IDEAS home Printed from https://ideas.repec.org/r/inm/oropre/v59y2011i6p1382-1394.html
   My bibliography  Save this item

“We Will Be Right with You”: Managing Customer Expectations with Vague Promises and Cheap Talk

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Tesnim Naceur & Yezekael Hayel, 2020. "Deterministic state-based information disclosure policies and social welfare maximization in strategic queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 96(3), pages 303-328, December.
  2. Johan, Sofia & Zhang, Yelin, 2020. "Quality revealing versus overstating in equity crowdfunding," Journal of Corporate Finance, Elsevier, vol. 65(C).
  3. Colm Crowley & Steven Guitron & Joseph Son & Oleg S Pianykh, 2020. "Modeling workflows: Identifying the most predictive features in healthcare operational processes," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
  4. Noam Shamir & Hyoduk Shin, 2016. "Public Forecast Information Sharing in a Market with Competing Supply Chains," Management Science, INFORMS, vol. 62(10), pages 2994-3022, October.
  5. Siddharth Prakash Singh & Mohammad Delasay & Alan Scheller‐Wolf, 2023. "Real‐time delay announcement under competition," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 863-881, March.
  6. Philipp Afèche & Opher Baron & Yoav Kerner, 2013. "Pricing Time-Sensitive Services Based on Realized Performance," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 492-506, July.
  7. Dennis J. Zhang & Gad Allon & Jan A. Van Mieghem, 2017. "Does Social Interaction Improve Learning Outcomes? Evidence from Field Experiments on Massive Open Online Courses," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 347-367, July.
  8. Ruomeng Cui & Jun Li & Dennis J. Zhang, 2020. "Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb," Management Science, INFORMS, vol. 66(3), pages 1071-1094, March.
  9. Erjie Ang & Sara Kwasnick & Mohsen Bayati & Erica L. Plambeck & Michael Aratow, 2016. "Accurate Emergency Department Wait Time Prediction," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 141-156, February.
  10. Oded Berman & Mohammad M. Fazel-Zarandi & Dmitry Krass, 2019. "Truthful Cheap Talk: Why Operational Flexibility May Lead to Truthful Communication," Management Science, INFORMS, vol. 65(4), pages 1624-1641, April.
  11. Rouba Ibrahim, 2018. "Sharing delay information in service systems: a literature survey," Queueing Systems: Theory and Applications, Springer, vol. 89(1), pages 49-79, June.
  12. Meijian Yang & Enjun Xia & Yang Yang, 2023. "Deterring Sellers’ Cheap Talk Actions via Online Rating Schemes," Mathematics, MDPI, vol. 11(6), pages 1-16, March.
  13. Jerry Anunrojwong & Krishnamurthy Iyer & Vahideh Manshadi, 2023. "Information Design for Congested Social Services: Optimal Need-Based Persuasion," Management Science, INFORMS, vol. 69(7), pages 3778-3796, July.
  14. Kimon Drakopoulos & Shobhit Jain & Ramandeep Randhawa, 2021. "Persuading Customers to Buy Early: The Value of Personalized Information Provisioning," Management Science, INFORMS, vol. 67(2), pages 828-853, February.
  15. Qiuping Yu & Yiming Zhang & Yong-Pin Zhou, 2022. "Delay Information in Virtual Queues: A Large-Scale Field Experiment on a Major Ride-Sharing Platform," Management Science, INFORMS, vol. 68(8), pages 5745-5757, August.
  16. Aurora García-Gallego & Penélope Hernández-Rojas & Amalia Rodrigo-González, 2019. "Efficient coordination in the lab," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(1), pages 175-201, March.
  17. Harish Guda & Milind Dawande & Ganesh Janakiraman, 2023. "The economics of process transparency," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1812-1829, June.
  18. Anglin, Aaron H. & Short, Jeremy C. & Drover, Will & Stevenson, Regan M. & McKenny, Aaron F. & Allison, Thomas H., 2018. "The power of positivity? The influence of positive psychological capital language on crowdfunding performance," Journal of Business Venturing, Elsevier, vol. 33(4), pages 470-492.
  19. Hoseinpour, Pooya & Jalili Marand, Ata, 2022. "Designing a service system with price- and distance-sensitive demand: A case study in mining industry," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1355-1371.
  20. Lu, Yuwei & Xie, Xiaolan & Jiang, Zhibin, 2018. "Dynamic appointment scheduling with wait-dependent abandonment," European Journal of Operational Research, Elsevier, vol. 265(3), pages 975-984.
  21. Qiuping Yu & Gad Allon & Achal Bassamboo, 2017. "How Do Delay Announcements Shape Customer Behavior? An Empirical Study," Management Science, INFORMS, vol. 63(1), pages 1-20, January.
  22. Dimitrios Logothetis & Antonis Economou, 2023. "The impact of information on transportation systems with strategic customers," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2189-2206, July.
  23. Pengfei Guo & Moshe Haviv & Zhenwei Luo & Yulan Wang, 2022. "Optimal queue length information disclosure when service quality is uncertain," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 1912-1927, May.
  24. Vasiliki Kostami, 2020. "Price and Lead time Disclosure Strategies in Inventory Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2760-2788, December.
  25. David Lingenbrink & Krishnamurthy Iyer, 2019. "Optimal Signaling Mechanisms in Unobservable Queues," Operations Research, INFORMS, vol. 67(5), pages 1397-1416, September.
  26. Robert J. Batt & Christian Terwiesch, 2015. "Waiting Patiently: An Empirical Study of Queue Abandonment in an Emergency Department," Management Science, INFORMS, vol. 61(1), pages 39-59, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.