How to cite this paper
Rashed, C., Bagum, M & Noshin, R. (2023). Causes and consequences of bullwhip effect on the boutique industry of Dhaka city.Accounting, 9(4), 203-214.
Refrences
Agrawal, S., Sengupta, R. N., & Shanker, K. (2009). Impact of information sharing and lead time on bullwhip effect and on-hand inventory. European Journal of Operational Research, 192(2), 576-593.
Aharon, B. T., Boaz, G., & Shimrit, S. (2009). Robust multi-echelon multi-period inventory control. European Journal of Operational Research, 199(3), 922-935.
Alwan, L. C., Liu, J. J., & Yao, D. Q. (2003). Stochastic characterization of upstream demand processes in a supply chain. IIE Transactions, 35(3), 207-219.
Ben-Daya, M. A., & Raouf, A. (1994). Inventory models involving lead time as a decision variable. Journal of the Operational Research Society, 45(5), 579-582.
Boute, R. N. (2007). Impact of replenishment rules with endogenous lead times on supply chain performance. 4OR, 5(3), 261-264.
Cachon, G. P., & Lariviere, M. A. (1999). Capacity choice and allocation: Strategic behavior and supply chain performance. Management Science, 45(8), 1091-1108.
Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032-1048.
Chaharsooghi, S. K., Faramarzi, H., & Heydari, J. (2008). A simulation study on the impact of forecasting methods on the bullwhip effect in the supply chain. In IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1875-1879). IEEE.
Chandra, C., & Grabis, J. (2005). Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand. European Journal of Operational Research, 166(2), 337-350.
Chatfield, D. C., Kim, J. G., Harrison, T. P., & Hayya, J. C. (2004). The bullwhip effect—impact of stochastic lead time, information quality, and information sharing: a simulation study. Production and Operations Management, 13(4), 340-353.
Chen, L., & Lee, H. L. (2009). Information sharing and order variability control under a generalized demand model. Management Science, 55(5), 781-797.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation (pp. 265-275). Gabler.
Clark, A. J., & Scarf, H. (2004). Optimal policies for a multi-echelon inventory problem. Management Science, 50(12_supplement), 1782-1790.
Dejonckheere, J., Disney, S. M., Lambrecht, M. R., & Towill, D. R. (2002). Transfer function analysis of forecasting induced bullwhip in supply chains. International journal of Production Economics, 78(2), 133-144.
Disney, S. M., Lambrecht, M., Towill, D. R., & Van de Velde, W. (2008). The value of coordination in a two-echelon supply chain. IIE Transactions, 40(3), 341-355.
Geary, S., Disney, S. M., & Towill, D. R. (2006). On bullwhip in supply chains—historical review, present practice and expected future impact. International Journal of Production Economics, 101(1), 2-18.
Giard, V., & Sali, M. (2013). The bullwhip effect in supply chains: a study of contingent and incomplete literature. International Journal of Production Research, 51(13), 3880-3893.
Hamister, J. W., & Suresh, N. C. (2008). The impact of pricing policy on sales variability in a supermarket retail context. International Journal of Production Economics, 111(2), 441-455.
Handfield, R. B., Handfield, R., & Nichols Jr, E. L. (2002). Supply chain redesign: Transforming supply chains into integrated value systems. Financial Times Prentice Hall, 371.
Heydari, J., Baradaran Kazemzadeh, R., & Chaharsooghi, S. K. (2009). A study of lead time variation impact on supply chain performance. The International Journal of Advanced Manufacturing Technology, 40, 1206-1215.
Higuchi, T., & Troutt, M. D. (2004). Dynamic simulation of the supply chain for a short life cycle product—Lessons from the Tamagotchi case. Computers & Operations Research, 31(7), 1097-1114.
Hoberg, K., Bradley, J. R., & Thonemann, U. W. (2007). Analyzing the effect of the inventory policy on order and inventory variability with linear control theory. European Journal of Operational Research, 176(3), 1620-1642.
Holland, W., & Sodhi, M. S. (2004). Quantifying the effect of batch size and order errors on the bullwhip effect using simulation. International Journal of Logistics Research and Applications, 7(3), 251-261.
