The advance of digitalization has generated an ever-increasing number of options in the digital sphere. This phenomenon has transformed multiple sectors, including e-commerce and, in particular, the fashion industry. Artificial intelligence (AI) has emerged as a powerful tool that is redefining the online shopping experience. However, there is little research on how AI influences this purchasing process, limiting its full exploitation. This study provides new insight into how artificial intelligence influences online purchase intention in this sector by examining Generation Z consumers’ attitude and purchase intention using the Echo Look AI device. This study involved 210 university students aged between 18 and 25 years old who were surveyed in the cities of Madrid and Barcelona. The results indicate that perceived quality, attitude towards AI and perceived usefulness have a positive influence on purchase intention. Based on these results, theoretical and practical implications are discussed.

The decision-making process (DMP) is essential in organizations and has changed due to multidisciplinary research, greatly influenced by the progress in information technologies and computational science. This work’s objective is analysing the progressive interaction between DMP and information technologies and the consequent breakthroughs in how business is conducted since 1950 to recent times. Therefore, a chronological review of the information-driven DMP evolvement is presented. The major landmarks that defined how technology influenced how information is generated, stored, managed, and used for making better decisions, minimizing the uncertainty and gaining knowledge, are covered. The findings showed that even if current data-driven trends in managerial decision making have led to competitive advantages and business opportunities, there is still a gap between the technological capabilities and the organizational needs. Nowadays, it has been reported that the adoption of technology solutions in many companies is faster than their capacity to adapt at managerial level. Aware of this reality, the “Circumplex Hierarchical Representation of Organization Maturity Assessment” (CHROMA) model has been developed. This tool makes it possible to evaluate whether the management of organizations is making decisions using the available data correctly and optimizing their information systems.

Purpose: This article presents a maturity model for the evaluation of the information-driven decision-making process (DMP) in small and medium enterprises. This model is called “Simplified Holistic Approach to DMP Evaluation (SHADE)”. The SHADE model is based in the “Circumplex Hierarchical Representation of the Organization Maturity Assessment” (CHROMA) framework for characterizing the information-driven DMP in organizationsDesign/methodology/approach: The CHROMA-SHADE provides a competency evaluation methodology regarding the SME’s use of data for making better-informed decisions. This model groups the main factors influencing the information-driven DMP and classifies them into five dimensions: data availability, data quality, data analysis and insights, information use and decision-making. It addresses these dimensions systematically, delivering a framework for positioning the organization from an uninitiated to a completely embedded stage. The assessment consists of interviews based on a standardized open-ended questionnaire performed to key company personnel followed by an analysis of the answers and their scoring performed by an expert evaluator.Findings: The results of its application indicate this model is well adapted to the SMEs resulting useful for identifying strengths and weaknesses, thereby providing insights for prioritizing improvement actions.Originality/value: The CHROMA-SHADE model follows a novel, holistic approach that embraces the complexities inherent in a multiplicity of factors that, at the technological and management level, converge to enable more objective and better-supported decisions to be made through the intelligent use of information

Influencer marketing has emerged as an effective way for brands to connect with consumers through social media influencers. Although this form of marketing has led to increased interest from researchers in recent years, relatively little is known about the content and engagement strategy of influencers and their links to follower behavior. In this digital context, it is worth citing a type of influencer related to literature: bookstagrammers. These are individuals who share their passion for books, review publishing news and encourage the habit of reading. This study analyzes how the content and engagement strategy of bookstagrammers (as measured by number of followers, content volume and posts of interest) is associated with the engagement of the followers of these cultural influencers on Instagram, both independently and interactively. The study analyzes a data set compiled from bookstagrammers by analyzing the content generated by these online influencers in order to test the proposed hypotheses. Our findings show that posts that include photographs of the author or book covers are positively associated with follower engagement on Instagram accounts, while emotional posts expressing feelings are negatively associated with follower engagement. These findings demonstrate that the elements and content strategy of literary influencers contribute to the engagement of followers on Instagram.

This article examines the role of digital communication, social media, and peer influence in Generation Z’s transition from fast fashion to more sustainable consumption practices. Building on sustainability and social influence theories, this study applies a mixed-methods design that combines qualitative content analysis of social media discourse with a quantitative online survey (n = 202). The survey instrument, validated by a panel of experts, measured four dimensions—digital communication, peer influence, sustainable attitudes, and sustainable behaviors—using Likert-type scales with adequate reliability (Cronbach’s α ≥ 0.70). The statistical analyses included descriptive statistics, Pearson correlations, and mean comparison tests (t-test, ANOVA). The results show that digital platforms not only raise awareness but also normalize sustainable choices through peer validation and community engagement. Strong correlations confirm that peer influence mediates the relationship between exposure to sustainability content and the adoption of responsible behaviors, while perceptions of brand sustainability show weaker associations with purchase intention. This study highlights a persistent attitude–behavior gap and identifies opportunities for more effective digital engagement. The findings contribute to the literature on sustainable fashion consumption by clarifying the communicative mechanisms shaping Gen Z’s decisions. Practical implications are offered for brands, policymakers, and educators seeking to foster authentic and inclusive sustainability strategies, particularly in addressing gender differences in sustainable adoption.

Recent studies have demonstrated the value that the Internet and web applications bring to businesses. Among other tools are those that enable the analysis and monitoring of searches, such as Google Trends, which is currently used by the fashion industry to guide experiential practices in a context of augmented reality and/or virtual reality, and even to predict purchasing behaviours through the metaverse. Data from this tool provide insight into fashion consumer search patterns. Understanding and managing this digital tool is an essential factor in rethinking businesses’ marketing strategies. The aim of this study is to analyse online user search behaviour by analysing and monitoring the terms “metaverse” and “fashion” on Google Trends. A quantitative descriptive cross-sectional method was employed. The results show that there is growing consumer interest in both concepts on the Internet, despite the lack of homogeneity in the behaviour of the five Google search tools.