Knowledge management determinants of breakthrough research productivity

Abstract

Recent technological advancements have brought about a wave of drastic change in the global supply and demand of knowledge and subsequently, in the generation of innovation. However, it has been argued that some industries and academic fields do not sufficiently take advantage of new opportunities afforded by the widespread, free and open availability of knowledge. Terms such as the Death of Innovation, Innovation Failure and Academic Failure have been used to describe the market failure of industrial Research and Development (R&D) and certain forms of academic research to sufficiently leverage these new opportunities, particularly with regard to societal problem-solving. An extensive and rapidly growing body of literature pertaining to new modes of knowledge productivity, such as open innovation, crowdsourcing and crowdfunding, through the use of the Internet, has demonstrated evidence that certain new technologies and methodologies may indeed offer significant economies of scope and scale in innovative problem solving. However, misaligned incentives may in some cases prevent the efficient leveraging of these new modes of productivity. These effects may be particularly pronounced in the academic context, which has long been criticised for its strict adherence to tradition and paradigmatic convergence. Despite this body of literature, there is a lack of knowledge as to the extent that academic researchers do indeed take advantage of these new modes of productivity, and furthermore, the extent to which their adoption influences research productivity. Thus, this research seeks to investigate the relationship between a behavioral orientation called ‘technological propensity’, or the extent to which individuals seize opportunities that offer significant economies of scale (such as crowdsourcing) and productivity. This research is undertaken at the individual level of analysis, which necessitates corresponding measurements of proximal, human-resources management determinants which may impact this relationship. These include personality, motivational values, work climate perceptions and human capital investments. Three studies are conducted to ascertain the extent of the relationships between these variables, and to provide a holistic perspective of the relationships between variables. First, a qualitative study, which samples award-winning scientists, academics researchers and innovators from across the world was conducted to develop theory. Amongst these are 3 Nobel Prize winners, 3 Lasker Award winners and 1 Fields Medal winner, among others. Second, a quantitative study, which sampled South African academic researchers, was conducted to test theory. Third and finally, a second quantitative study, which sampled ‘crowd-workers’, or users of an Internet-based crowdsourcing platform known as Amazon’s Mechanical Turk, was conducted to provide ii further insights into the relationships under study, in the open knowledge space (i.e. over the Internet). Qualitative data is analysed inductively, using thematic content analysis. Quantitative data is analysed through a series of statistical analyses, including multiple regression, mediation and moderation analyses. The findings of these studies suggest that the relationship between technological propensity and productivity is context-dependent and may only be suitable as a complementary methodology to certain forms of academic research, which is especially constrained by outside influences. Certain new modes of productivity may indeed enhance the rate at which ‘breakthrough’, or radically innovative research outputs are generated. The findings also suggest that differences in certain values-configurations and human capital investments may significantly impact this relationship. Based on the research findings, recommendations are made to improve research productivity in these contexts and recommendations for practice and for further research are made.