Variations in Strategy Perception among Business and Military Managers

The paper aims to identify the similarities and differences in the emphases and patterns that military and civilian managers attribute to strategy. Two different analysis methods were employed in order to achieve abovementioned research objective. In the first method, the aim was to reveal and compare strategy understanding of the sample groups. Towards that end, ten different strategy definitions and nine different necessity statements compiled from various definitions/statements in the existing strategic management literature were provided to the samples. Then, the samples were requested to consider how strategy and necessity of strategy is formed in their minds, and then to choose top three definitions out of 9/10, and finally rank them in preference order, from one to three. Lastly, we counted the ranks/perceived importance of the various strategy definitions and necessity statements that which statement is ranked to which place. Using mean rank assessment by nonparametric comparison method the study shows differences between military and civilian managers in following aspect: the comparison of the emphases that are attributed to approach to strategy identified significant differences among business and military managers. Concisely, the paper reveals the varying perceptions of business and military managers on strategy based on their personal perceptions.

Use of Depth Measure for Multivariate Functional Data in Disease Prediction: An Application to Electrocardiograph Signals

In this paper we develop statistical methods to compare two independent samples of multivariate functional data that differ in terms of covariance operators. In particular we generalize the concept of depth measure to this kind of data, exploiting the role of the covariance operators in weighting the components that define the depth. Two simulation studies are carried out to validate the robustness of the proposed methods and to test their effectiveness in some settings of interest. We present an application to Electrocardiographic (ECG) signals aimed at comparing physiological subjects and patients affected by Left Bundle Branch Block. The proposed depth measures computed on data are then used to perform a nonparametric comparison test among these two populations. They are also introduced into a generalized regression model aimed at classifying the ECG signals.