[1] Carbonneau, R., Laframboise, K., & Vahidov, R. (2008). Application of machine learning techniques for supply chain demand forecasting. European Journal of Operational Research, 184(3), 1140-1154.
[2] 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.
[3] Disney, S. M., Towill, D. R., & Van de Velde, W. (2004). Variance amplification and the golden ratio in production and inventory control. International Journal of Production Economics, 90(3), 295-309.
[4] Efendigil, T. (2014). Modeling Product Returns in a Closed-Loop Supply Chain Under Uncertainties: A Neuro Fuzzy Approach. Journal of Multiple-Valued Logic & Soft Computing, 23.
[5] Hofmann, E. (2017). Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect. International Journal of Production Research, 55(17), 5108-5126.
[6] Keshari, A., Mishra, N., Shukla, N., McGuire, S., & Khorana, S. (2018). Multiple order-up-to policy for mitigating bullwhip effect in supply chain network. Annals of Operations Research, 269(1-2), 361-386.
[7].Li, G., Yu, G., Wang, S., & Yan, H. (2017). Bullwhip and anti-bullwhip effects in a supply chain. International Journal of Production Research, 55(18), 5423-5434.
[8] Sirikasemsuk, K. Luong H. T. (2017). Measure of bullwhip effect in supply chains with first-order bivariate vector auto regression time-series demand model, Computers & Operations Research 78, 59-79.
[9] Makui, A., & Madadi, A. (2007). The bullwhip effect and Lyapunov exponent. Applied Mathematics and Computation, 189(1), 35-40.
[10] Ouyang, Y., & Li, X. (2010). The bullwhip effect in supply chain networks. European Journal of Operational Research, 201(3), 799-810.
[11] Nepal, B., Murat, A., & Chinnam, R. B. (2012). The bullwhip effect in capacitated supply chains with consideration for product life-cycle aspects. International Journal of Production Economics, 136(2), 318-331.
[12] Tanweer, A., Li, Y. Z., Duan, G., & Song, J. Y. (2014). An optimization model for mitigating bullwhip-effect in a two-echelon supply chain. Procedia-Social and Behavioral Sciences, 138, 289-297.
[13] Sadeghi, A. (2015). Providing a measure for bullwhip effect in a two-product supply chain with exponential smoothing forecasts. International Journal of Production Economics, 169, 44-54.
[14] Trapero, J. R., & Pedregal, D. J. (2016). A novel time-varying bullwhip effect metric: An application to promotional sales. International Journal of Production Economics, 182, 465-471.
[15] Zhao, Y., Cao, Y., Li, H., Wang, S., Liu, Y., Li, Y., & Zhang, Y. (2018). Bullwhip effect mitigation of green supply chain optimization in electronics industry. Journal of cleaner production n, 180, 888-912.
[16] Narayanan, A., Mackelprang, A., & Malhotra, M. (2019, July). Effect of Capacity and Flexibility Constraints on Bullwhip Effect in Supply Chains. In Academy of Management Proceedings (Vol. 2019, No. 1, p. 17864). Briarcliff Manor, NY 10510: Academy of Management.
[17] Martinez‐Moyano, I. J., & Richardson, G. P. (2013). Best practices in system dynamics modeling. System Dynamics Review, 29(2), 102-123.
[18] Wang, N., Ma, Y., He, Z., Che, A., Hung, Y. and Xu, J. (2014). The impact of consumer price forecasting behavior on the bullwhip effect. International Journal of Production Research,52(22): 6642-6663.
[19] Wangphanich, P., Kara, S., & Kayis, B. (2010). Analysis of the bullwhip effect in multi-product, multi-stage supply chain systems–a simulation approach. International journal of production Research, 48(15), 4501-4517.