根據交通部2015年調查，台灣是亞洲機車密度最高的國家，在進入訴求綠能環保的年代，油電混合或純電驅動勢必是未來發展的方向， 2016年睿能創意股份有限公司發表「GOGORO」的電動機車，打破既往電動機車充電的侷限，在續航力、速度與爬坡力與一般的125cc機車不相上下，而這種以換電模式下營運的電動機車，是否讓消費者接受，即是本研究探討的方向。本研究以GOGORO電動機車使用者作為研究對象，了解消費者對使用GOGORO的影響因素，以「知覺易用」、「知覺有用」、「使用態度」、「行為意圖」的科技接受模式為研究架構的基礎，同時考慮「時尚科技傾向」、「環保傾向」、「知覺風險」及「知覺價格」等構面，分析了解使用GOGORO的可能影響因素。
本研究以SurveyCake設計問卷，並在GOGORO社團網站(官方及非官方)發放，共發放297份網路問卷，回收297份，有效269份。將所蒐集到的資料利用統計軟體SPSS及AMOS分析，在信度分析結果具有高度的內部一致性；驗證性因素分析均有良好配適度指標、收斂及區別效度；而在結構方程模式結果中顯示：(1)使用態度對行為意圖有正向影響；(2)認知易用對使用態度有正向影響；(3)認知有用對使用態度有正向影響；(4)知覺風險對使用態度有負向影響；(5)知覺風險對認知有用有負向影響；(6)知覺價格對使用態度有正向影響；(7)時尚科技傾向對使用態度有正向影響；(8)時尚科技傾向對認知有用有正向影響；(9)環保傾向對認知有用有正向影響；(10)環保傾向對使用態度有正向影響。但是環保傾向對認知易用沒有顯著影響。最後，從研究結論，提供後續業者提升在GOGORO消費者接受程度的建議。

According to a survey conducted by the Ministry of Transportation and Communications R.O.C, in 2015, Taiwan is the country with the highest density of scooters in Asia. In this era of green energy and environmental protection, hybrid or pure electric driven vehicles are bound to be the future direction of transportation. In 2016, Rui-Neng Creative Co., Ltd. published the following statement: “The GOGORO electric scooter breaks the limitations of the previous electric scooter charging. Its endurance, speed and gradeability are comparable to those of an ordinary 125cc scooter.” Determining whether this electric scooter in the battery swapping mode is acceptable to consumers is the direction of this research. This study takes GOGORO electric scooter users as the research object to determine factors influencing use of GOGORO. The research framework is based on the technology acceptance model (TAM) indices, including perceived ease of use, perceived usefulness, attitude toward use, and behavioral intention. At the same time, other factors, including a tendency to be fashion prone, environmental awareness, perceived risk, and perceived price were analyzed to determine factors possibly influencing the use of GOGORO.
SurveyCake was used in this research to design questionnaires, which were put on the GOGORO community website (both official and unofficial). A total of 269 valid questionnaires were collected. The collected data was analyzed using SPSS and AMOS statistical software. The results of the reliability analysis indicated a high degree of internal reliability. The confirmatory factor analysis indicated good fitness indicators, convergence validity, and discriminative validity, and the results of the structural equation model showed the following: (1) attitude toward use has a positive effect on behavioral intention; (2) ease of use has a positive influence on attitude; (3) perceived usefulness has a positive influence on attitude; (4) perceived risk has a negative influence on attitude; (5) perceived risk has a negative effect on cognitive usefulness; (6) perceived price has a negative impact on attitude toward use; (7) tendency to be fashion prone has a positive effect on attitude toward use; (8) tendency to be fashion prone has a positive effect on cognitive usefulness; (9) environmental awareness has a positive effect on cognitive usefulness, and (10) environmental awareness has a positive effect on attitude. However, cognitive ease of use has no significant effect on cognitive ease of use. Finally, based on the overall conclusions, we provide suggestions for companies to improve consumer willingness toward use of the GOGORO electric scooter.

