Skip to main content
Top
Published in: Electronic Commerce Research 4/2020

21-07-2018

Allocating resources for a restaurant that serves regular and group-buying customers

Authors: Tianhua Zhang, Juliang Zhang, Fu Zhao, Yihong Ru, John W. Sutherland

Published in: Electronic Commerce Research | Issue 4/2020

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Restaurants in China have recently begun offering group-buying (GB) options on the internet as a marketing and advertising tool to attract customers. GB coupon is available to parties of any size and the groups do not need to go together to the restaurants. Such restaurants serve two types of customers: GB customers with GB coupons and regular customers without coupons. One common practice for these restaurants is to set a maximum number of tables for each type of customer in advance and ask customers to wait in separate queues when all the tables for that customer type are occupied. As a result, restaurants are interested in finding optimal table allocation to serve the two types of customers to maximize profits. Since customers come follow a stochastic and discrete process, eat on a table that can be regarded as being served by a server in a queueing system, and wait in the queue when the restaurant is full, the dining process of customers and operating process of the restaurant is suitable to be described by queueing system. So, this study applies queueing theory to examine the table allocation problem. The effects of customer related parameters such as arrival rate and patience degree on the optimal allocation are discussed. The simulation model is extended to consider customers arriving in parties of different and serving tables of different sizes. We find that for a specific type of customer, if the arrival rate increases, the number of tables allocated for them increases. Patience degree has opposite influences on table allocation for the two types of customers: if regular customers are not patient, more tables should be allocated to them; while if GB customers are not patient, less tables should be allocated to them. If considering different customer party sizes and table sizes, as the arrival rate of regular customer increases, number of GB table decreases, number of tables for large (small) regular party first decreases (increases) and then increases (decreases).

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Wang, J. J., Zhao, X., & Li, J. J. (2013). Group buying: A strategic form of consumer collective. Journal of Retailing, 89(3), 338–351. Wang, J. J., Zhao, X., & Li, J. J. (2013). Group buying: A strategic form of consumer collective. Journal of Retailing, 89(3), 338–351.
2.
go back to reference Jing, X., & Xie, J. (2011). Group buying: A new mechanism for selling through social interactions. Management Science, 57(8), 1354–1372. Jing, X., & Xie, J. (2011). Group buying: A new mechanism for selling through social interactions. Management Science, 57(8), 1354–1372.
3.
go back to reference Heo, C. Y. (2016). Exploring group-buying platforms for restaurant revenue management. International Journal of Hospitality Management, 52, 154–159. Heo, C. Y. (2016). Exploring group-buying platforms for restaurant revenue management. International Journal of Hospitality Management, 52, 154–159.
4.
go back to reference Ni, G., Luo, L., Xu, Y., Xu, J., & Dong, Y. (2015). Optimal decisions on group buying option with a posted retail price and heterogeneous demand. Electronic Commerce Research and Applications, 14(1), 23–33. Ni, G., Luo, L., Xu, Y., Xu, J., & Dong, Y. (2015). Optimal decisions on group buying option with a posted retail price and heterogeneous demand. Electronic Commerce Research and Applications, 14(1), 23–33.
5.
go back to reference Gross, D., Shortle, J. F., Thompson, J. M., & Harris, C. M. (2008). Fundamentals of queueing theory. Hoboken: Wileys. Gross, D., Shortle, J. F., Thompson, J. M., & Harris, C. M. (2008). Fundamentals of queueing theory. Hoboken: Wileys.
6.
go back to reference Lu, Y., Musalem, A., Olivares, M., & Schilkrut, A. (2013). Measuring the effect of queues on customer purchases. Management Science, 59(8), 1743–1763. Lu, Y., Musalem, A., Olivares, M., & Schilkrut, A. (2013). Measuring the effect of queues on customer purchases. Management Science, 59(8), 1743–1763.
