High Speed Rail Demand Adaptation and Travellers' Long- Title term Usage Patterns( Dissertation_全文 ) Author(s) Yeun-Touh, Li Citation 京都大学 Issue Date 2016-09-23 URL https://doi.org/10.14989/doctor.k19979 Right 許諾条件により本文は2017-04-01に公開 Type Thesis or Dissertation Textversion ETD Kyoto University High Speed Rail Demand Adaptation and Travellers’ Long-term Usage Patterns YEUN-TOUH LI i ii Acknowledgments The writing of this dissertation has been one of the most significant academic challenges I have ever had to face. A great many people have contributed to its production. Without their supports and guidance, this study would not have been completed. I would like to thank my sincere gratitude and deep regards to my supervisor, Associate Prof. Jan-Dirk Schmöcker, in Kyoto University for his patience, motivation, and immense knowledge. His guidance helped me in all the time of research and writing of this thesis. Besides my advisor, I would like to thank the rest of my thesis committee and co-supervisors: Prof. Satoshi Fujii in the Travel Behaviour Analysis Laboratory and Associate Prof. Nobuhiro Uno in the ITS group at Kyoto University, for their insightful comments and encouragements, but also for the hard question which inspired me to widen my research from various perspectives. Also my sincere thanks also goes to Assistant Prof. Toshiyuki Nakamura; Assistant Prof. Hiroki Yamazaki; Research Associate Dr. Prawira Fajarindra Belgiawan at Kyoto University; Associate Prof. Kuancheng Huang at National Chiao Tung University, Taiwan; Postdoctoral Associate Joel Teo at Singapore of MIT Alliance for research & Technology; Dr. Dong Zhang at Dalian University of Technology, China; who advised me at several stages. Without their precious support it would not be possible to conduct this research. Regards the assistance of administration process, I hope to give this opportunity to express a deep sense of gratitude to thanks to the secretaries, Mrs. Yuko Shii and Mrs. Yuko Ichihashi, their various help for living in Japan have made me concentrate on my research. Above all, I would like to thank members of ITS laboratory and all friends who have a great time and willing to share their thoughts and ideas with me in Japan. Last but not the least; I would like to thank my family: my parents and my parents-in-law, my sister, my lovely wife and my adorable daughter for supporting me spiritually throughout writing this thesis and my life in general. iii Abstract Adaptation of behavior is the process of adjusting one’s behavior to a change in the environment. In transportation, understanding adaptation towards a new public transportation mode is an important aspect for demand forecasting as well as to understand gradual changes in perception to the new travel mode. However, the timing of demand adaptation appears often difficult to predict. Initial demand might be low but only over a fairly long time period the demand might increase to somewhere near the predicted (user equilibrium) level. The aim of this dissertation is to understand the adaptation process of high speed rail (HSR) travellers. Especially Asian countries and regions have embraced HSR since the start of the 21st century. In Korea, China, and Taiwan, HSR began its operation and is significantly increasing these years. In Taiwan, the focus of most of this thesis, the HSR service opened in 2007 and cut the travel time from 4 hours to 1.5 hours for a journey from Taipei to Zuoying. This has greatly expanded overall accessibility throughout the whole Western coast region of Taiwan. In the first stage of this dissertation, the focus is on the HSR monthly aggregated demand in Taiwan. By controlling for economic and seasonal factors, this study aims to explain through econometric time series models the factors affecting ridership changes for the relatively new transportation scheme. The analysis is based on monthly ridership data from January 2007 to December 2013. The impact of THSR on competing modes such as air demand is also discussed. First, a seasonal autoregressive integrated moving average model was applied; showing that the ridership thrives and that the trend prediction fairly well performed if applied to data after 2012. Second, to specify the impact of explanatory variables, a first-order moving average model was fitted. Results show that ridership, population and fuel price have a positive effect, while unemployment and car ownership tend to reduce the THSR ridership. We include as a separate factor ‘months since operation start’, showing that this factor is significant. The methodology is then replicated to investigate the HSR local demand. In addition, the thesis assesses the impacts brought by access links for all HSR iv stations. Model results show that access links appear to be one stimulus for station demand. For suburban stations, the first-connected public transport connection has been observed to significantly impact travel demand. The result further suggests that access links are important, but operators should not overestimate the