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Per DeVellis (1991), Cronbach`s alpha coefficient values below 0.60 are considered unacceptable, whereas between 0.65 and 0.70 are minimally acceptable, the author considers that between 0.70 and 0.80, Cronbach’s alpha values are considered as good and between 0.80 and 0.90 are considered as very good. Therefore, as it can be observed on Table 1, all dimensions of the credibility scale obtained a Cronbach`s alpha equal or greater than 0.870, which reveals a high level of internal consistency of the scales. It is also possible to observe that both constructs - credibility and purchase intention - revealed high values of Cronbach’s alpha: 0.869 for credibility and 0.898 for purchase intention. To conclude, all scales are considered as having very good reliability according to DeVills (1991). Finally, the column labelled “Cronbach`s alpha if item deleted” reflects the change in Cronbach’s alpha that would be seen if that particular item were deleted, in order to make that scale more reliable, which is not the case due to the present results. Appendix 5 summarizes each variable computed, including their respective means and Cronbach`s alpha to measure their reliability. 4.1.5 Principal component analysis (PCA) A principal component analysis (PCA) is performed with the purpose of assessing the dimensionality of the scales used and to verify if all factors are aggregated around the component they are supposed to measure. Before running the PCA, sample size is a concern. Comrey and Lee (1992) define the efficiency of samples according to their sample size, whereas a sample size of 100 people is considered poor, 200 is fair, 300 is good, 500 is very good and lastly, 1000 is considered to be excellent. Regarding the principal component analysis, Hair et al. (2005), recommend a sample size superior to 200 participants. In this case, it is possible to conclude that the sample used is adequate for factor analysis, since 285 respondents compose it. To get these variables as different from each other, a Varimax Rotation method was run as it helps to interpret the factors by putting each dimension primarily on one of the factors. The results demonstrated that with the presence of these 4 components/factors, 73% of the total variance is explained. Also, the initial number of factors is the same as 41PDF Image | HOW INFLUENCERS CREDIBILITY ON INSTAGRAM IS PERCEIVED BY CONSUMERS AND ITS IMPACT ON PURCHASE INTENTION
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