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The purpose of this paper is to explore the effects of cross-border acquisitions on the efficiency and productivity of acquired companies in the cement industry in the context of a transitional economy.

The Data Envelopment Analysis (DEA) and Malmquist Productivity Index were used to assess the efficiency and productivity of the acquired companies over the period 2000–2018. DEA and Malmquist index are combined with bootstrapping to perform succinct statistical inferences for determining the accuracy of results. The study assesses partial efficiency and productivity of three inputs: material, capital and labour, as well as the total factor efficiency and productivity of the acquired companies in the short and long term after the acquisitions.

The research results suggest that efficiency of material, efficiency of labour and the total factor efficiency of the acquired companies are higher after the acquisitions than before, while efficiency of capital is lower. In addition, the results show that the acquisitions had a positive impact on total factor productivity of the acquired companies.

The results of this study have practical implications for managers, especially for policy-makers and industry analysts in deciding whether to encourage or discourage cross-border acquisitions in transitional economies.

The study contributes to a better understanding of the impact of cross-border acquisitions on efficiency and productivity of acquired companies in the manufacturing industry. Research in transitional economies related to subject matter is limited, and this study is the first empirical investigation of the effect of cross-border acquisitions on the efficiency and productivity in the cement industry in Serbia by applying the Data Envelopment Analysis.

This paper explores the impact of international acquisitions on the efficiency and productivity of the cement industry in an emerging economy.

The data envelopment analysis (DEA) and Malmquist index (MI) are used to calculate the partial efficiency and productivity of individual inputs (materials, labour and fixed assets), as well as the total factor efficiency and productivity during the period 2000–2018. DEA and MI are combined with bootstrapping to perform succinct statistical inferences for determining the accuracy of results. In this paper we apply the input-oriented CCR DEA Window model. With respect to the level of analysis, data was collected from individual companies and then aggregated data at the industry level.

The research results show that international acquisitions positively affect efficiency of the cement industry in the long term. Efficiency of capital is lower in the short period after acquisitions. Additionally, international acquisitions positively affect partial productivity, as well as total factor productivity of the cement industry.

The results of the study may be significant for managers and policy makers to design appropriate strategies for the improvement of the cement industry performance over time.

Research in emerging economies related to subject matter is limited, and this is one of the earliest research studies which explore change in efficiency and productivity at the level of Serbian cement industry.

The purpose of this paper is an analysis of the process of digital transformation of enterprises, by measuring the efficiency of the use of information and communication technologies (ICTs) in business in 29 European countries in the period from 2012 to 2020.

A Charnes, Cooper and Rhodes data envelopment analysis (CCR DEA, 1978) window model has been developed to measure the ICT efficiency of European countries. Several indicators of the use of information and communication technologies in enterprises are selected as the variables of the proposed models, which are available as such in the Eurostat database for European countries. Due to the sensitivity of the results obtained by applying the DEA method to measurement errors and output values, the robustness analysis of the obtained values of average efficiency is also performed, using the bootstrap method.

The obtained results show that the highest average technical efficiency of the use of ICT in companies by windows, in the observed period, is recorded in Belgium, while Denmark is in the second place. Bulgaria, Romania, Greece and Latvia have the lowest average technical ICT efficiency per window. The analysis of the obtained results by years in the same period brings identical conclusions. Only Belgium has been ICT efficient many times. In general, for all observed countries, the movement of average ICT efficiency in the observed period shows a slightly growing trend, with the exception of a significantly decline in 2013. However, the fact is that the ICT efficiency of the observed countries in the past period is relatively low and for all countries it is 46.36%, with no country being 100% efficient and with eight countries whose average efficiency is below 50% of best practice.

To measure and evaluate the efficiency of ICT use in enterprises, four variables for efficiency assessment are identified, given the fact that only these data are available continuously for the observed period from 2012 to 2020 in the Eurostat database.

Low efficiency of using digital potential in business of the observed countries indicates the need for better understanding of the nature and goals of the digital business transformation process by employees and management, to create conditions for effective implementation and optimization of business digitalization.

Measurement of digital transformation is the subject of a very small number of studies and research, which mainly focus on measuring and assessing the impact of digital transformation on individual countries and perform a comparative analysis of technological development in those countries. Also, analyses are mainly based on identifying similarities and differences between countries or ranking countries according to adopted evaluation criteria using different digitization indices. A step forward in this research is the application of the DEA window method for measuring the relative efficiency of the use of ICT in enterprises, and the development of a model that can be extended if necessary with indicators for which data are available.

