目前政府正致力於發展公共運輸以減少私人運具之使用，而為填補與大眾運輸系統相結合時，其第一和最後一哩路之服務，則出現了以共享經濟為概念的「共享電動機車服務」，目前對於共享電動機車服務的相關研究中，很少有研究透過系統中所包含之屬性和屬性中之變化來探討影響消費者是否採用該項系統的因素。本研究使用敘述性偏好法對732位民眾進行共享電動機車服務方案之選擇偏好調查。使用個體選擇模型之多項羅吉特模式來了解民眾對服務屬性偏好，並探討個人異質性之潛在心理因素對選擇偏好的影響，因此建立結合選擇模型與潛在變數的ICLV模式，即是將潛在心理變數加入至選擇模型中分析其選擇行為，以利相關業者作為調整其服務水準之參考。
研究結果顯示，第六分鐘後每分鐘之收費是屬性變數裡影響最大的，表示民眾對於後續每分鐘需付出之金額較敏感。當服務密度越高時，則會增加民眾選擇使用這項系統。當還車需多操作一個步驟時，會認為是件麻煩的事情，因此會降低其選擇效用。民眾較偏好於機車G品牌，可能因為他是新興的電動機車品牌。該項服務系統較吸引低年齡層的民眾關注。而本研究所選擇之三個潛在變數，分別為提倡共享電動機車服務、享樂性動機和態度皆正向且顯著影響服務選擇。結果亦指出有加入潛在變數的ICLV模式皆比沒有加入潛在變數的基本MNL模式更好，表示在衡量共享電動機車之服務方案選擇時，除了考量服務屬性變數和社會人口統計變數外，亦須考量個人潛在心理變數，如此才能更暸解消費者實際之選擇行為。

Few studies have explored the factors that influence whether people adopt Electric Scooter Sharing Service systems through the attributes contained in the system.This study uses the stated preference method to conduct a survey on the preferences of 732 people for the Electric Scooter Sharing Service scheme. Using multinomial logit model of the individual choice model to understand the public preference for service attributes, and to explore the influence of latent psychological factors of individual heterogeneity on choice preferences. Thus, establishing an ICLV model that combines choice models and latent variables.
The results show that people are more sensitive to the amount that needs to be paid every minute after paying the basic fee. When the service density is higher, it will increase people to use this system. When returning the e-scooter requires one more step, it will reduce people to use this system. People prefer brand G, a e-scooter brand, maybe it is a new electric scooter brand. The three latent variables are all positive and statistically significant impact on service choices.The results also show that the ICLV model with latent variables is better than the basic MNL model. It means that when evaluating the choice of Electric Scooter Sharing Service, not only considering its service attribute variables and socio-demographic variables but also considering the individual's latent psychological variables. In this way, we can better understand people actual choice behavior.

交通部. (2017). 能源轉型白皮書-運輸部門節能計畫. Retrieved from https://energywhitepaper.tw/upload/201801/151486565635105.pdf
財團法人車輛研究測試中心. (2015). 北高兩市支持，台灣有機會引進電動汽車共享營運模式. Retrieved from https://www.artc.org.tw/chinese/03_service/03_02detail.aspx?pid=2889
經濟部工業局. (2016). 產業結構優化推動計畫(4/5). Retrieved from https://library.tier.org.tw/webpac/bookDetail.do?id=36567
經濟部能源局. (2020). 2019年我國燃料燃燒二氧化碳排放統計與分析. Retrieved from https://www.moeaboe.gov.tw/ecw/populace/content/ContentDesc.aspx?menu_id=12036
Aaker, J. L. (1997). Dimensions of brand personality. Journal of marketing research, 34(3), 347-356.
Abate, T. G., Börger, T., Aanesen, M., Falk-Andersson, J., Wyles, K. J., & Beaumont, N. (2020). Valuation of marine plastic pollution in the European Arctic: Applying an integrated choice and latent variable model to contingent valuation. Ecological Economics, 169. doi:10.1016/j.ecolecon.2019.106521
Adnan, M., Altaf, S., Bellemans, T., Yasar, A.-u.-H., & Shakshuki, E. M. (2018). Last-mile travel and bicycle sharing system in small/medium sized cities: user’s preferences investigation using hybrid choice model. Journal of Ambient Intelligence and Humanized Computing, 10(12), 4721-4731. doi:10.1007/s12652-018-0849-5
Aguilera-García, Á., Gomez, J., & Sobrino, N. (2020). Exploring the adoption of moped scooter-sharing systems in Spanish urban areas. Cities, 96. doi:10.1016/j.cities.2019.102424
Al-Ayyash, Z., Abou-Zeid, M., & Kaysi, I. (2016). Modeling the demand for a shared-ride taxi service: An application to an organization-based context. Transport Policy, 48, 169-182. doi:10.1016/j.tranpol.2016.02.013
Alemi, F., Circella, G., Handy, S., & Mokhtarian, P. (2018). What influences travelers to use Uber? Exploring the factors affecting the adoption of on-demand ride services in California. Travel Behaviour and Society, 13, 88-104. doi:10.1016/j.tbs.2018.06.002
Almannaa, M. H., Ashqar, H. I., Elhenawy, M., Masoud, M., Rakotonirainy, A., & Rakha, H. (2020). A comparative analysis of e-scooter and e-bike usage patterns: Findings from the City of Austin, TX. International Journal of Sustainable Transportation, 1-9.