7.
go back to reference Sutherland, B. (2010). It’s a half-price kind of world: Millions of bargain hunters flock to online coupon sites like Groupon. com for deep discounts in everything from haircuts to meals. McClatchy-Tribune Business News (p. 7). Washington: Publicación del. Sutherland, B. (2010). It’s a half-price kind of world: Millions of bargain hunters flock to online coupon sites like Groupon. com for deep discounts in everything from haircuts to meals. McClatchy-Tribune Business News (p. 7). Washington: Publicación del.
8.
go back to reference Che, T., Peng, Z., & Hua, Z. (2016). Characteristics of online group-buying website and consumers intention to revisit: The moderating effects of visit channels. Electronic Commerce Research, 16(2), 171–188. Che, T., Peng, Z., & Hua, Z. (2016). Characteristics of online group-buying website and consumers intention to revisit: The moderating effects of visit channels. Electronic Commerce Research, 16(2), 171–188.
9.
go back to reference Liu, Y., & Sutanto, J. (2015). Online group-buying: Literature review and directions for future research. ACM SIGMIS Database, 46(1), 39–59. Liu, Y., & Sutanto, J. (2015). Online group-buying: Literature review and directions for future research. ACM SIGMIS Database, 46(1), 39–59.
10.
go back to reference Ke, C., Yan, B., & Xu, R. (2016). A group-buying mechanism for considering strategic consumer behavior. Electronic Commerce Research, 17(4), 1–32. Ke, C., Yan, B., & Xu, R. (2016). A group-buying mechanism for considering strategic consumer behavior. Electronic Commerce Research, 17(4), 1–32.
11.
go back to reference Chen, J., Guan, L., & Cai, X. (2017). Analysis on buyers’ cooperative strategy under group-buying price mechanism. Journal of Industrial & Management Optimization, 9(2), 291–304. Chen, J., Guan, L., & Cai, X. (2017). Analysis on buyers’ cooperative strategy under group-buying price mechanism. Journal of Industrial & Management Optimization, 9(2), 291–304.
12.
go back to reference Chen, J., Chen, X., & Song, X. (2007). Comparison of the group-buying auction and the fixed pricing mechanism. Decision Support Systems, 43(2), 445–459. Chen, J., Chen, X., & Song, X. (2007). Comparison of the group-buying auction and the fixed pricing mechanism. Decision Support Systems, 43(2), 445–459.
13.
go back to reference Liu, Y., & Sutanto, J. (2012). Buyers’ purchasing time and herd behavior on deal-of-the-day group-buying websites. Electronic Markets, 22(2), 83–93. Liu, Y., & Sutanto, J. (2012). Buyers’ purchasing time and herd behavior on deal-of-the-day group-buying websites. Electronic Markets, 22(2), 83–93.
14.
go back to reference Anand, K. S., & Aron, R. (2003). Group buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11), 1546–1562. Anand, K. S., & Aron, R. (2003). Group buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11), 1546–1562.
15.
go back to reference Chen, J., Chen, X., Kauffman, R. J., & Song, X. (2009). Should we collude? Analyzing the benefits of bidder cooperation in online group-buying auctions. Electronic Commerce Research and Applications, 8(4), 191–202. Chen, J., Chen, X., Kauffman, R. J., & Song, X. (2009). Should we collude? Analyzing the benefits of bidder cooperation in online group-buying auctions. Electronic Commerce Research and Applications, 8(4), 191–202.
16.
go back to reference Chen, J., Liu, Y., & Xiping, S. (2004). Group-buying online auction and optimal inventory policy in uncertain market. Journal of Systems Science and Systems Engineering, 13(2), 202–218. Chen, J., Liu, Y., & Xiping, S. (2004). Group-buying online auction and optimal inventory policy in uncertain market. Journal of Systems Science and Systems Engineering, 13(2), 202–218.
