The use of knowledge assets: modelling the potential effect of adding innovators to low-innovation and high-innovation SMEs. (16th March 2015)

• Record Type: Journal Article
• Authors: Mellor, Robert B.
• Is Part Of: International journal of knowledge-based development. Volume 5:Number 4(2014)
• Page Start: 367
• Page End: 380
• Publication Date: 2015-03-16
• Subjects: growth and financial returns -- innovation -- management -- modelling -- organisation -- SME; Knowledge management -- Periodicals; City planning -- Periodicals; Information technology -- Social aspects -- Periodicals; 307.116
• Languages: English
• ISSNs: 2040-4468

Abstract

SMEs rarely possess formal intellectual property (IP) in the sense of patents, etc. Broadly speaking, SMEs reap relatively short-term Schumpeterian profits by means of incremental innovation, where managing internal knowledge networks for 'mutual inspiration' can give rise to significant competitive advantages. Unfortunately estimates as to the best timing, how much benefit could be reaped and considerations of the organisations knowledge framework for future development are, at best, vague. To address this issue, a 3D quantitative fold is presented that pertains to a novel knowledge-based theory of the growth of SMEs via their knowledge assets and that contributes to a model that case studies can test. The fold allows quantitative estimations of the potential value of knowledge using Monte Carlo modelling (i.e., shooting virtual balls down the fold and analysing their final scatter distribution). Results indicate that adding middle-management innovators to low-innovation SMEs can contribute markedly to potential financial performance but adding innovators to high-innovation SMEs does not provoke an absolute increase in returns, but performance levels are reached earlier. In all cases potential financial performance was dramatically improved by laying down an innovative stratum early in SME development rather than on top of an already-established less-innovative middle management layer.