高雄輕軌捷運系統是臺灣第一個輕軌捷運系統，將於2015年通車，同時兼顧觀光旅運與日常生活運輸功能，為了瞭解高雄輕軌捷運系統通車後觀光旅客與在地居民的運具選擇情形，本研究將對高雄輕軌捷運系統之誘發需求利用Hybrid選擇模式進行探討及推估，並將遊憩專門化、科技接受模型、計劃行為理論中各個構面作為潛在變數進行分析，同時加入了負面忍受與輕軌認同兩個潛在變數。透過模式的推估，得到未來運具比例，再推估誘發需求之可能性。若能掌握誘發需求，可協助決策未來購買車輛與增建設施，使資源投入與利用更有效率。
分析結果Hybrid選擇模式較一般個體選擇模式表現更佳，在運具偏好分析上可以透過潛在變數解釋個人品味的異質性，選擇機率方面觀光旅客將有59.81%選擇輕軌，而整體配適度觀光旅客為0.38，在地居民將有23.35%選擇輕軌，其配適度為0.26，都較多項羅吉特模式改善許多。
而誘發需求部分利用對數線性迴歸模式對2021年觀光旅客成長率與人口成長率進行推估，得到觀光旅客成長率成長率為8.78%，人口成長率為0.51%；而以Hybrid選擇模式誘發傾向因子進行彈性分析，得到未來輕軌通車後，觀光旅客與在地居民分別可能增加2.72%、10.75%之選擇機率，為本研究初步的誘發需求數量推估結果。
利用Hybrid選擇模式在兩種客群進行運具選擇與誘發需求的推估，其運具選擇之比例、誘發需求之數量與潛在變數的偏好都可提供作為政府機關、營運業者在營運、行銷與決策之參考。

Demand forecasting is an important issue due to the higher cost and techniques in the railway transportation system, but the demand may be underestimated due to neglect the induced demand. Induced demand can be defined in terms of additional trips that would be made from the improvement of system or travel conditions. The catchment of induced demand may help operators to make the strategic decisions more efficient for examples with purchasing or building new passenger carriages and facilities. This study is aim at build mode choice and induced demand model for Kaohsiung light rail transit.
We utilized the discrete choice model which incorporating the latent variable including techniques acceptance, planned behaviors and recreation specialization as Hybrid Discrete Choice Model （HDCM） to model the mode choice with both tourists and commuters with sample size 369 and 362. The result of the choice probability about LRT is 57.75% in tourists and 23.35% in commuters, and the model fit in adjusted Rho square is 0.38 and 0.26.
In the induced demand model, we adopted the log-linear regression to estimate the induced demand with tourists growth and demography growth data. The model estimate the induced demand for tourism and citizen is 8.78% and 0.51%. We also estimated the elasticity with the intention of induced demand and light rail choice probability with 2.72% in tourists and 10.75% in commuters. The result of induced demand estimation and strategic implications will be presented and discussed.

中文部分
王盈惠（2007）臺灣高速鐵路營運後對城際間運能量影響之研究，逢甲大學交通工程與管理研究所碩士論文。
交通部公路總局高雄市區監理所（2014）高雄市汽機車統計月報。
交通部運輸研究所（2011）交通建設計畫評估手冊。
交通部觀光局（2012）國人旅遊狀況調查。
行政院經濟建設委員會（2012）中華民國2012至2060年人口推計報告。
吳欣憲（2009）北宜高通車對宜蘭地區旅客遊憩行為規劃之影響研究，國立成功大學都市計劃研究所碩士論文。
李芳穎（2012）台北創意城市構念之研究，國立台北教育大學文化創意產業經營學系碩士論文。
周瑀清（2003），考慮潛在變數之國道客運選擇模式，國立成功大學交通管理科學研究所碩士論文。
