This paper introduces a conceptual framework for integrating Conversational AI (CAI), specifically conversational agents (CAs), with Decision Support Systems (DSS) to enhance Supply Chain Management (SCM) decision-making processes. In today's complex supply chain environment, characterized by diverse processes and entities operating across different geographic locations, the effective use of AI in DSS is crucial. The proposed framework envisions a Conversationally Enabled Supply Chain (CESC) where decision-makers interact with the DSS using natural language through a CA, facilitating tasks such as data analysis, scenario analysis, and simulation. The choice of a conceptual framework as a research tool provides a systematic approach to collect and organize elements, offering a clear reference structure and a common language. This framework aims to enhance understanding, guide research and analysis, and integrate knowledge from diverse sources, contributing to a holistic understanding of the proposed CA-empowered DSS for SCM. The paper emphasizes the significance of CESC and sets the stage for future research and development in the domain, providing a foundation for ongoing work.

A Conversationally Enabled Decision Support System for Supply Chain Management: A Conceptual Framework / Pinto, Roberto; Lagorio, Alexandra; Ciceri, Claudia; Mangano, Giulio; Zenezini, Giovanni; Rafele, Carlo. - 58:(2024), pp. 801-806. (Intervento presentato al convegno 18th IFAC Symposium on Information Control Problems in Manufacturing, INCOM 2024 tenutosi a aut nel 2024) [10.1016/j.ifacol.2024.09.198].

A Conversationally Enabled Decision Support System for Supply Chain Management: A Conceptual Framework

Mangano, Giulio;Zenezini, Giovanni;Rafele, Carlo
2024

Abstract

This paper introduces a conceptual framework for integrating Conversational AI (CAI), specifically conversational agents (CAs), with Decision Support Systems (DSS) to enhance Supply Chain Management (SCM) decision-making processes. In today's complex supply chain environment, characterized by diverse processes and entities operating across different geographic locations, the effective use of AI in DSS is crucial. The proposed framework envisions a Conversationally Enabled Supply Chain (CESC) where decision-makers interact with the DSS using natural language through a CA, facilitating tasks such as data analysis, scenario analysis, and simulation. The choice of a conceptual framework as a research tool provides a systematic approach to collect and organize elements, offering a clear reference structure and a common language. This framework aims to enhance understanding, guide research and analysis, and integrate knowledge from diverse sources, contributing to a holistic understanding of the proposed CA-empowered DSS for SCM. The paper emphasizes the significance of CESC and sets the stage for future research and development in the domain, providing a foundation for ongoing work.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2996439
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