Abstract
There is a great deal of evidence that method bias is really sure influences item validities, measurement error, correlation and covariance between latent constructs and thus leading the researchers to erroneous conclusion due to inflation or deflation during hypothesis testing. To remedy this, the study provides a guideline to minimize the method bias in the context of structural equation modeling employing the covariance method (CB-SEM) using medical tourism model. A practical approach is illustrated for the identification of method bias based on the new construct namely common latent factor. Using this latent construct, we managed to identify which item has potential to permeate more variance from common latent factor. Nevertheless, we figure out that the method bias is do not exist in our developed model. Therefore, this measurement model is appropriate for structural model in order to achieve the research hypotheses. We hope that this discussion will help the researchers anticipate which items are likely exposed on method bias before proceed to advance modeling.
Highlights
There has been a germination of Structural Equation Modeling (SEM) in information system [1], entrepreneurship [2], tourism [3, 4, 5], social sciences [6,7], marketing [8, 9], management [10,11,12] and other fields [13, 14, 15]
There are two families of SEM have been penetrated in various areas such as Covariance or Common factor based SEM (CB-SEM) and Variance or Partial Least Square based SEM (PLS-SEM) but both methods are suggested should be applied in different situations whether in the confirmatory or exploratory research. [9] and [15] suggested that CB-SEM or traditional SEM is suitable for confirmatory testing or theory driven, while PLS-SEM is preferable for exploratory research
We provide a discussion regarding the common method bias with traditional SEM using medical tourism model
Summary
There has been a germination of Structural Equation Modeling (SEM) in information system [1], entrepreneurship [2], tourism [3, 4, 5], social sciences [6,7], marketing [8, 9], management [10,11,12] and other fields [13, 14, 15]. There are two families of SEM have been penetrated in various areas such as Covariance or Common factor based SEM (CB-SEM) and Variance or Partial Least Square based SEM (PLS-SEM) but both methods are suggested should be applied in different situations whether in the confirmatory or exploratory research. [9] and [15] suggested that CB-SEM or traditional SEM is suitable for confirmatory testing or theory driven, while PLS-SEM is preferable for exploratory research.
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