Tian Heong Chan

Complex and important decisions are often made with advice from a committee of experts. But how do a committee’s “rules of engagement” affect the way individuals discuss, how they vote, and ultimately the quality of their collective recommendation? Compiling verbatim transcripts from U.S. Food and Drug Administration advisory committee meetings, we study how a 2007 switch from sequential to simultaneous voting procedures changed discussions, information exchange, and decision making. Consistent with past findings, we show that, compared with a sequential voting protocol, simultaneous voting led to a reduction in the likelihood of unanimous votes. Importantly, we show novel evidence that the majority of this reduction in unanimity was mediated by changes in discussion patterns—specifically, by the increased diversity of information surfaced during discussions. We also find evidence of behavioral and linguistic changes that support our theory that voting protocols changed the incentives for members to elicit more diverse information from each other: under simultaneous voting, members exhibited greater equality in talking time, directed a greater proportion of questions to each other, and adopted language that was more positive, authentic, and equal in projecting status and confidence. Finally, we show that recommendations under simultaneous voting were more likely to be accurate, as drugs recommended and approved were less likely to encounter safety-related postmarket events. In sum, voting protocols affect the incentives for individuals to engage in robust discussions, leading to marked improvements in how information is exchanged between individuals, and in the process by which groups of experts arrive at joint recommendations.

Competition among firms has increasingly been through design. We show how computer vision algorithms can be leveraged to measure the visual similarity of design rights across large data sets of product design images. In particular: we extract and standardize 716,168 unique design images included in US design patents (1976–2023); adapt the structural similarity index measure to quantify design similarities between images; and rigorously validate the resulting measure of design rights similarity. We then use that measure to produce novel empirical evidence that a design space's similarity density exhibits an inverted U-shape with respect to the likelihood of that space's design rights being litigated—a relationship proposed previously but never tested. Our design rights similarity measure should facilitate the exploration of new research questions in the fields of design rights, innovation, and strategy. We grant open access to our code and data resources to encourage research in such fields.

2023

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