables or sets of variables. One of the underlying objectives of EFA is to reduce a large number of variables to a minimum number that can explain most of the characteristics of the original variables. Each component extracted from the original set of variables represents a discriminated aspect of the construct being studied. These extracted variables then can be used as independent variables in later analysis. The EFA model is expressed in the following equation: Fi=Wi1X1+ Wi2X2+ Wi3X3+…+ WikXk 43 where Fi : Estimated value of Factor i Wik : Weight or factor score coefficient Xk:: variable k k: Number of variable There are two common techniques used to extract factors in EFA, principal components analysis and principal factors analysis. In most cases, these two methods usually yield very similar results. However, principal components analysis is often preferred as a method for data reduction, while principal factors analysis is often preferred when the goal of the analysis is to detect structure (StatSoft, 2008). The current study employs principal components analysis with varimax rotation technique. As the ultimate purpose of running EFA in this study is to reduce the variables for MLR in the later stage, principal component analysis is a better choice. Principal components analysis with varimax rotation method maximizes the variance on the new axes; in other words, this combination will minimize numbers of variables with high factor loading in the same factor, lending itself to easier interpretation (Trong & Ngoc, 2005). The results of EFA are shown in table 4.3. There are 10 factors extracted at Eigenvalues of 1.022 and total explained variance of 70.641. all factor loading are greater than the cut-off value of 0.4. The result of KMO and Bartlett's Test is also very high (0.913 at p=0.00). This indicates that EFA is suitable and all measures can be used for the next analysis. 44 Table 4.3 – Rotated component matrix Observed Component variables 1 2 3 4 5 6 7 8 9 10 SQ1 0.094 0.175 0.141 0.083 0.071 0.041 0.067 0.131 0.785 0.084 SQ2 0.008 0.187 0.051 0.339 -0.052 0.149 0.101 0.132 0.685 0.075 SQ4 0.186 0.179 0.155 0.006 0.289 0.132 0.000 -0.075 0.691 0.18 SQ5 0.151 0.747 0.028 0.043 -0.088 0.081 0.058 0.017 0.172 0.125 SQ6 0.103 0.754 0.181 0.151 0.181 0.066 0.033 0.077 0.026 0.175 SQ7 -0.049 0.739 0.065 0.243 0.123 0.138 0.068 0.14 0.149 0.101 SQ8 -0.091 0.685 0.103 0.225 0.171 0.123 0.248 0.13 0.171 0.116 SQ9 -0.039 0.563 0.272 0.316 -0.033 0.185 -0.05 0.197 0.109 -0.18 SQ10 -0.043 0.365 0.092 0.496 0.192 0.241 0.186 0.083 0.325 -0.028 SQ11 0.163 0.202 0.081 0.782 0.083 0.14 0.089 0.004 0.045 0.065 SQ12 0.103 0.2 0.141 0.743 0.087 -0.027 0.176 0.013 0.136 0.081 SQ13 0.138 0.154 0.133 0.776 0.165 -0.004 -0.006 0.072 0.057 0.263 SQ14 0.203 0.164 0.193 0.488 0.447 0.137 0.009 0.027 0.175 0.226 PC1 0.802 0.021 0.133 0.105 0.118 0.029 0.175 0.005 0.051 0.111 PC2 0.831 0.012 0.09 0.161 0.114 0.079 0.107 -0.053 0.024 -0.041 PC3 0.808 0.019 0.023 0.03 0.175 0.047 0.19 -0.007 0.115 0.121 PC4 0.83 0.051 0.113 0.085 0.072 0.006 0.164 -0.007 0.053 0.16 PR1 0.188 0.028 0.138 0.179 0.253 0.127 0.223 0.018 0.081 0.685 PR2 0.107 0.197 0.14 0.15 0.081 0.25 0.131 0.135 0.179 0.743 PR3 0.164 0.299 0.134 0.193 -0.006 0.219 0.048 0.241 0.13 0.618 DF1 0.081 0.194 0.135 0.103 0.028 0.826 -0.009 0.1 0.063 0.115 DF2 0.032 0.08 0.111 0.102 0.098 0.825 0.115 0.14 0.13 0.09 DF3 0.054 0.154 0.068 -0.009 0.245 0.737 0.076 0.098 0.081 0.233 TR1 0.163 0.117 0.004 0.113 0.305 -0.04 -0.07 0.636 0.03 0.123 TR2 -0.078 0.152 0.164 0.001 -0.016 0.156 0.049 0.798 0.053 0.056 TR3 -0.123 0.088 0.135 0.01 0.005 0.204 0.12 0.794 0.1 0.073 RE1 0.286 0.127 0.217 0.167 0.231 0.114 0.637 -0.018 0.05 0.193 RE2 0.334 0.098 0.206 0.058 0.113 0.052 0.731 0.034 0.058 0.158 RE3 0.321 0.122 0.193 0.132 0.155 0.066 0.706 0.103 0.091 0.056 EE1 0.245 0.098 0.236 0.115 0.742 0.087 0.121 -0.033 0.11 0.152 EE2 0.205 0.033 0.235 0.181 0.723 0.203 0.14 0.156 0.002 0.061 EE3 0.087 0.105 0.222 0.131 0.741 0.099 0.229 0.139 0.136 0.033 RL1 0.163 0.042 0.602 0.123 0.205 0.057 0.313 0.15 0.1 0.04 RL2 0.063 0.199 0.791 0.067 -0.04 0.02 -0.022 0.092 0.075 0.092 RL3 0.042 0.074 0.713 0.13 0.188 0.158 0.195 0.133 0.159 -0.016 RL4 0.152 0.117 0.706 0.109 0.313 0.177 0.05 0.033 0.079 0.135 RL5 0.102 0.071 0.672 0.119 0.29 0.042 0.263 0.021 0.008 0.202 Eigenvalues 11.404 3.497 2.181 1.836 1.472 1.319 1.218 1.108 1.082 1.022 Extracted variance 9.369 8.632 8.557 7.976 7.369 6.671 5.703 5.493 5.472 5.399 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization. 