JBRMR
Online ISSN 2056-6271 ICO Registration Number: ZA522255
Accepting submissions

Article Details

Volume 02 Issue 2

Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail

Published: 28 Feb 2012 Issue:Volume 02 Issue 2 Apr 2008 Author details below

Soumitra Sharma

Institute of Technology, Banaras Hindu University

Reading View How to Cite BibTeX / RIS XML Metadata JSON Metadata View Issue
PDF file referenced for this article is missing from server storage.
Share

Article Metrics Report

Views, downloads, citations, engagement
Views 571032
Downloads 40
Citations 0
Engagement 571072

Cited by

Current citation count

Research summary

E-Tail, or Internet based retailing, has emerged as an innovative channel for retailers to reach target consumers in the comfort of their homes. E-Tailing has exhibited an upward trend across the world in recent years, though it’s more prevalent in certain regions such as Europe and North America. With varying levels of Internet penetration, telecom infrastructure, the business and legal environment, e-tailing is at varying stages of maturity in countries across the globe. In order to objectively compare the actual preparedness of various countries to exploit their potential for e-tail, an analytical model was built using Principal Component Analysis (PCA). This model returns a numeric value, coined as the e-Tail Readiness Index. A set of countries were subsequently ranked on the basis of this index. As expected, while the more developed countries of Europe and North America occupied the top slots, the emerging economies of Eastern Europe and Latin America occupied the middle slots. Surprisingly, India and China figured right at the bottom of the heap

Article History

Published 28 Feb 2012

How to Cite

Sharma, S.. (2012). Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail. Journal of Business and Retail Management Research, Volume 02 Issue 2.

Citation Context

Archive cited by No internal citing article yet
Reference depth 3 sources listed
DOI record DOI not listed
Citation signal Citation exports and metadata ready

APA

Sharma, S.. (2012). Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail. Journal of Business and Retail Management Research, Volume 02 Issue 2.

MLA

Sharma, Soumitra. "Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail." Journal of Business and Retail Management Research, Volume 02 Issue 2, 2012.

Chicago

Soumitra Sharma. "Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail." Journal of Business and Retail Management Research Volume 02 Issue 2 (28 Feb 2012).

Harvard

Sharma, S. (2012) Using Principal Component Analysis (PCA) to Rank Countries on their Readiness for E-Tail. Journal of Business and Retail Management Research, Volume 02 Issue 2

References

  1. (2005). ‘ACNielsen Announces One-Tenth of the World’s Population Shopping Online: 627 Million People Have, including 325 Million in the Last Month’. ACNielsen News Release Retrieved from http://www2.acnielsen.com/news/20051019.shtml on December 22, 2007  (2002). Canadian IT Law Newsletter. Canadian IT Law association
  2. Retrieved from http://www.it-can.ca/newsletters/040402.pdf  on December 22, 2007 (2003). Annexure on Principal Component Analysis. Department of Information Technology, Ministry of Communications and Information Technology, Government of India Retrieved from http://www.mit.gov.in/download/ANNEX_242-254.PDF on December 22, 2007  (2005). the 2005 E-Readiness Rankings. The Economist Intelligence Unit and the IBM Institute for Business Value – White Paper Retrieved from http://graphics.eiu.com/files/ad_pdfs/2005Ereadiness_Ranking_WP.pdf on December 22, 2007
  3. The Economist Intelligence Unit (EIU) Database – http://www.eiu.com

Related Articles

Browse Articles

Failure demand – how part of the total demand can become a burden
AI anxiety and consumer identity: Emotional responses to intelligent systems through the identity-aligned emotional model — quantitative evidence from a mediterranean high -uncertainty-avoidance consumer sample
Impact of heat waves on Spanish tourism demand
Colour and consumer buying behaviour in the UK fashion industry
The impact of the Qatar blockade on customer relationship management
Understanding the impact of reward and recognition, work life balance, on employee retention with job satisfaction as mediating variable on millennials in Indonesia
Organizational culture and job satisfaction: a study Of organized retail sector
How to win back the disgruntled consumer? The omni-channel way
Retail turnover clauses in an online world
Brand awareness of 'generation y' customers towards doughnut retail outlets in India
Failure demand – how part of the total demand can become a burden
AI anxiety and consumer identity: Emotional responses to intelligent systems through the identity-aligned emotional model — quantitative evidence from a mediterranean high -uncertainty-avoidance consumer sample
Impact of heat waves on Spanish tourism demand
Colour and consumer buying behaviour in the UK fashion industry
The impact of the Qatar blockade on customer relationship management