ANP-based analysis of ICT usage in Central European enterprises

Becker, Jarosław; Becker, Aneta; Sulikowski, Piotr; Zdziebko, Tomasz

doi:10.1016/j.procs.2018.07.231

Cited by 26 publications

(23 citation statements)

References 14 publications

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“…To assess ICT development, social development and broadly understood sustainability, the MCDA (multi-criteria decision analysis) methods are more frequently used [16][17][18]. Some of MCDA methods, as compared to IDI, are characterised by stronger sustainability, and thus lower compensation of criteria/indicators.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Digital Divide Using Fuzzy Forecasting

Ziemba

Becker

2019

Symmetry

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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.

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Section: Introductionmentioning

confidence: 99%

Analysis of the Digital Divide Using Fuzzy Forecasting

Ziemba

Becker

2019

Symmetry

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“…ANP's stepwise algorithm for the evaluation problem used in this study is summarized as follows (Becker, Becker, Sulikowski, & Zdziebko, ; Golcuk & Baykasoglu, ). Define the goal of decision problem, analyze the correlation between criteria, and construct the network structure of decision problem. Compare the criteria of the control layer with each other and construct the pairwise comparison matrix of the criteria of the control layer according to ANP's 1–9 scale (see Appendix C) method. Construct the pairwise comparison matrix of the subcriteria of the network layer on the basis of the criteria of control layer and obtain the normalized eigenvector and unweighted super matrix. Obtain a weighted super matrix by multiplying the weighted matrix of the control layer and the unweighted super matrix of the network layer. Transform the weighted super matrix into limit super matrix by computing limit relative ranking vector. …”

Section: Methodsmentioning

confidence: 99%

“…ANP's stepwise algorithm for the evaluation problem used in this study is summarized as follows (Becker, Becker, Sulikowski, & Zdziebko, 2018;Golcuk & Baykasoglu, 2016).…”

Section: F I G U R E 4 the Correlations Between The Subcriteriamentioning

confidence: 99%

Improving the risk management of Type 2 diabetes mellitus in China from the perspective of social relationships

et al. 2019

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In China, Type 2 diabetes mellitus (T2DM) is increasingly affecting people's health. Although many risk factors related to T2DM have been researched, the association between social relationships and risk management of T2DM in China has not been fully researched. Therefore, we obtained 2,969 valid cases from the National Chinese Medicine Clinical Research Base‐Key Disease of Diabetes Mellitus Study to evaluate the role of social relationships in the risk management of T2DM. We first establish an indicators system of social relationship factors and then propose a comprehensive method that integrates subjective (analytical network process) and objective (entropy weight method) evaluations to rank the importance of the 17 social relationship factors that were the most important and commonly used. The results suggest that different social relationship factors have different effects on the risk management of T2DM. Patients and health workers should pay more attention to the high‐benefit factors and thus improve the efficiency of the risk management of T2DM. These findings provided theoretical support for patients and health workers by developing the positive effects of social relationships in improving the risk management of T2DM to the fullest degree.

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“…In order to carry out the research, the authors used the author's conversion method that has many advantages. Among them, it is essential to mention that it combines both the precision of the results of the multicriteria methods, such as the AHP (Kubler, Robert, Derigent, Voisin, & Traona, 2016;Lya, Lai, Hsu, & Shih, 2018), ANP (Becker, Becker, Sulikowski, & Zdziebko, 2018), the ELECTRE (Corrente, Greco, & Słowiński, 2016), the PROMETHEE (Andreopoulou, Koliouska, Galariotis, & Zopounidis, 2018), verbal methods (Trzaskalik, 2014), TOPSIS (Chmielarz & Zborowski, 2018), BIPOLAR (Trzaskalik, 2014). Moreover, the process of collecting data for calculations is as simple as in a case of the scoring method, and the simplicity of the result processing which is the characteristic of the scoring method.…”

Section: Methodsmentioning

confidence: 99%