研究生: |
呂佳蓉 Lu, Chia-Jung |
---|---|
論文名稱: |
客服聊天機器人與自我揭露程度在外送情境下對消費者行為之影響 ---以咖啡外送為例 The Effect of Different Types of Customer Service Chatbots and Self-Disclosure on Customer Behavior in Delivery Service---An Example for Coffee Delivery Service |
指導教授: |
蔣旭政
Chiang, Hsu-Cheng |
口試委員: | 伍柏翰 宋涵鈺 蔣旭政 |
口試日期: | 2021/10/12 |
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: | 2021 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 150 |
中文關鍵詞: | 聊天機器人 、AI 、外送 、咖啡 、客服 、自我揭露 、消費者行為 、品牌態度 、購買意願 、口碑推薦意願 、品牌忠誠度 |
英文關鍵詞: | Chatbot, AI, delivery, coffee, customer service, self-disclosure, consumer behavior, brand attitude, purchase intention, word-of-mouth recommendation willingness, brand loyalty |
研究方法: | 實驗設計法 、 內容分析法 |
DOI URL: | http://doi.org/10.6345/NTNU202101617 |
論文種類: | 學術論文 |
相關次數: | 點閱:197 下載:42 |
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隨著客戶服務成為品牌與消費者間的重要連結,客服系統的自動化越來越重要,因此聊天機器人成為客服系統自動化的首要選擇,而隨著疫情的升溫,外送的需求大幅增加,使得客服問題層出不窮,加上台灣對於咖啡飲品的需求增加,因此適當的客服平台能為品牌方提升效益、節省成本。本研究以咖啡外送平台之客服聊天機器人為背景,實驗設計為2客服聊天機器人(AI式聊天機器人vs.規則式聊天機器人)× 2自我揭露程度(自我揭露程度高 vs. 自我揭露程度低),探討客服聊天機器人搭配自我揭露程度對消費者行為是否具有差異,並以年齡作為調節變項,探討年齡(數位移民vs.數位原民)是否會調節客服聊天機器人並對消費者行為產生差異,將消費者行為分為四個依變項(品牌態度、購買意願、口碑推薦意願以及品牌忠誠度)。本研究主要採用實驗法作為驗證研究假設分析之依據,以此驗證受測者在與聊天機器人互動過後,所產生的消費者行為是否與研究假設相符,再輔以滯後序列分析以了解消費者在與AI式聊天機器人互動過程中的行為,會為品牌方帶來哪些優勢。
本研究結果證實(1)「AI式聊天機器人」相較於「規則式聊天機器人」有較佳的消費者行為、(2)「自我揭露程度高」相較於「自我揭露程度低」有較佳的 消費者行為、(3)「與AI式聊天機器人互動」,相較於「與規則式聊天機器人互動」, 「數位原民」能產生較佳的消費者行為、(4)「與AI式聊天機器人互動」相較於「與規則式聊天機器人互動」,「自我揭露程度高」能產生較佳的消費者行為、(5)消費者與AI式聊天機器人互動過程中,所產生的消費者行為,能提高客戶服務效率與品質進而減少人力成本。
As customer service has become an important link between brands and consumers, the automation of customer service systems has become important. Therefore, chatbots have become the first choice for customer service system automation.
A 2 customer service chatbot(Rule-Based Chatbot vs. AI-Based Chatbot)× 2 self-disclosure degree(high vs. low), to discuss whether customer service chatbot with self-disclosure levels have any difference in consumer behavior, and consider age as an adjustment variable, to discuss whether age(digital immigrants vs. digital natives) will adjust customer service chatbots and make differences in consumer behavior. Consumer behavior is divided into four dependent variables(brand attitude, purchase intention, intention to recommend word of mouth, and brand loyalty).
The result of this research shows that:(1)compared to the Rule-Based Chatbot, AI-Based Chatbot leads to a better consumer behavior. ;(2)compared to the low self-disclosure, high self-disclosure degree leads to a better consumer behavior. ; (3)compared to Rule-Based Chatbot, AI-Based Chatbot with digital natives leads to a better consumer behavior. ;(4)compared to Rule-Based Chatbot, AI-Based Chatbot with high self-disclosure degree leads to a better consumer behavior. ;(5)Consumer behaviors generated during the interaction between consumers and AI-Based chatbots can improve the efficiency, quality of customer service and reduce labor costs.
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