Enhanced sourcing strategy for centralized multitier multiple suppliers network with failure risks

Abstract

Purpose

This paper attempts to address three key objectives. The primary aim is to enhance sourcing strategy for a centralized and coordinated multitier multiple suppliers networks with uncertain demand and supplier failure risks. The second objective is to enumerate all possible practical supplier(s) failure scenarios and quantify expected loss of demand cost. Finally, the work illustrates statistical experimentation to identify “influential” variables that can significantly impact the expected supply network and loss costs.

Design/methodology/approach

A seven-step solution framework is proposed to derive an optimal sourcing strategy for the specific network configuration with varied supplier failure scenarios. Five distinct models are formulated to address all possible scenarios of supplier failure events. Mixed-integer nonlinear programming technique is used to derive expected supply network cost and loss cost. The solution framework is verified using a real-life case.

Findings

A cross-case analysis indicates that an increase in suppliers' failure risk (SFR) probabilities or customer demand rate increases the expected loss of demand costs for a multitier supply network. Besides, an increase in unit component prices increases the expected supply network cost.

Research limitations/implications

A two-tier automotive supply network for a single product is considered for all case studies.

Practical implications

The enhanced strategy can facilitate practitioners enumerate different supply network failure scenarios and implement the best solution.

Originality/value

There is no evidence of earlier research to derive optimal sourcing strategy for a centralized, coordinated multitier multiple supplier's network, considering demand uncertainties and SFR.

Citation

Bagul, A. and Mukherjee, I. (2022), "Enhanced sourcing strategy for centralized multitier multiple suppliers network with failure risks", International Journal of Productivity and Performance Management, Vol. 71 No. 1, pp. 211-244. https://doi.org/10.1108/IJPPM-04-2020-0179