45 The service quality scale was developed basing on the Spiros et al (2004)’s scale which covered all aspects of Parasuraman et al (1988)’s service quality measurement. However, only three components were extracted (see table 4.3). They include three variables representing the tangible aspects (SQ1, SQ2,SQ4) and the scale is called tangibles as it was originally termed. The second component (SQ5 to SQ9) is closely related to the reliability and responsiveness perspective and here referred to as “affectivity”. The last component, consisting of 5 variables, SQ10 to SQ14, is characterized as “staff competence”. Factor loading of the variables contained in eight scales (10 components) are all greater than .4. The lowest is of variable SQ 14 – Bank [X]’s employees give me personal attention (0.448). Thus all the variables were then useable. The EFA result for each scale is provided in table 4.4. Table 4.4 – EFA result for individual measurement scales Initial Eigenvalues Extraction/rotation Sums of Squared Loadings Scales Total % of Variance Total % of Variance Service quality 60.575 60.575 Tangibles 5.730 40.962 3.186 22.756 affectivity 1.464 10.459 3.049 21.779 Staff competence 1.287 9.190 2.246 16.040 KMO=.852 (p=.00) Price competitiveness 3.008 75.208 3.008 75.208 KMO=.839 (p=.000) Brand promise 2.123 70.765 2.123 70.765 KMO=.673 (p=.000) Brand differentiation 2.257 75.24 2.257 75.24 KMO=.720 (p=.000) Brand trust 1.888 62.921 1.888 62.921 KMO=.616. (p=.000) Rational evaluation 2.202 73.386 2.202 73.386 KMO=.712 (p=.000) Emotional evaluation 2.302 76.722 2.302 76.722 KMO=.728 (p=.000) 46 Customer-brand relationship 3.099 61.988 3.099 61.988 KMO=.852 (p=.000) 4.4 Testing the research model and the hypotheses 4.4.1 Testing correlations between all constructs It was proposed in chapter 2 that the research model includes 13 hypotheses. To test those hypotheses, the first step was to test the correlations between dependent variables and the independent variables and among independent variables as well. Then multiple linear regressions were run to confirm the relationships among them. The correlation analysis results shown in table 4.5 temporarily allow us to expect that there are positive relationships between the brand evaluations and the brand associations (H1 to H 10) as well as between the customer-brand relationship and the brand evaluations (H11, H12, H13). 4.4.2 Testing research model 4.4.2.1 The relationship between rational evaluation and the brand associations. Hypotheses from H1 to H5 assume that the rational evaluation positively relate to the brand associations (see figure 4.4). The correlation analysis results preliminarily let us be aware of these relationships. However, to ascertain that they truly exist, or in other words, to confirm that all those hypotheses are statistical significant, the first MLR Model (Model I) was run. The “rational relationship” component extracted in the previous step then played the role of a dependent variable. The “enter” method was employed to select all independent variables that would be put into the model. 47 Figure 4.4. Relationships between rational evaluation and the brand associations The MLR results are presented in table 4.5a and table 4.5b. The regression coefficient R square (adjusted) is .424. ANOVA results showed that this model had a F value of 31.946. at sig. = .000 These results allowed us to reject the null hypothesis that all the regression coefficients equal zero ( β1 = β2= β3 =…= βk. =0). However, the adjusted R square value is rather low, indicating that the model’s goodness of fit for the population is not so high. Service quality Price Trust and Credibility Rational Evaluation Differentiation H2 H3 H4 H5 H1 Promise 48 Table 4.5 – Correlation matrix Tangibles Affectivity Staff competence Price Brand promise Differentiatio n Trust & credibility Rational evaluation Emotional evaluation Customer- brand relationship Tangibles Pearson Correlation 1 0.000 0.000 0.012 .308** .311** .316** .206** .167** .262** Sig. (2-tailed) 1.000 1.000 0.833 0.000 0.000 0.000 0.000 0.004 0.000 Affectivity Pearson Correlation 0.000 1 0.000 .308** .369** .192** 0.104 .341** .404** .339** Sig. (2-tailed) 1.000 1.000 0.000 0.000 0.001 0.073 0.000 0.000 0.000 Staff competence Pearson Correlation 0.000 0.000 1 .218** .319** .269** .163** .243** .279** .272** Sig. (2-tailed) 1.000 1.000 0.000 0.000 0.000 0.005 0.000 0.000 0.000 Price Pearson Correlation 0.012 .308** .218** 1 .373** .174** 0.017 .570** .416** .330** Sig. (2-tailed) 0.833 0.000 0.000 0.000 0.003 0.767 0.000 0.000 0.000 Brand promise Pearson Correlation .308** .369** .319** .373** 1 .478** .338** .465** .438** .438** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Differentiation Pearson Correlation .311** .192** .269** .174** .478** 1 .349** .301** .362** .354** Sig. (2-tailed) 0.000 0.001 0.000 0.003 0.000 0.000 0.000 0.000 0.000 Trust & credibility Pearson Correlation .316** 0.104 .163** 0.017 .338** .349** 1 .195** .264** .316** Sig. (2-tailed) 0.000 0.073 0.005 0.767 0.000 0.000 0.001 0.000 0.000 Rational evaluation Pearson Correlation .206** .341** .243** .570** .465** .301** .195** 1 .515** .543** Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 Emotional evaluation Pearson Correlation .167** .404** .279** .416** .438** .362** .264** .515** 1 .575** Sig. (2-tailed) 0.004 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Customer-brand relationship Pearson Correlation .262** .339** .272** .330** .438** .354** .316** .543** .575** 1 Sig. (2-tailed) 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 **. Correlation is significant at the 0.01 level (2-tailed). 49 Table 4.5a. Model summary Model I R R Square Adjusted R Square Std. Error of the Estimate 1 0.662 0.438 0.424 0.759 a. Predictors: (Constant), Trust & credability, Price, Staff competence, Tangibles, Affectivity, Differentiation, Brand promise To decide which hypothesis is statistically significant, partial regression coefficients were tested with t value. The results in table 4.5b show that four latent variables (representing three associations) are statistical significant5. In other words, only three hypotheses, out of six, are supported. (see figure 4.5) Table 4.5b – Coefficients a Unstandardized Coefficients Standardized Coefficients Model I B Std. Error Beta t Sig. (Constant) -2.80E-16 0.044 0 1 Tangibles 0.124 0.05 0.124 2.489 0.013 Affectivity 0.135 0.05 0.135 2.713 0.007 Staff competence 0.078 0.049 0.078 1.588 0.113 Price competitiveness 0.448 0.05 0.448 9.013 0.000 Brand promise 0.143 0.059 0.143 2.402 0.017 Differentiation 0.05 0.053 0.05 0.933 0.351 1 Trust & credability 0.056 0.05 0.056 1.13 0.259 a. Dependent Variable: Rational evaluation 5 All hypotheses in this study were tested at significance level of 0.05 50 Table 4.6 – Summary of hypotheses testing results (Model I) Hypotheses Confirmed H1: Rational evaluation is positively related to perceived service quality YES H2: Rational evaluation is positively related to price competitiveness YES H3: Rational evaluation is positively related to brand promise YES H4: Rational evaluation is positively related to brand differentiation NO H5: Rational evaluation is positively related to brand trust and credibility NO Figure 4.5. Results of model I Adjusted R square =.424 F value = 31.946 Sig. = .000 Service quality Price Promise Trust and Credibility Rational Evaluation Differentiation β=0.259 (sig.=.013) H2 H3 H1 β= 0.448 (sig.= .000) β=0.143 (sig.=.017) 51 4.4.2.2 The relationship between emotional evaluation and the brand associations. The same way as above, the second regression model (model II) was run to test the hypotheses between emotional evaluation and the brand associations (see figure 4.6). The adjusted R square of the second model is .358, F value is 24.434 at .000 significance. These results also allow us to conclude that the model fits with the data. Yet the goodness of fit is also quite low.( Table 4.6a) Figure 4.6. Relationships between emotional evaluation and the brand associations Table 4.6a - Model II Summary Model II R R Square Adjusted R Square Std. Error of the Estimate 1 .611a .373 .358 .80123111 a. Predictors: (Constant), Trust & credibility, Price competitiveness, Staff competence, Tangibles, Affectivity , Brand differentiation, Product quality, Brand promise Service quality Price Promise Trust and Credibility Emotional Evaluation Differentiation H7 H8 H9 H10 H6 52 Hypotheses from H6 to H10 were tested with this model and the results are shown in Table 4.6b and are summarized in table 4.7. Figure 4.7 is used to visually illustrations for the hypotheses testing results. Table 4.6b - Coefficientsa Unstandardized Coefficients Standardized Coefficients Model II B Std. Error Beta t Sig. (Constant) 2.38E-16 0.047 0 1 Tangibles 0.061 0.052 0.061 1.169 0.243 Affectivity 0.26 0.053 0.26 4.959 0.00 Staff competence 0.145 0.052 0.145 2.813 0.005 Price competitiveness 0.248 0.052 0.248 4.733 0.00 Brand promise 0.082 0.063 0.082 1.302 0.194 Differentiation 0.132 0.056 0.132 2.347 0.02 1 Trust & credability 0.116 0.053 0.116 2.207 0.028 a. Dependent Variable: Emotional evaluation Four hypotheses are supported by the results in model II. Table 4.7 – Summary of hypotheses testing results (Model II) Hypotheses Confirmed H6: Emotional evaluation is positively related to perceived service quality YES H7: Emotional evaluation is positively related to price competitiveness YES H8: Emotional evaluation is positively related to brand promise NO H9: Emotional evaluation is positively related to brand differentiation YES H10: Emotional evaluation is positively related to brand trust and credibility YES 53 Figure 4.7. Results of model II 4.4.2.3 The customer-brand relationships. Before testing the hypotheses assuming the relationship between “customer-brand relationships” construct and brand evaluations, this step first tests the assumption that the rational evaluation is positively related to the emotional evaluation (H11). The third regression was run (Model IIIa). Table 4.7a - Model III a Summary Model III a R R Square Adjusted R Square Std. Error of the Estimate 1 .515a .266 .263 .85840387 a. Predictors: (Constant), Emotional evaluation Service quality Price Promise Trust and Credibility Emotional Evaluation Differentiation H7 H9 H10 H6 β=0.405 (sig.=. 005) β=0.248 (sig.=. 000) β=0.132 (sig.=. 02) β=0.116 (sig.= .028) Adjusted R square =.358 F value = 24.434 Sig. = .000 54 Table 4.7b - Coefficientsa Unstandardized Coefficients Standardized Coefficients Model IIIa B Std. Error Beta t Sig. (Constant) -4.701E-16 .050 .000 1.000 1 Emotional evaluation .515 .050 .515 10.295 .000 a. Dependent Variable: Rational evaluation This model was also proved fit with data. The R square is .266, F value is 105.992 at sig.