The Management of Violence in a Conflict Organization: The Case of the Abu Sayyaf

The Abu Sayyaf is an organization which has left a trail of mayhem and murder in the southern Philippines for more than a decade. It has gained international notoriety through several high profile mass kidnappings. This article looks at how the Abu Sayyaf has managed to survive and at times prosper despite the state's efforts to eradicate it. By using organizational analysis the paper demonstrates how the Abu Sayyaf has developed structures and processes which make it such a deadly force. The organization has succeeded in gaining considerable fit with the environment in which it operates.     

Supervision als Fortbildungsangebot für stellvertretende schulleiter

Supervision as further education of vice-headmasters Our offer of further education aims at an improvement of executive activities of viceheadmasters. With the help of their first experiences with our concept they’ll become acquainted with the various processes of change in schools and can use it as an opportunity to support them. That’s our contribution to the development of the executive personnel in the schools of Sachsen-Anhalt.     

Editorial

Ohne Zusammenfassung

---

Editorial

     

Ebert. Wolfgang (2001): Systemtheorien in der Supervision — Bestandsaufnahme und Perspektiven

Ohne Zusammenfassung     

Personality and organizational health: the role of conscientiousness

Organizational health research identifies processes through which the work environment and individual differences combine to influence both individual and organizational outcomes. This study investigated the contribution of conscientiousness to organizational health. Research in the areas of occupational stress, work performance, and organizational climate was used to develop a framework for integrating different elements of organizational health. Within this framework, the work environment was assessed by perceptions of workload and role clarity ; individual well-being was assessed by psychological distress and job satisfaction ; and behaviour important for organizational success was assessed by contextual performance. Conscientiousness was investigated within the framework using self-reports from a sample of 104 Australian employees. Conscientiousness directly influenced contextual performance but did not influence well-being or perceptions of the work environment. Conscientiousness also reduced the impact of role clarity on both psychological distress and job satisfaction. The role of conscientiousness in a comprehensive model of organizational health is discussed.     

Optimization Model and Algorithm for Crew Management During Airline Irregular Operations

Airline irregular operations have long been a realm where human experience and judgement are the most important tools to utilize. Crew management during irregular operations is usually the bottleneck of the whole system-recovering process due to complicated crew schedules and restrictive crew legalities as well as the size and scope of the hub-and-spoke networks adopted by major carriers. A system-wide multi-commodity integer network flow model and a heuristic search algorithm for the above purpose are presented and discussed in this paper. The computational experiences show that the algorithm is efficient enough to solve problems of realistic size and also has the flexibility to accommodate practical business requirements.     

Early experiences of mentoring: Design and use of multimedia materials for teaching OR/MS

The MENTOR project, based at the University of Strathclyde, is producing multimedia computer based learning materials with the aim of improving both the effectiveness and the efficiency of teaching Operational Research/Management Science in higher education. The process of development has been carefully designed to encourage ownership of and commitment to the materials amongst lecturing staff in Universities, with the aim of ensuring widespread use. The paper outlines this process of development and design of materials. Experiences in introducing students to the use of these materials as an integrated part of a Management Science class are reported. Feedback from students has been very positive but also indicates the need for ongoing support and direction.     

Handling of missing data in long‐term clinical trials: a case study

Missing data in clinical trials is a well‐known problem, and the classical statistical methods used can be overly simple. This case study shows how well‐established missing data theory can be applied to efficacy data collected in a long‐term open‐label trial with a discontinuation rate of almost 50%. Satisfaction with treatment in chronically constipated patients was the efficacy measure assessed at baseline and every 3 months postbaseline. The improvement in treatment satisfaction from baseline was originally analyzed with a paired t‐test ignoring missing data and discarding the correlation structure of the longitudinal data. As the original analysis started from missing completely at random assumptions regarding the missing data process, the satisfaction data were re‐examined, and several missing at random (MAR) and missing not at random (MNAR) techniques resulted in adjusted estimate for the improvement in satisfaction over 12 months. Throughout the different sensitivity analyses, the effect sizes remained significant and clinically relevant. Thus, even for an open‐label trial design, sensitivity analysis, with different assumptions for the nature of dropouts (MAR or MNAR) and with different classes of models (selection, pattern‐mixture, or multiple imputation models), has been found useful and provides evidence towards the robustness of the original analyses; additional sensitivity analyses could be undertaken to further qualify robustness. Copyright © 2012 John Wiley & Sons, Ltd.     

Free energy methods for Bayesian inference: efficient exploration of univariate Gaussian mixture posteriors

Because of their multimodality, mixture posterior distributions are difficult to sample with standard Markov chain Monte Carlo (MCMC) methods. We propose a strategy to enhance the sampling of MCMC in this context, using a biasing procedure which originates from computational Statistical Physics. The principle is first to choose a “reaction coordinate”, that is, a “direction” in which the target distribution is multimodal. In a second step, the marginal log-density of the reaction coordinate with respect to the posterior distribution is estimated; minus this quantity is called “free energy” in the computational Statistical Physics literature. To this end, we use adaptive biasing Markov chain algorithms which adapt their targeted invariant distribution on the fly, in order to overcome sampling barriers along the chosen reaction coordinate. Finally, we perform an importance sampling step in order to remove the bias and recover the true posterior. The efficiency factor of the importance sampling step can easily be estimated a priori once the bias is known, and appears to be rather large for the test cases we considered.     

Data-driven Kriging models based on FANOVA-decomposition

Kriging models have been widely used in computer experiments for the analysis of time-consuming computer codes. Based on kernels, they are flexible and can be tuned to many situations. In this paper, we construct kernels that reproduce the computer code complexity by mimicking its interaction structure. While the standard tensor-product kernel implicitly assumes that all interactions are active, the new kernels are suited for a general interaction structure, and will take advantage of the absence of interaction between some inputs. The methodology is twofold. First, the interaction structure is estimated from the data, using a first initial standard Kriging model, and represented by a so-called FANOVA graph. New FANOVA-based sensitivity indices are introduced to detect active interactions. Then this graph is used to derive the form of the kernel, and the corresponding Kriging model is estimated by maximum likelihood. The performance of the overall procedure is illustrated by several 3-dimensional and 6-dimensional simulated and real examples. A substantial improvement is observed when the computer code has a relatively high level of complexity.