Purpose Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including hospitality management. Although for many researchers, SEM is equivalent to carrying out covariance-based SEM, recent research advocates the use of partial least...

Purpose – Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to...

Purpose – The purpose of this paper is to introduce the importance-performance map analysis (IPMA) and explain how to use it in the context of partial least squares structural equation modeling (PLS- SEM). Acase study, drawing on the IPMA module implemented in the SmartPLS 3 software,...

Uncovering unobserved heterogeneity is a requirement to obtain valid results when using structural equation modeling (SEM). Conventional segmentation methods usually fail in an SEM context because they account for the indicator data, but not for the latent variables and their relationships in...

Accounting for heterogeneity in tourism studies remains important to avoid parameter bias (e.g., Mazanec, 2000; Mazanec, Ring, Stangl, & Teichmann, 2010) when employing analysis techniques such as regression (e.g., Ye, Zhang, & Yuen, 2013), partial least squares structural equation modeling...

Purpose: This study aims to propose guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism...

Since its first introduction in the Schmalenbach Business Review, Hahn et al.'s (2002) finite mixture partial least squares (FIMIX-PLS) approach to response-based segmentation in variance-based structural equation modeling has received much attention from the marketing and management...

Mixture regression models are an important method for uncovering unobserved heterogeneity. A fundamental challenge in their application relates to the identification of the appropriate number of segments to retain from the data. Prior research has provided several simulation studies that compare...

This paper extends prior research on the reputation of nonprofit organizations (NPOs) by investigating the moderating role of socio-demographic characteristics in forming NPO reputation and reputation's effects on donating and volunteering behavior. The findings offer new insights into the role...