17.
go back to reference Kimes, S. E., & Renaghan, L. M. (2011). The role of space in revenue management. In I. Yeoman & U. McMahon-Beattie (Eds.), Revenue management (pp. 17–28). Basingstoke: Palgrave Macmillan. Kimes, S. E., & Renaghan, L. M. (2011). The role of space in revenue management. In I. Yeoman & U. McMahon-Beattie (Eds.), Revenue management (pp. 17–28). Basingstoke: Palgrave Macmillan.
18.
go back to reference Kimes, S. E., Wirtz, J., & Noone, B. M. (2002). How long should dinner take? Measuring expected meal duration for restaurant revenue management. Journal of Revenue and Pricing Management, 1(3), 220–233. Kimes, S. E., Wirtz, J., & Noone, B. M. (2002). How long should dinner take? Measuring expected meal duration for restaurant revenue management. Journal of Revenue and Pricing Management, 1(3), 220–233.
19.
go back to reference Zentner, M., Grandjean, D., & Scherer, K. R. (2008). Emotions evoked by the sound of music: Characterization, classification, and measurement. Emotion, 8(4), 494–521. Zentner, M., Grandjean, D., & Scherer, K. R. (2008). Emotions evoked by the sound of music: Characterization, classification, and measurement. Emotion, 8(4), 494–521.
20.
go back to reference Stroebele, N., & De-Castro, J. (2006). Listening to music while eating is related to increases in people’s food intake and meal duration. Appetite, 47(3), 285–289. Stroebele, N., & De-Castro, J. (2006). Listening to music while eating is related to increases in people’s food intake and meal duration. Appetite, 47(3), 285–289.
21.
go back to reference Milliman, R. E. (1986). The influence of background music on the behavior of restaurant patrons. Journal of Consumer Research, 13(2), 286–289. Milliman, R. E. (1986). The influence of background music on the behavior of restaurant patrons. Journal of Consumer Research, 13(2), 286–289.
22.
go back to reference Bell, R., & Pliner, P. L. (2003). Time to eat: The relationship between the number of people eating and meal duration in three lunch settings. Appetite, 41(2), 215–218. Bell, R., & Pliner, P. L. (2003). Time to eat: The relationship between the number of people eating and meal duration in three lunch settings. Appetite, 41(2), 215–218.
23.
go back to reference Clendenen, V. I., Peter Herman, C., & Polivy, J. (1994). Social facilitation of eating among friends and strangers. Appetite, 23(1), 1–13. Clendenen, V. I., Peter Herman, C., & Polivy, J. (1994). Social facilitation of eating among friends and strangers. Appetite, 23(1), 1–13.
24.
go back to reference Kimes, S. E., & Robson, S. K. (2004). The impact of restaurant table characteristics on meal duration and spending. Cornell Hotel and Restaurant Administration Quarterly, 45(4), 333–346. Kimes, S. E., & Robson, S. K. (2004). The impact of restaurant table characteristics on meal duration and spending. Cornell Hotel and Restaurant Administration Quarterly, 45(4), 333–346.
25.
go back to reference Heo, C. Y., Lee, S., Mattila, A., & Hu, C. (2013). Restaurant revenue management: Do perceived capacity scarcity and price differences matter? International Journal of Hospitality Management, 35(5), 316–326. Heo, C. Y., Lee, S., Mattila, A., & Hu, C. (2013). Restaurant revenue management: Do perceived capacity scarcity and price differences matter? International Journal of Hospitality Management, 35(5), 316–326.
26.
go back to reference Kimes, S. E., & Wirtz, J. (2002). Perceived fairness of demand-based pricing for restaurants. Cornell Hotel & Restaurant Administration Quarterly, 43(1), 31–37. Kimes, S. E., & Wirtz, J. (2002). Perceived fairness of demand-based pricing for restaurants. Cornell Hotel & Restaurant Administration Quarterly, 43(1), 31–37.
