近年來共享運具蓬勃發展，越來越多的城市引進各式共享運具，原引進共享運具之目的應為減少私人運具的持有以達到減碳、降低城市交通壅塞及降低能源消耗等目標，然而實際上共享運具卻可能是對大眾運輸產業造成影響，而非替代掉私有運具。臺灣目前在共享電動機車的市場中為全球第三名，投放的密集程度非常高，帶來便利性的同時可能會對原先就岌岌可危的公車運量造成更大的威脅。關於共享電動機車的相關研究中較少深入研究與其他運具間之關係。本研究使用敘述性偏好法調查了854位民眾在共享電動機車與公車間的長短途旅次運具偏好選擇，並利用個體選擇模式中的多項羅吉特分析民眾的運具服務屬性偏好，而為探討個人異質性中的潛在心理因素對選擇行為帶來的影響，本研究建立結合選擇模型與潛在心理變數的ICLV模型，將潛在心理變數加入選擇模型進行分析，探討在不同的旅次長度下，共享電動機車與公車間是否存在競爭關係。
研究結果顯示，旅行時間與旅行成本皆會顯著影響運具選擇。當運具費用越高時，會降低民眾使用公車與共享電動機車的意願；當抵達至可用運具時間、等待時間、車內時間及抵達至目的地時間越高時，也同樣會降低民眾選擇公車與共享電動機車的效用，而當中車內時間是屬性變數中影響最大的，表示民眾對於在運具上的時間會較為敏感。而本研究所選擇的三項潛在變數中，在短途旅次裡自主性會對運具有顯著影響，享樂性則在長短途旅次裡皆會對運具選擇產生顯著正向影響，結果指出加入潛在變數的ICLV模型適配度會比基礎的MNL模型更佳，表示在衡量運具選擇方案時，除了考慮運具屬性變數及人口統計變數外，也需考量個人潛在心理變數，才會更貼近受訪者的選擇行為。最後，研究結果顯示在短途旅次中較容易發生共享電動機車與公車的競爭情況，政府與業者須共同配合，讓共享電動機車在短途旅次中成為補足大眾運輸”第一哩路與最後一哩路”的最佳選項，而不是變成大眾運輸的競爭對象。

In recent years, shared mobility has thrived. While bringing convenience, Electric Scooter Sharing Service may pose a more significant threat to the bus industry. Few studies have explored the relationship between Electric Scooter Sharing and Public Transport. This study uses the stated preference method to conduct a survey on the mobility preferences of 854 people for long and short trip distances in Electric Scooter Sharing and public transport schemes. Establishing an ICLV model that combines choice models and latent variables and exploring a coopetition relationship between Electric Scooter Sharing and public transport under different trip lengths.
The results show that both travel time and travel cost significantly affect the mode choice. Moving time is the most influential attribute, indicating that people are more sensitive to the time on the vehicle. Among the three latent variables selected in this study, Independence has a negative and statistically significant impact on bus choice in short-distance trips, and hedonism has a significant positive impact on mobility in long-distance and short-distance trips. The results also show that the ICLV model with latent variables is better than the basic MNL model. Finally, the study shows that the competition between Electric Scooter Sharing and buses is more likely to occur on the short-distance trip. The government and the industry must work together to make Electric Scooter Sharing complement public transport in short-distance trips.

交通部，「民眾日常使用運具狀況調查」民109年。
運研所，「區域整體運輸規劃系列研究-旅次特性分析」民109年。
Abouelela, M., Al Haddad, C., & Antoniou, C. (2021). Are young users willing to shift from carsharing to scooter–sharing? Transportation Research Part D: Transport and Environment, 95, 102821.
Aguilera-García, Á., Gomez, J., & Sobrino, N. (2020). Exploring the adoption of moped scooter-sharing systems in Spanish urban areas. Cities, 96, 102424.
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.
Bardhi, F., & Eckhardt, G. M. (2012). Access-based consumption: The case of car sharing. Journal of consumer research, 39(4), 881-898.
Ben-Akiva, M., 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., & Lerman, S. R. (1985). Discrete choice analysis: theory and application to travel demand (Vol. 9): MIT press.
Bieliński, T., Kwapisz, A., & Ważna, A. (2021). Electric bike-sharing services mode substitution for driving, public transit, and cycling. Transportation Research Part D: Transport and Environment, 96, 102883.
Bouscasse, H. (2018). Integrated choice and latent variable models: A literature review on mode choice.
Bullock, C., Brereton, F., & Bailey, S. (2017). The economic contribution of public bike-share to the sustainability and efficient functioning of cities. Sustainable cities and society, 28, 76-87.
