A two-stage SEM-artificial neural network analysis of the organizational effects of Internet of things adoption in auditing firms
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 prim...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Growing Science
2023-01-01
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| Series: | Decision Science Letters |
| Online Access: | http://www.growingscience.com/dsl/Vol12/dsl_2023_8.pdf |
| Summary: | 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. |
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| ISSN: | 1929-5804 1929-5812 |