Knowledge that Transforms
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But what will it cost me? How do private costs of participation affect open source software projects?
Understanding productivity dynamics: A task taxonomy approach
A theory of grand innovation prizes
The past decade has witnessed a resurgence in innovation awards, in particular of grand innovation prizes (GIPs) which are rewards to innovators developing technologies reaching performance goals and requiring breakthrough solutions. GIPs typically do not preclude the winner also obtaining patent rights. This is in stark contrast with mainstream economics of innovation theories where prizes and patents are substitute ways to generate revenue and encourage innovation. Building on the management of innovation literature which stresses the difficulty to specify ex-ante all the technical features of the winning technologies, we develop a model in which innovative effort is multi-dimensional and only a subset of innovation tasks can be measured and contracted upon. We show that in this environment patent rights and cash rewards are complements, and that GIPs are often preferable to patent races or prizes requiring technologies to be placed in the public domain. Moreover, our model uncovers a tendency for patent races to encourage speed of discovery over quality of innovation, which can be corrected by GIPs. We explore robustness to endogenous entry, costly public funds, and incomplete information by GIP organizers on the surplus created by the technology.
Commercialization Strategy and IPO Underpricing
This paper studies the interplay between two defining features of technology-based firms: licensing as a commercialization strategy and the reliance on equity financing. Within the context of an IPO, we argue that the technology commercialization strategy of a firm going public affects information asymmetries and, therefore, IPO underpricing. In particular, we theorize that underpricing will be higher when a firm’s technology commercialization strategy is more based on licenses. We also posit that the size of the patent portfolio will mitigate this effect. Our results from a sample of 130 IPOs in the U.S. semiconductor industry confirm these predictions.
Drivers of knowledge accumulation in electronic waste management: An analysis of publication data
Innovation in UK higher education: A panel data analysis of undergraduate degree programmes
In the UK, higher education is increasingly a marketised service sharing many characteristics with other professional services such as legal, medical or financial services. With marketisation comes competition, and the need for Higher Education Institutions (HEIs) to develop and maintain strong programmes to attract and retain high-class faculty and fee-paying students. Here, we consider the drivers of programme innovation − i.e. the introduction of new programmes and the withdrawal of existing programmes − in UK universities. Our focus is on undergraduate programmes as these account for three-quarters of all student enrolments. Using panel data for UK universities we identify significant resource, internationalisation and business engagement effects. Financial stringency and more extensive international market engagement both encourage programme introduction. Collaboration with businesses has offsetting effects depending on the nature of the interaction. The results have both strategic and systemic implications.
Which industries are served by online marketplaces for technology?
A multi-sector growth model with technology diffusion and networks
Ideas production and international knowledge spillovers: Digging deeper into emerging countries
Research and Development (RD however, we find pockets (specific countries and certain groups) generating positive spillovers. A carefully choreographed policy focusing on such pockets might be fruitful. We hope that this study (i) complements the micro literature, (ii) furthers the existing macro literature and (iii) provides some new policy insights. Our results are robust to a range of robustness checks, including the estimators – a cointegration approach versus a simple fixed effects OLS estimator.