Copenhagen Business School

About: Copenhagen Business School is a education organization based out in Copenhagen, Hovedstaden, Denmark. It is known for research contribution in the topics: Corporate governance & Entrepreneurship. The organization has 2194 authors who have published 9649 publications receiving 341898 citations.

Marginality and Problem-Solving Effectiveness in Broadcast Search

Abstract: We examine who the winners are in science problem-solving contests characterized by open broadcast of problem information, self-selection of external solvers to discrete problems from the laboratories of large research and development intensive companies, and blind review of solution submissions. Analyzing a unique data set of 166 science challenges involving over 12,000 scientists revealed that technical and social marginality, being a source of different perspectives and heuristics, plays an important role in explaining individual success in problem solving. The provision of a winning solution was positively related to increasing distance between the solver's field of technical expertise and the focal field of the problem. Female solvers---known to be in the “outer circle” of the scientific establishment---performed significantly better than men in developing successful solutions. Our findings contribute to the emerging literature on open and distributed innovation by demonstrating the value of openness, at least narrowly defined by disclosing problems, in removing barriers to entry to nonobvious individuals. We also contribute to the knowledge-based theory of the firm by showing the effectiveness of a market mechanism to draw out knowledge from diverse external sources to solve internal problems.

The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generating New Product Ideas?

Abstract: Generating ideas for new products used to be the exclusive domain of marketers, engineers, and/or designers. Users have only recently been recognized as an alternative source of new product ideas. Whereas some have attributed great potential to outsourcing idea generation to the “crowd” of users (“crowdsourcing”), others have clearly been more skeptical. The authors join this debate by presenting a real-world comparison of ideas actually generated by a firm’s professionals with those generated by users in the course of an idea generation contest. Both professionals and users provided ideas to solve an effective and relevant problem in the consumer goods market for baby products. Executives from the underlying company evaluated all ideas (blind to their source) in terms of key quality dimensions, including novelty, customer benefit, and feasibility. The study reveals that the crowdsourcing process generated user ideas that score significantly higher in terms of novelty and customer benefit, and somewhat lower in terms of feasibility. However, the average values for feasibility – in sharp contrast to novelty and customer benefit – tended to be relatively high overall, meaning that feasibility did not constitute a narrow bottleneck in this study. Even more interestingly, it is found that user ideas are placed more frequently than expected among the very best in terms of novelty and customer benefit. These findings, which are quite counterintuitive from the perspective of classic new product development (NPD) literature, suggest that, at least under certain conditions, crowdsourcing might constitute a promising method to gather user ideas which can complement those of a firm’s professionals at the idea generation stage in NPD.

A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?

Abstract: We compare 330 ARCH-type models in terms of their ability to describe the conditional variance. The models are compared out-of-sample using DM-$ exchange rate data and IBM return data, where the latter is based on a new data set of realized variance. We find no evidence that a GARCH(1,1) is outperformed by more sophisticated models in our analysis of exchange rates, whereas the GARCH(1,1) is clearly inferior to models that can accommodate a leverage effect in our analysis of IBM returns. The models are compared with the test for superior predictive ability (SPA) and the reality check for data snooping (RC). Our empirical results show that the RC lacks power to an extent that makes it unable to distinguish 'good' and 'bad' models in our analysis.

Inside the Family Firm: The Role of Families in Succession Decisions and Performance

Abstract: This paper uses a unique dataset from Denmark to investigate (1) the role of family characteristics in corporate decision making, and (2) the consequences of these decisions on firm performance. We focus on the decision to appoint either a family or an external chief executive officer (CEO). We show that a departing CEO’s family characteristics have a strong predictive power in explaining CEO succession decisions: family CEOs are more frequently selected the larger the size of the family, the higher the ratio of male children and when the departing CEOs had only had one spouse. We then analyze the impact of family successions on performance. We overcome endogeneity and omitted variables problems of previous papers in the literature by using the gender of a departing CEO’s first-born child as an instrumental variable (IV) for family successions. This is a plausible IV as male first-child family firms are more likely to pass on control to a family CEO than female first-child firms, but the gender of the first child is unlikely to affect firms’ performance. We find that family successions have a dramatic negative causal impact on firm performance: profitability on assets falls by at least 6 percentage points around CEO transitions. These estimates are significantly larger than those obtained using ordinary least squares. Finally, our findings demonstrate that professional non-family CEOs provide extremely valuable services to the organizations they work for.