| 研究生: |
林伯晏 Lin, Po-Yen |
|---|---|
| 論文名稱: |
應用使用者知覺價值模型於產品設計決策 Applying User Perceived Value Model to Design Decisions: Using Run Tracking App As An Example |
| 指導教授: |
劉說芳
Liu, Shuo-Fang |
| 學位類別: |
碩士 Master |
| 系所名稱: |
規劃與設計學院 - 工業設計學系 Department of Industrial Design |
| 論文出版年: | 2019 |
| 畢業學年度: | 107 |
| 語文別: | 中文 |
| 論文頁數: | 94 |
| 中文關鍵詞: | 知覺價值模型 、設計決策 、結構方程模式 |
| 外文關鍵詞: | consumer perceived value model, Structural equation model, design decision |
| 相關次數: | 點閱:101 下載:1 |
| 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 |
隨著智慧型手機的普及與硬體發展,越來越多手機應用程式與服務型態出現,設計師與開發商無不希望能在競爭激烈的市場中,開發出比對手更成功的產品。然而面對前所未見的服務型態,順利的將產品所提供的服務與價值傳達給使用者,並且在眾多競爭對手中突出,變得越來越難。在此情況下,若能理解使用者對於產品價值的知覺方式,並進一步探討不同設計決策對於產品知覺價值的影響,將可以幫助產品設計師評估不同設計決策,更順利的將產品提供的服務價值傳遞給使用者。
本研究以運動紀錄此近年來新興的手機應用程式種類為例,將研究分為兩階段。在第一階段,本研究探討過去關於消費者知覺價值模型的的相關研究,以產品設計師的角度考慮其中各影響要素的優缺點與重要性,提出一以產品設計師所能影響之要素為主的使用者知覺價值模型,並設計量表測量模型中各要素,以結構方程模式驗證影響關係。第二階段則進一步探討不同設計決策對於產品知覺價值的影響,分析市場中運動紀錄手機應用程式的常見設計決策與決策的表現形式,以第一階段設計出之量表測量各表現形式,實際運用上階段的研究成果。
研究結果顯示使用者對於運動紀錄型手機應用程式的知覺價值會被知覺品質所影響,而知覺品質可由產品的美學特徵表現、功能特徵表現以及社交特徵表現所測量,其中知覺品質可解釋69%的知覺價值,而功能特徵要素則是與知覺品質最相關的產品要素,其次為美學特徵要素與社交特徵要素。而本研究亦透過驗證式因素分析確立了一可測量產品美學、功能及社交要素的量表。第二階段則實際分析現有產品的常見決策,將各決策表現形式的量表得分與其在市場中的趨勢比較,將設計決策分為確定型、差異化型、機會型及選擇型四種。設計師或開發商可以此架構分析產品與設計決策。在產品的層級,理解產品各面向的特徵中對使用者知覺價值影響最大的面向,作為開發或改良的重點。更進一步,在不同面向的設計決策層級,測量不同決策表現形式之得分以理解其對知覺價值的影響。
With the popularity and hardware development of smart phones, more and more mobile phone applications and service types have emerged. Designers and developers all hope to develop products that are more successful than their competitors in a highly competitive market. . However, in the face of unprecedented service types, it is becoming more and more difficult to successfully convey the services and values provided by the products to users and to stand out among many competitors. In this case, if you can understand the user's perceived of the value of the product and further explore the impact of different design decisions on the perceived value of the product, it will help the product designer to evaluate different design decisions and smoother the service value of the product. Passed to the user.
The results show that the perceived value of the running app is affected by the perceived quality, which can be measured by the aesthetic attributes, functional attributes, and social attributes, of the product. The perceived quality can explain 69% of perceived value, while functional feature elements are most relevant to perceived quality, followed by aesthetic attributes and social attributes. This study also develops a scale that measures the aesthetic, functional and social attributes of a product through a validation factor analysis. In the second stage, the common decisions of existing products are analyzed. The scores of the scales of each decision-making form are compared with their trends in the market. The design decisions are divided into four types: deterministic, differentiated, opportunistic and selective. Designers or developers can analyze product and design decisions with this model. At the level of the product, understanding the aspects of the product's various attributes that have the greatest impact on the user's perceived value. Furthermore, at different design-oriented decision-making levels, different decision-making performance scores are measured to understand their impact on perceived value.
黃芳銘(2004). 社會科學統計方法學 :結構方程模式. 台北市:五南圖書出版公司。
黃芳銘(2007). 結構方程模式:理論與應用. 台北市:五南圖書出版公司。
余桂霖(2011).結構方程式模型分析. 台北市:五南圖書出版公司。
吳明隆(2008).論文寫作與量化研究. 台北市:五南圖書出版公司。
張紹勳(2008).研究方法:理論與統計.台中市:滄海書局。
黃香穎(2013). 新產品屬性及產品吸引力對消費者購買意願研究. 國立成功大學工業設計研究所。
宋雨真(2014). 衛生棉之產品體驗知覺對於使用者在情感上的行為促發.國立高雄師範大學工業設計研究所。
甘美玲(2006). 知覺價格、知覺品質、知覺價值對購買意願之關係研究-以消費者購買數位內容產品為實證.國立成功大學高階管理碩士在職專班。
Amini, P., Falk, B., & Schmitt, R. (2014). Quantitative Analysis of the Consumer Perceived Value Deviation. Procedia CIRP, 21, 391-396. doi:10.1016/j.procir.2014.02.059
Bei, L.-T., Chiao, Y.-C. J. J. o. c. s., dissatisfaction, & behavior, c. (2001). An integrated model for the effects of perceived product, perceived service quality, and perceived price fairness on consumer satisfaction and loyalty. 14, 125.
