SMEs’ digital maturity: analyzing influencing factors and the mediating role of environmental factors

Purpose This study investigates the relationships among various dimensions influencing the digital maturity of small- and medium-sized enterprises (SMEs). A novel variable, namely SMEs' dependence level on environmental factors, is introduced to broaden the scope beyond traditional linear relationships, providing insights into the multifaceted nature of SME digital maturity. Design/methodology/approach The study employs correlation and regression analyses to unravel significant correlations and explore the impact of predictors on the dependent variable. The interconnectedness of Technology, Product, Organization, People, Strategy and Operations is scrutinized, revealing their collective influence on SMEs' digital maturity. Importantly, the absence of multicollinearity issues is confirmed, validating the reliability of the study’s results. The regression models demonstrate robust explanatory power, with the inclusion of a mediator significantly enhancing overall model performance. Findings The findings highlight the interconnected nature of key dimensions, emphasizing the collective influence of Technology, Product, Organization, People, Strategy and Operations on SMEs' digital maturity. Analysis of variance results further support the effectiveness of these predictors in capturing variability in the dependent variable. Beta values provide insight into the distinct contributions of each predictor, emphasizing their individual impacts on SMEs' digital maturity. Originality/value This study contributes to the field by emphasizing the need for more holistic models and methodological advancements to understand the complex dynamics that shape SMEs' digital maturity. By introducing the novel variable of SMEs' dependence level on environmental factors, the research expands the conceptual framework, offering a fresh perspective on the multifaceted nature of SME digital maturity. The study’s originality is underscored by robust statistical analyses and an exploration of relationships among key dimensions. The comparison and contrast of findings with existing literature further enhance the study’s unique contributions to the field.