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Dr Samuel Mwaura Hunter Centre for Entrepreneurship Samuel.mwaura@strath.ac.uk

Innovation, ennovation and firm-level productivity growth: a new Schumpeterian elaboration applicable in a development context . Dr Samuel Mwaura Hunter Centre for Entrepreneurship Samuel.mwaura@strath.ac.uk. Overview. Research problems/ paradoxes Gaps in innovation research

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Dr Samuel Mwaura Hunter Centre for Entrepreneurship Samuel.mwaura@strath.ac.uk

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  1. Innovation, ennovation and firm-level productivity growth: a new Schumpeterian elaboration applicable in a development context Dr Samuel Mwaura Hunter Centre for Entrepreneurship Samuel.mwaura@strath.ac.uk

  2. Overview • Research problems/ paradoxes • Gaps in innovation research • Dimensions of knowledge capital • Innovation vs. Ennovation • Link to productivity growth

  3. Research problem • Interest in the contribution of firms to economic development; especially the link between entrepreneurship and economic development, firm performance in LDCs • Early GEM studies ‘surprisingly’ found a U-Shaped relationship with very high levels of entrepreneurship in poor countries – no convincing explanation/ theory yet • Innovation conventionally recognised as the key driver of growth both the macro-level and at the firm and industry levels • Intuitive, but no convincing theory or empirical evidence, despite large surveys, e.g. Community Innovation Survey • The situation in developing countries inadequately understood. Little R&D, high imitation/adaption, but lots of ingenuity and new products in LDC contexts, especially by SMEs, yet low growth • What is the relationship between innovation and productivity growth?

  4. Innovation Research: Schumpeter • Schumpeter: invention different from innovation • Invention is basic scientific discovery. • Innovation entails: new products, new methods of production, new sources of supply, the exploitation of new markets, new ways to organise business (e.g. Taylorization). • New combinations of factors of production in kind, i.e. qualitative changes in the production function, must produce changes in the output. Hence, development and not mere growth.

  5. Innovation Research: Schumpeter • However… Innovation is ‘any doing things differently in the realm of economic life’; quite general and vague • Schumpeter Mark II – focus on R&D in large firms. • A clear shift from his Mark I emphasis on “carrying out” new combinations by entrepreneurs, to the “trying out” by large firms. • Based on observations rather than theory. Mark I in early 20th Century Europe (1911), Mark II in large corporations in America. • Ruttan (1959) - Schumpeter did not advance innovation theory at all.

  6. Innovation Research: Knowledge capital • Innovation research prioritised ‘technological innovation proper’ (Archibugi, 1988) • So, R&D investments = knowledge capital • Assumed R&D always leads to new products • Fitted well within “capital accumulation” and the production function (productivity and growth accounting framework) • However… Thomas Edison is said to have tested 1,600 different filament materials before finding his carbon filament solution (Scherer, 1986).

  7. Innovation Research: Knowledge capital • Is all this useful knowledge capital that contributes to actual production/ productivity? • ‘Swedish paradox’, high investments in R&D little growth (Audretsch and Keilbach, 2008; Ejermo and Kander, 2006) • Thus, R&D can be said to produce: • Purposed knowledge – the solution sought • Serendipitous knowledge – incidental discoveries • Mere chaff

  8. Innovation Research: Knowledge capital • Besides R&D not producing useful knowledge, useful knowledge may not implemented • “Real options” to exploit in the future (Bloom and Van Reenen, 2002) • Hoarded knowledge not likely to be used • Nokia - 4,000 market ready intellectual properties but unused (Hossain, 2012) • Other problems with R&D and patents: • Non-use of the patents system (Carlsson and Fridh, 2002; Raustiala and Sprigman, 2006) • Duplication of efforts across firms (Dasgupta and Stiglitz, 1980; Loury, 1979; Temin, 1979). • “waiting games” (Dasgupta, 1988) and “inventing around” existing patents (Mansfield et al. 1981)

  9. Innovation Research: knowledge capital • For small firms in particular… • Knowledge spill-over theory – new firms (spin-offs) exploiting knowledge developed by large R&D intensive firms (Acs et al., 2009) • For example, the semi-conductor and Bell Labs; Nokia-Finland Innovation Mill (Hossain, 2012) • Knowledge comes from different sources (Roper et al., 2008) • Open innovation (Chesbrough, 2003; Dahlander and Gann 2003)

  10. Innovation Research • Back to the big question: What is innovation and how does it contribute to economic performance? • Oslo Manual 1997 – technological innovation proper – R&D, high-tech industries • Crepon, Duguet, and Mairesse (CDM), 1998: Knowledge capital exploited in production is observable as shares of new products in firm sales. • Therefore, knowledge production before production proper (CDM, 1998) • R&D = innovation inputs • New products sales = Knowledge capital= innovation outputs

  11. Innovation Research • Oslo Manual 2005 – innovation happens everywhere – large firms, small firms, services, high-tech, low-tech, even governments • New focus: Innovation is about implementation – not just pursuit of novelty through R&D • However, innovation = implemented innovation • What is innovation again? • Back to CDM (1998) • Innovation inputs (R&D) → innovation outputs (knowledge capital, i.e. new products sales share) → productivity growth (through knowledge capital accumulation)

  12. Innovation Research • However, very little of knowledge capital, proxied by new products sales shares, is accounted for by R&D (Mairesse and Mohnen, 2002) • Various sources of knowledge, e.g networks, not just R&D (Roper et al., 2008; Love and Roper, 1999), open innovation (Chesbrough, 2003; Dahlander and Gann 2003) • Therefore R&D + other sources = total knowledge capital • Implement this knowledge capital, you get innovation outputs (New products sales share).

