Title

產品設計情感向度的傳達與決策分析模式

Translated Titles

Exploring the Emotional Dimensions on Product Design with a Decision Analysis Model

Authors

朱柏穎

Key Words

決策分析模式 ; 斐思指標 ; 情感向度 ; 產品開發 ; FASE index ; emotional dimensions ; product development ; decision analysis model

PublicationName

大同大學設計科學研究所學位論文

Volume or Term/Year and Month of Publication

2011年

Academic Degree Category

博士

Advisor

陳立杰

Content Language

繁體中文

Chinese Abstract

企業在產品設計與開發的過程中,要如何於決策時刻透過有效的程序與方法,選出適應市場需要的產品,是協助企業確保經營與成長的關鍵。雖然消費者會根據產品的效益,以價格和功能的評比等理性的訴求作為決策的參考,但消費行為卻往往超越理性,而以消費者主觀衡量得失之後的認知價值作為真正的決策核心。因此,為讓企業在面對今日漸趨複雜的產品設計開發環境中,能掌握住與消費市場溝通的脈動,本論文進行提昇產品認知價值的情感向度指標萃取、傳達方法與決策分析模式之研究,作為改進產品開發與決策品質的重要依據。 研究共分為三個階段:第一階段先透過文獻研究及訪談設計師與使用者的方式,找出建立情感向度的元素因子,隨後透過大規模的問卷調查,並進行因素分析。最後萃取出情感向度的四個構面,即非凡特質(F)、感性聯想(A)、社交尊嚴(S)與攝眾交心(E)這四個主要構面,本論文將之命名為斐思指標(FASE Index)。 第二階段則進行三個實驗,以驗證斐思指標的區辨能力。實驗一以三款經典設計商品,對決策性格不同的受測者進行實驗,並結合模糊理論與成對比較矩陣,對受測者斐思指標的權值進行評價。再藉由卡方分析、G2統計與四次的二因子變異數分析,檢定斐思指標的區別能力與實用性。統計分析結果顯示,受測者面對不同設計款式的產品,在斐思指標上具有顯著的感受差異。實驗二則以四款USB隨身碟為例,以背景相近的受測者進行實驗,藉由ANOVA的分析結果顯示出斐思指標對相同定位的產品也具有鑑別能力。實驗三則延續實驗二,以其中一款得到國際設計獎項的暢銷USB隨身碟並在設計師願意受訪的情況下,針對該作品的原創設計師以及實驗二的受測者進行實驗比對,以探討設計師概念模型及使用者心智模型之異同。實驗結果顯示,斐思指標可有效定義產品認知價值之情感向度,且設計師與使用者在斐思指標上也可呈現出相同的趨勢。 最後一個階段為斐思指標決策分析模式的驗證,藉由斐思指標發展出以群體決策為基礎的協同過濾推薦的權值聚合演算與決策分析模式,以作為改進產品開發與決策品質的重要依據。本階段並以某文創公司將要推出的新產品為例,由公司核心成員組成之決策小組進行評選,並以協同過濾推薦技術來衡量新產品與競爭產品在斐思指標的評價空間上的差異,作為新產品開發的決策參考。實驗結果也顯示結合斐思指標與協同過濾推薦技術的決策模式,可以避免傳統決策模式的盲點,提供較客觀的決策建議。 本研究預期斐思指標將可有效作為產品設計情感設計傳達的工具,同時產業將可藉由斐思指標的評量作為規劃產品開發策略之決策依據,除可提昇產品開發與決策品質,強化企業競爭優勢之外,本研究所提出的研究架構、論點與方法並可擴展成為生活、商業和公共政策等諸多領域的決策參考。

