Expert Decision-Making Complexity in New Industries: The Case of Security Analysts

Abstract

This paper examines how expertise influences actors' decision-making complexity. Drawing from the research on expert decision-making, and using the context of security analysts following firms in a new industry, I argue that expert analysts engage in top-down, automatic information processing that affects the complexity of their evaluations. Further, I develop the construct of evaluative complexity, which indicates the extent of nuance, uncertainty and inclusion of diverse perspectives in analyst evaluations. Historical data from the early internet industry (from 1995 to 2005) of approximately 1800 analyst reports on the initial public offerings in the internet industry support my predictions that expert analysts—those with either prior experience or prior status—demonstrate lesser complexity in their evaluations of internet firms as compared to novice or low-status analysts. Specifically, in new industry contexts, expert analysts are more likely to assess new firms from unitary perspectives and convey more certainty in a context that calls for caution. My research aims to contribute to our understanding of the role of expertise in new domains and the differences in decision-making complexity between experts and novices.