Designing a Food Product Traceability Software System Focusing in Consumers Social Interaction: A coffee use case

Traditionally, food traceability software systems have covered all the information and transformation of products from their origin to the retailer’s shelves. However, a significant amount of valuable information is lost by not including the perspective, experience, and opinions of the end consumer, which can be expressed through interactions with other consumers on social media platforms. This paper proposes a software system to face this problem. Incorporating the end consumers’ social media information into the traceability system, new valuable insights regarding product quality can emerge. These can improve business decision-making processes aimed at product and process improvement. Innovative technological components like Machine Learning, Blockchain and Natural Processing Language can help to broaden the scope of the system to include the consumer through their interactions on social media. To achieve this, quantitative and qualitative methodologies will be applied. Additionally, surveys will be conducted to examine food manufacturers and consumers opinions about Intelligent Enterprise Knowledge Management System (IEKMS) of food traceability. These surveys will be responded before and after IEKM use to gather quantitative and qualitative data. These results will help to proof or reject the hypothesis described in section IV.