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This study aims to explore the constituents of artificial intelligence (AI)-augmented knowledge management (AIKM) capability and its impact on clinical performance (CP) in the health-care sector. It further examines the mediating role of absorptive capacity (Abs Cap) and discusses the implications of these findings for marketing strategies, highlighting how enhanced CP through AIKM can lead to more effective and patient-centered marketing approaches.

This research uses a mixed-method design. A qualitative study through semi-structured interviews was conducted to explore the facets of AIKM. The synthesis of qualitative findings infused with the relevant literature to develop a hypothesized model of AKM, Abs cap and CP metrics (e.g. diagnostic accuracy, patient satisfaction and treatment effectiveness). A survey of health-care professional in India was conducted to assess the proposed model by using structural equation modeling (PLS-SEM).

The results demonstrate a significant positive relationship between AIKM and CP. Moreover, Abs Cap mediates this relationship partially, highlighting its crucial role in translating improved knowledge access and analysis enabled by AI into enhanced clinical outcomes.

The findings suggest that health-care organizations should invest in developing AIKM alongside strengthening Abs cap to maximize the positive impact of AI on CP and ultimately improve patient care. Future research can explore specific AIKM components and Abs cap facets influencing different aspects of CP.

This study represents a pioneering effort to conceptualize AIKM within the health-care context and empirically establish it as a higher-order factor. The inclusion of marketing strategies underscores the potential of AIKM not only in improving clinical outcomes but also in transforming health-care marketing. The mediating role of Abs Cap emphasizes the importance of organizational structures and processes that facilitate the absorption and utilization of knowledge, thereby contributing to both clinical and marketing excellence.

The primary purpose of this paper is to examine the role of perceived trust, information quality, positive word of mouth and societal norms toward real estate purchase intention. The study also examines how pro-environmental self-identity mediates the relationship between positive word of mouth and real estate purchase intent, as well as between societal norms and real estate purchase intention. This research aims to delve into these intricate dynamics through a multidimensional lens.

The research employs existing scholarly works and measurable variables evaluated through a five-point Likert scale, hypothesis testing and mediation analysis to examine the proposed framework. A structured survey comprising six sections was administered, yielding 385 valid responses. The data analysis process included the use of confirmatory factor analysis and structural equation modelling techniques.

The analysis indicates that pro-environmental self-identity has the most significant influence on real estate purchase intention, closely followed by positive word of mouth. Incorporating eco-friendly themes in marketing campaigns significantly boosts purchase intentions. However, perceived trust does not significantly impact purchase intentions. Other factors, such as information quality and societal norms, also play significant roles, underscoring the importance of understanding the complex dynamics shaping consumer decisions in the real estate market.

This research exclusively targets responses from young consumers in specific regions of India. Future studies should aim for a more extensive geographic scope, encompassing a diverse global population for a broader understanding of the subject.

Based on previous literature, this study is the first to identify the elements influencing the inclination to buy environmentally friendly real estate through social commerce.