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Purpose – The purpose of this chapter is to present a subset of seven statistical and methodological myths and urban legends (SMMULs). When present, SMMULs degrade the overall research process and make manuscript evaluation problematic during the review process. SMMULs covered here included those pertaining to accepting the theoretical model, conventional cutoff values, exploratory factor analysis, common method bias, moderation analysis, Baron and Kenny's four-step mediation test, and permitting correlated item residuals.

Design/Methodology – Given that the details underlying the SMMULs have already been published, the present chapter was a summary of each. The summaries presented the urban legend and sources for it. Subsequently, the kernel of truth underlying the SMMUL was presented, and how this truth may have been lost and distorted. Each summary ends with the recommended “good” practices as presented by the original authors.

Findings/Implications – The implication for researchers is to modify their current practices to strengthen their research and to make better inferences. And for editors and reviewers, the implication is to develop accurate decision rules to strengthen the review process.

Originality/Value – The overall value of the chapter is to improve the research process in general.

This chapter offers a case study of the distinctive political activism in Taiwanese metal by analysing the intertextuality of Just Not Meant to Be (還君明珠) (2015) by Crescent Lament (恆月三途). From the perspective of a cultural insider, the author examine the socio-cultural dynamics underlying this activism and explain how Taiwanese metal attempts to tackle the troubled past of Taiwan. The author brings attention to Just Not Meant to Be's commentary about the activism it takes part in, and reflect on problematics inherent to political activism in Taiwanese metal. Finally, the author explicates the problematics in the context of metal subculture in general. Pivotal throughout this chapter are the questions: Why does Taiwanese metal replicate forms of domination it seeks to counter? What can metal subculture in general learn from Taiwanese metal and its political activism?

Over the past decade, the rapid evolution of social media has impacted the field of human resource management in numerous ways. In response, scholars and practitioners have sought to begin an investigation of the myriad of ways that social media impacts organizations. To date, research evidence on a range of HR-related topics are just beginning to emerge, but are scattered across a range of diverse literatures. The principal aim of this chapter is to review the current literature on the study of social media in HRM and to integrate these disparate emerging literatures. During our review, we discuss the existent research, describe the theoretical foundations of such work, and summarize key research findings and themes into a coherent social media framework relevant to HRM. Finally, we offer recommendations for future work that can enhance knowledge of social media’s impact in organizations.

The effectiveness of corporate governance is a major factor in forecasting firm performance. We examine the relationships among cross-listing, corporate governance and firm performance for a sample of Chinese cross-listed companies. We show that cross-listed firms display higher overall quality of corporate governance compared to non-cross-listed firms. Consequently better corporate governance results in higher operating performance. Our results support the bonding hypothesis of cross-listing. Furthermore, we also illustrate that the cross-listing status encapsulates the higher quality of corporate governance that leads to higher operating performance. When forecasting performance of cross-listing companies, it is therefore important to recognize the substitute effect between cross-listing and corporate governance.

This chapter examines the associations between gender, social support, and health outcomes for individuals living with HIV disease. We include social integration and social isolation as structural measures of social support as well as perceived social support and social conflict as functional measures of social support. We include both mental health and physical health outcomes, which are too often studied in isolation of each other.

Data are from the Coping with HIV/AIDS in the Southeast (CHASE) study; this study reports on baseline data from 611 participants collected from 2001 to 2002. We first examined differences by gender and race, and then used blocked linear regression to determine the additive effects of the social support variables on both mental and physical health outcomes while controlling for potential confounders.

There were notable differences in the significance and strength of social support variables in health outcome models for men and women. Unlike men, social conflict was the strongest predictor of greater psychological distress and poorer physical health-related quality of life among women.

While the results from this study contribute to a greater understanding of gender differences in the relationships between social support and health outcomes, the data used for this study are limited to those living with HIV/AIDS in the Southeast.

Our findings suggest that social conflict may be more detrimental for the health of women than men.

This chapter seeks to contribute to an ongoing discussion about Asian Canadian identities, model minority stereotypes, and structural racism against Asian Canadian youth in the Canadian education system. Using a Bourdieusian lens, this narrative study explores how to understand the experiences of Asian Canadian youth who are streamed into STEM (science, technology, engineering, and mathematics)-related occupational trajectories. Using data obtained from semi-structured interviews, I explore how streaming in high schools affects the identity formation of these youth. I argue there is an insight to be gained by paying closer attention to homologies between racial tensions and disciplinary tensions within the public school system. Doing so opens up new ways of framing and recognizing partial and diffuse acts of resistance among Asian Canadian youth who would otherwise appear to have internalized dominant stereotypes and norms.

This chapter investigates the behavior of Reddit’s news subreddit users and the relationship between their sentiment on exchange rates. Using graphical models and natural language processing, hidden online communities among Reddit users are discovered. The data set used in this project is a mixture of text and categorical data from Reddit’s news subreddit. These data include the titles of the news pages, as well as a few user characteristics, in addition to users’ comments. This data set is an excellent resource to study user reaction to news since their comments are directly linked to the webpage contents. The model considered in this chapter is a hierarchical mixture model which is a generative model that detects overlapping networks using the sentiment from the user generated content. The advantage of this model is that the communities (or groups) are assumed to follow a Chinese restaurant process, and therefore it can automatically detect and cluster the communities. The hidden variables and the hyperparameters for this model are obtained using Gibbs sampling.

Bankruptcy prediction has attracted a great deal of research in the data mining/machine learning community, due to its significance in the world of accounting, finance, and investment. This chapter examines the influence of different dimension reduction techniques on decision tree model applied to the bankruptcy prediction problem. The studied techniques are principal component analysis (PCA), sliced inversed regression (SIR), sliced average variance estimation (SAVE), and factor analysis (FA). To focus on the impact of the dimension reduction techniques, we chose only to use decision tree as our predictive model and “undersampling” as the solution to the issue of data imbalance. Our computation shows that the choice of dimension reduction technique greatly affects the performances of predictive models and that one could use dimension reduction techniques to improve the predictive power of the decision tree model. Also, in this study, we propose a method to estimate the true dimension of the data.

This chapter seeks to investigate the role of student emotional intelligence (EI) in countering in-class cyberloafing behaviour by students, by exploring the mediating role of boredom proneness through a quantitative approach. A sample of 163 postgraduate university students in India was selected. The authors assessed the mediation model using PROCESS macro. The authors found that students who are more aware of their emotions are better equipped to handle internal and external distractions and work towards a desired goal or outcome and therefore are less likely to experience boredom. Results from this study revealed a significant direct and indirect negative relationship between students’ EI and cyberloafing behaviour. This chapter contributes to the body of literature by highlighting the positive effects of EI as an important antidote to student cyberloafing behaviour. On the practical front, the findings of this study can be used by academicians who are charged with the responsibility of understanding and enhancing student learning by diminishing cyberloafing behaviour among them. The proposed framework could provide a foundation for countering cyberloafing behaviour in educational settings.