Exploring Sentiment Analysis to Improve Supply Chain Decisions

Abstract

Purpose: Traditional information sharing and supply chain decisions are examined in light of emerging technologies. Focusing on the bullwhip effect, implications of information asymmetry for upstream firms, distant from a market, are highlighted. A novel approach is presented as effective for sensing changes in market demand without reliance on supply chain partners.Design/methodology/approach: Remedies for the bullwhip effect based on traditional supply chain management techniques and technologies are discussed, providing a series of succinct hypotheses that summarise key relationships. These hypotheses are used to establish the usefulness of an emerging technology. Findings: The paper explains how the emerging technology of sentiment analysis can meet the same fundamental requirements for supply chain managers. Through rapid and real-time monitoring of aggregated opinions expressed in social media, upstream suppliers can gather additional external data that reduce reliance on supply chain partners to achieve the same objectives. Research limitations/implications: The effectiveness of the process is demonstrated by logically extrapolating that the approach is valuable to upstream companies, after showing that a consumer-facing firm can use the approach with accuracy. Practical implications: The practical value of textual data analysis is highlighted to emphasise how upstream firms can improve sensitivity to market demand changes, without requiring collaboration with supply chain members.Originality/value: Through the novel application of sentiment analysis to support supply chain management, the value of this paper is the unique opportunity logically afforded upstream firms to increase transparency and speed of response to market changes.