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This paper aims to examine existing literature on halal food consumption from the perspective of consumer behaviour research. It identifies progress, current state and gaps and provides direction for future research to advance the field.

This paper reviewed papers from 2007 to 2023 using Scopus and WOS databases. The review used the Theories–Context–Characteristics–Methods (TCCM) framework and followed the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) protocol.

The review summarises the methods, theory and approaches used in the topic and presents key findings and a proposed framework. It can guide future researchers in developing their models, making it a valuable starting point for future research. Despite the existence of SRL in halal food to the best of the authors’ knowledge, this work is the first review that proposes a model for halal food in consumer behaviour.

This review provides a twofold contribution. First, this review's theoretical contribution is advancing consumer behaviour literature on halal food. Second, this work's practical contribution is to enrich practitioners' understanding of the antecedents of consumer behaviour regarding halal food. This is the first review proposing a consumer behaviour model for Halal food. It makes a theoretical contribution to understanding consumer behaviour on Halal food and provides practical insights for practitioners.

The purpose of this study is to examine the applicability of the technology acceptance model (TAM) in libraries considering the advanced technologies and users’ behaviour.

The research uses a critical reflective approach to review and synthesize a body of recent academic literature on the use of TAM in libraries. The review included assessing TAM’s historical evolution, its limitations and how it could be improved.

The findings indicated that, although TAM can be viewed as an appropriate theoretical model to explain the users’ intention towards technology acceptance, it is limited in explaining both the users’ attitude towards advanced technology and their behaviour in advanced library settings.

To enhance the practicality of TAM in libraries, several recommendations for strategic advancements have been proposed such as contextualizing TAM to libraries, exploring AI-driven adoption, integrating library-specific constructs, understanding cultural differences and using holistic research approaches.

The findings contribute to a deeper understanding of technology adoption in libraries and to the future possibilities of TAM.

The main focus is to provide a non-similar solution for the magnetohydrodynamic (MHD) flow of Casson fluid over a curved stretching surface through the novel technique of the artificial intelligence (AI)-based Lavenberg–Marquardt scheme of an artificial neural network (ANN). The effects of joule heating, viscous dissipation and non-linear thermal radiation are discussed in relation to the thermal behavior of Casson fluid.

The non-linear coupled boundary layer equations are transformed into a non-linear dimensionless Partial Differential Equation (PDE) by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ordinary differential equations (ODEs). The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.

The results indicate that the non-linear radiation parameter increases the fluid temperature. The Casson parameter reduces the fluid velocity as well as the temperature. The mean squared error (MSE), regression plot, error histogram, error analysis of skin friction, and local Nusselt number are presented. Furthermore, the regression values of skin friction and local Nusselt number are obtained as 0.99993 and 0.99997, respectively. The ANN predicted values of skin friction and the local Nusselt number show stability and convergence with high accuracy.

AI-based ANNs have not been applied to non-similar solutions of curved stretching surfaces with Casson fluid model, with viscous dissipation. Moreover, the authors of this study employed Levenberg–Marquardt supervised learning to investigate the non-similar solution of the MHD Casson fluid model over a curved stretching surface with non-linear thermal radiation and joule heating. The governing boundary layer equations are transformed into a non-linear, dimensionless PDE by using a non-similar transformation. The local non-similar technique is utilized to truncate the non-similar dimensionless system up to 2nd order, which is treated as coupled ODEs. The coupled system of ODEs is solved numerically via bvp4c. The data sets are constructed numerically and then implemented by the ANN.