Unveiling Business Activity Patterns of Digital Transformation through K-Means Clustering with Universal Sentence Encoder in Transport and Logistics Sectors

Abstract

Digital transformation brings several key benefits to transportation and logistics firms, such as operational efficiency, improved customer experience, and supply chain visibility. This study seeks to identify and categorize business activities within the transportation and logistics sector, focusing on themes related to digital transformation. Additionally, it analyses the impact of firm size and sales performance. Data were sourced from 24 annual reports of four firms listed in the SET, covering the study period of 2017-2022. The study used context-free grammar-based verb patterns and a custom-made dictionary to extract business activities. The study used the Universal Sentence Encoder to represent the text and relied on the Dunn-Index and Silhouette score to determine the optimal number of clusters (both 8 clusters). Subsequently, K-means clustering was performed using these 8 clusters, leading to the categorization of eight digital transformation themes. Among these themes, profit management and regulation compliance are interesting discoveries, as they are rarely mentioned in previous studies. A total of 104 business activities were extracted as a result. The study also found that Online-to-Offline activity is an effective method for business model innovation, as well as a contemporary marketing tool.