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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.

While there are several readiness assessments regarding digital transformation (DT) and Industry 4.0 in extant literature, this study aims to contribute to (a) a better understanding of digital readiness in supply chain (SC) aspects and (b) elaborate on differences between small and medium-sized enterprises (SMEs) and large enterprises.

The study is based on 409 companies that participated in the Digital Readiness Check (DRC) in the region of Salzburg (Austria) and Bavaria (Germany) – an online assessment for self-evaluating the digital readiness of companies.

The study's results provide insights for the categories of strategy, employees, initiation of business transactions and SC. These are further differentiated for SMEs and large enterprises.

The study is limited to two regions in Austria and Germany, based on a self-evaluation of companies in a single point of time perspective. For future research, the results of this study should be expanded for different regions. Further, the results could be validated regarding external observations and measuring results at a later point of time.

The DRC may help companies in benchmarking themselves and gaining a better understanding about categories that must be improved, especially regarding SC aspects of DT.

The DRC extends extant literature regarding the differentiation between SMEs and large enterprises as well as focussing on SC aspects of DT.

Industry 4.0 (I 4.0) consists of numerous digital technologies applied in organizations strategically to add value to the customer. Different organizations have varying degrees of technological capability and strategic flexibility. This paper aims to explore the relationship between technological capability and strategic flexibility on successful implementation of I 4.0.

A qualitative study using a grounded theory approach is conducted on 34 senior managers from Europe and North America who have implemented I 4.0 participated in this study through a theoretical sampling frame.

This study finds that technological capability and strategic flexibility have an impact on the successful implementation of I 4.0. The study also finds that different dimensions of technological capability also impact I 4.0. The interactive effect of strategic flexibility and technological capability is also noted. The study also develops a framework for successful implementation of I 4.0.

This study can be used by managers while implementing I 4.0 to devise a strategic roadmap for acquiring technological capability with I 4.0 technologies. Besides, it will help the managers to consider the bidirectional relationship between technological capability and strategic flexibility while formulating I 4.0 strategy for successful implementation of I 4.0 in their organizations.

Previous studies have examined the importance of I 4.0 technologies. However, this study extends the previous works by suggesting how technological capability and strategic flexibility can help in the successful implementation of I 4.0.

This study aims to develop a comprehensive conceptual framework that serves as a foundation for identifying most critical delay risk drivers for Building Information Modelling (BIM)-based construction projects.

A systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify key delay risk drivers in BIM-based construction projects that have significant impact on the performance of delay risk predictive modelling techniques.

The results show that contractor related driver and external related driver are the most important delay driver categories to be considered when developing delay risk predictive models for BIM-based construction projects.

This study contributes to the body of knowledge by filling the gap in lack of a conceptual framework for selecting key delay risk drivers for BIM-based construction projects, which has hampered scientific progress toward development of extremely effective delay risk predictive models for BIM-based construction projects. Furthermore, this study's analyses further confirmed a positive effect of BIM on construction project delay.