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The study seeks to understand the possible opportunities that Industry 5.0 might offer for various aspects of inclusive sustainability. The study aims to discuss existing perspectives on the classification of Industry 5.0 technologies and their underlying role in materializing the sustainability values of this agenda.

The study systematically reviewed Industry 5.0 literature based on the PRISMA protocol. The study further employed a detailed content-centric review of eligible documents and conducted evidence mapping to fulfill the research objectives.

The advancement of Industry 5.0 is currently underway, with noteworthy initial contributions enriching its knowledge base. Although a unanimous definition remains lacking, diverse viewpoints emerge concerning the recognition of fundamental technologies and the potential for yielding sustainable outcomes. The expected contribution of Industry 5.0 to sustainability varies significantly depending on the context and the nature of underlying technologies.

Industry 5.0 holds the potential for advancing sustainability at both the firm and supply chain levels. It is envisioned to contribute proportionately to the three sustainability dimensions. However, the current discourse primarily dwells in theoretical and conceptual domains, lacking empirical exploration of its practical implications.

This study comprehensively explores diverse perspectives on Industry 5.0 technologies and their potential contributions to economic, environmental and social sustainability. Despite its promise, the practical evidence supporting the effectiveness of Industry 5.0 remains limited. Certain conditions are necessary to realize the benefits of Industry 5.0 fully, yet the mechanisms behind these conditions require further investigation. In this regard, the study suggests several potential areas for future research.

This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.

The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.

Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.

While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.

This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.

Understanding how to retain users of augmented reality (AR) shopping apps and to motivate them to purchase is vital to the success of AR apps. This study assessed the chain effect of AR attributes on purchase intention and reuse intention through cognitive and affective factors.

The data were collected from Thai users of the IKEA Place app using an online survey. A link to the survey was posted on Thai furniture groups on social media platforms. The 439 responses were analysed using the partial least squares (PLS) approach.

The results revealed that all four AR attributes, namely interactivity, vividness, novelty and spatial presence, significantly influence perceived enjoyment, perceived diagnosticity and perceived value. Brand attitude, as a key driver of purchase intention, is influenced by perceived value. Attitude towards the app significantly affects reuse intention and is affected by affective and cognitive factors.

The findings enable shopping app designers and marketers to successfully promote the brand, retain users and boost sales by effectively incorporating AR.

The study extends the literature on the impacts of AR apps on customer behaviours by including affective factors in addition to cognitive factors to explain why AR attributes influence customer attitudes and behaviours. Furthermore, the study demonstrates the serial causal paths from AR attributes to customer behaviours.

Customers increasingly use food delivery applications (FDAs) to place orders. Despite the popularity of FDAs, limited research has investigated the drivers of the continuance intention to use FDAs. This study aims to uncover the drivers of the continuance intention to use FDAs by integrating the “technology continuance theory” (TCT) with perceived task-technology fit, perceived value and perceived food safety.

Data were collected from 398 individuals in Thailand and evaluated using “partial least squares” (PLS) and “fuzzy-set qualitative comparative analysis” (fsQCA).

The PLS results supported the significance of all direct relationships, except the effects of perceived ease of use on attitude and perceived usefulness on continuance intention. Accordingly, perceived food safety positively moderated the impact of perceived ease of use on attitudes. The fsQCA uncovered seven solutions with various combinations of factors that predicted high continuance intention.

This study enables food delivery apps to develop effective strategies for retaining users and sustaining financial performance.

This research contributes to the literature by investigating the factors underlying the continuous use of FDAs with a new PLS-fsQCA technique and applying TCT in a new technological context, FDAs and enriching it by adding three variables: perceived task-technology fit, perceived value and perceived food safety.

This study aims to undertake a comprehensive analysis of innovation models, tracing their evolution from Innovation 1.0 to Innovation 4.0 and introducing the concept of Innovation 5.0. It explores the intersection between innovation models and the principles of sustainability, resilience and human-centeredness, providing insights into their implications for Industry 5.0, and their potential to foster a resilient ecosystem amidst challenges and multiple crisis.

To achieve this objective, the authors used a systematic literature review approach, considering academic articles on Innovation 4.0, Industry 5.0 (specifically in the context of innovation) and helix models of innovation. The authors conducted thematic analysis and content analysis, followed by keyword co-occurrence analysis, enabling us to systematically synthesize and interpret the relevant literature.

The results conclude that Innovation 5.0 is a new paradigm for innovation that fosters broader societal engagement, and emphasizes sustainability, resilience and human-centeredness. Innovation 5.0 is evolving, but it has the potential to transform the way we produce, consume and live. Using insights from the sextuple helix model, this research leverages media and ICT as sixth helix vital role of knowledge sharing, digital transformation, innovation ecosystem and next industrial revolution in this process.

This study contributes to the ongoing discourse on exploring Innovation 5.0 through the sextuple helix model, offering a fresh perspective on innovation models and their collaborative potential. Its contribution lies in providing practical insights into the transition to Innovation 5.0, emphasizing the need for sustainability, regulatory support and awareness while also offering clear recommendations for future research.