How to cite this paper
Shokoohyar, S. (2018). Ride-sharing platforms from drivers’ perspective: Evidence from Uber and Lyft drivers.International Journal of Data and Network Science, 2(4), 89-98.
Refrences
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Banerjee, S., Riquelme, C., & Johari, R. (2015). Pricing in ride-share platforms: A queueing-theoretic approach.
Bimpikis, K., Candogan, O., & Daniela, S. (2016). Spatial pricing in ride-sharing networks.
Brodeur, A., & Nield, K. (2016). Has Uber Made It Easier to Get a Ride in the Rain?
Certify. (2017). Uber Declines, Lyft Picks Up in the Certify SpendSmartTM Report for Q3 2017. Retrieved from https://www.certify.com/2017-10-24-Uber-Declines-Lyft-Picks-Up-in-the-Certify-SpendSmart-Report-for-Q3-2017
Chen, L., Mislove, A., & Wilson, C. (2015). Peeking beneath the hood of uber. In Proceedings of the 2015 Internet Measurement Conference (pp. 495–508).
Chen, M. K., Chevalier, J. A., Rossi, P. E., & Oehlsen, E. (2017). The value of flexible work: Evidence from uber drivers.
Chen, M. K., & Sheldon, M. (2016). Dynamic Pricing in a Labor Market: Surge Pricing and Flexible Work on the Uber Platform. In EC (p. 455).
Cohen, M. C., & Zhang, R. P. (2017). Coopetition and profit sharing for ride-sharing platforms.
Cramer, J., & Krueger, A. B. (2016). Disruptive change in the taxi business: The case of Uber. American Economic Review, 106(5), 177–182.
Davidov, G. (2016). The status of Uber drivers: A purposive approach.
Dogtiev, A. (2017). Uber Revenue and Usage Statistics. Retrieved from http://www.businessofapps.com/data/uber-statistics/
Domingos, P., & Pazzani, M. (1997). On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, 29(2–3), 103–130.
Feeney, M., & companies Uber, R. (2015). Is Ridesharing Safe?
Firnkorn, J., & Müller, M. (2011). What will be the environmental effects of new free-floating car-sharing systems? The case of car2go in Ulm. Ecological Economics, 70(8), 1519–1528.
Guda, H., & Subramanian, U. (2018). Your Uber Is Arriving: Managing On-Demand Workers through Surge Pricing, Forecast Communication and Worker Incentives.
Hall, J., Kendrick, C., & Nosko, C. (2015). The effects of Uber’s surge pricing: A case study. The University of Chicago Booth School of Business.
Hall, J. V, & Krueger, A. B. (2015). An analysis of the labor market for Uber’s driver-partners in the United States. ILR Review, 0019793917717222.
Jacob, J., & Roet-Green, R. (2017). Ride Solo or Pool: The Impact of Sharing on Optimal Pricing of Ride-Sharing Services.
Jiao, J. (2018). Investigating Uber price surges during a special event in Austin, TX. Research in Transportation Business & Management.
Kokalitcheva, K. (2016). Uber now has 40 million monthly riders worldwide. Fortune Magazine.
Kosoff, M. (2014). Uber Drivers Across The Country Are Protesting Today: Here’s Why. Business Insider, 22.
Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In Mining text data (pp. 415–463). Springer.
Lyft. (2018a). Driver and passenger ratings. Retrieved from https://help.lyft.com/hc/en-us/articles/115013079948-Driver-and-passenger-ratings#passengerrating
Lyft. (2018b). Express Drive Rental Car Program. Retrieved from https://help.lyft.com/hc/en-us/articles/115013080108-Express-Drive-Rental-Car-Program
Malin, B. J., & Chandler, C. (2017). Free to work anxiously: Splintering precarity among drivers for Uber and Lyft. Communication, Culture & Critique, 10(2), 382–400.
Martin, E. W., & Shaheen, S. A. (2011). Greenhouse gas emission impacts of carsharing in North America. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1074–1086.
Newcomer, E. (2017). Lyft Gains on Uber in U.S. Business Travel, Doubling Share. Retrieved from https://www.bloomberg.com/news/articles/2018-04-30/lyft-gains-on-uber-in-u-s-business-travel-doubling-share
Oei, S.-Y., & Ring, D. M. (2017). The Tax Lives of Uber Drivers: Evidence from Internet Discussion Forums. Colum. J. Tax L., 8, 56.
Pang, B., & Lee, L. (2005). Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd annual meeting on association for computational linguistics (pp. 115–124).
Pang, B., Lee, L., & others. (2008). Opinion mining and sentiment analysis. Foundations and Trends®in Information Retrieval, 2(1--2), 1–135.
