The significant changes which have occurred in the competitive scenario in which fashion companies operate, combined with deep transformation in the lifestyles of final consumers, translate into the need to redefine the business models. Starting from a general overview of the emerging trends today affecting the fashion industry, the paper will devote particular attention to the analysis of the most important phenomena that are influencing this market and the drivers for long-lasting competitiveness: sustainability and attention to the so-called circular economy. According to the literature, from the consumer behavior’s point of view, the younger generations are paying growing attention to these issues. In light of these considerations, this paper aimed to analyze how sustainability and circular economy principles are influencing the perception of the fashion world among the new generations of consumers. After mapping the emerging trends in the fashion industry and analyzing the role of sustainability from both the demand and supply side, this paper presents the results of a survey conducted through an anonymous questionnaire made in collaboration with Insubria University. The results of the survey describe the students’ behaviour as regards fashion’s emerging trends, with particular attention to sustainability issues and the application of circular economy principles. The survey results were analyzed from both a descriptive and quantitative point of view with the aim to check the different perceptions as regards sustainable fashion and circular economy in fashion, focusing mainly on the so-called Generation Z. The results of the analysis proved to be consistent with the theoretical framework and confirm the relevance of sustainability issues in the fashion industry today in driving the demand of Generation Z, by considering a gender perspective. Moreover, the circular economy is descriptively analyzed with the aim to understand the relevance of the different facets for the entire sample of respondents.

Trends in the Fashion Industry. The Perception of Sustainability and Circular Economy: A Gender/Generation Quantitative Approach

The growing presence of social media influencers (SMIs) is increasingly modulating consumer behaviour in the travel industry. Trust is a vitally important topic in influencer and tourism marketing ...

The impact of social media influencers on travel decisions: the role of trust in consumer decision journey

Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda

Using social media to identify tourism attractiveness in six Italian cities

Industry 4.0 ten years on: A bibliometric and systematic review of concepts, sustainability value drivers, and success determinants

Consumers online interactions, posts, rating and ranking, reviews of products/attractions/restaurants and so on lead to a massive amount of data that marketers might access to improve the decision-making process, by impacting the competitive and marketing intelligence. The purpose of this paper is to develop understanding of consumers online-generated contents in terms of positive or negative comments to increase marketing intelligence.,The research focuses on the collection of 9,652 tweets referring to three fast fashion retailers of different sizes operating in the UK market, which have been shared among consumers and between consumer and firm, and subsequently evaluated through a sentiment analysis based on machine learning.,Findings provide the comparison and contrast of consumers’ response toward the different retailers, while providing useful guidelines to systematically making sense of consumers’ tweets and enhancing marketing intelligence.,The research provides an effective and systemic approach to accessing the rich data set on consumers’ experiences based the massive number of contents that consumers generate and share online and investigating this massive amount of data to achieve insights able to impact on retailers’ marketing intelligence.,To best of the authors’ knowledge, while other authors tried to identify the effect of positive or negative online comments/posts/reviews, the present study is the first one to show how to systematically detect the positive or negative sentiments of shared tweets for improving the marketing intelligence of fast fashion retailers.

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Making sense of consumers’ tweets: Sentiment outcomes for fast fashion retailers through Big Data analytics

https://research-information.bris.ac.uk/ws/files/216266551/final_brand_perception_of_luxury_hotels.pdf

Branding luxury hotels: Evidence from the analysis of consumers’ “big” visual data on TripAdvisor

Today georeferenced images posted on the social network provide a lot of information about people behaviours and movements Using social media platforms users upload photos, share locations and pos

Machine learning and points of interest: typical tourist Italian cities

The Industry 4.0 revolution is bringing major transformations in the tourism systems design suitable for technologically oriented consumers. Indeed, methods and technologies introduced by Big Data, Automation, Virtual and augmented reality, Robotics and ICT well fit with the Tourism 4.0 paradigm. However, tourism students are not yet trained on techniques, issues and methods related to the Industry 4.0 framework. Hence, relying on a careful examination of the literature on tourism market trends linked to the offer of innovative technological services, we identified conceptual, methodological, technological and practical skills to be developed in an academic curriculum for Tourism Science students. Learning path were focused on: i) processes of data acquisition from social media, ii) data analysis using Machine Learning techniques and iii) data design into significant elements useful to implement communication systems in the tourism field. Results showed that the most of participants achieved a medium-high evaluation for the implementation of the communication systems, applying appropriately techniques and tools learned along the course. Furthermore, the high percentage of students satisfaction registered in relation to the course, revealed that students enjoyed this experience. Outcomes reflects the acquisition and the awareness of those skills that will enable students to be conscious protagonists of their role in tourism 4.0.

Simona Giglio

Papers

Using social media to identify tourism attractiveness in six Italian cities

Making sense of consumers’ tweets: Sentiment outcomes for fast fashion retailers through Big Data analytics

Branding luxury hotels: Evidence from the analysis of consumers’ “big” visual data on TripAdvisor

Machine learning and points of interest: typical tourist Italian cities

Industry 4.0 technologies in tourism education: Nurturing students to think with technology