Industrial Engineering and Management Systems

  • 제7권3호
  • /
  • Pages.257-265
  • /
  • 2008
  • /
  • 1598-7248(pISSN)
  • /
  • 2234-6473(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
권호 표지

Optimal Lot-sizing and Pricing with Markdown for a Newsvendor Problem

  • Chen, Jen-Ming (Institute of Industrial Management National Central University) ;
  • Chen, Yi-Shen (Institute of Industrial Management National Central University) ;
  • Chien, Mei-Chen (Department of Industrial and Technology Management Vanung University)
  • 발행 : 2008.12.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper deals with the joint decisions on pricing and ordering for a monopolistic retailer who sells perishable goods with a fixed lifetime or demand period. The newsvendor-typed problem is formulated as a two-period inventory system where the first period represents the inventory of fresh or new-arrival items and the second period represents the inventory of items that are older but still usable. Demand may be for either fresh items or for somewhat older items that exhibit physical decay or deterioration. The retailer is allowed to adjust the selling price of the deteriorated items in the second period, which stimulates demand and reduces excess season-end or stale inventory. This paper develops a stochastic dynamic programming model that solves the problem of preseason decisions on ordering-pricing and a within-season decision on markdown pricing. We also develop a fixed-price model as a benchmark against the dual-price dynamic model. To illustrate the effect of the dual-price policy on expected profit, we conduct a comparative study between the two models. Extension to a generalized multi-period model is also discussed.

