We study the statistical properties of three estimation methods for a model of learning that is often fitted to experimental data: quadratic deviation measures without unobserved heterogeneity, and maximum likelihood with and without unobserved heterogeneity. After discussing identification...

Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based prescriptions. This paper explores the extent to...

Ziel dieser Arbeit ist es, Innovationen außerhalb von F&E zu beleuchten und zu einer breiteren und tieferen Wertschätzung von Lern- und Wissensschaffungsprozessen beizutragen, die für mitarbeiter- und individuumsgesteuerte Innovationen entscheidend sind. In mehreren Papern wird gezeigt, dass...

Distribution waterfalls in partnership and LLC agreements often incorporate IRR hurdles. Many of those agreements define IRR with reference to Microsoft Excel's XIRR function. That function, if given the correct inputs, can guess an IRR with impressive accuracy. When repurposed to compute IRR...

Consumers often consult the reviews of their peers before deciding whether to purchase a new experience good; however, their initial quality expectations are typically set by the product's observable attributes. This paper focuses on the implications of social learning for a monopolist firm's...

We study observational learning in environments where customers choose among multiple options with uncertain quality for which they observe the aggregate choices of previous customers (the sales of each option). When customers have heterogeneous knowledge about quality, the choices of better...

How much productivity improvement or cost reduction would be possible when the number of semiconductor chips fabricated increased from one million to two million? How many more wind farms or photovoltaic farms needed to be installed before their unit cost of producing electricity can become...

Popular models for decision making under ambiguity assume that people use not one but multiple priors. This paper is a first attempt to experimentally elicit multiple priors. In an ambiguous scenario with two underlying states we measure a subject's single prior, her other potential priors...