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- Title
Análisis bibliométrico de la investigación en big data y cadena de suministro.
- Authors
Duque Hurtado, Pedro Luis; Giraldo Castellanos, José David; Osorio Gómez, Iván Darío
- Abstract
As contemporary markets must manage large amounts of data, big data has become a crucial tool to address this need. In fact, competitive businesses are employing big data in various processes, including supply chain management. This paper analyzes existing scientific publications on the implementation of big data in the supply chain. To do so, a systematic literature review was conducted using the PRISMA methodology, and relevant documents were selected from the Scopus and Web of Science databases. Then, bibliometric techniques were applied; the documents were classified into three groups, representing the roots, trunk, and leaves of a knowledge tree; and research clusters were identified. The results revealed that using big data in the supply chain enhances decision-making, competitiveness, and logistics efficiency. It is concluded that this topic is receiving increasing attention from researchers, with China leading the way, and that strategic organizational changes are necessary. Although big data brings benefits in terms of efficiency and decision-making, it also faces challenges related to transition and resistance to change. The research clusters identified here have addressed aspects of big data such as performance, adaptability, management capacity, and connectivity. Finally, future research directions are proposed for big data in the areas of automation, the Internet of Things (IoT), and global challenges.
- Subjects
SUPPLY chain management; BIG data; ORGANIZATIONAL change; SCIENCE databases; WEB databases
- Publication
Revista CEA, 2023, Vol 9, Issue 20, p1
- ISSN
2390-0725
- Publication type
Article
- DOI
10.22430/24223182.2448