Utilization Of Eco-Friendly Technologies in Micro, Small, And Medium Enterprises (MSME) Focused on Entrepreneurship
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Abstract
In the pursuit of sustainability and competitiveness, the adoption of eco-friendly technologies has emerged as a critical agenda for Micro, Small, and Medium Enterprises (MSMEs). Despite their economic significance, MSMEs face disproportionate barriers to integrating advanced innovations such as High-Performance Computing (HPC), owing to resource constraints, limited digital readiness, and variable entrepreneurial capacity. The study examines the configurational conditions under which MSMEs adopt eco-technologies, emphasizing the interplay between structural, behavioral, and contextual factors. Grounded in the Technology-Organization-Environment (TOE) framework, Technology Acceptance Model (TAM), and entrepreneurial mindset theory, the research employs fuzzy-set Qualitative Comparative Analysis (fsQCA) to evaluate data from 66 MSMEs across IT, electronics, and automotive sectors in the Danube region. The methodological design incorporates both theoretical constructs and field insights to uncover pathways that lead to successful HPC adoption. Three dominant configurations emerged: strong entrepreneurial cognition supported by favorable environmental conditions; opportunity recognition in combination with agile organizational structures; and full-spectrum alignment across cognitive, organizational, technological, and external domains. The perception of usefulness and ease of use—key elements of TAM—also played a pivotal role in shaping adoption behavior. Medium-sized firms demonstrated a higher propensity for adoption, while micro-enterprises encountered greater challenges. The study concludes that eco-technology adoption in MSMEs is not driven by singular factors but by dynamic combinations of internal mindset and ecosystem readiness. These findings inform targeted strategies for policymakers, support agencies, and entrepreneurs seeking to accelerate sustainable innovation at the grassroots level.