[1] Juan Zhiru, Wang Haiyan,. Demand change detection and inventory costs minimization [J]. Journal of Southeast University (English Edition), 2016, 32 (3): 385-390. [doi:10.3969/j.issn.1003-7985.2016.03.021]
Copy
Demand change detection and inventory costs minimization(
)
需求变化检测和库存成本最小化
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 32
- Issue:
- 2016 3
- Page:
- 385-390
- Research Field:
- Economy and Management
- Publishing date:
- 2016-09-20
Info
- Title:
- Demand change detection and inventory costs minimization
- 需求变化检测和库存成本最小化
- Author(s):
- Juan Zhiru, Wang Haiyan
- School of Economics and Management, Southeast University, Nanjing 210096, China
- PACS:
- F252
- DOI:
- 10.3969/j.issn.1003-7985.2016.03.021
- Abstract:
- To minimize the inventory costs of detecting demand change, an acceptance/rejection method(threshold)is proposed. The proposed threshold can be identified by the newsvendor based on the excess cost, the shortage cost, the transitional probability of the demand change, and the magnitude of the demand change. Compared with the single exponential smoothing method, it is proved that the proposed method can save many more inventory costs when detecting a step change in demand. By analyzing the proposed method, it shows that as the magnitude of step change increases, the supply chain members turn to synchronously judge a step change, and as excess(shortage)cost increases, a newsvendor tends to respond slowly(early)to an increase in demand and responds early(slowly)to a decrease in demand. Observations from this study suggest that supply chain members should pay careful attention to different profit-margin products and different magnitude demand changes in cooperating and sharing demand information with others.
- 为了降低检测需求变化时的库存成本, 给出了一种接受/拒绝方法(阈值).该方法的阈值由报童的超出成本、缺货成本、需求变化概率和需求变化幅度共同决定.通过与指数平滑预测方法的对比实验, 证明了所提方法可以帮助报童节约更多的库存成本.此外, 通过对所提方法的分析发现, 随着需求变化幅度的增加, 供应链成员对需求变化的判断越来越同步;随着超出(缺货)成本的增加, 报童会越来越倾向于对需求增长作出过晚(过早)的反应, 而对需求减少作出过早(过晚)的反应.这表明供应链成员在与其他供应链成员进行合作和分享需求信息时应该审慎考虑由不同利润率的产品及不同变化幅度的需求所造成的影响.
References:
[1] Massey C, Wu G. Detecting regime shifts: The causes of under- and overreaction [J]. Management Science, 2005, 51(6): 932-947. DOI:10.1287/mnsc.1050.0386.
[2] Hardy E D. Barnes & Noble seeing heavy demand for Nook e-book reader [EB/OL].(2009-11-08)[2015-06-01].http://www.brighthand.com/news/barnes-noble-seeing-heavy-demand-for-nook-e-book-reader/.
[3] Worthen B. Future results not guaranteed: Contrary to what vendors tell you, computer systems alone are incapable of producing accurate forecasts [EB/OL].(2003-09-11)[2016-08-23]. http://www.cio.com.au/article/168757/future-results-guaranteed/.
[4] Tokar T, Aloysius J, Williams B, et al. Bracing for demand shocks: An experimental investigation [J]. Journal of Operations Management, 2014, 32(4): 205-216. DOI:10.1016/j.jom.2013.08.001.
[5] Akcay A, Biller B, Tayur S. Improved inventory targets in the presence of limited historical demand data [J]. Manufacturing & Service Operations Management, 2011, 13(3): 297-309. DOI:10.1287/msom.1100.0320.
[6] Sanders N R, Manrodt K B. Forecasting software in practice: Use, satisfaction, and performance [J]. Interfaces, 2003, 33(5): 90-93. DOI:10.1287/inte.33.5.90.19251.
[7] Sanders N R, Manrodt K B. The efficacy of using judgmental versus quantitative forecasting methods in practice [J]. Omega: The International Journal of Management Science, 2003, 31(6): 511-522. DOI:10.1016/j.omega.2003.08.007.
[8] Nassirtoussi A K, Aghabozorgi S, Wah T H, et al. Text minings of news-headlines for FOREX market prediction: a multi-layer dimension reducing algorithm with semantics and sentiment [J]. Expert Systems with Applications, 2015, 42(1): 306-324. DOI:10.1016/j.eswa.2014.08.004.
[9] Xie K L, Zhang Z L, Zhang Z Q. The business value of online consumer reviews and management response to hotel performance [J]. International Journal of Hospitality Management, 2014, 43: 1-12. DOI:10.1016/j.ijhm.2014.07.007.
[10] Goodwin P. Integrating management judgment and statistical methods to improve short-term forecasts [J]. Omega: The International Journal of Management Science, 2002, 30(2): 127-135. DOI:10.1016/s0305-0483(01)00062-7.
[11] Syntetos A A, Nikilopoulos K, Boylan J E. Judging the judges through accuracy-implication metrics: The case of inventory forecasting [J]. International Journal of Forecasting, 2010, 26(1):134-143.
[12] Swets J A, Tanner W P Jr, Birdsall T G. Decision processes in perception [J]. Psychological Review, 1961, 68(5): 301-340. DOI:10.1037/h0040547.
[13] Lynn S K, Barrett L E. ‘Utilizing’ signal detection theory [J]. Psychological Science, 2014, 25(9): 1663-1673. DOI:10.1177/0956797614541991.
[14] Lau H S. Simple formulas for the expected costs in the newsboy problem: An educational note [J]. European Journal of Operational Research, 1997, 100(3): 557-561. DOI:10.1016/s0377-2217(96)00117-8.
[15] Muth J F. Optimal properties of exponentially weighted forecasts [J]. Journal of the American Statistical Association, 1960, 55(290): 299-306. DOI:10.2307/2281742.
[16] Graves S C. A single-item inventory model for a nonstationary demand process [J]. Manufacturing & Service Operations Management, 1999, 1(1): 50-61. DOI:10.1287/msom.1.1.50.
Memo
- Memo:
-
Biographies: Juan Zhiru(1986—), male, graduate; Wang Haiyan(corresponding author), male, doctor, professor, hywang@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.71171049, 71390335).
Citation: Juan Zhiru, Wang Haiyan. Demand change detection and inventory costs minimization[J].Journal of Southeast University(English Edition), 2016, 32(3):385-390.DOI:10.3969/j.issn.1003-7985.2016.03.021.