[{"citation":{"ieee":"B. Barann, D. Beverungen, and O. Müller, “An open-data approach for quantifying the potential of taxi ridesharing,” Decision Support Systems, pp. 86--95, 2017.","short":"B. Barann, D. Beverungen, O. Müller, Decision Support Systems (2017) 86--95.","bibtex":"@article{Barann_Beverungen_Müller_2017, title={An open-data approach for quantifying the potential of taxi ridesharing}, DOI={10.1016/j.dss.2017.05.008}, journal={Decision Support Systems}, author={Barann, Benjamin and Beverungen, Daniel and Müller, Oliver}, year={2017}, pages={86--95} }","mla":"Barann, Benjamin, et al. “An Open-Data Approach for Quantifying the Potential of Taxi Ridesharing.” Decision Support Systems, 2017, pp. 86--95, doi:10.1016/j.dss.2017.05.008.","apa":"Barann, B., Beverungen, D., & Müller, O. (2017). An open-data approach for quantifying the potential of taxi ridesharing. Decision Support Systems, 86--95. https://doi.org/10.1016/j.dss.2017.05.008","chicago":"Barann, Benjamin, Daniel Beverungen, and Oliver Müller. “An Open-Data Approach for Quantifying the Potential of Taxi Ridesharing.” Decision Support Systems, 2017, 86--95. https://doi.org/10.1016/j.dss.2017.05.008."},"type":"journal_article","page":"86--95","uri_base":"https://ris.uni-paderborn.de","_id":"2856","status":"public","date_created":"2018-05-24T08:48:58Z","quality_controlled":"1","author":[{"first_name":"Benjamin","last_name":"Barann"},{"first_name":"Daniel","id":"59677","last_name":"Beverungen"},{"first_name":"Oliver","last_name":"Müller","id":"72849"}],"keyword":[],"publication":"Decision Support Systems","user_id":"21671","article_type":"original","abstract":[{"lang":"eng"}],"language":[{}],"creator":{"id":"40298","login":"vivienne"},"date_updated":"2022-01-06T06:58:08Z","dini_type":"doc-type:article","department":[{"tree":[{"_id":"195"},{"_id":"19"},{"_id":"44"},{"_id":"43"}],"_id":"526"}],"dc":{"rights":["info:eu-repo/semantics/closedAccess"],"subject":["Taxi ridesharing Collaborative consumption Transportation Open data Sustainability Shared mobility"],"language":["eng"],"type":["info:eu-repo/semantics/article","doc-type:article","text","http://purl.org/coar/resource_type/c_6501"],"identifier":["https://ris.uni-paderborn.de/record/2856"],"relation":["info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dss.2017.05.008"],"date":["2017"],"description":["Taxi ridesharing1 (TRS) is an advanced form of urban transportation that matches separate ride requests with similar spatio-temporal characteristics to a jointly used taxi. As collaborative consumption, TRS saves customers money, enables taxi companies to economize use of their resources, and lowers greenhouse gas emissions. We develop a one-to-one TRS approach that matches rides with similar start and end points. We evaluate our approach by analyzing an open dataset of > 5 million taxi trajectories in New York City. Our empirical analysis reveals that the proposed approach matches up to 48.34% of all taxi rides, saving 2,892,036 km of travel distance, 231,362.89 l of gas, and 532,134.64 kg of CO2 emissions per week. Compared to many-to-many TRS approaches, our approach is competitive, simpler to implement and operate, and poses less rigid assumptions on data availability and customer acceptance."],"creator":["Barann, Benjamin","Beverungen, Daniel","Müller, Oliver"],"source":["Barann B, Beverungen D, Müller O. An open-data approach for quantifying the potential of taxi ridesharing. Decision Support Systems. 2017:86--95. doi:10.1016/j.dss.2017.05.008"],"title":["An open-data approach for quantifying the potential of taxi ridesharing"]}}]