Skip to main content
SpringerLink
Log in

Managing long queues for holiday sales shopping

  • Research Article
  • Published:
Journal of Revenue and Pricing Management Aims and scope

Abstract

Long queues during holiday shopping events seem undesirable for both shoppers and retailers. However, the following article shows that, under some conditions, long queues benefit retailers for two reasons. First, long queues, by turning away high-time-cost shoppers, serve as a device of segmentation and targeting. Consequently, retailers deliver promotions only to low-time-cost shoppers. High-time-cost shoppers choose to purchase at a regular time (non-holiday shopping event) and pay the full price without having to make the wait. Second, longer queues prompt shoppers who stay in the line buy more products. In addition, the article shows that shoppers tend to wait longer when price discounts are greater. Accounting for the above findings, this article provides a numerical solution to jointly optimizing retailers’ promotional and operational decisions on holiday promotional sales.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6

Similar content being viewed by others

Notes

  1. We are aware that certain shoppers receive positive utility from the time spent on shopping even if they buy nothing. In this article we focus on those shoppers who deem such time-spending as a ‘loss’.

  2. It is possible that the per-unit shopping time might be smaller because of reduced crowdedness in regular-time shopping. Shoppers may self-adjust to spend a longer time purchasing when they become more relaxed. Yet the analysis gains little by adding an extra parameter at the expense of increased complexity.

  3. For high-time-cost shoppers, there may be some utility loss because of the delayed purchase. We assume the utility loss is minimal and do not consider it in the analysis for tractability.

References

  • Accenture (2010) Industrial Report: The Annual Accenture Holiday Shopping Survey. Published on 5 October.

  • Allen, K.G. and Reynolds, T. (2014) Early promotions, online shopping and improving economy changing the face of Black Friday Weekend. By National Retailer Federation. Published on 30 November, https://nrf.com/media/press-releases/early-promotions-online-shopping-and-improving-economy-changing-the-face-of.

  • Alreck, P.L. and Settle, R.B. (2002) The hurried consumer: Time-saving perceptions of internet and catalogue shopping. Journal of Database Marketing 10 (1): 25–35.

    Google Scholar 

  • American Research Group (2012) 2012 Christmas gift spending plans return to pre-recession levels. By American Research Group. Published on 15 November, http://americanresearchgroup.com/holiday/.

  • Ayvaz, N. and Huh, W.T. (2010) Allocation of hospital capacity to multiple types of patients. Journal of Revenue & Pricing Management 9 (5): 386–398.

    Article  Google Scholar 

  • Beatty, S.E. and Smith, S.M. (1987) External search effort: An investigation across several product categories. Journal of Consumer Research 14 (1): 83–95.

    Article  Google Scholar 

  • Bergadaà, M.M. (1990) The role of time in the action of the consumer. The Journal of Consumer Research 17 (3): 289–302.

    Article  Google Scholar 

  • Bermana, O. and Larson, R.C. (2004) Aqueueing control model for retail services having backroom operations and cross-trained workers. Computers & Operations Research 31 (2): 201–222.

    Article  Google Scholar 

  • Berry, L.L. (1979) The time-buying consumer. Journal of Retailing 55 (4): 58–69.

    Google Scholar 

  • Bocharov, P., D’Apice, C., Penchinkin, A. and Salerno, S. (2004) Queueing Theory. Utrecht, The Netherlands; Boston, MA: VSP.

    Google Scholar 

  • Campbell, J.Y. and Mankiw, N.G. (1989) Consumption, Income and Interest Rates: Reinterpreting the Time Series Evidence. Cambirdge, MA: MIT Press.

    Book  Google Scholar 

  • Cespedes, F.V. (1993) Ethical issues in distribution. In: N.C. Smith and J.A. Quelch (eds.) Ethics in Marketing. Homewood, IL: Richard D. Irwin, pp. 473–490.

    Google Scholar 

  • Chandra, A. and Tappata, M. (2011) Consumer search and dynamic price dispersion: An application to gasoline markets. The RAND Journal of Economics 42 (4): 681–704.

    Article  Google Scholar 

  • Christensen, L.R., Jorgenson, D.W. and Lau, L.J. (1975) Transcendental logarithmic utility functions. The American Economic Review 65 (3): 367–383.

    Google Scholar 

  • Darian, J.C. and Cohen, J. (1995) Segmenting by consumer time shortage. Journal of Consumer Marketing 12 (1): 32–44.