English Abstract

At the stage of product design and development, an effective method for selecting product concepts that fulfill market needs is the key to ensure the growth of a company. Although some consumers make their purchase decisions based on quality, functionality, usability, and cost performance index, many consumers consider the perceive values, such as the look-and-feel or the subjective understanding about the product, as the major factors of purchasing. However, in the literature, there is a lack of systematic methods to deal with communication and decision making for product concept selection based on perceived values. To address this issue, the objective of this research is to identify emotional factors that affect the perceived value of products and develop a quantitative method for decision making. This research included three stages. In the first stage, literature review and a large scale survey on the experiences of designers and customers were conducted to collect the factors that influenced the perceived values from emotional perspectives. Furthermore, using factor analysis, four emotional dimensions, i.e., Features (F), Association (A), Social-esteem (S), and Engagement (E), were identified and named as the FASE Index. To validate the applicability of the index, three experiments were carried out at the second stage. In the first experiment, the analysis of perception difference for three classic and heterogeneous products, which were considered as good designs in many textbooks, was conducted to verify the validity of the index. Participants with different decision styles were invited to evaluate these products. The results showed that FASE index was able to distinguish among products with different functions. In the second experiment, four homogeneous products with the same function served as the experimental samples. Similarly, this index could be used to discriminate these products successfully. In the third experiment, a comparative study examined whether or not designers and consumers exhibited any differences in judging two award winning products. The results indicated that their judgments shared the same trend in the emotional dimensions. The findings of these experiments had demonstrated that FASE index could be used as a structure for design communication from emotional perspectives. At the third stage, a quantitative method for group decision making was developed based on the index. Not only the uniqueness of product concepts but also the similarity among concepts and benchmark products were considered in the decision model. A case study was then used to illustrate the effectiveness of the method. Application of the FASE Index and the quantitative method could allow designers to create their products based on the characteristics expected by potential clients and to avoid situations in which designers and clients fail to communicate properly. In addition, companies could categorize their products according to the Index to ensure the uniqueness of a product. With the help of these approaches, the quality of product development decisions could be improved.

