Designing a Fuzzy Expert System for Personal Branding of Managers

Given the importance of personal branding as a key managerial competency, this study aims to present a hierarchical fuzzy mathematical model for the personal branding of managers within the Agricultural Jihad Organization of Gilan Province. This research is categorized as developmental–applied in terms of its purpose and employs a mixed-methods approach in terms of data nature. The qualitative phase involved a statistical population consisting of professional and academic experts, while the quantitative phase included all heads, managers, and experts with over 10 years of experience at the Agricultural Jihad Organization of Gilan Province. In the qualitative phase, data obtained through literature review and expert interviews were analyzed using thematic analysis. As a result, the dimensions, components, and indicators of managerial personal branding were identified and classified into 5 dimensions, 14 components, and 45 indicators. Subsequently, based on the qualitative model, a quantitative questionnaire was developed. Quantitative data were collected from a sample of 121 employees at the Agricultural Jihad Organization of Gilan Province. These data were then analyzed, and the quantitative model was developed using a hierarchical fuzzy inference system. The most significant outcome of this study is the construction of a hierarchical model for managerial personal branding. This model can be used to predict and evaluate the extent to which managers possess a personal brand within the organization.

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Publication Details

Journal
Digital Transformation and Administration Innovation
Published
2025-01-01
DOI
https://doi.org/10.61838/dtai.161
Primary Topic
Employer Branding and e-HRM
Type
article
Field-Weighted Citation Impact
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article

Designing a Fuzzy Expert System for Personal Branding of Managers

Mahdi Danesh, Forogh Rudgarnezhad, Maryam Ooshaksaraie
Digital Transformation and Administration Innovation
Employer Branding and e-HRM
article

Designing a Fuzzy Expert System for Personal Branding of Managers

Mahdi Danesh, Forogh Rudgarnezhad, Maryam Ooshaksaraie
article en

Abstract

Given the importance of personal branding as a key managerial competency, this study aims to present a hierarchical fuzzy mathematical model for the personal branding of managers within the Agricultural Jihad Organization of Gilan Province. This research is categorized as developmental–applied in terms of its purpose and employs a mixed-methods approach in terms of data nature. The qualitative phase involved a statistical population consisting of professional and academic experts, while the quantitative phase included all heads, managers, and experts with over 10 years of experience at the Agricultural Jihad Organization of Gilan Province. In the qualitative phase, data obtained through literature review and expert interviews were analyzed using thematic analysis. As a result, the dimensions, components, and indicators of managerial personal branding were identified and classified into 5 dimensions, 14 components, and 45 indicators. Subsequently, based on the qualitative model, a quantitative questionnaire was developed. Quantitative data were collected from a sample of 121 employees at the Agricultural Jihad Organization of Gilan Province. These data were then analyzed, and the quantitative model was developed using a hierarchical fuzzy inference system. The most significant outcome of this study is the construction of a hierarchical model for managerial personal branding. This model can be used to predict and evaluate the extent to which managers possess a personal brand within the organization.

Digital Transformation and Administration InnovationVol. 3(3)
Islamic Azad University Rasht Branch (IR), Islamic Azad University, Bandar Anzali Branch (IR)
Openalex Percentile: Top 68%
Employer Branding and e-HRM
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Designing a Fuzzy Expert System for Personal Branding of Managers — Mahdi Danesh, Forogh Rudgarnezhad, et al. · Digital Transformation and Administration Innovation (2025) | TGRS Research Map | TGRS