=.000. Thus Null hypothesis: R square= 0 can be rejected. This model has beta of .515 (positive), t value = 10.295 at sig. = .000. As the result, hypothesis H13 was confirmed (figure 48.a). Figure 4.8a – Hypothesis 11 Testing result The fourth regression model (model IIIb) then was run to test the last two hypotheses ( H12 & H13). The results are shown in table 4.8a, 4.8b and figure 4.8. Rational Evaluation Emotional Evaluation H11 β= .515 (sig. =000) 55 Table 4.8a - Model III b Summary Model III b R R Square Adjusted R Square Std. Error of the Estimate 1 .643a .414 .410 .76824887 a. Predictors: (Constant), Emotional evaluation, Rational evaluation Table 4.8b – Coefficients a Unstandardized Coefficients Standardized Coefficients Model (IIIa) B Std. Error Beta t Sig. (Constant) 1.594E-16 .045 .000 1.000 Rational evaluation .336 .052 .336 6.431 .000 1 Emotional evaluation .402 .052 .402 7.685 .000 a. Dependent Variable: Relationship Figure 4.8b. Results of model III b The results from this model indicate that the model fitted the data with F value = 103.06; sig.=.000. Hypotheses H12 and H13 are both supported with β = .336 and .402 Adj. R square = .410 F=103.065 Sig. = .000 Customer-Brand Relationship Rational Evaluation Emotional Evaluation H12 H13 β= .336 (sig. =000) β= .402 (sig. =000) 56 respectively and all at significance level of .000. Table 4.9 – Summary of hypotheses testing results (Model IIIa,b) Hypotheses Confirmed H11: Rational evaluation is positively related to emotional evaluation YES H12: Customer-brand relationship is positively related to rational evaluation YES H13: Customer-brand relationship is positively related to emotional evaluation YES 4.5 Findings and conclusion 4.5.1 Findings MLR results in this chapter have brought out some unexpected outcomes. “Brand differentiation” (H4) and “trust & credibility” (H5) were not supported in their relationship with “rational evaluation”. The contention might be that in the rational perspective, customers make their judgment based on what they see, feel or touch (service quality). It might be more important that a “real” rational evaluation, the cost/benefit evaluation (price) and/or what they expect to receive is satisfied by the bank (brand promise). In this perspective, emotion-based associations, like differentiation or trust and credibility, might not make sense. The results shown in table 4.5b clearly support this argument. Regarding the relationships between emotional evaluation and the brand associations, only four hypotheses were confirmed, H6 (service quality), H7 (price competitiveness), H9 (differentiation) and H10 (trust and credibility). If there is evidence that tangible aspect had an impact on rational evaluation (β=.123, sig=.014), it does not have an emotional impact. Only “affectivity” and “staff competence” were significantly correlated to the customer emotional appraisal. The 57 reasoning might be that the appearance of banking equipment and facilities may result in a professional image of the bank which may then generates trust from the customer for their rational consideration. However, it might not touch their emotion. But affectivity and employee competence are important factors that strongly influence customers’ sentimental preferences to the bank. By comparing the results in table 4.6b with those in table 4.5b, we can see “price competitiveness” is relevant to both rational and emotional evaluations. However, it plays a more important role in rational assessment (β=0.448, sig.=.000) than it does in the emotional perspective (β=0.248, sig.=.000). From this standpoint, service quality makes a larger proportion (β= 0.405, sig.=.005) than the price competitiveness (β=0.248, sig.=.000). Brand differentiation and brand trust and credibility also contributed to the emotional judgment of the customer. In sum, by comparing the results between model I and model II, we can conclude that, from a rational perspective, price competitiveness dominates the customer’s judgment. From the emotional angle, service quality takes over. From a causal-effect perspective, this study ultimately examines the contribution of rational evaluation and emotional evaluation to the customer-brand relationship. As the results in table 4.8b show, the statistical evidence lets us conclude that the customer’s emotional evaluation contributes more than the rational consideration to the customer loyalty to a brand (customer-brand relationship). This is in line with Berry (2000)’s argument that “great brands always make an emotional connection with the intended audience. They reach beyond the purely rational and purely economic level to spark feelings of closeness, affection, and trust”. The relationship is expressed in the following simple equation: RL = 0.402 EE + 0.366 RE Where RL : Customer-brand relationship 58 EE: Emotional evaluation RE: Rational evaluation (to simplify , no constant and residual are put in the equation) 4.5.2 Conclusion This chapter provides the analysis results and main findings of the study. The statistical evidence revealed some unexpected results. Several arguments that explain the research results are also presented in this chapter. Not all hypotheses from the research model were supported and therefore, an adjusted model is suggested below (Fig. 4.9). Figure 