Publication records

This is a revised version of the INSEAD paper, which was then published in Management Science. A pdf file of this working paper is available at SSRN.

This paper analyzes attempts to build user ideation communities aimed at inviting users to submit ideas and suggestions for future organizational actions. While earlier work has elaborated on the advantages of communities once they are created, our findings show that the ‘average’ organization struggles to build a vibrant community: most simply wither or die. We develop an argument about the importance of committing resources in the forms of (1) employees who submit suggestions to the community and (2) accepting suggestions from people in the community, and particularly suggestions from newcomers. Our findings suggest that creating communities often requires significant attention from the organizations seeking to develop them. However, our results are contingent upon the stage of the community, where we see different effects depending on whether the community has a history of accumulating suggestions or not. Our work has implications for scholars of open innovation by highlighting the importance of considering the innumerable failures, showing how focusing on communities that have reached a certain size can lead to misleading conclusions and specifying some conditions that explain why some are more successful than others.

With permission of the Academy of Management

We develop a model that relates self-control and conflict identification to cooperation patterns in social dilemmas. As predicted, we find in a laboratory public goods experiment a robust association between stronger self-control and higher levels of cooperation. This means that there is evidence for an impulse to be selfish and that cooperative behavior requires self-control effort. Free-riders differ from other contributor types only in their tendency not to have identified a self-control conflict in the first place.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Post-grant validity challenges at patent offices rely on the private initiative of third parties to correct mistakes made by patent offices. We hypothesize that incentives to bring post-grant validity challenges are reduced when many firms benefit from revocation of a patent and when firms are caught up in patent thickets. Using data on opposition against patents at the European Patent Office we show that opposition decreases in fields in which many others profit from patent revocations. Moreover, in fields with a large number of mutually blocking patents the incidence of opposition is sharply reduced, particularly among large firms and firms that are caught up directly in patent thickets. These findings indicate that post-grant patent review may not constitute an effective correction device for erroneous patent grants in technologies affected by either patent thickets or highly dispersed patent ownership.

We explore mortality beliefs by eliciting individual-level belief distributions for participants’ remaining lifespan. Across two independent samples, from Germany and the USA, we find that individuals – while accurately forecasting their life expectancy – substantially overestimate the likelihood of dying young (50 years) and overestimate the likelihood of reaching very old age (>100 years). In other words, the modes of the belief distributions are relatively accurate, but the tails of the belief distributions are significantly ‘fatter’ than the corresponding tails of distributions obtained from demographic data. Our results are robust to variations in belief elicitation techniques, and to assumptions underlying normative longevity forecasts. The results have implications for a range of questions of economic behavior – including intertemporal choice, consumption smoothing, saving, and risk management.

 

View all ESMT Working Papers in the ESMT Working Paper Series here. ESMT Working Papers are also available via SSRN, RePEc, EconStor, and the German National Library (DNB).

Na tentativa de extrair informação da imensidão de dados hoje colhidos de fontes internas e externas, muitas empresas estão investindo pesado em ferramentas de TI e contratando cientistas de dados. A maioria, contudo, pena para conseguir um retorno digno do esforço. Isso porque estão abordando projetos de “big data” e analítica da mesma forma que abordam qualquer outro projeto de TI, sem perceber que são dois bichos completamente distintos.