Incorporating demand, orders, lead time, and pricing decisions for reducing bullwhip effect in supply chains

Document Type : Article

Authors

1 Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran, P.O.BOX 15875-4413

2 Department of Industrial engineering, Amirkabir University of Technology, Tehran, Iran

Abstract

The purpose of this paper is to mitigate bullwhip effect (BWE) in a supply chain (SC). Four main contributions are proposed. The first one is to reduce BWE through considering its multiple causes (demand, pricing, ordering, and lead time) simultaneously. The second one is to model demands, orders, and prices dynamically for reducing BWE. Demand and prices have mutual effect on each other dynamically over time. In other words, a time series model is used in a game theory method for finding the optimal prices in an SC. Moreover, the optimal prices are inserted into the time series model for forecasting price sensitive demands and orders in an SC. The third one is to use demand of each entity for forecasting its orders. This leads to drastic reduction in BWE and mean square error (MSE) of the model. The fourth contribution is to use optimal prices instead of forecasted ones for demand forecasting and reducing BWE. Finally, a numerical experiment for the auto parts SC is developed. The results show that analysing joint demand, orders, lead time, and pricing model with calculating the optimal values of prices and lead times leads to the significant reduction in BWE.

Keywords

Main Subjects


References
1. Forrester, J.W. \Industrial dynamics, a major breakthrough
for decision makers", Harvard Bus. Rev., 36,
pp. 37-66 (1958).
2. Lee, H.L., Padmanabhan, V., and Whang, S. \Information
distortion in a supply chain: The bullwhip
e ect", Manage. Sci., 43(4), pp. 546-558 (1997a).
3. Dominguez, R., Cannella, S., and Framinan, J.M.
\On returns and network con guration in supply chain
dynamics", Transportation Research Part E, 73, pp.
152-167 (2015).
4. Dominguez, R., Cannella, S., and Framinan, J.M.
\The impact of the supply chain structure on bullwhip
e ect", Applied Mathematical Modelling, 39, pp. 7309-
7325 (2015).
5. Cannella, S., Barbosa-Povoa, A.P., Framinan, J.M.,
and Relvas, S. \Metrics for bullwhip e ect analysis",
Journal of the Operational Research Society, 64, pp.
1-16 (2013).
6. Chat eld, D.C., Hayya, J.C., and Cook, D.P. \Stockout
propagation and ampli cation in supply chain inventory
systems", International Journal of Production
Research, 51(5), pp. 1491-1507 (2013).
1740 R. Gamasaee and M.H. Fazel Zarandi/Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 1724{1749
7. Cannella, S., Lopez-Camposb, M., Domingueza, R.,
Ashayeric, J., and Miranda, P.A. \A simulation model
of a coordinated decentralized supply chain", Intl.
Trans. in Op. Res., 22, pp. 735-756 (2015).
8. Lee, H.L., Padmanabhan, V., and Whang. S. \The
bullwhip e ect in supply chains", Sloan Manage Rev.,
38(3), pp. 93-102 (1997b).
9. Ma, Y., Wang, N., Che, A., Huang, Y., and Xu.
J. \The bullwhip e ect under di erent informationsharing
settings: A perspective on price sensitive demand
that incorporates price dynamics", International
Journal of Production Research, 51(10), pp. 3085-3116
(2013a).
10. Ma, Y., Wang, N., Che, A., Huang, Y., and Xu, J.
\The bullwhip e ect on product orders and inventory:
A perspective of demand forecasting techniques", International
Journal of Production Research, 51(1), pp.
281-302 (2013b).
11. Metters, R. \Quantifying the bullwhip e ect in supply
chains", J. Oper. Manage, 15(2), pp. 89-100 (1997).
12. Chen, F., Drezner, Z., Ryan, J.K., and Simchi-Levi,
D. \Quantifying the bullwhip e ect in a simple supply
chain: The impact of forecasting, lead times, and
information", Manage. Sci., 46(3), pp. 436-443 (2000).
13. Dejonckheere, J., Disney, S.M., Lambrecht, M.R., and
Towill, D.R. \Transfer function analysis of forecasting
induced bullwhip in supply chains", Int. J. Prod.
Econ., 78(2), pp. 133-144 (2002).