4.9. Adjusted model of CBBE in banking service Rational associations Brand evaluations Customer-Brand Relationship Service quality Price Promise Trust and Credibility Rational Evaluation Emotional Evaluation Differentiation H1 H2 H3 H6 H7 H9 H10 H11 H12 H13 Rational & emotional associations 59 Chapter 5: CONCLUSIONS AND IMPLICATIONS 5.1 Introduction Chapter 4 presented the analysis results and the main findings of the study. A modified model was also proposed in the chapter. This chapter summarized all hypotheses that will be used to answer for the research questions in this chapter. Some implications are suggested for academics and practitioners as well. The limitations of this study and some suggestions for further research are also presented in this chapter. The structure for chapter five is showed in figure 5.1. Figure 5.1 – Outline of chapter 5 5.2 Conclusions of the study 5.2.1 Summary of all hypotheses To draw the conclusion for this study, the hypotheses testing results are repeated in table 5.1 for easier reference. 5.5 Conclusion 5.1 Introduction 5.2 Conclusions of the study 5.3 Implications of the study 5.4 Limitations and recommendations 60 Table 5.1. Summary of hypotheses Hypotheses Confirmed H1: Rational evaluation is positively related to perceived service quality YES H2: Rational evaluation is positively related to price competitiveness YES H3: Rational evaluation is positively related to brand promise YES H4: Rational evaluation is positively related to brand differentiation NO H5: Rational evaluation is positively related to brand trust and credibility NO H6: Emotional evaluation is positively related to perceived service quality YES H7: Emotional evaluation is positively related to price competitiveness YES H8: Emotional evaluation is positively related to brand promise NO H9: Emotional evaluation is positively related to brand differentiation YES H10: Emotional evaluation is positively related to brand trust and credibility YES H11: Rational evaluation is positively related to Emotional evaluation YES H12: Customer-brand relationship is positively related to rational evaluation YES H13: Customer-brand relationship is positively related to emotional evaluation YES 5.2.2 Conclusions of the study From the analysis outcomes and the findings presented in chapter 4, with reference to the above tested hypotheses, this study concludes that the first research question is not fully positively answered. This means that the original model of CBBE developed by Martensen & Grønholdt (2004) can not be applied in the Vietnamese banking service without any adaptation. As argued in chapter 2, product quality was not included in the model. As the results, only five brand associations are confirmed in the model. They consist of service quality, price, brand promise, brand differentiation and trust & 61 credibility. A modified model is proposed for the CBBE in the Vietnamese banking perspective. The relationship between emotional evaluation and rational evaluation; and those between these evaluations and customer-brand relationship were significantly supported. This result is consistent with the original model. To answer the second research question, the results in Table 5.1 reveal that, instead of six, only three parameters, service quality, price and brand promise correlate positively with customers’ rational evaluation. From the emotional perspective, there are only four parameters proved to be positively related to the emotional evaluation. These associations consist of service quality, price, brand differentiation and trust and credibility. 5.3 Implications of the study 5.3.1 Theoretical implications The aim of the current study is to test a general model of customer-based brand equity into the banking service perspective. The findings suggest that the theoretical model is not fully supported. However, the modified model can be used as a point of departure for those who intend to study the CBBE in the banking industry in Vietnam. As there is no specific model of CBBE for banking services in Vietnam so far, this model is the first that provides a clear image of the dimensions that contribute to the brand equity in banking service. Secondly, this study contributes to the marketing literature a measurement scale as a useful instrument to measure the brand equity in banking service. The advantage of this instrument is that it can be used flexibly. For example, most of the observed variables presented in this study might also be useful for those who would follow Aaker’s approach to measure brand equity of banking service in an emerging economy like Vietnam. 