The set-up interviews on usethis.com really spark my curiosity to find out what hardware and software is used by others. For me it is a continuous inspiration and a valuable source of information to see what others use and read about their workflow. So I decided to briefly share my set-up and my workflow here. For quantitative analysis [...]
A couple of weeks ago here at MCI we had an long discussion with the editor-in-chief of eco.nova a regional business magazine. We talked a lot about innovation and failure, about failure as an opportunity to learn, and about failure that is so deeply related to innovation that innovation cannot be thought about without thinking about failure. Some [...]
Today I have the pleasure to present some of our (Galia, Laursen, Salter and my) recent research. Here is briefly what it is about: Introduction. As stated by Hubbard, Vetter and Little (1998: 251): “The goal of science is empirical generalization, or knowledge development leading to some degree of understanding.” However, in many fields of science, the integrity of the pertinent empirical literatures are open to question because of what Rosenthal (1979) dubbed the “file drawer problem,” which implies that journals may be dominated by papers reporting results that are Type I errors (erroneous rejections of the null hypothesis), while the null outcome remain in the file drawers of researchers. In the top five journals of strategic management research, Goldfarb and King (2016) report that between 24 to 40 percent of the findings are likely the result of chance rather than a reflection of true relationships. Replication studies can help reduce this problem by establishing a set of robust empirical results (Bettis, 2012). In addition, even if we assume away the “file drawer problem”, statistical tests by nature produce Type I errors. The result is that in strategic management general and in open innovation research in particular, we know too little about which results are empirically generalizable, and hence whether they potentially add to our understanding. In many cases, however, researchers work on similar data sets and use similar or identical dependent variables, so that in principle, the robust (and not so robust) results could be extracted, while controlling for a host of other factors. When such general datasets are available, large scale replication studies can be conducted. By large-scale replication studies, we mean studies where different independent variables are included in a single empirical model with the same dependent variable. However, in these large scale replications as in most empirical applications, the “true model”, and therefore, the appropriate selection of explanatory variables, is essentially unknown, which leads to a phenomenon described as “model uncertainty” (Chatfield, 1995). Disregarding model uncertainty results in too small standard errors and too strong confidence in the statistical findings (Raftery, 1995). Additionally, it is model uncertainty that fundamentally facilitates the “file drawer problem”. […]
Last week we had a great session at a conference in Vienna. It was about failure. Interestingly the Austrian daily Der Standard extensively covered the session well. Find the online version of the article here. The open discussion of failure seems to be something that attracts media attention, particularly when you can show that failure presents [...]
The adoption of technology in higher education and teaching is constantly shifting the traditional modes of education. Technology helps to deliver content more swiftly, it facilitates distant learners to interact and to collaborate, it allows for faster processes in and around the classroom. Although we have already witnessed that technology enabled simulations have the potential to [...]
Over the last year I had the pleasure to co-supervise the PhD dissertation of Sören Simon Petersen. Sören collected four of his marvelous papers into his cumulative dissertation, where he analyzes the antecedents and the consequences of patenting and standardization activities in firms. He excellently defended his dissertation. Congratulations!
Last week Daniela Mathis a journalist from the daily DIE PRESSE asked a couple of interesting questions about the structure and the role of universities in the year 2048. My responses are in this post. Some of my ideas went into a kind of summary article today. Here.
Wer wird an ihnen lehren, welche Voraussetzungen und Kenntnisse werden nötig sein? Die Studierenden an Hochschulen im Jahr 2048 werden die Kinder der ersten Generation der Digital-Natives sein. Sie werden alle nötigen Informationen sofort und zielgerichtet abrufen können. Für die Lehrenden an Hochschulen im Jahr 2048 bedeutet das, dass Moderation, Motivation und Vernetzten die Information und [...]
At the EU-SPRI conference in Helsinki today we present a paper that we (Annalena Wiesend and me) have jointly drafted. The investigates how crowdfunding adresses failures in the innovaiton system. Crowdsourcing, that is the crowd as the origin of inspiration for innovation and as the source of novel solutions for given problems, has attracted some scholarly [...]
Our - i.e. Florian Becke's, Andreas Altmann's and my - paper "Embedding of a University Into the National System of Entrepreneurship" was presented at the QS-MAPLE conference last week in Doha. The paper highlights that the national system of entrepreneurship (Ács, Autio, and Szerb 2014) can be considered a sub-system of the national system of innovation [...]