فاطمه صراف

Despite the growth of financial technologies (FinTechs) and their impact on transforming financial services, the implementation of fintech for gaining a competitive advantage in banks appears essential. The aim of this article is to model and determine the relationships and relative importance of the dimensions and components of implementing fintech in the financial-banking system. To this end, the research was conducted with a qualitative and quantitative approach in 2023. The research community included 12 experts, comprising managers and senior specialists from state banks, who were selected purposefully and theoretically. The data collection tools were semi-structured interviews for the qualitative section and a pairwise comparison questionnaire for the quantitative section. The results of the qualitative section, analysed through content analysis, indicated that the model includes dimensions such as "infrastructure and technical", "organizational policies", "products and services", "market", "marketing and sales", "economic", "human resources" and "ecosystem." The quantitative results, analysed using fuzzy DEMATEL, showed that "products and services" is the most influential and critical dimension in the model, suggesting that the success of implementing the model depends on improving this dimension. "Ecosystem" is the most impactful dimension with the strongest relationship in implementing the model, leading to the model's improvement. The findings of the network analysis process also indicated that the components of "product and service diversity", "security and privacy protection", "product and service adaptability" and "creating a platform and sharing it" are the most important. Based on the results, it is recommended that banks invest in those financial technologies (fintech) that can quickly respond to the desires and needs of their customers for successful fintech implementation.

Resource management is a part of project management and its ultimate goal is to achieve maximum efficiency with the lowest level of inventory. Resource management is built around optimization and increased efficiency. In this paper, inventory optimization is done using fuzzy approach and statistical averaging methods are used to solve fuzzy multi-objective linear programming problems. These methods have been used to form a goal function of fuzzy multi-objective linear programming problems. First, in order to optimize inventory and find the weight of each product in Isfahan Steel Company, a model of fuzzy multi-objective linear programming problem is estimated. The highest weight of products is related to commodity ingots and the lowest weight related to other products. The Fuzzy Multi-Objective Linear Programming Estimation Model has compared the statistical methods with the Chondrasen method. The results show that this method has the capacity to optimize the amount of inventory, reduce storage costs and reduce interest costs due to working capital.