Analyzing technological convergence trends in a business ecosystem

Abstract

Purpose – The purpose of this paper is to provide a framework for understanding core technological competencies and identifying the trends on the technological convergence of a business ecosystem using the patent information of leading firms in the system. Design/methodology/approach – The proposed framework is composed of two steps: time-sequential text clustering analysis for comprehending changes in general technological fields and association rule analysis for identifying the trends of convergences in each field. The authors applied the proposed framework to the patents applied to United States Patent Trademark Office by Samsung Electronics, a market leader of the electronics industry, during the period from 2000 to 2011. Findings – In the sequential text clustering analysis, trends of 14 technological fields such as data storage medium and data processing, mobile, lights and heats and memory are identified. Moreover, changes of technological convergence in each field are identified using association rule analysis. For instance, in the case of technologies related to lights and heats, convergences occurred between radio transmission systems and modulated-carrier systems during the period from 2000 to 2001. However, recent convergences appeared between technologies regarding controlling lights and liquid crystal materials since 2008. Originality/value – Utilization of the framework will suggest new business opportunities to SMEs in a business ecosystem by identifying the trends of technological convergences.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 31 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.