各國推動節能減碳，共享經濟便是推廣的主要政策，其中共享單車系統是台灣主要推廣的項目之一，滿足大眾搭乘交通工具時「第一哩路」到「最後一哩路」的需求，隨著站點數的擴張，使用者數量也隨之上升，隨後也產生了有樁式共享單車缺車缺位的問題，以及傳統運補時每趟貨車裝載自行車數量不穩定造成的問題，不僅造成使用者服務體驗不佳也導致資源浪費的問題，靠近市區的站點夜間運補造成的噪音也是一大問題。因此本研究根據法國Vélib'實行的激勵機制解決方案為基礎，提出以折扣的方式吸引使用者將自行車歸還於指定地點或是從指定地點借車並且結合傳統運補，提升整體運補效率，降低成本、人力需求以及碳排放量。
本研究提出作業研究模型，傳統運補成本使用數量折扣來降低每趟貨車載送自行車數量不穩定的問題，而激勵機制成本則是企業給予的折扣越高，供給數量越多，鼓勵使用者自行將自行車歸還到指定站點或是從指定站點借車。
在結合傳統運補以及激勵機制運補下，市區主要是以傳統運補激勵機制為輔，郊區則是以激勵機制為主，兩者的結合運補下能降低成本以及探排放量，並且使用到傳統運補的地區每趟貨車皆有裝載50%最大容量的自行車，降低資源浪費，市區夜間在提升傳統運補的成本下，傳統運補數量也呈現顯著下降，減少了噪音的產生。

Promoting energy conservation and carbon reduction is a major policy in many countries, and the sharing economy is one of the key strategies. One of the main projects in Taiwan is the bike-sharing system. However, bike-sharing systems will have problems in that no bikes are available for rent or no available parking spaces to return the bikes, and the instability of the number of bikes loaded per trip during traditional transportation results in poor user experience and resource waste. Moreover, the nighttime transportation of bikes near urban regions also generates noise pollution.
This study proposes an incentive mechanism to attract users to return bikes to designated stations or rent bikes from designated stations by offering discounts. This approach is combined with traditional transportation methods to enhance overall transportation efficiency and reduce costs, manpower requirements, and carbon emissions.

論文審定書 i
摘要 ii
Abstract iii
Chapter 1 Introduction 1
1.1 Research Background 1
1.2 Research Motivation 2
1.3 Purpose 5
Chapter 2　 Literature Review 7
2.1 The Development History of Domestic and Foreign Bike-Sharing System 7
2.2 Shortage of Bikes and Parking Spaces Problem 9
2.3 Optimizing the Issue of Bike and Space shortages 12
2.4 The Impact of Price, Environment and Discounts on Products 14
2.5 Supply Chain Model 17
Chapter 3　Research method 20
3.1 Building Transportation Networks 20
3.2 Incentive Mechanism and Quantity discount Transportation Model 23
Chapter 4 Data Calculation 30
4.1 Research Tools 30
4.2 Data Collection and Data Content 30
4.3 Day-Long Data 31
4.4 Nighttime Data 36
Chapter 5 Conclusion 40
Managerial Insight 40
Limitation and Future Suggestion 44
Reference 46
Number Code Comparison Table 49
Region Mapping Figure 50

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