{"id":11991,"date":"2022-04-18T14:32:30","date_gmt":"2022-04-18T11:32:30","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=11991"},"modified":"2022-05-03T08:15:18","modified_gmt":"2022-05-03T05:15:18","slug":"modelyuvannya-prognozu-rozvytku-mizhnarodnoyi-elektronnoyi-komercziyi","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=11991","title":{"rendered":"\u041c\u043e\u0434\u0435\u043b\u044e\u0432\u0430\u043d\u043d\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443 \u0440\u043e\u0437\u0432\u0438\u0442\u043a\u0443 \u043c\u0456\u0436\u043d\u0430\u0440\u043e\u0434\u043d\u043e\u0457 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u0457"},"content":{"rendered":"

<\/p>\n

\u041c\u041e\u0414\u0415\u041b\u042e\u0412\u0410\u041d\u041d\u042f \u041f\u0420\u041e\u0413\u041d\u041e\u0417\u0423 \u0420\u041e\u0417\u0412\u0418\u0422\u041a\u0423 \u041c\u0406\u0416\u041d\u0410\u0420\u041e\u0414\u041d\u041e\u0407 \u0415\u041b\u0415\u041a\u0422\u0420\u041e\u041d\u041d\u041e\u0407 \u041a\u041e\u041c\u0415\u0420\u0426\u0406\u0407<\/p>\n

MODELING OF FORECAST FOR THE DEVELOPMENT OF INTERNATIONAL ELECTRONIC COMMERCE<\/p>\n

\"\"<\/a> \u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 145-153. \u041d\u043e\u043c\u0435\u0440: \u21162, \u0422\u043e\u043c 1, 2022 (304)<\/strong><\/p>\n

https:\/\/doi.org\/10.31891\/2307-5740-2022-304-2(1)-20<\/a><\/p>\n

\u0414\u0423\u0411\u0415\u041b\u042c \u041c. \u0412.
\nhttps:\/\/orcid.org\/0000-0003-2229-0419<\/a>
\ne-mail: m.dubel@donnu.edu.ua<\/a>
\n\u0414\u043e\u043d\u0435\u0446\u044c\u043a\u0438\u0439 \u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0438\u0439 \u0443\u043d\u0456\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442 \u0456\u043c\u0435\u043d\u0456 \u0412\u0430\u0441\u0438\u043b\u044f \u0421\u0442\u0443\u0441\u0430<\/p>\n

Mykhailo DUBEL
\nVasyl Stus Donetsk National University<\/p>\n

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\u0421\u0428\u0410 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u043e. \u0422\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c, \u0443 2021 \u0440\u043e\u0446\u0456 \u043e\u0431\u0441\u044f\u0433 \u043f\u0440\u043e\u0434\u0430\u0436\u0443 \u0437\u0431\u0456\u043b\u044c\u0448\u0438\u0442\u044c\u0441\u044f \u043d\u0430 361 \u043c\u043b\u0440\u0434 \u0434\u043e\u043b. \u0430\u0431\u043e 8,43%, \u0443 2022 \u0440\u043e\u0446\u0456 \u2013 \u043d\u0430 740 \u043c\u043b\u0440\u0434 \u0434\u043e\u043b. \u0430\u0431\u043e 16% \u0442\u0430 \u0443 2023 \u0440\u043e\u0446\u0456 \u2013 408 \u043c\u043b\u0440\u0434 \u0434\u043e\u043b. \u0430\u0431\u043e 7,58% (24,7% \u0443 \u043f\u043e\u0440\u0456\u0432\u043d\u044f\u043d\u043d\u0456 \u0437 \u0434\u0430\u043d\u0438\u043c\u0438 2021 \u0440\u043e\u043a\u0443). \u0411\u0435\u0440\u0443\u0447\u0438 \u0434\u043e \u0443\u0432\u0430\u0433\u0438 \u0432\u0456\u0434\u043d\u043e\u0441\u043d\u0456 \u0437\u043c\u0456\u043d\u0438 \u043f\u043e\u043a\u0430\u0437\u043d\u0438\u043a\u0456\u0432, \u0432\u0430\u0440\u0442\u043e \u0437\u0430\u0437\u043d\u0430\u0447\u0438\u0442\u0438, \u0449\u043e \u0437\u0431\u0456\u043b\u044c\u0448\u0435\u043d\u043d\u044f \u0432\u0456\u0434\u0441\u043e\u0442\u043a\u0443 \u043f\u0440\u043e\u043d\u0438\u043a\u043d\u0435\u043d\u043d\u044f \u0406\u043d\u0442\u0435\u0440\u043d\u0435\u0442\u0443 \u0432 \u0441\u0432\u0456\u0442\u0456 \u0442\u0430 \u0437\u043c\u0435\u043d\u0448\u0435\u043d\u043d\u044f \u0441\u0435\u0440\u0435\u0434\u043d\u044c\u043e\u0433\u043e \u0440\u0456\u0432\u043d\u044f \u0431\u0435\u0437\u0440\u043e\u0431\u0456\u0442\u0442\u044f \u043c\u0430\u044e\u0442\u044c \u0431\u0456\u043b\u044c\u0448\u0438\u0439 \u0432\u043f\u043b\u0438\u0432 \u043d\u0430 \u0442\u0435\u043c\u043f\u0438 \u0440\u043e\u0437\u0432\u0438\u0442\u043a\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u0457 \u0442\u0430 \u043e\u0431\u0441\u044f\u0433\u0438 \u0440\u0435\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457 \u0447\u0435\u0440\u0435\u0437 \u043c\u0435\u0440\u0435\u0436\u0443 \u0406\u043d\u0442\u0435\u0440\u043d\u0435\u0442, \u043d\u0456\u0436 \u0444\u0430\u043a\u0442\u043e\u0440\u0438 \u00ab\u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u043e\u043d\u043b\u0430\u0439\u043d-\u043f\u043e\u043a\u0443\u043f\u0446\u0456\u0432\u00bb \u0447\u0438 \u00ab\u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u043a\u043e\u0440\u0438\u0441\u0442\u0443\u0432\u0430\u0447\u0456\u0432 \u043c\u043e\u0431\u0456\u043b\u044c\u043d\u0438\u043c\u0438 \u0442\u0435\u043b\u0435\u0444\u043e\u043d\u0430\u043c\u0438\u00bb.<\/p>\n

