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研究生:曾清旗
研究生(外文):Ching-ChiTseng
論文名稱:休閒服飾設計之消費者需求研究
論文名稱(外文):A Study of Consumer Requirements on Leisure Clothing Design
指導教授:林銘泉林銘泉引用關係蕭世文蕭世文引用關係
指導教授(外文):Ming-Chyuan LinMing-Chyuan Lin
學位類別:博士
校院名稱:國立成功大學
系所名稱:工業設計學系碩博士班
學門:設計學門
學類:產品設計學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:147
中文關鍵詞:聯合分析自行車服裝設計消費者行為AIO生活型態量表
外文關鍵詞:conjoint analysisbike clothing designbuying behaviorAIO
相關次數:
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產品設計是為滿足人類需求的一種具有創造性的決策過程,而好的產品的推出便是要符合消費者的偏好與需求。新產品開發的通用模式是使設計師去了解產品之消費者的消費生活型態、需求、隱性消費族群之需求、購買行為及喜好態度,意圖找出產品在市場上受歡迎的因素,組合成最佳設計方案。
  騎乘自行車在維持健康的貢獻上已成為受歡迎的活動。自行車相關的服裝眾所皆知在舒適度和安全性扮演重要的角色。不幸的是,在自行車相關的服裝設計過程中幾乎沒有任何研究或設計上考慮到顧客的消費生活型態、需求、隱性消費族群之需求、購買行為及喜好態度。許多製造商主要焦點集中在改善衣服材料性能上的發展來滿足客戶的需求,而不是服裝設計。基於此,本研究即針對自行車服飾購買行為、消費生活型態及產品喜好態度等議題,發展一個客觀、量化的評估系統,協助設計師及使用者進行產品模擬設計。
本研究運用AIO(活動A,興趣I,意見O)生活型態量表,作問卷設計,運用SPSS統計分析軟體之敘述性統計分析、K平均數法集群分析、因素分析、AHP層級分析程序法、複迴歸分析在自行車相關的服裝設計上之消費者的消費生活型態、需求、隱性消費族群之需求、購買行為及喜好態度,以提供設計師有效的去了解顧客需求喜好。透過大量資料的收集及態度量表問卷的設計,全面性的了解自行車服飾顧客需求及使用者生活型態。運用因素分析法將顧客需求作分類,再將顧客需求屬性展開,再運用聯合分析法,推引出消費者需求偏好的最佳化產品設計之組合。最後,聯合分析的方法,獲得以客戶堅持的喜好度之最佳的自行車相關服飾設計組合。

Product design is a creative decision-making process that aims to satisfy human needs by releasing good products that can appropriately meet the preferential requirements of customers. In the development of new products, the designer must identify the preference and attitudes of customers toward certain products, ascertain the factors that make products popular in the market and devise optimum design plans for those products.
Biking has become a popular activity due its contribution in maintaining health. Bicycle-related clothing is known to play an important role in comfort level and safety. Unfortunately, there is hardly any research or designs that consider customer preferences in the bicycle-related clothing design process. Many manufacturers mainly focus on the improvement of the material properties of clothes instead of clothing design to meet the customer requirements. Therefore, this study is to examine buying behavior of biking clothing, consumption lifestyle, and product preference and attitudes. The acquired information is then used to develop an objective and quantitative evaluation system to assist designers and users to carry out product simulation design.
This study uses AIO (activity, interests and opinion) lifestyle scale to design the questionnaire. SPSS is used for descriptive statistics, cluster analysis of K-average method, factor analysis, AHP hierarchy analysis process, and regression analysis for consumers’ consumption lifestyle, needs, hidden consumers’ requirements, buying behavior, preferences and attitudes. This statistical information provides designers with an efficient approach to identify customer preferences and the lifestyle of consumer groups. Customer requirements are subsequently categorized through factor analysis, and critical requirement attributes are identified for conjoint analysis. Finally, conjoint analysis is used to obtain the optimal design combination for bicycle-related clothing that adheres to the preferences of customers.
Abstract(Chinese) I
Abstract (English) II
Acknowledgements IV
Contents VI
List of Tables IX
List of Figures XII
Chapter 1 Introduction 1
1.1 Research background 2
1.2 Problem statements 6
1.3 Research objectives 8
1.4 Organization of this dissertation 9
Chapter 2 Literature Review 11
2.1 Leisure clothing design and development 11
2.2 Consumer behavior theory 13
2.2.1 Definition of consumer behavior 14
2.2.2 Consumer behavior models 18
2.3 Lifestyle evaluation 26
2.3.1 Definition of lifestyle and objectives for
studying lifestyle 26
2.3.2 Impacts from lifestyle on consumer behavior and
satisfactory 28
2.3.3 Lifestyle research structure 29
2.3.4 Lifestyle evaluation and dimensions 30
2.3.5 Lifestyle evaluation methods 31
2.3.6 Lifestyle applications 32
2.4 Factor analysis 32
2.4.1 Applications of factor analysis 33
2.4.2 Factor analysis procedure 33
2.5 Analytic hierarchy process 34
2.5.1 AHP for product evaluation 34
2.5.2 AHP procedure 35
2.5.3 The seven features of AHP 38
2.5.4 Constructing the hierarchical structure for the
problem 39
2.5.5 Evaluation scale of AHP 39
2.5.6 Establishing a pairwise comparison matrix 40
2.5.7 Advantages and disadvantages of AHP 40
2.6 Kansei engineering 40
2.6.1 Kansei Engineering’s method classification 42
2.6.2 Kansei Engineering research applications 43
2.7 Conjoint analysis 46
2.7.1 Procedure of conjoint analysis 48
2.7.2 Advantages, disadvantages, and limitations of
conjoint analysis 54
2.7.3 Development of conjoint analysis for product
design 55
Chapter 3 Research Orientation 57
3.1 Research methods and means 57
3.2 Research procedure 60
3.3 Research limitations 63
Chapter 4 Data Collection and Analysis 65
4.1 Biking and biking clothing collecting and
integration 66
4.2 Definition of different biking groups and
questionnaire design for biking related clothing
demand attributes 76
4.3 Definition and analysis of preferences and buying
behavior of biking clothing demand attributes 82
Chapter 5 Factor Analysis 88
5.1 Statistical analysis of questionnaire data, orthogonal
array, and overall profile cards 88
5.2 Preparing the orthogonal array 101
Chapter 6 Conjoint analysis and product preference
combination 103
6.1 Conjoint analysis 103
6.2 Preference attitude analysis of bicyclists on clothing
products 109
Chapter 7 Conclusions 122
References 129
Appendix 137
VITA 145

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