林韋丞（2012），觀光地區遊客運具之選擇偏好－以臺灣好行日月潭線為例，國立交通大學交通運輸研究所碩士論文。
林韻如（2011），消費者之電動汽車購買偏好-潛在變數選擇模式之應用，國立成功大學交通管理科學研究所碩士論文。
施鴻志、段良雄、凌瑞賢（1984）都市交通計劃理論與實務，臺北市：茂昌圖書有限公司。
紀雲曜、李上妤、葉光毅（2004）公共設施最適服務/影響距離之評估模式，建築與規劃學報，5（2），頁150-177。
凌瑞賢（2004）運輸規劃原理與實務，臺北市：鼎漢工程顧問公司。
財團法人成大研究發展基金會（2012）高雄環狀輕軌捷運系統經營模式之研究，期末報告（未出版）。
高雄市政府（2014）訂定高雄市都市計畫（前鎮及苓雅部分地區）機關用地（配合高雄市立圖書館總館及其附屬會展文創會館設置）土地使用管制案計畫書。
高雄市政府民政局（2014）高雄市政府戶籍人口統計月報。
高雄市政府交通局（2009）高雄都會區家戶旅次訪問調查與旅次特性分析報告。
高雄市政府捷運工程局（2012）高雄都會區輕軌捷運系統高雄環狀輕軌捷運建設修正計畫書。
高雄市政府觀光局（2014）觀光遊客數量統計月報、年報。
高雄捷運股份有限公司（2014）高雄捷運營運運量統計日報。
張學孔（1999）高速鐵路運量模式之檢核與發展，行政院國家科學委員會專題研究計畫成果報告。
陳佩君（2013）自行車騎士自行車道選擇行為偏好異質性之研究，國立成功大學交通管理科學研究所博士論文。
陶治中、林孟潔（2014）城市景觀意象導向之輕軌車輛外型設計方案評選研究-以淡海輕軌為例，運輸計畫季刊，43（1），頁33-62。
楊孝博（2011）鐵路車站旅客運輸需求之實證性研究：地理加權迴歸之應用，國立台灣大學地理環境資源研究所碩士論文。
鼎漢工程國際工程顧問股份有限公司（2013）高雄都會區家戶旅次特性及屏柵線與周界交通量調查及分析期末報告。
諸連才（2005）軌道交通規劃中誘增交通量的若干問題，城市軌道交通研究，8（4），頁18-20。
鄭永祥、郭蕙瑜（2010）探討兩種不可儲存服務商品結合之旅客選擇行為，以高鐵與飯店服務為例，運輸計畫季刊，39（4），頁381-412。
賴思豪（2010）以整合選擇及潛在變數方法模化高速公路電子自動收費系統之選擇行為，國立交通大學交通運輸研究所碩士論文。
 
英文部分
Anja, H. and Astrid D.,（2013）, “Environmentally friendly holiday transport mode choices among students: the role of price, time and convenience,” Journal of Sustainable Tourism, 21（4）, pp. 596-613.
Aoife, A. A. and Nigel, T.（2008）, “The use of stated preference techniques to model modal choices on interurban trips in Ireland,” Transportation Research Part-A, 42, pp. 15–27.
Barros, G. （2012）, ”Transportation choice and tourist’s behaviour”, Tourism Economics, 18（3）, pp. 519-531.
Bekhor, S. and Albert, G. （2014） “Accountng for sensation seeking in route choice behavior with travel time information.” Transportation Research Part-F, 22, pp.39-49.
Ben-Akiva, M. and Lerman, S.（1985）, “Discrete Choice Analysis-Theory and Application to Travel Demand,” Cambridge: The MIT press.
Ben-Akiva, M., Cascetta, E., Coppola, P., Papola, A. and Velardi, V.（2010）, “High speed rail demand forecasting: Italian case study,” Proceedings of WCTR Conference, Lisbon.
Ben-Akiva, M., Mcfadden, D., Garling, T., Gopinath, D. Walker, J., Bolduc, D., Borsch-Supan, A., Delquie, P., Larchev, O.,Morikawa, T. Polydoropoulou, A. and Rao, V.（1999）, “Extended framework for modeling choice behavior,” Marketing Letters. 10, PP. 187-203.
Ben-Akiva, M., Mcfadden, D., Train, K., Walker, J., Bhat, C., Bierlaire, M., Bolduc, D.,Boersch-Supan, A., Brownstone, D., Bunch, D. S., Daly, A., Palma, A. D., Gopinath, D., Karlstrom, A., Munizaga, M. A.（2002） “Hybrid choice models: progress and challenges.” Marketing Letters. 13（3）, pp. 163-175.