\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430: \u0431\u0430\u0433\u0430\u0442\u043e\u0444\u0430\u043a\u0442\u043e\u0440\u043d\u0438\u0439 \u0430\u043d\u0430\u043b\u0456\u0437, \u0434\u0456\u0434\u0436\u0438\u0442\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u044f, \u0435\u043a\u043e\u043d\u043e\u043c\u0456\u043a\u043e-\u043c\u0430\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u043d\u0435 \u043c\u043e\u0434\u0435\u043b\u044e\u0432\u0430\u043d\u043d\u044f, \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u0430 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u044f , \u0456\u043d\u0442\u0435\u0440\u043d\u0435\u0442-\u0442\u043e\u0440\u0433\u0456\u0432\u043b\u044f, \u0441\u0432\u0456\u0442\u043e\u0432\u0430 \u0442\u043e\u0440\u0433\u0456\u0432\u043b\u044f<\/p>\n

\u0420\u043e\u0437\u0448\u0438\u0440\u0435\u043d\u0430 \u0430\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u0430\u043d\u0433\u043b\u0456\u0439\u0441\u044c\u043a\u043e\u044e \u043c\u043e\u0432\u043e\u044e<\/strong><\/p>\n

The article is devoted to modeling forecasts of global e-commerce indicators. In accordance with the set goal, the paper provides basic information on the effective factor Y (e-commerce sales) and factors influencing the spread of the Internet in the world, the number of online shoppers, global GDP per capita, global unemployment, mobile phone users The number of Visa and MasterCard cards, the volume of transfers in world banks, thanks to the multifactor analysis of Eviews 8 out of seven factors, four factors remain (the spread of the Internet in the world, the number of online shoppers, global unemployment, the number of mobile users According to the constructed four-factor model, factors X affect 99.95% of the performance factor Y, the probability of influence of other factors is only 0.05%. BPstat software is shown forecast data for influencing factors. The indicators were based on the boxing-Jenkins linear parametric method for the factors “number of online shoppers” and “total number of mobile phone users” and on the basis of the “Olympus” method for the factors “Internet penetration in the world” and “average unemployment rate”. in the world”. The choice of forecasting methods is due to the fact that of the four possible methods, these had the smallest approximation error. According to the constructed trend lines, the volume of electronic sales for the period 2021-2023 will amount to 4,641, 5,381 and 5,789 billion dollars. USA, respectively. Thus, in 2021, sales will increase by 361 billion dollars. or 8.43%, in 2022 – by 740 billion dollars. or 16% and in 2023 – 408 billion dollars. or 7.58% (24.7% compared to 2021). Given the relative changes in the indicators, it should be noted that increasing the percentage of Internet penetration in the world and reducing the average unemployment rate have a greater impact on the pace of e-commerce and sales over the Internet than factors “number of online shoppers” or “mobile users” by phone”.<\/p>\n

