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Impacts of Hyperbolic Discounting on Inventory Replenishment Policy Under Inflation
Yongwu ZHOU, Zhaozhan LIN
Journal of Systems Science and Information ›› 2016, Vol. 4 ›› Issue (1) : 24-39.
PDF(264 KB)
PDF(264 KB)
Impacts of Hyperbolic Discounting on Inventory Replenishment Policy Under Inflation
Considering time inconsistency and inter-temporal preference of the decision maker who is facing inter-temporal choices, this paper employs hyperbolic discounting to reflect these characteristics in governing inventory replenishment policy under inflation. The authors take the subjective perception of the decision maker and the objective indicator from the capital market into consideration. The decision maker's subjective perception includes confidence towards future value of money and anxiety to return the money, while the objective indicator is represented by the compounded discount rate. The results suggest that over the given planning horizon, with more confidence, inventory policy of larger order quantity and smaller order frequency should be adopted; with more anxiety within a threshold, inventory policy of smaller order quantity and larger order frequency should be adopted, and with more anxiety beyond this threshold, inventory policy keeps unchanged; with a larger discount rate, inventory policy of smaller order quantity and larger order frequency should be adopted.
inventory / hyperbolic discounting / time value of money / time inconsistency / deteriorating items {{custom_keyword}} /
[1] Adams A, Cherchye L, Rock B D, et al. Consume now or later? Time inconsistency, collective choice, and revealed preference. American Economic Review, 2014, 104(12): 4147-4183.
[2] Baucells M, Heukamp F H. Probability and time trade-off. Management Science, 2012, 58(4): 831-842.
[3] Ebert S, Strack P. Until the bitter end: On prospect theory in a dynamic context. American Economic Review, 2015, 105(4): 1618-1633.
[4] Jackson M O, Yariv L. Present bias and collective dynamic choice in the lab. American Economic Review, 2014, 104(12): 4184-4204.
[5] Read D, Frederick S, Orsel B, et al. Four score and seven years from now: The data/delay effect in temporal discounting. Management Science, 2005, 51(9): 1326-1335.
[6] Ainslie G. Pure hyperbolic discount curves predict “eyes open” self-control. Theory and Decision, 2012, 73(1): 3-34.
[7] Biais B, Hombert J, Weill P O. Equilibrium pricing and trading volume under preference uncertainty. Review of Economic Studies, 2014, 81: 1401-1437.
[8] Frederick S, Loewenstein G, O'Donoghue T. Time discounting and time preference: A critical review. Journal of Economic Literature, 2002, 40(2): 351-401.
[9] Huang Y S, Hsu C Z. An anticipative hyperbolic discount utility on intertemporal decision making. European Journal of Operational Research, 2008, 184(1): 281-290.
[10] Olea J L M, Strzalecki T. Axiomatization and measurement of quasi-hyperbolic discounting. Quarterly Journal of Economics, 2014, 129(3): 1449-1499.
[11] Toubia O, Johnson E, Evgeniou T, et al. Dynamic experiments for estimating preferences: An adaptive method of eliciting time and risk parameters. Management Science, 2013, 59(3): 613-640.
[12] Scholten M, Read D. Discounting by intervals: A generalized model of intertemporal choice. Management Science, 2006, 52(9): 1424-1436.
[13] Abdellaoui M, Diecidue E, Öncüler A. Risk preferences at different time periods: An experimental investigation. Management Science, 2011, 57(5): 975-987.
[14] Attema A E, Bleichrodt H, Rhode K I M, et al. Time-tradeoff sequences for analyzing discounting and time inconsistency. Management Science, 2010, 56(11): 2015-2030.
[15] Sayman S, Öncüler A. An investigation of time-inconsistency. Management Science, 2009, 55(3): 470-482.
[16] Zauberman G, Kim B K, Malkoc S A, et al. Discounting time and time discounting: Subjective time perception and intertemporal preferences. Journal of Marketing Research, 2009, 46(4): 543-556.
[17] Laibson D. Golden eggs and hyperbolic discounting. Quarterly Journal of Economics, 1997, 112(2): 443-477.
[18] Angeletos G M, Laibson D, Repetto A, et al. The hyperbolic consumption model: Calibration, simulation, and empirical evaluation. Journal of Economic Perspectives, 2001, 15(3): 47-68.
[19] Rohde K I M. The hyperbolic factor: A measure of time inconsistency. Journal of Risk and Uncertainty, 2010, 41(2): 125-140.
[20] Harris C, Laibson D. Instantaneous gratification. Quarterly Journal of Economics, 2013, 128(1): 205-248.
[21] Bendoly E, Croson R, Goncalves P, et al. Bodies of knowledge for research in behavioral operations. Production and Operations Management, 2010, 19(4): 434-452.
[22] Gans N, Croson R. Introduction to the special issue on behavioral operations. Manufacturing & Service Operations Management, 2008, 10(4): 563-565.
[23] Gino F, Pisano G. Toward a theory of behavioral operations. Manufacturing & Service Operations Management, 2008, 10(4): 676-691.
[24] Su X. Bounded rationality in newsvendor models. Manufacturing & Service Operations Management, 2008, 10(4): 566-589.
[25] Huang T, Allon G, Bassamboo A. Bounded rationality in service systems. Manufacturing & Service Operations Management, 2013, 15(2): 263-279.
[26] Plambeck E L, Wang Q. Implications of hyperbolic discounting for optimal pricing and scheduling of unpleasant services that generate future benefits. Management Science, 2013, 59(8): 1927-1946.
[27] Chen L, Kök A G, Tong J D. The effect of payment schemes on inventory decisions: The role of mental accounting. Management Science, 2013, 59(2): 436-451.
[28] Hariga M A. Optimal EOQ models for deteriorating items with time-varying demand. Journal of the Operational Research Society, 1996, 47(10): 1228-1246.
[29] Benkherouf L, Mahmoud M G. On an inventory model for deteriorating items with increasing time-varying demand and shortages. Journal of the Operational Research Society, 1996, 47(1): 188-200.
[30] Yang H L, Teng J T, Chern M S. Deterministic inventory lot-size models under inflation with shortages and deterioration for fluctuating demand. Naval Research Logistics, 2001, 48(2): 144-158.
[31] Yang H L, Teng J T, Chern M S. An inventory model under inflation for deteriorating items with stockdependent consumption rate and partial backlogging shortages. International Journal of Production Economics, 2010, 123(1): 8-19.
[32] Trippi R R, Lewin D E. A present value formulation of the classical EOQ problem. Decision Science, 1974, 5(1): 30-35.
[33] Moon I, Yun W. An economic order quantity model with a random planning horizon. The Engineering Economist, 1993, 39(1): 77-86.
[34] Hariga M A. Economic analysis of dynamic inventory models with non-stationary costs and demand. International Journal of Production Economics, 1994, 36(3): 255-266.
[35] Bakker M, Riezebos J, Teunter R H. Review of inventory systems with deterioration since 2001. European Journal of Operational Research, 2012, 221(2): 275-284.
[36] Pentico D W, Drake M J. A survey of deterministic models for the EOQ and EPQ with partial backordering. European Journal of Operational Research, 2011, 214(2): 179-198.
[37] Bose S, Goswami A, Chaudhuri A, et al. An EOQ model for deteriorating items with linear time-dependent demand rate and shortages under inflation and time discounting. Journal of the Operational Research Society, 1995, 46(6): 771-782.
[38] Chung K J, Liu J, Tsai S F. Inventory systems for deteriorating items taking account of time value. Engineering Optimization, 1997, 27(4): 303-320.
[39] Chung K J, Lin C N. Optimal inventory replenishment models for deteriorating items taking account of time discounting. Computers & Operations Research, 2001, 28(1): 67-83.
[40] Moon I, Giri B C, Ko B. Economic order quantity models for ameliorating/deteriorating items under inflation and time discounting. European Journal of Operational Research, 2005, 162(3): 773-785.
[41] Gilding B H. Inflation and the optimal inventory replenishment schedule within a finite planning horizon. European Journal of Operational Research, 2014, 234(3): 683-693.
Supported by National Natural Science Foundation of China (71131003, 71201061, 71371075), the Fundamental Research Funds for the Central Universities (2014ZZ0072), Guangdong Natural Science Foundation (2014A030310212)
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