    Article  Google Scholar 

  • Deacon, R.T. and Sonstelie, J. (1985) Rationing by waiting and the value of time: Results from a natural experiment. The Journal of Political Economy 93 (4): 627–647.

    Article  Google Scholar 

  • Debo, L.G., Toktay, L.B. and Wassenhove, L.N.V. (2008) Queueing for expert services. Management Science 54 (8): 1497–1512.

    Article  Google Scholar 

  • Deloitte (2012) Deloitte’s 2012 annual holiday survey: Will retailers’ registers jingle this holiday season? By Deloitte. Published on October, http://www.deloitte.com/view/en_US/us/Industries/Retail-Distribution/consumer-spending/index.htm.

  • DeSerpa, A.C. (1971) A theory of the economics of time. The Economic Journal 81 (324): 828–846.

    Article  Google Scholar 

  • Feldman, L.P. and Hornik, J. (1981) The use of time: An integrated conceptual model. The Journal of Consumer Research 7 (4): 407–419.

    Article  Google Scholar 

  • Hassin, R. (1986) Consumer information in markets with random product quality: The case of queues and balking. Econometrica 54 (5): 1185–1195.

    Article  Google Scholar 

  • Hassin, R. and Haviv, M. (2003) To Queue or Not to Queue: Equilibrium Behavior in Queuing Systems. Assinippi, MA: Kluwer Academic Pubilsher.

    Book  Google Scholar 

  • Heizer, J. and Render, B. (2004) Operations Management. 7th edn Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Hoch, S.J., Byung-Do Kim, A.L.M. and Rossi, P.E. (1995) Determinants of store-level price elasticity. Journal of Marketing Research 32 (1): 17–29.

    Article  Google Scholar 

  • Iyer, E.S. (1989) Unplanned purchasing: Knowledge of shopping environment and time pressure. Journal of Retailing. 65 (1): 40–57.

    Google Scholar 

  • Jensen, M. and Drozdenko, R. (2008) The changing price of brand loyalty under perceived time pressure. Journal of Product & Brand Management 17 (2): 115–120.

    Article  Google Scholar 

  • Kalai, E., Kamien, M.I. and Rubinovitch, M. (1992) Optimal service speeds in a competitive environment. Management Science. 38 (8): 1154–1163.

    Article  Google Scholar 

  • Kimes, S.E. (2011) Customer attitudes towards restaurant reservations policies. Journal of Revenue & Pricing Management 10 (3): 244–260.

    Article  Google Scholar 

  • Kremer, M. and Debo, L.G. (forthcoming) Inferring quality from wait time. Management Science.

  • LaurenceMetal (2010) Back to school 2010 report: Retailers Lose $21 Billion due to walkaways. Industrial Report. News excerpt (available at http://www.lawrencemetal.com/about/news.aspx).

  • Levin, R. (2000) Retailers find a winning mix. InformationWeek 803, 11 September: 345–354.

  • Lindsay, C.M. and Feigenbaum, B. (1984) Rationing by waiting lists. The American Economic Review 74 (3S): 404–417.

    Google Scholar 

  • Lu, Y., Musalem, A., Olivares, M. and Schilkrut, A. (2013) Measuring the effect of queues on customer purchases. Management Science. 59 (8): 1743–1763.

    Article  Google Scholar 

  • Martin, G.E., Grahn, J.L., Pankoff, L.D. and Madeo, L.A. (1992) A mechanism for reducing small-business customer waiting-line dissatisfaction. Managerial and Decision Economics 13 (4): 353–361.

    Article  Google Scholar 

  • Mathews, T. (2004) The impact of discounting on an auction with a buyout option: A theoretical analysis motivated by Ebay’s buy-it-now feature. Journal of Economics. 81 (1): 25–52.

    Article  Google Scholar 

  • McDonald, W.J. (1994) Time use in shopping: The role of personal characteristics. Journal of Retailing 70 (4): 345–365.

    Article  Google Scholar 

  • Messinger, P. and Narasimhan, C. (1997) A model of retail formats based on consumers’ economizing on shopping time. Marketing Science 16 (1): 1–23.

    Article  Google Scholar 

  • Naor, P. (1969) On the regulation of queue size by levying tolls. Econometrica 37 (1): 13–24.

    Article  Google Scholar 

  • National Retail Federation (2012) Back to school sales up as parents replenish children’s needs. By National Retail Federation. Published on 19 July, http://www.nrf.com/modules.php?name=News&op=viewlive&sp_id=1405.

