[Colloq] Hiring Talk - Christoph Riedl - The Novelty Paradox & Bias for Normal Science: Evidence from Randomized Medical Grant Proposal Evaluations - March 12, 3:15, 424A Hayden Hall

[Jessica Biron]

Please join the Supply Chain and Information Management Group and Christoph Riedl for his talk about 


“ The Novelty Paradox & Bias for Normal Science: Evidence from Randomized Medical Grant Proposal Evaluations ” 

on Tuesday, March 12 th from 3:15 – 4:15pm in 424A Hayden Hall . 



Christoph Riedl is a post-doctoral fellow at the Institute for Quantitative Social Science (IQSS) and Harvard Business School at Harvard University 



Abstract 
Central to any innovation process is the evaluation of proposed projects and allocation of resources. We investigate whether novel research projects, those deviating from existing research paradigms, are treated with a negative bias in expert evaluations. We analyze the results of a peer review process for medical research grant proposals at a leading medical research university, in which we recruited 142 expert university faculty members to evaluate 150 submissions, resulting in 2,130 randomly-assigned proposal-evaluator pair observations. Our results confirm a systematic penalty for novel proposals; a standard deviation increase in novelty drops the expected rank of a proposal by 4.5 percentile points. This discounting is robust to various controls for unobserved proposal quality and alternative explanations. Additional tests suggest information effects rather than strategic effects account for the novelty penalty. Only a minority of the novelty penalty could be related to perceptions of lesser feasibility of novel proposals. 

Bio 
Christoph Riedl is a post-doctoral fellow at the Institute for Quantitative Social Science (IQSS) and Harvard Business School at Harvard University, Cambridge, Massachusetts. He received his PhD in Information Systems from Technische Universität München (TUM), Germany in 2011. He received a BSc in Computer Science from TUM in 2006 and an MSc in Information Systems in 2007. His research interests center around business analytics, data science, "Big Data," and computational social science.