Background: The fundamental disruptions brought on by digital transformation create substantial uncertainties for small and medium-sized enterprises (SMEs). While the limited resources and unstructured nature of SMEs present challenges for their digital transformation efforts, these challenges can be overcome with proper alignment of their current and future capabilities. However, several questions remain about the validation of digital maturity models (DMMs) for use with SMEs. Our study’s primary objective is to remedy these challenges by validating our DMM for SMEs. Our study attempts to answer the research question, “How can SMEs’ digital maturity be further explored and used to validate our DMM for SMEs?”
Methods: Implementing a mixed-method approach, we use an original survey and 17 observation protocols as quantitative methods to explore SMEs’ digital capabilities. To confirm these initial findings, we conduct 17 semi-structured qualitative interviews to validate our interaction areas and dimensions based on SME-specific characteristics and answer our research question.
Results: The quantitative and qualitative findings and further validation allowed us to identify five propositions including stakeholder and SME interactions, mindset towards SMEs’ challenges and future digital development, and human capital capabilities. These results endorse the overall significance of our DMM for SMEs.
Conclusion: Our study contributes to the DMM literature by providing validated evidence to increase confidence in our model and allow SMEs to feel assured in using our DMM to gain a better understanding of their capabilities and an effective path toward digital transformation. Our validated model demonstrates that stakeholders, digital strategic and operational capabilities, and strategic planning and decision-making influence SMEs’ digital maturity.
Williams, Christopher A.; Krumay, Barbara; Schallmo, Daniel; and Scornavacca, Eusebio, "Digital Maturity Model for SMEs: Validation Through a Mixed-Method Approach" (2023). PAJAIS Preprints (Forthcoming). 12.