Sexuality and school shootings: what role does teasing play in school massacres?

Conventional explanations - lax gun control laws, media violence, single and working parents - do not adequately explain the recent spate of school shootings, and neither does bullying by itself, an explanation recently gaining more traction. A certain type of bullying, however, is revealed as particularly culpable. Many of the recent shootings share a disturbing component: The perpetrators were repeatedly, even relentlessly, accused by "preps and jocks" of being gay. Gay harassment is proposed as a point of departure for understanding the causes of school shootings. When boys who believe on some level that they warrant privilege, are instead harassed, they may feel driven to avenge the "wrong," and re-assert a more dominant, powerful, and victorious masculinity. These circumstances call for a cultural transformation such that "boys will be boys" is no longer used as an alibi for violence. The author presents implications for school-based social work practice, teacher and administrator interventions, as well as other prevention strategies.     

On Sampling Error in Market Share Estimates*

The relative error in the usual estimator of a brand's market share is reformulated in terms of marketing parameters. Such error is shown to be influenced in an important way by market penetration, as well as by variation in brand and product category volume. Of particular interest is the result that the relative error does not depend on the actual share level. Using data from a marketing research firm that supplies share estimates to the health products industry, we find that the relative error may be substantial even when a large sample is available. An upper bound on this relative error is obtained using marketing parameters that can frequently be measured using industry data and a company's internal records, thus reducing the level of judgmental input required in the planning of sample surveys.     

Ideal Values and Counter‐ideal Values as Two Distinct Forces: Exploring a Gap in Organizational Value Research

Motives and values at work have long been key topics of business and management studies. In a focused review of the literature on the nature of human values, this paper identifies a disconnect with the literature on human motivation, despite the otherwise inherent relatedness of the two fields. Specifically, extant theory and research have conceptualized values generally in terms of ideals, namely desired end‐states that individuals strive to approach. Although values, by this definition, express motivational concerns, theories of human motivation suggest that there are two forces to consider, i.e. approach and avoidance motivation. By applying this ‘two forces’ perspective to value research, this paper identifies a gap in the literature on values: namely, the idea that individuals are also influenced by counter‐ideal values, i.e. end‐states that they deliberately seek to avoid. The identification of this gap opens up new opportunities for value research in general and organizational value research in particular. To pave the way for future research, this paper critically discusses the few studies that have taken first steps in that direction and outlines research questions that may follow for issues such as employer branding and person–organization fit. This paper closes by providing suggestions on how to tackle the issue in organizational practice.     

Competitive and Cooperative Positioning in Supply Chain Logistics Relationships*

Cooperative logistics relationships require the sharing of information, which must be enabled by the integration of disparate information systems across partners. In this article, we theorize business‐to‐business logistics relationships should be managed using cooperative and competitive postures. Based on data from 91 dyadic relationships using interorganizational information technology (IT), we find that performance gains accrue when parties share strategic information and customize IT; mutual trust enables IT customization and strategic‐information flows and equitable relationship‐specific investments positively impact IT customization, mutual trust, and performance. Among other scholarly and practical implications discussed, partners should compete on resources for IT customization and cooperate to share strategic information. Managers tend to think of relationships with firms as polar opposites and view them as entirely cooperative or entirely competitive. Our results support active balancing and understanding of both competitive and cooperative stances. Such an approach enables conditions for participation symmetry that yields greater performance gains.     

Kurtosis modelling by means of the J-transformation

Summary: The H–family of distributions or H–distributions, introduced by Tukey (1960; 1977), are generated by a single transformation of the standard normal distribution and allow for leptokurtosis represented by the parameter h. Alternatively, Haynes et al. (1997) generated leptokurtic distributions by applying the K–transformation to the normal distribution. In this study we propose a third transformation, the so–called J–transformation, and derive some properties of this transformation. Moreover, so-called elongation generating functions (EGFs) are introduced. By means of EGFs we are able to visualize the strength of tail elongation and to construct new transformations. Finally, we compare the three transformations towards their goodness–of–fit in the context of financial return data.     

Regression Analysis of Restricted Mean Survival Time Based on Pseudo-Observations

Regression models for survival data are often specified from the hazard function while classical regression analysis of quantitative outcomes focuses on the mean value (possibly after suitable transformations). Methods for regression analysis of mean survival time and the related quantity, the restricted mean survival time, are reviewed and compared to a method based on pseudo-observations. Both Monte Carlo simulations and two real data sets are studied. It is concluded that while existing methods may be superior for analysis of the mean, pseudo-observations seem well suited when the restricted mean is studied.     

Nonlinear structural equation modeling: is partial least squares an alternative?

Nonlinear structural equation modeling provides many advantages over analyses based on manifest variables only. Several approaches for the analysis of latent interaction effects have been developed within the last 15 years, including the partial least squares product indicator approach (PLS-PI), the constrained product indicator approach using the LISREL software (LISREL-PI), and the distribution-analytic latent moderated structural equations approach (LMS) using the Mplus program. An assumed advantage of PLS-PI is that it is able to deal with very large numbers of indicators, while LISREL-PI and LMS have not been investigated under such conditions. In a Monte Carlo study, the performance of LISREL-PI and LMS was compared to PLS-PI results previously reported in Chin et al. (2003) and Goodhue et al. (2007) for identical conditions. The latent interaction model included six indicator variables for the measurement of each latent predictor variable and the latent criterion, and sample size was N=100. The results showed that PLS-PI’s linear and interaction parameter estimates were downward biased, while parameter estimates were unbiased for LISREL-PI and LMS. True standard errors were smallest for PLS-PI, while the power to detect the latent interaction effect was higher for LISREL-PI and LMS. Compared to the symmetric distributions of interaction parameter estimates for LISREL-PI and LMS, PLS-PI showed a distribution that was symmetric for positive values, but included outlying negative estimates. Possible explanations for these findings are discussed.