Nowadays electronic commerce plays an important role in many business activities, operations, and transaction processing. The recent advances on e-businesses have created tremendous opportunities to increase profitability. This paper presents a multi-objective marketing planning model which simultaneously determines efficient marketing expenditure, service cost and product's selling price in two competitive markets. To solve the proposed model, we discuss a multi-objective geometric programming (GP) approach based on compromise programming method. Since our proposed model is a signomial GP and global optimality is not guaranteed for the problem, we transform the model to posynomial form. Finally, the solution procedure is illustrated via a numerical example and a sensitivity analysis is presented.
DOI: j.msl.2011.02.001 Keywords: Optimal pricing ,Optimization ,Multi-objective decision making ,Geometric programming ,Compromise programming How to cite this paper: Bayati, M & Makui, A. (2011). A multi objective geometric programming approach for electronic product pricing problem.Management Science Letters, 1(3), 371-378.
References
Abad, P. L. (1988). Determining optimal selling price and the lot size when the supplier offers all-unit quantity discounts. Decision Sciences, 19, 622-634.
Beightler, C. S., & Philip, D. T. (1976). Applied Geometric Programming. New York: Wiley. Bhargava, H. K., Choudhary, V., & Krishnan, R. (2001). Pricing and Product Design: Intermediary Strategies in an Electronic Market. International Journal of Electronic Commerce, 5 , 37-56. Chen, Y. A., Wang, H. C., & Shen, H. Z. (2006). Study on the price competition between e-commerce retailer and conventional retailer. system engineering theory and practice, 26, 35-41. Chun, S., & Kim, J. (2005). Pricing strategies in B2C electronic commerce: Analytical and empirical approaches. decision support systems, 40, 375-388. Duffin, R., Peterson, E. L., & Zener, C. (1967). Geometric Programming: Theory and Application. New York: Wiley. Elmaghraby, W., & Keskinocak, P. (2003). Dynamic pricing in the presence of inventory considerations: research overview, current practices, and future directions. Management Science, 49, 1278-1309. Fathian, M., Sadjadi, S. J., & Sajadi, S. (2009). Optimal pricing model for electronic products. computers and industrial engineering, 56, 255-259. Jornsten, K., & Uboe, J. (2009). Strategic pricing of ommodities. Applied Mathematical Finance, 16 , 385-399. Jung, H., & Klein, C. M. (2001). Optimal inventory policies under decreasing cost functions via geometric programming. European Journal of Operational Research, 132, 628-642. kim, D. S., & Klein, W. J. (1998). Optimal joint pricing and lot sizing with fixed and variable capacity. European Journal of Operational Research, 109, 212-227. Lee, K. B., Yu, S., & Kim, S. J. (2006). Analysis of pricing for e- business companies providing information goods and services. Computers and Industrial Engineering, 51, 72-78. Lee, W. J. (1993). Determining selling price and order quantity by geometric programming, optimal solution, bounds and sensitivity. Decision Sciences, 24, 76-87. Lee, W. J., & Kim, D. S. (1993). Optimal and heuristic decision strategies for integrated production and marketing planning. Decision Sciences, 24, 1203-1213. Lee, W. J., Kim, D. S., & Cabot, A. V. (1996). Optimal demand rate, lot sizing, and process reliability improvement decisions. IIE Transactiona, 28, 941-952. Miettinen, K. M. (1999). Non-linear Multi-objective optimization. Kluwer's academic publisher. Sadjadi, S. J., Orougee, M., & Aryanezhad, M. B. (2005). Optimal production and marketing planning. Computational Optimization and Application, 30, 195-203. Serel, D. (2009). Optimal ordering and pricing in a quick response system. International Journal of Production Economics, 121, 700-714. Szidorovsky, F., Gershon, M. E., & Dukstein, L. (1986). Techniques for multi objective decision making in systems managemen. New York: Elsevier. |
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