Deep Learning Framework for Measuring the Digital Strategy of Companies from Earnings Calls
October 23, 2020 ยท Declared Dead ยท ๐ International Conference on Computational Linguistics
"No code URL or promise found in abstract"
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Authors
Ahmed Ghanim Al-Ali, Robert Phaal, Donald Sull
arXiv ID
2010.12418
Category
cs.CL: Computation & Language
Cross-listed
cs.CY,
cs.LG
Citations
3
Venue
International Conference on Computational Linguistics
Last Checked
4 months ago
Abstract
Companies today are racing to leverage the latest digital technologies, such as artificial intelligence, blockchain, and cloud computing. However, many companies report that their strategies did not achieve the anticipated business results. This study is the first to apply state of the art NLP models on unstructured data to understand the different clusters of digital strategy patterns that companies are Adopting. We achieve this by analyzing earnings calls from Fortune Global 500 companies between 2015 and 2019. We use Transformer based architecture for text classification which show a better understanding of the conversation context. We then investigate digital strategy patterns by applying clustering analysis. Our findings suggest that Fortune 500 companies use four distinct strategies which are product led, customer experience led, service led, and efficiency led. This work provides an empirical baseline for companies and researchers to enhance our understanding of the field.
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