隨著人工智慧技術普及，AI聊天機器人(AI Chatbot)已廣泛應用於各產業，作為服務延伸或替代之關鍵工具。中華航空身為國籍傳統航空公司，於2025年5月全面升級AI客服，然而過往研究較少針對航空產業情境下進行深入探討。因此，本研究基於推敲可能性模型(Elaboration Likelihood Model, ELM)，探討使用者如何處理AI 聊天機器人傳達之資訊，並區分為中央路徑（資訊品質、服務品質）與邊陲路徑（航空公司聲譽、感知新穎性），分析其對使用者內心評估（感知AI 聊天機器人智能性、AI 聊天機器人信任感）之影響，進而誘發滿意度與航空公司黏著度。此外，本研究亦納入AI 工具使用習慣作為調節變數。本研究以同時具備搭乘華航與使用其AI客服經驗者為對象，回收294份有效問卷，並採用偏最小平方法結構方程模型(PLS-SEM)進行統計。數據顯示，資訊品質、服務品質、感知新穎性對於感知AI聊天機器人智能性、AI聊天機器人信任感有顯著影響；感知AI聊天機器人智能性、AI聊天機器人信任感對於AI聊天機器人滿意度有顯著影響；AI聊天機器人滿意度對於航空公司黏著度有顯著影響。最後，也發現AI工具使用習慣會顯著正向影響資訊品質和感知AI聊天機器人智能性之間的關係。根據結果，本研究建議航空業應持續優化AI聊天機器人回覆的品質、減少外部連結跳轉，並整合會員數據提供個人化行程建議，達成滿意度後確實提升對該航空的黏著度。

AI chatbots have been widely implemented across various industries as critical tools for service extension or substitution. China Airlines, a leading legacy carrier, launched a comprehensive upgrade of its AI customer service in May 2025. However, prior research has seldom explored the context of the aviation industry. Therefore, based on the Elaboration Likelihood Model (ELM), this study investigates how users process information conveyed by AI chatbots.
Targeting individuals with experience in both flying with China Airlines and interacting with its AI chatbot, 294 valid questionnaires were collected and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The empirical results indicate that Information Quality, Service Quality, and Perceived Innovativeness significantly influence Perceived Intelligence and Trust in AI chatbot. These internal evaluations, in turn, significantly affect Satisfaction, which ultimately leads to increased Stickiness to Airline. Finally, the study found that AI tool Usage Habit significantly and positively moderates the relationship between Information Quality and Perceived Intelligence.
Based on these findings, this study suggests that the aviation industry should continuously optimize the response quality of AI chatbots, minimize external link redirections, and integrate member data to provide personalized itinerary recommendations, thereby effectively enhancing stickiness through heightened satisfaction.

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