A model to determine complexity in supply networks

Abstract

Purpose

The purpose of this paper is to further advance an existing supplier evaluation model for the purpose of identifying those supplier relations which predominantly threaten or worsen a company's performance. A defined basic set of parameters to determine complexity facilitates the identification of critical locations within a supply network (SN) under certain business conditions.

Design/methodology/approach

This paper is based on a structured literature review in scientific periodicals in logistics/supply chain management between 2000 and 2009. Articles are analysed based on a structured framework and the identified complexity parameters are operationalised using quantitative and summable measures. The conceptual model is applied within a multiple case study in the Austrian agricultural industry.

Findings

This paper illustrates how complexity in SNs can be operationalised in a company‐specific configuration in order to achieve concrete managerial recommendations. Hence, the model allows evaluating SN‐partners based on selected parameters to determine the contribution of a single partner to the overall complexity.

Research limitations/implications

Due to the literature review executed and the case study approach chosen, the research may lack generalisability. Therefore, continued validation by means of implementing a greater amount of use cases in other companies and industries is advisable.

Practical implications

Applying the model, a company is able to determine tier‐1 to tier‐n suppliers which are predominantly affecting its business from a complexity perspective.

Originality/value

Unlike typical current complexity evaluation approaches, the proposed model respects rapid and continuous applicability, profound conceptualisation and practical feasibility.

Citation

Gerschberger, M., Engelhardt‐Nowitzki, C., Kummer, S. and Staberhofer, F. (2012), "A model to determine complexity in supply networks", Journal of Manufacturing Technology Management, Vol. 23 No. 8, pp. 1015-1037. https://doi.org/10.1108/17410381211276853