Green Cabs vs. Uber in New York City

Lasse Korsholm Poulsen; Daan Dekkers; Nicolaas Wagenaar; Wesley Snijders; Ben Lewinsky; Raghava Rao Mukkamala; Ravi Vatrapu

doi:10.1109/BigDataCongress.2016.35

Green Cabs vs. Uber in New York City

Lasse Korsholm Poulsen, Daan Dekkers, Nicolaas Wagenaar, Wesley Snijders, Ben Lewinsky, Raghava Rao Mukkamala, Ravi Vatrapu

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016
Editors	Calton Pu, Geoffrey Fox, Ernesto Damiani
Number of pages	8
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Publication date	2016
Pages	222–229
Article number	7584941
ISBN (Print)	9781509026227
ISBN (Electronic)	9781509026227
DOIs	https://doi.org/10.1109/BigDataCongress.2016.35
Publication status	Published - 2016
Event	5th IEEE International Congress on Big Data: BigData Congress 2016 - San Francisco, CA, United States Duration: 27 Jun 2016 → 2 Jul 2016 Conference number: 5 http://www.ieeebigdata.org/2016/

Conference

Conference	5th IEEE International Congress on Big Data
Number	5
Country/Territory	United States
City	San Francisco, CA
Period	27/06/2016 → 02/07/2016
Internet address	http://www.ieeebigdata.org/2016/

Keywords

Uber
Big social data
Social set analysis
Social business
Visual analytics
Geo-spatial
GIS
Taxi
Green cabs

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Cite this

@inproceedings{496fe58f187e48d6a00a546ee2ee120f,

title = "Green Cabs vs. Uber in New York City",

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.",

keywords = "Uber, Big social data, Social set analysis, Social business, Visual analytics, Geo-spatial, GIS, Taxi, Green cabs, Uber, Big social data, Social set analysis, Social business, Visual analytics, Geo-spatial, GIS, Taxi, Green cabs",

author = "{Korsholm Poulsen}, Lasse and Daan Dekkers and Nicolaas Wagenaar and Wesley Snijders and Ben Lewinsky and Mukkamala, {Raghava Rao} and Ravi Vatrapu",

year = "2016",

doi = "10.1109/BigDataCongress.2016.35",

language = "English",

isbn = "9781509026227",

pages = "222–229",

editor = "Calton Pu and Geoffrey Fox and Ernesto Damiani",

booktitle = "Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016",

publisher = "IEEE",

address = "United States",

note = "5th IEEE International Congress on Big Data ; Conference date: 27-06-2016 Through 02-07-2016",

url = "http://www.ieeebigdata.org/2016/",

}

Korsholm Poulsen, L, Dekkers, D, Wagenaar, N, Snijders, W, Lewinsky, B, Mukkamala, RR & Vatrapu, R 2016, Green Cabs vs. Uber in New York City. in C Pu, G Fox & E Damiani (eds), Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016., 7584941, IEEE, Los Alamitos, CA, pp. 222–229, 5th IEEE International Congress on Big Data, San Francisco, CA, United States, 27/06/2016. https://doi.org/10.1109/BigDataCongress.2016.35

Green Cabs vs. Uber in New York City. / Korsholm Poulsen, Lasse; Dekkers, Daan; Wagenaar, Nicolaas et al.
Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016. ed. / Calton Pu; Geoffrey Fox; Ernesto Damiani. Los Alamitos, CA: IEEE, 2016. p. 222–229 7584941.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Mukkamala, Raghava Rao

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N2 - 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.

AB - 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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