Ben-Akiva, M., Morikawa, T.（1990）, “Estimation of switching models from revealed preferences and stated intentions”, Transportation Research Part-A, 24, pp.485 - 495.
Bhat, C. R. （1998）, “Accommodating variations in responsiveness to level-of-service measures in travel mode choice modeling.” Transportation Research Part-A, 32（7）, pp.495-507.
Bhattacharjee and Goetz, （2012）, “Impact of light rail on traffic congestion in Denver”, Journal of Transport Geography, 22, pp. 262-270.
Blainey, S.（2010）. “Trip end models of local rail demand in England and Wales” Journal of Transport Geography, 18（1）, 153-165.
Bo¨rjesson, M. （2008）, “Joint RP–SP data in a mixed logit analysis of trip timing decisions,” Transportation Research Part-E, 44, pp. 1025-1038.
Bolduc, D., Boucher, N. and Alvarez-Daziano, R. （2008）, “Hybrid choice modeling of new technologies for car choice in Canada.” Transportation Research Record, 2082, pp.63-71.
Boxall, C. and Adamowicz, W. （2002）,” Understanding heterogeneous preferences in random utility models: a latent class approach.” Environmental and Resource Economics, 23, pp.421-446.
Bryan, H. （1977） ”Leisure value system and recreational specialization: The case of trout fisherman. Journal of Leisure Research, 9（3）, pp. 174-187.
Can, V.（2013）, “Estimation of travel mode choice for domestic tourists to Nha Trang using the multinomial probit model”, Transportation Research Part-A, 49, pp. 149-159.
Cao and Schoner, （2014）, “The influence of light rail transit on transit use: An exploration of station area residents along the Hiawatha line in Minneapolis”, Transportation Research Part-A, 59, pp. 134-143.
Cevero, R. and Hansen, M.（2002）, “Induced travel demand and induced road investment,” Journal of Transport Economics and Policy, 36（3）, pp.469-490.
Cevero, R.（2002）, “Induced travel demand: research design, empirical evidence, and normative policies,” Journal of Planning Literature, 17（1）, pp. 3-20.
Charles, P.（1986）, “Induced demand-Can we ever know its extent?” Journal of Health Economics, 5, pp. 355-365.
Chen, C. D., Fan, Y. W. and Fam, C. K. （2007）, “Predicting electronic toll collection service adoption: an integration of the technology acceptance model and the theory of planned behavior.” Transportation Research Part-C, 15（5）, pp. 300-311.
Chen, C. and Cheng W.（2014）, “Sustainability SI: Exploring heterogeneity in cycle tourists’ preference for an integrated bike-ril transport choice.” Networks and Spatial Economics, (Article in press)
Chen, K., （2011）, “Combining linear and nonlinear model in forecasting tourism demand”, Expert System with Applications, 38（8）, pp. 10368 – 10378.
Chen, K., and Wang, C. （2007）, “Support vector regression with genetic algorithms in forecasting tourism demand”, Tourism Management, 28（1）, pp.215-226.
Cheng, Y. H.（2010）, “High-speed rail in Taiwan: New experience and issues for future development,” Transport Policy, 17, pp. 51-63.
Claveria, O. and Torra, S., （2014）, “Forecasting tourism demand to Catalonia: neural networks vs. time series models”, Economic Modelling, 36, pp. 220-228.
Coombe, D.（1996）, “Induced traffic: what do transportation models tell us?,” Transportation, 23, pp.83-101.
Daly, A., Hess, S., Patruni B., Potoglou D. and Rhor, C.（2012）, “Using ordered attitudinal indicators in a latent variable choice model: a study of impact of security on rail travel begavior.” Transportation. 39, pp. 267-297.
DellOlio, L., Ibeas, Angel, Dominguez, Alberto, Gonzalez and Felipe（2012）, “Passenger preference analysis: light rail transit or bus versus car.” Transport, 27（3）, pp. 276-285.
Dyck, C., Schneider, I., Thompson, M. and Virden, R. （2003）, “Specialization among mountaineers and its relationship to environmental attitudes.” Journal of Park and Recreation Administratiot, 21（2）, pp. 44-62.
Givoni, M.（2006）, “Development and impact of the modern high-speed train: a review”, Transport Reviews, 26（5）, pp. 593–611.
