從聊天機器人探究對話式服務體驗：認知負荷觀點

研究目的：本研究以刺激－機制－反應模式與資訊系統成功模式為基礎，從認知負荷觀點探究消費者與聊天機器人之互動品質（即系統品質、資訊品質、服務品質）如何影響其認知、態度與持續使用意圖。研究設計與方法：本研究採便利抽樣方式蒐集193筆曾經使用過聊天機器人的顧客，並以最小平方法進行結構方程模式分析。研究結果：研究結果顯示（1）消費者知覺系統、資訊與服務品質分別會負向與正向地影響認知負荷與使用態度；（2）消費者之持續使用意圖則是會受到認知負荷與使用態度所影響。研究限制與啟發：在數位環境中，每位消費者擁有的服務接觸體驗、平台使用經驗或使用習慣皆不同，則不同程度的先備知識與經驗對於消費者在面對不同資訊內容時，會展現出不同的處理能力，故未來研究可針對消費者認知基模對於認知負荷的影響進行探究。實務意涵：本研究建議企業應導入對話式商務模式，透過聊天機器人提供消費者良好的互動品質（即資訊系統、資訊內容與服務傳遞），不僅能降低消費者的認知負荷，更能創造優質的服務體驗。價值：過往研究主要著墨於聊天機器人介面之設計、擬人化及穩定性等功能性因素，而本研究進一步從資訊過載與互動品質觀點建構一實證模型，探究消費者之創新對話式服務體驗。

關鍵字

聊天機器人；對話式商務模式；刺激－機制－反應模式；認知負荷；互動品質

並列摘要

Purpose - This study examines the issues of cognitive load within the context of stimulus-organism-response theory and the information systems success model in developing a conceptual model by which to characterize interactions with chatbots in terms of system quality, information quality, and service quality. Design/methodology/approach - Structural equation modeling is employed to analyze survey data collected from 193 chatbot users recruited via convenience sampling. Findings - Our results reveal the following: (1) Customers perceiving a positive interaction with chatbots are less encumbered by cognitive load and are more likely to express a positive attitude toward the chatbot system; and (2) Reduced cognitive load and a positive attitude toward the chatbot both have significantly positive effects on the intention of consumers to continue using the system. Research limitations/implications - Within the context of digital environment, each consumer has different service contact experience, platform experience or habits. The capability to deal with various information may vary along with different levels of prior knowledge and experience of a consumer. Therefore, scholars can further study the impact of consumer's cognitive schema on their cognitive load in the future. Practical implications/Social implications - Our research suggests that companies might benefit from developing a chatbot-based conversational service to provide consumers with good interactive quality, which can not only reduce consumers' cognitive load, but also create excellent service experience. Originality/value - Most of the existing literature on chatbots has focused on its interface design, anthropomorphism, and stability, with relatively little research examining the cognitive mechanisms involved in the use of this technology. To contribute to this knowledge gap, this study develops a empirical model by which to characterize interactions with chatbots in terms of information overload and interactive quality (i.e., system quality, information quality, and service quality). The research findings provide valuable insights for scholars as well as marketers seeking to leverage the benefits of chatbots to enhance the customer experience.

並列關鍵字

chatbot ； conversational commerce ； stimulus-organism-response theory ； cognitive load ； interactive qualities

參考文獻

Ayres, Paul (2020), “Something Old, Something New from Cognitive Load Theory,” Computers in Human Behavior, 113, https://doi.org/10.1016/j.chb.2020.106503.

Campitelli, Guillermo (2015), “Memory Behavior Requires Knowledge Structures, Not Memory Stores,” Frontiers in Psychology, 6, 1696, https://doi.org/10.3389/fpsyg.2015.01696.

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Sands, Sean, Carla Ferraro, Colin Campbell, and Hsiu-Yuan Tsao (2020), “Managing the Human-Chatbot Divide: How Service Scripts Influence Service Experience,” Journal of Service Management, https://doi.org/10.1108/JOSM-06-2019-0203.

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從聊天機器人探究對話式服務體驗：認知負荷觀點

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