Impact of Predictive Analytics on the Strategic Business Models of Supply Chain Management

Pradhan, I., Sarwar, D. and Hosseinian Far, A. (2022) Impact of Predictive Analytics on the Strategic Business Models of Supply Chain Management. In: Integrated Business Models in the Digital Age :. Palgrave Macmilan.

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Item Type:	Book Section
Abstract:	This paper explores and analyses the impact of Predictive Analytics on Supply Chain Management. Predictive Analytics is expanding, and many organisations are utilising this technology for improved benefits and profits. The supply chain consists of different sectors which can inculcate this technology for overall optimization. This research uses primary and secondary data to illustrate the aim and objective of the research. The literature review gives an in-depth overview of the concepts of Big Data and Predictive Analytics (PA) in Supply Chain Management. The outcomes of this research have led to the conclusions that PA plays a critical role in supply chain function optimization and can provide important insights for better decision making. They also point to the improvement of Supply Chain processes through the effective and efficient application of Predictive Analytics, resulting in improved performance, optimised procedures, and increased profits. In addition to that, many technologies can aid new start-ups and entrepreneurs towards success with their effective implementation and give rise to new business models to even larger organizations. This research can thus aid other organisations to understand the importance of PA and how well it can aid in strategic planning and execution and gain an advantage over their competitors.
Creators:	Pradhan, Ishwari, Sarwar, Dilshad and Hosseinian Far, Amin
Publisher:	Palgrave Macmilan
Faculties, Divisions and Institutes:	Faculties > Faculty of Business & Law > Business Systems & Operations
Date:	22 June 2022
Date Type:	Publication
Title of Book:	Integrated Business Models in the Digital Age :
Language:	English
ISBN:	978-3-030-97876-1
DOI:	https://doi.org/10.1007/978-3-030-97877-8_6
Status:	Published / Disseminated
Refereed:	Yes
Related URLs:	https://link.springer.com/chapter/10.100... https://pure.northampton.ac.uk/en/public...
URI:	http://nectar.northampton.ac.uk/id/eprint/16905

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