Measuring the Impact of Perceived Risk and Trust on the Acceptance of IoT Technology

As IoT continues revolutionizing our interaction with the environment by connecting various devices, it introduces significant data privacy challenges. This study utilizes the Technology Acceptance Model (TAM) to examine the impact of Perceived Risk and Trust on IoT acceptance. Data were gathered from 300 IoT users and analyzed using Structural Equation Modeling - Partial Least Squares (SEM-PLS) to assess the relationships between key variables. The findings reveal that Trust enhances Perceived Usefulness, which positively influences the Intention to Adopt IoT technologies. Additionally, Perceived Risk indirectly affects adoption through Trust and Perceived Usefulness, underscoring the importance of managing security concerns to encourage IoT adoption. Moreover, Privacy Concerns significantly impact adoption rates, showing that users remain hesitant about the potential misuse of their personal data. These results highlight the need for increased security measures and greater transparency in IoT systems, providing crucial insights for both developers and policymakers aiming to promote secure and trusted IoT innovations.