Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application

Published Online:https://doi.org/10.1287/opre.1070.0409

References

  • Anderson S. P., de Palma A., Thisse J. F.Discrete Choice Theory of Product Differentiation (1992) (MIT Press, Cambridge, MA) CrossrefGoogle Scholar
  • Anupindi R., Dada M., Gupta S. Estimation of consumer demand with stockout based substitution: An application to vending machine products. Marketing Sci. (1998) 17:406–423LinkGoogle Scholar
  • Avsar Z. M., Baykal-Gursoy M. Inventory control under substitutable demand: A stochastic game application. Naval Res. Logist. (2002) 49:359–375CrossrefGoogle Scholar
  • Aydin G., Hausman W. H. Supply chain coordination and assortment planning. (2003) . Working paper, University of Michigan, Ann Arbor, MIGoogle Scholar
  • Ben-Akiva M., Lerman S. R.Discrete Choice Analysis: Theory and Application to Travel Demand (1985) (MIT Press, Cambridge, MA) Google Scholar
  • Bretthauer K. M., Shetty B. The nonlinear knapsack problem—Algorithms and applications. Eur. J. Oper. Res. (2002) 138:459–472CrossrefGoogle Scholar
  • Broniarczyk S. M., Hoyer W. D., McAlister L. Consumers' perception of the assortment offered in a grocery category: The impact of item reduction. J. Marketing Res. (1998) 35:166–176CrossrefGoogle Scholar
  • Bucklin R. E., Gupta S. Brand choice, purchase incidence, and segmentation: An integrated modeling approach. J. Marketing Res. (1992) 29:201–215CrossrefGoogle Scholar
  • Cachon G. P., Terwiesch C., Xu Y. Retail assortment planning in the presence of consumer search. Manufacturing Service Oper. Management (2005) 7(4):330–346LinkGoogle Scholar
  • Campo K., Gijsbrechts E., Nisol P. The impact of retailer stockouts on whether, how much, and what to buy. Internat. J. Res. Marketing (2003) 20:273–286CrossrefGoogle Scholar
  • Campo K., Gijsbrechts E., Nisol P. Dynamics in consumer response to product unavailability: Do stock-out reactions signal response to permanent assortment reductions? J. Bus. Res. (2004) 57:834–843CrossrefGoogle Scholar
  • Caprara A., Pisinger D., Toth P. Exact solution of the quadratic knapsack problem. INFORMS J. Comput. (1999) 11:125–137LinkGoogle Scholar
  • Chintagunta P. K. Investigating purchase incidence, brand choice and purchase quantity decisions of households. Marketing Sci. (1993) 12:184–208LinkGoogle Scholar
  • Cooper L. G., Nakanishi M.Market-Share Analysis: Evaluating Competitive Marketing Effectiveness (1988) (Kluwer Academic Publishers, Amsterdam, The Netherlands) CrossrefGoogle Scholar
  • Corstjens M., Doyle P. A model for optimizing retail space allocations. Management Sci. (1981) 27:822–833LinkGoogle Scholar
  • Dempster A. P., Laird N. M., Rubin D. B. Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Statist. Soc. B. (1977) 39:1–38Google Scholar
  • Downs B., Metters R., Semple J. Managing inventory with multiple products, lags in delivery, resource constraints, and lost sales: A mathematical programming approach. Management Sci. (2001) 47:464–479LinkGoogle Scholar
  • Dussault J. P., Ferland J. A., Lemaire B. Convex quadratic programming with one constraint and bounded variables. Math. Programming (1986) 36:90–104CrossrefGoogle Scholar
  • Fader P. S., Hardie B. G. S. Modeling consumer choice among SKUs. J. Marketing Res. (1996) 33:442–452CrossrefGoogle Scholar
  • Fitzsimons G. J. Consumer response to stockouts. J. Consumer Res. (2000) 27:249–266CrossrefGoogle Scholar
  • Gallo G., Hammer P. L., Simeone B. Quadratic knapsack problems. Math. Programming (1980) 12:132–149CrossrefGoogle Scholar
  • Green P. E., Krieger A. M. Models and heuristics for product line selection. Marketing Sci. (1985) 4(1):1–19LinkGoogle Scholar
  • Greene W. H.Econometric Analysis (1997) (Prentice Hall, Englewood Cliffs, NJ) Google Scholar
  • Gruen T. W., Corsten D. S., Bharadwaj S. Retail out-of-stocks: A worldwide examination of extent, causes and consumer responses. (2002) . Report, Grocery Manufacturers of America, Washington, D.C.Google Scholar