27.
go back to reference Kelly, T. J., Kiefer, N. M., & Burdett, K. (1994). A demand-based approach to menu pricing. Cornell Hotel & Restaurant Administration Quarterly, 35(1), 48–52. Kelly, T. J., Kiefer, N. M., & Burdett, K. (1994). A demand-based approach to menu pricing. Cornell Hotel & Restaurant Administration Quarterly, 35(1), 48–52.
28.
go back to reference White, Camilla. (2008). Pricing strategies in the restaurant industry. Scandinavian Journal of Hospitality and Tourism, 8(3), 251–269. White, Camilla. (2008). Pricing strategies in the restaurant industry. Scandinavian Journal of Hospitality and Tourism, 8(3), 251–269.
29.
go back to reference Hwang, J. (2008). Restaurant table management to reduce customer waiting times. Journal of Foodservice Business Research, 11(4), 334–351. Hwang, J. (2008). Restaurant table management to reduce customer waiting times. Journal of Foodservice Business Research, 11(4), 334–351.
30.
go back to reference Kimes, S. E., & Thompson, G. M. (2005). An evaluation of heuristic methods for determining the best table mix in full-service restaurants. Journal of Operations Management, 23(6), 599–617. Kimes, S. E., & Thompson, G. M. (2005). An evaluation of heuristic methods for determining the best table mix in full-service restaurants. Journal of Operations Management, 23(6), 599–617.
31.
go back to reference Thompson, G. M. (2002). Optimizing a restaurant’s seating capacity: Use dedicated or combinable tables? Cornell Hotel and Restaurant Administration Quarterly, 43(4), 48–57. Thompson, G. M. (2002). Optimizing a restaurant’s seating capacity: Use dedicated or combinable tables? Cornell Hotel and Restaurant Administration Quarterly, 43(4), 48–57.
32.
go back to reference Thompson, G. M. (2003). Optimizing restaurant-table configurations: Specifying combinable tables. The Cornell Hotel and Restaurant Administration Quarterly, 44(1), 53–60. Thompson, G. M. (2003). Optimizing restaurant-table configurations: Specifying combinable tables. The Cornell Hotel and Restaurant Administration Quarterly, 44(1), 53–60.
33.
go back to reference Bertsimas, D., & Shioda, R. (2003). Restaurant revenue management. Operations Research, 51(3), 472–486. Bertsimas, D., & Shioda, R. (2003). Restaurant revenue management. Operations Research, 51(3), 472–486.
35.
go back to reference Kimes, S. E. (1989). The basics of yield management. The Cornell Hotel and Restaurant Administration Quarterly, 30(3), 14–19. Kimes, S. E. (1989). The basics of yield management. The Cornell Hotel and Restaurant Administration Quarterly, 30(3), 14–19.
36.
go back to reference Vinod, B. (2016). Evolution of yield management in travel. Journal of Revenue and Pricing Management, 15(3–4), 203–211. Vinod, B. (2016). Evolution of yield management in travel. Journal of Revenue and Pricing Management, 15(3–4), 203–211.
37.
go back to reference Zheng, J., Liu, J., & Clarke, D. B. (2017). Ticket fare optimization for China’s high-speed railway based on passenger choice behavior. Discrete Dynamics in Nature and Society, 2017(1), 1–6. Zheng, J., Liu, J., & Clarke, D. B. (2017). Ticket fare optimization for China’s high-speed railway based on passenger choice behavior. Discrete Dynamics in Nature and Society, 2017(1), 1–6.
38.
go back to reference Li, G., Ran, L., Yue, X., & Wang, Z. (2013). Dynamic pricing and supply coordination with reimbursement contract under random yield and demand. Discrete Dynamics in Nature and Society, 2013(2), 1–10. Li, G., Ran, L., Yue, X., & Wang, Z. (2013). Dynamic pricing and supply coordination with reimbursement contract under random yield and demand. Discrete Dynamics in Nature and Society, 2013(2), 1–10.
