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Performance Assessment of R&D-Intensive Manufacturing Companies on Dynamic Capabilities

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  • Mohammadyasser Darvizeh

    (University of Manchester, UK)

  • Jian-Bo Yang

    (University of Manchester, UK)

  • Stephen Eldridge

    (University of Lancaster, UK)

Abstract

In today's business landscape, improving competitive advantage of manufacturing companies depends on their continuous performance improvement. This necessitates a generic and multi-dimensional view that organisational and managerial processes should be assessed by the underlying micro-foundation of dynamic capabilities (DC) in conjunction with enhanced new product development (NPD) projects. This study aims to propose an operationalised model of the conceptual DC framework including sensing, seizing, and reconfiguration capacities. The advantage of the two aforementioned models, which are based on a multi-criteria decision analysis (MCDA) framework, is that they can assist managers in the automotive industry to identify improvement plans and goals for sound and robust decision making. For this purpose, the evidential reasoning (ER) approach, which is realised in the intelligent decision system (IDS) software tool, is employed to perform performance self-assessment for the selected manufacturing companies on DC. This study provides managers with a useful tool to assess their company's strengths and weaknesses in regard to the DC components.

Suggested Citation

  • Mohammadyasser Darvizeh & Jian-Bo Yang & Stephen Eldridge, 2020. "Performance Assessment of R&D-Intensive Manufacturing Companies on Dynamic Capabilities," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 11(4), pages 1-23, October.
    • Handle: RePEc:igg:jsds00:v:11:y:2020:i:4:p:1-23
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