本研究是找出Ikari咖啡外部顧客及內部顧客的共同服務設計關鍵需求後，導入環境氛圍中的環境光與音樂關鍵需求並結合顧客七大表情辨識研究。環境光顏色從冷到暖的9種顏色變化及4種不同曲風的音樂，探討客人表情的變化，目的是提升客人愉悅的表情，天天都是美好的一天。
研究設計1首先探討外部顧客對服務設計的關鍵需求，採面對面的訪談，共訪談55位顧客，其中加盟店27位，直營店28位。訪談內容先調查顧客基本資料，涵蓋消費頻率、行業別、年齡、性別及婚姻；詢問來店消費的誘因，接著分別以人際互動設計、空間設計、作業流程設計及心中期待理想咖啡店的設計四項主軸進行訪談，最後將55位顧客的訪談內容彙整，採分類及歸納之方法，找出外部顧客關鍵需求。
研究設計2接著探討內部顧客對服務設計的關鍵需求，是以第一線主管、值班夥伴及小組長為研究對象，合計70位。採腦力激盪法、KJ法，運用特性要因圖、心智圖討論並歸納出內部顧客對服務設計的關鍵需求6大構面，分別為職能發展設計、環境設計、作業流程設計、工作設計、品牌行銷設計及跨部門合作設計，每構面找出前5項最需改善的服務設計，合計30項並擬訂行動計畫。
研究設計3則以研究設計1外部顧客服務設計關鍵需求及研究設計2內部顧客服務設計關鍵需求的環境氛圍關鍵需求環境光及音樂來進行實驗，欲經由環境光顏色與音樂的變化偵測表情，進而辨識與分析顧客的情緒。實驗前測，架構表情狀態轉換圖（Expressions State Transition Diagram）、選取Philip hue API智慧情境光及音樂、做人臉檢測和主動形狀模型（Active Shape Models ,ASM）特徵點提取；正式實驗將全套餐飲服務改為簡單的下午茶模式、將音樂選擇由原來的爵士樂、輕音樂，再增加古典樂及流行樂，分為對照組與實驗組進行3組實驗。對照組的情境為日光燈，無音樂；實驗組的三個情境分別為智慧情境光，播放音樂及智慧情境光中播放音樂執行表情辨識。受測者面對面坐著自訂主題聊天或閒聊，攝影機擺設在桌上裝飾的花盆中擷取畫面傳送至電腦，使用Ada-boost偵測人臉分類，再用ASM擷取五官特徵點，之後計算五官紋理與特徵點的移動，計算完成後使用類神經網絡(Artificial Neural Network, ANN) 進行表情分類進而產生辨識結果，並將結果傳送至資料庫儲存，智慧情境光連至資料庫並抓取當中的表情資料，在依原本分類好的七種表情相對應的顏色捕捉，然後每秒進行一次面部表情辨識，將辨識到的表情資料每30秒統計一次，取出現次數最多的表情，並將統計的結果傳送到資料庫，從Server端取最新一筆資料，作為智慧情境光顏色變化與音樂風格切換的依據。
受測者進行表情辨識的實測合計1,008次，受到外在環境因素的影響情況下，成功辨識次數為783次，女性342次、男性441次，表情成功辨識率為77.7%。得出的七種表情成功辨識率佔比分別悲傷的表情（sad）2.5％、恐懼的表情（fearful）6.0％、厭惡的表情（disgusted）16.1％、憤怒的表情（angry）4.2％、驚訝的表情（surprised）19.7％、平靜的表情（neutral）11.1％、愉悅的表情（joyful）18.2％，七大表情分類佔總次數％由高至低排序驚訝的、愉悅的、厭惡的、平靜的、恐懼的、憤怒的、悲傷的。
一、愉悅的表情分析（一）實驗組次數佔比愉悅的表情增加4.8％。（二）1.智慧情境光中，女性佔女性比愉悅的表情由23.8％提升至31.25％；2.播放音樂中，男性與女性合計佔比愉悅的表情由11.3％提升為19.3％，女性佔女性比愉悅的表情由13.8％提升至23.3％，女性佔總數比愉悅的表情由6.5％提升至10.4％，男性佔男性比愉悅的表情由9.1％提升為16.0％，男性佔總數比愉悅的表情由4.8％提升為8.9％；3.智慧情境光播放音樂中，女性佔女性比愉悅的表情由1.3％大幅提升至36％，女性佔總數比愉悅的表情由0.6％提升為9.6％，男性與女性合計佔比愉悅的表情由18.9％提升為29.2％。（三）在t檢定（n<30）的「愉悅的表情」具顯著性（p<0.05）。
二、正向情緒分析（一）實驗組與對照組合計佔比正向表情平靜的及愉悅的表情佔比皆有增加，達到100％，符合我們實驗的目的之一。（二）在接受智慧情境光的刺激後「女性的負向表情顯著下降」（p<0.05）。（三）在音樂的刺激下，受試者的「正向表情呈現顯著性」p<0.05）。（四）在智慧情境光播放音樂的情境下，受試者的「正向表情呈現顯著性」（p<0.05）。
三、表情辨識百分比分析愉悅表情佔比增減，驗證假設18項是否成立，其中成立11項，佔61％，7項不成立佔39％。
後續嘗試運用工作坊的設計及咖啡店現場進行企業應用實驗，全方位表情變化能突破不僅是臉部表情偵測其情緒，也能將其心理感受到的納入，最終的目的是創造一個快樂的咖啡店。

This study is to find out the Critical Needs of the common service design of Ikari coffee external customers and internal customers, and combine the seven major expression recognition researches of customers with ambient light and music. With the ambient light color changing from cold to warm in 9 colors and 4 different styles of music, we explore the changes in the expressions of the guests. The purpose is to enhance the joyful expressions of the guests; every day is a wonderful day.
