Demand Forecasting of the Bike-sharing Service in Beijing

In response to increasing urbanization, China seeks alternative public transportation methods, such as bikesharing, which has demonstrated social and environmental benefits. As a result, the number of bike-sharing programs has grown rapidly over the last five years in China. Our sponsoring company TalkingData collects bike-sharing usage data via smartphones and aims to provide insights to bike-sharing operators. Therefore, our main objective in this project is to analyze smartphone data to understand the bike-sharing demand in Beijing. We conducted interviews with bike-sharing stakeholders and investigated a one-month sample of data that TalkingData collected from bike-sharing operators in Beijing merging it with secondary data from online resources. We found that the level of bike-sharing activity varies across the city Beijing both in terms of location and time throughout the day. We discovered that both, time and environmental related factors significantly affect the bike-sharing demand. In contrast, our study revealed that some factors stated in literature such as pollution level do not affect bike-sharing demand in Beijing significantly. Hence, we suggest that drivers of bike-sharing demand differ across cities or countries making it worthwhile to perform location specific analysis. We fitted linear regressions, neural networks and random forests on the compiled dataset and compared their respective performance. We found that, based on the one-month sample, linear regression performs best amongst the three models in predicting hourly bike-sharing demand in Beijing. Capstone Advisor: Dr. Inma Borrella Postdoctoral Associate at MIT Center for Transportation and Logistics III Acknowledgements We would like to thank our advisor, Dr. Inma Borrella, for her supervision in this capstone project and generous support throughout the whole research process with enthusiasm, encouragement, sound advice good teaching, and lots of good ideas. We would like to thank our sponsor company, TalkingData, for their support, trust, and invaluable guidance throughout this project. Lastly, we would like to thank the Center for Transportation and Logistics of the Massachusetts Institute of Technology to provide us such a valuable opportunity to enhance our learning process. On behalf of Terry Liu I must express my very profound gratitude to my mother, thank you for your love, unfailing support and continuous encouragement throughout my time of study and research at MIT. This accomplishment would not have been possible without you. Thank you. On behalf of Leonhard Maximilian Fricke To my family, particularly my parents Ulrike and Ulrich, thank you for your love, support, and unwavering belief in me. I will forever be indebted to you giving me the opportunity to study at MIT and experiences that have made me who I am today. Above all I would like to thank my partner Shruti for her love and constant support, for all the late nights and early mornings, and for keeping me sane over the past few months. Thank you for being my editor, proofreader, and sounding board. But most of all, thank you for being my best friend.