Understanding Sentiment and Emotion through ChatGPT to Support Emotion-based Management Decision Making

Abstract

Effective management decision-making is a key element in organisational success. In the ever-evolving digital age, human interaction with computer systems is increasingly complex and diverse. One increasingly popular form of interaction is the use of Chatbots that are based on artificial intelligence technology. Chatbots trained using language models, such as ChatGPT, have demonstrated their ability to communicate with humans naturally and can be used in a variety of applications, including in management contexts. This research aims to fill this knowledge gap by proposing and implementing a customised ChatGPT model for understanding sentiment and emotion in the context of management decision-making. This research is a literature review that adopts a qualitative method approach, which means it will analyse and interpret data by relying on information and text from various sources. The study results show that understanding sentiment and emotion through ChatGPT is an important innovation that can support emotion-based management decision-making in an increasingly complex and rapidly changing business environment. By analysing and recognising feelings, views and attitudes in text, ChatGPT provides valuable insights for managers to respond to market changes, understand customer and employee views, enhance brand and reputation, and create a healthier and more productive work environment.

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