  • Guadagni P. M., Little J. D. C. A logit model of brand choice calibrated on scanner data. Marketing Sci. (1983) 2:203–238LinkGoogle Scholar
  • Hoch S. J., Bradlow E. T., Wansink B. The variety of an assortment. Marketing Sci. (1999) 25:342–355Google Scholar
  • Huffman C., Kahn B. E. Variety for sale: Mass customization or mass confusion? J. Retailing (1998) 74:491–513CrossrefGoogle Scholar
  • Kahn B. E., Lehmann D. R. Modeling choice among assortment. J. Retailing (1991) 67:274–275Google Scholar
  • Klastorin T. D. On a discrete nonlinear and nonseparable knapsack problem. Oper. Res. Lett. (1990) 9(4):233–237CrossrefGoogle Scholar
  • Kök A. G. Management of product variety in retail operations. (2003) . Ph.D. dissertation, The Wharton School, University of Pennsylvania, Philadelphia, PAGoogle Scholar
  • Kök A. G., Fisher M. L., Vaidyanathan R., Agrawal N., Smith S. Assortment planning: Review of literature and industry practice. Retail Supply Chain Management (2005) (Kluwer, Amsterdam, The Netherlands) Google Scholar
  • Kurt Salmon Associates Efficient consumer response: Enhancing consumer value in the grocery industry. (1993) . Food Marketing Institute Report #9-526, Washington, D.C.Google Scholar
  • Mahajan S., van Ryzin G. J., Tayur S., Ganeshan R., Magazine M. Retail inventories and consumer choice. Quantitative Methods in Supply Chain Management (1998) (Kluwer, Amsterdam, The Netherlands) Google Scholar
  • Mahajan S., van Ryzin G. Stocking retail assortments under dynamic consumer substitution. Oper. Res. (2001) 49:334–351LinkGoogle Scholar
  • McFadden D., Zarembka P. Conditional logit analysis of qualitative choice behavior. Frontiers in Econometrics (1974) (Academic Press, New York) Google Scholar
  • McGillivray A. R., Silver E. A. Some concepts for inventory control under substitutable demand. INFOR (1978) 16(1):47–63Google Scholar
  • Moorthy S. Market segmentation, self-selection, and product line design. Marketing Sci. (1984) 3:288–307LinkGoogle Scholar
  • Nahmias S., Schmidt C. P. An efficient heuristic for the multi-item newsboy model with a single resource constraint. Naval Res. Logist. (1984) 31:463–474CrossrefGoogle Scholar
  • Netessine S., Rudi N. Centralized and competitive inventory models with demand substitution. Oper. Res. (2003) 51:329–335LinkGoogle Scholar
  • Parlar M., Goyal S. K. Optimal ordering policies for two substitutable products with stochastic demand. Opsearch (1984) 21(1):1–15Google Scholar
  • Quelch J. A., Kenny D. Extend profits, not product lines. Harvard Bus. Rev. (1994) 72:153–160Google Scholar
  • Rajaram K. Assortment planning in fashion retailing: Methodology, application and analysis. Eur. J. Oper. Res. (2001) 129:186–208CrossrefGoogle Scholar
  • Rajaram K., Tang C. S. The impact of product substitution on retail merchandising. Eur. J. Oper. Res. (2001) 135:582–601CrossrefGoogle Scholar
  • Schary P. B., Christopher M. Anatomy of a stock out. J. Retailing (1979) 55:59–70Google Scholar
  • Shugan S. M. Product assortment in a triopoly. Management Sci. (1989) 35:304–320LinkGoogle Scholar
  • Simonson I. The effect of product assortment on buyer preferences. J. Retailing (1999) 75:347–370CrossrefGoogle Scholar
  • Smith S. A., Agrawal N. Management of multi-item retail inventory systems with demand substitution. Oper. Res. (2000) 48:50–64LinkGoogle Scholar
  • Talluri K., van Ryzin G. Revenue management under a general discrete choice model of consumer behavior. Management Sci. (2004) 50:15–33LinkGoogle Scholar
  • Urban T. L. An inventory-theoretic approach to product assortment and shelf space allocation. J. Retailing (1998) 74:15–35CrossrefGoogle Scholar
  • van Ryzin G., Mahajan S. On the relationship between inventory costs and variety benefits in retail assortments. Management Sci. (1999) 45:1496–1509LinkGoogle Scholar
  • Wu C. F. J. On the convergence properties of the EM algorithm. Ann. Statist. (1983) 11:95–103CrossrefGoogle Scholar
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