  • National Retail Federation (2013) Holiday retail sales up 3.0 percent to $579.8 Billion. By National Retail Federation. Published on 15 January, http://www.nrf.com/modules.php?name=News&op=viewlive&sp_id=1500.

  • Purohit, D. and Desai, P. (2004) ‘Let me talk to my manager’: Haggling in a competitive environment. Marketing Science 23 (2): 219–233.

    Article  Google Scholar 

  • Radhakrishnan, S. and Balachandran, K.R. (1996) Cost of congestion, operational eciency and management accounting. European Journal of Operational Research 89 (2): 237–245.

    Article  Google Scholar 

  • Reddy, S. and Gold, D. (2012) City nails sex-based pricing. By Forbes.com. Published on 23 May, http://online.wsj.com/article/SB10001424052702304019404577420651136722954.html.

  • Rothkopf, M.H. and Rech, P. (1987) Perspectives on queues: Combining queues is not always beneficial. Operations Research 35 (6): 906–909.

    Article  Google Scholar 

  • Sabelhaus, J. and Groen, J.A. (2000) Can permanent-income theory explain cross-sectional consumption patterns? Review of Economics and Statistics 82 (3): 431–438.

    Article  Google Scholar 

  • Sarantis, N. and Stewart, C. (1999) Is the consumption-income ratio stationary? Evidence from panel unit root tests. Economics Letters 64 (3): 309–314.

    Article  Google Scholar 

  • Train, K. and McFadden, D. (1978) The goods/leisure tradeoff and disaggregate work trip mode choice models. Transportation Research 12 (5): 349–353.

    Article  Google Scholar 

  • Weisselberg, R.C. and Cowley, J.G. (1969) QUICKEN QUEUE. Journal of Systems Management 20 (10): 30–35.

    Google Scholar 

  • Whang, S. (1989) Cost allocation revisited: An optimality result. Management Science 35 (10): 1264–1273.

    Article  Google Scholar 

  • Yeoman, I. and Morello, G. (2007) The futurology of revenue management and pricing. Journal of Revenue & Pricing Management 6 (4): 251–252.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Lazaridis School of Business and Economics, Wilfrid Laurier University, Waterloo, Canada

    Chun (Martin) Qiu

  2. Labovitz School of Business and Economics, University of Minnesota, Duluth, MN, USA

    Wenqing Zhang

Authors
  1. Chun (Martin) Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenqing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chun (Martin) Qiu.

Additional information

1received his PhD in marketing in 2008 from the University of Alberta, and is currently working as an Assistant Professor of Marketing at Wilfrid Laurier University, Canada. He is conducting research on retailing, competitive marketing strategies and mobile marketing.

Appendix

Appendix

Proof of Lemma 1

Differentiate w.r.t. , first-order condition The second-order condition is which is negative when is small, which is the necessary condition for shoppers to conduct holiday shopping.

We thus set d(U S )/dp 1 to 0 to solve for q S * with t 0=1 in the expression.

q R * is solved in a similar fashion by setting d=0 and w=0. □

Proof of Proposition 1

The sign is determined by the sign of the numerator of ∂q S */∂w. We need to show that

Since both sides are positive, we take the square of both sides of the above inequality. Now we need to show

which is satisfied since

 □Proof of Proposition 2

By definition of mean waiting time, we have (λ)/(2μ(μ−λ))≡w *, where Differentiate both sides w.r.t. to d, we have ((∂λ)/(∂d))/(2(μ−λ)2)=(∂* w)/(∂d). Note that is a function of both w * and d, that is, . Applying the chain rule, we have (∂λ)/(∂d)=

Substitute ∂λ/∂d back, and collect the items to simplify the expression, and we have

Everything else being equal, a bigger promotion will motivate more shoppers to join the queue, thus , and longer waiting will deter more shoppers from walking away, thus Therefore, both the numerator and the denominator of the right-hand side are positive. Hence, ∂* w/∂d>0.

The proof of ∂* w/∂K is similar. Note that in this case, μ is a function of K.

Since ∂μ/∂K>0, and that ; thus, the numerator of the right-hand side is negative. Also, we have so the denominator of the right-hand side is positive. Thus, ∂* w/∂K<0. □

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qiu, C., Zhang, W. Managing long queues for holiday sales shopping. J Revenue Pricing Manag 15, 52–65 (2016). https://doi.org/10.1057/rpm.2015.46

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1057/rpm.2015.46

Keywords

Search

Navigation