Specification of nonverbal behaviors for clinical assessment

Nine categories of nonverbal behavior (extremity movements, self-manipulations, facial expression, posture, orienting, gestures, voice quality/tone, speech rate/pressure, and sense of timing) were tested in a standardized role play situation of social skills. Each category was judged using a new midi-level system of assessment which permitted specification of component behaviors but allowed observers to make single ratings at the ends of videotaped episodes. The midi-level measurements were as reliable and practical as more traditional global measures of social skill and social anxiety. Midis were superior to globals (i.e., single overall ratings of skill and anxiety) in terms of predicting physiological indices of social anxiety. Voice quality/tone and sense of timing appeared to be the best predictors of criterion social skill measures and self-manipulations, extremity movements, and gestures had the highest weights in predicting criterion measures of social anxiety.     

Performance measurement with classification information: an enhanced additive DEA model

This paper presents an improved measurement tool for evaluating performance of branches within a major Canadian bank. While there have been numerous previous studies of performance in the banking industry, particularly at the branch level, this study is different in a very significant way: specifically two kinds of data are used to develop the model. The first type of data is that related to standard transactions, available from any bank; such have formed the basis of numerous previous studies. The second type of data, obtained from the site studied, is classification information, based on branch consultant/expert judgment as to good and poor performance of branches. The purpose herein is to present a modified version of an existing benchmarking model, data envelopment analysis (DEA), and to show how this tool is applied in the banking industry. The mechanism used herein to incorporate expert knowledge within the DEA framework is to first apply a discriminant or classification tool, to quantify the functional relation that best captures the expert's mental model for performance. The outcome of this first phase is an orientation of variables to aid in the definition of inputs and outputs. The resulting orientation then defines the DEA model that makes up the second phase of the model.     

Estimation from Zero-Failure Data

When performing quantitative (or probabilistic) risk assessments, it is often the case that data for many of the potential events in question are sparse or nonexistent. Some of these events may be well-represented by the binomial probability distribution. In this paper, a model for predicting the binomial failure probability, P , from data that include no failures is examined. A review of the literature indicates that the use of this model is currently limited to risk analysis of energetic initiation in the explosives testing field. The basis for the model is discussed, and the behavior of the model relative to other models developed for the same purpose is investigated. It is found that the qualitative behavior of the model is very similar to that of the other models, and for larger values of n (the number of trials), the predicted P values varied by a factor of about eight among the five models examined. Analysis revealed that the estimator is nearly identical to the median of a Bayesian posterior distribution, derived using a uniform prior. An explanation of the application of the estimator in explosives testing is provided, and comments are offered regarding the use of the estimator versus other possible techniques.     

Strategic learning with scenarios

Since the oil shocks upset the business world in the 1970s, the use of multiple scenario analysis has been increasingly propagated as an approach to deal effectively with the many long-run uncertainties that surround business organisations. Since its introduction, the scenario approach has undergone some considerable changes and it is now claimed fulfils a diverse range of functions. Newly-added functions include the stretching of managers' mental models and the triggering and acceleration of processes of organisational learning. Although these functions currently get most of the attention in academic and management journals in recent years, a satisfying explanation of how scenarios fulfil these functions is still missing in the scenario literature. The scenario methodology seems to tell only part of the story suggesting that construing and using scenarios ‘simply’ consists of sequentially completing several distinct phases. If multiple scenario analysis really is able to fulfil the wide range of functions ascribed to it another, more dynamic process has to be hidden behind the rather static phase model. The scenario literature does not give any insight into this latter process. This article aims to increase the understanding of multiple scenario analysis by unravelling some of the mysteries surrounding it. For this purpose, the role of scenarios in strategic management is studied from a cognitive perspective. It appears that scenarios can deal effectively with several bottlenecks that potentially hinder organisational learning on a strategic level in organisations.     

Data relaying with constraints in hierarchical sensor networks

In this paper we present and discuss several optimisation problems that arise in the management of data flow in wireless sensor networks (WSNets). We consider a hierarchical architecture for WSNets composed of sensors, relays, and relay gateways. Sensors send data they generate at a known average bit rate to relays in one hop. The relay nodes use a multi-hop mechanism to reach a set of assigned gateways which then forward the data directly to the base station. We are concerned with finding an assignment of relay gateways to relays so that certain constraints are satisfied. We define a unified model in which constraints such as lifetime, data delay, and data flow splitting are formulated in terms of four optimisation problem in graphs.     

Strategic Alliance Outcomes: a Transaction‐Cost Economics Perspective

Empirical research on strategic alliances has been limited because previous studies examined alliance outcomes, and the factors associated with them, from a single partner in a manufacturing alliance. Furthermore, many of these studies have been done from a transaction cost perspective and researchers have inferred opportunistic behavior, rather than directly measuring it and observing its actual relationship with alliance performance. Building on previous transaction cost theory and research, this study seeks to address these gaps by analyzing factors associated with both opportunistic behavior and alliance performance within a major service sector, namely the US healthcare industry. After controlling for asset specificity and alliance age, we found that partner trustworthiness and contractual safeguards were negatively related to opportunistic behavior. Furthermore, opportunistic behavior was negatively related to alliance performance, as hypothesized. Interestingly, mutual equity investments were found to be unrelated to opportunistic behavior, counter to transaction‐cost logic. These findings refine and extend the transaction‐cost economics perspective regarding our understanding of strategic alliance behavior and outcomes, and offer executives in service‐based industries some practical ideas for assuring favorable strategic alliance outcomes.     

Social Loafing: A Field Investigation

Social loafing was investigated by testing a multilevel model among 23 intact work groups comprised of 168 employees representing two organizations. Results demonstrated that as hypothesized at the individual level, increases in task interdependence and decreases in task visibility and distributive justice were associated with greater occurrence of social loafing. At the group level, increased group size and decreased cohesiveness were related to increased levels of social loafing. Of particular interest was the finding that group member perceptions of perceived coworker loafing was associated with reduced social loafing, opposite of our predictions. We suggested that this unexpected finding may provide evidence of a social compensation effect.     

Loneliness and Adolescents’ Neural Processing of Self,Friends, and Teachers: Consequences for the School Self‐Concept

The present interdisciplinary study explored whether perceived loneliness is associated with ventromedial prefrontal cortex (vMPFC) activation during self‐ and social judgments (friends and teachers) in adolescents. Moreover, we examined how vMPFC activity is related to the academic self‐concept (ASC). Results of manifest path analysis indicated that high perceived loneliness was related to lower neural response to self‐judgments. In turn, high neural response to self‐judgments was positively associated with the ASC, whereas there was a trendwise negative association between high neural response to teacher‐related judgments and ASC. This study reveals associations between perceived loneliness and neural processing of the self, underlining the idea that feeling isolated from others may hinder self‐insight and, by extension, the formation of a stable academic self‐concept.     

Inference for quantile measures of kurtosis,peakedness, and tail weight

Insight into measures of peakedness, heavy-tailedness, and kurtosis can be gained by studying Ruppert’s ratios of interquantile ranges. They are not only monotone in Horn’s measure of peakedness when applied to the central portion of the population, but also monotone in the practical tail-index of Morgenthaler and Tukey, when applied to the tails. Non-parametric confidence intervals are found for Ruppert’s ratios, and sample sizes required to obtain such intervals for a pre-specified relative width and level are provided. In addition, the empirical power of distribution-free tests for peakedness and bimodality are found for some symmetric distributions.