Goodwin, P.B.（1996）, “Empirical evidence on induced traffic,” Transportation, 23, pp.35-54.
Gorham, Roger（2009）, “Demystifying induced travel demand,” Technical Report of Ministry of Economic Cooperation and Development, Germany.
Greene, W. H. and Hensher, D. A. （2003）, “A latent class model for discrete choice analysis: contrasts with mixed logit.” Transportation Research Part-B, 37（8）, pp. 681-698.
Harris, K. M. and Keane, M. P.（1998）, “A model of health plan choice: Inferring preference and perceptions from a combination of reveal preference and attitudinal data,” Journal of Econometrics. 89, pp.131-157.
Hausman, J. and McFadden, D.（1984）, “A Specification Test for the Multinomial Logit Model”, Econometrica, 52, pp. 1219-1240.
Hensher D.A., Brotchie J. and Gunn H.F.（1989）, “A methodology for investigating the passenger demand high-speed rail,” Proceeding in 14th Australasian Transport Research Forum, Perth.
Hensher, D.A., Rose, J.M. and Greene, W.H.（2005）, “Applied Choice Analysis,” Cambridge University Press.
Hergesell, A. and Dickinger, A.（2013）, “Environmentallu friendly holiday transport mode choice among students: the role of price, time and convenience” Journal of Sustainable Tourism, 21(4), pp.596-613.
Hymel, K. M., Small, K. A. and Dender, K. V.（2010）, “Induced demand and rebound effects in road transport,” Transportation Research Part-B, 44, pp. 1220-1241.
Jamie, D.（2007）, “The challenges diverse visitor perceptions: rail policy and sustainable transport at the resort destination,” Journal of Transport Geography, 15（2）, pp. 104-115.
Johansson, Heldt and Johansson （2006）, “The effects of attitudes and personality traits on mode choice,” Transportation Research Part-A, 40, pp.507-525.
Jou, R.C., Hensher, D.A. and Hsu, T.L.（2011）, “Airport ground access mode choice behavior after the introduction of a new mode: A case study of Taoyuan International Airport in Taiwan”, Transportation Research Part-E, 47, pp. 371-381.
Keane, M. P.（1997）, “Modeling heterogeneity and stated dependence in consimer choice behavior,”Journal of Business and Economic Statistics 15（3）, pp 310-327.
Kim, S., Ulfarsson, G. F. and Hennessy, J. T. （2007）, “Analysis of light rail rider travel behavior: impacts of individual, built environment, and crime characteristics on transit access.” Transportation Research Part-A, 41, pp.511-522.
Kroes, E. P., and Sheldon, R. J. （1988）. “Stated preference method: An introduction.” Journal of Transportation Economics and Policy, 22（1）, pp.11-25.
Kuby, M., Barranda, A. and Upchurch, C.（2004）. Factors influencing light-rail station boardings in the United States. Transportation Research Part-A, 38（3）, 223-247.
Kuppam, A. R.,Pendyala, R. M.,Rahman, S.（2003）, “Analysis of the role of traveler attitude and perceptions in explaining mode-choice behavior.” Transportation Research Board, 1676, pp. 69-76.
Lai, W. T. and Chen, C. F. （2011）, “Behavioral intentions of public transit passengers – the role of service quality perceived value satisfaction and involvement.” Transportation Policy, 18, pp. 318-325.
LaMondia, J., Snell, T. and Bhat, C.（2010）, “Traveler behavior and value analysis in the context of vacation destination and travel mode choices: European union case study” Transportation Research Record, 2156, pp.140-149.
Lee and Senior, （2013）, “Do light rail services discourage car ownership and use? Evidence from Census data for four English cities”, Journal of Transport Geography, 29, pp. 11-23.
Lee, Jr. D.B., Klein, L.A. and Camus, G.（1999）, “Induced traffic and induced demand,” Transportation Research Record, 1659, pp.68-75.
Lieve C., Mario, C., Hans, T., Pieter-Jan, L., Davy, J. and Greet, W.（2012）, “Identifying the determinants of light rail model choice for medium- and long-distance trips: Results from a stated preference study,” Transportation Research Record, 2275, pp. 30-38.
Limtanakool, N., Dijst, M. and Schwanen, T. （2006）, “The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium- and longer-distance trips,” Journal of Transport Geography, 14, pp.327-341.
