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The purpose of this study is to comprehensively examine the ethical implications surrounding generative artificial intelligence (AI).

Leveraging a novel methodological approach, the study curates a corpus of 364 documents from Scopus spanning 2022 to 2024. Using the term frequency-inverse document frequency (TF-IDF) and structural topic modeling (STM), it quantitatively dissects the thematic essence of the ethical discourse in generative AI across diverse domains, including education, healthcare, businesses and scientific research.

The results reveal a diverse range of ethical concerns across various sectors impacted by generative AI. In academia, the primary focus is on issues of authenticity and intellectual property, highlighting the challenges of AI-generated content in maintaining academic integrity. In the healthcare sector, the emphasis shifts to the ethical implications of AI in medical decision-making and patient privacy, reflecting concerns about the reliability and security of AI-generated medical advice. The study also uncovers significant ethical discussions in educational and financial settings, demonstrating the broad impact of generative AI on societal and professional practices.

This study provides a foundation for crafting targeted ethical guidelines and regulations for generative AI, informed by a systematic analysis using STM. It highlights the need for dynamic governance and continual monitoring of AI’s evolving ethical landscape, offering a model for future research and policymaking in diverse fields.

The study introduces a unique methodological combination of TF-IDF and STM to analyze a large academic corpus, offering new insights into the ethical implications of generative AI across multiple domains.

Drawing on the personalization–privacy paradox and guided by means–end analysis, this study explores how consumers balance their concerns for privacy and the benefits of smart home device personalization and the role that trust plays in the process. More specifically, this study aims to investigate how perceptions of smart device personalization and privacy concerns are shaped by consumers’ experiences and the role of trust in the deliberation process.

In-depth interviews were conducted across diverse demographic groups of smart device users to shed light on the balancing act between personalization and privacy.

The study found that product experience, ownership type, perceived value of convenience and control and quality of life via “smart things” are key motivators for product usage. The benefits of tailored recommendations and high relevance are balanced against the risks of echo chamber effects and loss of control. The results also show the role of active involvement in the privacy calculus and trust level. The study points to the significance of an ecosystem-based service/business model in gaining consumer confidence when they balance between personalization and privacy.

Although many studies have explored trust, privacy concerns and personalization in an artificial intelligence (AI)-related context, few have addressed trust in the context of both smart devices and the personalization–privacy paradox. As such, this study adds to the existing literature by incorporating the concept of trust and addressing both privacy concerns and personalization in the AI context.

Organic food consumption has received great attention due to the increase in consumer environmental and health concerns. This study intends to analyse how customers' green purchasing intentions for organic food are affected by internal factors of attitude and health consciousness and external factors of social norms and environmental concern, as well as how green trust operates as a moderator between green purchase intention and actual purchase.

A quantitative research methodology was employed in this study. The data (n = 323) were gathered via a self-administered questionnaire. The respondents, who were current purchasers of organic food, were chosen through a purposive sampling technique. Data were analysed using exploratory factor analysis and structural equation modelling with the aid of IBM SPSS 25.0 and AMOS 25.

The results reveal that customers' green purchase intention for organic products is positively influenced by internal factors (attitude and health consciousness) and external factors (social norms and environmental concern). This study also shows the moderating effect of green trust on intention and action, demonstrating the necessity of building green trust among customers to diminish green purchasing inconsistency.

The study's results have ramifications for producers of organic goods, merchants and market oversight organizations. Establishing a viable strategy while considering customers' concerns about health and the environment is necessary. The formulated strategy must target specific customer niches, therefore strengthening customers' trust in and understanding of organic food items, which will in turn diminish green purchasing inconsistency in the organic industry.

This study contributes to the existing literature by extending the Theory of Planned Behaviour model to organic food consumption and by visualizing how various factors (internal, external and green trust) affect a consumer's inclination to make organic food purchases. The authors added to the empirical evidence that green trust plays a crucial role in stimulating green buying intentions into behaviour and ultimately diminishing green purchasing inconsistency.