Snow cover models in operational watershed forecasting

Yhteenveto: Lumimallit vesistöjen ennustemalleissa

'... the walls fell down but the blokes just coded ...' - Varieties of stability in software product development during organizational restructurings

Many Finnish IT companies have gone through numerous organizational changes over the past decades. This book draws attention to how stability may be central to software product development experts and IT workers more generally, who continuously have to cope with such change in their workplaces. It does so by analyzing and theorizing change and stability as intertwined and co-existent, thus throwing light on how it is possible that, for example, even if ‘the walls fall down the blokes just code’ and maintain a sense of stability in their daily work. Rather than reproducing the picture of software product development as exciting cutting edge activities and organizational change as dramatic episodes, the study takes the reader beyond the myths surrounding these phenomena to the mundane practices, routines and organizings in product development during organizational change. An analysis of these ordinary practices offers insights into how software product development experts actively engage in constructing stability during organizational change through a variety of practices, including solidarity, homosociality, close relations to products, instrumental or functional views on products, preoccupations with certain tasks and humble obedience. Consequently, the study shows that it may be more appropriate to talk about varieties of stability, characterized by a multitude of practices of stabilizing rather than states of stagnation. Looking at different practices of stability in depth shows the creation of software as an arena for micro-politics, power relations and increasing pressures for order and formalization. The thesis gives particular attention to power relations and processes of positioning following organizational change: how social actors come to understand themselves in the context of ongoing organizational change, how they comply with and/or contest dominant meanings, how they identify and dis-identify with formalization, and how power relations often are reproduced despite dis-identification. Related to processes of positioning, the reader is also given a glimpse into what being at work in a male-dominated and relatively homogeneous work environment looks like. It shows how the strong presence of men or “blokes” of a particular age and education seems to become invisible in workplace talk that appears ‘non-conscious’ of gender.

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.

Dynamic Factor Models and Forecasting Finnish Macroeconomic Variables

In recent years, thanks to developments in information technology, large-dimensional datasets have been increasingly available. Researchers now have access to thousands of economic series and the information contained in them can be used to create accurate forecasts and to test economic theories. To exploit this large amount of information, researchers and policymakers need an appropriate econometric model.Usual time series models, vector autoregression for example, cannot incorporate more than a few variables. There are two ways to solve this problem: use variable selection procedures or gather the information contained in the series to create an index model. This thesis focuses on one of the most widespread index model, the dynamic factor model (the theory behind this model, based on previous literature, is the core of the first part of this study), and its use in forecasting Finnish macroeconomic indicators (which is the focus of the second part of the thesis). In particular, I forecast economic activity indicators (e.g. GDP) and price indicators (e.g. consumer price index), from 3 large Finnish datasets. The first dataset contains a large series of aggregated data obtained from the Statistics Finland database. The second dataset is composed by economic indicators from Bank of Finland. The last dataset is formed by disaggregated data from Statistic Finland, which I call micro dataset. The forecasts are computed following a two steps procedure: in the first step I estimate a set of common factors from the original dataset. The second step consists in formulating forecasting equations including the factors extracted previously. The predictions are evaluated using relative mean squared forecast error, where the benchmark model is a univariate autoregressive model. The results are dataset-dependent. The forecasts based on factor models are very accurate for the first dataset (the Statistics Finland one), while they are considerably worse for the Bank of Finland dataset. The forecasts derived from the micro dataset are still good, but less accurate than the ones obtained in the first case. This work leads to multiple research developments. The results here obtained can be replicated for longer datasets. The non-aggregated data can be represented in an even more disaggregated form (firm level). Finally, the use of the micro data, one of the major contributions of this thesis, can be useful in the imputation of missing values and the creation of flash estimates of macroeconomic indicator (nowcasting).