Okanga, B. (2023). Explicating Enterprise Modelling As a Driver of the Small and Medium-Scale Manufacturing Enterprises’ Effective Performance. Economics & Management Information, 2(2), 1–18.

Explicating Enterprise Modelling As a Driver of the Small and Medium-Scale Manufacturing Enterprises’ Effective Performance

Enterprise modelling offers a comprehensive organisational configuration that aids holistic diagnosis to identify and correct areas of deficiencies. This often catalyses a manufacturing entity’s overall effective performance. In that context, this empirical research explores the iterative enterprise modelling’s edifying effects on the small and medium-size manufacturing entities’ (SMEs) effective performance. Using an exploratory case study research design, the empirical research evaluated the perceptions of twenty operational IT support personnel from twenty SMEs that are operating in Glasgow’s manufacturing sector on their level of enterprise modelling’s utilisation as a performance improvement initiative. Even if some of the narratives indicated some of the SMEs that are operating in Glasgow-Scotland to recognise the business values of enterprise modelling, findings still revealed most of the small and medium scale manufacturing entities to only use certain discrete generic operational diagnostic approaches. Such generic operational diagnostic approaches either entailed the use of less technologically-intensive diagnosis of whether a business’ performance is aiding the achievement of the desired outcomes or frequent manufacturing equipments’ diagnosis to minimise risks of major failures that often require complex technologically supported interventions. The study concludes with a framework that explicates the required critical iterative enterprise modelling processes that can be replicated by the small and medium scale manufacturing entities not only in Glasgow, but also across the world.

effective performance enterprise modelling small and medium scale manufacturing enterprises


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Supporting Agencies

  1. Funding: N/A