Hosoda, T., & Disney, S. M. (2004). An analysis of a three echelon supply chain model with minimum mean squared error forecasting. In Second World Conference on POM and 15th Annual POM Conference (pp. 1-24).
Huang, L., & Liu, Y. (2008). Supply chain dynamics under the sustainable development. In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1-6). IEEE.
Jakšič, M., & Rusjan, B. (2008). The effect of replenishment policies on the bullwhip effect: A transfer function approach. European Journal of Operational Research, 184(3), 946-961.
Khan, M. H., Ahmed, S., & Hussain, D. (2019). Analysis of bullwhip effect: a behavioral approach. In Supply Chain Forum: An International Journal (Vol. 20, No. 4, pp. 310-331). Taylor & Francis.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(2), 93-102.
Lee, H. T., & Wu, J. C. (2006). A study on inventory replenishment policies in a two-echelon supply chain system. Computers & Industrial Engineering, 51(2), 257-263.
Leedy, P. D., & Ormrod, J. E. (2001). Practical research: Planning and designing. New Jersey: Merritt Prentice Hall.
Liang, W. Y., & Huang, C. C. (2006). Agent-based demand forecast in multi-echelon supply chain. Decision Support Systems, 42(1), 390-407.
Liao, C. J., & Shyu, C. H. (1991). An analytical determination of lead time with normal demand. International Journal of Operations & Production Management, 11(9), 72-78.
Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. Journal of Marketing, 54(1), 1-26.
Mujaj, Y., Leukel, J., & Kirn, S. (2007). A Reverse Pricing Model for Multi-Tier Supply Chains. In The 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services (CEC-EEE 2007) (pp. 331-340). IEEE.
Paik, S. K., & Bagchi, P. K. (2007). Understanding the causes of the bullwhip effect in a supply chain. International Journal of Retail & Distribution Management, 35(4), 308-324.
Pujawan, I. N. (2004). The effect of lot sizing rules on order variability. European Journal of Operational Research, 159(3), 617-635.
Qualtricks. (2021, March). Retrieved from cross-tabulation: https://www.qualtrics.com/experience-management/research/cross-tabulation/
Şen, A. (2008). The US fashion industry: A supply chain review. International Journal of Production Economics, 114(2), 571-593.
Sohn, S. Y., & Lim, M. (2008). The effect of forecasting and information sharing in SCM for multi-generation products. European Journal of Operational Research, 186(1), 276-287.
Springer, M., & Kim, I. (2010). Managing the order pipeline to reduce supply chain volatility. European Journal of Operational Research, 203(2), 380-392.
Sucky, E. (2009). The bullwhip effect in supply chains—An overestimated problem? International Journal of Production Economics, 118(1), 311-322.
Sun, H. X., & Ren, Y. T. (2005). The impact of forecasting methods on bullwhip effect in supply chain management. In Proceedings. IEEE International Engineering Management Conference. (Vol. 1, pp. 215-219). IEEE.
Svensson, G. (2003). The bullwhip effect in intra‐organisational echelons. International Journal of Physical Distribution & Logistics Management, 33(2), 103-131.
Thonemann, U. W. (2002). Improving supply-chain performance by sharing advance demand information. European Journal of Operational Research, 142(1), 81-107.
Viswanathan, S., Widiarta, H., & Piplani, R. (2007). Value of information exchange and synchronization in a multi-tier supply chain. International Journal of Production Research, 45(21), 5057-5074.
Wang, J., Jia, J., & Takahashi, K. (2005). A study on the impact of uncertain factors on information distortion in supply chains. Production Planning & Control, 16(1), 2-11.
Warburton, R. D., & Disney, S. M. (2007). Order and inventory variance amplification: The equivalence of discrete and continuous time analyses. International Journal of Production Economics, 110(1-2), 128-137.
Zhao, W., & Wang, D. (2008). Application of information sharing to bullwhip effect restraining. In 2008 Chinese Control and Decision Conference (pp. 1143-1146). IEEE.
