Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers’ Supply

References

• Afèche P, Liu Z, Maglaras C (2023) Ride-hailing networks with strategic drivers: The impact of platform control capabilities on performance. Manufacturing Service Oper. Management 25(5):1890–1908.Link, Google Scholar
• Allon G, Cohen MC, Sinchaisri WP (2023) The impact of behavioral and economic drivers on gig economy workers. Manufacturing Service Oper. Management 25(4):1376–1393.Link, Google Scholar
• Asadpour A, Lobel I, van Ryzin G (2023) Minimum earnings regulation and the stability of marketplaces. Manufacturing Service Oper. Management 25(1):254–265.Link, Google Scholar
• Avedian S (2020) Uber & Lyft are locking drivers out in New York City. Accessed May 1, 2024, https://therideshareguy.com/nyc-uber-lyft-driver-lockout/.Google Scholar
• Baker KR (1974) Scheduling a full-time workforce to meet cyclic staffing requirements. Management Sci. 20(12):1561–1568.Link, Google Scholar
• Balseiro SR, Brown DB, Chen C (2021) Dynamic pricing of relocating resources in large networks. Management Sci. 67(7):4075–4094.Link, Google Scholar
• Benjaafar S, Ding JY, Kong G, Taylor T (2022) Labor welfare in on-demand service platforms. Manufacturing Service Oper. Management 24(1):110–124.Link, Google Scholar
• Bernstein F, DeCroix GA, Keskin NB (2021) Competition between two-sided platforms under demand and supply congestion effects. Manufacturing Service Oper. Management 23(5):1043–1061.Link, Google Scholar
• Besbes O, Castro F, Lobel I (2021) Surge pricing and its spatial supply response. Management Sci. 67(3):1350–1367.Link, Google Scholar
• Besbes O, Castro F, Lobel I (2022) Spatial capacity planning. Oper. Res. 70(2):1271–1291.Link, Google Scholar
• Bimpikis K, Candogan O, Saban D (2019) Spatial pricing in ride-sharing networks. Oper. Res. 67(3):744–769.Link, Google Scholar
• Cachon GP, Daniels KM, Lobel R (2017) The role of surge pricing on a service platform with self-scheduling capacity. Manufacturing Service Oper. Management 19(3):368–384.Link, Google Scholar
• Castillo-Salazar JA, Landa-Silva D, Qu R (2016) Workforce scheduling and routing problems: Literature survey and computational study. Ann. Oper. Res. 239(1):39–67.Crossref, Google Scholar
• Dantzig GB (1954) Letter to the editor-A comment on Edie’s “Traffic delays at toll booths”. J. OR Soc. Amer. 2(3):339–341.Abstract, Google Scholar
• Day PR, Ryan DM (1997) Flight attendant rostering for short-haul airline operations. Oper. Res. 45(5):649–661.Link, Google Scholar
• DFHV (2019) DFHV dashboard and statistical data sets. Accessed May 1, 2024, https://dfhv.dc.gov/page/dfhv-dashboard-and-statistical-data-sets.Google Scholar
• DoorDash (2023) Behind the dash: Insights into the flexibility and freedom of dashing. Accessed May 1, 2024, https://about.doordash.com/en-us/news/insights-into-the-flexibility-and-freedom-of-dashing.Google Scholar
• Edie LC (1954) Traffic delays at toll booths. J. OR Soc. Amer. 2(2):107–138.Abstract, Google Scholar
• Freund D, Hssaine C (2021) Fair incentives for repeated engagement. Preprint, submitted October 28, https://arxiv.org/abs/2111.00002.Google Scholar
• Gans N, Koole G, Mandelbaum A (2003) Telephone call centers: Tutorial, review, and research prospects. Manufacturing Service Oper. Management 5(2):79–141.Link, Google Scholar
• Gurvich I, Lariviere M, Moreno A (2019) Operations in the On-Demand Economy: Staffing Services with Self-Scheduling Capacity. Sharing Economy (Springer, Cham, Switzerland), 249–278.Google Scholar
• Hall JV, Krueger AB (2018) An analysis of the labor market for Uber’s driver-partners in the United States. Indust. Labor Relat. Rev. 71(3):705–732.Crossref, Google Scholar
• Hall J, Horton J, Knoepfle D (2023) Ride-sharing markets re-equilibriate. NBER Working Paper No. 30883, National Bureau of Economic Research, Cambridge, MA.Google Scholar
