درخت حوزه‌های تخصصی

In the technology-driven industries like automotive industry, the success of the companies depends on their ability to provide new and continuous innovations to the market. In this regard, technological capabilities lead to a competitive advantage. The purpose of this study is to identify the effective factors in the technology assessment based on the dynamic capabilities of small and medium automotive supply chains. In this study, by using the principal components analysis (PCA) method, the identification of the important factors according to the views of automotive industry experts has been addressed. The results show that from the perspective of dynamic capabilities, Absorbency and learning, Innovative capability and integration capabilities are the most effective factors. In terms of technology assessment, Processes and organizational structure and level of technology development are the most important factors identified in order to assess the technology of these companies. In addition, in this study, due to the effective factors, a new technology assessment model with dynamic capabilities approach has been proposed and a relevant questionnaire has been developed. The results of reliability analysis show that the proposed questionnaire has an appropriate accuracy and reliability in technology assessment of small and medium automotive supply chain companies.

To improve the operation level of the companies tailored to industry 4.0 it is necessary to develop logistics system. In order to develop the logistics level, the first step is to measure the growth and evolution of all logistics process. For measuring the evolution and growth of the logistics system (LS), the processes and components of the logistics system and then the evolution level should be determined, at the end their level of evolution should be measured for each firms. The purpose of this paper is to determine the evolution level of the LS in the large industries of Iran. The research method is descriptive - applied and Data were gathered in two steps. First utilizing interviews with logistics experts for identifying the logistics process and components. Second step was data collection by check list in local visits and direct observation in firms. Checklist was completed in group sessions with the help of managers and experts in each firm. Using the mean of the logistics components and degree of adoptive (DOA) technique, evolution of LS was measured in industries. Results shown that firms with heavy products have little progress in the evolution of logistics compared to other firms and also the firms that have automatic production system will growth in logistic evolution better than others especially in intra-logistics and material handling. The method and result of this paper can be seen as a roadmap for managers and organizations and they will plan development and evolution of logistics processes.