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Investigating Dynamic Pricing to Solve the Fleet Rebalancing Problem in Bike Sharing Systems

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Investigating Dynamic Pricing to Solve the Fleet Rebalancing Problem in Bike Sharing Systems INVESTIGATING DYNAMIC PRICING TO SOLVE THE FLEET REBALANCING PROBLEM IN BIKE SHARING SYSTEMS Word count: 24,996 Amaury Hellebuyck Student number : 000140581086 Supervisor: Prof. Dr. Dries Benoit Master’s Dissertation submitted to obtain the degree of: Master in Business Engineering: Data Analytics Academic year: 2018-2019 INVESTIGATING DYNAMIC PRICING TO SOLVE THE FLEET REBALANCING PROBLEM IN BIKE SHARING SYSTEMS Word count: 24,996 Amaury Hellebuyck Student number : 000140581086 Supervisor: Prof. Dr. Dries Benoit Master’s Dissertation submitted to obtain the degree of: Master in Business Engineering: Data Analytics Academic year: 2018-2019 Confidentiality Agreement Permission, I declare that the content of this Masters Dissertation may be consulted and/or reproduced, provided that the source is referenced. Name student: Hellebuyck, Amaury Student ID: 01405810 University: Ghent University, Belgium Signature: Abstract Hellebuyck, Amaury1 1) Ghent University, Belgium Bike Sharing is increasing in popularity and bike sharing systems are popping up in large cities all over the world. People tend to move away from the polluting transportation industry and welcome smart mobility concepts with open arms. One major problem all bike sharing operators are faced with is the rebalancing of the fleet. Currently, most operators are using a fleet of trucks to pick up unused bikes and redistribute them throughout the city. A new, experimental way of solving this problem is using incentive schemes, as a means of dynamic pricing, in order to motivate users to rebalance the system themselves. This research conducted a case study that focused on Mobit, a large Belgian bike sharing operator, and investigated whether or not using incentive schemes could lead to less trucks being used. The case study is two-fold. First, a qualitative in-depth interview was conducted to explore the topic and postulate a a-priori hypothesis. Secondly, a quantitative part was done to reject or accept this hypothesis. In this part a dataset provided by Mobit is being analysed. The results show that incentive schemes are an effective way to reduce the amount of trucks being used for the redistribution of the fleet. In the conclusion part, some managerial implications to implement a more dynamic pricing strategy are given. Keywords| Bike Sharing, Dynamic Pricing, Incentive Scheme, Fleet Rebalancing, Smart Mobility Preface Dear reader, First of all, thank you for taking the time to read my master dissertation. If you still have any questions or remarks, do not hesitate to contact me and I will be happy to reply. Since I was a kid, I have always had an entrepreneurial mindset. From selling candy on the play- ground to organizing prom in the final year. Going to university did not extinguish but invigorated this entrepreneurial drive. During these five beautiful years, I had the honour of working on small projects with some of my best friends as well as organize the graduation party for my fellow students, future colleagues and good friends. Writing this master dissertation was the final challenge before getting the degree of Master of Science Data Analytics in Business Engineering. My entrepreneurial drive together with a profound interest in new technologies and modern urban issues was the perfect inspiration source for this research paper. One day I came across a new phenomenon in China called bike sharing. Start-Ups offering shared bikes to local inhabitants bringing a solution to a lot of societal and environmental problems large cities encounter. I started wondering why this did not exist in Ghent, the city of bike riding students. What started as a small idea for a possible Start-Up soon turned into late night readings on Smart Mobility and Bike Sharing Systems. Instead of working out the idea, I decided to dive deeper into one specific problem of the bike sharing industry and that is how the research question of this thesis came to life. Through this way, I would like to thank everyone who made this research possible. First of all, my supervisor for giving me guidance and clarity where needed and always leaving the door open for questions of any kind. Secondly, Alexander De Bi`evre,co-founder of Mobit, for the collaboration in this research. Without the help of Mobit, this would not have been possible. And last but not least I would like to thank my family and in particular my parents. Not only for the unconditional love and support during these intense months of writing this research, but for making me into who I am today. I always tried to live up to quote of theirs: 'After all, it is not what you study that counts, but the person you've become when you finish those studies.' Thank you. Ghent, 4th of June 2019 Amo out. i Contents List of Figures iv List of Tables v 1 Situating 1 1.1 Problem statement . .1 1.1.1 Research Question . .2 1.2 Relevance of the paper . .2 1.3 Composition . .3 2 Introduction 4 2.1 Sharing Economies . .4 2.2 Vehicle Sharing Systems . .6 2.2.1 Car Sharing . .8 2.2.2 Scooter Sharing . 