62 5.3.2 Practical implications This study provides an insight into brand equity in banking industry. And thus, it can furnish bank managers a structured approach to formulate their branding strategies. The weight of the relationship between each of the brand equity dimensions or that of the sub components and the loyalty formation helps them to prioritize and allocate limited resources across brand equity dimensions/components to reach their objectives in a most efficient way. This is consistent with a study of banking system in New Zealand conducted by Macpherson Publishing (1999) whose argument is “banks need to understand what drives satisfaction and loyalty, and where there is greatest opportunity for improvement”. For example, maybe the bank management would rather maintain a reasonable price level while increase the service quality (affectivity, employee competence) to achieve more customer loyalty than merely use a price cut- down or promotion campaign. The modified CBBE model can be also used as a guideline for customer relationship management in banking service. By better understanding the contributions of brand equity components to the customer attitude towards the brand, bank managers might set up criteria to classify customers into different groups, for instance “price sensitive” group or “rationally-based” group and “emotionally-based” group. Then the bank can have different policy for each group. At the beginning of this study it was expected that the rational perspective (in terms of low price) would be most important for the banking industry. But interestingly the findings of this study do not support this view. Even though price competitiveness dominates the customer rational evaluation and is also involved in the emotional evaluation, the emotional evaluation finally contributes a larger proportion to the customer loyalty. On the one hand, it positively impacts on the rational perceptions, i.e. the more the customer’s mentally prefer the brand, the higher they perceive the brand value and the greater their satisfaction with the brand. On the other hand, emotional 63 perceptions play a larger role in forming customer loyalty to the brand. Understanding the way that customer loyalty is formed, bank managers might need to inspire emotions in the customer’s mind by offering superior service performance, differentiating the brand from competitors by providing customers with advantage that other banks would find hard to copy, generating trust from the target audience with consistent service quality and never communicating a value or service that the bank can not deliver. 5.4 Limitations and recommendations for further research Like any other research, this study has many limitations. The first one is in the sampling. Samples were selected by the convenience method. This is the least reliable form of non-probability sampling. Respondents were bank customers who are currently in transaction with the selected banks. Many of them are very familiar with the bank therefore they might over-rate the bank. In addition, the sample consists of individual customers only. This may not fully reflect all aspects of customer perception about bank operations, as others, for example business customers, may have very different views. Second, only two brands were selected in Can Tho city. Even though the banking industry is a very systematical industry (i.e. the consistence within a system nationwide is very high), this study needs to be repeated elsewhere, especially in bigger cities like Ho Chi Minh or Hanoi, and with more bank brands involved. Another limitation of the study is the lack of brand awareness in the model. Though brand awareness was not found significant in the model of CBBE in the financial service industry (Taylor et al, 2007) or in the hotel industry (Kayaman and Arasli, 2007), brand awareness is a critical dimension for brand equity (a key task of brand management is to get the brand in the target consumer’s consideration set) (Kayaman and Arasli, 2007). Therefore, it is suggested that brand awareness be 64 included as a parameter in an extended model of customer-based bank equity for banking services. Finally, readers are advised to interpret these research results with caution. As pointed out in chapter 4, the goodness of fit of the regression models were all acceptable but not so high. 65 List of References Aaker, D. A. (1996a). Building Strong Brand. New York: Free Press. Aaker, D. A. (1996b). “Measuring brand equity across products and markets”. California Management Re view, Spring 38, 3 Berry L.L. (2000), ”Cultivating Service Brand Equity”, Journal of the Academy of Marketing Science, volume 28, No. 1, 128-137 Chernatony, L.D and Cottam, S. (2006), “Why are all financial brands not great?”, Journal of product and brand management, February, 88-97 Colgate, M. & Norris, M. (2000). “Why customers leave or decide not to leave their banks”, Business Review , Volume 2, No. 2 , University Of Auckland. 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Kotler, P. & Pfoertsch, W. (2007), B2B Brand Management, Springer, Berlin. Kotler, P. and Keller, K. (2006), Marketing Management 12th Ed, Prentice Hall Krishnan, B.C. and Hartline, M.D. (2001), “ Brand Equity: Is It More Important in Service?”, Journal of service marketing. Vol.15, 328-342 Lam, R.; Lo, H.P. and Burton, S. (2005), Investigating The Drivers Of SMEs’ Banking Loyalty In Hong Kong, ANZMAC Conference: Consumer Behaviour. Leiser M. (2004), Understanding brand’s value: advancing brand equity tracking to brand equity management, Handbook of Business Strategy, Vol.5 No. 1, 217-221, MCB UP Limited. Martensen A. & Grønholdt L., (2004), “Building Brand Equity: A Customer-Based Modelling Approach”, Journal of Management Systems, Vol.16, No. 3 Myers, C.A. 