Figure 5.2B: Congeneric model for v-symbolic characteristics
The congeneric model for symbolic characteristics recorded Chi-Square =9.390, Degrees of Freedom = 8, Probability level = .310, RMSEA = .029, RMR = .033, AGFI = .956, CFI
= .998.
169 V-Physical Characteristics
Figure 5.3B: Congeneric model for v-physical characteristics
The congeneric model for physical characteristics recorded Chi-Square =12.571, Degrees of Freedom =11, Probability level = .322, RMSEA = .026, RMR = .029, AGFI = .954, CFI
= .998).
V- Beneficial Characteristics
Figure 5.4B: Congeneric model for v-beneficial characteristics
The congeneric model for beneficial characteristics recorded Chi-Square =3.203, Degrees of Freedom = 2, Probability level = .202, RMSEA = .054, RMR = .018, AGFI = .954, CFI
= .997.
171 Measurement Model
Based on the congeneric models for the three dimensions of the Vavilovian mimicry, it is shown by the results (Figure 5.2B – 5.4B) to achieve acceptable measures (Hu and Bentler, 1999; Holmes-Smith and Rowe, 1994). These three factors are then being used in the measurement model to ensure that the three dimensions of the scale are of acceptable measures.
Figure 5.5B: Measurement model for Vavilovian mimicry
In the next step of the measurement procedure, the three-factor structure was testing using CFA (Kelloway, 1998; Walsh and Mitchell, 2007). Based on the measurement model (Figure 5.5B), model identification was achieved with the 15 items and the model fit statistics are found to be of acceptable range and can be used for further analysis (Hu and Bentler, 1999) (Chi-Square =104.183, Degrees of Freedom = 83, Probability level = .058, RMSEA = .035,
RMR = .063, AGFI = .914, CFI = .989). The remaining items continue to fall under the definition of the Vavilovian mimicry construct which is intended to measure (content/face validity).
Using CFA, the 19 items (as shown in the congeneric models in Figure 5.2B – 5.4B) from post EFA has been refined to 15 remaining items. The other four items were removed due to low regression weights that were below the acceptable standards (Hu and Bentler, 1999).
These 15 items have indicated a good model fit within three dimensions.
Concluding comments for Study Six
Through CFA, the initial 23-items in the Vavilovian scale have been refined to 15 remaining items. These items are shown to have acceptable loadings. From this point on, further tests on reliability and validity can be conducted.
173 STUDY SEVEN: VALIDATION OF VAVILOVIAN MIMICRY SCALE
This step is conducted to establish the scale’s criterion validity (predictive) and construct/trait validity (nomological, discriminant and convergent). Studies by Campbell and Fiske (1959), Churchill (1979), and Walsh and Mitchell (2005) were followed as guides for this stage. For this to be achieved, new survey forms and collection of new data was required. This is discussed in the following section.
Sample
A new survey was designed by including the 15-item Vavilovian mimicry scale items and the measures to be used to test for predictive, nomological, discriminant and convergent validity.
The survey was pre-tested on respondents that are similar to the intended sample used for the main data collection. A focus group like exercise was conducted to collect feedback
regarding the possible issues with the readability, grammatical, comprehension of instructions, and so on. The pre-test showed that the new survey is fit to be used.
The data collection is conducted using a new group of respondents who do not have prior exposure to any of the mimicry scale development procedures. After removing any incomplete or inappropriately completed data, 104 useable responses remained.
Criterion (predictive) and Construct (nomological) Validity
Trait and nomological validity are both useful distinctions for the exploration of construct validity (Campbell, 1960). Eastman et al. (1999, p. 44) stated that “criterion validity is the extent to which a measure is related to actual behaviours of other real life outcomes (Anastasi, 1986; Nunnally, 1978)”. This form of validity relates to the ability of a scale “to predict something that should theoretically be related or ability to predict” (Oh, 2005, p. 301). In addition, Churchill (1979) proposes that as a final step to scale development, it is important to show that the measure behaves as expected to other constructs. Hence, criterion validity attempts to correctly predict the criterion measure. Perception of luxury and product evaluation of mimic brand is included to test for the criterion validity of the presence of Wicklerian-Eisnerian mimicry. Previous studies have demonstrated product similarities are expected to have a significant effect on product evaluation (Lefkoff-Hagius and Mason, 1993;
van Horen and Pieters, 2012). However, according to DeVellis (2003, p. 52) even if the correlation between a predictor measure and a criterion is high, the score obtained on the predictor may not serve as the most accurate estimate of the criterion.
