The major aim of the study is to review existing literature, conceptualize and map various future research avenues in line with integrating Artificial Intelligence (AI), Machine Learning (ML) and marketing applications. It employs bibliometric analysis, network analysis and theories, contexts, characteristics, and methodologies (TCCM) framework. Similar techniques were applied in social research studies to study and comprehensively report the existing research structure, gaps and probable studies to bridge them up. The sample data in this analysis collected from 2001 to 2025 and consists of 439 publications selected as per the criteria and used for further analysis, demonstrates the recency of research in AI, and ML in marketing applications. The results show an exponential growth in this domain and collaboration among authors throughout the world. It offers important social, practical and theoretical contributions to the evolving literature on AI, and ML in marketing applications. Originally, the study unpacked innovative development of new frameworks, impact assessment, emerging trends, identification of challenges and opportunities, cross disciplinary insights with significant advancement of effective professional practice and impactful theory development in line with AI, and ML in marketing applications.
PurposeThis study aims to examine the direct influence of activity-based costing (ABC) methods, innovation, information technology and service quality on competitive advantage in the small and medium-sized enterprises' (SMEs') manufacturing firms.Design/methodology/approachThe authors use a cross-sectional survey of manufacturing SMEs in Yogyakarta, Indonesian. Purposive sampling was used to identify eligible firms, and non-probability sampling was used to recruit managers and production employees as respondents. After a data screening, 432 valid questionnaires were analyzed. Competitive advantage, ABC, innovation, IT and service quality were measured using established multi-item scales, and the data were analyzed using multiple linear regressions.FindingsContrary to dominant expectations in the literature, the authors do not find statistically significant positive relationships between ABC, innovation or IT and competitive advantage. Their regression coefficients are small and not significantly different from zero. By contrast, service quality displays a positive and statistically significant association with competitive advantage and explains a substantial share of the variance in the dependent variable.Practical implicationsFor manufacturers operating in resource-constrained environments, investments in ABC, innovation and IT do not automatically yield competitive returns. Managers should prioritize strengthening service-quality capabilities such as reliability, responsiveness and assurance to customers before or alongside more complex cost-management and technology initiatives. Careful alignment between ABC/IT projects and the firm's strategic priorities and implementation capacity is essential.Originality/valueThis study offers new evidence that, contrary to much of the literature, activity-based costing, innovation, and information technology do not necessarily enhance competitive advantage in manufacturing SMEs. Instead, it identifies service quality as the primary driver, providing a more context-specific understanding of competitive advantage in resource-constrained environments.
The purpose of this study is to explore why and how sustainable consumption government policy influencers and message credibility directly impact Gen Z’s social media behavioural engagement in emerging markets. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was applied in the current study to provide a review of sustainable consumption. The PRISMA results indicate a probable, testable relationship between sustainable consumption government policy influencers and message credibility, and Gen Z’s social media behavioural engagement in emerging markets, as outlined in a designed conceptual model. The study adds to the theoretical literature development by extending knowledge on the proposed theorised conceptual modelling framework due to the paucity of research that has directly applied the same model to measure the impact of government policy influencers, message credibility, and Gen Z’s sustainable consumption behaviour in emerging markets. This study contributes to the conceptual development of theoretical and practical government policy directions. The conceptual modelling framework developed can be tested in future studies to establish its validity and reliability using alternative methodologies.
Non-Kekule benzenoid structures are molecular systems that cannot be represented by classical Kekule resonance forms with alternating single and double bonds. These compounds often possess unpaired electrons and exhibit distinct electronic characteristics, including diradical and polyradical behavior. In this study, we analyze the structural and topological properties of selected non-Kekule benzenoid systems by computing various molecular descriptors, including the Atom-Bond Connectivity (ABC) index, Geometric-Arithmetic (GA) index, Randi & cacute; index, First and Second Zagreb indices, Hyper Zagreb index and the Forgotten index. These topological indices offer valuable insights into the connectivity and branching patterns of the molecules, contributing to a deeper understanding of their structural complexity. The results may serve as a foundation for future investigations into the potential applications of these systems in fields such as materials science and molecular design.
The trade-off between mixing efficiency, energy consumption, and low maintenance costs presents a compelling rea-son to further explore energy-free and environmentally friendly hydraulic mixing. This research focused on designing a low-complexity static mixer with fixed components that achieves high efficiency while minimizing pressure drop and kinetic energy usage. The innovative mixer developed in this study adopted Tesla's micromixer structure, featur-ing a diameter of 170 mm and a height of 600 mm, making it an appropriate size for water treatment applications. To validate the effectiveness of this size Tesla-style mixer, computational fluid dynamics (CFD) were utilized to model the mixing currents created by vortices. The results indicated a promising mixing efficiency between coagulants and contaminants. Additionally, the study examined two optimized designs for the innovative mixer: one with sharp edges for the internal channels and another with rounded edges. To ensure accuracy in the analysis, the Realizable K-epsilon model was selected, known for its effectiveness in simulating high-intensity disturbances and complex flow con-ditions similar to those in this study. The sharp-edged design showed superior performance. Encouraging additional adjustments by increasing the number of mixing stages for the same size of the mixer. These enhancements improved mixing efficiency, as indicated by the pressure drop parameters and mixing VOF ratios for water and coagulants.
