The influence of bootstrapping in testing a model of motivation and visit intention of generation Z to the attractive building architecture destinations

This research aims to identify the impact of e-WOM on the enthusiasm of generation Z to travel in architectural tourist attractions using the theory of reasoned action. The four variables used in this analysis are e-WOM, attitude, subjective norm, and visit intention. Structural equation modeling (SEM) with Amos software is used to assess the impact of independent variables on the dependent variable. One of the prerequisites for using SEM is that the data is normally distributed; however, the data in the analysis was not normally distributed, so the bootstrapping process was used to solve this. This article focused on explaining the data processing process in SEM to concern the data testing and the effect of bootstrapping in the model forming and not discuss the model result, only compare the result before and after bootstrapping process. The most influential variable in each construct is the same between before and after bootstrapping. The goodness of fit result before bootstrapping in all categories is poor fit but after bootstrapping only one category is poor fit and others are a good fit.

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