Research on supply chain sourcing decision under the dual disturbance of demand uncertainty and forecast inaccuracy

WANG Junjin, LIU Jiaguo, SHI Lei, ZHOU Huan

Systems Engineering - Theory & Practice ›› 2022, Vol. 42 ›› Issue (11) : 2869-2880.

PDF(944 KB)
PDF(944 KB)
Systems Engineering - Theory & Practice ›› 2022, Vol. 42 ›› Issue (11) : 2869-2880. DOI: 10.12011/SETP2021-2320

Research on supply chain sourcing decision under the dual disturbance of demand uncertainty and forecast inaccuracy

  • WANG Junjin1, LIU Jiaguo1, SHI Lei1, ZHOU Huan2
Author information +
History +

Abstract

Motivated by the trend of overseas/cross-regional firms returning to domestic/local and the background of COVID-19 normalization, a sourcing decision model is proposed based on the cost-signal game under the demand uncertainty and forecast inaccuracy. We explore the trade-off between the efficient cross-regional sourcing and responsive local sourcing. The results show that the sourcing decision depends on the linkage performances of cost and information. Cross-regional sourcing always brings mighty cost performance, while the local sourcing can not always give full play to information performance advantage. Because if both firms choose local sourcing, the correlation effect between forecast information will hedge signal accuracy effect. Greater demand uncertainty and more accurate cross-regional sourcing forecast are driving films to return. Interestingly, this return may benefit all the firms, and break the Prisoner's Dilemma of symmetric cross-regional sourcing. The reason is that the returning can alleviate competition by inducing a new equilibrium sourcing structure. In response, this mixed equilibrium endows firms with “follower advantage” to realize local-Pareto improvement. With the increase of demand uncertainty and forecast inaccuracy, this mixed equilibrium will turn to the symmetric local sourcing, which temporarily reaches the overall Pareto-optimum. However, it will eventually fall into the Prisoner's Dilemma of lose-lose situation. In addition, it is also found that the poor local sourcing forecast will endow firms with ''mover advantage'', which will lead to the mover becoming better while the follower becoming worse.

Key words

sourcing decision / cross-regional sourcing / local sourcing / demand uncertainty / forecast inaccuracy / COVID-19 epidemic

Cite this article

Download Citations
WANG Junjin , LIU Jiaguo , SHI Lei , ZHOU Huan. Research on supply chain sourcing decision under the dual disturbance of demand uncertainty and forecast inaccuracy. Systems Engineering - Theory & Practice, 2022, 42(11): 2869-2880 https://doi.org/10.12011/SETP2021-2320