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.
Campbell, K. B., & Brakewood, C. (2017). Sharing riders: How bikesharing impacts bus ridership in New York City. Transportation Research Part A: Policy and Practice, 100, 264-282.
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.
Ceccato, R., & Diana, M. (2018). Substitution and complementarity patterns between traditional transport means and car sharing: a person and trip level analysis. Transportation, 1-18.
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.
Faghih-Imani, A., & Eluru, N. (2015). Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system. Journal of Transport Geography, 44, 53-64.
Feigon, S., & Murphy, C. (2016). Shared mobility and the transformation of public transit.
Gebhardt, L., Wolf, C., & Seiffert, R. (2021). “I’ll Take the E-Scooter Instead of My Car”—The Potential of E-Scooters as a Substitute for Car Trips in Germany. Sustainability, 13(13), 7361.
Gu, T., Kim, I., & Currie, G. (2019). Measuring immediate impacts of a new mass transit system on an existing bike-share system in China. Transportation Research Part A: Policy and Practice, 124, 20-39.
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).
Herberz, M., Hahnel, U. J. J., & Brosch, T. (2020). The importance of consumer motives for green mobility: A multi-modal perspective. Transportation Research Part A: Policy and Practice, 139, 102-118.
Kamargianni, M., Dubey, S., Polydoropoulou, A., & Bhat, C. (2015). Investigating the subjective and objective factors influencing teenagers’ school travel mode choice–An integrated choice and latent variable model. Transportation Research Part A: Policy and Practice, 78, 473-488.
Kong, H., Jin, S. T., & Sui, D. Z. (2020). Deciphering the relationship between bikesharing and public transit: Modal substitution, integration, and complementation. Transportation Research Part D: Transport and Environment, 85, 102392.
Kopplin, C. S., Brand, B. M., & Reichenberger, Y. (2021). Consumer acceptance of shared e-scooters for urban and short-distance mobility. Transportation Research Part D: Transport and Environment, 91, 102680.
Lee, M., Chow, J. Y. J., Yoon, G., & He, B. Y. (2021). Forecasting e-scooter substitution of direct and access trips by mode and distance. Transportation Research Part D: Transport and Environment, 96, 102892.
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.
Luo, H., Zhang, Z., Gkritza, K., & Cai, H. (2021). Are shared electric scooters competing with buses? a case study in Indianapolis. Transportation Research Part D: Transport and Environment, 97, 102877.
McFadden, D., Machina, M. J., & Baron, J. (1999). Rationality for economists? In Elicitation of preferences (pp. 73-110): Springer.
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), 1803. Retrieved from
Papu Carrone, A., Hoening, V. M., Jensen, A. F., Mabit, S. E., & Rich, J. (2020). Understanding car sharing preferences and mode substitution patterns: A stated preference experiment. Transport Policy, 98, 139-147.
Paulssen, M., Temme, D., Vij, A., & Walker, J. L. (2014). Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice. Transportation, 41(4), 873-888.
Politis, I., Papaioannou, P., & Basbas, S. (2012). Integrated Choice and Latent Variable Models for evaluating Flexible Transport Mode choice. Research in Transportation Business & Management, 3, 24-38.
Rabin, M. (1998). Psychology and economics. Journal of economic literature, 36(1), 11-46.
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.
Rejali, S., Aghabayk, K., Mohammadi, A., & Shiwakoti, N. (2021). Assessing a priori acceptance of shared dockless e-scooters in Iran. Transportation Research Part D: Transport and Environment, 100, 103042.
Sarkar, P. P., & Mallikarjuna, C. (2018). Effect of perception and attitudinal variables on mode choice behavior: A case study of Indian city, Agartala. Travel Behaviour and Society, 12, 108-114.
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.
Shi, X., Li, Z., & Xia, E. (2021). The impact of ride-hailing and shared bikes on public transit: Moderating effect of the legitimacy. Research in Transportation Economics, 85, 100870.
Tang, J., Gao, F., Han, C., Cen, X., & Li, Z. (2021). Uncovering the spatially heterogeneous effects of shared mobility on public transit and taxi. Journal of Transport Geography, 95, 103134.
Tikoudis, I., Martinez, L., Farrow, K., Bouyssou, C. G., Petrik, O., & Oueslati, W. (2021). Exploring the impact of shared mobility services on CO2.
Walker, J. L. (2001). Extended discrete choice models: integrated framework, flexible error structures, and latent variables. Massachusetts Institute of Technology,