A sustainability-oriented optimal allocation strategy of sharing bicycles: Evidence from ofo usage in Shanghai
A sustainability-oriented optimal allocation strategy of sharing bicycles: Evidence from ofo usage in Shanghai
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面向可持续发展的共享单车优化配置策略——来自上海ofo使用情况的证据
DOI：
10.1016/j.resconrec.2019.104510
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发表时间：
2020-02-01
影响因子：
13.2
通讯作者：
Jiang, Lu
中科院分区：
文献类型：
--
作者：
Jie, Tao;Wei, Wendong;Jiang, Lu
共享单车是一种被广泛认可的减少资源消耗、促进绿色出行、提高交通效率的方式，但自行车分布与需求之间的差异限制了其对经济可持续发展的影响。本文采用数据驱动的方法，以10个ofo共享单车停车场为案例，探讨共享单车的最优资源配置策略，包括停车场布局和投放单车数量，以最大化共享单车的正效应，实现可持续发展。调查结果显示，ofo单车的配置存在大量冗余，这主要是由于早期的“蝗虫式”发展模式。这些发现表明，共享单车企业应该调整战略，以实现更可持续的长期目标，将城市地区过剩的自行车转移到偏远地区也是切实可行的。此外，对于大学共享单车，研究结果表明，分配效率与到地铁站的距离之间存在倒“U”形关系。这一特点与共享单车作为解决“最后一公里”问题的有效途径相吻合。此外，还提出了一个简单而有效的自行车配置规则，即在繁华的居住区应投入更多的自行车资源，而在著名的商业区和居住密度较低的地区应投入较少的资源。
Sharing bicycles is a widely recognized way to reduce resource consumption, promote green travel and improve traffic efficiency, yet the discrepancy between bicycle distribution and demand limits its impact on sustainable economic development. By employing a data-driven approach and using 10 ofo shared bicycle parking lots as the case, this paper aims to explore an optimal resource allocation strategy of sharing bicycles, including the layout of parking lots and the quantity of distributed bicycles, in order to maximize the positive effect of sharing bicycles with the goal of sustainability. The findings show that there is a large amount of redundancy in the allocation of ofo bicycles, which is mainly due to the "locust-like" mode of development in earlier times. These findings indicate that shared bicycle companies should adjust their strategies to more sustainable long-term objectives, and it is also practical to move the excess bicycles in urban areas to remote areas. Furthermore, with respect to sharing bicycles at universities, the findings suggest an inverted "U"-shaped relationship between the allocation efficiency and the distance to subway stations. This characteristic is consistent with the fact that sharing bicycles serves as an effective solution to the "last mile" problem. In addition, a simple but effective rule for bicycle allocation is proposed; that is, more bicycle resources should be invested in bustling residential areas, while fewer resources should be placed in famous business districts and areas with low residential density.