Litman, T.（2011）, “Generated traffic and induced travel, implications for transport planning,” Report for the Victoria Transport Institute. http://www.vtpi.org/gentraf.pdf
Luk, J. and Chung, E.（1997）, “Induced demand and road investment – an initial appraisal,” Research Report, ARR299. Vermount South, Australia: ARRB Transport Research.
Madanat, S. C., Yang, C. Y. and Yen, Y. M.（1995）, “Analysis of stated route diversion intention under advanced traveler information system using latent variable modeling,” Transportaion Research Record 1485, pp. 10-17.
Matthies, E., Kuhn, S. and Klöckner, C. A. （2002）, “Travel Mode Choice of Women: The Result of Limitation, Ecological Norm, or Weak Habit?,” Environment and Behavior, 34, pp.163-177.
McCathy, P.（2001）, Transportation Economics, Theory and Practice: A Case Study Approach, Oxford: The Blackwell publishing
McFadden, D. （1986）, “The choice theory approach to market research,” Marketing Science, 5（4）, pp. 275-297.
McIntyre, N. and Pigram, J. J. （1992） “Recreation specialization reexamined: The case of vehicle-based campers. Leisure Sciences, 14, pp. 3-15.
Melo, P.C., Garham, D. J. and Canavan, S.（2012）, “Effects of road investmemts on economic output and induced travel demand,” Transportation Research Record, 2297, pp.163-171.
Meyer, M. D. and Miller, E. J.（2001）, Urban Transportation Planning, New York: McGraw Hill.
Morikawa, T., Ben-Akiva, M. and Mcfadden, D.（2002） “Discrete choic models incorporating revealed preference and psychometric data.” Econometric Models in Marketing, 16, pp. 29-55.
Nass, P., Nicolaisen M. and Strand, A.（2012）, “Traffic forecasts ignoring induced demand: a shaky fundament for cost-benefit analysis,” European Journal of Transport and Infrastructure Research, 12（3）, pp.291-309.
Needham, M., Scott, D. and Vaske, J.（2013）, “Recreation specialization and related concepts in leisure research”, Leisure Science, 35, pp. 199-202.
Noland, R. and Lem, L.（2002）, “A review of the evidence for induced travel and changes in transportation and environmental policy in the US and the UK,” Transportation Research Part-D, 7, pp. 1-26.
Noland, R.（2001）, “Relationship between highway capacity and induced vehicle travel,” Transportation Research Part-A, 35, pp. 47-72.
Noland, R.（2007）, “Transport planning and environmental assessment: implications of induced travel effects,” International Journal of Sustainable Transportation, 1, pp. 1-28.
Ortuzar, J.de D. and Willumsen, L.G.（2011）, Modelling transport, West Sussex: Wiley.
Ortuzar, Juan de D. and Iacobelli, A. （1998）, “Mixed modelling of interurban trips by coach and train,” Transportation Research Part-E, 32（5）, pp.345-357.
Outwater, M.,Castleberry, S.,Shiftan, Y.,Ben-Akiva, M.,Zhou, Y. S.,Kuppam, A.（2003）, “Attitudinal market segmentation approach to mode choice and ridership forecasting: structural equation modeling.” Transportation Research Board, 1854, pp. 32-42.
Pagliara, F. and Preston, J.（2013）, “An induced demand model for high speed 1 in UK,” Journal of Transportation Technologies, 3, pp. 44-51.
Pearmain, D. and Swanson, J., （1991）, “Stated preference techniques: a guide to practice,” Street Davies Gleave.
Prato, C. G., Bekhor, S. and Pronello, C.（2011） “Latene variables and route choice behavior.” Transportation. 39（2）, pp. 299-319.
Raveau, S., Yanez, M.G. and Ortuzar, J. de D.（2012） “Practical and empirical identifiability of hybrid discrete choice models” Transportation Research Part-B, 46, pp.1374-1383.
Rouwendal, J. and Meijer, M.（2001）, “Preference for housing, jobs, and commuting: A mixed logit analysis,” Journal of Regional Science, 41（3）, pp. 475-505.
Rust, R., Lemon, K. and Zeithaml, V.（2004）, “Return on marketing: Using customer equity to focus marketing strategy,” Journal of Marketing, 68（1）, pp. 109-127.
