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Published June 19, 2020 | Version v1
Dataset Open

Data, materials, methods and codes for publication Reis et al., "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.

  • 1. Earth and Life Institute, Université catholique de Louvain

Description

Explanation of the data and code used for the article: "Understanding the stickiness of commodity supply chains is key to improving their sustainability", 2020, One Earth.

 The file: "StickinessAnalysisCompleteGeneric_CleanUpdate18-5-2020.R" is the R code/ script containing all the data preparation and the stickiness analysis.

The file: "BRAZIL_SOY_V2.3_WITH_DOMESTIC_TRADERS.csv" contains the raw data of Brazil's soy exports and domestic consumption from trase.earth. This dataset can also be obtained from trase.earth in the latest version.

The file: "NodesCiS.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.

The file: "NodesCiR.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.

The file "NodesCiSMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.

The file "NodesCiRMunCountry.csv" is a table with the Ci (stickiness on linkages) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.

The file: "NodesWPiS.csv" is a table with the WPi (stickiness on flows) measured for the types of supply chain relationships: A. logistics hubs supplying traders, and D. traders supplying countries. They are put together in the same table because they are all "sending" relationships.

The file: "NodesWPiR.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: C. traders sourcing from logistics hubs, and E. countries sourcing from traders. They are put together in the same table because they are all "receiving" relationships.

The file "NodesWPiSMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: B. logistics hubs supplying countries (directly not passing through traders). This is separate in another table because it is a direct sending relationship from LHs to countries.

The file "NodesWPiRMunCountry.csv" is a table with the Ci (stickiness on flows) measured for the types of supply chain relationships: F. countries sourcing from logistics hubs (directly not passing through traders). This is separate in another table because it is a direct receiving relationship from LHs to countries.

Files

BRAZIL_SOY_V2.3_WITH_DOMESTIC_TRADERS.csv

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Additional details

Related works

Is supplement to
Preprint: 10.2139/ssrn.3508883 (DOI)

Funding

MIDLAND – Developing middle-range theories linking land use displacement, intensification and transitions 677140
European Commission
COUPLED – Operationalising telecouplings for solving sustainability challenges related to land use 765408
European Commission
IKnowFood: Integrating Knowledge for Food Systems Resilience BB/N02060X/1
UK Research and Innovation
GCRF Trade, Development and the Environment Hub ES/S008160/1
UK Research and Innovation