As a consumer, it is important to understand the implications of consumer patterns in developing countries. Furthermore, for a student interested in trade and governance, this map can provide a clear example of who benefits more in the global supply chains.
1. Data Collection from WTO, ILO, World Bank, H&M and Adidas annual reports. WTO: Identify main import and export countries of textiles and clothing. ILO: Information on minimum wages, union membership and earnings per occupation (from the textile and manufacturing industry) within countries. H&M and Adidas: Data collection on main suppliers, net sales, number of workers,number of female worker and number of stores.
During this process, there was a lot of data cleaning and preparing the datasets for geocoding. . Some of these datasets were easy to find, such as the information from WTO, Word Bank and ILO. However, information about the brands were hard to find, as much of the data was inside Annual Reports that were on PDF files. There weren’t many options to download information as spread sheets. Thus, much time was spent building datasets from scratch, starting with converting PDF files into Excel Sheets and later geocoding these datasets
2. Geocoding those datasets with ArcGIS and turning them into choropleth and point maps (shp files). Additionally, datasets from WTO, ILO and World Bank were joined to a World Map data set (shp. file)
3. Transferred those maps to Carto and styled them.
4. Transferred data sets to build a Webmap, where information layers on union membership, minimum wages, textile exporters and importers could be contrasted with the supply chain of each brand.
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