@inproceedings{pataci-etal-2022-digicall,
title = "{D}igi{C}all: A Benchmark for Measuring the Maturity of Digital Strategy through Company Earning Calls",
author = "Pataci, Hilal and
Sun, Kexuan and
Ravichandran, T.",
editor = "Chen, Chung-Chi and
Huang, Hen-Hsen and
Takamura, Hiroya and
Chen, Hsin-Hsi",
booktitle = "Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.finnlp-1.7",
doi = "10.18653/v1/2022.finnlp-1.7",
pages = "58--67",
abstract = "Digital transformation reinvents companies, their vision and strategy, organizational structure, processes, capabilities, and culture, and enables the development of new or enhanced products and services delivered to customers more efficiently. Organizations, by formalizing their digital strategy attempt to plan for their digital transformations and accelerate their company growth. Understanding how successful a company is in its digital transformation starts with accurate measurement of its digital maturity levels. However, existing approaches to measuring organizations{'} digital strategy have low accuracy levels and this leads to inconsistent results, and also does not provide resources (data) for future research to improve. In order to measure the digital strategy maturity of companies, we leverage the state-of-the-art NLP models on unstructured data (earning call transcripts), and reach the state-of-the-art levels (94{\%}) for this task. We release 3.691 earning call transcripts and also annotated data set, labeled particularly for the digital strategy maturity by linguists. Our work provides an empirical baseline for research in industry and management science.",
}
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<abstract>Digital transformation reinvents companies, their vision and strategy, organizational structure, processes, capabilities, and culture, and enables the development of new or enhanced products and services delivered to customers more efficiently. Organizations, by formalizing their digital strategy attempt to plan for their digital transformations and accelerate their company growth. Understanding how successful a company is in its digital transformation starts with accurate measurement of its digital maturity levels. However, existing approaches to measuring organizations’ digital strategy have low accuracy levels and this leads to inconsistent results, and also does not provide resources (data) for future research to improve. In order to measure the digital strategy maturity of companies, we leverage the state-of-the-art NLP models on unstructured data (earning call transcripts), and reach the state-of-the-art levels (94%) for this task. We release 3.691 earning call transcripts and also annotated data set, labeled particularly for the digital strategy maturity by linguists. Our work provides an empirical baseline for research in industry and management science.</abstract>
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%0 Conference Proceedings
%T DigiCall: A Benchmark for Measuring the Maturity of Digital Strategy through Company Earning Calls
%A Pataci, Hilal
%A Sun, Kexuan
%A Ravichandran, T.
%Y Chen, Chung-Chi
%Y Huang, Hen-Hsen
%Y Takamura, Hiroya
%Y Chen, Hsin-Hsi
%S Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F pataci-etal-2022-digicall
%X Digital transformation reinvents companies, their vision and strategy, organizational structure, processes, capabilities, and culture, and enables the development of new or enhanced products and services delivered to customers more efficiently. Organizations, by formalizing their digital strategy attempt to plan for their digital transformations and accelerate their company growth. Understanding how successful a company is in its digital transformation starts with accurate measurement of its digital maturity levels. However, existing approaches to measuring organizations’ digital strategy have low accuracy levels and this leads to inconsistent results, and also does not provide resources (data) for future research to improve. In order to measure the digital strategy maturity of companies, we leverage the state-of-the-art NLP models on unstructured data (earning call transcripts), and reach the state-of-the-art levels (94%) for this task. We release 3.691 earning call transcripts and also annotated data set, labeled particularly for the digital strategy maturity by linguists. Our work provides an empirical baseline for research in industry and management science.
%R 10.18653/v1/2022.finnlp-1.7
%U https://aclanthology.org/2022.finnlp-1.7
%U https://doi.org/10.18653/v1/2022.finnlp-1.7
%P 58-67
Markdown (Informal)
[DigiCall: A Benchmark for Measuring the Maturity of Digital Strategy through Company Earning Calls](https://aclanthology.org/2022.finnlp-1.7) (Pataci et al., FinNLP 2022)
ACL