For Vavilovian mimicry, the perception of luxury and product evaluation both recorded positive Cronbach’s alpha scores (α = .897 and α = .820 respectively). The criterion (predictive) validity of the Vavilovian scale was supported. Those who perceive a high presence of Vavilovian mimicry (measured by the scale developed for this study) had a significantly higher mean score of perception of luxury towards mimic brand (M = 4.9856, SD = .98561) than those who perceived a lower presence of Vavilovian mimicry (M = 3.7688, SD = 1.40332) (t = -5.557, p = .000). In addition, those who perceived a high presence of Vavilovian mimicry had a significantly higher mean score of product evaluation of mimic brand (M = 4.8243, SD = 1.16609) than those who perceived a lower presence of Vavilovian mimicry (M = 4.2266, SD = 1.2790) (t = -2.378, p = .022). This result is in line with van Horen and Pieters’ (2012a) results that suggested that mimics that are similar to the model brand in image and other non-physical attributes can lead to better evaluation of the mimic.
Therefore, this finding is in accordance to the definition of Vavilovian mimicry.
In conjunction with establishing criterion validity, the use of the consumers’ evaluation scale should also be used to establish “nomological validity”. Initially proposed by Cronbach and Meehl (1955), nomological validity serves as a form of construct validity that is lawlike and the examination of the constructs and measures is conducted using formal hypotheses based on theory (Peter, 1981; Cadogan et al., 1999). When an instrument is believed to have nomological validity, it will demonstrate relationship to another construct to which it is theoretically related (Churchill, 1995). The link between nomological validity and criterion (predictive) validity lies in the explanation that “the degree which the construct as measured by a set of indicators predicts other constructs that past theoretical or empirical work says it should predict” (Droge, 1997). As proposed by previous studies (e.g. van Horen and Pieters, 2012b) the presence of mimicry (similarity between products) should lead to attitude and evaluation formation. Therefore, to test for the nomological validity of the presence of mimicry scale, it is anticipated that there should be a relationship between presence of mimicry, perception of luxury and product evaluation as dictated in the literature (Hagtvedt and Patrick, 2008). This would provide evidence that the scale and the related constructs in the study should behave as what theory dictates (Cadogan et al., 1999).
Past studies have used correlations to test for the relationship between constructs in validation of scales (Heeler and Ray, 1972). In addition, when examining the nomological validity of a measure, it is paramount for the researcher to also concentrate on a pattern of the results
175 between the criterion and predictors rather than just the significance of the results (Cronbach and Meehl, 1955; Netemeyer et al., 1991). Therefore, while nomological validity is achieved in this study, further research that identify the patterns would need to be conducted in order to robustly justify the scales as having nomological validity. At this stage, with the support of previous results, the scales continue in their line of positive results towards validation.
Based on the results in Table 5.6B, it is shown that there are significant correlations between the presence of mimicry scale and other constructs which are theoretically related. Therefore it can be suggested that the presence of mimicry scale predicts the relationships as what past studies have documented. Although there are no direct studies that examine the presence of Vavilovian mimicry, it can be postulated that the scale has the “ability to predict” what past studies in imitation and product similarity has postulated.