Keywords: \u043cultifactor analysis, digitalization, economic and mathematical modeling, e-commerce, Internet trade, world trade<\/p>\n

\u041b\u0456\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430<\/strong><\/p>\n

    \n
  1. \u0421\u043b\u0454\u043f\u0454\u043d\u043a\u043e\u0432\u0430 \u0404., \u0414\u0443\u0434\u0430\u0440 \u0417. \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0441\u0442\u0438\u0447\u043d\u043e\u0433\u043e \u0430\u043d\u0430\u043b\u0456\u0437\u0443 \u0442\u0430 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0456\u0439 big data \u0432 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u0456\u0439 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u0457. \u041c\u0430\u0442\u0435\u0440\u0456\u0430\u043b\u0438 \u043a\u043e\u043d\u0444\u0435\u0440\u0435\u043d\u0446\u0456\u0439 \u041c\u0426\u041d\u0414<\/em>. 2020. \u0421. 61-62.<\/li>\n
  2. \u0427\u0435\u0440\u0432\u043e\u043d\u0430 \u041e. \u042e. \u0422\u0435\u043d\u0434\u0435\u043d\u0446\u0456\u0457 \u0440\u043e\u0437\u0432\u0438\u0442\u043a\u0443 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u0457. \u041d\u0430\u0443\u043a\u043e\u0432\u0438\u0439 \u0432\u0456\u0441\u043d\u0438\u043a \u0425\u0435\u0440\u0441\u043e\u043d\u0441\u044c\u043a\u043e\u0433\u043e \u0434\u0435\u0440\u0436\u0430\u0432\u043d\u043e\u0433\u043e \u0443\u043d\u0456\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u0443. \u0421\u0435\u0440\u0456\u044f \u00ab\u0415\u043a\u043e\u043d\u043e\u043c\u0456\u0447\u043d\u0456 \u043d\u0430\u0443\u043a\u0438\u00bb<\/em>. 2020. \u2116. 39. \u0421. 65-68.<\/li>\n
  3. \u041f\u2019\u044f\u0442\u043d\u0438\u0446\u044c\u043a\u0430 \u0413. \u0422., \u0413\u0440\u0438\u0433\u043e\u0440\u0435\u043d\u043a\u043e \u041e. \u041c. \u0415\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u0430 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u044f \u04122\u0421: \u0440\u043e\u0437\u0432\u0438\u0442\u043e\u043a \u0443 \u0441\u0445\u0456\u0434\u043d\u0456\u0439 \u0404\u0432\u0440\u043e\u043f\u0456, \u0440\u0438\u0437\u0438\u043a\u0438 \u0442\u0430 \u0435\u0444\u0435\u043a\u0442 \u0456\u043d\u0441\u0442\u0438\u0442\u0443\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u0432\u0438\u0442\u0456\u0441\u043d\u0435\u043d\u043d\u044f. \u041c\u0435\u043d\u0435\u0434\u0436\u043c\u0435\u043d\u0442 \u0442\u0430 \u043f\u0456\u0434\u043f\u0440\u0438\u0454\u043c\u043d\u0438\u0446\u0442\u0432\u043e \u0432 \u0423\u043a\u0440\u0430\u0457\u043d\u0456: \u0435\u0442\u0430\u043f\u0438 \u0441\u0442\u0430\u043d\u043e\u0432\u043b\u0435\u043d\u043d\u044f \u0442\u0430 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0438 \u0440\u043e\u0437\u0432\u0438\u0442\u043a\u0443<\/em>. 2019. \u2116. 1. \u0421. 121-129.<\/li>\n
  4. \u0410\u043d\u0434\u0440\u043e\u043d\u0456\u043a \u041e. \u041b., \u0412\u043e\u0440\u043e\u043d\u0456\u043d \u0410. \u0412. \u041c\u043e\u0436\u043b\u0438\u0432\u043e\u0441\u0442\u0456 \u0442\u0430 \u0437\u0430\u0433\u0440\u043e\u0437\u0438 \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u043e\u0457 \u043a\u043e\u043c\u0435\u0440\u0446\u0456\u0457 \u0432 \u0423\u043a\u0440\u0430\u0457\u043d\u0456. \u0415\u043a\u043e\u043d\u043e\u043c\u0456\u043a\u0430 \u0456 \u043e\u0440\u0433\u0430\u043d\u0456\u0437\u0430\u0446\u0456\u044f \u0443\u043f\u0440\u0430\u0432\u043b\u0456\u043d\u043d\u044f<\/em>. 2021. \u0421. 118-130.<\/li>\n
  5. Zatonatska T, Dluhopolskyi O, Chyrak I, Kotys N 2019 The internet and e-commerce diffusion in European countries (modeling at the example of Austria, Poland, and Ukraine). Innovative Marketing<\/em> 15(1) \u0441. 66-75<\/li>\n
  6. Individuals using the Internet (% of population) URL: https:\/\/data.worldbank.org\/indicator\/IT.NET.USER.ZS<\/li>\n
  7. Number of digital buyers worldwide. URL: https:\/\/www.statista.com\/statistics\/251666\/number-of-digital-buyers-worldwide\/<\/li>\n
  8. GDP per capita (current US$). URL: https:\/\/data.worldbank.org\/indicator\/NY.GDP.PCAP.CD<\/li>\n
  9. Unemployment, total (% of total labor force) (modeled ILO estimate) URL: https:\/\/data.worldbank.org\/indicator\/SL.UEM.TOTL.ZS<\/li>\n
  10. Number of smartphone users from 2016 to 2021. URL: https:\/\/www.statista.com\/statistics\/330695\/number-of-smartphone-users-worldwide\/<\/li>\n
  11. Number of Mastercard credit cards in the United States and worldwide. URL: https:\/\/www.statista.com\/statistics\/618137\/number-of-mastercard-credit-cards-worldwide-by-region\/<\/li>\n
  12. Personal remittances, received (current US$). URL: https:\/\/data.worldbank.org\/indicator\/BX.TRF.PWKR.CD.DT?view=chart<\/li>\n<\/ol>\n

