Determining an appropriate sample size is vital in drawing realistic conclusions from research findings. Although there are several widely adopted rules of thumb to calculate sample size, researchers remain unclear about which one to consider when determining sample size in their respective studies. ‘How large should the sample be?’ is one the most frequently asked questions in survey research. The objective of this editorial is three-fold. First, we discuss the factors that influence sample size decisions. Second, we review existing rules of thumb related to the calculation of sample size. Third, we present the guidelines to perform power analysis using the G*Power programme. There is, however, a caveat: we urge researchers not to blindly follow these rules. Such rules or guidelines should be understood in their specific contexts and under the conditions in which they were prescribed. We hope that this editorial does not only provide researchers a fundamental understanding of sample size and its associated issues, but also facilitates their consideration of sample size determination in their own studies.

This editorial outlines and responds to some of the most frequently asked questions regarding mediation analysis. Specifically, six key issues are addressed with reference to the state-of-theart mediation literature. In doing this, we provide practical guidelines for researchers to successfully conceptualize, test and interpret mediation models. Recent references are also provided to discourage researchers from using outdated mediation approaches in their theses/manuscripts. It is our hope that this effort will clarify misconceptions regarding mediation analysis and provide up-to-date guidelines for researchers to make informed decisions and conduct the analysis appropriately.

Purpose The purpose of this paper is to examine the casual relationship between training satisfaction, work engagement (WE) and turnover intention and the mediating role of WE between training satisfaction and turnover intention. Design/methodology/approach Data were collected from 409 oil and gas professionals using an email survey questionnaire. Structural equation modelling, using Analysis of Moment Structures (IBM AMOS) 22.0, was performed to test the hypothesized model. Findings The results suggest that training satisfaction is significantly positively related to employees’ level of WE and is negatively related to turnover intention. The results also reveal that WE mediates the relationship between training satisfaction and turnover intention. Practical implications Training has long been thought to play an important role in achieving positive attitudinal and behaviours outcomes among employees. This study reconfirms these ideas and highlights the importance of training satisfaction as being key to achieving greater WE and reducing voluntary turnover. Therefore, the finding of this study have a number of implications for research and human resource development practitioners. Originality/value This study makes a significant theoretical contribution to the literature as this is the first study to demonstrate the significance of training satisfaction and the mediating effects of WE in reducing the turnover intention of employees.

Although structural equation modeling (SEM) is a powerful statistical technique, understanding its methodological assumptions before data analyses is essential to attaining more robust results. In this editorial, we outline four major methodological issues which are related to the application of SEM in Malaysia along with their respective guidelines. These issues include 1) probability and non-probability sampling, 2) pre-testing and pilot study, 3) CB-SEM and PLS-SEM, and 4) exploratory and confirmatory factor analysis. We also recommend the steps that the local research community, especially the postgraduate students, should consider taking to keep themselves up-to-date with methodological advances and to make informed decisions about the use of SEM. This humble effort will help to clarify the confusion and doubts many lecturers and postgraduate students in Malaysia might have, and provide directions to help them proceed in a practical manner

This editorial is dedicated to moderation analysis. Similar to what we did with the earlier editorial about mediation analysis, this editorial addresses seven key issues related to moderation and provides guidelines to justify the inclusion of moderator(s) and perform the analysis. Specifically, it discusses identification, conceptualization, usage, analysis, and reporting of moderating variables. Additionally, it also explains several approaches pertaining to moderation analysis and highlights the key differences between a simple moderation analysis and a multi-group analysis. We hope that this editorial will be useful to academics and research students to conduct moderation analysis with rigor.