A Decade of Research on Blood and Supply Chain Management: A Bibliometrics Analysis

Abstract

Effective Blood Supply Chain Management has significant impacts on health and cost savings. This study aims to identify relevant research on the blood supply chain and recent trends in the Google Scholar database over the past decade (2012-2022) using bibliometric analysis. Articles were collected using the Publish or Perish software, yielding 339 articles after screening. Mendeley software was used for reference management and continuity, while VOSviewer software was used for article mapping. The journals with the highest number of articles were Computer & Chemical Engineering and Transfusion, each with 16 articles. The most cited article was by Jabbarzadeh et al. (2014), cited 357 times. Four clusters were identified, with the most frequent terms in each cluster being "blood," "model," "demand," and "blood product." The results indicate that technologies such as machine learning, AI, and blockchain, along with the development of integrated information systems, are the main focus for improving the efficiency and effectiveness of blood supply chain management. Managerial implications include enhanced blood stock management, optimized distribution, and reduced risk of shortages or overstock. The implementation of these technologies allows for more informed decision-making, ensures transparency and security in the supply chain, and improves coordination among stakeholders to ensure adequate and timely blood availability