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This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on TikTok (Douyin in China), focusing on how these recommendations affect user satisfaction and purchase intention, while also addressing potential privacy concerns. In addition, the research investigates the influence of AI-recommended product presentation, timing and placement, as well as social factors such as key opinion leaders’ (KOLs) influence on consumer decision-making.

Using the expectancy-value theory and the stimulus-organism-response model, this research used a qualitative methodology through interviews with Douyin users to explore their experiences and perceptions of AI-PPRs.

The findings indicate that Douyin’s proactive “push” mechanism of AI-PPRs enhances user engagement by effortlessly integrating product discovery into the entertainment experience. Content-driven AI-PPRs align with user preferences, decrease search time and increase satisfaction and purchase intentions through engaging short videos and live streaming. However, privacy concerns emerge when personalisation is perceived as excessively intrusive, leading to negative emotions and avoidance behaviours. Recommendation timing and cultural context significantly influence receptiveness, with inappropriate timing (e.g. during holidays) causing negative reactions. Technical challenges, such as network issues during live streaming, negatively impact user experience and engagement. Content quality is crucial, and poor or irrelevant content leads to negative perceptions and disengagement. While KOLs face scepticism due to perceived commercialisation, endorsements from trusted figures and authentic influencers are better received. Innovative payment methods, like “Douyin Monthly Payment”, enhance financial flexibility and promote customer loyalty. This study highlights the need to balance personalisation with privacy, emphasising the importance of content quality and authenticity in influencer marketing. For businesses using AI-PPRs, maintaining this balance is essential for preserving trust and sustaining consumer engagement and loyalty.

This study contributes valuable insights to the field by unravelling the intricate dynamics between AI-PPRs, user preferences and social influences. The findings provide practical implications for companies aiming to optimise personalised recommendation algorithms and enhance user engagement, thereby facilitating business growth in the dynamic short video e-commerce market.

The purpose of this paper is to provide managers with suitable strategic KPIs in decision-making processes, which aim to integrate the environmental dimension of sustainability at a business level in manufacturing organisations.

In view of the research proposal addressed, semi-structured interviews were conducted, based on theoretical milestones of the performance management system (PMS), with 48 managers that work in Italian manufacturing firms and specialise in green practices.

The authors developed a novel environmentally performed framework to adequately integrate environmental value drivers at a strategic level.

The resulting issues addressed in this paper, and their integration in the business strategy for managing environmental complexity, allows contributing, firstly, to the existing literature by suggesting the relevant key value drivers that need to be mostly studied from an accounting point of view. In addition, from these results, though their experience managers will have up-to-date key measures that could, in the future, help the integration process between the environmental aspect of the sustainability dimension and the PMS.

The results generate a robust roadmap for future analysis in this research field. Accordingly, the paper engenders a strategic alignment in the green transition process, providing scholars and practitioners with a clear view of the key sustainable drivers, metrics and potential solutions that have not been addressed to date.