The Double-Edged Sword of Industry Collaboration: Evidence from Engineering Academics in the UK

This paper studies the impact of university-industry collaboration on academic research output. We report findings from a unique longitudinal dataset on all the researchers in all the engineering departments of 40 major universities in the UK for the last 20 years. We introduce a new measure of industry collaboration based on the fraction of research grants that include industry partners. Our results show that productivity increases with the intensity of industry collaboration, but only up to a certain point. Above a certain threshold, research productivity declines. Our results are robust to several econometric estimation methods, measures of research output, and for various subsamples of academics

The Impact of Industry Collaboration on Academic Research Output: A Dynamic Panel Data Analysis

The aim of this paper is to analyse the impact of university knowledge and technology transfer activities on academic research output. Specifically, we study whether researchers with collaborative links with the private sector publish less than their peers without such links, once controlling for other sources of heterogeneity. We report findings from a longitudinal dataset on researchers from two engineering departments in the UK between 1985 until 2006. Our results indicate that researchers with industrial links publish significantly more than their peers. Academic productivity, though, is higher for low levels of industry involvement as compared to high levels

Research Output From University-Industry Collaborative Projects

We study collaborative and noncollaborative projects that are supported by government grants. First, we propose a theoretical framework to analyze optimal decisions in these projects. Second, we test our hypotheses with a unique data set containing academic publications and research funds for all academics at the major university engineering departments in the United Kingdom. We find that the type of the project (measured by its level of appliedness) increases the type of both the university and firm partners. Also, the quality of the project (number and impact of the publications) increases with the quality of the researcher and firm, and with the affinity in the partners' preferences. The collaboration with firms increases the quality of the project only when the firms' characteristics make them valuable partners

On the joint production of research and training

Universities and research institutions have the responsibility to produce science and to provide training to new generations of researchers. In this paper, we propose a model to analyze the determinants of a senior scientist’s decisions about allocating time between these tasks. The results of this decision depend upon the characteristics of the research project, the senior scientist’s concern for training and the expected innate ability of the junior scientist involved. We analyze the role that a regulator can play in defining both the value of scientific projects and the future population of independent scientists.info:eu-repo/semantics/publishedVersio

Collusion through Joint R&D: An Empirical Assessment

This paper tests whether upstream R&D cooperation leads to downstream collusion. We consider an oligopolistic setting where firms enter in research joint ventures (RJVs) to lower production costs or coordinate on collusion in the product market. We show that a sufficient condition for identifying collusive behavior is a decline in the market share of RJV-participating firms, which is also necessary and sufficient for a decrease in consumer welfare. Using information from the US National Cooperation Research Act, we estimate a market share equation correcting for the endogeneity of RJV participation and R&D expenditures. We find robust evidence that large networks between direct competitors – created through firms being members in several RJVs at the same time – are conducive to collusive outcomes in the product market which reduce consumer welfare. By contrast, RJVs among non-competitors are efficiency enhancing

MINPP1 prevents intracellular accumulation of the chelator inositol hexakisphosphate and is mutated in Pontocerebellar Hypoplasia

Inositol polyphosphates are vital metabolic and secondary messengers, involved in diverse cellular functions. Therefore, tight regulation of inositol polyphosphate metabolism is essential for proper cell physiology. Here, we describe an early-onset neurodegenerative syndrome caused by loss-of-function mutations in the multiple inositol-polyphosphate phosphatase 1 gene (MINPP1). Patients are found to have a distinct type of Pontocerebellar Hypoplasia with typical basal ganglia involvement on neuroimaging. We find that patient-derived and genome edited MINPP1−/− induced stem cells exhibit an inefficient neuronal differentiation combined with an increased cell death. MINPP1 deficiency results in an intracellular imbalance of the inositol polyphosphate metabolism. This metabolic defect is characterized by an accumulation of highly phosphorylated inositols, mostly inositol hexakisphosphate (IP6), detected in HEK293 cells, fibroblasts, iPSCs and differentiating neurons lacking MINPP1. In mutant cells, higher IP6 level is expected to be associated with an increased chelation of intracellular cations, such as iron or calcium, resulting in decreased levels of available ions. These data suggest the involvement of IP6-mediated chelation on Pontocerebellar Hypoplasia disease pathology and thereby highlight the critical role of MINPP1 in the regulation of human brain development and homeostasis

Fishing for complementarities : competitive research funding and research productivity

This paper empirically investigates complementarities between different sources of research funding with regard to academic publishing. We find for a sample of UK engineering academics that competitive funding is associated with an increase in ex-post publications but that industry funding decreases the marginal utility of public funding by lowering the publication and citation rate increases associated with public grants. However, when holding all other explanatory variables at their mean, the negative effect of the interaction does not translate into an effective decrease in publication and citation numbers. The paper also shows that the positive effect of public funding is driven by UK research council and charity grants and that EU funding has no significant effect on publication outcomes

Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study

BACKGROUND: Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules' performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. METHODS: Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. RESULTS: A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2-4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. CONCLUSION: Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved