Methods in general model localization

The aim of this study was to evaluate and test methods which could improve local estimates of a general model fitted to a large area. In the first three studies, the intention was to divide the study area into sub-areas that were as homogeneous as possible according to the residuals of the general model, and in the fourth study, the localization was based on the local neighbourhood. According to spatial autocorrelation (SA), points closer together in space are more likely to be similar than those that are farther apart. Local indicators of SA (LISAs) test the similarity of data clusters. A LISA was calculated for every observation in the dataset, and together with the spatial position and residual of the global model, the data were segmented using two different methods: classification and regression trees (CART) and the multiresolution segmentation algorithm (MS) of the eCognition software. The general model was then re-fitted (localized) to the formed sub-areas. In kriging, the SA is modelled with a variogram, and the spatial correlation is a function of the distance (and direction) between the observation and the point of calculation. A general trend is corrected with the residual information of the neighbourhood, whose size is controlled by the number of the nearest neighbours. Nearness is measured as Euclidian distance. With all methods, the root mean square errors (RMSEs) were lower, but with the methods that segmented the study area, the deviance in single localized RMSEs was wide. Therefore, an element capable of controlling the division or localization should be included in the segmentation-localization process. Kriging, on the other hand, provided stable estimates when the number of neighbours was sufficient (over 30), thus offering the best potential for further studies. Even CART could be combined with kriging or non-parametric methods, such as most similar neighbours (MSN).

Struggles Over Legitimacy in Global Organizational Restructuring: A Rhetorical Perspective on Legitimation Strategies and Dynamics in a Shutdown Case

Critical organization scholars have focused increasing attention on industrial and organizational restructurings such as shutdown decisions. However, little is known about the rhetorical strategies used to legitimate or resist plant closures in organizational negotiations. In this article, we draw from New Rhetoric to analyze rhetorical struggles, strategies and dynamics in unfolding organizational negotiations. We focus on the shutdown of the bus body unit of the Sweden-based Volvo Bus Corporation in Finland. We distinguish five types of rhetorical legitimation strategies and dynamics. These include the three classical dynamics of logos (rational arguments), pathos (emotional moral arguments), and ethos (authority-based arguments), but also autopoiesis (autopoietic narratives), and cosmos (cosmological constructions). Our analysis contributes to previous studies on organizational restructuring by providing a more nuanced understanding of how contemporary industrial closures are legitimated and resisted in organizational negotiations. This study also increases theoretical understanding of the role of rhetoric in legitimation more generally.