far more important as drivers of brand equity than awareness related dimen

Far more important as drivers of brand equity than

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far more important as drivers of brand equity than awareness-related dimen- sions (De Chernatony, 2001 ; Lovelock, 1991 ; Mourad et al. 2010 ). IIMI and IIMK; and MDI and IIFT are perceived very similar on independent variables. Though SPJIMR scores high on familiarity, XLRI is the preferred brand on other variables. NMIMS and NITIE are less preferred in this set of data. Figure 2. Perception map of business school on select nine attributes. Journal of Marketing For Higher Education 191 Downloaded by [Sapna Popli] at 08:08 20 December 2013
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Relationship between variables Consistency of the data is judged using aggregate pair-wise correlations among the seven variables, M1 through M7, for all the schools. The data show that all the measures are highly congruent with each other at 99% confidence levels. All variables show congruency at 95% confidence level with the minimum being 0.753 (for VFM and willingness to pay a premium) and the highest being 0.975 (for overall brand assessment and brand preference). As suggested by Netemeyer et al. ( 2004 ), favorable perceived quality, brand preference and per- ceived VFM are congruent with a greater willingness to pay the price premium for a brand and is also supported by Monroe in 1990 (as cited in Mourad et al., 2010 ). Dependent variable M5 (preference) is congruent with all independent variables (M1–M4) and also the two other dependent variables, M6 and M7. The choice intention (M7) is highly congruent with all input variables; whereas the willingness to pay a premium is congruent with overall brand assessment and preference at 99% confidence limits. Recent evidence supports that differentiators for the brand affect both the preferences and willingness to pay a higher price for the brand (Carpenter, Glazer, & Nakamoto, 1994 ; Kalra & Goodstein, 1998 ). Aggregate correlation between the seven measures of brand equity used for the suggested framework is estimated and shown in Table 4 . Individual level stepwise regression analysis is separately performed with M5 (preference for business schools), M6 (willingness to pay a fee premium) Figure 3. Positioning map for independent variables M1–M4. 192 A. Aggarwal Sharma et al. Downloaded by [Sapna Popli] at 08:08 20 December 2013
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and M7 (choice intention) as dependent variables using M1–M4 as the inde- pendent variables to study the relationship between them. For the aggregate per- ception, M2, each business school attribute score is considered against the consolidated score to identify the importance of each attribute in making the final choice. The attributes and variables affecting the dependent variables M5, M6 and M7 are presented in Table 5 . The figure in brackets against each variable shows the beta coefficient for the same. The data are significant at 95% confidence limits. It depicts the prime influencers among independent vari- ables on behavioral indicators (dependent variables).
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