Bachand-Marleau, J., Lee, B. H. Y., & El-Geneidy, A. M. (2012). Better Understanding of Factors Influencing Likelihood of Using Shared Bicycle Systems and Frequency of Use. Transportation Research Record: Journal of the Transportation Research Board, 2314(1), 66-71. doi:10.3141/2314-09
Baek, K., Lee, H., Chung, J.-H., & Kim, J. (2021). Electric scooter sharing: How do people value it as a last-mile transportation mode? Transportation Research Part D: Transport and Environment, 90, 102642.
Beck, S., Barker, L., Chan, A., & Stanbridge, S. (2020). Emergency department impact following the introduction of an electric scooter sharing service. Emergency Medicine Australasia, 32(3), 409-415.
Ben-Akiva, Walker, J., Bernardino, A. T., Gopinath, D. A., Morikawa, T., & Polydoropoulou, A. (2002). Integration of choice and latent variable models. Perpetual motion: Travel behaviour research opportunities and application challenges, 431-470.
Ben-Akiva, M. E., & Lerman, S. R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. Cambridge, Ma: MIT Press.
Bieliński, T., & Ważna, A. (2020). Electric Scooter Sharing and Bike Sharing User Behaviour and Characteristics. Sustainability, 12(22), 9640.
Campbell, A. A., Cherry, C. R., Ryerson, M. S., & Yang, X. (2016). Factors influencing the choice of shared bicycles and shared electric bikes in Beijing. Transportation Research Part C: Emerging Technologies, 67, 399-414. doi:10.1016/j.trc.2016.03.004
Cao, Z., Zhang, X., Chua, K., Yu, H., & Zhao, J. (2021). E-scooter sharing to serve short-distance transit trips: A Singapore case. Transportation Research Part A: Policy and Practice, 147, 177-196.
Caspi, O., Smart, M. J., & Noland, R. B. (2020). Spatial associations of dockless shared e-scooter usage. Transportation Research Part D: Transport and Environment, 86, 102396.
Chen, C.-F. (2019). Factors affecting the decision to use autonomous shuttle services: Evidence from a scooter-dominant urban context. Transportation Research Part F: Traffic Psychology and Behaviour, 67, 195-204.
Chia-Jung, C., & Pei-Chun, C. (2014). Preferences and willingness to pay for green hotel attributes in tourist choice behavior: The case of Taiwan. Journal of Travel & Tourism Marketing, 31(8), 937-957.
Degele, J., Gorr, A., Haas, K., Kormann, D., Krauss, S., Lipinski, P., . . . Hertweck, D. (2018). Identifying E-scooter sharing customer segments using clustering. Paper presented at the 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC).
Eccarius, T., & Lu, C.-C. (2020). Adoption intentions for micro-mobility–Insights from electric scooter sharing in Taiwan. Transportation Research Part D: Transport and Environment, 84, 102327.
Efthymiou, D., Antoniou, C., & Waddell, P. (2013). Factors affecting the adoption of vehicle sharing systems by young drivers. Transport Policy, 29, 64-73.
Fishman, E., Washington, S., Haworth, N., & Watson, A. (2015). Factors influencing bike share membership: An analysis of Melbourne and Brisbane. Transportation Research Part A: Policy and Practice, 71, 17-30. doi:10.1016/j.tra.2014.10.021
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
GOSURVEY. (2020). 共享機車使用行為解析. Retrieved from https://www.gosurvey.com.tw/web/insight/insight.jsp?sdmid=DM1583144551110
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis: Pearson new international edition. Essex: Pearson Education Limited, 1, 2.
Hardt, C., & Bogenberger, K. (2019). Usage of e-scooters in urban environments. Transportation research procedia, 37, 155-162.
Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: emerging concepts, methods and propositions. Journal of marketing, 46(3), 92-101.
Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fantasies, feelings, and fun. Journal of consumer research, 9(2), 132-140.
Hollingsworth, J., Copeland, B., & Johnson, J. X. (2019). Are e-scooters polluters? The environmental impacts of shared dockless electric scooters. Environmental Research Letters, 14(8), 084031.
Howe, E., & Bock, B. (2018). Global scootersharing market report 2018. InnoZ-Innovation Centre for Mobility and Societal Change (InnoZ) GmbH: Berlin, Germany.
