Evaluation of Indicators for ICT Development Index using an Integrated Entropy Weighting Method
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Dec 30, 2023
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Abstract
When designing a data analysis using information entropy, metrics derived from this method must be observed, evaluated, and utilized. Information entropy, which reflects the level of uncertainty in a random variable, can be applied to a range of fields, including information and communication technology (ICT). The methodology proposed aims to assign weights to the indicators within the ICT development index and sub-indexes, enabling their global, regional, and country-wise ranking. To test the effectiveness of this methodology, we examined its potential applications for evaluating indexes. Our model integrates a novel approach that combines the entropy weight coefficient method, bootstrap method, correlation coefficient weighting method, and S-shaped diffusion stages of ICT. We present the evaluation results of the integrated calculating method.
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Keywords
ICT indicators, entropy, entropy weight
References
[1] Measuring the Information Society Report 2016, 2009, ITU International Telecommunication Union Place des Nations CH-1211 Geneva Switzerland, ISBN 978-92-61-21431-9, 2016.
[2] Organization for Economic Cooperation and Development, Guide to measuring the information society. 2011, OECD. http://www.oecd.org
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[10] Francisco M Codoñer, Shirley O'Dea, Mario A Fares, “Reducing the false positive rate in the non-parametric analysis of molecular coevolution”, BMC Evolutionary Biology 8:106. 2008, https://doi.org/10.1186/1471-2148-8-106
[11] Peter,T.Munro, and D.A.Somerton, “Maximum likelihood and non-parametric methods for estimating trawl footrope selectivity”, ICES Journal of Marine Science 58:220-229,2001, https://doi.org/10.1006/jmsc.2000.1004
[12] Aaron J. Wilson, Bruce R. J. Warmack, Ali Riza Ekti, Yilu Liu,“Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors”, 2022, Sensors 22(22):8827, MDPI, https://doi.org/10.3390/s22228827
[13] Choudhary, D.; Shankar, R. “An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India”. Energy 2012, 42, 510–521, https://doi.org/10.1016/j.energy.2012.03.010
[14] Dinmohammadi, A.; Shafiee, M. “Determination of the most suitable technology transfer strategy for wind turbines using an integrated AHP-TOPSIS decision model”. Energies 2017, 10, 642, https://doi.org/10.3390/en10050642
[15] Karahalios, H. “The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators” Transp. Res. Part D Transp. Environ. 2017, 52, 172–184. https://doi.org/10.1016/j.trd.2017.03.001
[16] Deng, J.L. “Introduction grey system theory” J. Grey Syst. 1989, 1, 191–243, https://doi.org/10.1007/978-981-19-3424-7_1
[17] Zhao, H.; Yao, L.; Mei, G.; Liu, T.; Ning, Y. “A Fuzzy comprehensive evaluation method based on AHP and Entropy for landslide susceptibility map”. Entropy 2017, 19, 396, https://doi.org/10.3390/e19080396
[18] Saaty, T.L. “How to make a decision: the analytic hierarchy process”. Eur. J. Oper. Res. 1994, 24, 19–43, https://doi.org/10.1016/0377-2217(90)90057-I
[19] Saaty,T.L. “Decision making for leaders”, Pittsburgh: RWS Publications. 1990
[20] Dong, X.; Lu, H.; Xia, Y.; Xiong, Z. “Decision-making model under risk assessment based on entropy”. Entropy 2016, 18, 404, https://doi.org/10.3390/e18110404
[21] Lotfi, F.H.; Fallahnejad, R. “Imprecise Shannon’s Entropy and Multi Attribute Decision Making”. Entropy 2010, 12, 53–62, https://doi.org/10.3390/e12010053
[22] Erkhembaatar Narantuya, Bataa Otgonbayar. “Determining ICT indicators using entropy theory”, International conference on advanced communications technology (ICACT-2019), Korea, 2019, 217-222, https://doi.org/10.23919/ICACT.2019.8702010
[23] Shannon C. and Weaver W., “The mathematical theory of communication”, University of Illinois Press, 1949
[24] Erkhembaatar Narantuya, “Study on development of information potential”, International forum on strategic technology (IFOST-2013), Mongolia, proceedings, Volume II, 2013, 380-383 https://doi.org/10.1109/IFOST.2013.6616918
[25] Jose, F., G. Salvatore, and E. Matthias. 2005. “Multiple criteria decision analysis: State of the art surveys”. International Series in Operations Research & Management Science, Vol. 78. New York: Springer, https://doi.org/10.1007/978-1-4939-3094-4
