Given that the goal of this study was to examine the influence of different factors on a firm’s profitability, we designed a model with three categories of profitability determinants: firm-specific, industry-specific and macroeconomic. The analysis was performed on 9359 firms operating in the Croatian manufacturing industry during the 2006–2015 period. Since the designed model was formulated in a way that encompasses the dynamic aspect of profitability, the General Method of Moments (G.M.M.) dynamic panel estimator was applied. Formulation of such a model adds to the existing literature if one takes into account that a dynamic analysis of the drivers of profitability has not been done using data from the Croatian manufacturing sector. The results of the conducted analysis revealed that a firm’s age, labour cost and industry concentration, as well as G.D.P. growth and inflation, have significant influence on a firm’s profitability.

The aim of this research was to explore one of the most intriguing dimensions of every firm’s business—its performance. Aside from analysing the influence of industry’s characteristics on the firm’s performance, the authors addressed the characteristics of dynamic capabilities and their role in contribution to the firm’s ultimate success. The analysis was conducted on a sample of 118 small Croatian manufacturing companies. The application of the Structural Equation Modelling (SEM) approach revealed a statistically significant influence of both the industry’s characteristics (represented by Porter’s five forces framework) and dynamic capabilities (based on Teece’s theory) on the firm’s performance, where the influence of dynamic capabilities is proven to be larger than that of the industry.

The aim of this research was to determine the persistence of profit in an emerging banking sector of the Republic of Croatia. Most developing countries have experienced common changes within restructuring of the banking system and therefore, this issue has become crucial, especially after comparing poor empirical findings in these countries to the findings of developed countries. However, research related to this issue is non-existent in the Croatian banking sector. Moreover, among the few studies that were carried out on the territory of the Central and Eastern European banking markets, none of the studies have analysed the persistence of profit in terms of the Markov Chain stochastic process. In addition to the profit persistence analysis, authors defined and estimated a model that would enable the identification of the profitability determinants of Croatian banks. In this sense, the model incorporated three groups of profitability determinants: bank-specific, industry-specific and macroeconomic. The variables with a statistically significant impact on the profitability of banks were identified using a dynamic panel model, while the application of the Markov Chains stochastic process revealed that profit persistence was less likely to occur in banks with higher profit.

A company”s profitability has always attracted the attention of academics and practitioners interested in revealing the main factors that determine business success. Although profitability has been widely investigated in manufacturing industry as a whole, studies related to the individual sectors within this industry are fairly rare. This is especially true for the food and beverage industry. Accordingly, the aim of this paper was to investigate the factors that determine companies” profitability in the Croatian food and beverage industry during the period from 1999 to 2009. The results of the conducted dynamic panel analysis revealed negative and significant influence of company”s debt ratio on profitability; and significant positive influence of company”s size, concentration ratio and past performance on current profitability. Additionally, MES, risk, and asset turnover had no significant role in determining profitability.

Purpose: The aim of this paper is to analyze overall technical efficiency (OTE), pure technical efficiency (PTE) and scale efficiency (SE) of both life and non-life insurance sectors in three Central and Eastern European countries (CEE), i.e. Croatia, Hungary and Poland, in 2018. Methodology: The efficiency of insurance sectors is estimated by applying data envelopment analysis (DEA), while a one-way analysis of variance (ANOVA) is performed to find out whether there exists any statistically significant difference between the estimated levels of the efficiency of non-life and life insurance sectors in the observed CEE countries. Results: Out of 34 non-life Polish insurers, only two (6%) were overall technically efficient, while the remaining 32 were inefficient. Croatia and Hungary achieved better results with three (20%) and seven (43.7%) efficient insurers, respectively. However, when observing the life insurance segment, half of the Croatian life insurers were efficient according to the CCR model, while six (23%) Polish and three (23%) Hungarian efficient insurers were recorded. Conclusion: Research reveals that the Hungarian non-life insurers are the most efficient ones in terms of OTE, PTE and SE. They are followed by the Croatian insurers, leaving the Polish insurers behind. Regarding the life insurance sector, the domination of the Croatian insurers is recorded, while the Hungarian ones were found to be the least efficient. Moreover, inefficiency in both life and non-life sectors (except for the Hungarian life sector) is more related to scale than to managerial inefficiency. Finally, ANOVAs and Tukey post hoc tests revealed a statistically significant difference among considered groups of insurers.

Accession of Croatia to the EU brought legal, regulatory and market changes for the insurance companies. The question that arises is whether the new environment in which the companies operate has improved their efficiency. Accordingly, the aim of this paper is to separately estimate the efficiency of non-life and life insurance industry in Croatia and to compare it through the period before (2009-2012) and after (2013-2018) Croatian accession to the EU. The research is based on the Data Envelopment Analysis and the obtained results indicate an average increase in overall technical efficiency in both, non-life and life sector in period after Croatia’s accession to the EU. Still, this increase was not proved to be significant. Additionally, although increase in pure technical efficiency was significant in non-life sector, an insignificant slight decrease is recorded in life sector. Finally, insurers conducting (non)life business activities are mainly operating at increasing returns to scale.