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Tipi, Nicoleta
(2021).
URL: http://ciltuk.org.uk/LRN2021
Abstract
Purpose
Analysing data, constructing different models that evaluate different aspects of already existing data, developing models that will have the power to predict behaviours and give further understanding into the labyrinth of data all form part of analytics (Tipi, 2021, p4). The aim of this paper is to take a critical view on how business analytics in the supply chain are being considered and to challenge the current research agenda in the field of supply chain analytics.
Research Approach
To carry out this study, an evaluation of systematic literature reviews dealing with issues of analytics in the supply chain has been considered. The initial search started with 266 articles and following further filtration stages resulted in a restricted list of 20 articles that have been included in the final analysis (Tipi, 2021). These articles are evaluated in terms of their defined outcome that allows to challenge and set a future research agenda for the field of supply chain analytics.
Findings and Originality
This work takes a critical angle in its concluding remarks and puts forward a set of issues and challenges that face this area of research. A number of key themes are emerging as a result of this analysis some of which being: big data analytics, big data driven sustainable supply chain, smart factory, smart farming, resilience, big data technology, enabling technologies, self-thinking supply chains, etc. The value of this work sits in identifying common themes among the selected reviews, as well as capturing those themes unique to a particular review article. This material details a comprehensive list of issues to be considered as a future research agenda in this field.
Research Impact
This work brings theoretical contributions to the field of business analytics and supply chain analytics and highlights a set of research gaps.
Practical Impact
This paper offers practical impact by highlighting the challenges and opportunities offered by the implementation of different analytical tools and techniques that could have a shorter or longer impact to an organisation when implemented in practice.
References
Tipi, Nicoleta (2021). Supply Chain Analytics and Modelling: Quantitative Tools and Applications, Kogan Page, ISBN: 9780749498627, UK.
This paper considers extracts from Supply Chain Modelling and Analytics by Nicoleta Tipi © 2021 and reproduced with permission from Kogan Page Ltd.
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About
- Item ORO ID
- 78886
- Item Type
- Conference or Workshop Item
- ISBN
- 1-904564-66-6, 978-1-904564-66-9
- Keywords
- business analytics; supply chain
- Academic Unit or School
-
Faculty of Business and Law (FBL) > Business
Faculty of Business and Law (FBL) - Copyright Holders
- © 2021 Logistics Research Network
- Depositing User
- Nicoleta Tipi