APTM: A Model for Pervasive Traceability of Agrochemicals

A critical analysis of the integration of blockchain and artificial intelligence for supply chain

The integration between blockchain and artificial intelligence (AI) has gained a lot of attention in recent years, especially since such integration can improve security, efficiency, and productivity of applications in business environments characterised by volatility, uncertainty, complexity, and ambiguity. In particular, supply chain is one of the areas that have been shown to benefit tremendously from blockchain and AI, by enhancing information and process resilience, enabling faster and more cost-efficient delivery of products, and augmenting products' traceability, among others. This paper performs a state-of-the-art review of blockchain and AI in the field of supply chains. More specifically, we sought to answer the following three principal questions: Q1-What are the current studies on the integration of blockchain and AI in supply chain?, Q2-What are the current blockchain and AI use cases in supply chain?, and Q3-What are the potential research directions for future studies involving the integration of blockchain and AI? The analysis performed in this paper has identified relevant research studies that have contributed both conceptually and empirically to the expansion and accumulation of intellectual wealth in the supply chain discipline through the integration of blockchain and AI.

Traceability Information Model for Sustainability of Black Soybean Supply Chain: A Systematic Literature Review

Traceability information as a solution option becomes an important task for the industry in providing products, preparing sustainable raw materials, and ensuring adequate safety quality. The emergence of these demands makes the industry perform tracking in order to prepare product inventories ranging from raw materials to products that have been produced. Based on these reasons, the scope of this paper is to provide a systematic review of the literature on various aspects of implementing information traceability models and sustainability of supply chain on economic, social, environmental, technological, institutional, and infrastructural dimensions. For this purpose, we use the Scopus, Science Direct, EBSCO Host, and ProQuest databases. We used the PRISMA model to identify, filter, and test for the eligibility of articles to be included. We selected 52 articles contributed by this search engine. We found was that between 2018 to 2021 there was increasing interest in this research. The dominant traceability information model in the article uses blockchain, the rest use operations research (OR), Google Earth Engine (GEE), website-based, Unified Modeling Language (UML), Extensible Markup Language (XML), physical markup language (PML), logit, enterprise resource planning (ERP), soft independent modelling of class analogies (SIMCA), and Spatially Explicit Information on Production to Consumption Systems (SEI-PCS).

A Systematic Literature Review of Blockchain-Enabled Supply Chain Traceability Implementations

In recent years, traceability systems have been developed as practical tools for improving supply chain (SC) transparency and visibility, especially in health and safety-sensitive sectors like food and pharmaceuticals. Blockchain-related SC traceability research has received significant attention during the last several years, and arguably blockchain is currently the most promising technology for providing traceability-related services in SC networks. This paper provides a systematic literature review of the various technical implementation aspects of blockchain-enabled SC traceability systems. We apply different drivers for classifying the selected literature, such as (a) the various domains of the available blockchain-enabled SC traceability systems and relevant methodologies applied; (b) the implementation maturity of these traceability systems along with technical implementation details; and (c) the sustainability perspective (economic, environmental, social) prevalent to these implementations. We provide key takeaways regarding the open issues and challenges of current blockchain traceability implementations and fruitful future research areas. Despite the significant volume and plethora of blockchain-enabled SC traceability systems, academia has so far focused on unstructured experimentation of blockchain-associated SC traceability solutions, and there is a clear need for developing and testing real-life traceability solutions, especially taking into account feasibility and cost-related SC aspects.