Modeling Oral Business History Data

We shed light on oral business history data, widely available and yet underutilized, as a relevant and useful resource for strategy and management scholars. Specifically, we outline a novel methodology based on topic modeling and sentiment analysis to illustrate that such data can be used to generate insight about the relationship between a firm's past financial performance and the language and tone of speeches by the firm's CEO. Using 88 CEO interviews conducted between 2008 and 2017, archived at the publicly accessible Harvard Business School online repository titled "Creating Emerging Markets", we employ our unique methodology to study how environmental factors such as unexpected market returns are related to the range of topics and sentiments expressed by CEOs' spoken words. In doing so, we match the data from the CEO interviews with financial performance data for the set of firms led by those CEOs as well as market performance data from the countries in which these firms are headquartered. Our results suggest that greater abnormal returns just prior to the date of the CEO interview are positively correlated with certain emotions expressed by CEOs, such as surprise, fear, and anticipation, an indication that unanticipated firm performance heightens the emotional states of firm leadership, with possible consequences for subsequent strategy choices. Furthermore, greater abnormal returns also are positively correlated with a CEO's tendency to focus their speech more on work-related topics rather than personal topics