• Hassin R, Nathaniel A (2021) Self-selected task allocation. Manufacturing Service Oper. Management 23(6):1669–1682.Link, Google Scholar
• Heydenreich B, Müller R, Uetz M (2007) Games and mechanism design in machine scheduling-an introduction. Production Oper. Management 16(4):437–454.Crossref, Google Scholar
• Hsu WL (1984) Approximation algorithms for the assembly line crew scheduling problem. Math. Oper. Res. 9(3):376–383.Link, Google Scholar
• Hu M, Zhou Y (2020) Price, wage and fixed commission in on-demand matching. Preprint, submitted August 31, https://dx.doi.org/10.2139/ssrn.2949513.Google Scholar
• Krishnan V, Iglesias R, Martin S, Wang S, Pattabhiraman V, Van Ryzin G (2022) Solving the ride-sharing productivity paradox: Priority dispatch and optimal priority sets. INFORMS J. Applied Anal. 52(5):433–445.Link, Google Scholar
• Lobel I, Martin S (2024) Detours in shared rides. Management Sci., ePub ahead of print, May 17, https://doi.org/10.1287/mnsc.2020.03125.Link, Google Scholar
• Lobel I, Martin S, Song H (2024) Employees, contractors, or hybrid: An operational perspective. Manufacturing Service Oper. Management 26(4):1189–1585.Link, Google Scholar
• Mao W, Ming L, Rong Y, Tang CS, Zheng H (2022) On-demand meal delivery platforms: Operational level data and research opportunities. Manufacturing Service Oper. Management 24(5):2535–2542.Link, Google Scholar
• Nisan N, Ronen A (2001) Algorithmic mechanism design. Games Econom. Behav. 35(1–2):166–196.Crossref, Google Scholar
• Ongweso E Jr, French H (2020) The lockout: Why Uber drivers in NYC are sleeping in their cars. Accessed May 1, 2024, https://www.vice.com/en_us/article/pkewqb/the-lockout-why-uber-drivers-in-nyc-are-sleeping-in-their-cars.Google Scholar
• Parrott JA, Reich M (2018) An earnings standard for New York City’s app-based drivers. Accessed May 1, 2024, https://www.centernyc.org/an-earnings-standard.Google Scholar
• Parrott J, Reich M (2020) A minimum compensation standard for Seattle TNC drivers. Accessed May 1, 2024, https://www.seattle.gov/documents/Departments/LaborStandards/Parrott-Reich-Seattle-Report_July-2020%280%29.pdf.Google Scholar
• Schneider T (2020) Taxi and ridehailing usage in New York City. Accessed May 1, 2024, https://toddwschneider.com/dashboards/nyc-taxi-ridehailing-uber-lyft-data/.Google Scholar
• Segal M (1974) The operator-scheduling problem: A network-flow approach. Oper. Res. 22(4):808–823.Link, Google Scholar
• SFCTA (2017) TNCs today. Accessed May 1, 2024, http://tncstoday.sfcta.org/.Google Scholar
• Taylor TA (2018) On-demand service platforms. Manufacturing Service Oper. Management 20(4):704–720.Link, Google Scholar
• TheExpressWire (2020) Ride sharing market. Accessed May 1, 2024, https://www.theexpresswire.com/pressrelease/Ride-Sharing-Market-2020-Global-Industry-Size-Share-Future-Challenges-Revenue-Demand-Industry-Growth-and-Top-Players-Uber-Lyft-Fasten-Analysis-to-2026_11402466.Google Scholar
• TLC (2018) NYC Taxi & Limousine Commission fact book. Accessed May 1, 2024, https://www1.nyc.gov/assets/tlc/downloads/pdf/2018_tlc_factbook.pdf.Google Scholar
• Via (2020) Earn hourly with Via Blue. Accessed May 1, 2024, https://drivewithvia.com/push/37830-copy/.Google Scholar
• Walmart (2018) New scheduling system gives associates more consistency and flexibility. Accessed May 1, 2024, https://corporate.walmart.com/newsroom/2018/11/13/new-scheduling-system-gives-associates-more-consistency-and-flexibility.Google Scholar
• Warner DM, Prawda J (1972) A mathematical programming model for scheduling nursing personnel in a hospital. Management Sci. 19(4-part-1):411–422.Link, Google Scholar
• Zhou Q, Wang J, Du J (2021) Balancing supply with demand in ride-hailing platforms: An operational approach. Preprint, submitted May 27, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3851162.Google Scholar