The Survivability of Swedish Emergency Management Related Research Centers and Academic Programs : A Preliminary Sociology of Science Analysis

The Survivability of Swedish Emergency Management Related Research Centers and Academic Programs: A Preliminary Sociology of Science Analysis Despite being a relatively safe nation, Sweden has four different universities supporting four emergency management research centers and an equal and growing number of academic programs. In this paper, I discuss how these centers and programs survive within the current organizational environment. The sociology of science or the sociology of scientific knowledge perspectives should provide a theoretical guide. Yet, scholars of these perspectives have produced no research on these related topics. Thus, the population ecology model and the notion of organizational niche provide my theoretical foundation. My data come from 26 interviews from those four institutions, the gathering of documents, and observations. I found that each institution has found its own niche with little or no competition – with one exception. Three of the universities do have an international focus. Yet, their foci have minimal overlap. Finally, I suggest that key aspects of Swedish culture, including safety, and a need aid to the poor, help explain the extensive funding these centers and programs receive to survive. 

Performance determinants For Swedish Financial Monetary Institutions: Panel Data evidence between 2010-2014.

Due to the rapid changes that governs the Swedish financial sector such as financial deregulations and technological innovations, it is imperative to examine the extent to which the Swedish Financial institutions had performed amid these changes. For this to be accomplish, the work investigates what are the determinants of performance for Swedish Financial Monetary Institutions? Assumptions were derived from theoretical and empirical literatures to investigate the authenticity of this research question using seven explanatory variables. Two models were specified using Returns on Asset (ROA) and Return on Equity (ROE) as the main performance indicators and for the sake of reliability and validity, three different estimators such as Ordinary Least Square (OLS), Generalized Least Square (GLS) and Feasible Generalized Least Square (FGLS) were employed. The Akaike Information Criterion (AIC) was also used to verify which specification explains performance better while performing robustness check of parameter estimates was done by correcting for standard errors. Based on the findings, ROA specification proves to have the lowest Akaike Information Criterion (AIC) and Standard errors compared to ROE specification. Under ROA, two variables; the profit margins and the Interest coverage ratio proves to be statistically significant while under ROE just the interest coverage ratio (ICR) for all the estimators proves significant. The result also shows that the FGLS is the most efficient estimator, then follows the GLS and the last OLS. when corrected for SE robust, the gearing ratio which measures the capital structure becomes significant under ROA and its estimate become positive under ROE robust. Conclusions were drawn that, within the period of study three variables (ICR, profit margins and gearing) shows significant and four variables were insignificant. The overall findings show that the institutions strive to their best to maximize returns but these returns were just normal to cover their costs of operation. Much should be done as per the ASC theory to avoid liquidity and credit risks problems. Again, estimated values of ICR and profit margins shows that a considerable amount of efforts with sound financial policies are required to increase performance by one percentage point. Areas of further research could be how the individual stochastic factors such as the Dupont model, repo rates, inflation, GDP etc. can influence performance.