The paper analyzes the relative technical efficiency of the transition economies of the Western Balkans in the period 2007–2021, in comparison with the former countries with a socialist state system, today members of the European Union (EU), based on selected macroeconomic indicators and panel data.

Data envelopment analysis (DEA), i.e. its extension, DEA Window analysis, is applied. Total technical efficiency, as a prerequisite of economic efficiency, is decomposed into pure technical efficiency (PTE) and scale efficiency (SE). Bootstrapping method and Mann–Whitney U test were used to check the robustness of the obtained results, i.e. efficiency values.

The results show that in 2020, all observed countries recorded a significant drop in economic efficiency as a result of a general, disproportionate drop in the value of selected macroeconomic variables, which occurred due to the global economic crisis and the slowdown in economic activity caused by the COVID-19 pandemic. This drop in efficiency was significantly greater in the former socialist states, now members of the European Union, which showed their greater sensitivity to global crises. None of the observed economies in the observed period was relatively efficient, that is, at the level of best practice, which occurred primarily as a consequence of the inefficiency of business conditions expressed in the economies of scale.

The main limitation of this study stems from the very nature of the concept of DEA efficiency, which is relative in nature. Also, the results and their interpretation are also significantly influenced by the choice of model variables, as shown by Lábaj et al. (2013), as well as a small number of decision-making units (DMUs). The mentioned limitations prevent unambiguous interpretation and generalization of the obtained results.

The study may be of importance to economic policy makers in macroeconomic decision-making. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage on the international market.

Since research of this type is very limited, the results of this study make a theoretical and empirical contribution to the literature, creating a basis for future research and reexamination. The application of the DEA concept in measuring the technical efficiency of national economies is a useful tool in the analysis of macroeconomic performance and a benchmarking approach for positioning and achieving competitive advantage in the international market.

The aim of this paper is to evaluate the intensity and success of the digitalization process, by measuring the efficiency of the use of information and communication technologies in business in the Republic of Serbia (RS) in the period from 2006 to 2019.

The data envelopment analysis method is applied and due to the sensitivity of the results to measurement errors, the robustness analysis of the obtained values of average efficiency is performed, using the bootstrapping method.

The results show an intensive, expansive and relatively efficient process of digital business transformation in the RS. The results indicate inefficient use of software packages, While the efficiency of e-commerce in companies in most years is over 80%.

The research is limited to the RS, so the conclusions cannot be generalized in a broader context.

The biggest problem in the implementation of digital business transformation in the RS is the understanding of management and employees in organizations that digital business transformation will take place only if software solutions are purchased and installed, with less attention paid to their proper application and low use of their maximum capabilities.

Digital transformation measurement is the subject of a very small number of studies. Through a review of the literature, the authors of this paper do not find the use of data envelopment analysis to measure the efficiency of digital business transformation in the way they present it in this paper.

With the expansion of dining out, visiting ethnic restaurants is becoming one of dominant trends worldwide. Given the fact that ethnic restaurants involve a number of peculiar elements that are not present when visiting regular “local” restaurants, the purpose of this paper is to identify the key determinants of choosing a particular ethnic-themed restaurant, as well as factors that have an impact on an ethnic restaurant’s perceived image.

Research was done by conducting two separate studies. The first study identified factors that were generally the most significant to respondents when making a choice of an ethnic restaurant in which to dine. For the second study, a new sample of respondents – consisting of those who had just visited such an establishment – was used in order to determine which factors have the most significant impact on creating an image of ethnic restaurants. The research was therefore directed toward those restaurants where the customers can experience a unique atmosphere and ambiance that are synonymous within a given culture.

The results obtained from the first study show that quality of food and price are the two most significant factors that determine which restaurant will be visited. On the other hand, the interior and exterior ranked as the two least important factors. In addition, the second study revealed that following the visit, the strongest impact on the restaurant’s image was its interior. Following interior, service quality surfaced as the most important antecedent of perceived image, while the impacts of price and exterior were weaker, but still statistically significant.

The study itself was done in two stages. In the first stage the analytical hierarchical process (AHP) model was used for ranking factors significant for choosing an ethnic restaurant, while in the second stage, structural equation modeling (SEM) model was used to identify triggers of perceived image after a visit to an ethnic restaurant. Future research should utilize both models to determine antecedents of the variables used. Apart from this, it is recommended to employ new variables that further explore the uniqueness of the ethnic restaurants.

One of the main contributions of this work is related to combining of the AHP and SEM models, with the objective of completing a comparative results analysis, identifying in the process the positive aspects of both models and building a foundation for their coordination in terms of future use. This is significant, given that only a few prior studies have used such synergy.