Table 5.6B: Results for criterion and construct validity (Vavilovian mimicry) Pearson
Correlations Presence of
Mimicry Perception of
Luxury Product
Evaluation
Presence of Mimicry 1
Perception of Luxury .555** 1
Product Evaluation .330** .508** 1
**p ≤ 0.01
Trait Validity (discriminant and convergent)
Based on the fundamental principles in science, a particular construct or trait should be measurable by more than one method (Churchill, 1979). Furthermore, Peter (1981) has stated that in addition to construct validity, trait validity provides necessary information for
accepting construct validity. Distinctive to construct validity, trait validity relates to the empirical relationship between measures of different constructs (Peter, 1981). Trait validity can be conducted using discriminant and convergent validity tests (Campbell and Fiske, 1959). The intention to conduct discriminant and convergent validity tests is to primarily examine “the amount of systematic variance in a measure’s scores and determine whether the systematic variance results in high correlations with other measures of the construct and low correlations with constructs of other phenomena with which the construct should not be associated” (Peter, 1981, p. 135). Convergent validity relates to the degree of agreement in measures of the same or similar construct, whereas discriminant relates to the degree which
measures of conceptually different constructs differ (Campbell and Fiske, 1959; Churchill, 1979; Oh, 2005).
According to Ping (2004), discriminant validity has been typically established in past studies as using correlations. It is determined by demonstrating that a measure does not highly correlate with another measure from which it is different (Campbell, 1960). It is suggested that correlations with other measures below 0.7 is deemed as acceptable and can serve as evidence of measuring distinctness and discriminant validity (Ping, 2004). On the other hand, convergent validity is “based on the correlation between responses obtained by maximally different methods of measuring the same construct” (Peter, 1981). Following Ping (2004) and Walsh and Mitchell’s (2005) as guidelines for the validity tests, for discriminant validity the Brand Familiarity scale is used. The Brand Familiarity scale is chosen because it is believed that theoretically, the presence of mimicry scale should not be related to Brand Familiarity (Walsh and Mitchell, 2005) as the items that the scale consists of are “I am familiar…”, “I am knowledgeable about…”. The three-item scale was reliable (α = .938). The Brand Familiarity scale is from Kent and Allen (1994).
For convergent validity, the use of Sproles and Kendall’s (1986) Overload-Confusion scale was used and the scale is found to be reliable (α = .861). The Overload-Confusion scale is selected based on the justification that when consumers are faced with brands that are closely similar and with a great number of brands to choose from, they become overloaded with information (Walsh and Mitchell, 2005). As a consumer, one will begin to simplify the information they can process about the brands (Sproles and Kendall, 1986). According to Walsh and Mitchell (2005), when there are a great number of brands in a product category to choose from, it is often a sign of brand copying and in this case testing for the presence of mimicry scale further emphasizes the presence of brands with similar features. Therefore, based on this premise, it is postulated that information overload and presence of mimicry likely to be positively correlated.
In order to show discriminant validity, a correlations test is conducted between the Brand Familiarity scale and the presence of mimicry scale. As previously discussed, it is postulated that Brand Familiarity should not theoretically relate to the presence of mimicry scale since brand familiarity discusses the level of knowledge a consumer has (Kim and Chung, 2012), as opposed to whether there are similar attributes between two products (presence of mimicry
177 scale). The results in Table 5.7B shows that the presence of mimicry and the Brand
Familiarity scale has a low but significant correlation, which shows some discriminant validity.
In order to demonstrate convergent validity, a correlations test is conducted between the Confusion-Overload and the presence of mimicry scale. The bivariate correlation (Pearson) between the two scales was .519 and is statistically significant at .00, this suggests a degree of convergent validity.
Table 5.7B: Results for convergent and discriminant validity (Vavilovain mimicry) Pearson Correlations Presence of
Mimicry
Confusion Overload
Brand Familiarity
Presence of Mimicry 1
Confusion Overload .519** 1
Brand Familiarity .177* .063 1
**p ≤ 0.01, *p ≤ 0.05
Concluding comments for Study Seven
From this study, we can observe that the proposed Vavilovian mimicry scale performed successfully in the predictive, nomological, convergent and discriminant validity tests.
STUDY EIGHT: GENERALIABILITY OF VAVILOVIAN MIMICRY SCALE