1.i-Buzz網路口碑研究中心. (2016年10月14)。電動機車口碑報告：環保意識帶領購買潮？售價、便利與安全才是網友關切重點！。西元2016年10月14日。取自https://i-buzz.com.tw/industry/article_page/?id=NjE=&n=c2aa848012df6d484d0ed1362d2c2651
2.于永芳. (2016)。個人創新對使用態度與行為意圖之研究-以智慧型手機為例。臺北城市科技大學碩士論文。
3.中時新聞網. (2016年9月23日)。gogoro 首度南下參加臺南生綠展。西元2016年9月23日。取自https://www.chinatimes.com/newspapers/20160923000523-260511?chdtv
4.中時新聞網. (2019年1月3日)。《產業》電動機車去年逆揚，GOGORO銷售倍增。西元2019年1月3日。取自https://www.chinatimes.com/realtimenews/20190103001844-260410?chdtv
5.李長緯. (2018)。感知易用性、感知有用性、使用態度與行為意圖之研究-以街口支付為例。實踐大學企業管理學系碩士論文。
6.林孟璋. (2008)。消費者的綠色認知與生活型態對綠色消費行為影響之研究。2008第九屆管理學域學術研討會論文集。
7.林明瑞、林盛隆、胡康寧、顏冠忠. (2008)。就使用成本及環境的觀點進行電動機車與燃油機車之比較研究。中華民國環境保護學會學刊，31(1)。
8.林美秀. (2017)。以科技接受模式分析民眾對於多元化計程車服務搭乘意願之研究。中華大學運輸科技與物流管理學系碩士論文。
9.侯建章. (2012)。澎湖電動機車二氧化碳排放量之研究。島嶼觀光期刊，5(1)，70-83。
10.洪連成. (2010)。台灣機車產業發展與未來。生活科技教育月刊，43(3)，47-65。
11.科技新報. (2015年1月7日)。智慧電動機車與電池交換站體系並進，GOGORO 打造「平民特斯拉」。西元2015年1月7日。取自https://technews.tw/2015/01/07/GOGORO-smartscooter-is-tesla-for-the-everyman/
12.徐于婷. (2010)。認知風險、認知可信賴度、信任、認知易用性、認知有用性對線上拍賣消費者購買意圖之影響。國立成功大學企業管理系碩士論文。
13.張淑青. (2006)。顧客忠誠驅動因子之研究-顧客知覺價值的關鍵角色及顧客滿意與信任的中介影響。輔仁管理評論，13(1)，107-132。
14.梁世安、余國瑋. (2005)。以科技接受模式探討二輪式電動代步車消費者接受程度。行銷評論, 2(2), 135-148。
15.許致維. (2018)。台灣電動機車廠商之成長策略探討：以Gogoro為例。國立臺灣大學管理學院商學研究所碩士論文。
16.許貞. (2008)。以科技接受模式探討消費者在綠色環保意識下對油電混合車之使用態度及行為意圖。國立彰化師範大學行銷與流通管理研究所碩士論文。
17.郭柏成. (2010)。台灣電動機車的消費者購買行為之研究。國立成功大學經營管理碩士論文。
18.郭裕元. (2013)。以科技接受模式探討影響消費者使用智慧電動車意圖之要素。國立成功大學工學院管理碩士論文。
19. 陳宛宜. (2010)。消費者購買環保電動機車屬性偏好之研究。國立成功大學交通管理科學系碩士論文。
20. 陳珮琪. (2015)。知覺價格、品牌權益與促銷方案對消費者購買意願之影響-以智慧型手機為例。東吳大學國際經營與貿易學系碩士論文。
21.陳澤義. (2005)。科技管理：理論與應用。台灣：華泰文化事業股份有限公司。
22.華南投顧產業週報. (2018年1月8日)。產業週報-機車產業。西元2018年1月8日。取自https://events.entrust.com.tw/news/20190108weekly-432
23.黃上晏、邱城英、廖妙羚. (2015)。台灣消費者購買電動機車意願之關鍵成功因素研究。觀光與休閒管理期刊，3(1)，139-152。
24.黃紹軒. (2018)。以科技接受模式及知覺風險探討消費者對於有先進駕駛輔助系統車輛之購買意圖。國立臺北科技大學車輛工程研究所碩士論文。
25.鉅亨新聞網. (2019年1月2日)。〈車市〉2018 Gogoro銷量翻倍至7.2萬台 吃下電動機車近9成版圖。西元2019年1月2日。取自https://news.cnyes.com/news/id/4262592
26.廖恆漢. (2013)。台灣電動機車推廣政策研究。國立成功大學工學院工程管理碩士論文。
27.劉姿珊. (2011)。評估台灣消費者對導入電動車創新服務模式之接受意願－以台中地區為例。國立中興大學科技管理研究所碩士論文。
28. 數位時代新聞網. (2020年12月15日)。Gogoro怎麼了？銷售衰退50％背後，產品長不願面對的真相。西元2020年12月15日。取自https://www.bnext.com.tw/article/60518/gogoro-tesla-december-price
29.蔡宜珮. (2012)。解構時尚科技之神話-以Apple品牌為例。天主教輔仁大學大眾傳播學研究所碩士論文。
30.謝宜軒. (2016)。以科技接受模式與創新擴散理論探討UBER之使用意圖。國立勤益科技大學資訊管理系碩士論文。
1.Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: a replication. MIS quarterly, 16(2), 227-247.
2.Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Australasian Marketing Journal, 19(7), 223-229.
