The UNCTAD B2C E-commerce Index 2020: Spotlight on Latin America and the Caribbean

 

Switzerland Climbs to Top of Global E-Commerce Index

https://unctad.org/webflyer/unctad-b2c-e-commerce-index-2020-spotlight-latin-america-and-caribbean

e-Commerce & retail employment

There is a perception that online e-commerce is decreasing employment in the traditional bricks and mortar retail industry. In order to gauge this assumption, data on overall retail trade and pure play online retail employment in the European Union (EU) and the United States was analyzed. Apart from overall retail trade employment, both also have a breakdown of employment by pure play retail e-commerce (i.e., no physical store). The current International Standard Industrial Classification (ISIC) has a class (4791) under retail trade that encapsulates retail e-commerce: "Retail sale via mail order houses or via Internet." Mail order is included but likely comprises a small portion. Both the EU and the United States have employment data for this category.

Retail employment grew in both between 2011 and 2016. In the EU, traditional retail trade did decline but this was more than made up for by the increase in retail sales over the Internet and mail order. In the USA, both traditional retail and e-commerce employment grew. Bricks and mortar retail also grew e-commerce related employment. However these figures are not possible to determine.

Retail trade employment change (000s), 2011-2016
	EU	USA
Retail	(120.51)	674
via Internet	220.13	118
Net	99.62	792

Note: Retail excludes via Internet.
Source: Eurostat and Bureau of Labor Statistics.

Retail e-commerce also generates downstream employment in logistics including delivery services and warehousing. A study found that in the United States, around 400,000 jobs were created in the electronic shopping and warehouse industries between 2007 and 2017 compared to a loss of 140,000 in brick and mortar retail (i.e., a net gain of 260,000); 2.1 jobs were created in warehousing for each job in e-commerce (Mandel 2017).

The United States Bureau of Labor Statistics compiles detailed occupational data on employment in the electronic shopping industry. Around two fifths of occupations are administrative, just over 15% are related to transportation and 6% have to do with computer and related activities. Arts and design occupations such as catalog creation and photography accounted for 3%.

NAICS 454100 - Electronic Shopping and Mail-Order Houses, May 2017, United States
Code	Occupation	Employment	Share
43-0000	Office and Administrative Support Occupations	165,950	42%
53-0000	Transportation and Material Moving Occupations	61,340	16%
41-0000	Sales and Related Occupations	40,360	10%
13-0000	Business and Financial Operations Occupations	29,820	8%
11-0000	Management Occupations	23,960	6%
15-0000	Computer and Mathematical Occupations	23,210	6%
51-0000	Production Occupations	13,870	4%
29-0000	Healthcare Practitioners and Technical Occupations	13,090	3%
27-0000	Arts, Design, Entertainment, Sports, and Media Occupations	10,930	3%
	Others	8,700	2%

UNCTAD B2C E-COMMERCE INDEX 2017

UNCTAD B2C E-commerce Index 2017 (TN/UNCTAD/ICT4D/09) 03 Oct 2017

UNCTAD E-commerce Index

UNCTAD's 2015 Information Economy Report has as its theme e-commerce for developing countries. A tool included in the report is a B2C e-commerce index that allows countries to benchmark themselves against others and gauge their strengths and weaknesses in various e-commerce aspects.
The selection of indicators for the index was made in several steps. First, proxy indicators were assigned to the various elements needed to fully carry out an e-commerce transaction including payment and delivery. This includes access to the Internet by the consumer, a web site to receive the order, a payment method and a delivery method. Second, a statistical analysis was performed by regressing these indicators on the percentage of individuals who have made an online purchase for 77 countries where such data was available. Indicators with the highest statistical significance were then selected to create the index. These indicators are shown below. The results of the regression show a good fit, with a coefficient of determination of 0.85. All indicators, except secure servers, are in a normative form where 100 is the maximum value. The data on secure servers were normalized to 100 by rescaling the values.  The values of the indicators were then averaged to obtain an index value.

1. Percentage of individuals using Internet (ITU, Eurostat and national surveys, 2013, 216 economies)
2. Credit card (% age 15+) (World Bank Findex survey, 2011, 149 economies) 
3. Secure Internet servers (per 1 million people) (World Bank, 2013, 209 economies)
4. Percentage of the population having mail delivered at home (Universal Postal Union, 2012, 168 economies)

The index comprises 130 economies with all available indicators using data for 2013 (or latest year available). Several observations can be made about the highest ranked economies. Firstly, most are from developed economies. Secondly, most are relatively small and/or distant from major market centers. Smaller physical retail markets appear to stimulate online shopping including a significant amount from abroad. The top ten ranked developing economies in the index are all upper-middle and high-income economies, six of which from Asia and the remaining four from Latin America.

Top 10 countries in UNCTAD e-commerce index

Top 10 developing countries in UNCTAD e-commerce index

A review of the index with reply comments is here: http://ictlogy.net/20150401-a-critique-to-unctad-b2c-e-commerce-index/