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Designing an On-Demand Dynamic Crowdshipping Model and Evaluating Its Ability to Serve Local Retail Delivery in New York City Shirin Najaf Abadi CUNY City College

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Designing an On-Demand Dynamic Crowdshipping Model and Evaluating Its Ability to Serve Local Retail Delivery in New York City Shirin Najaf Abadi CUNY City College City University of New York (CUNY) CUNY Academic Works Dissertations and Theses City College of New York 2019 Designing an On-Demand Dynamic Crowdshipping Model and Evaluating its Ability to Serve Local Retail Delivery in New York City shirin najaf abadi CUNY City College How does access to this work benefit ou?y Let us know! More information about this work at: https://academicworks.cuny.edu/cc_etds_theses/809 Discover additional works at: https://academicworks.cuny.edu This work is made publicly available by the City University of New York (CUNY). Contact: [email protected] DESIGNING AN ON-DEMAND DYNAMIC CROWDSHIPPING MODEL AND EVALUATING ITS ABILITY TO SERVE LOCAL RETAIL DELIVERY IN NEW YORK CITY A Dissertation Presented to The Academic Faculty by Shirin Najaf-Abadi In Partial Fulfillment Of the Requirements for the Degree Doctor of Philosophy The School of Civil and Environmental Engineering The City University of New York May 2019 1 © 2019 Shirin Najaf-Abadi All Rights Reserved 2 APPROVAL PAGE 3 This thesis is dedicated to my wonderful parents and to Ali without whom I would have never made it a success 4 Ph.D. Committee Dr. Mahdieh Allahviranloo, Advisor, Dept. of Civil Engineering, the City College of New York, Dr. Alison Conway, Dept. of Civil Engineering, the City College of New York, Dr. Naresh Devineni, Dept. of Civil Engineering, the City College of New York, Dr. Huy T. Vo, Dept. of Computer Science, New York University, Dr. Anil Yazici. Dept. of Civil Engineering, Stony Brook University, 5 ACKNOWLEDGMENT I would like to express my sincere gratitude to my advisor Dr. Mahdieh Allahviranloo for the continuous support of my Ph.D. study and related research, for her patience, motivation, and immense knowledge. This journey would not have been complete without her boundless support. I would also like to extend my gratefulness to my thesis committee members Prof. Alison Conway, Prof. Naresh Devineni, Prof. Anil Yacizi, and Prof. Huy Vo, for their insightful comments that helped to profoundly improve the content of this thesis. Next, I would like to express my gratitude to my friends and great office-mates Niloufar Nouri, Niloofar Ghahramani, Amirhossein Baghestani, and Carla Tejada, from room T117.Thank you very much for always being there for me and your continuous support. Exceptional gratitude goes out to my friend Dr. Napoleon Hernandez Warren for his guidance during my Ph.D. journey. Thank you for teaching me the object-oriented coding and for proofreading this thesis. I would also like to thank my parents, Vida and Mahdi, and my brother Shahin for their unconditional love and being super supportive in the past 34 years. Their love and support made this journey easier to me. Last, but not least, I would like to thank my husband, Ali for everything. I truly appreciate your incessant support and love. 6 TABLE OF CONTENTS ACKNOWLEDGMENT................................................................................................................. 6 TABLE OF CONTENTS ................................................................................................................ 7 LIST OF FIGURES ...................................................................................................................... 11 LIST OF TABLES ........................................................................................................................ 13 ABSTRACT .................................................................................................................................. 14 INTRODUCTION AND LITERATURE REVIEW ........................................... 17 Introduction and Motivation........................................................................................... 17 Objective and Research Question .................................................................................. 24 Literature Review ........................................................................................................... 24 1.3.1 Taxi Demand Prediction ..................................................................................................... 24 1.3.2 Crowdshipping and Integrated approaches for City Logistics ............................................ 27 1.3.3 Analysis of Crowdshipping Service Adoption by Public.................................................... 29 Dissertation Structure ..................................................................................................... 33 AN ON-DEMAND DYNAMIC CROWDSHIPPING MODEL ........................ 36 Background .................................................................................................................... 37 The Dynamic Crowdshipping Setting ............................................................................ 41 2.2.1 Definitions ........................................................................................................................... 42 2.2.2 Mathematical Formulation .................................................................................................. 46 2.2.3 Time Horizon Setting .......................................................................................................... 51 Numerical Analysis ........................................................................................................ 53 7 2.3.1 Case 1: ................................................................................................................................. 54 2.3.2 Case Study of New York .................................................................................................... 57 Datasets .......................................................................................................................... 59 Instance Design Using Gaussian Copula Method .......................................................... 60 Results of the DCM ........................................................................................................ 62 Discussion ...................................................................................................................... 66 PRELIMINARY ANALYSIS OF TAXI RIDERSHIP ...................................... 69 Methods .......................................................................................................................... 72 3.1.1 Long Short-Term Memory Model (LSTM) ........................................................................ 73 3.1.2 Decision Tree Regression Model ........................................................................................ 77 3.1.3 Adaptive Boosting Regression Model ................................................................................ 77 Experiment Design ......................................................................................................... 78 Preliminary Analysis ...................................................................................................... 79 Clustering using Principal Component Analysis ........................................................... 80 Model Specification, evaluation, and comparison ......................................................... 83 Long-Term Prediction Results ....................................................................................... 84 Short-Term Prediction Results ....................................................................................... 85 3.7.1 Grid Level Short Term Analysis ......................................................................................... 86 Discussion and Conclusion ............................................................................................ 91 ANALYSIS OF ACCEPTANCE OF CROWDSHIPPING SERVICE BY PEOPLE: A CASE STUDY OF NEW YORK CITY .................................................................. 94 8 Background .................................................................................................................... 94 Survey Design and Data Collection ............................................................................... 98 Framing the Questions of the Survey ............................................................................. 98 Expletory Data Analysis............................................................................................... 101 4.4.1 Sample Description and General Statistics ....................................................................... 101 4.4.2 Inferring Preference from Data (Being Requester or Being Carriers) .............................. 103 Methods ........................................................................................................................ 108 Results .......................................................................................................................... 111 4.6.1 Requester Models Results ................................................................................................. 111 4.6.2 Carrier Models Results ...................................................................................................... 112 Discussion .................................................................................................................... 115 CONCLUSIONS AND FINAL REMARKS .................................................... 118 Final Remarks .............................................................................................................. 118 5.1.1 Inference Spatiotemporal Distribution of Taxi Demand ................................................... 121 5.1.2 The On-Demand
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