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 Recent references are also provided to discourage researchers from using outdated mediation approaches in their theses/manuscripts.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.

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

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.

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.

Purpose-The purpose of this paper is twofold. First, it examines the impact of person-organisation fit (P-O fit) on work engagement (WE) and the impact of WE on turnover intention. Second, it examines the mediating role of WE between P-O fit and turnover intention. Design/methodology/approach-A cross-sectional online survey design was used to collect data through snowball sampling procedure. In total, 422 oil and gas (O&G) professionals participated in this study. In total, 13 incomplete samples were excluded during initial screening. As a result, 409 samples were used for final data analysis. The partial least squares-structural equation modelling, using SmartPLS3.0, was performed to test the hypothesised model. Findings-The results of the study revealed strong ties between P-O fit, WE, and turnover intention. Specifically, P-O fit was found to be a strong predictor of WE and WE is negatively related to employees' turnover intention. Further, WE mediated the relationship between P-O fit and turnover intention. Practical implications-The findings of this study suggest that O&G organisations must pay greater attention to P-O fit to increase employees' level of engagement and decrease voluntary turnover rate. Overall, the findings provide pragmatic insights for human resource management practitioners and the relevant stakeholders. Originality/value-To date, little attention has been devoted to understanding the mediating role of WE between P-O fit and turnover intention. The present study addresses this gap in the literature.

PurposeThis study aims to examine the impact of employees' satisfaction with human resource management (HRM) practices (i.e. training satisfaction, performance appraisal satisfaction and pay satisfaction) on work engagement and subsequently employee turnover intentions. The mediating role of work engagement between employee satisfaction with HRM practices and turnover intentions is also assessed.Design/methodology/approachData were collected from Malaysian oil and gas (O&G) professionals. A total of 442 useable questionnaires were obtained for the final data analysis. Partial least squares structural equation modeling (PLS-SEM) was performed to test the hypothesised relationships.FindingsThe findings indicate that training satisfaction and performance appraisal satisfaction are the key drivers of employee engagement at work. Work engagement in turn has a negative impact on employee turnover intentions. Furthermore, work engagement mediates the relationship between employees' satisfaction with HRM practices (i.e. training satisfaction and performance appraisal satisfaction) and turnover intentions. Nevertheless, it did not have any mediating effect on pay satisfaction and turnover intention.Practical implicationsTraining plans should be designed to make the relevant jobs more attractive and fulfilling, thus increasing employees' level of work engagement. Besides, ensuring that the appraisal system is fair is pivotal to work engagement. Work engagement will cultivate a strong sense of emotional attachment between employees and employers, thus reducing the turnover intention of Malaysian O&G professionals.Originality/valueTo date, little has been done on employees' satisfaction with HRM practices with respect to their attitudinal and behavioural outcomes. The present study enhances our understanding of the importance of employees' satisfaction with HRM practices and its relation to employees' work engagement and turnover intentions.

In partial least squares structural path modelling, the reflective-formative type of hierarchical component models (HCMs) (also known as Higher-Order Model) have become a popular choice for researchers. However, current approaches to estimate the reflective-formative type of HCM are ambiguous especially when used as an endogenous construct or a mediator. This paper presents a comparison between five different approaches (repeated indicator, two types of two-stage, hybrid, and improved repeated indicator) with two different estimation modes (Mode A and Mode B) when modelling a mediator construct of a reflective-formative HCM in the structural model. By using a model based on stimulus-organism-response theory, an empirical application to the tourism field is adopted in this study. The proposed HCM model examines perceived relative advantages as a mediation of the relationship between Communicability and Intention to Purchase Travel Online. The findings suggest that the improved repeated indicator approach with Mode B estimation yields better path coefficients, goodness of fit, explained variance, and predictive relevance as compared to other approaches. The study provides valuable recommendations and guidelines for tourism researchers to properly conduct an HCM analysis.