Prabowo, R., & Thelwall, M. (2009). Sentiment analysis: A combined approach. Journal of Informetrics, 3(2), 143–157.
Rassman, C. L. (2014). Regulating rideshare without stifling innovation: Examining the drivers, the insurance gap, and why Pennsylvania should get on board. Pitt. J. Tech. L. & Pol’y, 15, 81.
Redfearn III, R. L. (2016). Sharing economy misclassification: Employees and independent contractors in transportation network companies. Berkeley Tech. LJ, 31, 1023.
Rideshare Central. (2017). Lyft Driver Promos vs. Uber Driver Promos. Retrieved from https://ridesharecentral.com/lyft-driver-promos-vs-uber-driver-promos
Rogers, B. (2015). The social costs of Uber. U. Chi. L. Rev. Dialogue, 82, 85.
Scheiber, N. (2017). How Uber uses psychological tricks to push its drivers’ buttons. The New York Times, 2.
Stiglic, M., Agatz, N., Savelsbergh, M., & Gradisar, M. (2016). Making dynamic ride-sharing work: The impact of driver and rider flexibility. Transportation Research Part E: Logistics and Transportation Review, 91, 190–207.
Truong, M., & Trivedi, R. (2017). Updates to the Rating System. Retrieved from https://www.uber.com/newsroom/ratingsupdate-2/
Uber. (2018). Car Offers, Wheels by the Week. Retrieved from https://www.uber.com/drive/vehicle-solutions/
Vinodhini, G., & Chandrasekaran, R. M. (2012). Sentiment analysis and opinion mining: a survey. International Journal, 2(6), 282–292.
Wang, M., & Mu, L. (2018). Spatial disparities of Uber accessibility: An exploratory analysis in Atlanta, USA. Computers, Environment and Urban Systems, 67, 169–175.
Woo, C., & Bales, R. A. (2017). The Uber Million Dollar Question: Are Uber Drivers Employees or Independent Contractors?
Ye, Q., Zhang, Z., & Law, R. (2009). Sentiment classification of online reviews to travel destinations by supervised machine learning approaches. Expert Systems with Applications, 36(3), 6527–6535.
Yu, X., Liu, Y., Huang, X., & An, A. (2012). Mining online reviews for predicting sales performance: A case study in the movie domain. IEEE Transactions on Knowledge and Data Engineering, 24(4), 720–734.
Banerjee, S., Riquelme, C., & Johari, R. (2015). Pricing in ride-share platforms: A queueing-theoretic approach.
Bimpikis, K., Candogan, O., & Daniela, S. (2016). Spatial pricing in ride-sharing networks.
Brodeur, A., & Nield, K. (2016). Has Uber Made It Easier to Get a Ride in the Rain?
Certify. (2017). Uber Declines, Lyft Picks Up in the Certify SpendSmartTM Report for Q3 2017. Retrieved from https://www.certify.com/2017-10-24-Uber-Declines-Lyft-Picks-Up-in-the-Certify-SpendSmart-Report-for-Q3-2017
Chen, L., Mislove, A., & Wilson, C. (2015). Peeking beneath the hood of uber. In Proceedings of the 2015 Internet Measurement Conference (pp. 495–508).
Chen, M. K., Chevalier, J. A., Rossi, P. E., & Oehlsen, E. (2017). The value of flexible work: Evidence from uber drivers.
Chen, M. K., & Sheldon, M. (2016). Dynamic Pricing in a Labor Market: Surge Pricing and Flexible Work on the Uber Platform. In EC (p. 455).
Cohen, M. C., & Zhang, R. P. (2017). Coopetition and profit sharing for ride-sharing platforms.
Cramer, J., & Krueger, A. B. (2016). Disruptive change in the taxi business: The case of Uber. American Economic Review, 106(5), 177–182.
Davidov, G. (2016). The status of Uber drivers: A purposive approach.
Dogtiev, A. (2017). Uber Revenue and Usage Statistics. Retrieved from http://www.businessofapps.com/data/uber-statistics/
Domingos, P., & Pazzani, M. (1997). On the optimality of the simple Bayesian classifier under zero-one loss. Machine Learning, 29(2–3), 103–130.
Feeney, M., & companies Uber, R. (2015). Is Ridesharing Safe?
Firnkorn, J., & Müller, M. (2011). What will be the environmental effects of new free-floating car-sharing systems? The case of car2go in Ulm. Ecological Economics, 70(8), 1519–1528.
Guda, H., & Subramanian, U. (2018). Your Uber Is Arriving: Managing On-Demand Workers through Surge Pricing, Forecast Communication and Worker Incentives.
