What is it about?
This paper explores a system called Enterprise Just-in-Time Decision Support System (EJDSS) that uses deep learning to analyze social media data for quick business decisions, especially in marketing. A case study on reverse logistics recycling shows EJDSS’s high performance (83.62% precision, 78.44% robustness, 83.67% F1-score, 3.79% variance). The study demonstrates how businesses can use social media insights to enhance decision-making and optimize processes, particularly in recycling and customer engagement.
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Why is it important?
This paper is important because it introduces a new system (EJDSS) that helps businesses make quick and smart decisions by analyzing social media data. Social media contains a wealth of information about customer opinions and market trends, but it's hard to process due to its unstructured nature. EJDSS uses advanced deep learning techniques to turn this data into actionable insights. This is especially useful for improving marketing strategies and optimizing processes like recycling. The case study in the paper shows that EJDSS is highly accurate and effective, making it a valuable tool for businesses looking to leverage social media data for better decision-making.
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This page is a summary of: Unveiling just-in-time decision support system using social media analytics: a case study on reverse logistics resource recycling, Industrial Management & Data Systems, May 2024, Emerald,
DOI: 10.1108/imds-12-2023-0921.
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