Upfront Commitment in Online Resource Allocation with Patient Customers
Published Online:4 Sep 2025https://doi.org/10.1287/mnsc.2022.03335
References
- (2021) Strategic timing and dynamic pricing for online resource allocation. Management Sci. 67(8):4880–4907.Link, Google Scholar
- (2020) Thickness and information in dynamic matching markets. J. Political Econom. 128(3):783–815.Crossref, Google Scholar
- (2020) Dynamic stochastic matching under limited time. Proc. 21st ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 789–790.Google Scholar
- (2004) On customer contact centers with a call-back option: Customer decisions, routing rules, and system design. Oper. Res. 52(2):271–292.Link, Google Scholar
- (2020) Online resource allocation with limited flexibility. Management Sci. 66(2):642–666.Link, Google Scholar
- (2017) Min-cost bipartite perfect matching with delays. Approximation, Random. Combinatorial Optim. Algorithms Techniques (APPROX/RANDOM 2017) 81:1–1. Google Scholar
- (2015) Truthful online scheduling with commitments. Proc. 16th ACM Conf. Econom. Comput., 715–732.Google Scholar
- (2009) Toward robust revenue management: Competitive analysis of online booking. Oper. Res. 57(4):950–963.Link, Google Scholar
- (2023) Single-leg revenue management with advice. Proc. 24th ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 207.Google Scholar
- (2013) Fairness, efficiency, and flexibility in organ allocation for kidney transplantation. Oper. Res. 61(1):73–87.Link, Google Scholar
- (2006) An integrated approach to single-leg airline revenue management: The role of robust optimization. Technical report, Erasmus Research Institute of Management, Rotterdam, Netherlands.Google Scholar
- (2020) Matching queues, flexibility and incentives. Preprint, submitted June 26, https://arxiv.org/pdf/2006.08863v3.Google Scholar
- (2017) Stability of service under time-of-use pricing. Proc. 49th Annual ACM SIGACT Sympos. Theory Comput. (Association for Computing Machinery, New York), 184–197.Google Scholar
- (2004) Multi-processor scheduling to minimize flow time with ϵ resource augmentation. Proc. 36th Annual ACM Sympos. Theory Comput. (Association for Computing Machinery, New York), 363–372.Google Scholar
- (2018) Robust dynamic pricing with strategic customers. Math. Oper. Res. 43(4):1119–1142.Link, Google Scholar
- (2019) Optimal design of process flexibility for general production systems. Oper. Res. 67(2):516–531.Abstract, Google Scholar
- (2016) Sparse process flexibility designs: Is the long chain really optimal? Oper. Res. 64(2):416–431.Link, Google Scholar
- (2023) Understanding the value of fulfillment flexibility in an online retailing environment. Manufacturing Service Oper. Management 25(2):391–408.Link, Google Scholar
- (2019) On-demand service sharing with collective dynamic pricing. Preprint, submitted January 20, https://doi.org/10.2139/ssrn.3403232.Google Scholar
- (2015) Retailing with opaque products. Preprint, submitted September 11, https://doi.org/10.2139/ssrn.2659211.Google Scholar
- (2019) The value of flexibility from opaque selling. Preprint, submitted November 19, https://doi.org/10.2139/ssrn.3483872.Google Scholar
- (2021) Batching and optimal multi-stage bipartite allocations. Proc. 12th Innovations Theoret. Comput. Sci. Conf. (Schloss Dagstuhl-Leibniz-Zentrum für Informatik, Wadern, Germany).Google Scholar
- (2004) Revenue management of flexible products. Manufacturing Service Oper. Management 6(4):321–337.Link, Google Scholar
- (2015) Online resource allocation with customer choice. Preprint, submitted November 5, https://arxiv.org/abs/1511.01837.Google Scholar
- (1996) Reservation planning for elective surgery under uncertain demand for emergency surgery. Management Sci. 42(3):321–334.Link, Google Scholar
- (2023a) Online resource allocation with samples. Preprint, submitted June 21, https://arxiv.org/abs/2306.12282.Google Scholar
- (2023b) Online resource allocation with convex-set machine-learned advice. Preprint, submitted June 21, https://arxiv.org/abs/2306.12282.Google Scholar
- (2020) Dynamic pricing for heterogeneous time-sensitive customers. Manufacturing Service Oper. Management 22(3):562–581.Link, Google Scholar
