Saptiyanto, Nessa Deragia
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TECHNOLOGY READINESS PROFILING OF SMES WITH K-MEANS CLUSTERING IN BANDUNG, INDONESIA : Technology Readiness Profiling of SMEs With K-Means Clustering in Bandung, Indonesia Lestari, Resanti; Lestari, Fitri; Saptiyanto, Nessa Deragia; daffansyah, Chasano
JURNAL EKONOMI BISNIS DAN MANAJEMEN (EKO-BISMA) Vol 4 No 2 (2025): JURNAL EKONOMI BISNIS DAN MANAJEMEN (EKO-BISMA)
Publisher : PUBLISHER ABISATYA DINAMIKA ISWARA PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58268/eb.v4i2.221

Abstract

This study profiles and segments the Technology Readiness Level (TRL) of Micro, Small, and Medium Enterprises (SMEs) in Greater Bandung, Indonesia, using the Technology Readiness Index (TRI) framework. A quantitative, cross-sectional survey was conducted with 171 SME owners across Bandung City, Cimahi City, Bandung Regency, West Bandung Regency, and Sumedang Regency. The TRI framework comprises four dimensions: optimism, innovativeness, discomfort, and insecurity. Data analysis was carried out in two stages: descriptive statistics to examine the overall pattern of technology readiness, and K-Means clustering to identify distinct TRL profiles among SMEs. The K-Means analysis revealed three readiness clusters: High Readiness (34.5%), characterised by high optimism and innovativeness with extensive technology adoption; Moderate Readiness (41.5%), showing partial digital integration and moderate confidence; and Low Readiness (24.0%), dominated by high discomfort and insecurity. One-way ANOVA confirmed significant differences in TRL scores across clusters (p < 0.001). The findings indicate that SME readiness is heterogeneous even within a single metropolitan area, requiring differentiated policy approaches. High readiness SMEs may benefit from advanced digital ecosystem integration, moderate readiness firms need targeted capacity building, and low readiness firms require foundational digital literacy support. The use of K-Means profiling provides a practical and replicable approach for identifying readiness patterns in diverse contexts. This study contributes to the literature on digital adoption in developing economies and offers actionable insights for policymakers and industry stakeholders in designing targeted digitalisation programs. Keywords: Technology Readiness Level, Technology Readiness Index, SMEs, Entrepreneurship, K-Means Clustering, Bandung.