Jiao, J., & Bai, S. (2020). Understanding the shared e-scooter travels in Austin, TX. ISPRS International Journal of Geo-Information, 9(2), 135.
Jöreskog, K. G., & Goldberger, A. S. (1975). Estimation of a model with multiple indicators and multiple causes of a single latent variable. journal of the American Statistical Association, 70(351a), 631-639.
Kafyeke, T. (2017). Sharing is caring: The rise of electric scooters. Reset. Retrieved from https://en.reset.org/blog/sharing-caring-rise-electric-scooters-03032017.
Kim, J., Rasouli, S., & Timmermans, H. J. P. (2017). The effects of activity-travel context and individual attitudes on car-sharing decisions under travel time uncertainty: A hybrid choice modeling approach. Transportation Research Part D: Transport and Environment, 56, 189-202. doi:10.1016/j.trd.2017.07.022
Krueger, R., Rashidi, T. H., & Rose, J. M. (2016). Preferences for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies, 69, 343-355. doi:10.1016/j.trc.2016.06.015
Laa, B., & Leth, U. (2020). Survey of E-scooter users in Vienna: Who they are and how they ride. Journal of transport geography, 89, 102874.
Lee, H., Baek, K., Chung, J.-H., & Kim, J. (2021). Factors affecting heterogeneity in willingness to use e-scooter sharing services. Transportation Research Part D: Transport and Environment, 92, 102751.
Li, J., Jia, S., Zhang, S., & Wang, Y. (2019). Modeling and Analysis of Ticketing Channel Choice for Intercity Bus Passengers: A Case Study in Beijing, China. Journal of Advanced Transportation, 2019, 1-14. doi:10.1155/2019/8198346
Li, W., & Kamargianni, M. (2020). An integrated choice and latent variable model to explore the influence of attitudinal and perceptual factors on shared mobility choices and their value of time estimation. Transportation Science, 54(1), 62-83.
Liao, F., Molin, E., Timmermans, H., & van Wee, B. (2018). Carsharing: the impact of system characteristics on its potential to replace private car trips and reduce car ownership. Transportation, 47(2), 935-970. doi:10.1007/s11116-018-9929-9
Madigan, R., Louw, T., Wilbrink, M., Schieben, A., & Merat, N. (2017). What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems. Transportation Research Part F: Traffic Psychology and Behaviour, 50, 55-64. doi:10.1016/j.trf.2017.07.007
Mao, B., Ao, C., Cheng, Y., Jiang, N., & Xu, L. (2020). Exploring the role of public risk perceptions on preferences for air quality improvement policies: An integrated choice and latent variable approach. Journal of Cleaner Production, 269. doi:10.1016/j.jclepro.2020.122379
McFadden. (1997). The Theory and practise of disaggregate demand forecasting for various modes of urban transportation. Transport economics: selected readings. TH Oum, JS Dodgson, DA Hensheret al. In: Amsterdam, Harwood Academic Publishers.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
Moreau, H., de Jamblinne de Meux, L., Zeller, V., D’Ans, P., Ruwet, C., & Achten, W. M. J. (2020). Dockless E-Scooter: A Green Solution for Mobility? Comparative Case Study between Dockless E-Scooters, Displaced Transport, and Personal E-Scooters. Sustainability, 12(5). doi:10.3390/su12051803
Pearmain, D., & Kroes, E. P. (1990). Stated preference techniques: a guide to practice.
Ratan, R., Earle, K., Rosenthal, S., Chen, V. H. H., Gambino, A., Goggin, G., . . . Lee, K. M. (2021). The (digital) medium of mobility is the message: Examining the influence of e-scooter mobile app perceptions on e-scooter use intent. Computers in Human Behavior Reports, 3, 100076.
Raveau, S., Álvarez-Daziano, R., Yáñez, M. F., Bolduc, D., & de Dios Ortúzar, J. (2010). Sequential and simultaneous estimation of hybrid discrete choice models: some new findings. Transportation Research Record, 2156(1), 131-139.
Reck, D. J., & Axhausen, K. W. (2021). Who uses shared micro-mobility services? Empirical evidence from Zurich, Switzerland. Transportation Research Part D: Transport and Environment, 94, 102803.
Ryan, M., & Wordsworth, S. (2000). Sensitivity of willingness to pay estimates to the level of attributes in discrete choice experiments. Scottish Journal of Political Economy, 47(5), 504-524.
Shaheen, S., & Chan, N. (2016). Mobility and the sharing economy: Potential to facilitate the first-and last-mile public transit connections. Built Environment, 42(4), 573-588.
Shen, Y., Zhang, X., & Zhao, J. (2018). Understanding the usage of dockless bike sharing in Singapore. International Journal of Sustainable Transportation, 12(9), 686-700.
Walker, J. L. (2001). Extended Discrete Choice Models: Integrated Framework, Flexible Error Structures, and Latent Variables. Unpublished Doctoral Dissertation. Massachusetts Institute of Technology.