This article deals with the Analytic Hierarchy Process (AHP) method, which can be calculated in several ways. The aim of the paper is to analyze and describe the AHP method as essential for strategic managerial decision-making to determine which method is efficient for the calculation and to set the proper order of criteria. In the contribution, we show how the AHP method can be used through different techniques. In the article, there are included methods that can be used in order to calculate the matrix in the AHP process for setting criteria. This study also focused on the accuracy of various methods used to compute AHP. The paper contains the procedure of using the Saaty method through the Excel program. The results of the research show that the most accurate method is the Saaty method. In comparison with the Saaty method is the geometric mean method with the slightest deviation (CI = 0.00010), followed by the Row sum of the adjusted Saaty matrix with deviation (CI = 0.00256), reverse sums of the Saaty matrix columns (CI = 0.00852), Arithmetic mean and Row sums of the Saaty matrix (CI = 0.01261). All of these methods are easy to calculate and can be performed without major mathematical calculations. The AHP method is often used with other methods such as SWOT, FUZZY, etc. The survey was carried out through an inquiry with managers who graduated from universities in Slovakia and showed that the respondents considered the Saaty method as the most complex and the most difficult. The geometric mean and average mean methods were regarded as the simplest methods. Respondents (44%) stated that they were able to use a program to calculate the AHP. Respondents (46%) had experience with some method related to the strategic managerial decision-making process. Managers (72%) regarded this skill as important for decision-making in their managerial position. The contribution of this paper is to show the advantages of the AHP method in its wide use in various fields.

Digital technologies play a key role in reviving the world economy. The EU has pledged to combine recovery support with resilient digital transformation. The COVID-19 pandemic highlighted the lack of digitization in Slovakia and the shortcomings of digital skills in citizens and communication with institutions. Digital skills are important and should form part of educational policy. ICT skills can help people succeed in the labour market and improve communication with public administration. Digitization and globalization increase the importance to communicate through the Internet, applications, and other e-based gadgets. Digital skills are one of the essential parts of e-Government, so people can use e-Government services in communication with public administration. The current crisis is affecting citizens’ use of online services. Indices concerning the digital economy are analysed, such as the digital economy and society index DESI and e-Government digital skills (EGDI) from 2018 to 2021 revealed a stagnant state in 2018 and 2019, and in 2020, there was a decrease in basic digital skills. The next index is E-Government Digital Index. It focuses on human capital and digital skills in these indices. The paper analyses and identifies the digital skills of citizens in the context of e-Government development and describes the use of e-Government services by EU citizens with a focus on the Slovak Republic. The data were collected through a questionnaire survey of Slovak Republic citizens’ digital skills according to selected categories, the use of e-Government services as well as awareness of e-Government services. Solutions that improve e-Government in the Slovak Republic are gradually being implemented. Improving digital skills according to the National Coalition for Digital Skills and Professions in the Slovak Republic is one of the priorities of The Ministry of Education, Science, Research and Sport of the Slovak Republic, which has adopted an action plan for 2019–2022 to improve the results in the DESI index by 2025 and focus on the digital skills required by employers. The survey revealed that in Slovakia, the majority of schools offer only weak support for digital education (about the EU-27 average of 68% and 45%, respectively). The research also revealed a decreased level of digital literacy among young people. These competencies are very important to gain a position in the labour market in the digital society. The projects aim to support the development of digital skills of primary and secondary school students, and the integration of new technologies into teaching.

E-Government is one area of digitization that has been under way for several years in European countries. In this paper, we focus on identifying different indices that are aimed at measuring digitalization or e-Government. The results of the analysis showed that there are several indices that focus on this area within the EU, such as EGDI, EPI, LOSI, DGI, e-Government benchmark, Eurostat—Internet use, GII, DSGI, Going Digital toolkit, and DESI. Subsequently, the index areas to be used in the DEA method to measure the efficiency of e-Government-related inputs and outputs within the EU were identified. Inputs and outputs were selected logically and then verified using correlation analysis. Among the input and output indices chosen were Internet usage, DSGI, GII, e-Government benchmark, and interaction with public administration online. From the analysis, three inputs and three outputs were used and the models were output oriented. After implementing the correlation, it can be said that the values between the selected sub-variables are suitable for DEA analysis. Two models were chosen for the calculation, namely the CCR and BCC models. The CCR model found 10 states to be efficient and BCC model found 13 states to be efficient. In addition, in the close analysis, we took a closer look at the CCR model’s inference. Countries such as Denmark, Finland, Estonia, Malta, and Portugal were efficient outliers. When comparing the regions within the EU, we can conclude that the countries of Northern Europe are the most efficient in the field of digitalization (e-Government). As many as four countries out of seven are efficient.

Digitalisation is one of the European Union's priorities. The European Parliament is shaping and helping to shape new legislation in this area. Digitisation should also help in the transition to a greener economy and in achieving climate neutrality. E-government is one area of digitisation that has been under way for several years in European countries. In this paper, we have focused on identifying different indices that are aimed at measuring digitalization or e-Government. The results of the analysis showed that there are several indices that focus on this area within the EU, such as EGDI, EPI, LOSI, DGI, e-Government benchmark, Eurostat - internet use, GII, DSGI, Going Digital toolkit and DESI. Subsequently, the index areas to be used in the DEA method to measure the effectiveness of e-Government related inputs and outputs within the EU were identified. As can be seen from the analysis, the DEA method has various uses. In order to be able to use the method properly it was necessary to select the most appropriate parameter and to verify their suitability by means of correlation analysis. Among the input and output indices were chosen Internet usage, DSGI, GII, e-Government benchmark, Interaction with public administration online. From the analysis 3 inputs and 3 outputs were used. After implementing the correlation, it can be said that the values between the selected sub-variables are suitable for DEA analysis. Two models were chosen for the calculation, namely CCR and BCC model. CCR model evaluated 10 states as efficient and BCC model evaluated 13 states as efficient. In addition, in the close analysis, we have taken a closer look at the CCR model's inference. Countries such as Denmark, Finland, Estonia, Malta, Portugal, etc. were efficient outliers. When comparing the regions within the EU, we can conclude that the countries of Northern Europe are the most efficient in the field of digitalization (e-Government). As many as 4 countries out of 7 are efficient. In a future study it would be useful to use the SBM model and try to measure the impact of digitalization on selected areas such as economy, society, environment, etc.

This article describes the Analytic Hierarchy Process (AHP) method which can be calculated by several methods. The AHP method is essential for the managerial decision-making to recognize which method is efficient for the calculation and to determine the proper order of criteria. In the article there are included methods that can be used in order to calculate the matrix in the AHP process for setting criteria such as Geometric mean, Arithmetic mean, Row sum of the adjusted the Saaty matrix, Reverse sums of the Saaty matrix columns and Row sums of the Saaty matrix. The paper is focused on the accuracy of the methods used. The results show that the most accurate method is the Saaty method, and the second most accurate method is the geometric mean in order to determine the ranking. This method is easier to use when the same order is achieved as in the Saaty method, followed by Geometric mean, which is favourable for fast and easy determination of alternatives using in the AHP process. The survey carried out among managers graduated from Universities and Colleges in Slovakia showed that the respondents considered the Saaty method as the most complex and also the most difficult method and the geometric mean average method the simplest method. 44% of respondents stated that they are capable to use a program to calculate the AHP. 46% of respondents said they had experience with some method related to the managerial decision-making process. 72% of managers regarded as important to manage some method for decision-making in their managerial position.