3.Bauer, R. A. (1960). Consumer Behavior as Risk Taking. In: Hancock, R.S., Ed., Dynamic Marketing for a Changing World, Proceedings of the 43rd. Conference of the American Marketing Association, 389-398.
4.Bei, L.-T., & Chiao, Y.-C. (2001). An Integrated Model for the Effects of Perceived Product, Perceived Service Quality, and Perceived Price Fairness on Consumer Satisfaction and Loyalty. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 14.
5.Bentler, P. M., & Lee, S.-Y. (1983). Covariance Structures Under Polynomial Constraints: Applications to Correlation and Alpha-Type Structural Models. Journal of Educational Statistics, 8(3), 207-222.
6.CDIAC Data Transition. https://cdiac.ess-dive.lbl.gov/.
7.Chang, I., Hwang, H. G., Hung, M. C., Lin, M. H., & Yen, D. C. (2007). Factors affecting the adoption of electronic signature: Executives' perspective of hospital information department. Decision Support Systems, 44(1), 350-359.
8.Chen, C. F., & Chen, P. C. (2011). Applying the TAM to travelers’ usage intentions of GPS devices. Expert Systems with Applications, 38(5), 6217-6221.
9.Chen, J. V., Yen, D. C., & Chen, K. (2009). The acceptance and diffusion of the innovative smart phone use: A case study of a delivery service company in logistics. Information & Management, 46(4), 241-248.
10.Cheung, G. W., & Rensvold, R. B. (2002). Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance. Structural Equation Modelling, 9, 233-255.
11.Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63, 160-175.
12.Cronin, J. J., & Taylor, S. A. (1992). Measuring Service Quality: A Reexamination and Extension. Journal of Marketing, 56(3), 55-68.
13.David F. M., & Dowling, G. R. (1978). Innovativeness: The Concept and Its Measurement. Journal of Consumer Research, 4(4), 229-242.
14.Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man machine studies.
15.Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly.
16.Depietro, R., Wiarda, E., & and Mitchell Fleischer. (1990). The Context for Change: OrganizationTechnology and Environment. The processes of technological innovation, 151-175.
17.Elkington, J., & Hailes, J. (1989). The Green Consumer Guide.
18.Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research.
19.Folkes, V. S. (1988). Recent Attribution Research in Consumer Behavior: A Review and New Directions. Journal of Consumer Research, 14(4), 548-565.
20.Fornell, C., & Larcker, D. F. (1981). Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. Journal of Marketing Research, 18, 382-388.
21.Guieford. (1965). Fundamental Statistics in Psychology and Education. New York: McGraw-Hill.
22.Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571.