Topic Category 人文學 > 藝術
設計學院 > 設計科學研究所
Reference
  1. 1. Adomavicius, G., & Tuzhilin, A. (2005). Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734-749.
    連結:
  2. 3. Ariely, D. (2008). Predictably irrational: The hidden forces that shape our decisions. New York: HarperCollins.
    連結:
  3. 4. Bahn, S., Lee, C., Nam, C. S., & Yun, M. H. (2009). Incorporating affective customer needs for luxuriousness into product design attributes. Human Factors and Ergonomics in Manufacturing, 19(2), 105-127.
    連結:
  4. 5. Barrena, R. & Sanchez, M. (2009). Using emotional benefits as a differentiation strategy in saturated markets. Psychology and Marketing, 26(11), 1002-1030.
    連結:
  5. 6. Baxter, M. (1995). Product design: A practical guide to systematic methods of new product development. London: CRC Press.
    連結:
  6. 7. Bloch, P. H. (1995). Seeking the Ideal Form : Product Design and Consumer Response. Journal of Marketing, 59, 16-29.
    連結:
  7. 8. Brodsky, N. Burlingham, B. (2009) 。師父:那些我在課堂外學會的本事(The Knack: How Street-smart Entrepreneurs Learn to Handle Whatever Comes Up)(林茂昌譯)。台北市 : 早安財經。(原作2008年出版)
    連結:
  8. 10. Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 14.
    連結:
  9. 12. Chang, W. C., & Hsu, Y. (2005). Electric knowledge management in design consultancies. Design Management Review. 16(2), 49-54.
    連結:
  10. 13. Chen, M. F., Tzeng, G. H., & Ding, C. G. (2008). Combining fuzzy AHP with MDS in identifying the preference similarity of alternatives. Applied Soft Computing, 8(1), 110-117.
    連結:
  11. 14. Cooper, R.G. (1983). A Process Model for Industrial New Product Development. IEEE Transactions, EM-30(1), pp.2-11.
    連結:
  12. 15. Cooper, R.G. (1993). Winning at New Products. Boston : Addison Wesley.
    連結:
  13. 16. Dell'Era, C., & Verganti, R. (2007). Strategies of Innovation and Imitation of Product Languages. Journal of Product Innovation Management, 24(6), 580-599.
    連結:
  14. 19. Desmet, P.M.A. (2003). Measuring emotion; development and application of an instrument to measure emotional responses to products. In: Blythe M.A., Monk A.F., Overbeeke K., & Wright P.C. (Eds.), Funology: from usability to enjoyment (pp. 111-123). Dordrecht: Kluwer Academic.
    連結:
  15. 23. Ertugrul, I., & Karakasoglu, N. (2009). Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Systems with Applications, 36(1), 702-715.
    連結:
  16. 26. Güngör, Z., Serhadlıoğlu, G., & Kesen, S. E. (2008). A fuzzy AHP approach to personnel selection problem. Applied Soft Computing, 9(2), 641-646.
    連結:
  17. 28. Hassenzahl, M. (2004). The thing and I: Understanding the relationship between user and product. In M. A. Blythe, K. Overbeeke, A. F. Monk & P. C. Wright (Eds.), Funology: From Usability to Enjoyment (pp. 31-42). Dordrecht: Kluwer Academic.
    連結:
  18. 29. Hsiao, S.W., & Chou, J.R. (2004). A creativity-based design process for innovative product design. International Journal of Industrial Ergonomics, 34, 421-443.
    連結:
  19. 30. Hsu, S. H., Chuang, M.C., & Chang, C. C. (2000). A semantic differential study of designers & users product form perception. International Journal of Industrial Ergonomics, 25(4), 375-391.
    連結:
  20. 31. Huang, M. H. (2001). The Theory of Emotions in Marketing, Journal of Business and Psychology, 16(2), 239-247.
    連結:
