Determinan resiliensi UKM dari perspektif manajemen teknologi: sebuah systematic literature review
DOI:
https://doi.org/10.37631/ebisma.v7i1.2322Keywords:
SME resilience, technology management, digital transformation, dynamic capabilities, system dynamicsAbstract
SME resilience has become a strategic issue because small and medium enterprises operate in increasingly turbulent environments shaped by crises, market shifts, supply chain disruptions, and rapid digitalization, while the technology management perspective provides a relevant lens for explaining how SMEs survive, adapt, and recover. This study aims to identify the determinants of SME resilience from a technology management perspective and to synthesize the conceptual relationships among variables as a foundation for developing a system dynamics model. The study employs a PRISMA-based Systematic Literature Review using four databases, namely Scopus, Taylor & Francis, IEEE, and ScienceDirect, resulting in 18 included articles. The findings show that the determinants of SME resilience can be grouped into four major categories: internal technological capabilities, managerial and organizational capabilities, external environment and ecosystem support, and resilience outcomes. The most dominant variables in the literature include digital transformation, dynamic capabilities, IT capability, digital capability, absorptive capability, organizational agility, and government support. The conceptual synthesis further reveals that technology-related factors rarely influence resilience directly, but rather operate through mediating mechanisms such as digital transformation, organizational agility, ambidexterity, and strategic flexibility. The novelty of this study lies in its synthesis of SME resilience determinants from a technology management perspective that is explicitly directed toward supporting the development of a system dynamics model. Accordingly, this review does not merely identify the determinants of SME resilience, but also organizes them into a conceptual foundation for modelling dynamic and interconnected causal relationships.
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