Leveraging real-time digital twins for smart livestreaming platforms to enhance consumers’ experience

Abstract Livestreaming platforms (LSP) as a shopping medium have grown in recent years. This commercial platform offers an unprecedented opportunity for vendors to deliver their services and create value for consumers. Vendors seeking a competitive advantage are finding that LSP enables them to promote their products and generate digital data rapidly for real-time decisions, while consumers are gaining unique shopping experiences. LSP has many advantages but also some critical limitations that hinder applications. While the extent literature on LSP highlights its strength, studies on LSP shortcomings are neglected or highly superficial and fragmented with little guidance on how to overcome limitations. Against this backdrop, this conceptual paper introduces a novel analytical model, real-time Live-Streaming Digital Twins (LsDT) as a conceptual guide to investigate LSP, enhance its strength, and overcome its major limitations. A real-time digital twin (DT) is a virtual replica or representation of a physical entity that are continuously updated with real-time data from sensors or other sources. This enables managers to monitor, analyze, and optimize their assets in real-time and value to consumers. The paper offers significant theoretical and practical contributions, and delineates important avenues for future research, emanating from the conceptual framework.