论文标题
深度学习框架，用于衡量从收入电话的公司数字策略的数字策略
Deep Learning Framework for Measuring the Digital Strategy of Companies from Earnings Calls
论文作者
论文摘要
当今的公司正在竞争，以利用最新的数字技术，例如人工智能，区块链和云计算。但是，许多公司报告说，他们的策略未达到预期的业务结果。这项研究是第一个将最先进的NLP模型应用于非结构化数据的研究，以了解公司正在采用的数字策略模式的不同群集。我们通过分析2015年至2019年之间的财富全球500家公司的收入电话来实现这一目标。我们将基于变压器的体系结构用于文本分类，这表明对对话环境有了更好的了解。然后，我们通过应用聚类分析来研究数字策略模式。我们的发现表明，《财富》 500强公司使用了四种不同的产品LED策略，客户体验LED，服务LED和效率LED。这项工作为公司和研究人员增强我们对该领域的理解提供了经验基准。
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.
