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In this chapter, the authors critically examine the application of unmeasured latent method factors (ULMFs) in human resource and organizational behavior (HROB) research, focusing on addressing common method variance (CMV). The authors explore the development and usage of ULMF to mitigate CMV and highlight key debates concerning measurement error in the HROB literature. The authors also discuss the implications of biased effect sizes and how such bias can lead HR professionals to oversell interventions. The authors provide evidence supporting the effectiveness of ULMF when a specific assumption is held: a single latent method factor contributes to the data. However, the authors dispute this assumption, noting that CMV is likely multidimensional; that is, it is complex and difficult to fix with statistical methods alone. Importantly, the authors highlight the significance of maintaining a multidimensional view of CMV, challenging the simplification of a CMV as a single source. The authors close by offering recommendations for using ULMFs in practice as well as more research into more complex forms of CMV.

The present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.

The study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.

Overall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.

The study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.

The purpose of this study is to explore how intercultural competencies impact the employment of young people, and to showcase virtuous examples of practices by the University of Turin and the company Global Mindset Development.

Drawing upon a comprehensive review of relevant literature, this paper highlights the theoretical foundations of intercultural competencies and their relevance to labor market integration. It examines their multidimensional nature, encompassing knowledge, skills, attitudes and awareness necessary for individuals to effectively navigate and engage with diverse cultural contexts. The paper then presents several good and promising practices realized by the University of Turin and the training and consultancy company Global Mindset Development. Furthermore, it addresses potential challenges associated with developing and implementing intercultural competencies in practice.

The study enriches the body of literature on the importance of intercultural competencies for young workers acquired through experiences such as international mobility for labor market integration.

The study presents some innovative approaches to training through experiential and mobility training programs. These new examples of practices can inspire further research and implementation.