In an increasingly digitalized world, enterprises that neglect to adapt and innovate risk losing their competitive edge and lagging behind industry trends. Recognizing the unique challenges that small and medium-sized enterprises (SMEs) encounter in this transformative process, there is a pressing need for an evaluation system to aid decision-making regarding digital technology factors that can enhance the performance of these firms. This study employs a multiple-criteria decision analysis (MCDA) approach that integrates cognitive mapping and the Best–Worst Method (BWM) to systematically identify evaluation criteria and their intricate interactions. To ensure the relevance and applicability of the research findings, a panel of experts was recruited from among professionals with knowledge and experience in this area, who were able to provide added value to the research. The results include a proposed decision-support model, the practical potential of which was discussed and validated by both the panel members and a project manager from COTEC Portugal—a leading think-and-action network dedicated to advancing technology diffusion and business innovation cooperation. Due to its process-oriented nature, this research contributes to bridging the gap between theoretical insights and practical applications. Its contributions and limitations are also analyzed, offering valuable insights for researchers, practitioners and policymakers alike. Overall, this comprehensive and unique approach addresses the critical need for understanding the nuanced interplay between digital technologies and SME performance in today’s dynamic business environment.

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Best–Worst Method (BWM),Cognitive mapping,Digital technologies,Firm performance,Small and medium-sized enterprises (SMEs)

• Economics and Business - Social Sciences