Essays zu Umwelteinflüssen und Wachstum akademischer Spin-Offs

This dissertation explores different perspectives on the growth trajectory of companies spun off from publicly funded research. It is composed of four papers, of which the first one provides an overview of the environment for spin-offs in Canada, and the three remaining papers present quantitative studies. Environmental factors are considered in the quantitative studies in two ways: Through explicit operationalization and through a two-country design of the empirical research – using the examples of Germany and Canada. The three empirical papers document how both of these environmental influences are significant. Where analysed, significant differences are found between Germany and Canada, in particular in the higher-order interaction terms, indicate that different combinations of factors lead to company sales growth in the two national contexts observed

Inclusive Innovation in Developed Countries: The Who, What, Why, and How

Although widely appreciated as an important driver of economic growth, innovation has also been established as a contributor to increasing economic and social inequalities. Such negative consequences are particularly obvious in the context of developing countries and extreme poverty, where innovation’s contributions to inequalities are considered an issue of social and economic exclusion. In response, the concept of inclusive innovation has been developed to provide frameworks and action guidelines to measure and reduce the inequality-increasing effects of innovation. In developing countries, attention has only recently turned to the role of innovation in increasing inequalities, for example in the context of the degradation of employment in the transition from production to service industries. Although the focus of this early work is primarily on economic growth, innovation in developed countries also contributes to social exclusion, both of groups traditionally subject to social exclusion and new groups marginalized through arising innovations. This article summarizes the origins of the concept of inclusive innovation and proposes a four-dimensional framework for inclusive innovation in developed countries. Specifically, innovation needs to be inclusive in terms of people, activities, outcomes, and governance: i) individuals and groups participating in the innovation process at all levels; ii) the types of innovation activities considered; iii) the consideration of all positive and negative outcomes of innovation (including economic, social, and environmental); and iv) the governance of innovation systems. This framework is intended to guide policy development for inclusive innovation, as well as to encourage academics to investigate all dimensions of inclusive innovation in developed countries

Classifying Organizations for Food System Ontologies using Natural Language Processing

Our research explores the use of natural language processing (NLP) methods to automatically classify entities for the purpose of knowledge graph population and integration with food system ontologies. We have created NLP models that can automatically classify organizations with respect to categories associated with environmental issues as well as Standard Industrial Classification (SIC) codes, which are used by the U.S. government to characterize business activities. As input, the NLP models are provided with text snippets retrieved by the Google search engine for each organization, which serves as a textual description of the organization that is used for learning. Our experimental results show that NLP models can achieve reasonably good performance for these two classification tasks, and they rely on a general framework that could be applied to many other classification problems as well. We believe that NLP models represent a promising approach for automatically harvesting information to populate knowledge graphs and aligning the information with existing ontologies through shared categories and concepts.Comment: Presented at IFOW 2023 Integrated Food Ontology Workshop at the Formal Ontology in Information Systems Conference (FOIS) 2023 in Sherbrooke, Quebec, Canada July 17-20th, 202

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements