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COMPARATIVE ANALYSIS OF MCDM METHODS FOR THE ASSESSMENT OF ICT DEVELOPMENT IN G7 COUNTRIES

Year 2022, , 55 - 73, 29.06.2022
https://doi.org/10.36543/kauiibfd.2022.003

Abstract

Information and communication technology (ICT) enable information to be accessed and processed through all kinds of visual, audio, printed and written tools. This study aimed to evaluate the ICT development of G7 countries by using Multi Criteria Decision Making (MCDM) methods. Accordingly, the Entropy method was used to specify the criteria weights, and the Proximity Indexed Value (PIV), Range of Value (ROV), and the COmplex PRoportional ASsessment (COPRAS) methods were used to rank the alternatives. In the final stage, the rankings obtained by the Entropy based PIV, ROV, COPRAS methods were compared with the results obtained by the Level Based Weight Assessment (LBWA) based Measurement Alternatives and Ranking according to Compromise Solution (MARCOS) method, and a comparative analysis was performed. Finally, it was determined that the criteria weights obtained by objective and subjective methods had different effects on the ranking results.

References

  • Aldalou, E. and Perçin, S. (2020). Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector. International Journal of Procurement Management, 13(1), 1-23.
  • Chatterjee, P., Athawale, V. M. and Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials and Design, 32, 851-860.
  • Chen, J. K. and Chen, I. S. (2015). The assessment of intellectual capital for the information and communication technology industry in Taiwan applying a hybrid MCDM model. European J. of International Management, 9(1), 88–107.
  • Das, M. C., Sarkar, B. and Ray, S. (2012). A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology. Socio-Economic Planning Sciences, 46, 230-241.
  • Ishida, H. (2015). “The effect of ICT development on economic growth and energy consumption in Japan”. Telematics and Informatics, 32(1), 79-88.
  • Madić, M. and Radovanović, M. (2015). Ranking of some most commonly used non-traditional machining processes using ROV and CRITIC methods. UPB Scientific bulletin, Series D: Mechanical Engineering, 77(2), 193-204.
  • Mahmud, A. J., Olander, E., Eriksén, S. and Haglund, B. J. (2013). Health communication in primary health care-A case study of ICT development for health promotion. BMC medical informatics and decision making, 13(1), 1-15.
  • McCarney, J. (2004). Effective models of staff development in ICT. European Journal of Teacher Education, 27(1), 61-72.
  • Meng, Q. and Li, M. (2002). New economy and ICT development in China. Information economics and policy, 14(2), 275-295.
  • Merkevičius, J. and Yadav, R. (2019). “Evaluation of ICT usages in virtual business by applying MCDM methods”. 22nd Conference for Young Researchers" Economics and Management, Vilnius, Lithuania.
  • Mufazzal, S. and Muzakkir, S. M. (2018). A New Multi-Criterion Decision Making (MCDM) Method Based on Proximity Indexed Value for Minimizing Rank Reversals. Computers & Industrial Engineering, 119, 427-438.
  • Nath, H. K. and Liu, L. (2017). Information and communications technology (ICT) and services trade. Information Economics and Policy, 41, 81-87.
  • OECD, Access to computer from home (Indicator), 2021a, “https://data.oecd.org/ict/access-to-computers-from-home.htm” (Accessed on 06 October 2021).
  • OECD, ICT employment (Indicator), 2021b, “https://data.oecd.org/ict/ict-employment.htm” (Accessed on 06 October 2021).
  • OECD, ICT goods exports (Indicator), 2021c, “https://data.oecd.org/ict/ict-goods-exports.htm” (Accessed on 06 October 2021).
  • OECD, ICT investment (Indicator), 2021d, “https://data.oecd.org/ict/ict-investment.htm” (Accessed on 06 October 2021).
  • OECD, ICT value added (Indicator), 2021e, “https://data.oecd.org/ict/ict-value-added.htm” (Accessed on 06 October 2021).
  • OECD, Internet Access (Indicator), 2021f, “https://data.oecd.org/ict/internet-access.htm” (Accessed on 06 October 2021).
  • Sarkar, S. (2012). The role of information and communication technology (ICT) in higher education for the 21st century. Science, 1(1), 30-41.
  • Štirbanović, Z., Stanujkić, D., Miljanović, I. and Milanović, D. (2019). Application of MCDM Methods for Flotation Machine Selection. Minerals Engineering, 137, 140-146.
  • Wang, T. C. and Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert systems with applications, 36(5), 8980-8985.
  • Yan, Z., Shi, R. and Yang, Z. (2018). ICT development and sustainable energy consumption: A perspective of energy productivity. Sustainability, 10(7), 2568.
  • Zavadskas, E. K., & Podvezko, V. (2016). Integrated Determination of Objective Criteria Weights in MCDM. International Journal of Information Technology & Decision Making, 1–17.
  • Zoraghi, N., Amiri, M., Talebi, G., & Zowghi, M. (2013). A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries. Journal of Industrial Engineering International, 9(1), 1-13.
  • Yousefi, A. (2011). The impact of information and communication technology on economic growth: Evidence from developed and developing countries. Economics of Innovation and New Technology, 20(6), 581-596.

