reza ameri siyahooei; mostafa kazemi; Omid soleimani fard; Alireza Pooya
Abstract
One of the most important factors in understanding customer behavior is identifying their expectations. Therefore, this study in order to design customer expectations model for platform with agent-based model approach. At first, for finding customers and servants expectations was used of semi-structure ...
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One of the most important factors in understanding customer behavior is identifying their expectations. Therefore, this study in order to design customer expectations model for platform with agent-based model approach. At first, for finding customers and servants expectations was used of semi-structure interview and then was done automatic clustering with using meta-heuristic algorithms in order to find different factors. Then, with the factor-based simulation approach, the model was designed in Any Logic software. After designing the model, using design method of Taguchi experiments (Qualitek-4 software), scenarios for the growth and development of the platform based on effective factors (liquidity the quality of communication and trust) designed on four levels and finally simulation was performed and scenarios were examined in the simulation environment. the research results showed that the appropriate level of platform growth and development indicators in the fourth level of liquidity, the fourth level of communication quality and the fourth level of trust. In addition, after implementing the optimal scenario in the simulation environment was determined that the percentage of value created on the Instagram platform due to the implementation of the desired scenario is equal to 0.934.
hamid bekamiri; Mohammad Lagzian; Alireza Pooya; Hossein Sharif
Abstract
While this study identifies the most important key indicators that influence the banking industry, it also attempts to provide a forecast for the Iranian banking industry in the future. Scenario planning and cross-impact matrix are used in this study. Among all the identified factors, 29 key factors ...
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While this study identifies the most important key indicators that influence the banking industry, it also attempts to provide a forecast for the Iranian banking industry in the future. Scenario planning and cross-impact matrix are used in this study. Among all the identified factors, 29 key factors influencing the future of the industry were selected through a fuzzy analytical hierarchical process and then the impact of each of these factors was determined through analysis of the cross-impact matrix. The cross-impact balance was then used to write scenarios.Accordingly, of all combined scenarios, the most likely strong scenarios were clustered into five general categories using K-mode clustering. Finally, four scenarios were identified, including optimism for the bank, banking industry development, inflationary conditions and sanctions. It was therefore possible to define action plans for each of the scenarios.
