台灣的人們無論是天氣熱還是天氣冷的時候，都很喜歡在手搖飲料點購買手搖飲料，大家總是能在街上看到行人手上拿著一杯飲料。但是，總有一群人會花很多時間在想到底要喝什麼飲料。但是在花了很多時間之後，他們還是會選一樣的飲料。這份研究旨在探討人工智慧對話機器人的使用，是否可以降低人們選擇飲料和品牌時的困難，同時也達到使用者對於各個品牌和飲品的經驗累積，作為顧客對於商家關係管理的資訊平台。本研究目的期能找出商家關係管理與經驗導向如何協助顧客獲得更好的服務體驗，進而引導商家行銷符合顧客期待的價值主張。我們正在發展人工智慧對話機器人的雛型，這個機器人使用了RASA NLU作為自然語言處理(NLP)的訓練模型， Neo4j作為圖形資料庫，LINE則是作為用戶互動的介面。
本研究扮演人工智慧對話機器人開發過程中雛型測試的角色，採用情境式問卷，以顧客點選手搖飲料的過程中，對於品牌和飲品種類選擇的困難與否作為使用情境。使用者以顧客的角色揭露其在品牌和飲品種類選擇困難的四種組合條件中一種組合後，進入模擬與人工智慧對話機器人的互動畫面，並在使用者閱讀完所展示的互動畫面後，以確定其精確掌握對話歷程通過後，然後回答問卷問題
本研究中，總共有214位參與者，並獲得了214份有效回應。根據回應，我們可以看出人工智慧智慧機器人的確是可以協助人們在減少選擇手搖飲料的時間。經過統計分析問卷的結果，總結了人工智慧對話機器人可以達成經驗導向知識管理進而促進商家關係管理，同時或許也能在未來協助人們的行銷工具以達成更完整的顧客旅程，也能減少人們在決定要喝什麼手搖飲料的時間。本研究的結果可以提供給有關人工智慧對話機器人與商家關係管理相關研究的參考。

People in Taiwan love to drink hand-shaken tea at the tea shop, no matter whether the weather is cold or hot, you can always see people having their drinks on the street all the time. However, a group of people has been taking so much time to think about what they are going to drink, and after spending such a long time, they still have the same choice. The research would like to see how to use the conversational AI chatbot to assist people to lower the difficulties when choosing hand-shaken tea and brands, also record the users’ hand-shaken tea drinking experience as a customer information platform to realize Vendor Relationship Management (VRM). The goal of the research is to find out how VRM and experienced-based help customers to get a better customer experience to guide the businesses’ marketing strategies to meet customers’ needs. We have been developing a conversational AI chatbot with RASA NLU, Neo4j, and LINE. We use RASA NLU as an AI NLP learning model, Neo4j as a graph database, and LINE as a user conversational chatbot interface.
The conversational AI chatbot plays a role in developing the model, we will use a scenario survey and set up scenarios if people have choosing difficulties on brands and drinks. The participants will be assigned to one of four scenarios based on their responses in the survey to answer the questionnaire after clearly understanding the reading of the scenario conversation.
The research has 214 participants involved and got 214 responses. Based on the response from the participants, we can see the conversational AI chatbot can really help people to reduce their decision-making time on choosing drinks. According to the result of the survey, we can conclude that the conversational AI chatbot can realize experience-based knowledge management which enables the VRM, also can possibly become one of the marketing utilities to fulfill better customer journeys in the future, and can also help people to reduce their decision-making time. Hopefully in the future can become the reference for related research of the conversational AI chatbot and VRM.

摘要 i
Abstract ii
Acknowledgment iii
Table of Content iv
Lists of Figures and Tables vii
Chapter 1 Introduction 1
1.1 Research background 1
1.2 Research objectives 2
Chapter 2 Literature Review 3
2.1 Vendor Relationship Management (VRM) 3
2.2 Conversational AI chatbot 4
2.3 Experience-based knowledge management 5
2.4 A framework of experience-based knowledge management system 7
Chapter 3 Research Methodology 12
Chapter 4 Scenario Design and Survey Deployment 14
4.1 Scenario design 14
4.2 Survey design and distribution 15
Chapter 5 Results and Discussions 32
5.1 Participant profiles 32
5.2 Results 33
5.3 Discussions 38
5.3.1 Segment marketing strategies with the conversational AI chatbot 38
5.3.2 User experiences of the conversational AI chatbot 40
5.3.3 VRM as a marketing tool 41
5.3.4 Knowledge management 41
5.4 Research limitations 42
5.5 Future research 42
Chapter 6 Conclusion 44
References 46
Appendix 51
Appendix A. Questions of Scenario-based Survey （Chinese) 51
Appendix B. Questions Translated to English 56

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