Aharon, B. T., Boaz, G., & Shimrit, S. (2009). Robust multi-echelon multi-period inventory control. European Journal of Operational Research, 199(3), 922-935.
Alwan, L. C., Liu, J. J., & Yao, D. Q. (2003). Stochastic characterization of upstream demand processes in a supply chain. IIE Transactions, 35(3), 207-219.
Ben-Daya, M. A., & Raouf, A. (1994). Inventory models involving lead time as a decision variable. Journal of the Operational Research Society, 45(5), 579-582.
Boute, R. N. (2007). Impact of replenishment rules with endogenous lead times on supply chain performance. 4OR, 5(3), 261-264.
Cachon, G. P., & Lariviere, M. A. (1999). Capacity choice and allocation: Strategic behavior and supply chain performance. Management Science, 45(8), 1091-1108.
Cachon, G. P., & Fisher, M. (2000). Supply chain inventory management and the value of shared information. Management Science, 46(8), 1032-1048.
Chaharsooghi, S. K., Faramarzi, H., & Heydari, J. (2008). A simulation study on the impact of forecasting methods on the bullwhip effect in the supply chain. In IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1875-1879). IEEE.
Chandra, C., & Grabis, J. (2005). Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand. European Journal of Operational Research, 166(2), 337-350.
Chatfield, D. C., Kim, J. G., Harrison, T. P., & Hayya, J. C. (2004). The bullwhip effect—impact of stochastic lead time, information quality, and information sharing: a simulation study. Production and Operations Management, 13(4), 340-353.
Chen, L., & Lee, H. L. (2009). Information sharing and order variability control under a generalized demand model. Management Science, 55(5), 781-797.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation (pp. 265-275). Gabler.
Clark, A. J., & Scarf, H. (2004). Optimal policies for a multi-echelon inventory problem. Management Science, 50(12_supplement), 1782-1790.
Dejonckheere, J., Disney, S. M., Lambrecht, M. R., & Towill, D. R. (2002). Transfer function analysis of forecasting induced bullwhip in supply chains. International journal of Production Economics, 78(2), 133-144.
Disney, S. M., Lambrecht, M., Towill, D. R., & Van de Velde, W. (2008). The value of coordination in a two-echelon supply chain. IIE Transactions, 40(3), 341-355.
Geary, S., Disney, S. M., & Towill, D. R. (2006). On bullwhip in supply chains—historical review, present practice and expected future impact. International Journal of Production Economics, 101(1), 2-18.
Giard, V., & Sali, M. (2013). The bullwhip effect in supply chains: a study of contingent and incomplete literature. International Journal of Production Research, 51(13), 3880-3893.
Hamister, J. W., & Suresh, N. C. (2008). The impact of pricing policy on sales variability in a supermarket retail context. International Journal of Production Economics, 111(2), 441-455.
Handfield, R. B., Handfield, R., & Nichols Jr, E. L. (2002). Supply chain redesign: Transforming supply chains into integrated value systems. Financial Times Prentice Hall, 371.
Heydari, J., Baradaran Kazemzadeh, R., & Chaharsooghi, S. K. (2009). A study of lead time variation impact on supply chain performance. The International Journal of Advanced Manufacturing Technology, 40, 1206-1215.
Higuchi, T., & Troutt, M. D. (2004). Dynamic simulation of the supply chain for a short life cycle product—Lessons from the Tamagotchi case. Computers & Operations Research, 31(7), 1097-1114.
Hoberg, K., Bradley, J. R., & Thonemann, U. W. (2007). Analyzing the effect of the inventory policy on order and inventory variability with linear control theory. European Journal of Operational Research, 176(3), 1620-1642.
Holland, W., & Sodhi, M. S. (2004). Quantifying the effect of batch size and order errors on the bullwhip effect using simulation. International Journal of Logistics Research and Applications, 7(3), 251-261.
Hosoda, T., & Disney, S. M. (2004). An analysis of a three echelon supply chain model with minimum mean squared error forecasting. In Second World Conference on POM and 15th Annual POM Conference (pp. 1-24).