  21. 32. Izard, C. E. (1977). Human Emotions. New York: Plenum Press.
    連結:
  22. 36. Khalid, H. M., & Helander, M. G. (2004). A framework for affective customer needs in product design. Theoretical Issues in Ergonomics Science, 5, 27-42.
    連結:
  23. 38. Kohrs, A., & Merialdo, B. (2001). Creating user-adapted Websites by the use of collaborative filtering, Interacting with Computers, 13(6), 695-716.
    連結:
  24. 40. Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty's priority theory. Fuzzy Sets and Systems, 11(1-3), 199-227.
    連結:
  25. 41. Lang, P., & Bradley, M. (1994). Measuring emotion: The self-assesment manikin and the semantic differential. Journal of Behavior Therepy & Experimental Psychiatry, 25(1), 49-59.
    連結:
  26. 42. Lang, P. J. (1985). The Cognitive Psychophysiology of Emotion: Anxiety and the Anxiety Disorders. Hillsdale: Lawrence Erlbaum.
    連結:
  27. 43. Laros, F. J. M., Steenkamp, J. B. E. M. (2005). Emotions in consumer behavior: A hierarchical approach. Journal of Business Research, 58(10), 1437-1445.
    連結:
  28. 44. Leong, B. D., & Clark, H. (2003). Culture-Based Knowledge Towards New Design Thinking and Practice - A dialogue. Design Issues, 19(3), 48-58.
    連結:
  29. 45. Lin, R. T. (2007). Transforming Taiwan aboriginal cultural features into modern product design: A case study of a cross-cultural product design model. International Journal of Design, 1(2), 45-33.
    連結:
  30. 46. Linden, G., Smith, B., & York, J. (2007). Amazon.com Recommendations: Item-to-Item Collaborative Filtering. IEEE Internet Computing, 7(1), 76-80.
    連結:
  31. 47. Ma, M.Y., Chen, C.Y., & Wu, F.G. (2007). A design decision-making support model for customized product color combination. Computers in Industry, 58(6), 504-518.
    連結:
  32. 48. Machleit K.A., & Eroglu S.A. (2000). Describing and Measuring Emotional Response to Shopping Experience. Journal of Business Research, 49, 101-111.
    連結:
  33. 50. Miller, G. (1956). The magical number seven plus or minus two: Some limits on our capacity for processing information. The Psychological Review, 63(2), 81-97.
    連結:
  34. 53. Mugge, R., Schoormans, J. P. L., & Schifferstein, H. N. J. (2009). Emotional bonding with personalised products. Journal of Engineering Design, 20(5), 467-476.
    連結:
  35. 54. Myers, I. B., & McCaulley, M. H. (1998). MBTI Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator (3rd ed.). Palo Alto: Consulting Psychologists Press.
    連結:
  36. 55. Nagamachi M. (1995). Kansei Engineering: A new ergonomic consumer-oriented technology for product development. International Journal of Industrial Ergonomics, 15, 3-11.
    連結:
  37. 56. Nagamachi M. (2002). Kansei engineering as a powerful consumer-oriented technology for product development. Applied Ergonomics, 33(3), 289-294.
    連結:
  38. 58. Norman, D. A. (2004). Emotional design: Why we love (or hate) everyday things. New York: Basic Books.
    連結:
  39. 59. Nurkka, P., Kujala, S., & Kemppainen, K. (2009). Capturing users' perceptions of valuable experience and meaning. Journal of Engineering Design, 20(5), 449-465.
    連結:
  40. 60. Önüt, S., Kara, S. S., & Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2, Part 2), 3887-3895.
    連結:
  41. 61. Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
    連結:
