The introduction of a culture of environmental responsibility is becoming not just a branding tool, but also an important factor in business development. This article explores the possibility of increasing the environmental performance of companies through green methods of personnel management using the example of Iranian car manufacturers. The study combines survey and correlation-analytical methods. The study reveals that the improvement of green methods of human resource management, covering such aspects as recruitment, training, and performance management, has a positive and significant impact upon the environmental performance of companies. The effectiveness of these activities increases with the use of new technologies such as learning management systems (LMS), cloud computing, and artificial intelligence. The application of green methods in personnel management stimulates the implementation of a corporate strategy of sustainable development and opens new career opportunities for employees. The benefits for the companies lie in the improvement of corporate image, the growing demand for their products, the improvement of production safety, and, consequently, that of the internal organizational climate.
One of the most important development strategies with the emphasis on small and medium industries is the geographical concentration of production units and the formation of cluster. The industrial cluster is a globally economic phenomenon that has been proposed as a modern model for economic development. Theoretically, an industrial cluster can strengthen specialized sectors and facilitate industrial cooperation. The aim of this study was to provide a comprehensive model for measuring the performance dimensions of industrial clusters in Markazi province using a hybrid approach of Q-factor analysis and cluster analysis. For this purpose, at first and in the first phase of the research, 41 effective factors in the clustering of the performance dimensions of the statistical population were identified with the study of previous research and the use of Q-factor analysis, and in the second phase, a model for comprehensive performance measurement of industrial clusters was presented using cluster analysis in R software. The results of the study indicated that industrial clusters in Markazi province have four financial, competitive, economic and environmental performance dimensions.
Considering the mediating role of the new financial technologies, this paper aims to study the relationship between the use of knowledge management (KM) and the enhancing financial performance of banks in the banking industry of Iran. In terms of purpose, the paper was applied and correlational one in terms of descriptive method. The statistical sample was made up of 180 senior and middle managers of active banks in Iran with at least 5 years of work experience (tenure) in KM and new financial technologies. Moreover, A questionnaire was applied to collect research data, and the validity and reliability were confirmed through CVR and Cronbach's alpha indices. Upon collecting the data to test the research hypotheses, the structural equation modeling method was applied in the SmartPLS. The results showed that KM holds a positive and significant effect on enhancing financial performance and 0.682 directly predicts the changes related to the financial performance of the studied banks. Furthermore, further analysis of the results showed that KM through modern financial technologies holds a positive and significant effect on the financial performance of active banks in the banking industry of Iran. Consequently, applying KM dimensions (use of knowledge, acquisition of knowledge, and integration of knowledge) along with modern financial technologies - such as cloud computing technology, smart contracts, and artificial intelligence – is likely to enhance the financial performance of banks and provide sustainable profitability.
Increased productivity and new investment are two methods for the development of industry, and one of the differences between advanced industrial countries and developing countries is to pay particular attention to development through increased productivity. In recent years, new models have been developed in the industry sector, dating to less than fifteen years; one of them is the model of industrial cluster development. Industrial clustering is being carried out today in almost every country in the world. In Iran, the industrial cluster issue is considered in scientific and decision-making centers, as well as in the development plans of the country. The purpose of this research was to identify and prioritize the effective factors on the development and creation of industry cluster of rail industries in the Markazi Province using the network analysis technique. In order to identify cluster creation factors, library studies and the Delphi method were used with the cooperation of the expert group. In the following, we examined the relative importance of these factors using the network analysis technique and the factors were prioritized by Super Decision Application. The results showed that the indicators of geographical concentration and environmental factors are included in the most important factors and the communication index is the least important factor in the creation and development of industrial clusters of rail industries in the Markazi Province.
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