Browsing by Author "Lundgren, Sofia"

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A group's acquisition of a family business -Change in the Management Control Systems at an operative level
(2014-09-24) Lundgren, Sofia; Andrén, Nathalie; University of Gothenburg/Department of Business Administration; Göteborgs universitet/Företagsekonomiska institutionen
Background and problem: Changes in the ownership structure and growth are two examples of variables that can change the management control systems. There are literatures that carefully describe how the controlling elements change when growing internally. These literatures combined with acquisition theories have been used to discuss the changes in the management control systems in this case study. Most of earlier researches have been done on the top-level management. Purpose: The purpose of this thesis is to see how the management control systems change at an operative level when a family business transforms into a unit of a big group trough an acquisition. Methodology: This research is a qualitative case study on a gym facility in Askim, Gothenburg. The theoretical framework is based on theories from experts within the concerned field. Most of the empirical data have been collected by in-depth interviews with employees and customers. Discussion and Conclusion: The family business was mainly controlled by corporate culture with shared values. After the acquisition this informal control changed to formal control with formalized routines and strict budgets. The facility went from using interactive to diagnostic control were goals got explicit and individual goals connected with rewards got introduced. After the acquisition the employees and managers did not feel supervised anymore and were able to work more independently. Further research: It could be interesting to do further research on a big company with a more controlling top-management. Studies about rewards systems combined with acquisition would also probably contribute to the research.
Decision Making in an Organization without Managers
(2016-09-20) Andersson, Lisa; Lundgren, Sofia; University of Gothenburg/Graduate School; Göteborgs universitet/Graduate School
This paper discusses the phenomena of an organization that has chosen to structure their firm without hierarchical layers and management positions, and how decision making unfolds in an organization as such. The research is conducted on a Gothenburg-based “app” firm, through an in-depth case study. Due to the lack of managers, the company has chosen to distribute the leadership among all organizational actors. The aim of this paper is therefore to answer how organizational activities such as decision making plays out in a firm structured without managers. Our findings show that an organization who tries to break out of the institution by not having managers, makes decisions through four different constellations; individual, small teams, big team and combined. Thereby, decision making appears to be a social process. Furthermore, the study shows that these four processes are impacted by the institutional pressure the organization experiences, but also adapted to the characteristics of the decisions that are to be made.
Importance of daily data in long horizon inflation forecasting - a MIDAS approach
(2018-02-19) Ekström, Katrin; Lundgren, Sofia; University of Gothenburg/Department of Economics; Göteborgs universitet/Institutionen för nationalekonomi med statistik
We examine the accuracy of forecast models for the monthly Euro area inflation, focusing on the MIDAS approach. We compare two mixed frequency models with four low frequency models, using fourteen mixed frequency variables sampled at daily or monthly frequency. Our data set covers the period of February 1999 until August 2017, and we use a 10-year rolling window to construct the forecasts. We use MIDAS models with one- respectively five-month lags, as these specifications provide the lowest average MSEs. Our findings show that the MIDAS model with five month lags perform better in-sample compared to the MIDAS model with one-month lag. The opposite applies for our out-of-sample forecasts. Furthermore, our findings suggest, in line with previous findings, that the MIDAS models perform well for short forecast horizons. On the contrary to previous research, we find that the MIDAS models provide worse forecasts than an AR(1) for longer forecast horizons.