Abstract

Abstract: This research employs an innovative approach, combining data mining with econometric models, to investigate the complementarity of Business Innovation and Growth Support (BIGS) programs for Small and Medium-sized Enterprises (SMEs). Utilizing association rule mining, we identify the more important programs used by SMEs and analyze patterns in program combinations. Building on these insights, our econometric analysis employs a multiple-period difference-in-differences framework to quantitatively assess the causal impact of these program combinations on SME performance. This paper aims to provide a better understanding of the synergies within BIGS programs and their effects on SME economic performance.