Research design 1: First we explored the critical demands of external customers for service design. We investigated customers’ basic data, including purchasing frequency, occupation, age, sex, and marital status before interviewing 55 customers face to face, 27 of whom came from franchise stores and 28 of whom came from regular chain stores. We roughly inquired why they came to our stores and then interviewed them according to 4 domains: interpersonal interaction design, space design, operating procedure design and ideal-café design. After collecting the data of the interviews, we concluded the critical demands of external customers by categorizing and inductive method.
Research design 2: Then, we explored the critical demands of internal customers for service design. The design is based on the 70 subjects consisting of the frontline supervisors, coworkers on duty and team leaders. We adopted brainstorming, KJ conception and cause and effect diagram, mind-mapping to conclude 6 facets of critical demands for service design from interior customers. The six facets are career development design, environmental design, operating procedure design, working design, brand-marketing design and trans-department cooperation design. Top 5 service designs requiring improvement most in every facet are found. Thus, the detailed items are amounted to 30 and we draft an operation scheme.
Research design 3 is to perform the experiment by combing external customers and interior customers’ mutual critical demands and lights as well as music. We detect expressions through ambient light colors and musical changes and further recognize and analyze customers’ emotions. We build the ESTD（Expressions State Transition Diagram）and choose Philip hue API smart ambient light and music, using Ada- Boost detects the face and ASM（Active Shape Models） to capture the features of the facial features, then calculates the movement of the facial features and feature points. After the calculation is completed, the ANN (Artificial Neural Network) is used to classify the expressions to generate the identification results, the environment of the control group is with fluorescent light but without music and that of the experiment group is with the smart ambient light, with music and the smart ambient light with music.
The test performed a total of 1,008 actual expressions. Under the influence of external environmental factors, the number of successful identifications was 783, 342 females and 441 males. The successful recognition rate was 77.7%.
