Classification and Efficiency Analysis of Slovenian Restaurant SMEs

Abstract

Focusing on the characteristics of restaurant smes, the purpose of this paper is to use (1) a cluster analysis (ca), and (2) data envelopment analysis (dea) approach to classify restaurant smes into different groups based on their physical and managerial characteristics and attempts to determine whether differences exist in the efficiency performance of different groups. The study has conducted a two-step ca and dea analysis to identify the effects of restaurant characteristics on efficiency performance. This method takes into consideration the presence of heterogeneous subsets in efficiency assessment. Restaurants were preselected based on their operational characteristics. smes whose only source of income was their restaurant business were included in the study. Surveys were performed with restaurant managers, and the firms' financial reports were analysed. Two diverse groups were identified: smaller restaurants with younger and less experienced managers, and bigger restaurants with older and more experienced managers. The various physical (number of seats, years of business activity) and managerial (age, and professional experience) characteristics appeared to significantly affect restaurant types differently. Established restaurants with more seats, older and more experienced managers proved to be more efficient. This is the very first study to analyse Slovenian restaurant businesses efficiency with a combined ca-dea approach. Primary data was collected by surveying restaurant managers while secondary financial data was provided by national tax authorities after the implementation of fiscal cash registers.

COVID-19’s Impact on the Restaurant Industry

“…Regarding the debt of restaurant businesses, Planinc and Kukanja [43] argue that these companies have difficulties in achieving positive financial results. Vivel-Búa et al [40] state that location influences indebtedness.…”

Efficiency analysis of Indian banking industry over the period 2008–2017 using data envelopment analysis

“…Further, DEA has been applied to analyze hotel efficiency (Alberca-Oliver et al , 2015; Barros, 2005) and restaurant efficiency (Assaf et al , 2010; Fang and Hsu, 2014). Both cluster analysis and DEA has been applied to assess efficiency of Slovenian restaurant SMEs by Planinc et al (2018). In higher education and universities, efficiency analysis is done through internal performance indicators, indicators of operational performance, external performance indicators and research performance indicators (Chalmers, 2008; Pereira and Tavares, 2002; Ward, 2007).…”

Cost-Effective Service Excellence: Exploring the Relationships Among Restaurants’ Operational Efficiency, Size and Service Quality

“…Operational financial data, which were obtained from SMEs' official financial reports (the latter are in public domain) were used as variables to perform DEA. As suggested by Barros and Santos (2006), and Planinc, Kukanja, and Planinc (2018), the following groups of variables were included in the model -costs of goods sold, material and services, labour costs, and write-downs (as inputs), and net sales revenues (as output). First, we ensured that all inputs were statistically correlated (p<0.01) to the output (Reynolds and Thompson 2007).…”