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The estimates and forecasts of worldwide e-commerce

Published: 15 August 2005 Publication History

Abstract

Estimate and forecast of e-commerce status in the world is an important subject in the development of e-commerce. The development status of e-commerce can be reflected by the Internet users' number and the per capita trade volume on net. On the basis of the data collected extensively and the reference of relevant materials, this paper is to give a forecast of the Internet user number in the coming years using the cubic curve and Logistic curve prediction method, and then to calculate the short-term and long-term forecasts of the value of on-line transactions, which is expected to provide scientific basis for Chinese e-commerce development decision-making.

References

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United Nations Conference on Trade and Development, E-commerce and Development Report 2003, Internet: http://www.unctad.org/en/docs//ecdr2003_en.pdf, 2003, p xviii.
[2]
United Nations Conference on Trade and Development, E-commerce and Development Report 2004, Internet: http://r0.unctad.org/ecommerce/ecommerce_en/edr04_en.htm, 2004, p12
[3]
Chinese Electronic Commerce Annals Newsroom, Chinese Electronic Commerce Annals 2003, Chinese Electronic Commerce Annals Newsroom, Beijing, 2003, p20
[4]
IDC Research, Internet Usage and Commerce in Western Europe 2001-2006, Summary available, Internet: http://www.idc.com/getdoc.jhtml?containerId=fr2002_04_19_115126. 2002
[5]
Forrester Research Inc. Global Online Trade Will Climb to 18% of Sales. Brief dated 26 December, Internet: http://www.for-rester.com/ER/Research/Brief/0,1317,1372 0,FF.html. 2001
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eMarketer, Inc., The E-Commerce Trade and B2B Exchanges Report, March. Executive summary available. Internet: http://www.emar-keter.com. 2002
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United Nations Conference on Trade and Development E-commerce and Development Report 2004, Internet: http://r0.unctad.org/ecommerce/ecommerce_en/edr04_en.htm, 2004, pp. 1--10.
[8]
Yang Jianzheng, Principles and Practice of Electronic Commerce (Fourth Edition), Publishing House of Xidian University, Xi'an. 2004.
[9]
Zhu bingjing, Zhu Xianchen, Principles and Methods of Prediction, Publisheing House of Shanghai Jiaotong University, Shanghai, 1992.
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Wei Zongshu, Textbook of Probability and Statistics. Higher Education Press, Beijing, 1983.
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Terence Mills. Econometric Modelling of Financial Time Series, Cambridge University Press, 1995.
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Organization for Economic Cooperation and Development (OECD), Defining and Measuring E-Commerce: A Status Report, DSTI/ICCP/IIS(99)4/FINAL. 1999.
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Cited By

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  • (2015)Leveraging return policy for price premiumJournal of Revenue and Pricing Management10.1057/rpm.2015.1914:4(276-292)Online publication date: 19-Jun-2015
  • (2009)A Domain-Driven Approach for Detecting Event Patterns in E-MarketsWorld Wide Web10.1007/s11280-008-0053-112:1(69-86)Online publication date: 1-Mar-2009

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Published In

cover image ACM Other conferences
ICEC '05: Proceedings of the 7th international conference on Electronic commerce
August 2005
957 pages
ISBN:1595931120
DOI:10.1145/1089551
  • Conference Chairs:
  • Qi Li,
  • Ting-Peng Liang
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 August 2005

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Author Tags

  1. electronic commerce
  2. forecast
  3. logistic curve
  4. polynomial fit

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Cited By

View all
  • (2015)Leveraging return policy for price premiumJournal of Revenue and Pricing Management10.1057/rpm.2015.1914:4(276-292)Online publication date: 19-Jun-2015
  • (2009)A Domain-Driven Approach for Detecting Event Patterns in E-MarketsWorld Wide Web10.1007/s11280-008-0053-112:1(69-86)Online publication date: 1-Mar-2009

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