- (2014) Real-time optimization of personalized assortments. Management Sci. 60(6):1532–1551.Link, Google Scholar
- (2022) Dynamic type matching. Manufacturing Service Oper. Management 24(1):125–142.Link, Google Scholar
- (2013) Multiresource allocation scheduling in dynamic environments. Manufacturing Service Oper. Management 15(2):280–291.Link, Google Scholar
- (2021) Online resource allocation under partially predictable demand. Oper. Res. 69(3):895–915.Google Scholar
- (2017) Ride solo or pool: The impact of sharing on optimal pricing of ride-sharing services. Preprint, submitted July 28, https://doi.org/10.2139/ssrn.3008136.Google Scholar
- (2008) Generalized online routing: New competitive ratios, resource augmentation, and asymptotic analyses. Oper. Res. 56(3):745–757.Link, Google Scholar
- (1995) Principles on the benefits of manufacturing process flexibility. Management Sci. 41(4):577–594.Link, Google Scholar
- (2000) Speed is as powerful as clairvoyance. J. ACM 47(4):617–643.Crossref, Google Scholar
- (2005) Pricing strategies and service differentiation in queues—A profit maximization perspective. Working paper, Department of Industrial Engineering and Operations Research, Columbia University, New York.Google Scholar
- (2001) Scheduling and reliable lead-time quotation for orders with availability intervals and lead-time sensitive revenues. Management Sci. 47(2):264–279.Link, Google Scholar
- (1972) Forecasting and control of passenger bookings. AGIFORS Sympos. Proc. 12:95–117.Google Scholar
- (2020) Dynamic pricing with heterogeneous patience levels. Oper. Res. 68(4):1038–1046.Link, Google Scholar
- (2015) Reliable facility location design under uncertain correlated disruptions. Manufacturing Service Oper. Management 17(4):445–455.Link, Google Scholar
- (2021) On policies for single-leg revenue management with limited demand information. Oper. Res. 69(1):207–226.Link, Google Scholar
- (2020) An approximation algorithm for network revenue management under nonstationary arrivals. Oper. Res. 68(3):834–855.Link, Google Scholar
- (2009) Stochastic programming approach to process flexibility design. Flexible Services Manufacturing J. 21(3):75–91.Crossref, Google Scholar
- (2010) Robust controls for network revenue management. Manufacturing Service Oper. Management 12(1):56–76.Link, Google Scholar
- (2012) Using flexible products to cope with demand uncertainty in revenue management. OR Spectrum 34(1):215–242.Crossref, Google Scholar
- (2002) Optimal time-critical scheduling via resource augmentation. Algorithmica 32(2):163–200.Crossref, Google Scholar
- (2021) Resource augmentation. Beyond the Worst-Case Analysis of Algorithms (Cambridge University Press, Cambridge, UK), 72.Google Scholar
- (2019) Reliable flexibility design of supply chains via extended probabilistic expanders. Production Oper. Management 28(3):700–720.Crossref, Google Scholar
- (2012) Understanding the performance of the long chain and sparse designs in process flexibility. Oper. Res. 60(5):1125–1141.Link, Google Scholar
- (2015) Worst-case analysis of process flexibility designs. Oper. Res. 63(1):166–185.Link, Google Scholar
- (2011) Order acceptance and scheduling: A taxonomy and review. Eur. J. Oper. Res. 212(1):1–11.Crossref, Google Scholar
- (2018) A review of choice-based revenue management: Theory and methods. Eur. J. Oper. Res. 271(2):375–387.Crossref, Google Scholar
- (2021) Near-optimal primal-dual algorithms for quantity-based network revenue management. Preprint, submitted January 6, https://doi.org/10.2139/ssrn.3728397.Google Scholar
- (1998) An analysis of bid-price controls for network revenue management. Management Sci. 44(11-part-1):1577–1593.Link, Google Scholar
- (2004) Revenue management under a general discrete choice model of consumer behavior. Management Sci. 50(1):15–33.Link, Google Scholar
- (2012) Ordering, pricing, and lead-time quotation under lead-time and demand uncertainty. Production Oper. Management 21(3):576–589.Crossref, Google Scholar
- (2025) The benefits of delay to online decision-making. Management Sci., ePub ahead of print August 6, https://doi.org/10.1287/mnsc.2023.00549.Google Scholar