14. Chandra, Ch. and Grabis, J. \Application of multisteps
forecasting for restraining the bullwhip e ect and
improving inventory performance under autoregressive
demand", Eur. J. Oper. Res., 166, pp. 337-350 (2005).
15. Hosoda, T. and Disney, S.M. \On variance ampli -
cation in a three-echelon supply chain with minimum
mean square error forecasting", Omega, 34, pp. 344-
358 (2006).
16. Sucky, E. \The bullwhip e ect in supply chains|
an overestimated problem?", Int. J. Production Economics,
118, pp. 311-322 (2009).
17. Wang, N., Ma, Y., He, Zh., Che, A., Huang, Y.
and Xu, J. \The impact of consumer price forecasting
behavior on the bullwhip e ect", International Journal
of Production Research, 52(22), pp. 6642-6663 (2014).
18. Fazel Zarandi, M.H. and Gamasaee, R. \A type-2 fuzzy
system model for reducing bullwhip e ects in supply
chains and its application in steel manufacturing", Scientia
Iranica, Transactions E: Industrial Engineering,
20(3), pp. 879-899 (2013).
19. Nepal, B., Murat, A., and Chinnam, R.B. \The
bullwhip e ect in capacitated supply chains with
consideration for product life-cycle aspects", Int. J.
Production Economics, 136, pp. 318-331 (2012).
20. Adenso-Daz, B., Moreno, P., Gutierrez, E., and
Lozano, S. \An analysis of the main factors a ecting
bullwhip in reverse supply chains", Int. J. Production
Economics, 135(2), pp. 917-928 (2012).
21. Ciancimino, E., Cannella, S., Bruccoleri, M., and
Framinan, J.M. \On the bullwhip avoidance phase:
The synchronised supply chain", Eur. J. Oper. Res.,
221(1), pp. 49-63 (2012).
22. Samvedi, A. and Jain, V. \A grey approach for
forecasting in a supply chain during intermittent disruptions",
Eng. Appl. Artif. Intel., 26, pp. 1044-1051
(2013).
23. Lau, H.C.W., Ho, G.T.S., and Zhao, Y. \A demand
forecast model using a combination of surrogate data
analysis and optimal neural network approach", Decis.
Support. Syst., 54(3), pp. 1404-1416 (2013).
24. Cho, D.W. and Lee, Y.H. \The value of information
sharing in a supply chain with a seasonal demand
process", Computers & Industrial Engineering, 65(1),
pp. 97-108 (2013).
25. Montanari, R., Ferretti, G., Rinaldi, M., and Bottani,
E. \Investigating the demand propagation in EOQ
supply networks using a probabilistic model", International
Journal of Production Research, 53(5), pp.
1307-1324 (2015).
26. Kelle, P. and Milne, A. \The e ect of (s,S) ordering
policy on the supply chain", Int. J. Prod. Econ., 59,
pp. 113-122 (1999).
27. Lee, H.T. and Wu, J.C \A study on inventory replenishment
policies in a two-echelon supply chain system",
Comput. Ind. Eng., 51(2), pp. 257-263 (2006).
28. Potter, A. and Disney, S.M. \Bullwhip and batching:
An exploration", Int. J. Prod. Econ., 104(2), pp. 408-
418 (2006).
29. Sodhi, M.S. and Tang. Ch.S. \The incremental bullwhip
e ect of operational deviations in an arborescent
supply chain with requirements planning", Eur. J.
Oper. Res., 215, pp. 374-382 (2011).
30. Wang, J-L., Kuo, J-H., Chou, Sh-Y., and Wang, Sh-
Zh. \A comparison of bullwhip e ect in a single-stage
supply chain for autocorrelated demands when using
correct, MA, and EWMA methods", Expert. Syst.
Appl., 37(7), pp. 4726-4736 (2010).
31.  Ozelkan, E.C. and Lim, C. \Conditions of reverse
bullwhip e ect in pricing for price-sensitive demand
functions", Ann. Oper. Res., 164, pp. 211-227 (2008).
32.  Ozelkan, E.C. and Cakanyildirim, M. \Reverse bullwhip
e ect in pricing", Eur. J. Oper. Res., 192, pp.
302-312 (2009).
33. Zhang, X. and Burke, G.J. \Analysis of compound
bullwhip e ect causes", Eur. J. Oper. Res., 210, pp.
514-526 (2011).
34. Cachon, G.P. and Lariviere, M.A. \Capacity choice
and allocation: Strategic behavior and supply chain
performance", Manage. Sci., 45(8), pp. 1091-1108
(1999).
35. Agrawal, S., Nandan Sengupta, R., and Shanker,
K. \Impact of information sharing and lead time on
bullwhip e ect and on-hand inventory", Eur. J. Oper.
Res., 192, pp. 576-593 (2009).
R. Gamasaee and M.H. Fazel Zarandi/Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 1724{1749 1741