The basic idea of exploratory factor analysis is the following. For a given set of observed response variables one wants to find a set of latent factors, fewer in number than the observed variables. These factors are supposed to account for the intercorrelations of the response variables in the sense that when the factors are partialed out from the observed variables, there should no longer rem...

The purpose of this research is to test the tourist’s perception in the choice of selection a destination under the perspective of Bangladeshi tourism environment. The survey instrument was employed by using convenience sampling procedure on 250 tourists from significant tourist’s destination places from Bangladesh. Exploratory factor analysis (EFA) followed by Confirmatory factor analysis (CFA...

The study focuses on designing a Multicultural Competence Scale in Helping-Profession Students. The aim was to create an assessment tool of multicultural competence in students of helping professions as such a tool has been non-existent so far in the Central Europe. The scale construction was inspired by the four following instruments: CBMCS, MAKSS, MSPCCS and IIMCS. Through content validation,...

Background: The rising market competition and demand for innovative need based products by customers have compelled the banking industry to look alternative cost-effective product services. integration of insurance with banks will contribute more economy. Purpose: Bancassurance has a tremendous acceptance growth across nation. It is know their customer perceived value over various bancassurance...

It is well-known that the classic exploratory factor analysis (EFA) of data with more observations than variables has several types of indeterminacy. We study the factor indeterminacy and show some new aspects of this problem by considering EFA as a specific data matrix decomposition. We adopt a new approach to the EFA estimation and achieve a new characterization of the factor indeterminacy pr...

Principal components analysis and factor analysis are common methods used to analyze groups of variables for the purpose of reducing them into subsets represented by latent constructs (Bartholomew, 1984; Grimm & Yarnold, 1995). Even though PCA shares some important characteristics with factor analytic methods such as exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), the ...