196
Views
1
CrossRef citations to date
0
Altmetric
Articles

Using survival modeling for turn-time predictions in foodservice settings

ORCID Icon, , &

References

  • Baesens, B., Van Gestel, T., Stepanova, M., Van den Poel, D., & Vanthienen, J. (2005). Neural network survival analysis for personal loan data. Journal of Operational Research Society, 56(9), 1089–1098. doi:10.1057/palgrave.jors.2601990
  • Barros, C. P., Butler, R., & Correia, A. (2010). The length of stay of golf tourism: A survival analysis. Tourism Management, 31(1), 13–21. doi:10.1016/j.tourman.2009.02.010
  • 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.
  • Bland, M. (2004). An introduction to medical statistics (3rd ed.). New York, NY: Oxford University Press.
  • Clark, D. B., Parker, A. M., & Lynch, K. G. (1999). Psychopathology and substance-related problems during early adolescence: A survival analysis. Journal of Clinical Child & Adolescent Psychology, 28(3), 333–341. doi:10.1207/S15374424jccp280305
  • Cox, D. R., & Oakes, D. (1984). Analysis of survival data. New York, NY: Chapman and Hall Ltd.
  • Cutler, S. J., & Ederer, F. (1958). Maximum utilization of the life table method in analyzing survival. Journal of Chronic Diseases, 8(6), 699–712.
  • Davidson, R., & MacKinnon, J. G. (2004). Econometric theory and methods. New York, NY: Oxford University Press.
  • Ducimetiere, P., Eschwege, E., Papoz, L., Richard, J. L., Claude, J. R., & Rosselin, G. (1980). Relationship of plasma insulin levels to the incidence of myocardial infarction and coronary heart disease mortality in a middle-aged population. Diabetologia, 19(3), 205–210.
  • Ghahramani, S. (2000). Fundamentals of probability (2nd ed.). Upper Saddle River, NJ: Prentice Hall.
  • Glennon, D. C., & Nigro, P. (2005). Measuring the default risk of small business loans: A survival analysis approach. Journal of Money, Credit, & Banking, 37(5), 923–947. doi:10.1353/mcb.2005.0051
  • Gokovali, U., Bahar, O., & Kozak, M. (2007). Determinants of length of stay: A practical use of survival analysis. Tourism Management, 28(3), 736–746. doi:10.1016/j.tourman.2006.05.004
  • Golub, J. (2007). Survival analysis and the European Union decision-making. European Union Politics, 8(2), 155–179. doi:10.1177/1465116507076428
  • Hassett, M. J., & Stewart, D. G. (1999). Probability for risk management. Winsted, CT: Actex Publications.
  • 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, 316–326. doi:10.1016/j.ijhm.2013.05.007
  • Holy, T. E. (1997). Analysis of data from continuous probability distributions. Physical Review Letters, 79(19), 3545–3548. doi:10.1103/PhysRevLett.79.3545
  • Jones, P., & Mifll, M. (2001). Menu development and analysis in UK restaurant chains. Tourism and Hospitality Research, 3(1), 61–71. doi:10.1177/146735840100300105
  • Kalbfleisch, J. D., & Prentice, R. L. (2002). The statistical analysis of failure time data (2nd ed.). Hoboken, New Jersey: John Wiley & Sons, Inc.
  • Kaniovski, S., Peneder, M., & Smeral, E. (2008). Determinants of firm survival in the Austrian accommodation sector. Tourism Economics, 14(3), 527–543. doi:10.5367/000000008785633587
  • Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53, 457–481. doi:10.1080/01621459.1958.10501452
  • Kapoor, K., Sun, M., Srivastav, J., & Ye, T. (2014, August 24-27). A hazard based approach to user return time prediction. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, NY.
  • Kennedy, P. (2008). A guide to econometrics (6th ed.). Malden, MA: Blackwell Publishing.
  • Kimes, S., & Beard, J. (2013). The future of restaurant revenue management. Journal of Revenue and Pricing Management, 12(5), 464–469. doi:10.1057/rpm.2013.22
  • Kimes, S. E. (1999). Implementing restaurant revenue management: A five-step approach. Cornell Hotel and Restaurant Administration Quarterly, 40(3), 16–21. doi:10.1177/001088049904000315