  42. 62. Ortony, A., & Turner, T. J. (1990). What's basic about basic emotions? Psychological Review, 97, 315-331.
    連結:
  43. 64. Plutchik, R. (1980). A general psychoevolutionary theory of emotion. In R. Plutchik & H. Kellerman (Eds.), Emotion: Theory, research, and experience: Vol. 1. Theories of emotion (pp. 3-33). New York: Academic.
    連結:
  44. 65. Plutchik, R. (2001). The Nature of Emotions. American Scientist, 89(4), 344-350.
    連結:
  45. 66. Preece, J., Rogers, Y., & Sharp, H. (2006)。互動設計(Interaction design: beyond human-computer interaction)(陳建雄譯)。台北市:全華科技。(原作2003年出版)
    連結:
  46. 68. Richins, M. L. (1997). Measuring emotions in the consumption experience. Journal of Consumer Research, 24, 127–146.
    連結:
  47. 69. Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
    連結:
  48. 70. Saaty, T. L., & Takizawa, M. (1986). Dependence and independence: From linear hierarchies to nonlinear networks. European Journal of Operational Research, 26(2), 229-237.
    連結:
  49. 73. Seva, R. R., Duh, H. B. L. & Helander, M. G. (2007). The marketing implications of affective product design. Applied Ergonomics, 38(6), 723-731.
    連結:
  50. 74. Shaver, P. R., Schwartz, J., Kirson, D., & O’Connor, C. (1987). Emotion knowledge: Further exploration of a prototype approach. Journal of Personality and Social Psychology, 52, 1061-1086.
    連結:
  51. 75. Smith, A. S. G., & Blandford, A. (2003). MLTutor: An Application of Machine LearningAlgorithms for an Adaptive Web-based Information System. International Journal of Artificial Intelligence in Education, 13(2-4), 233-260.
    連結:
  52. 79. Teng, J. Y., & Tzeng, G. H. (1996). Fuzzy multicriteria ranking of urban transportation investment alternatives. Transportation Planning and Technology, 20(1), 15-31.
    連結:
  53. 80. Tiger, L. (1992). The Pursuit of Pleasure. London: Little Brown & Co.
    連結:
  54. 82. Verganti, R. (2008). Design, Meanings, and Radical Innovation: A Metamodel and a Research Agenda. Journal of Product Innovation Management, 25(5),436-456.
    連結:
  55. 83. Westbrook, R. A., & Oliver, R. L. (1991). The dimensionality of consumption emotion patterns and consumer satisfaction. Journal of Consumer Research, 18, 84–91.
    連結:
  56. 86. Wu, F. G., Lee, Y. J., & Lin, M. C. (2004). Using the fuzzy analytic hierarchy process on optimum spatial allocation. International Journal of Industrial Ergonomics, 33(6), 553-569.
    連結:
  57. 88. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353.
    連結:
  58. 89. Zadeh, L. A. (1999). Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 100(Supplement 1), 9-34.
    連結:
  59. 90. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.
    連結:
  60. 91. Zeleny, M. (1982). Multiple Criteria Decision Making. New York : McGraw-Hill.
    連結:
  61. 92. Zhang, G. W., Li, D. Y., Li, P., Kang, J. C., & Chen G. S. (2007). A collaborative filtering recommendation algorithm based on cloud model. Journal of Software, 18(10), 2403−2411.
    連結:
  62. 94. 王小璘、劉若瑜(2001)。由景觀生態學觀點探討都市基質環境之永續利用-以台中市東區及南屯區為例。設計學報,6(2),1-21。
    連結:
  63. 99. 何秋慧 (2006) 。電腦介面角色與使用者互動之情緒感染與性別差異。國立清華大學資訊系統與應用研究所碩士論文,未出版,台灣新竹。
    連結:
  64. 101. 李玉琇 (2000) 。工作記憶的限制在人因心理學中的意涵。應用心理研究,5, 55-67。
    連結:
  65. 102. 林俊宏、曾國雄、任維廉(2005)。利用 VIKOR 方法解決企業資源規劃系統評選問題。農業與經濟,34,69-90。
    連結:
  66. 103. 林榮泰(2005)。文化創意 設計加值。藝術欣賞,1(7), 26-32。
    連結:
  67. 105. 林銘煌(2001)。產品設計中造形的編碼與解碼。設計學報,6(2),39-52。
