Template-Type: ReDIF-Article 1.0
Author-Name: Seyedeh Masoumeh Mousavizadeh
Author-Name-First: Seyedeh Masoumeh
Author-Name-Last: Mousavizadeh
Author-Email: modir.mba3@gmail.com
Author-Workplace-Name: Department of Management, Neyshabur Branch, Islamic Azad University, Neyshabor, Iran
Author-Name: Seyed Rasoul Hoseini
Author-Name-First: Seyed Rasoul
Author-Name-Last: Hoseini
Author-Email: rasol.h.88@gmail.com
Author-Workplace-Name: PhD in Management, Department of Management, Torbet Heydarieh Branch, Islamic Azad University, Torbet Heydarieh, Iran
Author-Name: Mahdi Hajahmadi
Author-Name-First: Mahdi
Author-Name-Last: Hajahmadi
Author-Email: modir.mba7@gmail.com
Author-Workplace-Name: PhD in Communication Sciences, Department of Communication Sciences, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Title: Identification and Evaluation of Factors Influencing Resilient Economy in Businesses based on Meta-Synthesis Method and Cognitive Mapping
Abstract: 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.
Classification-JEL: JEL
Keywords: Resilient Economy; Business; Meta-synthesis; Fuzzy Cognitive Map
Journal: International Journal of Resistive Economics
Pages: 120-135
Volume: 13
Issue: 3
Year: 2025
Month: July
DOI: 10.22034/oajre.2024.475368.1095
File-URL: https://www.oajre.ir/article_207458_50cf7b54399677fe045c70bf252e13e9.pdf
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File-Function: Full text
File-URL: https://www.oajre.ir/article_207458.html
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Handle: RePEc:trd:journl:207458