Technological Opportunity Analysis for the Telehealth Industry

Abstract

Early identification of emerging technological opportunities is crucial for companies to formulate technology strategies that can provide a core competitive advantage over competitors in the future. It is required to have an effective approach to support industrial practitioners to identify and analyze technological opportunities, especially for a new emerging technology-enabled market. This research develops an outlier-based patent analysis approach to explore potential technological opportunities for the telehealth industry. The proposed methodology applies text mining based on the vector space model (VSM) to represent patent documents as a term-document matrix. Latent semantic analysis (LSA), a technique in natural language processing, is used to transform the original term-document matrix into a lower dimensional space to alleviate the problem of curse of dimensionality. Then, the angle-based outlier detection (ABOD) method is applied to determine outlier patents that provide fresh ideas for new technological opportunities. Several potential opportunities are identified from the experimental results, such as new material, unified data transmission hub, new indicators for more accurate data collection, and facilitating coordination among care team members. The research finding may help Taiwans telehealth firms identify potential opportunities and improve their product strategies.