Assassination and leadership: Traditional approaches and historiometric methods

Research on the assassinations and attempted assassinations of leaders seems warranted, as leaders and their interactions with extreme followers (e.g., fanatics) and non-followers (e.g., assassins) can have tremendous consequences not only for the leaders but also their larger collectives (e.g., nations, social movements). Based on the traditional and established leadership approaches of power orientation and outstanding leadership, we explored whether particular types of leaders were more likely victims of assassinations and targets of assassination attempts. Using historiometric methods, we found that socialized as well as pragmatic and ideological leaders were the most frequent victims of assassinations; but personalized as well as pragmatic and ideological leaders were the most frequent targets of assassination attempts; and for U.S. Presidents, socialized charismatics were the most frequent victims of assassinations and targets of assassination attempts. Results regarding leader paranoia, regions of the world, and assassins operating alone or as a group in relation to assassinations and leadership approaches also are presented. Implications of these findings for future leadership research involving leaders and their extreme followers, non-followers, and larger collectives are discussed.     

A 25-year perspective on levels of analysis in leadership research

The purpose of this article is to present a comprehensive 25-year review of the incorporation of levels of analysis into conceptual and empirical leadership research published within Leadership Quarterly throughout its history. We assessed the population of Leadership Quarterly's research (790 research articles) on four key levels of analysis-based issues: (1) explicit statement of the focal level(s) of analysis; (2) appropriate measurement given level of constructs; (3) use of a multi-level data analysis technique; and, (4) alignment of theory and data. Prior reviews regarding levels of analysis incorporation into leadership research have been limited to major research domains. Results revealed that while both conceptual and empirical articles only explicitly state the focal level of analysis in approximately one-third of the articles, appropriate levels-based measurement and alignment between theory and data are relatively strong areas of achievement for the articles within Leadership Quarterly. Multi-level data analysis techniques are used in less than one-fifth of all articles. Although there is room for improvement, there is evidence that Leadership Quarterly is a premier outlet for levels-based leadership research. Given the increasing complexity of organizational science with regard to groups, teams and collectives, Leadership Quarterly has an opportunity to model for organizational research on how to build and test complicated multi-level theories and models.     

Use and misuse of levels of analysis in leadership research: An illustrative review of leader–member exchange

Prior reviews have focused on if leadership literature pays homage to levels of analysis; our purpose is to take stock of how well and in what ways levels issues are implemented in theory and hypotheses formulation, construct conceptualization, measurement, and data analysis. To illustrate these notions, we provide an in-depth review of 163 multi-level empirical leader–member exchange (LMX) and vertical dyad linkage (VDL) studies published between 1972 and 2012. Our findings indicate that the volume of multi-level studies in LMX has drastically increased recently and the majority of these studies cast theory and hypotheses at the same level. With regard to alignment of levels of theory/hypotheses with measurement and with data analyses, however, roughly one out of two published studies suffers from misalignment of levels. Most of this misalignment occurs in studies where the dyad level of analysis, a key component of LMX, is an explicit or implicit focus. We conclude with a discussion of the implications for the LMX literature, and present recommendations to guide multi-level leadership research.     

Sequential Comparison of d Populations and Related Tables

The paper deals with the numerical solution of the likelihood equations for incomplete data from exponential families, that is for data being a function of exponential family data. Illustrative examples especially studied in this paper concern grouped and censored normal samples and normal mixtures. A simple iterative method of solution is proposed and studied. It is shown that the sequence of iterates converges to a relative maximum of the likelihood function, and that the convergence is geometric with a factor of convergence which for large samples equals the maxi-mal relative loss of Fisher information due to the incompleteness of data. This large sample factor of convergence is illustrated diagrammaticaily for the examples mentioned above. Experiences of practical application are mentioned.     

Article quality and publication impact via levels of analysis incorporation: An illustration with transformational/charismatic leadership

Calls for the inclusion of levels of analysis in theory building and testing have increased over the last 25 years. Through analysis of 539 published articles we assess the prevalence of incorporation of levels of analysis in theory/hypothesis formulation, measurement, data analysis, and subsequent theory–data alignment (i.e., article quality) within charismatic and transformational leadership research. Additionally, we examine the relationship between incorporation of levels of analysis into research and publication source quality, as reflected by journal impact factors or when not available, estimated journal impact factors. When controlling for the level of analysis within all articles, results revealed that increasing the complexity of the level of analysis (i.e., higher than individual level), increased the likelihood that measurement, analysis and alignment of theory and data would be presented at the appropriate levels of analysis. In contrast, for articles with published impact factors, when controlling for the level of analysis, results revealed that increasing the complexity of the level of analysis (i.e., higher than individual level) decreased the likelihood that measurement, analysis and alignment of theory and data would be presented at the appropriate levels of analysis.     

Clustering confidence sets

In this article, we present a novel approach to clustering finite or infinite dimensional objects observed with different uncertainty levels. The novelty lies in using confidence sets rather than point estimates to obtain cluster membership and the number of clusters based on the distance between the confidence set estimates. The minimal and maximal distances between the confidence set estimates provide confidence intervals for the true distances between objects. The upper bounds of these confidence intervals can be used to minimize the within clustering variability and the lower bounds can be used to maximize the between clustering variability. We assign objects to the same cluster based on a min–max criterion and we separate clusters based on a max–min criterion. We illustrate our technique by clustering a large number of curves and evaluate our clustering procedure with a synthetic example and with a specific application.     

Organizational Communication-Strategies at International Level

Human resources management represents the management of a company’s workforce. Human resources is not just a simple resource, it is also an important investment for companies. At the international level, communication in the management of human resources is more important because attraction, selection and training is not just for the regional level and needs to be adapted to international standards. We are trying to investigate in the first part of our research the character of organizational communication, based on human resources and to explain the strategies that can be used in organizational communication nowadays. In the second part of our research we analyze the content of successful organizational communication at the international level.     

Assassination of political leaders: The role of social conflict

Given human aggression and warfare are often described as the most pressing behavioral problems of our time, we focus on a related phenomenon, with large-scale social, political, and economic consequences: assassination of political leaders. We explore the role of social conflict as a predictor of political assassination and use historiometric methods and an extensive archival dataset to identify and code for contextual factors associated with social conflict and political homicide. Our results indicate an increase in social conflict increases the likelihood of assassination; moreover, environmental constraints and traditional culture predict leader assassination through social conflict. We discuss implications of these findings and suggest future research on contextual factors, assassination of political leaders, and their collective-level impact.