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Blockmodeling is viewed often as a data reduction method. However, this is a simplistic view of the class of methods designed to uncover social structures, identify subgroups, and reveal emergent roles. Worse, this view misses the richness of the method as a tool for uncovering novel human resource management (HRM) insights. Here, we provide a brief overview of some essentials of blockmodeling and discuss research questions that can be addressed using this approach in applied HRM settings. Finally, we offer an empirical example to illustrate blockmodeling and the types of information that can be gleaned from its implementation.

Purpose – This chapter aims at proposing a methodology for evaluating long-term income distributions according to the equality of opportunity principle.

Approach – We refer to the concept that there is equality of opportunity if the value of the set of opportunities is the same for all individuals, regardless of their circumstances. This approach partitions the population into types, that is, groups of individuals with the same set of circumstances. The type-specific outcome distribution is interpreted as the opportunity set of individuals with the same circumstances. We propose partial and complete rankings on long-term type-specific distributions. Accordingly, these rankings capture inequality between types, and are neutral to inequality within types.

Findings – We show the relationship between long-run and short-run inequality of opportunity and that this relationship can be interpreted in terms of intragenerational mobility. We also show that mobility can act as an equalizer of opportunities when the accounting period is extended.

Originality – The contribution of this work is twofold. First, we develop a decomposition of some measures of long-term inequality of opportunity into measures of short-term inequality of opportunity, applied to distributions, which neutralize the effect of effort on individual income, and may be employed to explain eventual differences arising from an analysis based on the intertemporal context. Second, we propose an index to measure intragenerational mobility and show how it can be interpreted as long-term EOp. Our measure captures only that part of reranking due to the equalization of opportunities over time.

Purpose – Criminal groups have long been central to explanations of crime and deviance. Yet, challenges in measuring their dynamic and transient nature meant that group-level explanations were often displaced in favor of individual-level ones. This chapter outlines how network methods provide a powerful tool for modeling the dynamic nature of criminal groups.

Approach – The chapter starts by providing a brief introduction to social network analysis, including key concepts and terminology. The chapter then focuses on the types of relational data available to study criminal groups, and how network methods can be used to delineate group boundaries. The chapter concludes by presenting a framework for understanding group dynamics from a network perspective, describing the contributions of network analysis to theories of group processes.

Findings – Network methods have provided meaningful advances to the study of group dynamics, leading scholars to revisit assumptions about the impact of group’ structure on delinquent behavior. Network studies of group dynamics have primarily focused on the cohesion–delinquency link (within-group structure) and the social contagion of conflict (between-group structure), highlighting important opportunities for the intersection of these two inquiries.

Value – Network methods provide a means to revisit and extend theories of crime and delinquency with a focus on social structure. The unique affinity between group dynamics and network methods highlights immense opportunities for expanding the knowledge of collective trajectories.

Distributed ledger technologies, and particularly blockchain, have attracted significant attention recently and we believe that it is right time to look back the literature and digest the accumulated knowledge. The purpose of this study is to contribute to the existing knowledge of blockchain technology by surveying the stock of research about this newly rising technology. We conducted a descriptive analysis of current academic and business research on blockchain technology and categorized the studies according to source, field, approach, geography, affiliation, and cryptocurrency-focus. We accompanied this with a global patent publication analysis and presented our insights and takeaways from our analyses.