스타트업 데이터 기반의 시장융합 다이내믹스 분석: 한국을 중심으로

Abstract

Market convergence plays an increasingly important role in sustaining competitiveness and providing impetus for the new product development. However, existing research focused mostly on the analysis of convergence at technology level. This study examines the phenomenon of market convergence based on the start-up data. Similar to the analysis of technology convergence, this study adopts the concept of co-classification analysis for constructing the co-occurrence matrix and the corresponding network. In this context, network centrality measures were calculated to assess the influence of individual market segments. Based on three metrics “growth”, “persistence” and “novelty”, the market convergence dynamics were explored and promising interactions between two distinct market segments were highlighted. The findings suggest that both segments “AI” and “blockchain” are acting as a driver that fosters market convergence in the startup landscape. The analysis results can provide valuable information for the R&D managers and policy makers in the design of targeted policies and programs, which can promote market convergence and interdisciplinary knowledge transfer.