  13. Innovation Research • However, high sales share a poor proxy for knowledge capital as one piece of knowledge, one new product, can account for even 100% of sales • What then is knowledge capital and innovation outputs? • R&D = Innovation inputs • Knowledge from R&D = Innovation outputs • Conversion success (Extent of new products sold) = Innovation outputs’ outputs • Contribution to productivity = Innovation outputs’ outputs’ outputs • Serious equivocation issues

  14. Innovation Research: knowledge capital • Besides, again, very little of new products sales shares is accounted for by R&D (Mairesse and Mohnen, 2002) • In fact, for the vast majority of small firms, the introduction of new products is something that ‘just happens’ (Vermeulen et al., 2005) • In developing countries, (small) firms churn out new products all the time with little R&D, whether imitations or basic ingenuity/ creativity.

  15. Innovation Research: knowledge capital • In LDCs, unable to employ the conventional constructs of innovation such as R&D investments and “new to the market/ new to the world” originations, anything new at the firm level is considered as innovation (Mytelka, 2000; van Dijk and Sandee, 2002). • Methodologically, without R&D inputs, the structural CDM model cannot work in developing countries; new products do not derive from R&D. • Besides, since high new products sales shares may be from high sales of one new item, that may even be an imitation, sales shares a poor proxy of knowledge capital • Innovation research hamstrung by a “certain degree of ‘fuzziness’ with respect to basic concepts” (Fagerberg, 2004)

  16. Rethinking knowledge: Three dimensions • Knowledge assemblage: the magnitude and substance of what is known. • A collection of “modules of knowledge”. • Each module of knowledge is produced, i.e. discovered, only once (fixed costs, but no marginal costs except for transmission). • Different modules have different levels of substance, e.g. General Purpose Technology has a higher substance than a solution to a minor bug • Knowledge lore-range: how many people are proficiently knowledgeable about a given module • Knowledge mileage: the extent to which a given module of knowledge is employed in actual production

  17. Rethinking knowledge: Three dimensions

  18. Rethinking knowledge: Three dimensions • Since capital stock refers to capital employed in production, with intangible knowledge, it is the increasing the mileage of a particular module of knowledge, and not increasing the assemblage of knowledge, that is equivalent to increasing physical capital stock • Merely increasing the assemblage, through R&D, e.g. Nokia’s hoard, or increasing the lore-range through education, without employing the knowledge in production yields no output • Stocks of knowledge capital vs stacks of knowledge capital

  19. Rethinking knowledge: Three dimensions • Developing countries - different scenarios: • High mileage, and therefore low marginal product, from old technologies • Low lore-range, and therefore low mileage, in new high substance knowledge (ICT, etc) • Low contributions to new knowledge, and therefore, no first-mover advantage/ technological leadership. Hence, low marginal product by the time they join the technological bandwagon • Low mileage in new low substance modules of knowledge (i.e. monopolistic competition). Highly prodigal introduction of new(ish) products, especially by SMEs

  20. Innovation, ennovation and the pedigree of productivity growth • Knowledge is not innovation, since, as above knowledge can be treated as a factor of production (capital) • Back to the original Schumpeterian insight • Economic development (productivity growth) comes from “carrying out new combinations of factors of production” • From “novate” – simply make new • Thus, the essence is that change happens in/ to the firm’s production function. It is this that effects a change in the output, hence growth

  21. Innovation, ennovation and the pedigree of productivity growth • Early research assumed change is only from R&D, so innovation = R&D • When this was not confirmed, investigate the indirect impact of R&D on productivity, therefore innovation inputs → outputs →outputs’ outputs • But we see, lots of changes ‘new combinations of factors of production’ with no R&D or any observable ‘knowledge’ inputs at all – the case with many small firmsin developing countries • We explain very little productivity growth • Alternative approach, try to explain ultimate output change itself proceeding backwards

  22. Innovation, ennovation and the pedigree of productivity growth • Productivity/ production growth is wholly attributable to the aggregate of yet unidentified changes in the inputs side. Growth is the manifestation of these actual changes • Simulating Schumpeter, define, ennovation: the occurrenceof new combinations of factors of production • Simply captures the occurrence of change. Unlike innovation, no claim/ requirement that the firm/ entity in questions is the first to carry out this change. • Shares of sales of new products  the extent to which the firm has shifted production towards new products

  23. Innovation, ennovation and the pedigree of productivity growth

  24. The relationship between ennovation and productivity growth

  25. Implications • Separation of the various concepts and constructs • No need to consider sub-samples of innovators in research – selection bias issues • Inferencing extant studies, e.g. why R&D explains very little of new products sales shares. • Contributes to the growth accounting framework • Unriddles the “Swedish paradox” – high marginal assemblage of knowledge (through R&D), low mileage. Cf. Nokia • Operationalisationproblems remain, especially the mileage of knowledge

  26. Thank you.

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