Do Consumer Demographics Affect Dynamic Price Markdowns of Seasonal Goods?
DOI:
https://doi.org/10.14738/abr.35.1559Abstract
In this research we investigate the consumer demographics impact on consumer strategic purchase behavior of seasonal goods. Our findings would be beneficial for retailers and firms in the fashion industry to help them decide how to do their price markdowns during the season. We develop different demographic segments as these segments react differently to price markdowns based on the factors that they have in common, and the elements which differentiates them. We use demographic factors to identify different market segments for seasonal products. We show that reducing the prices based on the expected response of different demographics segments in the market would help the retailer to plan the price markdowns in the seasonal goods industry, and also would help them in capturing the most out of different demographic segments in the market. Our findings can particularly be useful in terms of generating and managing demand, and selling the product in their best possible price.
References
Aviv, Y., & Pazgal, A. (2008). Optimal pricing of seasonal products in the presence of forward-looking consumers. Manufacturing & Service Operations Management, 10(3), 339-359
Besanko, D., & Winston, W. L. (1990). Optimal price skimming by a monopolist facing rational consumers. Management Science, 36(5), 555-567.
Bitran, G. R., & Mondschein, S. V. (1997). Periodic pricing of seasonal products in retailing. Management Science, 43(1), 64-79.
Bitran, G., Caldentey, R., & Mondschein, S. (1998). Coordinating clearance markdown sales of seasonal products in retail chains. Operations research, 46(5), 609-624.
Bruno, H. A., & Vilcassim, N. J. (2008). Research Note-Structural Demand Estimation with Varying Product Availability. Marketing Science, 27(6), 1126-1131.
Dasu, S., & Tong, C. (2010). Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes. European Journal of Operational Research, 204(3), 662-671.
Elmaghraby, W., & Keskinocak, P. (2003). Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions. Management Science, 49(10), 1287-1309.
Erdem, T., Imai, S., & Keane, M. P. (2003). Brand and quantity choice dynamics under price uncertainty. Quantitative Marketing and Economics, 1(1), 5-64.
Erdem, T., & Keane, M. P. (1996). Decision-making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing science, 15(1), 1-20.
Feng, Y., & Gallego, G. (1995). Optimal starting times for end-of-season sales and optimal stopping times for promotional fares. Management Science, 41(8), 1371-1391.
Gallego, G., & Van Ryzin, G. (1994). Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management science, 40(8), 999-1020.
Gönül, F., & Srinivasan, K. (1996). Estimating the impact of consumer expectations of coupons on purchase behavior: A dynamic structural model. Marketing Science, 15(3), 262-279.
Hendel, I., & Nevo, A. (2006). Measuring the implications of sales and consumer inventory behavior. Econometrica, 74(6), 1637-1673.
Hoch, S. J., Kim, B. D., Montgomery, A. L., & Rossi, P. E. (1995). Determinants of store-level price elasticity. Journal of marketing Research, 17-29.
Kim, B. D., Srinivasan, K., & Wilcox, R. T. (1999). Identifying price sensitive consumers: the relative merits of demographic vs. purchase pattern information. Journal of Retailing, 75(2), 173-193.
Lazear, E. P. (1984). Retail pricing and clearance sales (No. w1446). National Bureau of Economic Research.
Liu, Q., & van Ryzin, G. J. (2008). Strategic capacity rationing to induce early purchases. Management Science, 54(6), 1115-1131.
Mantrala, M. K., & Rao, S. (2001). A decision-support system that helps retailers decide order quantities and markdowns for fashion goods. Interfaces, 31(3_supplement), S146-S165.
McAfee, R. P., & Te Velde, V. (2006). Dynamic pricing in the airline industry. forthcoming in Handbook on Economics and Information Systems, Ed: TJ Hendershott, Elsevier.
Melnikov, O. (2000). Demand for differentiated durable products: The case of the US computer printer market. Manuscript. Department of Economics, Yale University.
Musalem, A., Olivares, M., Bradlow, E. T., Terwiesch, C., & Corsten, D. (2010). Structural estimation of the effect of out-of-stocks. Management Science, 56(7), 1180-1197.
Nair, H. (2007). Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games. Quantitative Marketing and Economics, 5(3), 239-292.
Pashigian, B. P. (1988). Demand uncertainty and sales: A study of fashion and markdown pricing. The American Economic Review, 936-953.
Pashigian, B. P., & Bowen, B. (1991). Why are products sold on sale?: Explanations of pricing regularities. The Quarterly Journal of Economics, 1015-1038.
Smith, S. A., & Achabal, D. D. (1998). Clearance pricing and inventory policies for retail chains. Management Science, 44(3), 285-300.
Song, I., & Chintagunta, P. K. (2003). A micromodel of new product adoption with heterogeneous and forward-looking consumers: Application to the digital camera category. Quantitative Marketing and Economics, 1(4), 371-407.
Soysal, G. P., & Krishnamurthi, L. (2012). Demand dynamics in the seasonal goods industry: An empirical analysis. Marketing Science, 31(2), 293-316.
Su, X. (2007). Intertemporal pricing with strategic customer behavior. Management Science, 53(5), 726-741.
Sweeting, A. (2008). Equilibrium price dynamics in perishable goods markets: The case of secondary markets for Major League Baseball tickets (No. w14505). National Bureau of Economic Research.
Zhao, W., & Zheng, Y. S. (2000). Optimal dynamic pricing for perishable assets with nonhomogeneous demand. Management science, 46(3), 375-388.
Cho, M., Fan, M., & Zhou, Y. P. (2009). Strategic consumer response to dynamic pricing of perishable products. In Consumer-Driven Demand and Operations Management Models (pp. 435-458). Springer US.
