1 Introduction

We study E-Commerce job offers in a selected list of countries based on two data sets:

We limit our scope to Australia, Canada, China, Denmark, France, Germany, India, Italy, South Korea, Spain, United Kingdom, and United States.

The Glassdoor original data features only job titles containing the term “E-Commerce” or close variants, when we restrict it to our countries in scope we keep 7,770 observations.

The LinkedIn original data features only jobs offered in the countries in scope, when we restrict it to observations whose job title contains the term “E-Commerce” or close variants, and to locations that can be identified, we keep 17,551 observations.

Those two filtered data set were merged into a main dataset of 25,311 observations, to merge them we kept as many variables as possible, manually creating new variables for both datasets (GlassDoor: seniority and employment type; LinkedIn: sector) based on text matching of job titles and descriptions.

We display below a further breakdown of the data by country and language identified from job description.

country LinkedIn: English LinkedIn: Other GlassDoor: English GlassDoor: Other All: English All: Other
Australia 300 2 72 0 372 2
Canada 1468 95 352 72 1820 167
China 377 100 286 15 663 115
Denmark 61 26 15 22 76 48
France 54 2138 84 825 138 2963
Germany 252 3249 92 1011 344 4260
India 1231 6 473 1 1704 7
Italy 68 353 22 168 90 521
South Korea 28 18 11 1 39 19
Spain 160 357 26 56 186 413
United Kingdom 2880 2 1066 3 3946 5
United States 4293 3 3104 13 7397 16
All 11172 6349 5603 2187 16775 8536