Modeling Fashion Business Models Based on Consumer Demand Dynamics for Non-Standard Femininity

Анотація

The relevance of the study is determined by the transformation of the contemporary fashion industry under the influence of the digitalization of consumer behaviour, the growing popularity of niche aesthetic trends, and the increasing role of personalized consumption in shaping brands’ competitive advantages. Under these conditions, conventional approaches to business model design are becoming less capable of responding to rapidly changing consumer demand, highlighting the need to integrate digital demand analytics and adaptive value creation mechanisms into strategic management. The purpose of the article is to develop an analytical framework for modeling successful business models in the fashion industry based on the analysis of consumer demand dynamics for non-standard femininity and to identify strategic mechanisms for transforming this demand into sustainable competitive advantage. Methods. The study employs methods of theoretical generalization, analysis and synthesis, systematization, comparative analysis, structural and logical modeling, interpretation of digital market indicators, and generalization of evidence obtained from Google Trends and industry analytical reports. Results. The conceptual characteristics of non-standard femininity as a factor of differentiation in the contemporary fashion market are examined, and its significance for developing new approaches to customer value creation is substantiated. The potential of digital demand indicators for assessing the dynamics of aesthetic trends and supporting strategic decision-making is identified. It is demonstrated that changes in consumer preferences directly affect the configuration of business models, requiring the adaptation of product policy, market positioning, distribution channels, partnership strategies, and managerial processes. The principal strategic, marketing, and organizational challenges associated with demand volatility, consumer market fragmentation, dependence on digital platforms, and the need for rapid managerial decision-making are determined. Conclusions. The expediency of integrating digital demand analytics, continuous consumer behaviour monitoring, and adaptive value creation strategies into fashion business model design is substantiated in order to improve organizational flexibility, strengthen competitive positioning, and ensure long-term business performance. Prospects for further research are associated with the development of predictive models of aesthetic demand, the assessment of relationships between digital consumer signals and commercial performance, and the application of artificial intelligence technologies to support strategic business model innovation in the fashion industry.