方法目的鏈（Mean-end Chain, MEC）具有屬性→結果利益→隱含價值的連結關係，國內外文獻已有許多探討運用MEC於不同商品或服務等之需求要素研究。由於近年出現熱門時尚話題元宇宙指數股票型基金（Exchange Trade Fund, ETF）投資，本研究運用MEC探索投資人對於元宇宙ETF的認知與價值結構。研究取向希望提供ETF商品開發機構在商品設計與開發過程，直接發掘投資人的需求和期待價值，縮短研究與實務運用上的缺口。
研究動機為探索元宇宙ETF新科技商品的運用，希望發掘投資人真正的需求和期待訴求。研究目的：
一、 瞭解元宇宙ETF的屬性本質與內涵。
二、 以MEC探索投資人的認知與價值觀點。
依MEC理論及方法，結果發現整體價值階層圖顯示，推演元宇宙ETF主要隱含價值為「體驗潮流科技的新鮮感」、「對元宇宙實現的憧憬」等。與隱含價值連結較高的結果利益為「先佈局元宇宙科技股」、「持有虛實整合數位資產」等。而投資人對元宇宙ETF的商品主要認知屬性是「投資最新潮流科技」等。本研究另和實務經驗比較後發現，研究結果投資人認知屬性主要源自最近熱門時尚話題元宇宙ETF投資、但實務上更簡化認為這是屬於追逐投資新科技產業的族群。本研究結論整理對於MEC運用過程的發現，重點例如：要素定義越清楚，能探索出投資人認知屬性與結果利益，更能推演投資人的內心隱含價值。受訪者資格需要試訪談，以確定研究對象是既有客群，或可以更擴大為潛在客群。專家訪談反饋意見，提醒截取值以下的要素，有些可能更符合認知屬性等。最後，建議商品開發機構可被動地參考研究結果以豐富新產品的開發，或者可以主動的對投資人行銷教育認知與價值結構的觀念，置入性培養新的投資族群客戶。

The Mean-End Chain (MEC) has a link relationship of attributes→ outcome benefits → embedded values. There are already many domestic and foreign literatures that explore the application of MEC at different commodities or services on element of demand. Due to a hot trend topic of Metaverse ETF ( Exchange Trade Fund ) investment appears in recent years, this study will apply the MEC to explore the investors’ cognitive and value structure of the Metaverse ETF. The orientation of this study aims to provide product development institutions, in their product design and development process, ability to directly dig out investors’ demands and expected values, so as to reduce the gap between study and practical application.
This study will explore the investors’ cognitive and value structure of Metaverse ETF through applying the MEC. The study motivation is to explore the application in Metaverse ETF new technology commodity. Hope to discover the real investors’ expected demand and real needs. The study objectives are:
1. To understand the nature and connotation of the properties of Metaverse ETF;
2. To investigate the cognitive and value viewpoints of investors using MEC.
According to the MEC theory and method, the results found that the overall value hierarchy chart shows, it can be derived that the main embedded values of Metaverse ETF including “Experience the freshness of trendy technology”; “A vision of the realization of the metaverse”; Those outcome benefits with higher links of embedded values are "Early deployment of Metaverse technology stocks"; "Holding digital assets of integration the virtual and reality". Investors’ main commodity cognitive attributes of Metaverse ETF is "Investing in the latest trend technology". Due to investors’ cognitive attributes, through the link of key factors, obtain the outcome benefits and deduce the final embedded values.
The conclusion is to sort out the findings on the application process of MEC. As important as: the clearer the definition of elements, the better the investors' cognitive attributes and results can be explored, and the better the investor's inner embedded value can be deduced. Pre-interviews customers to verify whether the study object is an existing customer group, or it can be expanded into a potential customer group. Experts interview feedback, reminding the elements below the cut-off value, some of which may be more in line with cognitive attributes. Finally, it is suggested that commodity development institutions can passively refer to the study results to enrich the development of new products or can actively educate and marketing investors on the concept of cognitive and value viewpoints, placement to cultivate new investment group customers.

