Recently, Building Information Modeling (BIM) technology has attracted much attention in the Architecture, Engineering, and Construction (AEC) industry. Despite the growing interest in BIM technology, the benefits of BIM have not yet been fully realized during the course of implementation of BIM because of its low adoption rate among architects. Therefore, it is significant important in successful adoption of BIM in design organizations, understanding of the factors influencing the adoption of BIM. The aim of this study is to empirically examine the individual, organizational, social, and technical factors affecting architects' adoption of BIM. The 162 architects with experience using BIM tools at three major design firms in South Korea were selected to participate in the face-to-face survey. This study extends the Technology Acceptance Model (TAM) by incorporating constructs such as computer self-efficacy from the individual domain, top management support and technical support from the organizational domain, subjective norm from the social domain and compatibility from the technical domain. The results strongly support the extended TAM in predicting the intention of users to adopt BIM. It also demonstrates the significant effect of computer self-efficacy, top management support, subjective norm, and compatibility on behavioral intention through perceived ease of use and perceived usefulness. This study provides academics and practitioners with the understanding of factors leading to the successful implementation of BIM in design organizations. It also provides insight into the role management plays in the adoption of BIM among architects in the AEC industry.
The manufacture of gears by applying hot or cold bulk forming processes is a quite widespread production method due to its well-known basic advantages such as material and time cost reduction and the increased strength of the teeth. However, the associated process planning and tool design are more complicated. In the precision forging of gears, the workpiece volume, the die design, the power requirement and careful processing are more critical than traditional forging technology. For complete filling up, predicting the power requirement is an important feature of the near net-shape forging process. In this paper, a finite element analysis is utilized to investigate the material properties such as yielding stress, strength coefficient and strain hardening exponent effects on forming load and maximum effective stress. The adductive network was then applied to synthesize the data set obtained from the numerical simulation. The predicted results of the maximum forging load and maximum equivalent stress of bevel gear forging from the prediction model are consistent with the results obtained from FEM simulation quite well. After employing the prediction model one can provide valuable references in prediction of the maximum forging load and maximum equivalent stress of bevel gear forging under a suitable range of material parameters.
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