impact of such service improvements. This implies that possibly there exists a threshold accessibility in that general accessibility through public transport is important, but further improvements do not generate significant additional journeys in Taiwan. With aggregate data a more detailed understanding of how such demand adaptation takes place, is though not feasible. Therefore, the study is continued by proposing a new data collection methodology approach to understand the demand adaptation process with data from individuals. Moreover, this dissertation further expands the study area to the other side of Taiwan Strait, the HSR network in China, with a focus on Shanghai. HSR demand were dramatically growing since 2008. A web-based survey was conducted among HSR travellers. At the heart of the survey is the design of graphical usage patterns to describe individual’s HSR usage over several years. These 10 hypothetical graphical usage patterns were finalized after feedback from a pilot survey in both Taiwan and Shanghai were obtained. They are presented to respondents together with a textual description. Respondents are asked to select the abstract pattern that most fits to their actual long-term usage. Comparisons of actual usage frequency and usage patterns (recall frequency) suggest that the patterns fit the usage. The visualized usage pattern allows travellers to reconsider their longer-term travel behaviour (over several years) without concerning the accuracy issues of single answers. Moreover, a descriptive analysis is conducted of the usage pattern explaining the reasons of a) motivation to start HSR usage, b) reasons to increase HSR usage, c) reasons to continue, and d) reasons to drop/stop HSR usage. The analysis has proven that one can extract valuable factors that influence the HSR usage and partly explain the gradual changes in HSR usage over several years. To further explore the usefulness and limitations of the information obtained from the novel survey, a number of modelling approaches were adopted. Multi-nominal logit (MNL) regression results suggest that we can distinguish and partly explain the behavior of some user groups by attitudinal factors and v perceived perceptions. As alternative to the MNL results, and more in line with the assumption that “choices happen to people” we also test discriminant analysis with the same “explanatory variables” which in this context should be referred to as “predictor variables”. Discriminant analysis is to utilize a set of predictor variables to distinguish the factor of interest in this case the chosen pattern while utility maximization does not have to be assumed in MNL. The results obtain similar conclusions for both types of analysis. Though there are important differences in the estimation process, both models aim to show the explanatory power of the explanatory variables/predictors for the same dependent variable/factor. Moreover, the pattern specific discriminant analysis revealed strong evidence that the formation of long-term usage patterns involve self-planning, initial perceptions of the new mode, receiving further information about it over time and reflecting previous experiences. Therefore, the discussion on the reasons to change HSR usage provide an overview regarding these varies kinds of adaptation processes. Keywords: Travel Demand Forecasting, High Speed Rail, Usage pattern, Adaptation Effect vi Preface Parts of this thesis have been published in the following paper: I. Li, Y.-T., Schmöcker, J.-D., & Fujii, S. (2014). Demand Adaptation towards New Transport Modes: Case of High Speed Rail in Taiwan. 93th TRB Annual Meeting, Washington DC, USA. (Chapter 3) II. Li, Y.-T., & Schmöcker, J.-D. (2014). Demand Impact of Access Links to Taiwan High Speed Rail. Proceeding of the 19th International Conference of Hong Kong Society for Transportation Studies, 103-110. Hong Kong, China. (Chapter 4) III. Li, Y.-T., & Schmöcker, J.-D. (2015). Using Graphical Pattern to Model Adaptation Process of Long-term High Speed Rail Usage. The 14th International Conference on Travel Behaviour Research, Windsor, UK. (Chapter 5) IV. Li, Y.-T., & Schmöcker, J.-D. (2015). Explaining Adaptation Patterns to High Speed Rail Usage in Taiwan and China. 52nd Autumn Conference of Committee of Infrastructure Planning and Management, Akita, Japan. (Chapter 5 and 6) V. Li, Y.-T., Schmöcker, J.-D., & Fujii, S. (2015). Demand adaptation towards new transport modes: the case of high-speed rail in Taiwan. Transportmetrica B: Transport Dynamics, 3(1), 27-43. doi:10.1080/21680566.2014.946456 (Chapter 3 and 4) VI. Li, Y.-T., & Schmöcker, J.-D. (2016). Adaptation Patterns to High Speed Rail Usage in China and Taiwan. 95th TRB Annual Meeting, Washington DC, USA. (Chapter 5) VII. Li, Y.-T., Schmöcker, J.-D., Zhang, D. (2016). Adaptation process of travel behavior towards high speed rail: An initial analysis on usage patterns in Taiwan and Shanghai area. The 14th World Conference on Transport Research, Shanghai, China. (Chapter 5 and 6) VIII. Li, Y.-T., & Schmöcker, J.-D.