13 2.2.3 Bike Sharing . 14 2.3 Advantages of Bike Sharing Systems . 17 2.3.1 Individual Benefits . 18 2.3.2 Public Benefits . 18 2.4 Disadvantages of Bike Sharing Systems . 19 2.4.1 Vandalism and Theft . 19 2.4.2 Bad Parking Behaviour . 20 2.4.3 Lack of Infrastructure . 22 2.4.4 Load Balancing . 22 2.5 Pricing . 25 2.5.1 Static Pricing . 26 2.5.2 Dynamic Pricing . 26 2.6 Hypothesis . 31 ii Contents iii 3 Methodology 32 3.1 Research Design . 32 3.1.1 Mobit . 33 3.2 Research Methods . 35 3.2.1 Qualitative Research . 35 3.2.2 Quantitative Research . 39 3.3 Reliability and validity . 54 3.3.1 Reliability . 54 3.3.2 Validity . 55 4 Results 56 4.1 Qualitative Research . 56 4.1.1 Competition in Belgium . 57 4.1.2 Pricing Strategy . 60 4.1.3 Motives for using Bike Sharing Systems . 61 4.1.4 Fleet Rebalancing Problem . 61 4.2 Quantitative Research . 62 4.2.1 Descriptive statistics . 62 4.2.2 Conclusive results . 69 5 Discussion 74 5.1 Brief Summary of Results . 74 5.2 Conclusion . 75 5.2.1 Managerial Implications . 76 5.3 Discussion . 76 5.4 Limitations . 77 5.5 Suggestions for future research . 78 A Appendix 79 A.1 In-depth Interview . 79 Bibliography 85 List of Figures 2.1 Global two-yearly evolution (2006-2016). .8 2.2 Global overview: Members (2016). 10 2.3 Global overview: Fleet (2016). 10 2.4 China: Pile of Bikes. 21 2.5 Map: Typically full or empty stations in Washington D.C. 29 3.1 First 10 lines of the raw data from the .txt-file. 41 3.2 First 10 lines of the structured dataset. 41 3.3 Density plot of gps deviation. 49 3.4 Partial density plot of gps deviation. 50 3.5 Example of ordered dataset. 52 4.1 Plot of amount of trips per day of the week ordered from most to least. 63 4.2 Proportion of trips during weekday and weekend. 64 4.3 Proportion of trips picked up by user or truck. 65 4.4 Map: Operational cities of Mobit in Belgium. 66 4.5 Map: Centre of Kortrijk. 72 4.6 Map: Outskirt of Kortrijk. 72 iv List of Tables 2.1 Global market in terms of members and fleet size (2016). .9 3.1 Tariffs per 20 min. 34 3.2 Number of unique counts. 43 3.3 Original data types of different variables. 44 3.4 Number of missing values per variable. 45 3.5 Modified data types of different variables. 46 4.1 Overview of Belgian Bike Sharing Market. 59 4.2 Descriptive statistics of Full dataset. 63 4.3 Descriptive statistics of subset Before Bonus Bikes. 67 4.4 Descriptive statistics of subset After Bonus Bikes. 67 4.5 Descriptive statistics of subset from Weekdays. 68 4.6 Descriptive statistics of subset from Weekends. 68 4.7 Descriptive statistics of subset from Centre Data. 69 4.8 Descriptive statistics of subset from Outskirt Data. 69 4.9 P-value per city. 71 v Chapter 1 Situating This first chapter covers the definition of the problem statement and the according research question of this dissertation followed by a view on the relevance this research. The chapter ends by giving an overview of the composition of this dissertation. 1.1 Problem statement Bike sharing is seen as a solution to many problems of modern society. Because of rapid urbanization, there is an overload of cars in the cities. People drive to work with their cars on a daily basis causing low air quality, excessive air pollution, congestion etc. One reason why people do not shift to public transportation is called the last mile problem. Even when they use bus, tram, train, metro or other means of transportation, there is always a certain distance to cover from the final destination of the transportation method to the final destination of the user. This is not the case when using a car. A bike sharing system offers the perfect solution to cover this last mile. Another recent trend within society is that people become more and more conscious about their ecological footprint. They tend to move away from everything that is polluting the earth. Off course, emissions of transport have a big, negative impact on the environment. Riding a bike is an emission-free means of transportation and when integrated well in the public transport it offers an efficient and convenient alternative to the car.
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