一、中文文獻
1. 王石番（1996年），傳播內容分析法—理論與實證，台北：幼獅文化事業公司。
2. 白佩玉（2016年05月），銀行服務之顧客價值階層之研究：方法目的論與KANO模式之運用；朝陽科技大學企業管理系碩士論文。
3. 尼爾･史蒂文森（Neal Stephenson），李卓翰、陳夏民譯（2008年06月30日），潰雪（Snow Crash）；開元書印。
4. 李傑（2021年12月31日），元宇宙的科學計量分析；大陸科學院文獻中心，網址：https:blog.sciencenet.cnlblog-554179-1326199.html。
5. 李弘康（2001年07月），國內銀行財富管理業競爭策略之研究－以S銀行為個案；中華大學企業管理系碩士論文。
6. 呂文博、謝宗恒、周欣宜、陳佩君、歐聖榮（2018年06月），以方法目的鏈模式建構公司社群網路環境；興大園藝 （Horticulture NCHU），38（4），頁111~125。
7. 汪美香、楊棠堯、魏志誠（2013年），旅遊目的地價值內涵之研究；Journal of e-Business 電子商務學報，第二十卷第一期，頁1~32。
8. 邱未頌正、李梅菲（2002年01月），行動電話購買行為研究－「方法－目的鏈」之研究；傳播與管理研究，2002卷01期，頁213~237。
9. 林毓才（2021年），利用短線交易成本探討商品ETF價格合理性－以元大石油ETF為例；國立台北大學統計學系碩士論文。
10. 林榮春、邱天佑、林茂雄（2011年03月），影響網路銀行實際使用行為之研究；顧客滿意學刊，第七卷第一期，頁01~22。
11. 林宗賢、侯錦雄。2007。遊客溫泉旅遊渡假區知覺意象之度量—以谷關為例。戶外遊憩研究。20（2），頁79~99。
12. 林勤豐、葉明義、邱兆民。2000。探討消費者「屬性-結果-價值鏈」之建構特性。輔仁管理評論。7（2），頁21~48。
13. 林宗賢、蕭慧齡。2008。檢視遊客参與鹽水蜂炮節慶活動之重遊行為意圖。戶外遊憩研究。21（2），頁01~22。
14. 洪伈華（2012年07月），以方法目的鏈探討金門觀光懷舊體驗的內涵與價值；國立金門大學觀光管理學系碩士論文。
15. 洪銘凰（2021年07月），比較不同投資策略之表現績效—以富邦公司治理100 ETF、元大MSCI 台灣ETF、元大台灣50 ETF為例；國立屏東大學運用數學系碩士論文。
16. 許旭昇（2020年03月），探討方法目的鏈運用於科技政策規劃之可行性－以網路預約叫車服務為例，國家實驗研究院科技政策研究與資訊中心科技政策觀點研究成果，網址 portal.stpi.narl.org.tw。
17. 許瑞宋譯（2017年09月），巴菲特寫給股東的信，許瑞宋譯，時報出版。
18. 陳思倫、劉錦桂。1992。影響旅遊目的地選擇之地點特性及市場區隔之研究。戶外遊憩研究。5（2），頁39~70。
19. 陳宜芬、賴靖憲（2021年12月），以方法目的鏈（MEC）探討中高齡者使用Line之因素；資訊管理學報，第二十六卷第二期，頁121~151。
20. 陳宜芬、蔡逸帆（2019年04月），以客為尊－以方法目的鏈探討行動銀行對顧客價值之研究；Journal of e-Business 電子商務學報，第二十三卷第二期，頁119~152。
21. 婁文信、李政達、廖涵玟（2011年），銀行顧客之購買行為與多重通路使用關聯性；行銷評論，2011年冬季第8卷，第4期，頁453~472。
22. 郭建良、白玫莉（2015年），結合方法-目的鏈及消費者決策模型進行新興服務體驗流程設計的可行性研究，Journal of e-Business 電子商務學報，第十七卷第三期，頁345~374。
23. 黃淑琴、陳貞吟（2011年10月），從價值與魅力品質理論探討女性的婚紗夢，管理與系統，第十八卷第四期，頁581~605。
24. 曾光華、陳貞吟、張永富。2004。以方法目的鏈探討旅客懷舊體驗的內涵與價值。戶外遊憩研究。17（4），頁43~69。
25. 張淙皓（2018年06月），以方法目的鏈探討消費者對食物浪費的認知；東海大學餐旅管理學系碩士論文。
26. 詹定宇、彭西鄉。2010。蜜月旅行價值內涵之研究：方法目的鏈之運用。戶外遊憩研究。23（1），頁01~26。
27. 萬文隆（2004年），深度訪談在質性研究中的運用；生活科技教育月刊，三十七卷第四期。
28. 葛思惠（2003年06月），指數股票型基金之制度規劃；證券暨期貨管理，2003年06月號月刊。
29. 經理人月刊（2014年12月16日），找出客戶真正想要的價值，勾起購買動機，2014年12月號月刊。
二、英文文獻
1. Bagazzi, R., and Dabholkar, P. (1994). Consumer recycling goals and their effect on decision to recycle: A means-end Analysis. Psychology and Marketing, 11(4), 313~340.
