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Mitigating Hi-tech products risks due to rapid technological innovation

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  • Yang, P.C.
  • Wee, H.M.
  • Liu, B.S.
  • Fong, O.K.
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    Abstract

    The risks on international trade have increased continuously in recent years. One such risk for Hi-tech products is the result of rapid technological innovation, which results in a significant decline in the component cost, the selling price and the demand (due to newer products introduction). The Hi-tech products include computers and communication consumer products. From a practical viewpoint, there is a need to develop an innovative replenishing policy to consider the impact of the risk. In this paper, an economic order quantity model with finite planning horizon is developed for a buyer, when the component cost, the selling price and the demand rate of the end-consumer decline at a continuous rate. A numerical example and sensitivity analysis for two case studies are carried out to illustrate this model.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 39 (2011)
    Issue (Month): 4 (August)
    Pages: 456-463

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    Handle: RePEc:eee:jomega:v:39:y:2011:i:4:p:456-463

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    Keywords: Hi-tech products Innovation Replenishment policy Risks;

    References

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    1. Erel, E, 1992. "The effect of continuous price change in the EOQ," Omega, Elsevier, vol. 20(4), pages 523-527, July.
    2. Kevin Hsu, Wen-Kai & Yu, Hong-Fwu, 2009. "EOQ model for imperfective items under a one-time-only discount," Omega, Elsevier, vol. 37(5), pages 1018-1026, October.
    3. Ramasesh, Ranga V., 2010. "Lot-sizing decisions under limited-time price incentives: A review," Omega, Elsevier, vol. 38(3-4), pages 118-135, June.
    4. Wee, H.M. & Yu, Jonas & Chen, M.C., 2007. "Optimal inventory model for items with imperfect quality and shortage backordering," Omega, Elsevier, vol. 35(1), pages 7-11, February.
    5. Hariga, Moncer A. & Benkherouf, Lakdere, 1994. "Optimal and heuristic inventory replenishment models for deteriorating items with exponential time-varying demand," European Journal of Operational Research, Elsevier, vol. 79(1), pages 123-137, November.
    6. Wang, Kung-Jeng & Wee, Hui-Ming & Gao, Shin-Feng & Chung, Shen-Lian, 2005. "Production and inventory control with chaotic demands," Omega, Elsevier, vol. 33(2), pages 97-106, April.
    7. Khouja, Moutaz & Park, Sungjune, 2003. "Optimal lot sizing under continuous price decrease," Omega, Elsevier, vol. 31(6), pages 539-545, December.
    8. Wee, Hui-Ming, 1995. "Joint pricing and replenishment policy for deteriorating inventory with declining market," International Journal of Production Economics, Elsevier, vol. 40(2-3), pages 163-171, August.
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    Cited by:
    1. Sarkar, Mitali & Sarkar, Biswajit, 2013. "An economic manufacturing quantity model with probabilistic deterioration in a production system," Economic Modelling, Elsevier, vol. 31(C), pages 245-252.
    2. Zhang, Juan & Gou, Qinglong & Liang, Liang & Huang, Zhimin, 2013. "Supply chain coordination through cooperative advertising with reference price effect," Omega, Elsevier, vol. 41(2), pages 345-353.
    3. Chung-Yuan Dye & Tsu-Pang Hsieh, 2013. "A particle swarm optimization for solving lot-sizing problem with fluctuating demand and preservation technology cost under trade credit," Journal of Global Optimization, Springer, vol. 55(3), pages 655-679, March.
    4. Wee, Hui Ming & Widyadana, Gede Agus, 2013. "A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule," Omega, Elsevier, vol. 41(6), pages 941-954.

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