企業在進行服務流程優化時，不同情境脈絡下待解決的核心問題不同，本研究聚焦在人工智慧與人協作的情境與價值，企業想要雇用人工智慧一起來完成什麼樣的任務(用途)?當特殊情境下的任務完成，價值便由服務提供者與消費者體驗共同創造。近年來人機協作應用案例越來越多，腦中所想像的化為各領域實際的應用。透過與人工智慧協作將人類從繁瑣的工作中解脫，並快速完成過去無法處理的智慧性工作，更能為人類賦能而不被制式化的工作所制約，以發揮更高價值。因此，人類事實上是與人工智慧的技術在進行協作共創，而並非被取代，如此顛覆性的創新有助於創建嶄新的服務體驗流程和價值網絡。
本研究目的主要是在探討企業在不同需求情境下，運用人工智慧進行分析並展開與人協作的情境。以某連鎖餐飲企業的三種不同情境脈絡下的人機協作過程來探索其應用，進一步探究人機協作的價值共創。為求實務與理論的相互驗證，本研究採取個案研究法，透過創新用途理論與服務主導邏輯的視角來探討人工智慧扮演行動者(Actor)的角色，透過知識能力運用與其它行動者共創價值，進而影響企業服務流程的轉變。
本研究獲致如下發現 : (一)需要以使用者的痛點與需求為核心，找到運用人工智慧輔助與人協作的方式，方能完成情境下的任務並從中與人共創價值。價值是在消費體驗與人機協作的使用下產生。(二)人工智慧處理重複性高且耗時的運算分析工作，並在協作過程中賦能予人類，將人從執行者轉為管理者，因此人類距離面臨被取代工作的威脅還有程度上的差距。(三)藉由研究發現，
深入探討創新用途理論與服務主導邏輯對於人工智慧協作在不同實務情境脈絡下的價值共創有顯著相關。

　This research focuses on the collaboration between Artificial Intelligence (AI) and human and the co-create value. What jobs do enterprise, customer and user want to hire Artificial Intelligence to accomplish together? Once the specific job is accomplished, the value is jointly created by producer and consumer. The main objective of this research is to explore how enterprises hire AI to collaborate with human under different cases. This research takes the case of a chain restaurant for study, which collaborates with Artificial Intelligence in three different scenarios, and further exploits value co-creation by Human-Robot Collaboration. For mutual verification of practice and theory, this research adopts a case study approach to explore the role of artificial intelligence as an actor through the perspective of Theory of Jobs to Be Done and Service-Dominant Logic(SDL).
　　Key findings of this research: (1) Focusing on consumers’ problems and needs, searching for the way human and artificial Intelligence can co-work to accomplish jobs hired and co-create value. (2) Artificial Intelligence handles highly repetitive and time-consuming calculation and analysis work, and empowers humans in the process of collaboration, transforming people from doers to managers. (3) The in-depth discussion of the theory of innovative uses and Service-Dominant Logic are significantly related to the value co-creation of artificial intelligence collaboration in different contexts.

壹、中文文獻
方世杰、李慶芳（2017）。價值共創策略思維的五步驟。價值共創學術研究社群(VCC)。取自http://teamwork0035.blogspot.com/2017/05/blog-post_31.html。
方世杰（2016）。打造共創平台 : 互動的氛圍。價值共創學術研究社群(VCC)。
取自https://teamwork0035.blogspot.com/2016/04/?view=classic。
尹寶才、王文通、王立春（2015）。深度學習研究综述。北京工業大學學報，1，48-59。
李力、林懿倫、曹東璞、鄭南寧、王飛跃（2017）。平行學習—機器學習的一個新型理論框架。自動化學報，1，1-8。
李開復、王詠剛（2017）。人工智慧來了。台北市：天下文化。
郭良文、林素甘（2001）。質化與量化研究方法之比較分析。資訊傳播與圖書館學，7，4。
郭麗麗、丁世飛 （2015）。深度學習研究進展。計算機科學，5，28-33.
陳偉華（2015）。連鎖餐飲業經營的六大致勝關鍵。管理知識中心。取自https://mymkc.com/article/content/22152
黃筱雯（2019）。應用數位科技智慧，驅動未來人才培訓新模式。產業人才發展資訊網。取自https://www.italent.org.tw/ePaperD/35/ePaper20190600030。
馮芷艷、郭迅華、曾大軍、陳煜波、陳國青（2013）。大數據背景下商務管理研究若干前沿课题 ①。管理科學學報，16(1)。
蔡鳳凰（2019）。AIoT智慧健康在慢性疾病的應用發展。經濟前瞻，182， 116-120。
蕭佑和（2018）。完整解析AI人工智慧：3大浪潮＋3大技術＋3大應用。Meet數位時代。取自https://reurl.cc/Na3DNn。
蕭瑞麟（2007）。不用數字的研究: 鍛鍊深度思考力的質性研究。台北市：台灣培生教育。
 