키워드

참고문헌

  1. Abad, P. L. (1996), Optimal pricing and lot-sizing under conditions of perishability and partial backordering, Management Science, 42(8), 1093-1104. https://doi.org/10.1287/mnsc.42.8.1093
  2. Bernstein, F. and DeCroix, G. A. (2004), Decentralized pricing and capacity decisions in a multitier system with modular assembly, Management Science, 50(9), 1293-1308. https://doi.org/10.1287/mnsc.1040.0255
  3. Bitran, G. R. and Mondschein, S. V. (1993), Pricing perishable products: an application to the retail industry, Working Paper #3592-93, Massachusetts Institute of Technology, Cambridge, MA.
  4. Bitran, G. R. and Mondschein, S. V. (1997), Periodic pricing of seasonal products in retailing, Management Science, 43(1), 64-79. https://doi.org/10.1287/mnsc.43.1.64
  5. Belobaba, P. P. (1987), Airline yield management: an overview of seat inventory control, Transportation Science, 21(2), 63-73. https://doi.org/10.1287/trsc.21.2.63
  6. Brynjolfsson, E. and Smith, M. D. (2000), Frictionless commerce? A comparison of internet and conventional retailers, Management Science, 46(4), 563-585. https://doi.org/10.1287/mnsc.46.4.563.12061
  7. Burnetas, A. N. and Smith, C. E. (2000), Adaptive ordering and pricing for perishable products, Operations Research, 48(3), 436-443. https://doi.org/10.1287/opre.48.3.436.12437
  8. Chun, Y. H. (2003), Optimal pricing and ordering policies for perishable commodities, European Journal of Operational Research, 144, 68-82. https://doi.org/10.1016/S0377-2217(01)00351-4
  9. Deng, S. and Yano, C. A. (2006), Joint production and pricing decisions with setup costs and capacity constraints, Management Science, 52(5), 741-756. https://doi.org/10.1287/mnsc.1050.0491
  10. Eliashberg, J. and Steinberg, R. (1993), Marketing-production joint decision-making, in Handbooks in Operations Research and Management Science, Marketing, 5, J. Eliashberg and G. L. Lillien (eds.), Elsevier Science Publishers B. V.
  11. Federgruen, A. and Heching, A. (1999), Combined pricing and inventory control under uncertainty, Operations Research, 47(3), 454-475. https://doi.org/10.1287/opre.47.3.454
  12. Feldman, J. M. (1990), Fares: to raise or not to raise, Air Transportation World, 27(6), 58-59.
  13. Feng, Y. and Gallego, G. (1995), Optimal starting times for end-of-season sales and optimal stopping times for promotional fares, Management Science, 41(8), 1371-1391. https://doi.org/10.1287/mnsc.41.8.1371
  14. Feng, Y. and Gallego, G. (2000), Perishable asset revenue management with Markovian time dependent demand intensities, Management Science, 46(7), 941-956. https://doi.org/10.1287/mnsc.46.7.941.12035
  15. Feng, Y. and Xiao, B. (1999), Maximizing revenues of perishable assets with a risk factor, Operations Research, 47(2), 337-341. https://doi.org/10.1287/opre.47.2.337
  16. Feng, Y. and Xiao, B. (2000a), A continuous-time yield management model with multiple prices and reversible price changes, Management Science, 46(5), 644- 657. https://doi.org/10.1287/mnsc.46.5.644.12050
  17. Feng, Y. and Xiao, B. (2000b), Optimal Policies of yield management with multiple predetermined prices, Operations Research, 48(2), 332-343. https://doi.org/10.1287/opre.48.2.332.13373
  18. Friend, S. C. and Walker, P. H. (2001), Welcome to the new world of merchandising, Harvard Business Review, November, 133-141.
  19. Gallego, G. and van Ryzin, G. (1994), Optimal dynamic pricing of inventories with stochastic demand over finite horizons, Management Science, 40(8), 999- 1020. https://doi.org/10.1287/mnsc.40.8.999
  20. Gallego, G. and van Ryzin, G. (1997), A multiproduct dynamic pricing problem and its applications to network yield management, Operations Research, 45(1), 24-41. https://doi.org/10.1287/opre.45.1.24
  21. Gilbert, S. M. (2000), Coordination of pricing and multiple- period production across multiple constant priced goods, Management Science, 46(12), 1602-1616. https://doi.org/10.1287/mnsc.46.12.1602.12073
  22. Goh, C. H., Greenberg, B. S., and Matsuo, H. (1993), Two-period perishable inventory models, Management Science, 39(5), 633-649. https://doi.org/10.1287/mnsc.39.5.633
  23. Goyal, S. K. and Giri, B. C. (2001), Recent trends in modeling of deteriorating inventory: an invited review, European Journal of Operational Research,134(1), 1-16. https://doi.org/10.1016/S0377-2217(00)00248-4
  24. Law, A. M. and Kelton, W. D. (1991), Simulation Modeling and Analysis, 2nd edition, McGraw-Hill, New York.
  25. Lazear, E. P. (1986), Retail pricing and clearance sales, The American Economic Review, 76(1), 14-32.
  26. Lee, H. L., Padmanabhan, V., Taylor, T. A., and Whang, S. (2000), Price protection in the personal computer industry, Management Science, 46(4), 467-482. https://doi.org/10.1287/mnsc.46.4.467.12058
  27. Levy, D., Bergen, M., Dutta, S., and Venable, R. (1997), The magnitude of menu costs: direct evidence from large U.S. supermarket chains, The Quarterly Journal of Economics, 112(3), 791-825. https://doi.org/10.1162/003355397555352
  28. McGill, J. I. and van Ryzin, G. J. (1999), Revenue management: research overview and prospects, Transportation Science, 33(2), 233-256. https://doi.org/10.1287/trsc.33.2.233
  29. Montgomery, A. L. (1994), The impact of micro-marketing on pricing strategies, Ph.D. Thesis, Graduate School of Business, University of Chicago, Illinois.
  30. Nahmias, S. (1982), Perishable inventory theory: a review, Operations Research, 30(4), 680-708. https://doi.org/10.1287/opre.30.4.680
  31. Pashigian, B. P. (1988), Demand uncertainty and sales: a study of fashion and markdown pricing, The American Economic Review, 78(5), 936-953.
  32. Pashigian, B. P. and Bowen, B. (1991), Why are products sold on sale?, explanations of pricing regularities, The Quarterly Journal of Economics, 106, 1015- 1038. https://doi.org/10.2307/2937955
  33. Pashigian, B. P., Bowen, B., and Gould, R. (1995), Fashion, styling, and the within-season decline in automobile prices, Journal of Law and Economics, 38, 281-309. https://doi.org/10.1086/467333
  34. Petruzzi, N. C. and Dada, M. (1999), Pricing and the newsvendor problem: a review with extensions, Operations Research, 47(2), 183-194. https://doi.org/10.1287/opre.47.2.183
  35. Raafat, F. (1991), Survey of literature on continuously deteriorating inventory models, Journal of the Operational Research Society, 42, 27-37. https://doi.org/10.1057/jors.1991.4
  36. Rajan, A., Rakesh, and Steinberg, R. (1992), Dynamic pricing and ordering decisions by a monopolist, Management Science, 38(2), 240-262. https://doi.org/10.1287/mnsc.38.2.240
  37. Raz, G. and Porteus, E. L. (2006), A fractiles perspective to the joint price/quantity newsvendor model, Management Science, 52(11), 1764-1777. https://doi.org/10.1287/mnsc.1060.0584
  38. Smith, B. C., Leimkuhler, J. F., and Darrow, R. M. (1992), Yield management at American Airlines, Interfaces, 22(1), 8-31. https://doi.org/10.1287/inte.22.1.8
  39. Smith, S. A. and Achabal, D. D. (1998), Clearance pricing and inventory policies for retail chains, Management Science, 44(3), 285-300. https://doi.org/10.1287/mnsc.44.3.285
  40. Van Ryzin, G. and McGill, J. (2000), Revenue management without forecasting or optimization: an adaptive algorithm for determining airline seat protection levels, Management Science, 46(6), 760-775. https://doi.org/10.1287/mnsc.46.6.760.11936
  41. Weatherford, L. R. and Bodily, S. E. (1992), A taxonomy and research overview of perishable-asset revenue management: yield management, overbooking, and pricing, Operations Research, 40(5), 831-844. https://doi.org/10.1287/opre.40.5.831
  42. Yano, C. A. and Gilbert S. M. (2004), Coordinated pricing and production/procurement decisions: a review, In: Chakravarty, Eliashberg (eds), Managing Business Interfaces: Marketing, Engineering, and Manufacturing Perspectives, Springer, 65-103.
  43. Zhao, W. and Zheng, Y. S. (2000), Optimal dynamic pricing for perishable assets with nonhomogeneous demand, Management Science, 46(3), 375-388. https://doi.org/10.1287/mnsc.46.3.375.12063