Breivik, E., & Olsson, U. H. (2001). Adding variables to improve fit: the effect of model size on fit assessment in LISREL. In R. Cudeck, du Toit Stephen, & D. Sörbom (Eds), Structural equation modeling: Present and future. A festschrift in honor of Karl Jöreskog (pp.169-194). IL: SSI.
Bloch, P. H. J. T. J. o. M. (1995). Seeking the ideal form: Product design and consumer response. 16-29.
Boztepe, S. J. D. s. (2007). Toward a framework of product development for global markets: a user-value-based approach. 28(5), 513-533.
Butz Jr, H. E., & Goodstein, L. D. (1996). Measuring customer value: gaining the strategic advantage. Organizational dynamics, 24(3), 63-77.
Cagan, J., & Vogel, C. M. (2002). Creating breakthrough products: Innovation from product planning to program approval: Ft Press.
Carmines, E. G., & McIver, J. P. (1981). Analyzing Models with Unobserved Variables: Analysis of Covariance Structures. In G. W. Bohrnstedt, & E. F. Borgatta (Eds.), Social Measurement: Current Issues (pp. 65-115). Beverly Hills: Sage Publications, Inc.
Chen, C.-F., & Chen, F.-S. J. T. m. (2010). Experience quality, perceived value, satisfaction and behavioral intentions for heritage tourists. 31(1), 29-35.
Chen, Z., & Dubinsky, A. J. (2003). A conceptual model of perceived customer value in e‐commerce: A preliminary investigation. Psychology & Marketing, 20(4), 323-347.
Crilly, N., Moultrie, J., & Clarkson, P. J. J. D. s. (2004). Seeing things: consumer response to the visual domain in product design. 25(6), 547-577.
Crilly, N., Moultrie, J., & Clarkson, P. J. J. D. S. (2009). Shaping things: intended consumer response and the other determinants of product form. 30(3), 224-254.
Dodds, W. B., Monroe, K. B., & Grewal, D. J. J. o. m. r. (1991). Effects of price, brand, and store information on buyers' product evaluations. 307-319.
Doll, W. J., Xia, W., & Torkzadeh, G. (1994). A Confirmatory Factor Analysis of the End-User Computing Satisfaction Instrument. MIS Quarterly, 12(2), 259-274.
Giese, J. L., Malkewitz, K., Orth, U. R., & Henderson, P. W. (2014). Advancing the aesthetic middle principle: Trade-offs in design attractiveness and strength. Journal of Business Research, 67(6), 1154-1161.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1-55.
Kumar, M., & Noble, C. H. (2016). Beyond form and function: Why do consumers value product design?. Journal of Business Research, 69(2), 613-620.
Leszinski, R. and Marn, M.V. (1997), “Setting value, not price”, The McKinsey Quarterly, No. 1,pp. 99-115.
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. J. S. e. m. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. 9(2), 151-173.
MacCallum, R. C., & Austin, J. T. J. A. r. o. p. (2000). Applications of structural equation modeling in psychological research. 51(1), 201-226.
McDonald, R. P., & Ho, M. R. (2002). Principles and practice in reporting structural equation analysis. Psychological methods, 7, 64-82.
Mulaik, S. A., James, L. R., Altine, J. V., Bennett, N., Lind, S., & Stilwell, C. D. (1989). Evaluation of goodness-of-fit indices for structural equation models. Psychological Bulletin, 105(3), 430-445.
Neslin, S. A. J. J. o. M. R. (1981). Linking product features to perceptions: Self-stated versus statistically revealed importance weights. 80-86.
Richardson, P. S., Dick, A. S., & Jain, A. K. J. T. J. o. M. (1994). Extrinsic and intrinsic cue effects on perceptions of store brand quality. 28-36.
Rosseel, Y. J. J. o. s. s. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). 48(2), 1-36.
Sheth, J. N., Newman, B. I., & Gross, B. L. J. J. o. b. r. (1991). Why we buy what we buy: A theory of consumption values. 22(2), 159-170.
Sirohi, N., McLaughlin, E. W., & Wittink, D. R. J. J. o. r. (1998). A model of consumer perceptions and store loyalty intentions for a supermarket retailer. 74(2), 223-245.
Sweeney, J. C., & Soutar, G. N. J. J. o. r. (2001). Consumer perceived value: The development of a multiple item scale. 77(2), 203-220.
Teas, R. K., & Agarwal, S. J. J. o. t. A. o. m. S. (2000). The effects of extrinsic product cues on consumers’ perceptions of quality, sacrifice, and value. 28(2), 278-290.
Ulaga, W., & Chacour, S. (2001). Measuring customer-perceived value in business markets: a prerequisite for marketing strategy development and implementation. Industrial marketing management, 30(6), 525-540.
Ullman, J. B. (2001). Structural equation modeling. In B. G. Tabachnick and L. S. Fidell (2001), Using Multivariate Statistics (4th ed.): 653-771. Needham Heights, MA: Allyn and Bacon.
Vandermerwe, S. J. S. m. r. (2000). How increasing value to customers improves business results. 42(1), 27-27.
Vasic, N., Kilibarda, M., & Kaurin, T. (2019). The Influence of Online Shopping Determinants on Customer Satisfaction in the Serbian Market. Journal of Theoretical and Applied Electronic Commerce Research, 14(2), 70-89. doi:10.4067/s0718-18762019000200107
Voss, G. B., Parasuraman, A., & Grewal, D. (1998). The roles of price, performance, and expectationsin determining s atisfaction in service exchanges. The Journal of Marketing, 46-61.
Xu, Y., Summers, T. A., & Belleau, B. D. J. J. o. B. R. (2004). Who buys American alligator?: Predicting purchase intention of a controversial product. 57(10), 1189-1198.
Zeithaml, V. A. J. T. J. o. m. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. 2-22.
校內:2022-01-01公開