本研究旨在深入探討於服務主導邏輯(Service-Dominant Logic, SD-Logic)框架下，非人類行動者如人工智慧物聯網(AIoT）如何參與智慧交通領域中的價值共創(Value Co-creation)。近年來，數位轉型的浪潮席捲全球，各國紛紛投入智慧城市(Smart City)建設，智慧交通作為智慧城市的核心應用領域之一而受到廣泛關注。在此背景下，服務生態系統中，AIoT等非人類行動者將如何整合資訊並與其他行動者協作以達價值共創之目的是重要研究課題。然而，既有文獻對於非人類行動者的探討仍較少見，大多數研究聚焦於人類行動者之間的互動，故本研究透過理論與實務的結合，以智慧交通中領先企業的遠通電收公司(FETC)為研究對象，探討個案企業中的行動者之間如何協作，共同創造出具有價值之服務生態系統。
研究結果指出，非人類行動者如AI與IoT技術，透過自主資訊蒐集、即時資料分析與動態決策制定，成功地參與智慧交通服務生態系統內的資源整合與價值共創過程。遠通電收透過AI演算法即時調整交通管理策略，並利用IoT感測器收集道路與車輛資訊，有效提高ETC系統的效率與使用體驗。此外，智慧停車場系統亦透過AIoT的應用，改善了停車資源的即時配置與使用者的便利性，進一步凸顯數位技術在價值共創中的主動性角色。綜合上述，本研究不僅拓展了服務主導邏輯理論中對非人類行動者的討論範疇，亦提供智慧交通領域之服務創新的具體建議。未來研究建議可擴大個案數量與範圍，深入探討不同情境下非人類行動者的角色與參與模式，以進一步豐富理論與實務的發展。

This study aims to explore in depth how non-human actors, such as Artificial Intelligence and the Internet of Things (AIoT), participate in value co-creation within the smart transportation sector under the framework of Service-Dominant Logic (SD-Logic). In recent years, the global wave of digital transformation has driven many countries to invest in the development of smart cities, where smart transportation has emerged as a core application area. Against this backdrop, it is a crucial research issue to investigate how non-human actors like AIoT integrate information and collaborate with other actors within service ecosystems to co-create value.
However, existing literature offers limited discussion on non-human actors, with most studies focusing on interactions among human actors. To address this gap, the present research combines theoretical and practical perspectives by examining the case of Far Eastern Electronic Toll Collection Co., Ltd. (FETC), a leading firm in Taiwan's smart transportation industry. It investigates how various actors within the case organization collaborate to jointly create a value-laden service ecosystem.
The findings reveal that non-human actors such as AI and IoT technologies actively engage in resource integration and value co-creation through autonomous data collection, real-time analysis, and dynamic decision-making. FETC utilizes AI algorithms to adjust traffic management strategies in real time and employs IoT sensors to gather road and vehicle data, thereby enhancing the efficiency and user experience of the ETC (Electronic Toll Collection) system. Furthermore, the smart parking system, empowered by AIoT applications, improves real-time allocation of parking resources and user convenience, further highlighting the proactive role of digital technologies in value co-creation.
In summary, this study not only expands the scope of SD-Logic by incorporating the role of non-human actors but also provides concrete recommendations for service innovation in the smart transportation sector. Future research is encouraged to include more cases across different contexts to further examine the roles and participation patterns of non-human actors, thereby enriching both theoretical insights and practical applications.

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