研究生: |
林晏竹 LIN, Yen-Chu |
---|---|
論文名稱: |
AI客服聊天機器人與媒介豐富度對消費者態度與行為意圖之影響—以電商平台為例 The Effect of AI Customer Service Chatbots and Media Richness on Consumer Attitude and Behavior Intentions - Take an E-commerce Platform as an Example |
指導教授: |
蔣旭政
Chiang, Hsu-Cheng |
口試委員: |
林慧斐
LIN, Hui-Fei 林芝璇 LIN, Jhih-Syuan 蔣旭政 CHIANG, Hsu-Cheng |
口試日期: | 2022/03/31 |
學位類別: |
碩士 Master |
系所名稱: |
大眾傳播研究所 Graduate Institute of Mass Communication |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 200 |
中文關鍵詞: | 聊天機器人 、人工智慧 、客戶服務 、媒介豐富度 、社會資訊處理模式 、消費者行為 、電商平台 |
英文關鍵詞: | Chatbot, Artificial Intelligence, Customer Service, Media Richness, Social Information Processing model, Consumer Behavior, E-commerce Platform |
DOI URL: | http://doi.org/10.6345/NTNU202200459 |
論文種類: | 學術論文 |
相關次數: | 點閱:406 下載:0 |
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行動商務與即時通訊軟體的蓬勃成長使聊天機器人受到高度的發展與運用。為了提供良好的客戶服務,電商平台利用聊天機器人作為即時服務媒介創造更優質的服務體驗。然而,任務導向聊天機器人卻無法解決在既定腳本外更深入、細微的消費問題,進而影響消費者行為。由此,本研究透過將人工智慧應用於客服聊天機器人,期望藉此提升消費者行為。本研究以電商平台為研究背景,採2(對話導向AI聊天機器人 vs. 任務導向聊天機器人)x2(高媒介豐富度 vs. 低媒介豐富度)二因子組間實驗設計,且就個人相關使用經驗(網路購物售後服務經驗)做進一步研究分析,並以聊天機器人態度、持續使用意圖與口碑推薦意願等三元素為消費者行為組合作為依變項,探討自變項與依變項兩者之間的交互作用與影響。
本研究結果證實:(1)對話導向AI聊天機器人相較於任務導向聊天機器人,對於消費者行為有較佳的影響;(2)高媒介豐富度相較於低媒介豐富度,對於消費者行為有較正面的影響;(3)無論是何種媒介豐富度,在對話導向AI聊天機器人中,對於聊天機器人態度、持續使用意圖與口碑推薦意願皆不會有差異;(4)在任務導向聊天機器人中,高媒介豐富度相較於低媒介豐富度,會產生較佳的聊天機器人態度、持續使用意圖與口碑推薦意願;(5)使用客服聊天機器人後,相較於使用前會產生較正面的消費者行為;(6)具有網路購物售後服務經驗的消費者,相較於無網路購物售後服務經驗的消費者,會產生較佳的持續使用意圖,但在聊天機器人態度與口碑推薦意願則無顯著差異。
The flourishing mobile commerce and instant messaging software have made chatbots highly developed and used. To provide more satisfactory customer service, e-commerce platforms use chatbots as an instant service medium to create a better service experience. However, task-oriented chatbots cannot solve the deeper and nuanced consumption problems beyond the established script, thereby affecting consumer behavior. Accordingly, this study hopes to improve consumer behavior by applying artificial intelligence to customer service chatbots. Based on the research background of e-commerce platforms, this study adopted a 2 (chit-chat AI chatbots vs task-oriented chatbots) x2 (high media richness vs low media richness) 2-factor, between-subject experimental design, and uses personal correlation Use experience (online shopping after-sales service experience) for further research and analysis, and uses the three elements of attitude toward chatbot, continuance intention and word-of-mouth intention to combine consumer behavior as dependent variables to explore the interaction and effects between independent variables and dependent variables.
The results indicated that: (1) compared with task-oriented chatbots, chit-chat AI chatbots demonstrated more favorable behavior;
(2) compared with chatbots with low media richness, chatbots with high media richness generated more favorable behavior;
(3) no matter what level of media richness, in chit-chat AI chatbots, there will be no significant differences in attitude toward chatbot, continuance intention, and word-of-mouth intention;
(4) in task-oriented chatbots, compared with low media richness, high media richness generated a more favorable attitude toward chatbot, continuance intention, and word-of-mouth intention;
(5) compared with before using the customer service chatbot, using the customer service chatbot demonstrated more favorable behavior;
(6) compared with consumers without online shopping after-sales service experience, consumers with online shopping after-sales service experience generated more favorable continuance intention, but there will be no significant differences in attitude toward chatbot and word-of-mouth intention.
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