[26] Erkhembaatar Narantuya, “Defining information entropy and potential in the communication network”, International forum on strategic technology (IFOST-2018), China, 2018, 89-94
[27] Arindam Sutradhar, Pritirekha Daspattanayak. ”A regional model for the variability of Agricultural development: evidence from a drought-prone region of Rarh Bengal, Eastern India”, Modeling Earth Systems and Environment, Springer Nature journal,2023, https://doi.org/10.1007/s40808-023-01721-6
[28] Erkhembaatar Narantuya, Bataa Otgonbayar “Entropy weight method for evaluating indicators of ICT development index”, International journal of current advanced research, Volume 9; Issue 12 (C); December 2020; 23500-23505, https://doi.org/10.24327/ijcar.2020.23504.4654
[29] Liping Wang, Zhongyi Qu, Wei Yang,“Coupled urbanisation and ecological protection along the Yellow river basin in the context of dual carbon”, Sustainability,MDPI, 15(7):5728, 4-16, 2023, https://doi.org/10.3390/su15075728
[30] Tang, C. M., A. Y. T. Leung, and K. C. Lam. 2006. “Entropy application to improve construction finance decisions. Journal of construction engineering and management” 132(10):1099–111
[31] Gumus, A.T.; Yayla, A.Y.; Elik, E.; Yildiz, A. “A combined fuzzy-AHP and fuzzy-GRA methodology for hydrogen energy storage method selection in Turkey”. Energies 2013, 6, 3017–3032, https://doi.org/10.3390/en6063017
[32] Sun, L.; Liu, Y.; Zhang, B.; Shang, Y.; Yuan, H.; Ma, Z. “An integrated decision-making model for transformer condition assessment using game theory and modified evidence combination extended by d numbers”. Energies 2016, 9, 697, https://doi.org/10.3390/en9090697
[33] Kang, H.Y.; Hung, M.C.; Pearn, W.L.; Lee, A.H.I.; Kang, M.S. ”An integrated multi-criteria decision making model for evaluating wind farm performance”. Energies 2011, 4, 2002–2026, https://doi.org/10.3390/en4112002
[34] Lee, A.H.I.; Lin, C.Y.; Kang, H.Y.; Wen, H.L. “An integrated performance evaluation model for the photovoltaics industry”. Energies 2012, 5, 1271–1291, https://doi.org/10.1016/j.solener.2022.12.039
[35] Zeng, F.; Cheng, X.; Guo, J.; Tao, L.; Chen, Z. “Hybridising human judgment, ahp, grey theory, and fuzzy expert systems for candidate well selection in fractured reservoirs”. Energies 2017, 10, 447, https://doi.org/10.3390/en10040447
[36] Guili, Y.; Jianhua, Z.; Tianhong, W.; Juan, D. “Comprehensive energy-saving evaluation of thermal power plants based on TOPSIS gray relational projection and the weight sensitivity analysis”. J. Chin. Soc. Power Eng.2015, 35, 404–411.
[37] Wang, Y.M.; Luo, Y. “Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making”. Math. Comput. Model. 2010, 51, 1–12, https://doi.org/10.1016/j.mcm.2009.07.016
[38] Diakoulaki, D.; Mavrotas, G.; Papayannakis, L. “Determining objective weights in multiple criteria problems: The critic method”. Comput. Oper. Res. 1995, 22, 763–770, https://doi.org/10.1016/0305-0548(94)00059-H
[39] Lo, T.P.; Guo, S.J. “Effective weighting model based on the maximum deviation with uncertain information”. Expert Syst. Appl. 2010, 37, 8445–8449, https://doi.org/10.1016/j.eswa.2010.05.034
[40] Gan, Y.; Duan, Q.; Gong, W.; Tong, C.; Sun, Y.; Chu, W.; Ye, A.; Miao, C.; Di, Z. “A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model”. Environ. Model. Softw. 2014, 51, 269–285, https://doi.org/10.1016/j.envsoft.2013.09.031
[41] Babamoradi, H.; Berg, F.V.D.; Rinnan, “A. Bootstrap based confidence limits in principal component analysis-A case study”. Chemom. Intell. Lab. Syst. 2013, 120, 97–105, https://doi.org/10.1016/j.chemolab.2012.10.007
[42] Dolgorsuren Dulamjav, Buyankhishig Zundui, “The Analysis of FSO Link Performance in Ulaanbaatar”. ICTFocus. Volume 1, Number 1, 2022, 47-54, https://doi.org/10.58873/sict.v1i1.26
[2] Organization for Economic Cooperation and Development, Guide to measuring the information society. 2011, OECD. http://www.oecd.org
[3] Organization for Economic Cooperation and Development, “Guide to measuring the information society”, Partnership on Measuring ICT for Development, 2011
[4] Measuring the Information Society Report 2011, 2011 ITU International Telecommunication Union Place des Nations CH-1211 Geneva Switzerland, ISBN 978-92-61-21431-9, 2011.
