Exploring the state-of-the-art of halal food research using latent Dirichlet allocation - Abderahman Rejeb; Karim Rejeb; Imen Zrelli (Discover Food)
Abstract The rapid growth of the halal food (HF) industry has created a pressing need for a comprehensive synthesis of the existing body of knowledge. However, there remains a significant gap in the literature regarding the key themes, patterns, and emerging areas in HF research. This study addresses this gap by systematically analyzing the HF literature to identify key themes, patterns, and emerging areas of interest in the HF field. The study employs latent Dirichlet allocation (LDA)-based topic modeling to uncover and map the underlying themes in the HF literature, analyzing 738 publications from Scopus to determine the main topics and trends in HF research. The analysis reveals six main topics in HF research: (1) HF quality, safety assessment, and production methods; (2) HF supply chain management; (3) HF detection and authentication methods; (4) HF and Islamic culture; (5) HF and consumer behavior; and (6) HF and tourism and hospitality. The study identifies an overall increasing trend in HF research over the years, with particular emphasis on HF supply chain management and consumer behavior, while HF and Islamic culture received comparatively lower levels of attention. This study offers a novel and comprehensive analysis of the HF literature using LDA-based topic modeling, highlighting the key themes and patterns in the field. The insights derived from this study hold significant theoretical and practical implications for researchers, policymakers, manufacturers, retailers, and consumers in the rapidly growing HF industry. By identifying the main areas of focus and research gaps, the study serves as a valuable foundation for further research and analysis in the field, ultimately contributing to the ongoing development and evolution of HF research.