貳、英文文獻
Booms, B., & and Bitner, M. (1981). MarketingStrategies andOrganizationStructuresforServiceFirms.
Brynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review.
Chen, Y., Argentinis, J. E., & Weber, G. (2016). IBM Watson: how cognitive computing can be applied to big data challenges in life sciences research. Clinical therapeutics, 38(4), 688-701.
Christensen, C. M., Hall, T., Dillon, K., & Duncan, D. S. (2016). Know your customers’ jobs to be done. Harvard Business Review, 94(9), 54-62.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
Dirican, C. (2015). The impacts of robotics, artificial intelligence on business and economics. Procedia-Social andBehavioral Sciences, 195, 564-573.
Fyrberg, A., & Jüriado, R. (2009). What about interaction? Networks and brands as integrators within service-dominant logic. Journal of Service Management, 20(4), 420-432.
Gartner (2019, September 12). Top Trends on the Gartner Hype Cycle for Artificial Intelligence. Retrieved November 9, 2019, from https://www.gartner.com/smarterwithgartner/top-trends-on-the-gartner-hype-cycle-for-artificial-intelligence-2019/
Ghosh, R., Jain, J., & Dekhil, M. E. (2017). Acquiring customer insight in a retail environment. In: Google Patents.
Goi, C. L. (2009). A review of marketing mix: 4Ps or more? International journal of marketing studies, 1(1), 2.
Grönroos, C., & Voima, P. (2013). Critical service logic: making sense of value creation and co-creation. Journal of the Academy of marketing Science, 41(2), 133-150.
Haenlein, M., & Kaplan, A. J. C. M. R. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. 61(4), 5-14.
Kaplan, J. (2015). Humans need not apply: A guide to wealth and work in the age of artificial intelligence: Yale University Press.
Li, R., & Li, H. (2018). Have housing prices gone with the smelly wind? Big data analysis on landfill in Hong Kong. Sustainability, 10(2), 341.
Mills, P. K., & Morris, J. (1986). Clients as “partial” employees of service organizations: Role development in client participation. Academy of management review, 11(4), 726-735.
Minsky, M. L. J. A. m. (1982). Why people think computers can't. AI magazine, 3(4), 3-3.
Nilsson, N. J. (2014). Principles of artificial intelligence: Morgan Kaufmann.
Normann, R., & Ramirez, R. (1993). From value chain to value constellation: Designing interactive strategy. Harvard Business Review, 71(4), 65-77.
O'Leary, D. E. (2013). Artificial intelligence and big data. IEEE Intelligent Systems, 28(2), 96-99.
Pannu, A. (2015). Artificial intelligence and its application in different areas. Artificial Intelligence, 4(10), 79-84.
Prahalad, C. K., & Ramaswamy, V. (2004). Co-creation experiences: The next practice in value creation. Journal of interactive marketing, 18(3), 5-14.
Price, R., & Wrigley, C. (2016). Design and a deep customer insight approach to innovation. Journal of International Consumer Marketing, 28(2), 92-105.
Ramirez, R., & Normann, R. (1998). Designing interactive strategy: From value chain to value constellation: J. Wiley.
Reichman, O. J., Jones, M. B., & Schildhauer, M. P. (2011). Challenges and opportunities of open data in ecology. Science, 331(6018), 703-705.
Saarijärvi, H., Kannan, P., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European business review, 25(1), 6-19.
Simon, H. A. (1977). Thinking by computers. In Models of Discovery (pp. 268-285): Springer.
Vargo, S. L., & Akaka, M. A. (2009). Service-dominant logic as a foundation for service science: clarifications. Service Science, 1(1), 32-41.
Vargo, S. L., & Akaka, M. A. (2012). Value cocreation and service systems (re) formation: A service ecosystems view. Service Science, 4(3), 207-217.
Vargo, S. L., & Lusch, R. (2008). Service-dominant logic: continuing the evolution. Journal of the Academy of marketing Science, 36(1), 1-10.
Vargo, S. L., & Lusch, R. F. (2004). The four service marketing myths: remnants of a goods-based, manufacturing model. Journal of service research, 6(4), 324-335.
Xu, Z., Liu, Y., Mei, L., Hu, C., & Chen, L. (2015). Semantic based representing and organizing surveillance big data using video structural description technology. Journal of Systems and Software, 102, 217-225.