  • Kimes, S. E. (2004). Restaurant revenue management: A implementation at Chevys Arrowhead. Cornell Hotel and Restaurant Administration Quarterly, 45(1), 52–67. doi:10.1177/0010880403260107
  • Kimes, S. E., Barrash, D., & Alexander, J. (1999). Developing a restaurant revenue-management strategy. Cornell Hotel and Restaurant Administration Quarterly, 40(5), 18–29. doi:10.1177/001088049904000505
  • Kimes, S. E., & Robson, S. (2004). The impact of restaurant table characteristics on meal duration and spending. Cornell Hotel and Restaurant Administration Quarterly, 45(4), 333–346. doi:10.1177/0010880404270063
  • Kimes, S. E., & Thompson, G. M. (2004). Restaurant revenue management at Chevys: Determining the best table mix. Decision Sciences, 35(3), 371–392. doi:10.1111/deci.2004.35.issue-3
  • Kimes, S. E., & Wirtz, J. (2013). Revenue management: Advanced strategies and tools to enhance firm profitability. Foundations and Trends in Marketing, 8(1), 1–68. doi:10.1561/1700000037
  • 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. doi:10.1057/palgrave.rpm.5170026
  • Klien, J. P., & Moeschberger, M. L. (2003). Survival analysis: Techniques for censored and truncated data (2nd ed.). New York, NY: Springer-Verlag Inc.
  • Martinez-Garcia, E., & Raya, J. M. (2008). Length of stay for low-cost tourism. Tourism Management, 29(6), 1064–1075. doi:10.1016/j.tourman.2008.02.011
  • Molose, T. (2012). Guidelines for revenue management in small, medium and micro restaurant enterprises: A case study approach. Research Journal of Finance and Accounting, 3(8), 53–62.
  • Noone, B. M., Kimes, S., Mattila, A., & Wirtz, J. (2007). The effect of meal pace on customer satisfaction. Cornell Hospitality Quarterly, 48(3), 231–244. doi:10.1177/0010880407304020
  • Noone, B. M., Wirtz, J., & Kimes, S. E. (2012). The effect of perceived control on consumer responses to service encounter pace: A revenue management perspective. Cornell Hospitality Quarterly, 53(4), 295–307. doi:10.1177/1938965512460343
  • Parmar, K. B., & Machin, D. (1996). Survival analysis. West Sussex, England: John Wiley & Sons Ltd.
  • Peister, C. (2007). Table-games revenue management: Applying survival analysis. Cornell Hotel and Restaurant Administration Quarterly, 48(1), 70–87. doi:10.1177/0010880406298252
  • Sill, B. T. (1991). Capacity management: Making your service delivery more productive. Cornell Hotel and Restaurant Administration Quarterly, 31(4), 77–88. doi:10.1177/001088049103100420
  • Sloot, T., & Verschuren, P. (1990). Decision-making speed in the European community. Journal of Common Market Studies, 29(1), 75–85. doi:10.1111/j.1468-5965.1990.tb00382.x
  • Stock, J. H., & Watson, M. W. (2007). Introduction to econometrics (2nd ed.). Boston, MA: Pearson Education Inc.
  • Susskind, A. M. (2017). The food-service industry: Best of time, worst of times. Cornell Hospitality Report, 17(16), 3–7.
  • Susskind, A. M., & Curry, B. (2016). The influence of table top technology in full-service restaurants. Cornell Hospitality Report, 16(22), 3–9.
  • Thomas, L., & Reyes, E. (2014). Tutorial: Survival estimation for Cox Regression Models with time-varying coefficients using SAS and R. Journal of Statistical Software, 61(1), 1–22. doi:10.18637/jss.v061.c01
  • Thompson, G. (2009). (Mythical) revenue benefits of reducing dining duration in restaurants. Cornell Hospitality Quarterly, 50(1), 96–112. doi:10.1177/1938965508328422
  • Thompson, G. (2010). Restaurant profitability management: Evolution of restaurant revenue management. Cornell Hospitality Quarterly, 51(3), 308–322. doi:10.1177/1938965510368653
  • Thompson, G., & Sohn, H. (2009). Time- and capacity-based measurement of restaurant revenue. Cornell Hospitality Quarterly, 50(4), 520–539. doi:10.1177/1938965509349217
  • Thompson, G. M., & Kwortnik, R. J. (2008). Pooling restaurant reservations to increase service efficiency. Journal of Service Research, 10(4), 335–346. doi:10.1177/1094670508314267

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.