Scanning the Transparency of Commodity Supply Chains: Lessons from Beef Production in the Brazilian Amazon

Publikation: KonferencebidragPaperForskning

Abstract

In recent years, a flurry of supply chain tracing systems and research initiatives have emerged to address beef-related deforestation in the Brazilian Amazon, the cattle industry being responsible for 90% of forest loss. To what extent are these transparency systems capable of promoting accountability for deforestation? Based on multisite field research, interviews, public transparency evaluations, and an extensive collection of reports and audits, we examine the anatomy, evolution, and key transparency dilemmas germane to Brazil’s pioneering supply chain transparency initiatives (i.e. the Beef Zero Deforestation Commitment [Beef ZDC]). Our results highlight four key dilemmas that hinder the capacity of transparency to bring about accountability. These dilemmas, denoted by the acronym SCAN, include the ubiquity of misrepresentation in self-reporting, complexity that hampers tracing and popular comprehension, access to public information failures, and non-comprehensive coverage of the supply chain. SCAN has implications for commodity supply chains around the world. Our findings enjoin policymakers to strengthen commitments to transparency and, given the failures of current systems, consider using remote monitoring, individual vehicle and cattle tracking, and co-reporting systems.
OriginalsprogEngelsk
Publikationsdato2024
Antal sider48
StatusUdgivet - 2024
BegivenhedSASE 36th Annual Conference 2024: For Dignified and Sustainable Economic Lives: Disrupting the Emotions, Politics, and Technologies of Neoliberalism - University of Limerick, Limerick, Irland
Varighed: 27 jun. 202429 jun. 2024
Konferencens nummer: 36
https://sase.org/event/2024-limerick/

Konference

KonferenceSASE 36th Annual Conference 2024
Nummer36
LokationUniversity of Limerick
Land/OmrådeIrland
ByLimerick
Periode27/06/202429/06/2024
Internetadresse

Emneord

  • Transparency
  • Deforestation
  • Supply chain tracing
  • Amazon
  • Cattle
  • Beef

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