Iranian Business Management Association International Journal of Resistive Economics 2345-4954 13 3 2025 07 01 Identification and Evaluation of Factors Influencing Resilient Economy in Businesses based on Meta-Synthesis Method and Cognitive Mapping 120 135 207458 10.22034/oajre.2024.475368.1095 EN Seyedeh Masoumeh Mousavizadeh Department of Management, Neyshabur Branch, Islamic Azad University, Neyshabor, Iran Seyed Rasoul Hoseini PhD in Management, Department of Management, Torbet Heydarieh Branch, Islamic Azad University, Torbet Heydarieh, Iran 0000-0003-0382-055X Mahdi Hajahmadi PhD in Communication Sciences, Department of Communication Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran 0000-0003-3418-0540 Journal Article 2024 08 26 The complexities governing a country's economy and increasing external pressures demand changes in the country's economic policies to not only withstand external pressures but also foster the growth and development of the nation. The aim of this research is to identify and investigate the factors influencing business development based on a resilient economy using the fuzzy cognitive map approach. The study utilizes the meta-synthesis method for identifying factors affecting business development in a resilient economy and employs the cognitive map method to examine the relationship among the identified factors. This research systematically reviews texts and selects 43 research titles for examination within the period of 2013-2024. Following text extraction and analysis, key codes are extracted and clustered using Atlas.ti software, organized into concepts and components. Ultimately, 14 themes, 49 concept categories, and 290 distinct codes are extracted and classified. Additionally, the quantitative section of the research investigates the relationship among the identified factors. The research population in the quantitative section consists of 18 experts in resilient economics. The sample is non-probabilistic and selected using the snowball sampling method. Semi-structured interviews are used for data collection, and FCMapper and Pajek software are employed for quantitative analysis of the results. The findings reveal that economic factors had the highest impact with a magnitude of 3.733, while cognitive population factors had the highest susceptibility with a value of 3.058. In terms of centrality, economic factors with a value of 4.523 exhibit the highest centrality. https://www.oajre.ir/article_207458_50cf7b54399677fe045c70bf252e13e9.pdf