Sakano, R. and Benjamin, J.（2011） “A structural model for mode-activity choice: The case of commuter rail in a medium-size metropolitian area.” Transport Policy, 18, pp.434-445
Sccott, D. and Shafer, C. S. （2001） “Recreation specialization: A critical look at the construct. Journal of Leisure Research, 33（3）, pp.319-343.
Scherer, M. （2010）, “Is light rail more attractive to users than bus transit? Arguments based on cognition and rational choice,” Transportation Research Record, 2144, pp.11-19.
Song , H. and Li, G., （2008）, ”Tourism demand modelling and forecasting—A review of recent research”, Tourism Management, 29（2）, pp.203-220.
Song, H., Witt, S. F. and Jensen, T. C. （2003）, “Tourism forecasting: accuracy of alternative econometric models”, International Journal of Forecasting, 19, pp. 123–141.
Song, H., Wong, K. and Chon, K., （2003）, “Modelling and forecasting the demand for Hong Kong tourism”, International Journal of Hospitality Management, 22（4）, pp.435-451.
Temme, D., Paulssen, M. and Dannewald, T.（2008）, “Incorporating latent variables into discrete choice model-A simultaneous sdtimation approach using SEM software.” BuR – Business Research 1（2）, pp. 220-237.
Tobler, W. （1970）, ”A computer movie simulating urban growth in the Detroit region” Economic Geography, 46（2）, pp. 234-240.
Townsend, C. and Zacharias, J.（2010）, “Built environment and pedestrian behavior at rail rapid transit stations in Bangkok,” Transportation, 37（2）, pp. 317-330.
Train, K. E. （2009） “Discrete Choice Method with Simulation,” Cambridge University Press
Verplanken, B. , Aarts, H.,Van Knippenberg, A.（1997）, “Habit, information acquisition, and the process of making travel mode choices.” European Journal of Social Psychology, 27, pp. 539-560.
Vij, A., Carrel, A. and Walker, J. L. （2013） “Incorprating the influence of latent modal preferences on travel mode choice behavior” Transportation Research Part-A, 54, pp.164-178.
Waight, C and Bath, A.（2014）, “Recreation specialization among ATV users and its relationgship to environmental attitudes and management preference on the island of newfoundland”, Leisure Science, 36, pp. 161-182.
Wang, Y., Kockelman, K. and Wang, X. （2011）, “Anticipation of land use change through use of geographically weighted regression models for discrete response” Transportation Research Record, 2245, pp.111-123.
Weis, C. and Axhausen, K. W.（2009）, “Induced travel demand: evidence from a pseudo panel data based structural equation model.” Research in Transportation Economics, 25, pp. 8-18.
Wen, C. H. and Lai, S. C. （2010）, “Latent class models of international air carrier choice.” Transportation Research Part-E, 46（2）, pp. 211-221.
Wen, C. H., Wang, W. C. and Fu, C. （2012）,” Latent class nested logit model for analyzing high-speed rail access mode choice.” Transportation Research Part-E, 48（2）, pp. 545-554.
Williams, H.C.W.L. and Moore, L.A.R.（1990）, “The appraisal of highway investments under fixed and variable demand,” Journal of Transport Economics and Policy, 24, pp.61-81.
Wu, L., Zhang, J. and Fujiware, A. （2012）, “Dynamic analysis of Japanese tourists’ three stage choices: tourism participation, destination choice and travel mode choice”, Transportation Research Record, 2322, pp.91-101.
Yang, Z.（2003）, “Intelligent tourist bus system and its effects on modal split between tourist spots,” Eastern Asia Society for Transportation Studies, 4, pp. 150-159.
Yao E. and Morikawa T.（2003）, “The induced travel analysis for a non-existing intercity high speed rail system with accessibility measure approach.” Journal of Eastern Asia Society for Transportation Studies, 5, pp. 1502-1517.
Yao E. and Morikawa T.（2005）, “A study of an integrated intercity travel demand model,” Transportation Research Part-A, 39, pp. 367-381.
Zhao, S. and He, N.（2011）, “Elasticity-based model applies in forecasting of highway induced traffic,” Journal of Transportation System Engineering and Information Techonology, 11（3）, pp. 1-7.