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

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › 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.

Originalsprog	Engelsk
Titel	Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016
Redaktører	Calton Pu, Geoffrey Fox, Ernesto Damiani
Antal sider	8
Udgivelsessted	Los Alamitos, CA
Forlag	IEEE
Publikationsdato	2016
Sider	222–229
Artikelnummer	7584941
ISBN (Trykt)	9781509026227
ISBN (Elektronisk)	9781509026227
DOI	https://doi.org/10.1109/BigDataCongress.2016.35
Status	Udgivet - 2016
Begivenhed	5th IEEE International Congress on Big Data: BigData Congress 2016 - San Francisco, CA, USA Varighed: 27 jun. 2016 → 2 jul. 2016 Konferencens nummer: 5 http://www.ieeebigdata.org/2016/

Konference

Konference	5th IEEE International Congress on Big Data
Nummer	5
Land/Område	USA
By	San Francisco, CA
Periode	27/06/2016 → 02/07/2016
Internetadresse	http://www.ieeebigdata.org/2016/

Emneord

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

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10.1109/BigDataCongress.2016.35Licens: Ikke-specificeret

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Citationsformater

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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. i C Pu, G Fox & E Damiani (red), Proceedings of the 2016 IEEE International Congress on Big Data. BigData Congress 2016., 7584941, IEEE, Los Alamitos, CA, s. 222–229, 5th IEEE International Congress on Big Data, San Francisco, CA, USA, 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. red. / Calton Pu; Geoffrey Fox; Ernesto Damiani. Los Alamitos, CA: IEEE, 2016. s. 222–229 7584941.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › 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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