The Financing of Innovation: Learning and Stopping
By Dirk Bergemann, U. Hege. 2004
356 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/b1e18846b43c160a32501540eab03d43e48b39a0
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Citations in the corpus
- Learning While Voting: Determinants of Collective Experimentation (2010, methodology): “(6)Exponential bandits have also been used in economics by Malueg and Tsutsui (1997), Bergemann and Hege (1998, 2001), and Décamps and Mariotti (2004).”
- Heuristics, learning and the business angel investment decision-making process (2015, background): “…behaviour by changing their investments in response to the outcomes of past investments, and anticipate learning from future ones, exhibiting explorative behaviour by directing investment towards new investment opportunities (Sorensen 2007, 39; Bergemann and Hege 1998, 2005; Goldfarb et al. 2007).”
- Optimal Contracts for Experimentation (2016, background): “Thus, they are interested in applications such as venture capital financing (Bergemann and Hege, 1998, 2005), whereas we are interested in applications where the principal initially owns the project or the agent cannot directly accrue the full social benefits from project success.”
- Barriers to Innovation among Spanish Manufacturing SMEs (2009, background): “These factors are similar to studies of barriers to innovation in other countries (Hewitt-Dundas 2006; Frishammar and Horte 2005; Bergemann 2005; Mohen and Roller 2005; Baldwin and Lin 2002; Mosey, Clare, and Woodcock 2002; Zwick 2002; Giudici and Paleari 2000; Osterman 2000; Storey 2000).”
- Stochastic Multi-Armed-Bandit Problem with Non-stationary Rewards (2014, background): “Since their inception, MAB problems with various modifications have been studied extensively in Statistics, Economics, Operations Research, and Computer Science, and are used to model a plethora of dynamic optimization problems under uncertainty; examples include clinical trials ([3]), strategic pri”