COMPARATIVE ANALYSIS OF MCDM METHODS FOR THE ASSESSMENT OF ICT DEVELOPMENT IN G7 COUNTRIES

Year 2022, , 55 - 73, 29.06.2022
https://doi.org/10.36543/kauiibfd.2022.003

Abstract

Bilgi ve iletişim teknolojileri (BİT), her türlü görsel, işitsel basılı ve yazılı araçlar aracılığıyla bilgiye ulaşılmasını, bilginin işlenmesini sağlamaktadır. Bu çalışmada, Çok Kriterli Karar Verme (ÇKKV) yöntemleri kullanılarak G7 ülkelerinin BİT gelişiminin değerlendirilmesi amaçlanmıştır. Bu doğrultuda, Entropy yöntemi kriterlerin ağırlıklarını belirlemek amacıyla kullanılmış, Yakınlık Endeksli Değer (PIV), Değer Aralığı (ROV), ve Karmaşık Oransal Değerlendirme (COPRAS) yöntemleri ise alternatifleri sıralamak için kullanılmıştır. Bu çalışmanın son aşamasında, Entropy temelli PIV, ROV, COPRAS yöntemleri ile elde edilen sıralamalar ile Seviye temelli ağırlık değerlendirme (LBWA) temelli Uzlaşma Çözümüne Göre Alternatiflerin Ölçülmesi ve Sıralanması (MARCOS) yöntemi ile elde edilen sonuçlar kullanılarak karşılaştırmalı bir analiz gerçekleştirilmiştir. Çalışma sonunda, objektif ve subjektif yöntemlerle elde edilen kriter ağırlıklarının sıralama sonuçları üzerinde farklı etkiye neden olduğu saptanmıştır.