39.
go back to reference Sahut, J. M., Hikkerova, L., & Pupion, P. C. (2016). Perceived unfairness of prices resulting from yield management practices in hotels. Journal of Business Research, 69(11), 4901–4906. Sahut, J. M., Hikkerova, L., & Pupion, P. C. (2016). Perceived unfairness of prices resulting from yield management practices in hotels. Journal of Business Research, 69(11), 4901–4906.
40.
go back to reference Piga, C. A., & Nicolini, M. A. M. (2015). Combined effects of capacity and time on fares: Insights from the yield management of a low-cost airline. Review of Economics and Statistics, 97(4), 900–915. Piga, C. A., & Nicolini, M. A. M. (2015). Combined effects of capacity and time on fares: Insights from the yield management of a low-cost airline. Review of Economics and Statistics, 97(4), 900–915.
41.
go back to reference Mattos, C. L. C., Barreto, G. A., & Cavalcanti, F. R. P. (2014). An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. Electronic Commerce Research, 14(1), 51–70. Mattos, C. L. C., Barreto, G. A., & Cavalcanti, F. R. P. (2014). An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. Electronic Commerce Research, 14(1), 51–70.
42.
go back to reference Elmaghraby, A. S., Kumar, A., Kantardzic, M. M., & Mostafa, M. G. (2005). A scalable pricing model for bandwidth allocation. Electronic Commerce Research, 5(2), 203–227. Elmaghraby, A. S., Kumar, A., Kantardzic, M. M., & Mostafa, M. G. (2005). A scalable pricing model for bandwidth allocation. Electronic Commerce Research, 5(2), 203–227.
43.
go back to reference Kimes, S. E., Chase, R. B., Choi, S., Lee, P. Y., & Ngonzi, E. N. (1998). Restaurant revenue management: Applying yield management to the restaurant industry. Cornell Hotel & Restaurant Administration Quarterly, 39(3), 32–39. Kimes, S. E., Chase, R. B., Choi, S., Lee, P. Y., & Ngonzi, E. N. (1998). Restaurant revenue management: Applying yield management to the restaurant industry. Cornell Hotel & Restaurant Administration Quarterly, 39(3), 32–39.
44.
go back to reference Erlang, A. K. (1909). The theory of probabilities and telephone conversations. Nyt Tidsskr Mat Ser B, 20, 33–39. Erlang, A. K. (1909). The theory of probabilities and telephone conversations. Nyt Tidsskr Mat Ser B, 20, 33–39.
45.
go back to reference Erlang, A. K. (1917). Solution of some problems in the theory of probabilities of significance in automatic telephone exchanges. Post Office Electrical Engineers Journal, 13, 5–13. Erlang, A. K. (1917). Solution of some problems in the theory of probabilities of significance in automatic telephone exchanges. Post Office Electrical Engineers Journal, 13, 5–13.
46.
go back to reference Molina, E. C. (2014). Application of the theory of probability to telephone trunking problems. Bell System Technical Journal, 6(3), 461–494. Molina, E. C. (2014). Application of the theory of probability to telephone trunking problems. Bell System Technical Journal, 6(3), 461–494.
47.
go back to reference Pollaczek, F. (1932). Lösung eines geometrischen wahrscheinlichkeitsproblems. Mathematische Zeitschrift, 35(1), 230–278. Pollaczek, F. (1932). Lösung eines geometrischen wahrscheinlichkeitsproblems. Mathematische Zeitschrift, 35(1), 230–278.
48.
go back to reference Crommerin, C. D. (1932). Delay probability formulae when the holding times are constant. Post Office Electrical Engineer’s Journal, 25, 41–50. Crommerin, C. D. (1932). Delay probability formulae when the holding times are constant. Post Office Electrical Engineer’s Journal, 25, 41–50.
