Abstract
PESTLE analysis has been used for decades to help companies in taking challenging and complex decisions with regards to aspects such as the development of new lines
of products, or the expansion into new markets. Despite its complexity, PESTLE analysis is still performed manually, with issues related to the efficiency of the overall process, and the quality of the suggested actions. In this work, leveraging on recent advances in Artificial Intelligence, we propose a framework for companies which can be used to support performing PESTLE analysis. In particular, we focus on the Legal aspect of the PESTLE acronym, that is one of the most complex to investigate.
of products, or the expansion into new markets. Despite its complexity, PESTLE analysis is still performed manually, with issues related to the efficiency of the overall process, and the quality of the suggested actions. In this work, leveraging on recent advances in Artificial Intelligence, we propose a framework for companies which can be used to support performing PESTLE analysis. In particular, we focus on the Legal aspect of the PESTLE acronym, that is one of the most complex to investigate.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the EMerging Technology conference (EMiT) 2019 |
| Editors | M. K. Bane, V. Holmes |
| Publisher | The Emerging Technology (EMiT) Conference |
| Pages | 66-68 |
| Number of pages | 3 |
| ISBN (Print) | 9780993342646 |
| Publication status | Published - Jul 2019 |
| Event | Emerging Technology Conference - University of Huddersfield, Huddersfield, United Kingdom Duration: 9 Apr 2019 → 11 Apr 2019 https://emit.tech/ |
Conference
| Conference | Emerging Technology Conference |
|---|---|
| Abbreviated title | EMiT |
| Country/Territory | United Kingdom |
| City | Huddersfield |
| Period | 9/04/19 → 11/04/19 |
| Internet address |