    References<\/strong><\/p>\n

      \n
    1. Sliepienkova Ye., Dudar Z. Vykorystannia prohnostychnoho analizu ta tekhnolohii big data v elektronnii komertsii. Materialy konferentsii MTsND. 2020. S. 61-62.<\/li>\n
    2. Chervona O. Yu. Tendentsii rozvytku elektronnoi komertsii. Naukovyi visnyk Khersonskoho derzhavnoho universytetu. Seriia \u00abEkonomichni nauky\u00bb. 2020. \u2116. 39. S. 65-68.<\/li>\n
    3. Piatnytska H. T., Hryhorenko O. M. Elektronna komertsiia V2S: rozvytok u skhidnii Yevropi, ryzyky ta efekt instytutsionalnoho vytisnennia. Menedzhment ta pidpryiemnytstvo v Ukraini: etapy stanovlennia ta problemy rozvytku. 2019. \u2116. 1. S. 121-129.<\/li>\n
    4. Andronik O. L., Voronin A. V. Mozhlyvosti ta zahrozy elektronnoi komertsii v Ukraini. Ekonomika i orhanizatsiia upravlinnia. 2021. S. 118-130.<\/li>\n
    5. Zatonatska T, Dluhopolskyi O, Chyrak I, Kotys N 2019 The internet and e-commerce diffusion in European countries (modeling at the example of Austria, Poland, and Ukraine). Innovative Marketing<\/em> 15(1) \u0441. 66-75<\/li>\n
    6. Individuals using the Internet (% of population) URL: https:\/\/data.worldbank.org\/indicator\/IT.NET.USER.ZS<\/li>\n
    7. Number of digital buyers worldwide. URL: https:\/\/www.statista.com\/statistics\/251666\/number-of-digital-buyers-worldwide\/<\/li>\n
    8. GDP per capita (current US$). URL: https:\/\/data.worldbank.org\/indicator\/NY.GDP.PCAP.CD<\/li>\n
    9. Unemployment, total (% of total labor force) (modeled ILO estimate) URL: https:\/\/data.worldbank.org\/indicator\/SL.UEM.TOTL.ZS<\/li>\n
    10. Number of smartphone users from 2016 to 2021. URL: https:\/\/www.statista.com\/statistics\/330695\/number-of-smartphone-users-worldwide\/<\/li>\n
    11. Number of Mastercard credit cards in the United States and worldwide. URL: https:\/\/www.statista.com\/statistics\/618137\/number-of-mastercard-credit-cards-worldwide-by-region\/<\/li>\n
    12. Personal remittances, received (current US$). URL: https:\/\/data.worldbank.org\/indicator\/BX.TRF.PWKR.CD.DT?view=chart<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":4,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[63],"tags":[],"_links":{"self":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/11991"}],"collection":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=11991"}],"version-history":[{"count":5,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/11991\/revisions"}],"predecessor-version":[{"id":12395,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/11991\/revisions\/12395"}],"wp:attachment":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=11991"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=11991"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=11991"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}