    連結:
  68. 111. 莊雅量 (2007) 。CAKE:擴充性感性意象調查與分析系統。國立台灣科技大學設計研究所博士論文,未出版,台北市。
    連結:
  69. 112. 陳文亮、陳姿樺(2008)。模糊決策模式在職校技藝競賽選手評選之研究-以服裝製作組為例。設計學報,13(3),23-38。
    連結:
  70. 115. 單承剛、何明泉(2005)。設計政策指標建構之研究。設計學報,10(2),13-28。
    連結:
  71. 117. 程雅伶(2007)。燈飾造型愉悅性之研究。大同大學工業設計研究所碩士論文,未出版,台北市。
    連結:
  72. 118. 衛萬里(2007)。應用分析網路程序法選擇最佳產品設計方案之決策模式分析。國立台灣科技大學設計研究所博士論文,未出版,台北市。
    連結:
  73. 119. 衛萬里、張文智(2005)。應用模糊德爾菲與分析網路程序法選擇最佳產品設計方案之研究。設計學報,10(3),59-80。
    連結:
  74. 2. Akin, Ö. (1984). An exploration of design process. In N. Cross (Eds), Developments in design methodology (pp. 189-207). New York: John Wiley & Sons.
  75. 9. Brown, T. (2010) 。設計思考改造世界(Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation)(吳莉君譯)。台北市 : 聯經。(原作2009年出版)
  76. 11. Caicedo, D. G., & Desmet, P. M. A. (2009). Designing the new prEmo – An empirical research on how to improve the emotion measuring tool. Unpublished manuscript, Delft University of Technology.
  77. 17. Design and Emotion Society. (2006). Template for tools & methods. Retrieved January 25, 2008, from http://www.designandemotion.org /society/knowledge_base/template.html.
  78. 18. Desmet, P. M. A., & Hekkert, P. (2007). Framework of product experience. International Journal of Design, 1(1), 57-66.
  79. 20. Ekman, P. (1999). Basic Emotions. In T. Dalgleish and M. Power (Eds.), Handbook of Cognition and Emotion (pp. 45-60). Sussex, U.K.: John Wiley & Sons.
  80. 21. Ekman, P. (2004)。心理學家的面相術:解讀情緒的密碼(Emotions Revealed — Understanding Faces and Feelings)(易之新譯)。台北:心靈工坊。(原作2004年出版)
  81. 22. Engage (2005). European Project on Engineering Emotional Design Report of the State of the Art- Round 1. Report Valencia.
  82. 24. Gaver, B., & Martin, H. (2000). Alternatives: exploring information appliances through conceptual design proposals. Proceedings of CHI 2000, 2(1), 209-216. Hague: ACM Press.
  83. 25. Gobe, M. (2004) 。公民品牌,感性行銷(Citizen brand : 10 commandments for transforming brands in a consumer democracy)(藍美貞、高仁君譯)。台北市 : 天下雜誌。(原作2002年出版)
  84. 27. Hair, J. F. Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate Data Analysis (5th ed.). Upper Saddle River, NJ: Prentice-Hall.
  85. 33. Jones, J. C. (1992). Design methods (2nd ed.). New York: John Wiley & Sons.
  86. 34. Jordan, P. W. (1999). Pleasure with products: human factors for body, mind and soul. In W. S. Green & P. W. Jordan (Eds.), Human factors in product design: current practice and future trends (pp. 206-217). London: Taylor & Francis.
  87. 35. Jordan, P. W. (2000). Designing Pleasurable Products: An Introduction to the New Human Factors. New York: Taylor & Francis.
  88. 37. Kim, W. C., & Mauborgne, R. (2005)。藍海策略(Blue Ocean Strategy)(黃秀媛譯)。台北市 : 天下文化。(原作2004年出版)
  89. 39. Krippendorff, K., & Butter, R. (1984). Product Semantics: Exploring the symbolic qualities of form. Inovation, The Journal of IDSA, 3(2), 4–9.
  90. 49. Mehrabian, A., & Russell, J.A. (1974). An Approach to Environmental Psychology. Cambridge, MA: MIT Press.
  91. 51. Mitsuhara, H., Ochi, Y., Kanenishi, K., & Yano, Y. (2002). An adaptive Web-based learning system with a free-hyperlink environment. In P. Brusilovsky, N. Henze, & E. Millán (Eds.), Proceedings of Workshop on Adaptive Systems for Web-Based Education at the 2nd International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH'2002 (pp. 81-91). Málaga, Spain.
