Date of Award

8-2025

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Agricultural and Applied Economics

Committee Chair/Advisor

Dr. Alba J. Collart

Committee Member

Dr. Elizabeth Canales

Committee Member

Dr. Anastasia Thayer

Abstract

In 2022, the United States Department of Agriculture (USDA) Partnerships for Climate-Smart Commodities (PCSC) program set aside over $3 billion to be invested in 141 projects for agricultural products produced using practices that reduce greenhouse gas emissions or increase carbon sequestration. Although the majority of the PCSC funding was canceled in 2025, save a few selected projects that could potentially receive funding under the USDA’s new Advancing Markets for Producers initiative, there is no USDA-certified label to verify the climate-smart commodities that already received funding or similar products that exist in the market. However, third-party verified carbon footprint labels can still signal a product’s commitment to carbon reduction. Meanwhile, the USDA-certified organic label is well-established among consumers, clearly identifying organically produced goods. However, fraudulent labeling of these attributes remains a concern, undermining consumer trust. Blockchain technology is considered a potential tool to combat labeling fraud and boost consumer trust by creating a verifiable record of production practices along the supply chain.

This thesis examines United States consumer preferences for the use of blockchain-based and standard (non-blockchain) traceability QR codes as tools to provide information about cow’s milk and ribeye steak products bearing the USDA-certified organic label and newly introduced carbon footprint labels by The Carbon Trust. Chapter One evaluates consumer willingness to pay (WTP) for the use of blockchain technology to track organic and carbon footprint claims for cow’s milk. Chapter Two assesses WTP for the same technology used for ribeye steak. Methodologically, both chapters employ discrete choice experiments (DCEs) and analyze the impact of a proposed geographically informed price vector design on model fit and consumer food choice behavior. Our findings show that consumer preferences for blockchain technology vary based on the commodity being tracked and the combination of labels present. This thesis offers valuable insights for dairy and beef producers considering implementing carbon-reducing and organic agriculture certifications and integrating blockchain technology and digital traceability initiatives into their supply chains.

Available for download on Monday, August 31, 2026

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