研究生: |
郭宇程 Yu-Cheng Kuo |
---|---|
論文名稱: |
聊天機器人是否能夠取代客服人員: 以國內某電信業者客服系統為例 Can customer service center been replace by chatbots : A case of a domestic telecommunication company |
指導教授: |
葉穎蓉
Ying-Jung Yeh |
口試委員: |
房美玉
mfang@cc.ncu.edu.tw 陳春希 cvchen@mgt.ncu.edu.tw |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 管理學院MBA School of Management International (MBA) |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 33 |
中文關鍵詞: | 聊天機器人 、客服系統 、自動化服務 、客服人員 |
外文關鍵詞: | Automatic service |
相關次數: | 點閱:205 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
中文摘要
近年來人工智能與大數據技術迅速發展,許多自動化的技術也逐漸在第三級產業(服務業)種興盛起來,聊天機器人正是其中應用最為廣泛的技術之一。本研究的目的在於探討聊天機器人在服務業中的發展是否有可能造成客服人員被其取代的現象,本研究使用個案分析方法,針對國內某個已在客服系統內建置聊天機器人的電信公司進行專家訪談。研究結果發現,以目前的科技,聊天機器人尚無法完全取代客服人員,目前的聊天機器人在客服系統內所能處理的的問題仍限於高重複性與較為單純的問題,而對於使用聊天機器人有疑慮或困難者,抑或是複雜而少見的問題則依然需要客服人員親自處理,而對於客戶的情緒管理以及客服人員所展現出的同理心及對話互動中的溫度,也成為客服人員難以被取代的原因。結合當前的科技、業界情況來看,聊天機器人與客服人員的關係,最好的情況是互補互助,而非取代與淘汰。
ABSTRACT
The technology like AI and big data have been developed rapidly in past few years , many of them are already been tested in field , for example , chatbots are used in service industry , the purpose of this study is to find out is it possible that chatbots will replace customer service center in near future . This research has done a case analysis against a domestic telecommunication company which had already used chatbot as a choice of customer service for users . The result tells that chatbots are not likely to replace current customer service center in near future , current chatbots can only deal with simple and duplicate questions , for those who are not familiar with new technology or users with complex and rarely happen problems , still need customer service crew to process . Main reasons that customer service crew can’t be replace by chatbots is the emotions management skill against customers , also the empathy from the crew when interact with users . From the perspective of this research , the best way is to use customer service crew and chatbots simultaneously .
參考文獻
1. 中華民國經濟部統計處網站(https://dmz26.moea.gov.tw/GMWeb/common/CommonQuery.aspx)
2. A. H. Qureshi, Y. Nakamura, Y. Yoshikawa and H. Ishiguro, (2016) Robot gains social intelligence through multimodal deep reinforcement learning, Humanoid Robots (Humanoids) 2016 IEEE-RAS 16th International Conference on, pp. 745-751.
3. Buttle, Francis (1996), SERVQUAL: Review, Critique, Research Agenda, European Journal of Marketing, 30 (1), 8-32.
4. Dale, R., (2016). The return of the chatbots. Published online by Cambridge University Press.
5. Fernández-Sabiote, E., & Román, S. (2015). The multichannel customer’s service experience: building satisfaction and trust. Service Business.
6. Frey, C. B. & Osborne, M. A. (2013).The Future of Employment:How Susceptible Are Jobs to Computerisation? Technological Forecasting and Social Change
7. Fernández-Sabiote, E., & Román, S. (2015). The multichannel customer's service experience: Building satisfaction and trust. Service Business.
8. Hildebrand C, Bergner A (2019) AI-driven sales automation: using chatbots to boost sales. NIM Mark Intell Rev 11:36–41.
9. Kotler, P. (1997). Marketing Management: Analysis, Planning, Implementation, and Control. 9th Edition, Prentice Hall, Upper Saddle River.
10. Payne, A. (1993). The Essence of Services Marketing
11. Pine, J. & Gilmore, J. (1999). The Experience Economy pp. 41-65
12. Tussyadiah, I., & Park, S. (2018). Consumer evaluation of hotel service robots. In B. Stangl & J. Pesonen (Eds.), Information and communication technologies in tourism 2018 pp. 308–320