Hall, J., Kendrick, C., & Nosko, C. (2015). The effects of Uber’s surge pricing: A case study. The University of Chicago Booth School of Business.
Hall, J. V, & Krueger, A. B. (2015). An analysis of the labor market for Uber’s driver-partners in the United States. ILR Review, 0019793917717222.
Jacob, J., & Roet-Green, R. (2017). Ride Solo or Pool: The Impact of Sharing on Optimal Pricing of Ride-Sharing Services.
Jiao, J. (2018). Investigating Uber price surges during a special event in Austin, TX. Research in Transportation Business & Management.
Kokalitcheva, K. (2016). Uber now has 40 million monthly riders worldwide. Fortune Magazine.
Kosoff, M. (2014). Uber Drivers Across The Country Are Protesting Today: Here’s Why. Business Insider, 22.
Liu, B., & Zhang, L. (2012). A survey of opinion mining and sentiment analysis. In Mining text data (pp. 415–463). Springer.
Lyft. (2018a). Driver and passenger ratings. Retrieved from https://help.lyft.com/hc/en-us/articles/115013079948-Driver-and-passenger-ratings#passengerrating
Lyft. (2018b). Express Drive Rental Car Program. Retrieved from https://help.lyft.com/hc/en-us/articles/115013080108-Express-Drive-Rental-Car-Program
Malin, B. J., & Chandler, C. (2017). Free to work anxiously: Splintering precarity among drivers for Uber and Lyft. Communication, Culture & Critique, 10(2), 382–400.
Martin, E. W., & Shaheen, S. A. (2011). Greenhouse gas emission impacts of carsharing in North America. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1074–1086.
Newcomer, E. (2017). Lyft Gains on Uber in U.S. Business Travel, Doubling Share. Retrieved from https://www.bloomberg.com/news/articles/2018-04-30/lyft-gains-on-uber-in-u-s-business-travel-doubling-share
Oei, S.-Y., & Ring, D. M. (2017). The Tax Lives of Uber Drivers: Evidence from Internet Discussion Forums. Colum. J. Tax L., 8, 56.
Pang, B., & Lee, L. (2005). Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales. In Proceedings of the 43rd annual meeting on association for computational linguistics (pp. 115–124).
Pang, B., Lee, L., & others. (2008). Opinion mining and sentiment analysis. Foundations and Trends®in Information Retrieval, 2(1--2), 1–135.
Prabowo, R., & Thelwall, M. (2009). Sentiment analysis: A combined approach. Journal of Informetrics, 3(2), 143–157.
Rassman, C. L. (2014). Regulating rideshare without stifling innovation: Examining the drivers, the insurance gap, and why Pennsylvania should get on board. Pitt. J. Tech. L. & Pol’y, 15, 81.
Redfearn III, R. L. (2016). Sharing economy misclassification: Employees and independent contractors in transportation network companies. Berkeley Tech. LJ, 31, 1023.
Rideshare Central. (2017). Lyft Driver Promos vs. Uber Driver Promos. Retrieved from https://ridesharecentral.com/lyft-driver-promos-vs-uber-driver-promos
Rogers, B. (2015). The social costs of Uber. U. Chi. L. Rev. Dialogue, 82, 85.
Scheiber, N. (2017). How Uber uses psychological tricks to push its drivers’ buttons. The New York Times, 2.
Stiglic, M., Agatz, N., Savelsbergh, M., & Gradisar, M. (2016). Making dynamic ride-sharing work: The impact of driver and rider flexibility. Transportation Research Part E: Logistics and Transportation Review, 91, 190–207.
Truong, M., & Trivedi, R. (2017). Updates to the Rating System. Retrieved from https://www.uber.com/newsroom/ratingsupdate-2/
Uber. (2018). Car Offers, Wheels by the Week. Retrieved from https://www.uber.com/drive/vehicle-solutions/
Vinodhini, G., & Chandrasekaran, R. M. (2012). Sentiment analysis and opinion mining: a survey. International Journal, 2(6), 282–292.
Wang, M., & Mu, L. (2018). Spatial disparities of Uber accessibility: An exploratory analysis in Atlanta, USA. Computers, Environment and Urban Systems, 67, 169–175.
Woo, C., & Bales, R. A. (2017). The Uber Million Dollar Question: Are Uber Drivers Employees or Independent Contractors?
Ye, Q., Zhang, Z., & Law, R. (2009). Sentiment classification of online reviews to travel destinations by supervised machine learning approaches. Expert Systems with Applications, 36(3), 6527–6535.
Yu, X., Liu, Y., Huang, X., & An, A. (2012). Mining online reviews for predicting sales performance: A case study in the movie domain. IEEE Transactions on Knowledge and Data Engineering, 24(4), 720–734.