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Innovation and Commercialization in the Canadian Bioproduct Industry. Pamela Laughland John Cranfield David Sparling University of Guelph. Motivation. Industrial biotech an growing area of interest Shift waste into something of value
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Innovation and Commercialization in the Canadian Bioproduct Industry Pamela Laughland John Cranfield David Sparling University of Guelph
Motivation • Industrial biotech an growing area of interest • Shift waste into something of value • CND’s resource based gives it a competitive advantage vis-à-vis biomass • Product development process is complex • Gap regarding commercialization and innovation activities and related drivers • Information gap to help policy makers understand better firm’s activities, industry structure and characteristics
A changing industry? Source: Statistics Canada, Bioproducts Development Survey, 2003 & 2006
Primary focus of enterprises Source: Statistics Canada, Bioproducts Development Survey, 2003 & 2006
Regional location of enterprises Source: Statistics Canada, Bioproducts Development Survey, 2003 & 2006
Raising capital Source: Statistics Canada, Bioproducts Development Survey, 2003 & 2006
Raising capital, cont Source: Statistics Canada, Bioproducts Development Survey, 2003 & 2006
Conceptual framework • Portfolio of products/projects – add or trim? • Uncertain of benefits • Maximize CE of portfolio of products under development or on the market • Choose level of hard and soft capital allocated to the respective product/project • Subject to a resource constraint on (hard and soft) capital • Non-negativity constraint on hard & soft capital
Conceptual framework, cont • FOC equates net marginal benefits • Corner versus interior solution • Optimal level of hard & soft capital expressed as a share of overall capital
Conceptual framework, cont • Resource based theory of the firm: sustained competitive advantage arises from heterogeneous resources and inimitatability
Methods & Data • Share of (hard and soft) capital allocated to each product is a latent variable • Map to a count of the number of products • Negative bionomial count data model of number of products under development or on the market • Variables capturing internal and external resources to the firm (and how these might be deployed strategically), market environment
Methods & Data, cont • 2003 & 2006 Bioproducts Development Survey • Internal: IP; firm size; age; BP R&D spending per employee; early/late focus; BP share of revenue; benefits, barriers and strategies for development; private firm • External: access capital; SR&ED; collaborations • Market: sub-sector of predominant focus; region
Benefits, barriers & strategies • Likert scale response items • 1=low importance, 5=high importance • Analyzed using PCA (with varimax rotation)
Benefits, barriers & strategies, cont 1=low importance, 5=high importance
Take home points • From 2003 to 2006, more smaller firms with slightly higher count of products • Impact of importance of benefits changed: product/sales versus cost/environmental • IP, collaborations & BP R&D expenditure positively associated with count of products • Large effects associated with sub-sector & some regional variables
Future work • Need to be able to link databases to create panels • Link firms to measure performance in more desirable way • Understand industry dynamics better • Distribution of BP importance • Network effects • Non/semi-parametric analysis
Any questions? THANK YOU