Analysis of the Digital Divide Using Fuzzy Forecasting

Abstract

In the countries of the former Eastern Bloc (Central and Eastern Europe) belonging to the European Union, a gradual elimination of the technological gap, greater expenditures, competitiveness and productivity can be noticed. In this context, analysis and forecast of the level of accessibility and use of ICT (information and communication technologies) by households in these countries has become interesting. It allows for the selection of digitally excluded regions, or those threatened with this phenomenon in the coming years (2018–2020). To carry out the analysis, a framework based on fuzzy numbers and the NEAT F-PROMETHEE (New Easy Approach To Fuzzy-PROMETHEE) method was developed. The potential of the fuzzy outranking approach taking into account the uncertainty of input data (criteria and preferences) has been demonstrated as an alternative to the IDI (ICT Development Index) methodology widely used in research on regional ICT development based on composite indices. Research has shown that Estonia is the leader in the area of ICT expansion among households, and in the next three years will definitely maintain its dominant position. Slovenia follows shortly after, followed by Latvia. At the end of the ranking were the countries with the largest percentage in Central and Eastern Europe of population excluded digitally or threatened with this phenomenon; these are: Poland, Slovakia, Bulgaria and, in last place, Romania. Within this framework, the robustness of the obtained rankings to change in the degree of uncertainty of preferences was also examined. It turned out that eliminating the uncertainty of preferences resulted in an increase in the uncertainty of the aggregate, fuzzy grades obtained at the output.

A Fuzzy Multi-Criteria Analysis of Barriers and Policy Strategies for Small and Medium Enterprises to Adopt Green Innovation

“…Therefore, triangular fuzzy numbers (TFNs) has been used to analyze the alternatives with respect to each of their criteria. Linguistic variables can help in reducing the uncertain problem by converting it into quantitative terms [71]. There are various ways to represent linguistic variables using TFNs; Table 4 shows the linguistic variables scale of the present study.…”

Inter-Criteria Dependencies-Based Decision Support in the Sustainable wind Energy Management

“…Another constraint linked to the decision problem itself is that the decision-maker, when considering a similar decision problem, may formulate other criteria, the inclusion of which may, of course, be given a different ranking of alternatives. Finally, it should be noted that this is an ex-ante study so that the values of the alternatives in terms of evaluation criteria are uncertain and may change to some extent [103].…”

Assessment of City Sustainability Using MCDM with Interdependent Criteria Weight

“…Developing a forecast approach to predict the future sustainable development of cities may also be an important topic of interest. A forecast can be developed using a fuzzy approach with reference to the research of Ziemba et al [57].…”