公共自行車使用者於他站租還車之願受價格研究-以台北市YouBike為例

目前實務上在處理自行車共享系統車隊在空間上分布不平衡的問題時，大多是由業者以卡車去各站取、送空車來進行車隊的重新配置以改善供需失衡的現象，屬於較為被動的做法，且造成業者在成本上的負擔。本研究考慮行動共享系統營運業者可以從資訊系統即時發現車輛或車位即將不足之場站，以提供費用折扣誘因的方式，主動建議使用者前往鄰近可以立即取車的場站租車，或是附近有停車格的場站還車。此種作法將可以引導部分使用者前往鄰近場站租車或還車，預防供需不平衡的狀況，也可以減輕業者在車輛調度方面的作業成本。為了了解使用者在此費用折扣誘因下願意接受業者建議去鄰站租還車的費用折扣範圍，本研究以台北市YouBike使用者為對象，採用敘述性偏好方法設計問卷情境，探討自行車共享系統使用者在不同情境組合下對於前往鄰近場站租、還車之願受價格，並且建立與估計個體選擇模式，探討相關因素對於使用者願受價格之影響。研究結果顯示，在不同租、還車情境下，使用Probit和Logit模型所估計之使用者願意接受之價格折扣介於總費用30%到40%間。後續若業者有意採取這項以費用折扣誘因為基礎之主動推薦措施來輔助車輛調度作業，本研究成果將可提供業者參考，設計出有效的費用折扣機制。

關鍵字

自行車共享；行動共享系統；願受價格；個體選擇模型

並列摘要

Practically, the most common approach adopted by system operators to deal with the spatial imbalance of the fleet in bike-sharing systems is sending trucks to stations to relocate empty trucks so as to balance the supply and demand in these systems. This type of fleet rebalancing approach is passive and incurs significant operating costs to system operators. This study considers an alternative that operators can utilize real-time information to identify problematic stations which will run out of bike or stand inventory in a short time and guide (or suggest) users to pick up bikes from or return bikes to nearby stations with sufficient bikes or stands, respectively, by providing users with price discount incentives. This is a proactive approach that may prevent some stations from running of bikes or stands in advance and reduce the operating cost for system operators on relocating empty bikes. In order to understanding users’ willingness to accept (WTA) operators’ suggestion of pickup or return stations given price discount incentives, this study adopts the stated preference approach to design scenarios in the questionnaire, and conduct a survey to collect data from YouBike users in Taipei to investigates the users’ WTA prices under different scenarios. We also establish and estimate disaggregate choice models to examine the impact of model parameters on the users’ WTA prices. The results show that the WTA price discounts, estimated using Probit and Logit models, are between 30% and 40% of the original prices under different scenarios. The findings of this research will help shared-mobility system operators design effective price discount incentive mechanisms, if system operators intend to adopt this proactive incentive-based approach to facilitate their fleet rebalancing in the future.