[5] Core list of ICT indicators, March 2016 version, Partnership on Measuring ICT for Development, 2016
[6] Regional outcomes from IDI 2017, Measuring the Information Society Report 2017, Volume 1, ITU International Telecommunication Union Place des Nations CH-1211 Geneva Switzerland, ISBN 978-92-61-24521-4, 2017.
[7] Measuring Digital Development: ITU Facts and figures 2019, ITU International Telecommunication Union Place des Nations, CH-1211 Geneva Switzerland ISBN 978-92-61-29521-9, 2019.
[8] Kauffman, R. J., and A. Kumar, “A critical assessment of the capabilities of five measures for ICT development”, Working paper, Carlson School of Management, University of Minnesota, Minneapolis, 2005
[9] Nicoletta Corrocher, Andrea Ordanini, “Measuring the digital divide: a framework for the analysis of cross-country differences”, Journal of Information Technology 17:9–19, 2002. https://doi.org/10.1080/02683960210132061
[10] Francisco M Codoñer, Shirley O'Dea, Mario A Fares, “Reducing the false positive rate in the non-parametric analysis of molecular coevolution”, BMC Evolutionary Biology 8:106. 2008, https://doi.org/10.1186/1471-2148-8-106
[11] Peter,T.Munro, and D.A.Somerton, “Maximum likelihood and non-parametric methods for estimating trawl footrope selectivity”, ICES Journal of Marine Science 58:220-229,2001, https://doi.org/10.1006/jmsc.2000.1004
[12] Aaron J. Wilson, Bruce R. J. Warmack, Ali Riza Ekti, Yilu Liu,“Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors”, 2022, Sensors 22(22):8827, MDPI, https://doi.org/10.3390/s22228827
[13] Choudhary, D.; Shankar, R. “An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India”. Energy 2012, 42, 510–521, https://doi.org/10.1016/j.energy.2012.03.010
[14] Dinmohammadi, A.; Shafiee, M. “Determination of the most suitable technology transfer strategy for wind turbines using an integrated AHP-TOPSIS decision model”. Energies 2017, 10, 642, https://doi.org/10.3390/en10050642
[15] Karahalios, H. “The application of the AHP-TOPSIS for evaluating ballast water treatment systems by ship operators” Transp. Res. Part D Transp. Environ. 2017, 52, 172–184. https://doi.org/10.1016/j.trd.2017.03.001
[16] Deng, J.L. “Introduction grey system theory” J. Grey Syst. 1989, 1, 191–243, https://doi.org/10.1007/978-981-19-3424-7_1
[17] Zhao, H.; Yao, L.; Mei, G.; Liu, T.; Ning, Y. “A Fuzzy comprehensive evaluation method based on AHP and Entropy for landslide susceptibility map”. Entropy 2017, 19, 396, https://doi.org/10.3390/e19080396
[18] Saaty, T.L. “How to make a decision: the analytic hierarchy process”. Eur. J. Oper. Res. 1994, 24, 19–43, https://doi.org/10.1016/0377-2217(90)90057-I
[19] Saaty,T.L. “Decision making for leaders”, Pittsburgh: RWS Publications. 1990
[20] Dong, X.; Lu, H.; Xia, Y.; Xiong, Z. “Decision-making model under risk assessment based on entropy”. Entropy 2016, 18, 404, https://doi.org/10.3390/e18110404
[21] Lotfi, F.H.; Fallahnejad, R. “Imprecise Shannon’s Entropy and Multi Attribute Decision Making”. Entropy 2010, 12, 53–62, https://doi.org/10.3390/e12010053
[22] Erkhembaatar Narantuya, Bataa Otgonbayar. “Determining ICT indicators using entropy theory”, International conference on advanced communications technology (ICACT-2019), Korea, 2019, 217-222, https://doi.org/10.23919/ICACT.2019.8702010
[23] Shannon C. and Weaver W., “The mathematical theory of communication”, University of Illinois Press, 1949
[24] Erkhembaatar Narantuya, “Study on development of information potential”, International forum on strategic technology (IFOST-2013), Mongolia, proceedings, Volume II, 2013, 380-383 https://doi.org/10.1109/IFOST.2013.6616918
[25] Jose, F., G. Salvatore, and E. Matthias. 2005. “Multiple criteria decision analysis: State of the art surveys”. International Series in Operations Research & Management Science, Vol. 78. New York: Springer, https://doi.org/10.1007/978-1-4939-3094-4
[26] Erkhembaatar Narantuya, “Defining information entropy and potential in the communication network”, International forum on strategic technology (IFOST-2018), China, 2018, 89-94
