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on Intellectual Property Rights |
| By: | Astebro, Thomas B. (HEC Paris) |
| Abstract: | This report to the "Investigation on development of the innovation and entrepreneurship climate in Sweden" SOU 2016:72 regards governmental policies for university technology commercialization. It contains a literature review that spans several areas of research addressing the potential effect of changing the allocation of Intellectual Property rights between universities and their employees. There is also some original research; several secondary datasets are re‐analyzed and some primary interview and case data from a few universities are also added. |
| Keywords: | Technology Commercialization; Intellectual Property; Universities; Property Rights; Technology Transfer |
| JEL: | D72 D81 K31 O31 P14 |
| Date: | 2024–02–08 |
| URL: | https://d.repec.org/n?u=RePEc:ebg:heccah:1502 |
| By: | Ashish Arora; Sharon Belenzon; Elia Ferracuti; Jay Prakash Nagar |
| Abstract: | Estimating the private value of patents is important, yet challenging. By developing a method that uses stock market returns to produce a distribution of patent values (and not just an estimate of the mean of that distribution), Kogan, Papanikolaou, Seru, and Stoffman (2017) (KPSS) opened venues for new research. Researchers have used these estimates to compare average values of different types of patents. In this paper, we argue that KPSS values should not be used in their current form to compare mean values of different groups of patents, and show this to be the case in the context of research on the private returns to scientific patents. We extend the original KPSS method to allow for patents to be drawn from two distinct value distributions. Using this approach, we find that scientific patents have a higher mean value compared to non-scientific patents. |
| JEL: | O3 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33056 |
| By: | Ataman, Berk (Koç University); Pauwels, Koen (Northeastern University); Srinivasan, Shuba (Boston University); Vanhuele, Marc (HEC Paris) |
| Abstract: | Managers often count on advertising to create and reinforce brand differentiation, which should, in theory at least, translate into lower price sensitivity for their brands. But to what extent does it do so, what is the route through which this effect of advertising materializes, and what are the boundary conditions? The authors develop a Dynamic Linear Model that links advertising to brand price elasticity directly and indirectly through consideration and main brand preference mindset metrics. Model estimation on six and a half years of data, on average, for 350 brands in 39 categories of fast-moving consumer goods shows that advertising indeed decreases the magnitude of price elasticity. The effect is mainly direct (97.5%) and partly indirect (2.5%), through brand preference. The direct effect shows that advertising predominantly decreases price sensitivity among the consumers who already consider the brand and among the consumers who already prefer it. When converted into incremental revenue impact, monetary gains from this increased pricing power are especially pronounced for expensive brands in complex and frequently purchased categories. The findings thus help managers demonstrate the benefits of advertising in sustaining brand performance. |
| Keywords: | Advertising; price elasticity; mindset metrics; long-term effects; dynamic linear models; and empirical generalization. |
| JEL: | M30 M31 M37 |
| Date: | 2024–01–24 |
| URL: | https://d.repec.org/n?u=RePEc:ebg:heccah:1500 |