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In recent years, the use of structural equation modeling (SEM) has become widespread in tourism and hospitality research. Because there are two different approaches to SEM (i.e., covariance-based SEM and variance-based, partial least squares SEM), this brings challenges for researchers about which SEM to use and what to report in each SEM approach. Therefore, the purpose of this chapter is to discuss the differences between CB-SEM and PLS-SEM and to provide comprehensive guidelines for researchers on how to apply each SEM. Within this context, the authors first briefly summarize the fundamentals and advantages of using SEM. Then, the authors explain in detail the major issues that should be considered when selecting between CB-SEM and PLS-SEM. Finally, to ensure rigorous research practices, the authors provide step-by-step guidelines for the application of both CB-SEM and PLS-SEM.

Tourism research contains a large share of consumer behavior-orientated studies using multidimensional constructs (exogenous/endogenous). Accordingly, scholars have mainly made use of a two-step approach that can be referred to as PCA-MLR (principal component analysis and then ordinary least squares multiple linear regression analysis) to examine the relationships among exogenous and endogenous constructs in a statistical model. Although this two-step approach has contributed to the advancement of tourism research, it still suffers from a number of drawbacks which can readily be overcome by a so-called second-generation statistical tool, namely, partial least squares approach to structural equation modeling (PLS-SEM). The current chapter explains and illustrates (with an application to tourism data) the advantages (e.g., several layers of estimations, suiting small sample sizes, robustness to multicollinearity, model-based clustering, etc.) of PLS-SEM both from a statistical and practical point of view. Finally, an elucidation is also provided for suggesting PLS-SEM as an alternative to PCA-MLR instead of COV-SEM (covariance-based structural equation modeling). The chapter concludes by proposing that PLS-SEM is a reliable and flexible statistical approach that is of high value, in particular, for applied research.

This chapter reviews the methods available to hospitality and tourism researchers to perform moderation analysis with continuous variables in partial least squares structural equation modeling (PLS-SEM), with the objective of enhancing understanding and encouraging the use of these techniques in future papers. The product term method is presented first, followed by an empirical example/application in the context of hospitality and tourism. Two extensions, namely the two-stage approach that can help cope with formative and higher-order constructs, and the orthogonalizing approach that can help generate more accurate results and overcome multicollinearity among tourism variables in the presence of a continuous moderator variable, are then presented and discussed. The chapter concludes by presenting guidelines and recommendations for improving the use of interaction effects in analyses of tourism variables, as well as highlighting ongoing developments in both the product term method and PLS-SEM software.

Great uncertainty accompanies entrepreneurs’ processes of designing promising business models (BMs). Therefore, stabilising factors act as important means in this process. In this study, we examined the impact of cognitive dispositions and visual BM frameworks on the BM process and outcomes. By using partial-least-square structural equation modelling (PLS-SEM) and an experimental setting, our results show that the stabilising function of BM frameworks depends on entrepreneurs’ cognitive dispositions. This finding contributes to the cognitive BM perspective and explains how cognitive dispositions and visual framing effects act as boundary conditions for the theory of stabilising factors. This also has important implications for applying frameworks in practice.

Introduction: Commercial banks play a vital role in the global economy, facilitating economic growth and providing essential financial services. As key intermediaries between savers and borrowers, these institutions operate in a dynamic and complex environment characterised by various risk factors that can significantly impact their profitability and overall stability. Understanding the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability is crucial for effective risk management strategies and the development of appropriate regulatory frameworks.

Purpose: Commercial banks play a critical role in the global economy by facilitating economic growth and providing financial services. This study examines the interconnected relationships between credit risk, interest rate risk, liquidity risk, and profitability in commercial banking.

Methodology: The sample consists of licenced scheduled commercial banks on the Bombay Stock Exchange (BSE) from 2015 to 2022. Using the Smart PLS-SEM 3.0 path analysis technique, the study evaluates the combined influence of these risk factors on profitability and provides evidence-based recommendations for risk management strategies.

Findings: The findings can assist banks in enhancing their risk management practices, and regulators in developing appropriate regulatory frameworks. By understanding the key risk factors and their impact on profitability, banks and regulators can mitigate risks, enhance transparency, and promote stability within the banking sector.

Significance/value: The value of this study lies in its focus on the interconnectedness of risk factors, profitability, and the potential implications for decision-making, risk management strategies, regulatory frameworks, and the overall stability of the commercial banking sector.

Introduction: In this era, financial literacy is conceptualised diversely in the literature. However, as a general term, ‘Financial Literacy’ can be said to mean acting in line with one’s material realities whilst using or managing money. Increasing the financial literacy rate amongst students in Kosovo is paramount since it will prepare and support them in making informed investment decisions and in managing their financial situations.

Aim: The study aims to determine the financial literacy levels of students in Kosovo and to determine the relationship between investment decisions and the Covid-19 pandemic.

Method: The dataset examines four factors (i.e. financial literacy, self-control, peer influence and COVID-19) that influence investment behaviour amongst young students in Kosovo. A total of 228 students from Kosovo participated in the study, and the survey measured their financial literacy, investment knowledge, and the COVID-19 impact on their investment decisions using the random sampling technique. The reflective measurement was made using the Partial Least Squares Structural Equation Model (PLS-SEM) on the data scanned from the survey (N = 228). The measurement includes the evaluation of external loading, internal reliability, and convergent reliability. The final equation model was evaluated and estimated using the Smart-PLS v.3.3.3 program.

Findings: The research findings are useful for companies seeking potential investors from generation Y. In addition to that, the results of the research show that students from Kosovo who are more financially literate are more skilled and make more well-informed decisions when investing. In this study, it was determined that the COVID-19 pandemic did not have a negative effect on the investment decisions of students from Kosovo.

This research aimed to determine the mediating effect of entrepreneurial self-efficacy on the relationship between entrepreneurial passion and leadership styles. Two hundred hardware and footwear entrepreneurs from the Las Malvinas Commercial Emporium, Lima, Peru were surveyed. The partial least squares structural equation modelling (PLS-SEM) multivariate statistical technique was applied for data analysis. It was found that there is a complementary mediating effect of entrepreneurial self-efficacy in the relationship between entrepreneurial passion and leadership styles. On the other hand, it was concluded that entrepreneurial passion has a positive influence on entrepreneurial self-efficacy. Likewise, there is a positive influence of entrepreneurial self-efficacy on leadership styles, and there is a positive influence of entrepreneurial passion for leadership styles. This research contributed theoretically to the academic literature and provided empirical evidence of the relationship of the proposed variables; it proved a new predictive and explanatory structural model that can now be used in future research worldwide and generated a model of the studied variables that are useful for both academia and the business world.