ICACT20240473 Slide.18
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Thank you
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ICACT20240473 Slide.17
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REFERENCES
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ICACT20240473 Slide.16
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REFERENCES
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ICACT20240473 Slide.15
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The IDI indicators of aimags were analyzed using the CC weight method, entropy weight method, and the proposed method equation.
The present study has assessed the levels of ICT development across capital city and 21 aimags by employing a composite result derived from ten selected indicators.
Additionally, the weighted analysis introduced in this article can serve as a valuable instrument for fine-tuning the weights of IDI indicators. Furthermore, the methodology presented in this paper can be applied irrespective of any changes in the number or composition of indicators within IDI sub-indexes.
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ICACT20240473 Slide.14
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The following table shows the most recent values of the IDI, based on data published by ITU in 2023.
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ICACT20240473 Slide.13
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With the CC weight method, the results emphasize Umnugovi aimag (0.0728) as the highest in ICT development in the country, while Arkhangai aimag (0.0227) in the Khangai region ranks the lowest. Applying the proposed weighting method, Umnugovi aimag (0.0728) and Ulaanbaatar city (0.0687) emerge as the most developed in ICT in the country. Conversely, Arkhangai aimag (0.0413) in the Khangai region is identified as the least developed in terms of ICT development
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ICACT20240473 Slide.12
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Slide shows Analysis of the IDI indicators of aimags.
The outcomes of the entropy weight method reveal that Umnugovi aimag (0.0554) in the central region and Ulaanbaatar city (0.0421) attain the highest rank in IDI. Conversely, Bayan-Ulgii aimag (0.0413) in the western region and Bulgan aimag (0.0421) in the central region secure the lowest ranks.
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ICACT20240473 Slide.11
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It appears that weights between indicators calculated by equations pillar scores in the Figure, are generally favorable, with values ranging from 0.0003-0.262 for the We, from 0.0842-0.1072 for the Wcc, and from 0.0003-0.3145 for the Wec.
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ICACT20240473 Slide.10
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The slide shows Analysis of the IDI indicators of aimags. The outcomes of the entropy weight method reveal that Umnugovi aimag (0.0554) in the central region and Ulaanbaatar city (0.0421) attain the highest rank in IDI. Conversely, Bayan-Ulgii aimag (0.0413) in the western region and Bulgan aimag (0.0421) in the central region secure the lowest ranks. This suggests effective summarization of information from indicators into pillars.
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ICACT20240473 Slide.09
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Mongolia is divided into 21 aimags or provinces.
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ICACT20240473 Slide.08
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The Table displays the correlation coefficients related to the indicators of capital city and aimags in Mongolia. Mongolia is divided into 21 aimags or provinces. In general, the correlation coefficients exhibit the anticipated signs within the chosen set of indicators.
The indicators within the universal connectivity category exhibit positive and moderate to strong correlations with each other. All correlations are stronger than 0.183 in both pillars. The strong positive correlation observed between the indicators measuring mobile broadband coverage with at least 3G and 4G/LTE technologies implies that these two indicators can be consolidated into a singular measure within the meaningful connectivity infrastructure category.
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ICACT20240473 Slide.07
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Correlation analysis in research is a statistical method used to measure the strength of the linear relationship between two variables and compute their association.
Correlation analysis stands as a crucial statistical tool in the development of composite indicators. By elucidating the statistical relationships among the indicators under consideration for inclusion, it offers an initial insight into the robustness of an index and potential issues related to internal consistency.
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ICACT20240473 Slide.06
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The ICT development index (IDI) was established with the purpose of gauging the advancement of the information and communication technology sector. Published by the ITU, this composite indicator was active from 2009 to 2017 but was discontinued in 2018 due to challenges related to the availability and quality of data. The IDI was established with the purpose of gauging the advancement of the ICT sector. Published by the ITU, this composite indicator was active from 2009 to 2017 but was discontinued in 2018 due to challenges related to the availability and quality of data. The Table shows indicators of IDI by methodology of the ICT Development Index Version 3.1, ITU.
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ICACT20240473 Slide.05
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Entropy weights, Correlation coefficient weights and integrated weights can be obtained through result, which is formulated as follows:
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ICACT20240473 Slide.04
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The entropy weighting method is used to compute index values under objective conditions, improving the objectivity of rank lists and reducing the subjectivity of weight assignment.
Entropy weighing method is procedure of calculating the index values of analyses under objective conditions, may evaluate intent and degree of order and efficiency, attributing to entropy estimation of the information.
The entropy weighting approach enhances the objectivity of rank lists. This approach reduces the subjectivity of the weight assigned to various parameters, resulting in assessment results that better reflect the actual situation.
The entropy weight is defined by judgment matrices, with more available information resulting in less entropy. The weight assessment process involves formulating alternatives and evaluation index and deriving the entropy weight using Shannon's entropy theory.
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ICACT20240473 Slide.03
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The slide shows METHODOLOGY FOR INDEX EVALUATION. 1 Entropy weighting method. The concept of information entropy measures the amount of information that can be obtained from a source of random data. It was introduced by Shannon. The entropy weighing method is a process used to calculate index values in analyses conducted under objective conditions. 2 Correlation coefficient weighting method To examine the correlation among indicators of ICT development, the correlation coefficient formula was applied. Correlation analysis, a quantitative analytical tool, is employed to assess the extent of the relationship between independent and dependent variables. 3 Proposed weighting method. This subsection aims to provide a detailed description of the proposed integration algorithm.
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ICACT20240473 Slide.02
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Since 2009, ITU has annually released the IDI. This index serves as a valuable resource for policymakers and researchers in evaluating the efficacy of policies and initiatives geared toward promoting ICT development. Through quantitative metrics and benchmarks, the IDI offers an objective assessment of international performance. Decision-makers find it to be an indispensable tool for measuring ICT growth and progress globally. Additionally, the IDI acknowledges the convergence of technology and the emergence of new technologies, making it effective in assessing the impact of ICT on society and the economy. ITU’s Council noted in September 2023 during the annual meetings, that the IDI methodology, the Version 3 document, was finalized, now called Version 3.1 with 10 indicators, and has been submitted for approval by Member States.
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ICACT20240473 Slide.01
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Hi everybody, Our presentation today is about a Study on the evaluation of the ICT development indexes and some results
Presentation outline consist of METHODOLOGY FOR INDEX EVALUATION and ASSESSMENT OF INDICATORS IN THE CASE OF ICT DEVELOPMENT INDEX in provinces Mongolia.
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ICACT20240473 Slide.00
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a Study on the evaluation of the ICT development indexes and some results
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