49.
go back to reference Palm, C. (1938). Analysis of the Erlang traffic formula for busy-signal arrangements. Ericsson Technics, 5, 39–58. Palm, C. (1938). Analysis of the Erlang traffic formula for busy-signal arrangements. Ericsson Technics, 5, 39–58.
50.
go back to reference Daley, D. J. (1965). General customer impatience in the queue GI/G/1. Journal of Applied Probability, 2(1), 186–205. Daley, D. J. (1965). General customer impatience in the queue GI/G/1. Journal of Applied Probability, 2(1), 186–205.
51.
go back to reference Rao, S. S. (1967). Queueing models with balking and reneging. Annals of the Institute of Statistical Mathematics, 19(1), 55. Rao, S. S. (1967). Queueing models with balking and reneging. Annals of the Institute of Statistical Mathematics, 19(1), 55.
52.
go back to reference Stidham, S. (2009). Optimal design of queueing systems. Boca Raton: CRC Pr I Llc. Stidham, S. (2009). Optimal design of queueing systems. Boca Raton: CRC Pr I Llc.
53.
go back to reference Wang, Y. L. (2015). Analysis the supermarket casher number based on the m/m/c/∞ queuing model. Journal of Taiyuan Normal University-Natural Science, 14(2), 5–8. Wang, Y. L. (2015). Analysis the supermarket casher number based on the m/m/c/∞ queuing model. Journal of Taiyuan Normal University-Natural Science, 14(2), 5–8.
54.
go back to reference Ismail, Z., & Shokor, S. S. A. (2016). The application of waiting lines system in improving customer service management: The examination of malaysia fast food restaurants industry (Vol. 32, p. 012074)., IOP conference series: Earth and environmental science Bristol: IOP Publishing. Ismail, Z., & Shokor, S. S. A. (2016). The application of waiting lines system in improving customer service management: The examination of malaysia fast food restaurants industry (Vol. 32, p. 012074)., IOP conference series: Earth and environmental science Bristol: IOP Publishing.
55.
go back to reference Rashida, A. R., Fadzli, M., Ibrahim, S., & Goh, S. R. (2016). Modeling and simulation of m/m/c queuing pharmacy system with adjustable parameters, 1707(1), 917–922. Rashida, A. R., Fadzli, M., Ibrahim, S., & Goh, S. R. (2016). Modeling and simulation of m/m/c queuing pharmacy system with adjustable parameters, 1707(1), 917–922.
56.
go back to reference Knight, V. A., Harper, P. R., & Smith, L. (2012). Ambulance allocation for maximal survival with heterogeneous outcome measures. Omega, 40(6), 918–926. Knight, V. A., Harper, P. R., & Smith, L. (2012). Ambulance allocation for maximal survival with heterogeneous outcome measures. Omega, 40(6), 918–926.
57.
go back to reference Brigham, G. (1955). On a congestion problem in an aircraft factory. Journal of the Operations Research Society of America, 3(4), 412–428. Brigham, G. (1955). On a congestion problem in an aircraft factory. Journal of the Operations Research Society of America, 3(4), 412–428.
58.
go back to reference Morse, P. M. (1958). Queues, inventories and maintenance. Hoboken: Wiley. Morse, P. M. (1958). Queues, inventories and maintenance. Hoboken: Wiley.
59.
go back to reference Ke, J. C., & Wang, K. H. (1999). Cost analysis of the m/m/r machine repair problem with balking, reneging, and server breakdowns. Journal of the Operational Research Society, 50(3), 275–282. Ke, J. C., & Wang, K. H. (1999). Cost analysis of the m/m/r machine repair problem with balking, reneging, and server breakdowns. Journal of the Operational Research Society, 50(3), 275–282.
60.
go back to reference Bell, C. E. (1980). Optimal operation of an m/m/2 queue with removable servers. Operations Research, 28(5), 1189–1204. Bell, C. E. (1980). Optimal operation of an m/m/2 queue with removable servers. Operations Research, 28(5), 1189–1204.
