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The ongoing transformation of the fashion industry is driven by an increasing focus on sustainability, ethical practices, and responsible consumer behavior. Simultaneously, social media platforms have emerged as influential forces in this field, shaping fashion trends and consumer preferences. Despite a substantial body of literature investigating consumer preferences between fast and sustainable fashion, a gap in understanding the intricate relationship between fashion preferences, socio-economic profiling, and social media engagement is evident. Thus, this research was aimed at comparatively decoding EU consumers’ preferences for fast fashion against sustainable fashion by exploring the interplay of demographic factors ‒ age, gender, and geographical location ‒ on fashion preferences, as expressed through the digital engagement with fashion-related content on the Meta social platforms. The research methodology implied resorting to logistic regression analysis, aiming to uncover the underlying patterns that fundamentally characterize consumers’ preferences for fashion in the EU. The results provide novel insights into how digital engagement with fashion-related content can act as a barometer for regional fashion identities and preferences, useful for the identification of both convergence and inflection points. Moreover, findings offer a robust foundation for crafting strategies that promote sustainable fashion practices, tailored to specific EU age, gender, and location demographics, by leveraging the insights gained about EU consumer preferences.
The ongoing transformation of the fashion industry is driven by an increasing focus on sustainability, ethical practices, and responsible consumer behavior. Simultaneously, social media platforms have emerged as influential forces in this field, shaping fashion trends and consumer preferences. Despite a substantial body of literature investigating consumer preferences between fast and sustainable fashion, a gap in understanding the intricate relationship between fashion preferences, socio-economic profiling, and social media engagement is evident. Thus, this research was aimed at comparatively decoding EU consumers’ preferences for fast fashion against sustainable fashion by exploring the interplay of demographic factors ‒ age, gender, and geographical location ‒ on fashion preferences, as expressed through the digital engagement with fashion-related content on the Meta social platforms. The research methodology implied resorting to logistic regression analysis, aiming to uncover the underlying patterns that fundamentally characterize consumers’ preferences for fashion in the EU. The results provide novel insights into how digital engagement with fashion-related content can act as a barometer for regional fashion identities and preferences, useful for the identification of both convergence and inflection points. Moreover, findings offer a robust foundation for crafting strategies that promote sustainable fashion practices, tailored to specific EU age, gender, and location demographics, by leveraging the insights gained about EU consumer preferences.
Labour costs are a fundamental component of production expenses, significantly impacting both the quantity and quality of output. This study explores the determinants of labour costs within EU member states that have implemented minimum wage policies over the past two decades. The research technique includes a comprehensive panel analysis of EU member states to identify significant variables influencing labour costs, as well as cluster analysis to discover underlying patterns across the nations under examination. Our findings reveal that higher minimum wage levels, higher employment rates, increased labour productivity, and greater trade openness are positively correlated with higher labour costs. Specifically, increases in these variables lead to higher wages and a broader tax base, while greater trade openness results in elevated labour costs due to expanded market opportunities. Conversely, gross fixed capital formation negatively affects labour costs, as investments in production assets tend to reduce labour requirements or hours worked. The cluster analysis led to the identification of three distinct groups. The first cluster consists of well-developed economies with modest labour cost increases and average minimum wages. The second cluster includes countries with substantial labour cost increases, low minimum wages, and significant productivity gains. The third cluster features nations with high minimum wages and high employment rates. This paper contributes to the field by highlighting the complex interplay between labour costs and economic factors, offering insights for decision-makers to tailor macroeconomic and company-level strategies to specific local conditions. The findings emphasise the importance of balancing wage policies with sustainable economic development to enhance competitiveness while ensuring fair labour conditions.
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