Green Cabs vs. Uber in New York City

2016 IEEE International Congress on Big Data (BigData Congress) Pub Date : 2016-06-01 DOI:10.1109/BigDataCongress.2016.35

L. K. Poulsen, D. Dekkers, N. Wagenaar, Wesley Snijders, Ben Lewinsky, R. Mukkamala, Ravikiran Vatrapu

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引用次数: 18

Abstract

This paper reports on the process and outcomes of big data analytics of ride records for Green cabs and Uber in the outer boroughs of New York City (NYC), USA. Uber is a new entrant to the taxi market in NYC and is rapidly eating away market share from the NYC Taxi & Limousine Commission's (NYCTLC) Yellow and Green cabs. The problem investigated revolves around where exactly Green cabs are losing market share to Uber outside Manhattan and what, if any, measures can be taken to preserve market share? Two datasets were included in the analysis including all rides of Green cabs and Uber respectively from April-September 2014 in New York excluding Manhattan and NYC's two airports. Tableau was used as the visual analytics tool, and PostgreSQL in combination with PostGIS was used as the data processing engine. Our findings show that the performance of Green cabs in isolated zip codes differ significantly, and that Uber is growing faster than Green cabs in general and especially in the areas close to Manhattan. We discuss meaningful facts from the analysis, outline actionable insights, list valuable outcomes and mention some of the study limitations.

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纽约市的绿色出租车和优步

本文报道了美国纽约市(NYC)外城区Green出租车和Uber乘车记录的大数据分析过程和结果。Uber是纽约市出租车市场的新进入者，正在迅速蚕食纽约市出租车和豪华轿车委员会(NYC taxi & Limousine Commission)的黄色和绿色出租车的市场份额。调查的问题围绕着在曼哈顿以外，Green出租车究竟在哪些地方被优步抢走了市场份额，以及如果有的话，可以采取什么措施来保持市场份额?分析中包含了两个数据集，分别包括2014年4月至9月在纽约(不包括曼哈顿和纽约的两个机场)的Green出租车和Uber的所有乘坐情况。使用Tableau作为可视化分析工具，使用PostgreSQL结合PostGIS作为数据处理引擎。我们的研究结果表明，在孤立的邮政编码地区，绿色出租车的表现差异很大，总的来说，优步的增长速度快于绿色出租车，尤其是在曼哈顿附近的地区。我们从分析中讨论有意义的事实，概述可操作的见解，列出有价值的结果，并提到一些研究的局限性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2016 IEEE International Congress on Big Data (BigData Congress)

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