A Fuzzy Inference System-Based Approach For Assessing Strategic Capabilities In Global Production Networks

Abstract

Intangible factors, e.g. the availability of infrastructure at a production site, and implicit knowledge, have an essential influence on the decision-making in global production networks. However, the consideration of intangible factors and implicit knowledge, especially in planning the production network configuration and determining the production network strategy, is usually done implicitly or only based on qualitative and subjective estimations. This can cause biased decisions and miscalculations that make additional and expensive adaptions in the global production network necessary. In order to address this challenge, this paper develops a methodology based on fuzzy inference systems (FIS) to enable a more quantitative and objective consideration of strategic network capabilities influenced by intangible factors and implicit knowledge. For this, the strategic network capabilities are described by several criteria aggregated through one or multiple cascading fuzzy inference systems. The resulting metrics for strategic network capabilities as well as intangible factors are normalized and comparable. Transparency about strategic network capabilities allows a focused discussion about the strategic configuration of the production network. Moreover, the metrics can also be used in other quantitative approaches such as mathematical optimization. The proposed methodology is demonstrated with 70 intangible factors, six strategic network capabilities, and 21 sub-capabilities from academic literature. It can be shown that the developed methodology can map intangible factors and implicit knowledge in a very flexible and detailed manner by selecting and weighting the describing criteria within the FIS in order to quantify strategic network capabilities.