This study employs Identity Regulation Theory (IRT) to investigate how identity-related psychological tensions, such as identity incongruence and dissonance, influence the discontinuation intentions of social media users. Using a cross-sectional survey of 294 active users via Prolific Academic, structural equation modeling (PLS-SEM) was employed to analyze the relationships among these tensions, platform fatigue, and discontinuation. Results show neither tension directly affects discontinuation, but both influence it through platform fatigue. This offers a new perspective on the psychological costs of social media, with fatigue serving as a key mediator in transforming identity tension into discontinuation intent. The paper adds to IRT research and helps firms understand why users leave social media.

The application of Artificial Intelligence (AI)-enabled technologies into the retail environment has led to the emergence of the Marketing 4.0 paradigm, which integrates customer digital and physical touch-points to deliver value. The study used sociomateriality as a theoretical lens to examine how AI-driven marketing practices were enacted, negotiated, and established in retail organizations through human-material entanglements. The crowdsourcing platform Prolific Academic was used to collect data from retail professionals through open-ended essays. Data were analyzed using Gioia's methodology, which led to the identification of five dimensions—sociomaterial entanglement, material agency, situated practices, temporal emergence, and sociomaterial identity—which aligned with sociomateriality theory, encouraging the adoption of Marketing 4.0 in the retail context. The study developed a holistic framework to visualize the relationships that emerged from the participants' responses, addressing the criticalities of the Marketing 4.0 ecosystem.

Generative artificial intelligence is playing a significant role in the transformation of digital ecosystems by reinventing the processes of content generation, process automation, product innovation and customer experience. At the same time that these technologies are becoming more integrated into routine operations, the focus has shifted to the ethical and environmental consequences associated with their widespread application. An investigation of the operational sustainability associated with the generative artificial intelligence systems would be crucial, as it would provide information about how these systems match ideals such as efficiency, circularity and environmental responsibility. We explore how users understand and engage with sustainability principles, specifically lean, circular and green operational frameworks within generative artificial intelligence environments. We collect user reviews of 72 recently launched generative AI platforms from 2022 to 2024 and utilise advanced machine learning methods, including Word2Vec modelling, sentiment and regression analysis, to reveal how text datasets reflect customer perceptions. We find that the lean theme is the most prominent feature of operational sustainability, with the highest sentiment score, followed by the green and circular themes. Our findings show that there is a growing respect among the general public for artificial intelligence systems that exhibit responsible and efficient design.

Purpose – This study utilizes intellectual capital theory (ICT) to examine the impact of intellectual agility, digital creativity, platform readiness, algorithmic autonomy support, networking competence and emotional congruence on the social media reuse likelihood of employees. This study also explores the moderating role of platform literacy between intellectual capital dimensions and social media reuse likelihood. Design/methodology/approach – This study employed a cross-sectional, quantitative research design by collecting data from 300 employees working across diverse industries. Covariance-based structured equation modelling is used to analyse the data and test the hypotheses. Findings – The findings demonstrate that intellectual agility, digital creativity, platform readiness and algorithmic autonomy significantly shape the social media reuse likelihood of employees. The results also established the moderating role of platform literacy between digital creativity, networking competence and social media reuse likelihood. Originality/value – This study offers a novel framework grounded in intellectual capital theory by integrating dimensions of human capital, structural capital, relational capital and platform literacy to predict the social media reuse likelihood of employees in technology-centred workplaces.