61.
go back to reference Wang, P. P. (1996). Markovian queueing models with periodic-review. Computers & Operations Research, 23(8), 741–754. Wang, P. P. (1996). Markovian queueing models with periodic-review. Computers & Operations Research, 23(8), 741–754.
62.
go back to reference Caldentey, R., & Wein, L. M. (2003). Analysis of a decentralized production-inventory system. Manufacturing & Service Operations Management, 5(1), 1–17. Caldentey, R., & Wein, L. M. (2003). Analysis of a decentralized production-inventory system. Manufacturing & Service Operations Management, 5(1), 1–17.
63.
go back to reference Huang, S. M., & Su, J. C. P. (2013). Impact of product proliferation on the reverse supply chain. Omega-international Journal of Management Science, 41(3), 626–639. Huang, S. M., & Su, J. C. P. (2013). Impact of product proliferation on the reverse supply chain. Omega-international Journal of Management Science, 41(3), 626–639.
64.
go back to reference Stolletz, R., & Manitz, M. (2013). The impact of a waiting-time threshold in overflow systems with impatient customers. Omega, 41(2), 280–286. Stolletz, R., & Manitz, M. (2013). The impact of a waiting-time threshold in overflow systems with impatient customers. Omega, 41(2), 280–286.
65.
go back to reference Hillier, F. S. (1963). Economic models for industrial waiting line problems. Management Science, 10(1), 119–130. Hillier, F. S. (1963). Economic models for industrial waiting line problems. Management Science, 10(1), 119–130.
66.
go back to reference Stidham, S. J. (1970). On the optimality of single-server queuing systems. Operations Research, 18(4), 708–732. Stidham, S. J. (1970). On the optimality of single-server queuing systems. Operations Research, 18(4), 708–732.
67.
go back to reference Jain, S., & Smith, M. G. (1994). Open finite queueing networks with m/m/c/k parallel servers. Computers & Operations Research, 21(3), 297–317. Jain, S., & Smith, M. G. (1994). Open finite queueing networks with m/m/c/k parallel servers. Computers & Operations Research, 21(3), 297–317.
68.
go back to reference Subramanian, M. G., Ayyappan, G., & Sekar, G. (2011). M/m/c retrial queueing system with breakdown and repair of services. Asian Journal of Mathematics & Statistics, 4(4), 214–223. Subramanian, M. G., Ayyappan, G., & Sekar, G. (2011). M/m/c retrial queueing system with breakdown and repair of services. Asian Journal of Mathematics & Statistics, 4(4), 214–223.
69.
go back to reference Bhat, U. N., & Rao, S. S. (1972). A statistical technique for the control of traffic intensity in the queueing systems M/G/1 and GI/M/1. Operations Research, 20(5), 955–966. Bhat, U. N., & Rao, S. S. (1972). A statistical technique for the control of traffic intensity in the queueing systems M/G/1 and GI/M/1. Operations Research, 20(5), 955–966.
70.
go back to reference Grassmann, W. K., Chen, X., & Kashyap, B. R. K. (2001). Optimal service rates for the state-dependent m/g/1 queues in steady state. Operations Research Letters, 29(2), 57–63. Grassmann, W. K., Chen, X., & Kashyap, B. R. K. (2001). Optimal service rates for the state-dependent m/g/1 queues in steady state. Operations Research Letters, 29(2), 57–63.
Metadata
Title
Allocating resources for a restaurant that serves regular and group-buying customers
Authors
Tianhua Zhang
Juliang Zhang
Fu Zhao
Yihong Ru
John W. Sutherland
Publication date
21-07-2018
Publisher
Springer US
Published in
Electronic Commerce Research / Issue 4/2020
Print ISSN: 1389-5753
Electronic ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-018-9315-x

Other articles of this Issue 4/2020

Electronic Commerce Research 4/2020 Go to the issue