References

[1] Wu X L, Zhang F Q. Home or overseas? An analysis of sourcing strategies under competition[J]. Management Science, 2014, 60(5): 1223-1240.
[2] Ferreira J, Prokopets L. Does offshoring still make sense?[J]. Supply Chain Management Review, 2009, 13(1): 20-27.
[3] Fisher M L. What is the right supply chain for your product?[J]. Harvard Business Review, 1997, 75: 105-117.
[4] Elmaghraby W J. Supply contract competition and sourcing policies[J]. Manufacturing & Service Operations Management, 2000, 2(4): 350-371.
[5] Li Y, Lim A, Rodrigues B. Global sourcing using local content tariff rules[J]. IIE Transactions, 2007, 39(5): 425-437.
[6] Burke G J, Carrillo J E, Vakharia A J. Single versus multiple supplier sourcing strategies[J]. European Journal of Operational Research, 2007, 182(1): 95-112.
[7] Özer Ö, Raz G. Supply chain sourcing under asymmetric information[J]. Production and Operations Management, 2011, 20(1): 92-115.
[8] Choi T M. Multi-period risk minimization purchasing models for fashion products with interest rate, budget, and profit target considerations[J]. Annals of Operations Research, 2016, 237(1-2): 77-98.
[9] Niu B Z, Mu Z H, Chen K L. Quality spillover, tariff, and multinational firms' local sourcing strategies[J]. International Transactions in Operational Research, 2019, 26(6): 2508-2530.
[10] 刘阳, 田军, 冯耕中. 基于数量柔性契约与Markov链的应急物资采购模型[J]. 系统工程理论与实践, 2020, 40(1): 119-133.Liu Y, Tian J, Feng G Z. Government's relief supplies procurement model based on quantity flexible contract and Markov chain[J]. Systems Engineering — Theory & Practice, 2020, 40(1): 119-133.
[11] Iyer A V, Bergen M E. Quick response in manufacturer-retailer channels[J]. Management Science, 1997, 43(4): 559-570.
[12] Gurnani H, Tang C S. Note: Optimal ordering decisions with uncertain cost and demand forecast updating[J]. Management Science, 1999, 45(10): 1456-1462.
[13] Donohue K L. Efficient supply contracts for fashion goods with forecast updating and two production modes[J]. Management Science, 2000, 46(11): 1397-1411.
[14] Choi T M. Local sourcing and fashion quick response system: The impacts of carbon footprint tax[J]. Transportation Research Part E: Logistics and Transportation Review, 2013, 55: 43-54.
[15] 陈志刚, 王先甲, 方德斌. 双渠道订货条件下基于预测更新过程的报童模型研究[J]. 系统工程理论与实践, 2018, 38(11): 2805-2816.Chen Z G, Wang X J, Fang D B. A dual sourcing newsvendor model with forecast evolution process[J]. Systems Engineering — Theory & Practice, 2018, 38(11): 2805-2816.
[16] Cachon G P, Swinney R. The value of fast fashion: Quick response, enhanced design, and strategic consumer behavior[J]. Management Science, 2011, 57(4): 778-795.
[17] Yang D J, Qi E, Li Y J. Quick response and supply chain structure with strategic consumers[J]. Omega, 2015, 52: 1-14.
[18] Lee C H, Choi T M, Cheng T C E. Selling to strategic and loss-averse consumers: Stocking, procurement, and product design policies[J]. Naval Research Logistics, 2015, 62(6): 435-453.
[19] Wang T, Thomas D J, Rudi N. The effect of competition on the efficient-responsive choice[J]. Production and Operations Management, 2014, 23(5): 829-846.
[20] Li L, Zhang H T. Confidentiality and information sharing in supply chain coordination[J]. Management Science, 2008, 54(8): 1467-1481.
[21] Niu B Z, Chen L, Zou Z B, et al. Demand signal transmission in a certified refurbishing supply chain: Rules and incentive analysis[J]. Annals of Operations Research, 2019(1): 1-46.
[22] Anand K S, Goyal M. Strategic information management under leakage in a supply chain[J]. Management Science, 2009, 55(3): 438-452.
[23] Niu B Z, Dai Z P, Chen L. Information leakage in a cross-border logistics supply chain considering demand uncertainty and signal inference[J]. Annals of Operations Research, 2022, 309(2): 785-816.
[24] Shin H, Tunca T I. Do firms invest in forecasting efficiently? The effect of competition on demand forecast investments and supply chain coordination[J]. Operations Research, 2010, 58(6): 1592-1610.
[25] Taylor T A, Xiao W Q. Does a manufacturer benefit from selling to a better-forecasting retailer?[J]. Management Science, 2010, 56(9): 1584-1598.
[26] Lester T. Making it safe to rely on a single partner[N]. Financial Times, 2002-04-01.
[27] Yue X, Liu J. Demand forecast sharing in a dual-channel supply chain[J]. European Journal of Operational Research, 2006, 174(1): 646-667.
[28] Ericson W A. A note on the posterior mean of a population mean[J]. Journal of the Royal Statistical Society: Series B: Methodological, 1969, 31(2): 332-334.
[29] Li L. Cournot oligopoly with information sharing[J]. The RAND Journal of Economics, 1985, 16(4): 521-536.
[30] Choi T M, Wallace S W, Wang Y. Big data analytics in operations management[J]. Production and Operations Management, 2018, 27(10): 1868-1883.
[31] Niu B X, Dai Z P, Zhuo X P. Co-opetition effect of promised-delivery-time sensitive demand on air cargo carriers' big data investment and demand signal sharing decisions[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 123(3): 29-44.
[32] Bjoern B, Andreas W. Challenges and success factors of air cargo revenue management[J]. Journal of Revenue and Pricing Management, 2010, 9(1/2): 171-184.

Funding

Key Project of the National Social Science Foundation of China (22AGL020)
PDF(944 KB)

1207

Accesses

0

Citation

Detail

Sections
Recommended

/