No abstract

CHANDRAPALA PATHIRAWASAM, KNÁPKOVÁ ADRIANA: Firm-specifi c factors and fi nancial performance of fi rms in the Czech Republic. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2013, LXI, No. 7, pp. 2183-2190 The objective of this study is to investigate the role of internal factors in generating fi nancial performance of fi rms in the Czech Republic. The paper examines the impact of fi rm specifi c factors on company fi nancial performance of 974 fi rms in the Czech Republic over the period 2005 to 2008, using data in the Albertina database. Pooled and panel cross-sectional time series techniques are used for the data analysis. Return on Assets (ROA) is the dependent variable of the model and eight fi rm specifi c factors are introduced as the explanatory variables. Using Return on Assets as the dependent variable, it is established that the fi rm size, sales growth and capital turnover are having signifi cant positive impact on fi nancial performance of fi rms. At the same time, debt ratio and inventory refl ect signifi cant negative impact on fi nancial performance of fi rms. Overall explanatory powers of the two models are low and further research is necessary to increase the statistical power of the model. The results from the present study may be very encouraging and useful for managers as well as investors to plan investment and operational activities to achieve profi tability objectives more effi ciently and eff ectively. The fi ndings have important managerial implications. fi nancial performance, Czech Republic, return on assets (ROA), fi rm specifi c factors

Previous research presented in numbers of studies strongly suggests that locating in a cluster generates valuable benefits to clustered firms. These include better access to suppliers and other scarce inputs, superior knowledge and innovation, a better position from which to build a social network as well as proximate to successful competitors. Yet when the positive impact of agglomeration and clustering has been questioned on the strictly financial performance of clustered firms, the results of these studies are not so convincing and question the enthusiasm for cluster theory shown by scholars, practitioners, and policymakers. The aim of our research is to enrich existing knowledge concerning the benefits of clustering, as well as to test if localisation in a natural cluster, and membership in a cluster organisation has a positive impact on financial performance. We propose to measure that by selected financial indicators such as ROA, ROS, labour productivity and Economic Value Added, focussing our research on traditional industrial sectorsplastics and textiles seated in the Czech Republic. The results of analysing firm-level data in the period of 2009-2016 fail to confirm any significant influence of firm localisation in natural cluster or membership in the cluster organisation on financial performance for firms in studied sectors. We achieved the same results by investigation of potential differences for young firms, SMEs or underperforming firms.

The choice of a suitable measure for company's performance and identification of key performance indicators are among the most frequently discussed topics in the field of corporate management strategizing. This paper shows how the value-based measure represented by Economic Value Added (EVA) and its pyramidal breakdown could act as facilitators in revealing value drivers. The univariate sensitivity analysis and the Stochastic Frontier Analysis are employed to identify the key performance indicators. The analysis is based on the samples of original equipment manufacturers and suppliers in Czech automotive sector. The automotive industry, in general, is sensitive to the business cycle. Therefore, KPIs of the multiple EVA/Sales distinguished for the samples in the Precrisis, Crisis and Post-crisis periods are identified. The detailed sensitivity analysis reveals several differences in these periods in both samples and across companies of different sizes. Some of the results are further confirmed by the Stochastic Frontier Analysis. Besides other indicators, value added is demonstrated as the key driver with the highest positive impact and personnel cost with the highest negative impact on EVA in all periods although the magnitude of these effects is changing. Analysis of the technical efficiency scores reveals that companies in the crisis periods are more similar to each other and are closer to the best-performing companies than in other periods.

No abstract