Strategic planning in a changing corporate environment

Strategic planning is about nothing, if it is not about attempting to achieve desirable futures. In the past this has often been seen as an excuse, or indeed a necessity, for fixed goals which are constantly timed. Such a state of planning has, fortunately, for a long time now been discredited and this paper concentrates upon the concepts of strategic planning within the changing corporate environment, an environment which therefore has to effect both the goals as well as the process of planning. Furthermore, the author concentrates upon the concept of a planning, allocating, and monitoring cycle of strategic planning which sets the strategic planning concept within a process cycle as well as within an effective allocative structure. The author considers this latter point an extremely important one since, as he says, ‘planning can become a very sterile and barren activity if it is not viewed integrally with acting and doing’. Finally, this paper concentrates on the important fact that planning must, within a dynamic environment, be an iterative and a learning process.     

War-related mental health problems of today's veterans: new clinical awareness

1. Veterans of the military conflicts in Iraq and Afghanistan may have been exposed to significant psychological stressors, resulting in mental and emotional disorders. 2. Posttraumatic stress disorder (PTSD) is characterized by symptoms in three domains: reexperiencing the trauma, avoiding stimuli associated with the trauma, and symptoms of increased autonomic arousal. 3. Treatment of PTSD often requires both psychological and pharmacological interventions. 4. In addition to PTSD, other mental disorders may be precipitated or worsened by exposure to combat, including depression, anxiety, psychosis, and substance abuse.     

Estimating the hazard functions of two alternating recurrent events in the presence of covariates

The motivation for this paper is a cystic fibrosis data which records a patient’s times to relapse and times to cure under several recurrences of the disease. The idea is to study the impact of covariates on the hazard rates of two alternately occurring events. The dependence between the times to the two events over the different cycles is modeled through an autoregressive-type setup. The partial likelihood function is then derived and the estimators obtained. The estimators are shown to be consistent and asymptotically normal. The technique is applied to study the motivating data. A simulation study is also conducted to corroborate the results.     

What is Real and What is Realism in Sociology?

In the physical sciences a realist ontology rests on our ability to demonstrate the actual and real nature of material entities. Realist metaphysics of social entities, most influentially Bhaskar's critical realism, attempt to provide a related philosophical foundation for the social sciences. This paper examines the central issue of what is real about society it concludes that social relations and the organisations they constitute do exist and discusses the conditions of their demonstration. Realist interpretations of Bourdieu's theories are given particular attention in an argument that accepts the necessity of social realism but remains cautious about the development of methodologies able to provide effective demonstration.     

Assessment of Indoor Route-finding Technology for People with Visual Impairment

This study investigated navigation with route instructions generated by digital-map software and synthetic speech. Participants, either visually impaired or sighted wearing blind folds, successfully located rooms in an unfamiliar building. Users with visual impairment demonstrated better route-finding performance when the technology provided distance information in number of steps rather than walking time or number of feet.     

Computation aspects of the parameter estimates of linear mixed effects model in multivariate repeated measures set-up

The number of parameters mushrooms in a linear mixed effects (LME) model in the case of multivariate repeated measures data. Computation of these parameters is a real problem with the increase in the number of response variables or with the increase in the number of time points. The problem becomes more intricate and involved with the addition of additional random effects. A multivariate analysis is not possible in a small sample setting. We propose a method to estimate these many parameters in bits and pieces from baby models, by taking a subset of response variables at a time, and finally using these bits and pieces at the end to get the parameter estimates for the mother model, with all variables taken together. Applying this method one can calculate the fixed effects, the best linear unbiased predictions (BLUPs) for the random effects in the model, and also the BLUPs at each time of observation for each response variable, to monitor the effectiveness of the treatment for each subject. The proposed method is illustrated with an example of multiple response variables measured over multiple time points arising from a clinical trial in osteoporosis.