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( 2005), “Understanding (customer- based) brand equity in financial services”, Journal of Services Marketing, 21/4, 241–252 Zeithaml, V.A., “Consumer Perceptions of Price, Quality, And Value: A Means-end Model and Synthesis of Evidence”, Journal of Marketing, Jul, Vol.52/3, 2-22 68 Appendix 1 – Questionnaire (Vietnamese version) Xin kính chaøo quí vò Xin chaân thaønh caûm ôn quí vò ñaõ nhaän lôøi tham traû lôøi phoûng vaán. Baûng caâu hoûi naøy chæ taäp trung tìm hieåu quí vò nghó gì veà thöông hieäu ngaân haøng [X] vaø moái quan heä giöõa quí vò vaø thöông hieäu naøy. Do vaäy, khoâng coù caâu traû lôøi ñuùng hay sai maø moïi thoâng tin ñöôïc cung caáp bôûi quí vò ñeàu raát coù giaù trò ñoái vôùi nghieân cöùu cuûa toâi. Raát mong quí vò traû lôøi ÑAÀY ÑUÛ caùc caâu hoûi vaø ôû möùc ñoä chính xaùc cao nhaát coù theå. Moïi thoâng tin caù nhaân cuûa quí vò ñeàu ñöôïc giöõ kín. Thoâng tin do quí vò cung caáp seõ chæ ñöôïc trình baøy trong baùo caùo döôùi daïng toång hôïp. Khoâng coù baát kyø moät baûng caâu hoûi naøo ñöôïc coâng boá rieâng leû ra ngoaøi. Traân troïng kính chaøo I. Thoâng tin chung (phaàn naøy do phoûng vaán vieân ghi) Teân ngaân haøng: ………………… ……..….. ……….(döôùi ñaây kyù hieäu laø [X]) Teân phoûng vaán vieân: ................................................... Ngaøy phoûng vaán: ........./....../2009 Mã số : ………………………………………………………………………………… II. Caâu hoûi veà giaù trò thöông hieäu ngaân haøng Xin vui loøng cho bieát möùc ñoä ñoàng yù hoaëc khoâng ñoàng yù cuûa quí vò ñoái vôùi caùc phaùt bieåu döôùi ñaây baèng caùch khoanh troøn vaøo MOÄT con soá theo qui öôùc sau: 1 = raát khoâng ñoàng yù 2 = khoâng ñoàng yù 3 = trung laäp 4 = ñoàng yù 5 = raát ñoàng yù Phaùt bieåu 1. Trang thiết bị của ngaân haøng [X] rất hiện đại 1 2 3 4 5 2. Trang phuïc cuûa nhaân vieân ngaân haøng [X] raát ñeïp vaø lòch söï. 1 2 3 4 5 3. Vò trí cuûa ngaân haøng [X] raát thuaän tieän ñoái vôùi toâi. 1 2 3 4 5 4. Cô sôû vaät chaát cuûa ngaân haøng [X] troâng raát haáp daãn 1 2 3 4 5 5. Ngaân haøng [X] thöïc hieän dòch vuï ñuùng thôøi ñieåm nhö ñaõ höùa 1 2 3 4 5 6. Khi toâi gaëp vaán ñeà, ngaân haøng [X] theå hieän söï quan taâm chaân thaønh trong giaûi quyeát vaán ñeà. 1 2 3 4 5 7. Nhaân vieân cuûa ngaân haøng [X] phuïc vuï toâi nhanh choùng, ñuùng haïn. 1 2 3 4 5 8. Nhaân vieân ngaân haøng [X] luoân luoân saün loøng giuùp ñôõ toâi. 1 2 3 4 5 9. Toâi caûm thaáy an toaøn khi giao dòch vôùi ngaân haøng [X]. 1 2 3 4 5 10. Nhaân vieân cuûa ngaân haøng [X] bao giôø cuõng toû ra lòch söï, nhaõ nhaën. 1 2 3 4 5 11. Nhaân vieân cuûa ngaân haøng [X] hieåu raát kyõ veà saûn phaåm vaø dòch vuï cuûa ngaân 1 2 3 4 5 69 haøng. 12. Nhaân vieân cuûa ngaân haøng [X] coù kieán thöùc ñeå traû lôøi caùc caâu hoûi cuûa toâi. 1 2 3 4 5 13. Nhaân vieân ngaân haøng [X] hieåu ñöôïc nhu caàu cuûa toâi vaø saûn phaåm, dòch vuï naøo coù theå ñaùp öùng ñöôïc nhöõng nhu caàu ñoù 1 2 3 4 5 14. Ngaân haøng [X] theå hieän söï quan taâm ñeán caù nhaân toâi 1 2 3 4 5 15. Laõi suaát cuûa ngaân haøng [X] raát caïnh tranh 1 2 3 4 5 16. Phí dòch vuï cuûa ngaân haøng [X] raát caïnh tranh 1 2 3 4 5 17. Ngaân haøng [X] cho toâi ñöôïc thöông löôïng giaù 1 2 3 4 5 18. Möùc giaù cuûa ngaân haøng [X] ñöa ra cho toâi raát hôïp lyù 1 2 3 4 5 19. Ngaân haøng [X] mang laïi höùa heïn raát coù yù nghóa 1 2 3 4 5 20. Ngaân haøng [X] thöïc hieän ñuùng nhöõng gì maø [X] höùa heïn mang laïi cho toâi. 1 2 3 4 5 21. Ngaân haøng [X] taïo ñöôïc nhöõng lieân töôûng vaø aán töôïng toát 1 2 3 4 5 22. Ngaân haøng [X] khaùc bieät hôn caùc ngaân haøng khaùc (theo nghĩa tích cực) 1 2 3 4 5 23. Ngaân haøng [X] coù nhöõng neùt ñoäc ñaùo khi so saùnh vôùi caùc ngaân haøng khaùc 1 2 3 4 5 24. Ngaân haøng [X] taïo ñöôïc nhöõng thuaän lôïi cho khaùch haøng maø caùc ngaân haøng khaùc khoâng coù ñöôïc 1 2 3 4 5 25. Ngaân haøng [X] giao thieäp moät caùch trung thöïc vaø côûi môû 1 2 3 4 5 26. Ngaân haøng [X] raát ñaùng tin töôûng vaø tin caäy 1 2 3 4 5 27. Toâi raát tin töôûng vaøo ngaân haøng [X] 1 2 3 4 5 28. Ngaân haøng [X] mang laïi cho toâi giaù trò xöùng ñaùng ñoàng tieàn 1 2 3 4 5 29. Ngaân haøng [X] ñaùp öùng raát toát nhöõng kyø voïng (mong muoán) cuûa toâi? 1 2 3 4 5 30. Nhìn chung, toâi raát haøi loøng ñoái vôùi ngaân haøng [X] 1 2 3 4 5 31. Khi nghó veà ngaân haøng [X], toâi coù caûm giaùc raát aám cuùng 1 2 3 4 5 32. Toâi caûm thấy ngaân haøng [X] rất coù yù nghóa ñoái vôùi toâi 1 2 3 4 5 33. Toâi thaáy haõnh dieän khi laø khaùch haøng cuûa ngaân haøng [X] 1 2 3 4 5 34. Laàn tôùi khi coù yù ñònh giao dòch vôùi moät ngaân haøng, toâi seõ laïi giao dòch vôùi ngaân haøng [X] 1 2 3 4 5 35. Toâi seõ giôùi thieäu ngaân haøng [X] vôùi nhöõng ngöôøi khaùc 1 2 3 4 5 36. Nhìn chung, toâi thaáy ngaân haøng [X] raát haáp daãn so vôùi caùc ngaân haøng khaùc 1 2 3 4 5 37. Toâi raát quan taâm tôùi ngaân haøng [X] 1 2 3 4 5 38. Vieäc tieáp tuïc duy trì moái quan heä vôùi ngaân haøng [X] trong töông lai laø raát quan troïng ñoái vôùi toâi 1 2 3 4 5 70 III. Thoâng tin caù nhaân 1. Xin oâng (baø) vui loøng cho bieát teân: ………………………………………………………… Soá ÑT: …………………………. Ñòa chæ (hoaëc nôi coâng taùc): ………..………… ………. ……………………………………………………………………….. (neáu coù theå cung caáp) Giôùi tính: Nam