[27] Arindam Sutradhar, Pritirekha Daspattanayak. ”A regional model for the variability of Agricultural development: evidence from a drought-prone region of Rarh Bengal, Eastern India”, Modeling Earth Systems and Environment, Springer Nature journal,2023, https://doi.org/10.1007/s40808-023-01721-6
[28] Erkhembaatar Narantuya, Bataa Otgonbayar “Entropy weight method for evaluating indicators of ICT development index”, International journal of current advanced research, Volume 9; Issue 12 (C); December 2020; 23500-23505, https://doi.org/10.24327/ijcar.2020.23504.4654
[29] Liping Wang, Zhongyi Qu, Wei Yang,“Coupled urbanisation and ecological protection along the Yellow river basin in the context of dual carbon”, Sustainability,MDPI, 15(7):5728, 4-16, 2023, https://doi.org/10.3390/su15075728
[30] Tang, C. M., A. Y. T. Leung, and K. C. Lam. 2006. “Entropy application to improve construction finance decisions. Journal of construction engineering and management” 132(10):1099–111
[31] Gumus, A.T.; Yayla, A.Y.; Elik, E.; Yildiz, A. “A combined fuzzy-AHP and fuzzy-GRA methodology for hydrogen energy storage method selection in Turkey”. Energies 2013, 6, 3017–3032, https://doi.org/10.3390/en6063017
[32] Sun, L.; Liu, Y.; Zhang, B.; Shang, Y.; Yuan, H.; Ma, Z. “An integrated decision-making model for transformer condition assessment using game theory and modified evidence combination extended by d numbers”. Energies 2016, 9, 697, https://doi.org/10.3390/en9090697
[33] Kang, H.Y.; Hung, M.C.; Pearn, W.L.; Lee, A.H.I.; Kang, M.S. ”An integrated multi-criteria decision making model for evaluating wind farm performance”. Energies 2011, 4, 2002–2026, https://doi.org/10.3390/en4112002
[34] Lee, A.H.I.; Lin, C.Y.; Kang, H.Y.; Wen, H.L. “An integrated performance evaluation model for the photovoltaics industry”. Energies 2012, 5, 1271–1291, https://doi.org/10.1016/j.solener.2022.12.039
[35] Zeng, F.; Cheng, X.; Guo, J.; Tao, L.; Chen, Z. “Hybridising human judgment, ahp, grey theory, and fuzzy expert systems for candidate well selection in fractured reservoirs”. Energies 2017, 10, 447, https://doi.org/10.3390/en10040447
[36] Guili, Y.; Jianhua, Z.; Tianhong, W.; Juan, D. “Comprehensive energy-saving evaluation of thermal power plants based on TOPSIS gray relational projection and the weight sensitivity analysis”. J. Chin. Soc. Power Eng.2015, 35, 404–411.
[37] Wang, Y.M.; Luo, Y. “Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making”. Math. Comput. Model. 2010, 51, 1–12, https://doi.org/10.1016/j.mcm.2009.07.016
[38] Diakoulaki, D.; Mavrotas, G.; Papayannakis, L. “Determining objective weights in multiple criteria problems: The critic method”. Comput. Oper. Res. 1995, 22, 763–770, https://doi.org/10.1016/0305-0548(94)00059-H
[39] Lo, T.P.; Guo, S.J. “Effective weighting model based on the maximum deviation with uncertain information”. Expert Syst. Appl. 2010, 37, 8445–8449, https://doi.org/10.1016/j.eswa.2010.05.034
[40] Gan, Y.; Duan, Q.; Gong, W.; Tong, C.; Sun, Y.; Chu, W.; Ye, A.; Miao, C.; Di, Z. “A comprehensive evaluation of various sensitivity analysis methods: A case study with a hydrological model”. Environ. Model. Softw. 2014, 51, 269–285, https://doi.org/10.1016/j.envsoft.2013.09.031
[41] Babamoradi, H.; Berg, F.V.D.; Rinnan, “A. Bootstrap based confidence limits in principal component analysis-A case study”. Chemom. Intell. Lab. Syst. 2013, 120, 97–105, https://doi.org/10.1016/j.chemolab.2012.10.007
[42] Dolgorsuren Dulamjav, Buyankhishig Zundui, “The Analysis of FSO Link Performance in Ulaanbaatar”. ICTFocus. Volume 1, Number 1, 2022, 47-54, https://doi.org/10.58873/sict.v1i1.26
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Erkhembaatar, N. (2023). Evaluation of Indicators for ICT Development Index using an Integrated Entropy Weighting Method. ICT Focus, 2(1), 1–13. https://doi.org/10.58873/sict.v2i1.43
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