Improving Sustainability Performance through AI-Enabled Decision Support: Evidence from MSMEs

This study involved 168 MSME owners and managers from various business sectors. The majority operate in the culinary sector, followed by fashion and tourism, while smaller proportions are found in retail, services, and manufacturing. This distribution reflects the dominance of food-related and creative businesses within the MSME structure.
Most enterprises are relatively young, with the largest proportion operating between two and five years, followed by businesses under two years. Only a small share has operated for more than ten years, indicating a dynamic and developing MSME environment.
In terms of financial scale, most respondents report monthly revenues between ten and fifty million rupiah, representing typical small-enterprise operations. Only a limited number operate at higher revenue levels. Consistent with this profile, most businesses employ between one and ten workers, confirming the small-scale and owner-driven nature of MSMEs.
Overall, the sample represents typical MSME characteristics, including small operational scale, moderate revenue, limited workforce, and relatively young business age, providing an appropriate context for examining technology-enabled decision making and sustainability performance.
The analysis was conducted using Partial Least Squares Structural Equation Modeling. The evaluation followed two main stages consisting of the measurement model and the structural model, followed by mediation testing, as recommended in SEM-PLS procedures.