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A social media analytic framework for improving operations and service management: A study of the retail pharmacy industry

Yuanzhu Zhan, Runyue Han, Mike Tse, Mohd Helmi Ali and Jiayao Hu

Technological Forecasting and Social Change, 2021, vol. 163, issue C

Abstract: The revolution in the digital economy is forcing the retail pharmacy industry to develop new business models to achieve operational excellence. A large amount of user-generated content on social media can be captured and analysed to help organisations gain insights into market requirements and enhance business intelligence. Accordingly, this study proposes an analytic framework for retail pharmacy organisations to: a) use social media and highlight the most-discussed topics by consumers, b) to identify the key areas for improvement based on the most negative comments received, and c) to determine the connections amongst the important concepts and enhance customer loyalty by adding values to consumers. We conduct an in-depth analysis on the Twitter platforms of the three largest retail pharmacy organisations in the UK: Boots, Lloyds and Superdrug. The findings show that issues with marketing, customer service and product are the key improvement areas for the retail pharmacies. Particularly, Boots received an overall better sentiment performance than Lloyds and Superdrug. We also determine the relationships amongst the important concepts discussed by consumers. The analysis generates insights into the use of social media for supporting pharmacy organisations in developing their social media strategies as well as improving their operations and service quality.

Keywords: Social media analytics; Retail pharmacy industry; Twitter data; Text mining; Sentiment analysis (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:163:y:2021:i:c:s0040162520313305

DOI: 10.1016/j.techfore.2020.120504

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