Huang, L., & Liu, Y. (2008). Supply chain dynamics under the sustainable development. In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (pp. 1-6). IEEE.
Jakšič, M., & Rusjan, B. (2008). The effect of replenishment policies on the bullwhip effect: A transfer function approach. European Journal of Operational Research, 184(3), 946-961.
Khan, M. H., Ahmed, S., & Hussain, D. (2019). Analysis of bullwhip effect: a behavioral approach. In Supply Chain Forum: An International Journal (Vol. 20, No. 4, pp. 310-331). Taylor & Francis.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). Information distortion in a supply chain: The bullwhip effect. Management Science, 43(4), 546-558.
Lee, H. L., Padmanabhan, V., & Whang, S. (1997). The bullwhip effect in supply chains. Sloan Management Review, 38(2), 93-102.
Lee, H. T., & Wu, J. C. (2006). A study on inventory replenishment policies in a two-echelon supply chain system. Computers & Industrial Engineering, 51(2), 257-263.
Leedy, P. D., & Ormrod, J. E. (2001). Practical research: Planning and designing. New Jersey: Merritt Prentice Hall.
Liang, W. Y., & Huang, C. C. (2006). Agent-based demand forecast in multi-echelon supply chain. Decision Support Systems, 42(1), 390-407.
Liao, C. J., & Shyu, C. H. (1991). An analytical determination of lead time with normal demand. International Journal of Operations & Production Management, 11(9), 72-78.
Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. Journal of Marketing, 54(1), 1-26.
Mujaj, Y., Leukel, J., & Kirn, S. (2007). A Reverse Pricing Model for Multi-Tier Supply Chains. In The 9th IEEE International Conference on E-Commerce Technology and The 4th IEEE International Conference on Enterprise Computing, E-Commerce and E-Services (CEC-EEE 2007) (pp. 331-340). IEEE.
Paik, S. K., & Bagchi, P. K. (2007). Understanding the causes of the bullwhip effect in a supply chain. International Journal of Retail & Distribution Management, 35(4), 308-324.
Pujawan, I. N. (2004). The effect of lot sizing rules on order variability. European Journal of Operational Research, 159(3), 617-635.
Qualtricks. (2021, March). Retrieved from cross-tabulation: https://www.qualtrics.com/experience-management/research/cross-tabulation/
Şen, A. (2008). The US fashion industry: A supply chain review. International Journal of Production Economics, 114(2), 571-593.
Sohn, S. Y., & Lim, M. (2008). The effect of forecasting and information sharing in SCM for multi-generation products. European Journal of Operational Research, 186(1), 276-287.
Springer, M., & Kim, I. (2010). Managing the order pipeline to reduce supply chain volatility. European Journal of Operational Research, 203(2), 380-392.
Sucky, E. (2009). The bullwhip effect in supply chains—An overestimated problem? International Journal of Production Economics, 118(1), 311-322.
Sun, H. X., & Ren, Y. T. (2005). The impact of forecasting methods on bullwhip effect in supply chain management. In Proceedings. IEEE International Engineering Management Conference. (Vol. 1, pp. 215-219). IEEE.
Svensson, G. (2003). The bullwhip effect in intra‐organisational echelons. International Journal of Physical Distribution & Logistics Management, 33(2), 103-131.
Thonemann, U. W. (2002). Improving supply-chain performance by sharing advance demand information. European Journal of Operational Research, 142(1), 81-107.
Viswanathan, S., Widiarta, H., & Piplani, R. (2007). Value of information exchange and synchronization in a multi-tier supply chain. International Journal of Production Research, 45(21), 5057-5074.
Wang, J., Jia, J., & Takahashi, K. (2005). A study on the impact of uncertain factors on information distortion in supply chains. Production Planning & Control, 16(1), 2-11.
Warburton, R. D., & Disney, S. M. (2007). Order and inventory variance amplification: The equivalence of discrete and continuous time analyses. International Journal of Production Economics, 110(1-2), 128-137.
Zhao, W., & Wang, D. (2008). Application of information sharing to bullwhip effect restraining. In 2008 Chinese Control and Decision Conference (pp. 1143-1146). IEEE.