Managing price and service rate in customer-intensive services under social interactions
Abstract
This paper investigates the price and service rate decisions in a customer-intensive service in an M/M/1 queue system under the influence of social interactions, where a higher value of the service is perceived if more customers purchase the service. The customer-intensive nature of the service requires a low service speed to maintain its quality, which may increase the congestion of the system. Two cases where customers are either homogeneous or heterogeneous in terms of the customer intensity are considered. It is found that social interactions can always benefit the service provider as more expected revenue can be achieved, and potential profits would be lost if the influence of social interactions is ignored. For the case with heterogeneous customers, the optimal price and service rate decisions are solved with or without considering social interaction effect. The study finds the proportions of high and low sensitive customers and the social interaction intensity are critical to the operational decisions and the market coverage strategies. These results offer a better understanding on the interplay between the quality-speed conundrum and the influence of social interactions in customers’ purchase behaviour in managing customer-intensive services.
Keyword : Customer-intensive service, M/M/1 queue, Heterogeneous customers, Price, Service rate, Social interactions
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Ata, B., & Shneorson, S. (2006). Dynamic control of an M/M/1 service system with adjustable arrival and service rates. Management Science, 52(11), 1778-1791. https://doi.org/10.1287/mnsc.1060.0587
Bohlmann, R. N., Rosa, J. A., Bolton, R. N., & Qualls, W. J. (2006). The effect of group interactions on satisfaction judgment: satisfaction escalation. Marketing Science, 25(4), 301-321. https://doi.org/10.1287/mksc.1050.0182
Brock, W. A., & Durlauf, S. N. (2001). Discrete choice with social interactions. Review of Economic Studies, 68(2), 235-260. https://doi.org/10.1111/1467-937X.00168
Brock, W. A., & Durlauf, S. N. (2007). Identification of binary choice models with social interactions. Journal of Economics, 140(1), 52-75. https://doi.org/10.1016/j.jeconom.2006.09.002
Campbell, A. (2015). Word of mouth models for sales. Economics Letters, 133, 45-50. https://doi.org/10.1016/j.econlet.2015.04.019
Li, C., Jiang, M., & Yuan, X. (2018). Managing operations in customer-intensive services with forward-looking customers. Kybernetes, 47(10), 1941-1955. https://doi.org/10.1108/K-11-2017-0436
Godes, D. (2016). Product policy in markets with word-of-mouth communication. Management Science, 63(1), 267-278. https://doi.org/10.1287/mnsc.2015.2330
Ni, G., Xu, Y., & Dong, Y. (2013). Price and speed decisions in customer-intensive services with two classes of customers. European Journal of Operational Research, 228(2), 427-436. https://doi.org/10.1016/j.ejor.2013.01.053
Hanson, W. A., & Puter, D. S. (1996). Hits and misses: herb behavior and online product popularity. Marketing Letters, 7(4), 297-305. https://doi.org/10.1007/BF00435537
Hartmann, W. R. (2010). Demand estimation with social interactions and the implications for targeted marketing. Marketing Science, 29(4), 585-601. https://doi.org/10.1287/mksc.1100.0559
Hassin, R., & Haviv, M. (2003). To queue or not to queue: equilibrium behavior in queuing systems (1st ed.). Norwell: Kluwer Academic Publishers. https://doi.org/10.1007/978-1-4615-0359-0
Kostami, V., Kostamis, D., & Ziya, S. (2017). Pricing and capacity allocation for shared services. Manufacturing and Service Operations Management, 19(2), 230-245. https://doi.org/10.1287/msom.2016.0606
Marand, A. J., Tang, O., & Li, H. (2019). Quandary of service logistics: fast or reliable? European Journal of Operational Research, 275(3), 983-996. https://doi.org/10.1016/j.ejor.2018.12.007
Moretti, E. (2011). Social learning and peer effects in consumption: evidence from movie sales. Review of Economic Studies, 78(1), 356-393. https://doi.org/10.1093/restud/rdq014
Nie, P. Y., Wang, C., & Yang, Y. C. (2019). Vertical integration maintenance commitments. Journal of Retailing and Consumer Services, 47, 11-16. https://doi.org/10.1016/j.jretconser.2018.10.008
Onnela, J-P., Reed-Tsochas, F., & Stanley, H. E. (2010). Spontaneous emergence of social influence in online system. Proceedings of the National Academy of Sciences of the United States of America, 107(43), 18375-18380. https://doi.org/10.1073/pnas.0914572107
Papanastasiou, Y., & Savva, N. (2017). Dynamic pricing in the presence of social learning and strategic consumers. Management Science, 63(4), 919-939. https://doi.org/10.1287/mnsc.2015.2378
Qiu, L., & Whinston, A. B. (2017). Operational strategies under behavioral observational learning in social networks. Production and Operations Management, 26(7), 1249-1267. https://doi.org/10.1111/poms.12693
Simonsohn, U., & Ariely, D. (2008). When rational sellers face nonrational buyers: evidence from herding on eBay. Management Science, 54(9), 1624-1637. https://doi.org/10.1287/mnsc.1080.0881
Spathis, C., Petridou, E., & Glaveli, N. (2004). Managing service quality in banks: customers’ gender effects. Managing Service Quality: An International Journal, 14(1), 90-102. https://doi.org/10.1108/09604520410513695
Stidham, S. (2002). Analysis, design, and control of queueing systems. Operations Research, 50(1), 197-216. https://doi.org/10.1287/opre.50.1.197.17783
Veeraraghavan, S., & Debo, L. (2009). Joining longer queues: information externalities in queue choice. Manufacturing and Service Operations Management, 11(4), 543-562. https://doi.org/10.1287/msom.1080.0239
Li, X., Guo, P., & Lian, Z. (2016). Quality-speed competition in customer-intensive services with boundedly rational customers. Production and Operations Management, 25(11), 1885-1901. https://doi.org/10.1111/poms.12583
Li, X., Li, Q., Guo, P., & Lian, Z. (2017). On the uniqueness and stability of equilibrium in quality-speed competition with boundedly-rational customers: The case with general reward function and multiple servers. International Journal of Production Economics, 193, 726-736. https://doi.org/10.1016/j.ijpe.2017.08.026
Yu, M., Debo, L., & Kapuscinski, R. (2016). Strategic waiting for consumer-generated quality information: dynamic pricing of new experience goods. Management Science, 62(2), 410-435. https://doi.org/10.1287/mnsc.2014.2134
Yuan, X., & Hwarng, H. B. (2018). Managing a service system under the influence of social interactions. Working paper. Singapore University of Social Sciences.
Zhang, J., Liu, Y., & Chen, Y. (2015). Social learning in networks of friends versus strangers. Marketing Science, 34(4), 573-589. https://doi.org/10.1287/mksc.2015.0902