Applying the technology acceptance model to risk communication dashboards: a case study

Purpose: This study examines how the design characteristics of risk communication dashboards influence user acceptance in Small and Medium-sized Enterprises (SMEs). As dashboards become essential for data-driven decision-making, identifying which visual and functional elements drive adoption is critical. The research focuses on features that most strongly affect perceived usefulness (PU) and perceived ease of use (PEOU), two core constructs of the Technology Acceptance Model (TAM), within organisational risk communication and decision support.
Methodology: Based on the extended TAM3 framework, three design characteristics: Notifications and Alerts, Data Context, and Education level were analysed, with Age and Data-to-Ink ratio as moderators. Data were collected from 67 SME executives through an online survey. Structural relationships were tested using Partial Least Squares Structural Equation Modelling (PLS-SEM) to assess reliability, validity, and model fit, leading to the evaluation of nine hypotheses.
Findings: The results indicate that Notifications and Alerts significantly enhance PU, while Data Context improves PEOU. PU positively influences Attitude Toward Use (ATU), which emerges as the strongest predictor of Behavioural Intention (BI). Education level negatively affects PU, Age moderates the relationship between dashboard functionality and PU, and Data-to-ink ratio moderates the effect of Data Context on PEOU.
Practical implications: The findings offer actionable guidelines for designing dashboards that improve clarity, usability, and risk communication efficiency in SMEs, thereby fostering greater engagement with digital decision-support tools.
Originality: This study extends TAM3 to the domain of static risk communication dashboards, demonstrating that design elements are critical determinants of user acceptance in Industry 4.0 decision environments.