23.Hoffer, T. B. (1992). Middle School Ability Grouping and Student Achievement in Science and Mathematics. Educational Evaluation and Policy Analysis, 14(3), 205-227.
24.Huang, Z., Janz, B. D., & Frolick, M. N. (2008). A comprehensive examination of Internet EDI adoption. Information Systems Management, 25(3), 273-286.
25.Isabella, L. A., & Waddock, S. A. (1994). Top Management Team Certainty: Environmental Assessments, Teamwork, and Performance Implications. Journal of Management, 20(4), 835-858.
26.Joo, J., & Sang, Y. (2013). Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Computers in Human Behavior, 29(6), 2512-2518.
27.Kotler, P. (1999). Marketing Management: Analysis, Planning, Implementation and Control. 9th Edition. Prentice Hall College Inc.
28.Limayem, M., Khalifa, M., & Frini, A. (2000). What makes consumers buy from Internet? A longitudinal study of online shopping. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 30, 421-432.
29.Lin, H. F. (2014). Understanding the determinants of electronic supply chain management system adoption: Using the technology–organization–environment framework. Technological Forecasting and Social Change, 86, 80-92.
30.Lin, J., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a web site. International journal of information management, 20(3), 197-208.
31.Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial management & data systems, 111(7), 1006-1023.
32.McDonald, R. P., & Ho, M. R. (2002). Principles and practice in reporting structural equation analysis. . Psychological Methods, 7, 64-82.
33.McKnight, D., Choudhury, V., & Kacmar, C. (2002). The Impact of Initial Consumer Trust on Intentions to Transact with a Web Site: A Trust Building Model. The Journal of Strategic Information Systems, 11, 297-323.
34.Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217-230.
35.Nunnally, J. C. (1978). Psychometric theory. McGraw-Hill.
36.Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17, 460-469.
37.Olsen, J. P. (2002). The Many Faces of Europeanization. JCMS: Journal of Common Market Studies, 40(5), 921-952.
38.Persico, D., Manca, S., & Pozzi, F. (2014). Adapting the Technology Acceptance Model to evaluate the innovative potential of e-learning systems. Computers in Human Behavior, 30, 614-622.
39.Read, W., Robertson, N., & McQuilken, L. (2011). A novel romance: The Technology Acceptance Model with emotional attachment. Australasian Marketing Journal (AMJ), 19(4), 223-229.
40.Rogers, E. M. (1995). DIFFUSION OF INNOVATIONS Attributes of Innovations and Their Rate of Adoption, 205-251.
41.Seymour, R. S., GIBERNAU, M., & PIRINTSOS, S. A. (2009). Thermogenesis of three species of Arum from Crete. Plant, Cell & Environment, 32(10), 1467-1476.
42.Tarhini, A., Hone, K., & Liu, X. (2013). User Acceptance Towards Web-based Learning Systems: Investigating the Role of Social, Organizational and Individual Factors in European Higher Education. Procedia Computer Science, 17, 189-197.
43.Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of Competing Models. Information systems research, 6(2), 144-176.
44.Tornatzky, L. G., & and Fleischer, M. (1990). The Process of Technological Innovation. Lexington. Mass.: Lexington Books.
45.Tushman, M., & Nadler, D. (1992). Designing Organizations that Have Good Fit: A Framework for Understanding New Architectures. In Organization Architecture.
46.Valarie, A. Z., Leonard L. B., & Parasuraman A. (1996). The Behavioral Consequences of Service Quality. Journal of Marketing , 60(2), 31-46.
47.Varki, S., & Colgate, M. (2001). The Role of Price Perceptions in an Integrated Model of Behavioral Intentions. Journal of Service Research, 3(3), 232-240.
48.Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342-365.
49.Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
50.Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management science, 46(2), 186-204.
51.Vijayasarathy, L. R. (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747-762.
52.Xu, S., Zhu, K., & Gibbs, J. (2004). Global Technology, Local Adoption: A Cross‐Country Investigation of Internet Adoption by Companies in the United States and China. Electronic Markets, 14(1), 13-24.
53.Zeithaml, V. (1988). Consumer Perceptions of Price, Quality and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52, 2-22.