2. Bech-Larsen, T., & Nielsen, N. A. (1999). A comparison of five elicitation techniques for elicitation of attributes of low involvement products. Journal of Economic Psychology, 20(3), 315~341.
3. Borgardt, E. (2017). Motivation and consumer behavior, Konsumpcja I Rozwoj, 4(21).
4. Borgardt, E. (2018). Conventional and extended versions of Means-End Chain theory. Zeszyty Naukowe Uniwersytetu Eknonomicenego w Krakowie. 3(395). 191~204.
5. Budd, R. W., Thorp, R. K., & Donohew, L. (1967). Content analysis of communications. New York: Macmillan.
6. Celsi, R. L., & Olson, J. C. (1988). The Role of Involvement in Ayyention and Comprehension Processes. Journal of Consumer Research, 15, 210~224. http://dx.doi.org/10.1086/209158
7. Chen, N. H., Lee, C. H., & Huang, C. T. (2015). Why buy organic rice? Genetic algorithm-based fuzzy association mining rules for means-end chain data. International Journal of Consumer Studies, 39(6), 692~707.
8. Chen, L. H., & Ko, W. C. (2010). Fuzzy linear programming models for NPD using a four phase QFD activity process based on the means-end chain concept. European Journal of Operational Research, 201(2), 619~632.
9. Cheng, K. F., Chen, C. Y., & Chang, Y. F. (2004). Tourist’s perceived meanings and values of nostalgic experiences: A means-end chain approach. Journal of Outdoor Recreation Study, 17(4), 43~69.
10. Elena Borgardt (2020). MEANS-END CHAIN THEORY: A CRITICAL REVIEW OF LITERATURE. RESEARCH PAPERS OF WROCLAW UNIVERSITY OF ECONOMICS AND BUSINESS, 2020, vol. 64, nr 3.
11. Gengler, C. E., Mulvey, M. S., and Janet E. (1999). A means-end analysis of mothers’ infant feeding choices. Journal of Public Policy and Marketing, 18(2), 172~188.
12. Goldenberg, M. A., D. B. Klenosky, J. T. O’Leary, and T. J. Templin. 2000. A means-end investigation of ropes course experience. J. Leisure Res. 32（2）: 208~224.
13. Grunert, K. G. and S. C. Grunert. (1995). Measuring subjective meaning structures by the laddering method: Theoretical consideration and methodological problems. Int. J. Res. Market. 12（3）: 209~225.
14. Gutman, J. 1982. A mean-end chain model based on consumer categorization processes. J. Market. 46（2）: 60~72.
15. Gutman, J. and Miaoulis, G. (2003), “Communicating a quality position in service delivery: An application in higher education”, Managing Service Quality, 13(2).
16. Ho, C. I., Yu, C. L., Huang, S. C., & Lai, Y. H. (2015). Psychological values of cycling around Taiwan: A hierarchical analysis of value-based motivations. Sports and Exercise Research, 17(4), 383~402.
17. Howard, J. A. (1977). Consumer behavior: Application of theory. New York: McGraw-Hill.
18. Jung, Y., & Kang, H. (2010). User goals in social virtual worlds: A means-end chain approach. Computers in Human Behavior, 26(6), 218~225.
19. Kaden, R., Gerald. L., and Price. M. (2012). Leading edge marketing research:21st-century tools and practices. Thousand Oaks, Calif.: SAGE.
20. Kahle,L. R., Patricia Kennedy (1989). Using the List of Values (LOV) to Understand Consumers. Journal of Consumer Marketing 6(3):5~12.
21. Kassarjian. 1977. Content analysis in customer research. J. Consum. Res. 4（1）: 8~18. Olson, J. C. and T. J. Reynolds. (1983). Understanding consumers’ cognitive structures: implications for marketing strategy. In: Advertising and consumer psychology, L. L. Percy and A. G. Woodside (eds.). Mass: Lexington Books, Lexington. pp. 77~90.
