Signaling valuable human capital: Advocacy group work experience and its effect on employee pay in innovative firms

© 2018 John Wiley & Sons, Ltd. Research Summary: The ability of innovative firms to create and capture value depends on innovations that are quickly and widely adopted. Yet, stakeholder concerns can establish important barriers to diffusion. We study the human capital aspect of this challenge and investigate whether innovative firms pay salary premiums to new hires with work experience from advocacy groups like Transparency International. We integrate strategic human capital with stakeholder theory and suggest that advocacy group experience creates signals for valuable human capital in terms of stakeholder knowledge and legitimacy transfers to innovative firms. Using matched data for 3,562 employees in Denmark, we find that new hires with advocacy group experience enjoy larger salary premiums at technologically leading firms, in occupations with direct stakeholder interaction, and for advocacy group top management. Managerial Summary: Innovation research is increasingly aware of the non-technological factors behind successful innovations. Users, regulators, or public opinion can be benevolent supporters or stingy opponents of innovations. Employees with an understanding of the needs and sensitivities of societal stakeholders should therefore be valuable to innovative firms. We find this to be the case when innovative firms hire employees from advocacy groups representing such stakeholders (e.g., Transparency International). Such employees receive higher salaries than an otherwise comparable reference group. These findings indicate that recruiting needs of innovative firms reward stakeholder experience, not merely technological expertise. They demonstrate how firms can create value in the pursuit of the public interest. Further, advocacy groups emerge as an important career stage allowing individuals to develop credible signals for stakeholder expertise

ResearchFlow: Understanding the Knowledge Flow between Academia and Industry

Understanding, monitoring, and predicting the flow of knowledge between academia and industry is of critical importance for a variety of stakeholders, including governments, funding bodies, researchers, investors, and companies. To this purpose, we introduce ResearchFlow, an approach that integrates semantic technologies and machine learning to quantifying the diachronic behaviour of research topics across academia and industry. ResearchFlow exploits the novel Academia/Industry DynAmics (AIDA) Knowledge Graph in order to characterize each topic according to the frequency in time of the related i) publications from academia, ii) publications from industry, iii) patents from academia, and iv) patents from industry. This representation is then used to produce several analytics regarding the academia/industry knowledge flow and to forecast the impact of research topics on industry. We applied ResearchFlow to a dataset of 3.5M papers and 2M patents in Computer Science and highlighted several interesting patterns. We found that 89.8% of the topics first emerge in academic publications, which typically precede industrial publications by about 5.6 years and industrial patents by about 6.6 years. However this does not mean that academia always dictates the research agenda. In fact, our analysis also shows that industrial trends tend to influence academia more than academic trends affect industry. We evaluated ResearchFlow on the task of forecasting the impact of research topics on the industrial sector and found that its granular characterization of topics improves significantly the performance with respect to alternative solutions

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

How does working on university-industry collaborative projects affect science and engineering doctorates' careers? Evidence from a UK research-based university

This paper examines the impact of industrial involvement in doctoral projects on the particular nature of the training and careers of doctorates. We draw on an original survey of job histories of doctorates in physical sciences and engineering from a research-based university in the UK. Using multivariate probit analysis and linearised (robust) and resampling (jackknife) variance estimation techniques, we found that projects with industrial involvement are associated with higher degree of socialisation with industry. There is some evidence showing that these projects are also more likely to focus on solving firm-specific technical problems or developing firm-specific specifications/prototypes, rather than exploring high-risk concepts or generating knowledge in the subject areas. Crucially, these projects result in fewer journal publications. Not surprisingly, in line with existing literature, we found that engaging in projects with industrial involvement (in contrast to projects without industrial involvement) confers advantages on careers in the private sector. Nevertheless, there is also a hint that engaging in projects with industrial involvement may have a negative effect on careers in academia or public research organisations. While acknowledging that the modelling results are based on a small sample from a research-based university and that therefore the results need to be treated with caution, we address implications for doctorates, universities and policymakers

Embracing open innovation to acquire external ideas and technologies and to transfer internal ideas and technologies outside

The objective of this dissertation is to increase understanding of how organizations can embrace open innovation in order to acquire external ideas and technologies from outside the organization, and to transfer internal ideas and technologies to outside the organization. The objective encompasses six sub-objectives, each addressed in one or more substudies. Altogether, the dissertation consists of nine substudies and a compendium summarizing the substudies. An extensive literature review was conducted on open innovation and crowdsourcing literature (substudies 1–4). In the subsequent empirical substudies, both qualitative research methods (substudies 5–7) and quantitative research methods (substudies 8–9) were applied. The four literature review substudies provided insights on the body of knowledge on open innovation and crowdsourcing. These substudies unveiled most of the influential articles, authors, and journals of open innovation and crowdsourcing disciplines. Moreover, they identified research gaps in the current literature. The empirical substudies offer several insightful findings. Substudy 5 shows how non-core ideas and technologies of a large firm can become valuable, especially for small firms. Intermediary platforms can find solutions to many pressing problems of large organizations by engaging renowned scientists from all over world (substudy 6). Intermediary platforms can also bring breakthrough innovations with novel mechanisms (substudy 7). Large firms are not only able to garner ideas by engaging their customers through crowdsourcing but they can also build long-lasting relations with their customers (substudies 8 and 9). Embracing open innovation brings challenges for firms too. Firms need to change their organizational structures in order to be able to fully benefit from open innovation. When crowdsourcing is successful, it produces a very large number of new ideas. This has the consequence that firms need to allocate a significant amount of resources in order to identify the most promising ideas. In an idea contest, customarily, only one or a few best ideas are rewarded (substudy 7). Sometimes, no reward is provided for the selected idea (substudies 8 and 9). Most of the ideas that are received are not implemented in practice