This paper examines the role of vision as a mediating variable of the relationship between organizational factors and IoT adoption in audit firms in the US. Using a combination of analyses based on structural equation modeling (SEM) and artificial neural network (ANN) technology as the primary research methodology. Seven hypotheses were accepted, including one related to the impact of vision on IoT adoption. In general, all accepted hypotheses had a positive effect on IoT adoption. In addition to the direct positive impact of vision on IoT technology adoption, the magnitude of that effect varied depending on the context of each hypothesis. Drawing evidence from the results, this study demonstrates that vision was a partial mediating variable in the relationship between the organizational factor and IoT adoption. As a result, the model can help audit firms adopt IoT technology successfully. On the other hand, it makes essential recommendations for implementing IoT technology in light of the role that vision plays as a mediating variable in this model. The Technology-Organization-Environment (TOE) framework and Diffusion of Innovation theory (DOI) are combined with the vision to improve model predictive power.

The Internet of Things (IoT) is one of the most evolving technologies, which has a major impact on our daily life. Almost all new devices will have a feature to be connected and controlled over the Internet. Several applications are utilizing IoT to enhance routine processes and actions efficiently. The Internet of Vehicles (IoV) evolved from IoT, where vehicles communicate with each other or with other objects to have a better transportation environment to reduce the number of accidents and save people’s lives. IoV is considered new fields that need security requirements including confidentiality, integrity, availability, authentication, and trust. Trust management technique is used to validate entities behaviors automatically against well-defined policies. The major categories of trust model in IoV are based on entity, data, or a combination of both. This paper proposes a trust model which is based on a combination of entity and data to define the trust of vehicles and utilize the public key infrastructure to distribute certificates to vehicles. Based on certificate validation, messages will be trusted and accepted. This model has been tested across different simulation scenarios which showed that the proposed model detected malicious vehicles and trusted vehicles did not accept their messages.