22. Klenosky, D. B., Frauman.E., Norman, W. C., and Gengler, C. E. (1998). Nature-based tourists’ use of interpretive service: A means-end investigation. Journal of Tourism studies, 9(2), 26~36.
23. Klenosky, D. B. (2002). The “Pull” of Tourism Destinations: A Mean-End Investigation. Journal of Travel Research, 40(4), 396~403.doi:10.1177/004728750204000405
24. Kuisma, T., Laukkanen, T., & Hiltunen, M. (2007). Mapping the reasons for resistance to Internet banking: A means-end approach. International Journal of Information Management, 27(2), 75~85.
25. Kuo, C. L., & Pai, M. L. (2015). A feasibility study on developing a service experience design methodology for emerging services by integrating means-end chain and the consumer decision-making model. Journal of e-Business, 17(3), 345-374. Elicitation of attributes of low involvement products. Journal of Economic Psychology, 20(3), 315~341.
26. Lin, C. F., Yeh, M. Y., & Chiu, C. M. (1999). Applying means-end chains analysis to establishing marketing research variables and marketing strategies. Web Journal of Chinese Management Review, 2(6), 107~128.
27. Lin, Y. L., & Lin, H. W. (2011). A study on the goal value for massively multiplayer online role-playing games players. Computers in Human Behavior, 27(6), 2153-2160.
28. Olson, J. C., & Reynolds, T. J. (1983). Understanding consumers’ cognitive structures: Implications for advertising strategy. In Percy, L., & Woodside, A. (Eds.), Advertising and consumer psychology. Lexington, MA: Lexington Books.
29. Pieters, R., Baumgartner, H., & Allen, D. (1995). A means-end chain approach to consumer goal structures. International Journal of Research in Marketing, 12(3), 227~244.
30. Peter, J. P. , and Olson, J. C. (1996). Consumer behavior and marketing strategy, New York: Irwin Book.
31. Reynolds, T. J., & Gutman, J. (1988). Laddering theory, method, analysis, and interpretation. Journal of Advertising Research, 28(1), 11~31.
32. Reynolds, T. J., & Olso, J. C. (2001). Understanding consumer decision making: The means-end approach to marketing and advertising strategy. Mahwah, NJ: Lawrence Erlbaum Associates.
33. Rokeach, M. J. 1973. The Nature of Human Values. The Free Press, New York.
34. Schoell, W. F., & Guiltian, J. P. (1990). Marketing: Contemporary concepts and practices, 173.
35. Stanton, W. J., & Etzel, Michael, J. (1991). Fundamentals Marketing, 9th ed., 168.
36. Sun, P. C., Cheng, H. K., & Finger, G. (2009). Critical functionalities of a successful e-learning system: An analysis from instructors’ cognitive structure toward system usage. Decision Support Systems, 48(1), 293~302.
37. Ter Hofstede, F., Audenaert, A., Steenkamp, J. B. E., & Wedel, M. (1998). An investigation into the association pattern technique as a quantitative approach to measuring means end chains. International Journal of Research in Marketing, 15(1), 37~50.
38. Tolman, E. C. (1932). Purposive behavior in animals and men. New York: Appleton-Century-Crofts.
39. Vinson, D. E., Scott, J. E., & Lamont, L. M. (1977). The role of personal values in marketing and consumer behavior. Journal of Marketing, 41(2), 44~50.
40. Veludo-de-Oliveira, T. M., Ikeda, A. A., & Campomar, M. C. (2006). Discussing laddering application by the means-end chain theory. The Qualitative Report, 11(4), 626~642.
41. Valette-Florence, P., & Rapacchi, B. (1991). Improvements in means-end chain analysis: Using graph theory and correspondence analysis. Journal of Advertising Research. 31, ebruary / March, 30~45.
42. Wang, M. H., Yang, T. Y., & Wei, C. C. (2018). Creating social networking environment for workers through a means-end chain model. Journal of e-Business, 20(1), 1~32.
43. Yen, R. H. J., Li, E. Y., Hsiao, C. C., & Lin, K. S. (2006). Exploring the hierarchy of customer relational benefits: An application of means-end chain. Management Review, 25(1), 95~119.
44. Young, S., & Feigin, B. (1975). Using the benefit chain for improved strategy formulation. Journal of Marketing, 39(3), 72~74.