Watson Deliverable D2.1 – Key Stakeholders Expectations, Socioeconomic Drivers and Vulnerability Assessment of Food Systems (Interim Report)

Executive Summary:

This is the first deliverable of Watson Work Package 2 (WP2) ‘Socioeconomic Methodologies, Tools and
Approaches for Prevention of Food Fraud’. It introduces an updated methodology and workplan for WP2,
based on the first insights from research. Its aims are to update and detail the methodology followed within
WP2, to report on first results and insights from ongoing work in tasks 2.1 and 2.2 and to detail the future
work plan of WP2 based on these first findings. The results and analyses presented in this deliverable are to
be understood as preliminary, as for most of the tasks presented here data collection is not complete. Yet
these first results are of importance for Watson progress as they enable to identify the most salient
challenges encountered by supply chain stakeholders.

The deliverable first presents the overall approach taken within WP2 to build the knowledge base on the
socio-economic aspects of food fraud and how it can be addressed. It introduces the different methods used
for data collection and analysis. These are a literature review (T2.1), semi-structured interviews (T2.1, T2.2,
T2.3), workshops (T2.4), a survey including a choice experiment (T2.2) and an assessment of ethical guideline
(T2.5). Combining of these methods in different tasks provides Watson with a systemic perspective on
understanding food fraud vulnerabilities.

The preliminary results of tasks 2.1 and 2.2 are then presented. The literature review highlights critical
characteristics of the reviewed papers on the current state of the art of practices and technologies used in
food chains for transparency, including their primary focus areas determined by keywords, research
questions, and methods. In terms of technology, blockchain technology emerges as a crucial enabler for
traceability and transparency in the food supply chain, providing end-to-end traceability, data integrity, and
trust through its decentralized and immutable nature. The discussion centres on the benefits of blockchain
technology for food safety, waste prevention, distribution efficiency, and source identification of foodborne
illnesses. The text anticipates the further analysis and discussion of these preliminary findings in a
forthcoming Systematic Literature Review (SLR), which will be conducted in the coming months.

Across various supply chains, expert interviews have revealed common themes related to food fraud
prevention. These practices include mislabelling by botanical or geographical origin, adulteration, the use of
additives and counterfeiting. Challenges include limitations of existing analytical methods, a lack of uniform
regulation, information gaps and demands for improved traceability technology. The preliminary results
presented here will be further deepened in the coming months’ interviews within WP2 and in the Watson
use cases.