Abstract. The main objective of this paper is to present an empirical application of the DEA method, by proposing an adequate model for determining the relative efficiencies of seven Croatian airports, and by analysing the obtained scores. To highlight different crucial aspects of airport performance in Croatia, four indicators are used for the period 2009-2014: personnel costs/airport throughput unit (ATU), total expenditures excluding personnel costs/ATU and total assets/ATU as input variables, while the output variable is total revenue/ATU. To overcome certain limitations associated with the relationship between the number of the observed entities and the number of employed variables, and to provide dynamic efficiency results that usually reflect reality better than static ones, window analysis is used as an extension of basic input-oriented DEA models. In general, the findings indicate that, over the observed period, performance rankings change, and, with the exception of the last observed year, the relative performance of Croatian airports is gradually declining. Consequently, the airports of Split, Pula and Zadar were found to be efficient ("best practice" airports) in the four years, and the airports of Zagreb and Osijek in one single year. Based on the efficiency score averaged across the observed period, Split turned out to be most efficient whilst Osijek appeared to be least efficient. Total assets per ATU are identified as the most significant source of inefficiency. Using both constant and variable returns to scale assumptions, this paper is the first to decompose the technical efficiency of Croatian airports into two components -pure technical efficiency, which reflects the ability of an airport to obtain maximal outputs at an optimal scale, and scale efficiency, which reflects the distance of an observed airport from the most productive scale size. The significance of these results is in the fact that they offer the possibility of directly identifying inefficiency causes, and can serve as a basis for an a posteriori correction of previously made disadvantageous decisions.
Abstract. The approach used in this paper expands on existing research that focuses on devising prediction models for companies experiencing financial difficulties and which in turn serves as a criteria-based diagnosis tool for distinguishing healthy companies from those facing seriously financial difficulties. It draws on auditors' reports on company financial statements that emphasize a company's ability to continue as a going concern as the main criterion used to distinguish companies experiencing financial difficulties from companies that are not. Two closely-related hypotheses were tested in this paper. First, the authors tested the hypothesis that an auditor's report accompanied by an explanatory paragraph pointing out issues associated with the going concern assumption is the proper criterion for differentiating companies experiencing financial difficulties from those that are not. Second, the central assumption that is tested relates to a combination of financial ratios whereby authors presume that an appropriate combination of financial ratios is a good analytical tool for distinguishing companies experiencing serious financial difficulties from those that are not. Research results conducted among 191 companies listed on the Zagreb Stock Exchange confirm both hypotheses. The LRA model -a diagnosis tool for identifying companies with financial problems, was also derived using logistic regression analysis. The statistical adequacy and quality of the model was tested using measures like Nagelkerke R2, type 1 and type 2 errors that appear when calculating the classification ability of the model. All measures indicated that model was statistically sufficient and validated its use as a diagnosis tool in recognizing the companies facing financial difficulties.
Case-based reasoning represents a method for solving problems and decision making support which is based on the previous business experience. It uses cases from the past to solve new problems. Case can be defined as conceptualized piece of knowledge representing the experience that teaches a lesson fundamental to achieving the goals of the decision maker and it usually incorporate input (situation part of the case) and output features (solution part of the case). Many studies tried to explain types and impact of different factors that determine audit fees. Mostly all authors concentrate their research on the impact of following determinants: auditee size, auditee complexity, auditee profitability, ownership control, timing variables, auditor location and auditor size. In paper all mentioned factors are described except auditor size and location since these factors are not significant in Croatian audit service market. All significant audit fee determinants will be appropriately quantified in order to build a case-based reasoning model for determining audit fee for smaller and mid sized auditing firms in Croatia but also for the same firms in the other, particularly transition, countries too.
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