One-way Substitution Purchasing Strategy of Organic Agricultural Products under Supply Disruption Risk

2021 ◽  
Author(s):  
Cong Jia
2018 ◽  
Vol 10 (9) ◽  
pp. 3293 ◽  
Author(s):  
Kelei Xue ◽  
Ya Xu ◽  
Lipan Feng

Supply disruption is a common phenomenon in industry, which brings destructive effects to downstream firms and damages the sustainability of the supply chain. To mitigate the supply disruption risk, the authors investigate two types of procurement strategies for a firm with two ordering opportunities. Through establishing Stackelberg game models, the authors drive the supplier’s optimal production, and the firm’s optimal procurement and replenishment strategies under the option purchase (OP) strategy and the procurement commitment (PC) strategy, respectively. The findings show that, under both types of strategies, the firm’s procurement follows a “threshold” principle. Moreover, the firm’s procurement quantity can be represented by two newsvendor solutions. A lower option price or option exercise price benefits the firm, while it damages the supplier. The supplier benefits from a higher mean value (MV) of emergency procurement price and the firm benefits from a lower market demand variability. Counter-intuitively, a lower MV of the emergency procurement price is not always beneficial to the firm. A higher market demand variability could be beneficial to the supplier under the PC strategy. The firm should first choose the PC strategy and then change to the OP strategy as the disruption risk increases.


2020 ◽  
Vol 22 (1) ◽  
pp. 247-262
Author(s):  
Eley Suzana Kasim ◽  
Dalila Daud ◽  
Jamaliah Said ◽  
Norlaila Md Zin ◽  
Elisa Kusrini

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dayanidhi Jena ◽  
Pritee Ray

Purpose The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement. Design/methodology/approach A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha. Findings From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases. Research limitations/implications The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well. Practical implications This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant. Originality/value This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).


2018 ◽  
Vol 21 (4) ◽  
pp. 883-895 ◽  
Author(s):  
Jie Xiang ◽  
Juliang Zhang ◽  
Jose Maria Sallan

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