Social media and expert analysis cast light on the mechanisms of underlying problems in pharmaceutical supply chain: An exploratory approach

Mohammad Reza Seddigh, Aida Targholizadeh, Sajjad Shokouhyar, Sina Shokoohyar

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Purpose
This study aims to identify the major underlying problems associated with pharmaceutical supply chains (PSC), and the mechanisms through which these issues are happening and propose the main solutions to them. This research also assesses the value of the data extracted from social media.

Methodology
This study extracted data from Twitter and combines the power of an effective software (Python) with expert analysis (Delphi study in three rounds) to identify the key issues in pharmaceutical industry that have been neglected by decision makers. Furthermore, combination of the two powerful tools (Python and Delphi) is another merit of this work since it is a sophisticated method.

Findings
This research has recognized that there are four major key problems that are highly critical and need urgent attention and proposes the key resolutions to these issues. The expert panel believed that the results from Twitter data are very helpful and gives decision makers new insight into pharmaceutical supply chain.

Originality
Several items gathered this study make it unique. First, by using social media, this paper has discovered the underlying problems of PSC that are not usually detected by PSC management systems or are being neglected by them. Second, through a Delphi study, this research discovered the patterns of these issues and mechanisms by which they are formed and also provided new effective solutions. Many other papers have just stated that social media is useful for supply chains, but the vast majority of them did not actually conduct an in-depth analysis on social media to discover problems in pharmaceutical supply chain, and very few studies explored the mechanisms by which those problems were formed.
Original languageEnglish
Article number122533
JournalTechnological Forecasting and Social Change
Volume191
DOIs
Publication statusPublished - 1 Jun 2023
Externally publishedYes

Keywords

  • Big data analytics
  • Delphi
  • Pharmaceutical supply chain
  • Sentiment analysis
  • Supply chain management
  • Twitter data

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