- 1 Nöõ
- 2 Tuoåi: Döôùi 30 tuoåi
- 1 Töø 31 – 45
- 2 Töø 46 – 60
- 3 Treân 60 tuoåi
- 4 4. Xin vui loøng cho bieát thôøi gian oâng(baø) ñaõ giao dòch vôùi ngaân haøng [X] 1. Döôùi 3 thaùng
- 1 2. Töø 3 thaùng ñeán moät naêm
- 2 3. Treân moät naêm
- 3 5. Xin vui loøng cho bieát möùc ñoä thöôøng xuyeân oâng (baø) giao dòch vôùi ngaân haøng [X] 1. Raát thöôøng xuyeân ( ít nhaát 5 laàn/tuaàn)
- 1 2. Thöôøng xuyeân (1- 3 laàn/tuaàn)
- 2 3. Khaù thöôøng xuyeân (1-2 laàn/thaùng)
- 3 4. Vaõng lai (ngaãu nhieân hoaëc chæ khi caàn thieát)
- 4 Xin caûm ôn quí vò ñaõ daønh thôøi gian hoaøn taát baûng caâu hoûi naøy! 71 Appendix 2 – Observed variables Service quality 1. Bank [X] has up to date equipments 2. Bank [X]’s physical facilities are visually appealing. 3. I find it very convenient with the location of bank [X] 4. Bank [X]’s employees are well dressed and appear neat. 5. Bank [X] provides its services at the time it promises to do so 6. When I have problems, bank [X] is sympathetic in solving them 7. I receive prompt service from bank [X]’s employees 8. Bank [X]’s employees are always willing to help me. 9. I feel safe in my transaction with bank [X] 10. Bank [X]s‘ employees are polite 11. Bank [X]’s employees know the bank’s product and service very well 12. Bank [X]’s employees have necessary knowledge to answer my questions 13. Bank [X]’s employees know what my needs are and how the bank’s products can satisfy them 14. Bank [X]’s employees give me personal attention Price 15. Interest rates of bank [X] are very competitive 16. Service fees of bank [X] are very competitive 17. Bank [X] offers me price deals 18. Bank [X] offers me very reasonable price Brand promise 19. Bank [X] creates meaningful promises for me 20. Bank [X] lives up to its promises 21. Bank [X] creates positive associations and images Differentiation 22. Bank [X] differs from other banks in a positive way 23. Bank [X] is unique compared to other banks 24. Bank [X] offers advantages that other banks can not Trust and credibility 25. Bank [X] communicates openly and honestly 26. Bank [X] is trustworthy and credible 27. I have great faith in Bank [X] Rational evaluation 28. Bank [X] provides good value for money 29. Bank [X] greatly meets expectations. 30. Overall, I am very satisfied with bank [X] Emotional evaluation 31. When thinking of bank [X], I get a positive and warm feeling 32. Bank [X] means a lot to me 72 33. I am proud to be a customer of bank[X] Customer-brand relationships 34. The next time I am going to transact with a bank, I am going to bank [X] again 35. I will recommend bank [X] to others 36. Overall, I find bank [X] more attractive than other banks? 37. I am very interested in bank [X] 38. It is important for me to maintain the relationship with bank [X] in the future 73 Appendix 3 - Descriptive Statistics of variables Observed variables N Minimum Maximum Mean Std. Deviation Skewness Kurtosis Statistic Statistic Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error SQ1 295 1.00 5.00 3.8407 .75483 -.587 .142 .886 .283 SQ2 295 1.00 5.00 4.1492 .76806 -.987 .142 1.704 .283 SQ3 295 1.00 5.00 4.0034 .88255 -.634 .142 .143 .283 SQ4 295 1.0 5.0 3.617 .8283 -.197 .142 .060 .283 SQ5 295 1.00 5.00 4.0407 .67389 -.653 .142 1.584 .283 SQ6 295 1.00 5.00 4.0237 .74422 -.537 .142 .507 .283 SQ7 295 1.00 5.00 4.1729 .69542 -.797 .142 1.591 .283 SQ8 295 1.00 5.00 4.1627 .72419 -.906 .142 1.648 .283 SQ9 295 1.00 5.00 4.1932 .78243 -1.040 .142 1.848 .283 SQ10 295 1.00 5.00 4.1966 .77063 -.892 .142 1.210 .283 SQ11 295 1.00 5.00 4.0305 .68195 -.492 .142 .979 .283 SQ12 295 1.00 5.00 3.9966 .71189 -.337 .142 .274 .283 SQ13 295 1.00 5.00 3.9186 .73782 -.535 .142 .943 .283 SQ14 295 1.00 5.00 3.7492 .80694 -.178 .142 -.270 .283 PC1 295 1.00 5.00 3.0814 1.05953 -.267 .142 -.615 .283 PC2 295 1.00 5.00 3.2169 1.08502 -.312 .142 -.500 .283 PC3 295 1.00 5.00 2.9051 1.12386 -.232 .142 -.799 .283 PC4 295 1.00 5.00 3.3119 .96417 -.362 .142 -.019 .283 PR1 295 2.00 5.00 3.6576 .66604 -.107 .142 -.127 .283 PR2 295 1.00 5.00 3.8712 .68289 -.348 .142 .666 .283 PR3 295 1.00 5.00 3.9559 .65576 -.392 .142 1.021 .283 DF1 295 1.00 5.00 3.8712 .73101 -.164 .142 -.056 .283 DF2 295 1.00 5.00 3.8305 .77706 -.177 .142 -.225 .283 DF3 295 1.00 5.00 3.7864 .81555 -.270 .142 -.031 .283 TR1 295 1.00 5.00 3.8441 .79288 -.786 .142 1.374 .283 TR2 295 2.00 5.00 4.2136 .69875 -.500 .142 -.181 .283 74 TR3 295 1.00 5.00 4.1661 .71157 -.651 .142 .837 .283 RE1 295 2.00 5.00 3.7186 .72292 -.170 .142 -.170 .283 RE2 295 1.00 5.00 3.6373 .74731 -.429 .142 .224 .283 RE3 295 1.00 5.00 3.7695 .78750 -.367 .142 .064 .283 EE1 295 2.00 5.00 3.6136 .76475 .003 .142 -.393 .283 EE2 295 2.00 5.00 3.7661 .74883 -.029 .142 -.484 .283 EE3 295 2.00 5.00 3.8068 .73305 .006 .142 -.557 .283 RL1 295 2.00 5.00 4.0373 .66647 -.181 .142 -.282 .283 RL2 295 1.00 5.00 3.8441 .81405 -.735 .142 .900 .283 RL3 295 1.00 5.00 3.8000 .77635 -.207 .142 -.132 .283 RL4 295 2.00 5.00 3.7831 .72870 -.172 .142 -.218 .283 RL5 295 2.00 5.00 3.8915 .75261 -.204 .142 -.400 .283