(一) In the joyful expression analysis of the expression recognition,1.The number of times of showing joyful in experimental groups increased by 4.8%. 2. (1) In the atmosphere of smart-ambient light analysis, the joyful expressions of females increased from 23.8% to 31.25%. (2) In the atmosphere of music, the proportion of females to all females increased from 13.8% to 23.3%. The proportion of males to all males increased from 9.1% to 16.0 %. (3) In the smart-ambient light vibe, however, when playing music, the proportion of joyful expression of females to all females largely increased from 1.3% to 36%. The ratio of females to total increased from 0.6% to 9.6%. 3. The positive expression "joyful” at t test (n < 30) was significant (p < 0.05).
(二) Positive expression analysis, 1. The experimental group and the control combination accounted for an increase in the positive expression and the expression of the joyful expression, reaching 100% with the purpose of our experiment. 2. After receiving the stimulation of “ambient light", "the negative expression of women's negative expression decreased significantly" (p < 0.05). 3. Under the stimulation of "music", the subject's "positive expression is significant" (p < 0.05). 4. In "music and ambient light", the "positive expression is significant" (p < 0.05).
(三) Percentage analysis of facial expressions analysis of joyful expression, verifying that 18 items are assumed to be established, of which 11 items are established, accounting for 61%, and 7 items are not established, accounting for 39%.
The design of workshops and the application of enterprises for the experiment in coffee shops are consequent attempts. All-dimensional expression change recognition can not only detect the people’s emotions but include their feeling inside as a breakthrough. The ultimate goal is to create a happy coffee shop.
Keywords: service design, key requirements, ambient light, expression recognition.

誌謝 0
摘要 i
ABSTRACT iii
目次 v
表次 vii
圖次 ix
第壹章 緒論 1
第一節 研究背景與動機 2
第二節 研究目的與問題 4
第貳章 文獻探討 6
第一節 服務設計研究相關文獻 6
第二節 表情辨識研究相關文獻 11
第參章 研究設計 22
第一節 研究流程 23
第二節 研究設計 24
第肆章 研究結果 44
第一節 研究結果1-探討外部顧客對服務設計的關鍵需求 44
第二節 研究結果2-探討內部顧客對服務設計的關鍵需求 52
第三節 研究結果3-環境光與音樂的變化辨識表情 58
第伍章 結論與建議 116
第一節 結論 116
第二節 後續研究建議 118
參考文獻 122
中文部份 122
英文部份 125
附錄一 研究設計1問卷A 129
附錄二 研究設計1問卷B 130
附錄三 研究設計3 前測問卷 132
附錄四 研究設計3 正式問卷 140
附錄五 研究設計1 顧客資料分析表 146
附錄六 半結構式問卷實地訪查表 147
附錄七 研究設計3前測流程作業表 148
附錄八 We need YOU for a Coffee Shop Experiment ! 149
附錄九 研究設計3流程作業表 150
附錄十 肖像權使用同意書 151

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55.Music retrieved from https://youtu.be (https://youtu.be/UEOiPGm4Z1E) (https://youtu.be/NUl41QeUJTg)(https://youtu.be/TgrT8aSL12U)(https://youtu.be/ahSmNv0P7lA)(https://youtu.be/7y5DS2NHWEE)(https://youtu.be/0PfQ_Ux970k)(https://youtu.be/PXMVkQ70I88)(https://youtu.be/MHgBObK9acY)(https://youtu.be/LEGp4nrUIs4)(https://youtu.be/f8GQpZLAxX)(https://youtu.be/1exF8HB6dXs) (https://youtu.be/z0aCVCLdd1s)(https://youtu.be/lyo9Zo2Ux2U)(https://youtu.be/rNsgHMklBW0)(https://youtu.be/1exF8HB6dXs)(https://youtu.be/_DRNgL76OLc)(https://youtu.be/ggPooXtzUD0)(https://youtu.be/imYJpr09IgQ)(https://youtu.be/0sce10t4r24)(https://youtu.be/LhGwYpm2_tk).