2020/10/23 by Ahmed Alali, Ahmed Ghanim Al-Ali, Al-Ali, Ahmed Ghanim +4
Business, Management and Accounting · Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Big Data and Business Intelligence #Computation and Language (cs.CL) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Market Dynamics and Volatility #Stock Market Forecasting Methods #cs.CL #cs.CY #cs.LG
paper · pdf · doi:10.48550/arxiv.2010.12418
Proceedings of The 28th International Conference on Computational Linguistics, 9 pages, 1 figure
openalex publication_date 2020/10/23 · arxiv created 2020/12/03 · arxiv updated 2020/12/04 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
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.