References

  • Aldalou, E. and Perçin, S. (2020). Application of integrated fuzzy MCDM approach for financial performance evaluation of Turkish technology sector. International Journal of Procurement Management, 13(1), 1-23.
  • Chatterjee, P., Athawale, V. M. and Chakraborty, S. (2011). Materials selection using complex proportional assessment and evaluation of mixed data methods. Materials and Design, 32, 851-860.
  • Chen, J. K. and Chen, I. S. (2015). The assessment of intellectual capital for the information and communication technology industry in Taiwan applying a hybrid MCDM model. European J. of International Management, 9(1), 88–107.
  • Das, M. C., Sarkar, B. and Ray, S. (2012). A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology. Socio-Economic Planning Sciences, 46, 230-241.
  • Ishida, H. (2015). “The effect of ICT development on economic growth and energy consumption in Japan”. Telematics and Informatics, 32(1), 79-88.
  • Madić, M. and Radovanović, M. (2015). Ranking of some most commonly used non-traditional machining processes using ROV and CRITIC methods. UPB Scientific bulletin, Series D: Mechanical Engineering, 77(2), 193-204.
  • Mahmud, A. J., Olander, E., Eriksén, S. and Haglund, B. J. (2013). Health communication in primary health care-A case study of ICT development for health promotion. BMC medical informatics and decision making, 13(1), 1-15.
  • McCarney, J. (2004). Effective models of staff development in ICT. European Journal of Teacher Education, 27(1), 61-72.
  • Meng, Q. and Li, M. (2002). New economy and ICT development in China. Information economics and policy, 14(2), 275-295.
  • Merkevičius, J. and Yadav, R. (2019). “Evaluation of ICT usages in virtual business by applying MCDM methods”. 22nd Conference for Young Researchers" Economics and Management, Vilnius, Lithuania.
  • Mufazzal, S. and Muzakkir, S. M. (2018). A New Multi-Criterion Decision Making (MCDM) Method Based on Proximity Indexed Value for Minimizing Rank Reversals. Computers & Industrial Engineering, 119, 427-438.
  • Nath, H. K. and Liu, L. (2017). Information and communications technology (ICT) and services trade. Information Economics and Policy, 41, 81-87.
  • OECD, Access to computer from home (Indicator), 2021a, “https://data.oecd.org/ict/access-to-computers-from-home.htm” (Accessed on 06 October 2021).
  • OECD, ICT employment (Indicator), 2021b, “https://data.oecd.org/ict/ict-employment.htm” (Accessed on 06 October 2021).
  • OECD, ICT goods exports (Indicator), 2021c, “https://data.oecd.org/ict/ict-goods-exports.htm” (Accessed on 06 October 2021).
  • OECD, ICT investment (Indicator), 2021d, “https://data.oecd.org/ict/ict-investment.htm” (Accessed on 06 October 2021).
  • OECD, ICT value added (Indicator), 2021e, “https://data.oecd.org/ict/ict-value-added.htm” (Accessed on 06 October 2021).
  • OECD, Internet Access (Indicator), 2021f, “https://data.oecd.org/ict/internet-access.htm” (Accessed on 06 October 2021).
  • Sarkar, S. (2012). The role of information and communication technology (ICT) in higher education for the 21st century. Science, 1(1), 30-41.
  • Štirbanović, Z., Stanujkić, D., Miljanović, I. and Milanović, D. (2019). Application of MCDM Methods for Flotation Machine Selection. Minerals Engineering, 137, 140-146.
  • Wang, T. C. and Lee, H. D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert systems with applications, 36(5), 8980-8985.
  • Yan, Z., Shi, R. and Yang, Z. (2018). ICT development and sustainable energy consumption: A perspective of energy productivity. Sustainability, 10(7), 2568.
  • Zavadskas, E. K., & Podvezko, V. (2016). Integrated Determination of Objective Criteria Weights in MCDM. International Journal of Information Technology & Decision Making, 1–17.
  • Zoraghi, N., Amiri, M., Talebi, G., & Zowghi, M. (2013). A fuzzy MCDM model with objective and subjective weights for evaluating service quality in hotel industries. Journal of Industrial Engineering International, 9(1), 1-13.
  • Yousefi, A. (2011). The impact of information and communication technology on economic growth: Evidence from developed and developing countries. Economics of Innovation and New Technology, 20(6), 581-596.
There are 25 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Nazlı Ersoy 0000-0003-0011-2216

Publication Date June 29, 2022
Acceptance Date November 26, 2021
Published in Issue Year 2022

Cite

APA Ersoy, N. (2022). COMPARATIVE ANALYSIS OF MCDM METHODS FOR THE ASSESSMENT OF ICT DEVELOPMENT IN G7 COUNTRIES. Kafkas Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 13(25), 55-73. https://doi.org/10.36543/kauiibfd.2022.003

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