Zericho R. Marak

Conventional approaches to customer segmentation, static and retrospective by nature, fail to adequately capture rapid consumer shifts in dynamic market environments. Drawing from dynamic capabilities theory, this article reconceptualizes segmentation as an adaptive, capability‐driven practice rather than as a passive classification exercise. Using a sequential mixed‐methods approach comprising qualitative insights from industry practitioners and quantitative validation via structural equation modelling, this study affirms and extends the dynamic capabilities of sensing, seizing, and reconfiguring. The findings reveal that customer understanding, market scanning, and data integration capabilities (sensing) drive the capability to process big data, which, in turn, improves data interpretation competency and strengthens agile strategic capability (seizing), as well as enhancing data‐driven positioning effectiveness to support real‐time segmentation reconfiguration (reconfiguring). In contrast, data and information processing overload and organizational inertia showed the hypothesized directional weakening of these capability pathways, though none of the three interaction effects reached statistical significance, which positions both as directionally suggested rather than statistically confirmed constraints on the transition from passive to adaptive segmentation practices. Marketers can thus leverage the actionable insights from this study to implement real‐time segmentation and sustain competitive advantage in dynamic, rapidly evolving markets.

AI has revolutionized breast cancer care. It enhances diagnostic accuracy, improves early detection, and personalizes treatment while reducing unnecessary testing. Thus, it is crucial to examine the incorporation of AI to emphasize its potential benefits for diagnostic precision, screening optimization, and overall patient outcomes within clinical workflows. Utilizing bibliometric analysis, this research identifies significant contributions and landmark studies that have driven advancements in AI applications for breast cancer. This analysis further highlights trending themes and technologies, which are vital for guiding future research initiatives and aligning resource allocation with the most urgent challenges in the field. The research analyses ninety-seven articles concerning AI applications in the detection and treatment of breast cancer, which are indexed in the Web of Science, for the purpose of identifying themes and conducting analysis. The initial section presents a comprehensive overview of research growth, leading authors, key publishers and journals contributing to the literature. Subsequently, an analysis of major studies related to AI in the detection and treatment of breast cancer have been provided. There has been a marked upward trend in research output on AI applications in breast cancer in 2023 following a gradual rise over the past 25 years. Future research directions in AI for breast cancer should emphasize enhancing algorithm accuracy, integrating multi-modal imaging data, and improving real-time analytical capabilities. Additionally, further exploration of AI’s role in personalized treatment plans and patient monitoring could substantially improve clinical outcomes and optimize healthcare resources.

This systematic literature review examines the evolution and current state of green marketing research in South Asian, East Asian, and Southeast Asian countries. Utilizing the PRISMA methodology and TCCM framework, the study analyzes 97 articles published between 2000 and 2025 to map research trends, dominant variables, theoretical underpinnings, and methodological approaches. The findings reveal regional disparities in publication volume, a reliance on Western-centric theories, and methodological limitations such as overuse of convenience sampling. India and China emerge as key contributors, while many Asian countries remain underrepresented. The review identifies frequently studied constructs, including environmental concern, attitude, and green purchase intention, and recommends expanding theoretical diversity and context-specific research. It offers a comprehensive research agenda and practical insights for marketers aiming to foster sustainable consumer behavior across diverse Asian markets.

Purpose. This study investigates the factors influencing consumers’ intentions to purchase organic food products in an emerging economy. It addresses the knowledge gap regarding the slower growth of the organic food market in these regions despite the global trend toward environmental sustainability. Methodology / approach. A survey approach involving 350 participants was used. Structural equation modeling (SEM) with SmartPLS 4 and Artificial Neural Network (ANN) with IBM SPSS 28 were used to analyse the impact of awareness of need, personal norms, environmental concern, and health consciousness on the intention to purchase organic food products. Results. The study found significant positive influences of awareness of need, personal norms, environmental concern, and health consciousness on the intention to purchase organic food products, explaining 63.1 % of the variance. Both the analysis approaches (PLS-SEM & ANN) revealed that, health consciousness, followed by awareness of need, emerged as the most important factor related to the intention to purchase organic food products. The results highlight the importance of awareness and personal values in driving pro-environmental behaviour. Originality / scientific novelty. This research offers essential insights into the determinants of organic food purchase intentions in an emerging economy. It emphasises the significance of awareness and personal values in fostering sustainable consumption behaviour, addressing a less explored area in existing literature. Practical value / implications. The findings have important implications for policymakers and marketers. Strategies focused on consumer education about the benefits of organic food can enhance awareness and appeal. Understanding core psychological needs and beliefs that shape consumer motivations can guide the development of effective marketing strategies. The study highlights the strong environmental consciousness among consumers and their desire to protect the environment.