184.108.40.206 The Discriminant Validity Analysis In order to ensure further, it is important to establish construct validity and the discriminant validity of outer model. Hence, prior to hypotheses testing, discriminant validity was ensured. Discriminant validity refers to the level to which items can differentiate among different constructs in which it shows that the items of different constructs are not overlapping. Additionally, discriminant validity of measures share variance between each individual construct and hence, it should be higher than the variance shared among specific constructs (Compeau, Higgins, & Huff, 1999). In this study, the discriminant validity of measures was established through Fornell and Larcker (1981) method, where the square root of AVE for the entire constructs was replaced at the diagonal elements of the correlation matrix as demonstrated in Table 4.6 Seventeen items were dropped to enhance the result and those items are no more in this study. All the other values are less than 0.90 and hence, the outer model‘s discriminant validity was established as suggested by Hair, Black, Babin, and Anderson (2010). The above results of the outer model‘s construct validity ensure that it is appropriate to test the proposed hypotheses. 220.127.116.11 The Construct Validity The construct validity and content validity is defined as the level to which the proposed items suitably measure the concept of the constructs that they are designed to measure (Hair, Black, Babin, & Anderson, 2010). Stated differently, items measuring a construct should load higher on their respective constructs. Hence, items are considered through a
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- Summer '17