Designing a beauty and fashion consumer buying behavior model using digital marketing (with emphasis on Foundation data theory)

Subject Areas : Jounal of Marketing Management

Somayeh Hozouri ¹ , mohamad ali Abdolvand ² , Kambiz Heidarzadeh ³ , Mohsen Khunsiavash ⁴

1 - PhD Student in Marketing Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - Associate Professor, Business Management Department, Science and Research Unit, Islamic Azad University, Tehran, Iran
3 - Associate Professor, Business Management Department, Science and Research Unit, Islamic Azad University, Tehran, Iran
4 - Assistant Professor, Department of Business Administration, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Received: 2023-11-10 Accepted : 2024-01-23 Published : 2024-10-02

Keywords: Consumer buying behavior, Digital marketing, Foundation data theory, Fashion, Fashionconsumer.,

Abstract :

Introduction: According to the business perspective of the digital market fashion to the fashion and beauty consumer, which aims to influence the buying behavior and win her trust, there are concerns about the body image that leads the consumer to the ever-increasing demand for fashion services. So far, no research has been done to investigate the buying behavior of fashion consumers based on the patterns of changing buying behavior using the digital space, so the purpose of this research is to design consumer buying behavior model for different situations of buying behavior in the digital market.

Methodology: The research method of this study is a qualitative method. The technique used was determined based on foundational data theory. 14 experts and managers of the digital market were selected by non-probability and purposeful sampling method (snowball). Information and data were collected in the form of open codes through specialized interviews with experts and managers of the digital market. Then, the research data were classified and monitored by communicating between micro and macro categories and finally confirmed.

Results and Discussion: Data were extracted after open coding, axial and selective coding in the form of 32 concepts and 9 main categories. In the end, based on the foundational data theory, the identified codes were categorized into strategic factors, components, causal cases, basis conditions, influencing conditions, and consequences.

Conclusion:The categories are: strategic factors of the digital market, components of the digital market, causal factors influencing the buying behavior of consumers in the digital space, external stimuli and influential basis conditions in the digital space, fashion components, The component of fashion consumer buying behavior, The factor of influential conditions in the fashion market, The factor of positive consequences of the fashion market and the digital market, The factor of negative consequences of the fashion market and the digital market.

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