  92. 52. Moalosi, R., Popovic, V., & Hickling-Hudson, A. (2007). Product analysis based on Botswana’s postcolonial socio-cultural perspective. International Journal of Design, 1(2), 35-43
  93. 57. Norman, D. A. (1988). The Design of Everyday Things. New York: Basic Books.
  94. 63. Ortony, A., Clore, G. L., & Collins, A. (1988). The Cognitive Structure of Emotions. New York: Cambridge University Press.
  95. 67. Resnick, P., & Varian, H. (1997). Recommender systems, Communications of the ACM, 40(3), 56-58.
  96. 71. Schütte, S. (2005). Engineering Emotional Values in Product Design: Kansei Engineering in Development. Linköping Studies in Science and Technology Dissertation 951. Linköping, Sweden: UniTryck .
  97. 72. Schütte, S., Eklund, J., Ishihara, S. & Nagamachi M. (2008). Affective meaning: The Kansei Engineering approach. In H. N. J. Schifferstein & P. Hekkert (Eds.), Product Experience (pp. 477-496). New York: Elsevier.
  98. 76. Smith, H. S. (2008). Emotional evaluation of a product/system. Unpublished doctoral dissertation, University of Central Florida, Orlando, Florida.
  99. 77. B. Sarwar, G. K., Konstan, J. & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International World Wide Web Conference (pp. 285-295). Hong Kong.
  100. 78. Tabachnick, B. G., & Fidell L. S. (1989). Using Multivariate Statistics (2nd ed.). New York: Harper & Row.
  101. 81. Ulrich, K.T., & Eppinger, S.D. (2003). Product Design and Development. New York : McGraw-Hill.
  102. 84. Wikimedia Foundation, Inc. (2009, Feb. 10). Myers-Briggs Type Indicator. Retrieved February 11, 2009, from http://en.wikipedia.org/wiki/Myers-Briggs_Type_Indicator.
  103. 85. Wikimedia Foundation, Inc. (2010, Mar. 18). Wilhelm Wundt. Retrieved March 22, 2010, from http://en.wikipedia.org/wiki/Wilhelm_Wundt.
  104. 87. Yoon, K. P., Hwang, C. L. (1995). Multiple Attribute Decision Making: An Introduction. Thousand Oaks : Sage Pubns.
  105. 93. Zimmermann, H. J. (1996). Fuzzy Sets and its Applications (3rd ed.). Norwell: Kluwer Academic Publishers.
  106. 95. 王淑俐(2003)。情緒管理—祝你健康快樂。台北:全華。
  107. 96. 王鴻祥(2010)。我要念工業設計。台北市:桑格。
  108. 97. 台灣設計師連線(2010)。設計師週簡介。2010年5月29日,取自:http://www.designersweek.tw/about2.html#。
  109. 98. 江睿智(2011)。向大老闆學江湖智慧。非凡新聞週刊,266。
  110. 100. 余泰魁、林益民 (2002)。情境擾動影響電子商店購物行為之研究。資訊管理展望,(4)1,97-116。
  111. 104. 林榮泰(2009)。文化創意產品設計:從感性科技、人性設計與文化創意談起。人文與社會科學簡訊,11(1),32-42。
  112. 106. 林銘煌(2005)。Alessi 義大利設計精品的築夢工廠。台北市:桑格文化。
  113. 107. 邱皓政(2006)。量化研究與統計分析-SPSS中文視窗版資料分析範例解析。台北市:五南。
  114. 108. 翁振益、周瑛琪、張保隆(2006)。決策分析方法與應用(4-189頁)。台北市:華泰文化。
  115. 109. 翁頌舜、陳文典(2006)。整合情境資訊之多維度推薦環境。2006電子商務與數位生活研討會論文集[光碟版],台北:台北大學。
  116. 110. 張春興 (1991) 。現代心理學 。台北市:東華。
  117. 113. 陳昱廷(2007)。社會服務環境中之社會要素、背景要素對消費者認知評價、情緒與因應行為之研究。國立中山大學企業管理研究所碩士論文,未出版,高雄。
  118. 114. 陳國祥、管倖生、鄧怡莘、張育銘(2001)。 感性工學─將感性予以理性化的手法。工業設計,29(1),2-16。
  119. 116. 程炳林(2005)。因素分析。在陳正昌、程炳林、陳新豐、劉子鍵編著,多變量分析方法-統計軟體應用(四版)(213-254 頁)。台北市:五南。
  120. 120. 鄧成連(1999)。設計管理:產品設計之組織、溝通與運作。台北市:亞太圖書。
  121. 121. 鄧成連(2001)。設計策略:產品設計之管理工具與競爭利器。台北市:亞太圖書。
  122. 122. 鍾毓珊(2006)。傳達情感的手法運用於產品設計。 國立雲林科技大學工業設計系碩士班碩士論文,未出版,台灣雲林。
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  2. 吳羽姍(2015)。納入通勤時間考量之租屋資訊服務架構與研究。中興大學資訊管理學系所學位論文。2015。1-62。
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  4. 蔡宜庭(2017)。手工製模式與品牌真實性及產品設計構面之關係-以文創產品為例。淡江大學國際企業學系碩士班學位論文。2017。1-66。