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.
Original language | English |
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Pages (from-to) | 1015-1037 |
Number of pages | 23 |
Journal | Journal of Manufacturing Technology Management |
Volume | 23 |
Issue number | 8 |
DOIs | |
Publication status | Published - Jun 2012 |
Keywords
- Agriculture
- Austria
- Channel relationships
- Complexity
- Supplier evaluation
- Suppliers
- Supply chain management
- Supply networks