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The challenges seafarers face are unique due to the nature of their work. Individuals in this profession face unique stressors such as limited interaction with people, isolation from society, confined workspaces, unpredictable weather conditions and exposure to hazardous situations. Quantitative methods used in studies on seafarers’ well-being fail to capture the individual experiences, emotions and motivations that make up their rich tapestry. The prevailing reliance on close-ended questionnaires is a hindrance to seafarers’ expression of subjective experiences and difficulties. It is essential to prioritize their well-being, both from a humanitarian standpoint and an economic perspective.

For this study, the authors coted qualitative data using open-ended semi-structured questionnaires from 35 (35) merchant navy sailors. The drive of the study was clearly stated to the respondents by the researchers. The study focuses on the emotional detachment of seafarers and follows a two-phase sampling process: criterion sampling and snowball sampling. The sampling methods are chosen in accordance with the purpose of the study.

The in-depth qualitative inquiry and detailed analysis of interview excerpts generated three broad themes that explain the occurrence of emotional detachment among seafarers. The qualitative study advances the knowledge base of the intricate phenomena of mariner’s emotional detachment. The themes illuminate the causes and outcomes of emotional detachment, also necessitating the need for intervention.

This study highlights the issue of seafarers at work, which tends to affect their personal and professional lives. The lived experiences of seafarers help us understand the issue of emotional detachment from a better and more in-depth perspective. This certainly helps companies and policymakers customize their interventions to seafarers’ needs.

The disconnect between producers and consumers is a fundamental issue causing irregularities, inefficiencies and leakages in the agricultural sector, leading to detrimental impacts on all stakeholders, particularly farmers. Despite the potential benefits of Metaverse technology, including enhanced virtual representations of physical reality and more efficient and sustainable crop and livestock management, research on its impact in agriculture remains scarce. This study aims to address this gap by identifying the critical success factors (CSFs) for adopting Metaverse technology in agriculture, thereby paving the way for further exploration and implementation of innovative technologies in the agricultural sector.

The research employed integrated methodology to identify and prioritise critical success criteria for Metaverse adoption in the agricultural sector. By adopting a mixed-method technique, the study identified a total of 15 CSFs through a literature survey and expert consultation, focusing on agricultural and technological professionals and categorising them into three categories, namely “Technological”, “User Experience” and “Intrinsic” using Kappa statistics. Further, the study uses grey systems theory and the Ordinal Priority Approach to prioritise the CSFs based on their weights.

The study identifies 15 CSFs essential for adopting Metaverse technology in the agricultural sector. These factors are categorised into Technological, User Experience-related and Intrinsic. The findings reveal that the most important CSFs for Metaverse adoption include market accessibility, monetisation support and integration with existing systems and processes.

Identifying CSFs is essential for successful implementation as a business strategy, and it requires a collaborative effort from all stakeholders in the agriculture sector. The study identifies and prioritises CSFs for Metaverse adoption in the agricultural sector. Therefore, this study would be helpful to practitioners in Metaverse adoption decision-making through a prioritised list of CSFs in the agricultural sector.

The study contributes to the theory by integrating two established theories to identify critical factors for sustainable agriculture through Metaverse adoption. It enriches existing literature with empirical evidence specific to agriculture, particularly in emerging economies and reveals three key factor categories: technological, user experience-related and intrinsic. These categories provide a foundational lens for exploring the impact, relevance and integration of emerging technologies in the agricultural sector. The findings of this research can help policymakers, farmers and technology providers encourage adopting Metaverse technology in agriculture, ultimately contributing to the development of environment-friendly agriculture practices.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

This study aims to map the conceptual structure and evolution of the recent scientific literature published in marketing journals to identify the areas of interest and potential future research directions.

The 100 most influential marketing academic papers published between 2018 and 2022 were identified and scrutinized through a bibliometric analysis.

The findings further upheld the critical role of emerging technologies such as Blockchain in marketing and identified artificial intelligence and live streaming as emerging trends, reinforcing the importance of data-driven marketing in the discipline.

The data collection included only the 100 most cited documents between 2018 and 2022, and data were limited only to Scopus database and restrained to the Scopus-indexed marketing journals. Moreover, documents were selected based on the number of citations. Nevertheless, the data set may still provide significant insight into the marketing field.

Influential authors, papers and journals identified in this study will facilitate future literature searches and scientific dissemination in the field. This study makes an essential contribution to the marketing literature by identifying hot topics and suggesting future research themes. Also, the important role of emerging technologies and the shift of marketing toward a more data-driven approach will have significant practical implications for marketers.

To the best of the authors’ knowledge, this is the first comprehensive study offering a general overview of the leading trends and researchers in marketing state-of-the-art research.

Human and artificial intelligence has often been examined through competitive and oppositional lenses, which may no longer suffice in modern digital and knowledge-based societies. This paper advocates for a holistic perspective by integrating human and artificial intelligence within the conceptual framework of intellectual capital (IC).

Employing a deductive approach rooted in systems theory, this study reinterprets established dimensions of IC for the era of artificial intelligence.

Drawing inspiration from the Information Variety Model and the 4C Curve Model, both developed within the research framework of the Viable Systems Approach, a conceptual framework is proposed to transcend fragmented perspectives. It aims to provide researchers and practitioners with a comprehensive understanding of human–artificial intelligence relations within the realm of IC.

This paper contributes to the ongoing discourse on the potential evolution of IC in the era of artificial intelligence by presenting a multidisciplinary framework that challenges reductionist perspectives. It underscores the importance of systems thinking in reframing, analyzing and discussing key dimensions of IC in the context of the artificial intelligence era.

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.