在2016年LINE、FB、IBM、微軟等各大公司已經開始在認知運算與聊天機器人市場投入大量的心力與資源，除了提供許多開發的套件與框架，也開發了許多不同產業和應用領域的聊天機器人，包括了旅遊、批發零售、航空、娛樂、教育等等，正式進入了對話式商務的元年。大家在透過網路購物上又多了一個新的選擇，只要行動裝置有社群通訊軟體，不管在何時何地，只要透過簡單的對話即能達到使用者的需求。
而過去的文獻指出，科技接受模型(TAM)與資訊系統成功模型(ISS)中的相關因素會影響聊天機器人的使用意願，但較少提出針對上述模型構面的相關實務開發指引，因此本研究透過現況觀察以及文獻資料蒐集，針對聊天機器人找出四個可以改善的地方，包括對話流程、推薦機制、認知理解與訓練資料的建置，並提出TAM與ISS相關構面的開發指引，再以電玩遊戲領域為基礎，進行改善開發出概念性的聊天機器人---遊戲專家(Game Expert)，再透過問卷進行使用性調查，驗證是否有達到改進的效果並提升使用意願。
根據驗證問卷統計資料結果顯示，本研究的開發的確有改善整體聊天機器人的使用體驗，也有效解決了本研究提出的聊天機器人的問題，並提升使用者的使用意願。

In 2016, LINE, FB, IBM, Microsoft and other major companies have developed in cognitive computing and put a lot of efforts and resources in chatbots market. In addition to providing a lot of development kits and frameworks, they also developed different industries and applications of the chatbots, including the tourism, wholesale and retail, aviation, entertainment, education, etc. that officially entered the first year of Conversational Commerce. People have a new option for online shopping, and as long as mobile device has social networking apps, you can meet the needs of users with a simple conversation whenever they need.
In past studies, constructors of TAM and ISS model will affect the willingness of chatbot, but lack of relevant practice development guidelines for the above model. Through the observation of the status quo and the collection of literature,we find that chatbots are still lots of things need to be improved .So we propose four problems, including dialogue process, recommendation mechanism, understanding of sentence and training data generating. After that we propose guidelines based on TAM and ISS model and create a proof of concept chatbot named Game Expert that based on case in video games to solve the problems and then we use an online questionnaire which based on TAM and ISS model to make the use of the survey to verify whether to achieve improved results and enhance the use of willingness.
According to the results of the verification questionnaire, the development of this study does not only improve the overall user experience, but also effectively solve the problem of chatbot proposed in this study and enhance the user's willingness to use.

英文文獻:
Brown, F.A., Snavely, E.D., Miller, T.M., Wooters, C.C. and Culley, B.M. (2016) ‘Conversation User Interface’, .
David Berkowitz(2016)‘Multiple Metrics for Measuring Chatbots’
Allan Stormon(2016)’5 Chatbot Challenges and How to Overcome Them’
Anirudh Khanna1 , Bishwajeet Pandey1 , Kushagra Vashishta1 , Kartik Kalia1 , Bhale Pradeepkumar and Teerath Das (2015)‘A Study of Today’s A.I. through Chatbots and Rediscovery of Machine Intelligence’
Mittal, A., Agrawal, A., Chouksey, A., Shriwas, R. and Agrawal, S. (2016) ‘A comparative study of Chatbots and humans’, International Journal of Advanced Research in Computer and Communication Engineering, 5(3).
Salto Martínez Rodrigo, Jacques García Fausto Abraham (2012)’Development and Implementation of a Chat Bot in a Social Network’
Anirudh Khanna, Bishwajeet Pandey, Kushagra Vashishta, Kartik Kalia, Bhale ,Pradeepkumar and Teerath Das (2015)’A Study of Today’s A.I. through Chatbots and Rediscovery of Machine Intelligence,’
Luka Bradeško, Janez Starc, Dunja Mladenic, Michael Witbrock,(2016) ‘Curious Cat Conversational Crowd based and Context Aware Knowledge Acquisition Chat Bot’
Mariya Yao(2016)’When Bots Go Bad: Common UX Mistakes In Chatbot Design’
Emanuela Haller, Traian Rebedea Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest, Romania (2013)’Designing a Chat-bot that Simulates an Historical Figure’
Seth Earley (2015)’Cognitive Computing, Analytics, and Personalization’ IT Professional
Mochamad Vicky Ghani Aziz; Ary Setijadi Prihatmanto; Diotra Henriyan; Rifki Wijaya (2015)’Design and implementation of natural language processing with syntax and semantic analysis for extract traffic conditions from social media data Purchase or Sign In’ System Engineering and Technology (ICSET), 2015 5th IEEE International Conference on 10-11 Aug.
J. Octavio Gutierrez-Garcia; Emmanuel López-Neri (2015)Cognitive Computing: A Brief Survey and Open Research Challenges
Ruby Bhati (2016)’Open domain question answering system using cognitive computing’
Amit Sheth ; Pramod Anantharam ; Cory Henson,( 2016 )’Semantic, Cognitive, and Perceptual Computing: Paradigms That Shape Human Experience’ , Computer Volume: 49, Issue: 3
Emanuela Haller, Traian Rebedea (2013)’Designing a Chat-bot that Simulates an Historical Figure’, 2013 19th International Conference on Control Systems and Computer Science
Salto Martínez Rodrigo, Jacques García Fausto Abraham (2012)’Development and Implementation of a Chat Bot in a Social Network’, 2012 Ninth International Conference on Information Technology- New Generations
Tony Ahn , Seewon Ryu , Ingoo Han (2007)’The impact of Web quality and playfulness on user acceptance of online retailing’
Robert Rubinoff(2004 )‘How To Quantify The User Experience’
Kraft. C (2012)’User Experience Innovation: User Centered Design that Workd: Apress’
Rauschenberger,Schrepp,Cota,Olschner&Thomaschwesli(2014)’Applying the User Experience Questionnaire (UEQ) in different evaluation scenarios’

中文文獻:
徐慧雯(2016)‘聊天機器人使用意願影響因素之研究’
張偉男&劉挺 (2016) ‘深度 | 一篇文章看懂聊天机器人的历史、技术和研究 进展’,中国人工智能学会通讯 , 2016 年第 6 卷第 1 期.
蔡易達(2008)’寵物機器人之消費者科技接受度研究－以UgobePleo為例’
郭欣鑫(2008) ’智慧生活概念接受度之研究-以居家服務機器人為例’
陳建亮 黃昀莉(2011)’阻止購物網站顧客轉換行為之關鍵因素’
陳筠昀 沈文龍 吳邦昌(2012)’以資訊系統成功模型探討消費者對行動購物系統滿意度與購買意願之研究’
梁定澎(1997)’資訊系統導論’
林宗翰(2016)’成人教學輔助系統設計之研究-「學思達」概念之應用’
陳建浩(2013)’學習成效評估系統建置之研究’
許誌謙(2016)’響應式網頁設計元素對使用者經驗影響之研究’

網路文獻:
MARK(2016)’後App時代：為什麼Facebook、LINE、Slack都爭住開發Chatbot？對話式電子商務要來了！’
極客公園(2016)’Google Assistant 會是聊天機器人該有的樣子嗎？’
Jonathan Shriftman(2017)’2017年關於聊天機器人的四大預測’
Sergei Burkov(2016)’ 聊天機器人為什麼需要進行深度學習？’