An estimation model for hypertension drug demand in retail pharmacies with the aid of big data analytics

Papanagnou, C and Matthews-Amune, O 2017, An estimation model for hypertension drug demand in retail pharmacies with the aid of big data analytics , in: 19th IEEE Conference on Business Informatics, 24-26 July 2017, Thessaloniki, Greece.

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Abstract

The unpredictability of consumer preference observed in the last few years has coincided with the global digital data explosion as consumers are increasingly relying on internet information to guide their buying behaviour. The emergence of this trend has resulted in demand volatility and uncertainty in the retail industry, leading to negative consequences on inventory control and on shareholder profits in the long-run. This paper examines whether retail pharmacies in Abuja, Nigeria may exploit the increasing availability of relevant big data (structured, semi-structured and unstructured) from different sources to anticipate the changes on demand profiles for antihypertensive medication. In order to examine this, we consider a VARX model with non-structured data as exogenous to obtain the best estimation

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > Salford Business School > Salford Business School Research Centre
Journal or Publication Title: IEEE 19th Conference on Business Informatics (CBI) 2017
Publisher: IEEE
Related URLs:
Depositing User: Dr Christos Papanagnou
Date Deposited: 06 Jul 2017 10:21
Last Modified: 02 Oct 2017 08:01
URI: http://usir.salford.ac.uk/id/eprint/42860

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