Abstract
Previous empirical studies reveal that the personalities of senior executives may influence corporate decisions. Grounded in the big-five personality model established in the field of psychology and guided by the design science methodology, the work reported in this paper examines the predictive power of executives' personalities on corporate behaviors. Our main contributions are twofold. First, we design a novel deep learning-based artifact, namely pAttCLSTM which analyzes the senior executives' personalities on a large scale through social media data. In our experiment, pAttCLSTM outperforms other state-of-the-art detectors over two benchmark datasets. Second, empowered by pAttCLSTM, we empirically verify the predictive power of executives' personalities on firms' policy variables by using a dataset including Tweets of 507 executives worked in S&P 1500 companies. To our best knowledge, this is the first successful design of an automatic detector for senior executives' personalities, and hence to examine their impact on firms' behaviors.
Original language | English |
---|---|
Title of host publication | 40th International Conference on Information Systems, ICIS 2019 |
Publisher | Association for Information Systems |
Number of pages | 17 |
ISBN (Print) | 9780996683197 |
Publication status | Published - Dec 2019 |
Event | 40th International Conference on Information Systems (ICIS 2019) - Internationales Congress Center München (ICM), Munich, Germany Duration: 15 Dec 2019 → 18 Dec 2019 https://icis2019.aisconferences.org/ https://aisel.aisnet.org/icis2019/ |
Publication series
Name | International Conference on Information Systems, ICIS |
---|
Conference
Conference | 40th International Conference on Information Systems (ICIS 2019) |
---|---|
Country/Territory | Germany |
City | Munich |
Period | 15/12/19 → 18/12/19 |
Internet address |
Research Keywords
- Corporate Behaviors
- Design Science
- Machine Learning
- Personality Detection