Analysis of Muslim Consumer Trust toward AI-Generated Products in Halal Business
DOI:
https://doi.org/10.35335/vv3et798Keywords:
Artificial Intelligence, Muslim Consumer Trust, Halal Business, AI Ethics, Halal AssuranceAbstract
The rapid development of Artificial Intelligence (AI) has significantly transformed modern business practices, including the halal industry. AI technologies such as recommendation systems, chatbot services, automated halal marketing, and AI-generated product information are increasingly integrated into halal business operations to improve efficiency and customer experience. However, the implementation of AI in halal business also raises concerns among Muslim consumers regarding halal authenticity, transparency, ethics, accountability, data privacy, and religious compliance. This study aims to analyze Muslim consumer trust toward AI-generated products and services in halal business and identify the factors influencing trust. The research employs a quantitative approach using a cross-sectional survey design involving 200 Muslim consumers who have interacted with AI-based halal products or services. Data were collected through online questionnaires and analyzed using descriptive statistics and Structural Equation Modeling–Partial Least Squares (SEM-PLS). The findings reveal that Muslim consumers generally show positive attitudes toward AI-generated halal products and services, although trust remains highly dependent on halal assurance, AI transparency, ethical perception, AI reliability, perceived usefulness, and technology familiarity. Among these factors, halal assurance and AI transparency emerged as the strongest determinants of consumer trust. This study contributes to the literature on Islamic business, halal marketing, and AI consumer behavior by integrating technological and religious perspectives into the analysis of consumer trust. Practically, the findings provide important implications for halal businesses, AI developers, and policymakers in designing ethical, transparent, and halal-compliant AI systems to strengthen consumer confidence in the digital halal economy.
References
Amoako, G., Omari, P., Kumi, D. K., Agbemabiase, G. C., & Asamoah, G. (2021). Conceptual framework—artificial intelligence and better entrepreneurial decision-making: the influence of customer preference, industry benchmark, and employee involvement in an emerging market. Journal of Risk and Financial Management, 14(12), 604.
Anam, J., Sany Sanuri, B. M. M., & Ismail, B. L. O. (2018). Conceptualizing the relation between halal logo, perceived product quality and the role of consumer knowledge. Journal of Islamic Marketing, 9(4), 727–746.
Battour, M., Mady, K., Elsotouhy, M., Salaheldeen, M., Elbendary, I., Marie, M., & Elhabony, I. (2021). Artificial intelligence applications in halal tourism to assist Muslim tourist journey. International Conference on Emerging Technologies and Intelligent Systems, 861–872.
Bonne, K., & Verbeke, W. (2008). Muslim consumer trust in halal meat status and control in Belgium. Meat Science, 79(1), 113–123.
Butt, M. M., Khong, K. W., & Alam, M. (2021). Managing corporate brand behavioural integrity: a case of alleged violation of Halal certification. Journal of Islamic Marketing, 12(6), 1219–1238.
Egbuhuzor, N. S., Ajayi, A. J., Akhigbe, E. E., Agbede, O. O., Ewim, C. P.-M., & Ajiga, D. I. (2021). Cloud-based CRM systems: Revolutionizing customer engagement in the financial sector with artificial intelligence. International Journal of Science and Research Archive, 3(1), 215–234.
Ha, H., & Perks, H. (2005). Effects of consumer perceptions of brand experience on the web: Brand familiarity, satisfaction and brand trust. Journal of Consumer Behaviour: An International Research Review, 4(6), 438–452.
Héder, M. (2020). A criticism of AI ethics guidelines. Információs Társadalom: Társadalomtudományi Folyóirat, 20(4), 57–73.
Kayed, R. (2008). Managing Risk of Islamic Equity Investments: Initiatives and Strategies. ISLAMIC CAPITAL MARKETS.
Khan, M. M., Asad, H., & Mehboob, I. (2017). Investigating the consumer behavior for halal endorsed products: Case of an emerging Muslim market. Journal of Islamic Marketing, 8(4), 625–641.
Latifah, L. (2020). Presentation: The Influence of Demographic, Socio-Economic and Environmental on the Preference and Behavior of Middle Class Muslims in Forming the Potential of Halal Hospital (Research in Middle Class Muslim Surabaya).
Leatham, K. R. (2012). Problems identifying independent and dependent variables. School Science and Mathematics, 112(6), 349–358.
Li, J., & Huang, J.-S. (2020). Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society, 63, 101410.
Lipowski, M., & Angowski, M. (2016). Gender and consumer behaviour in distribution channels of services. International Journal of Synergy and Research, 5.
Mohammed, A. A., Akash, T. R., Zubair, K. M., & Khan, A. (2020). AI-driven Automation of Business rules: Implications on both Analysis and Design Processes. Journal of Computer Science and Technology Studies, 2(2), 53–74.
Mohsin Butt, M., & Aftab, M. (2013). Incorporating attitude towards Halal banking in an integrated service quality, satisfaction, trust and loyalty model in online Islamic banking context. International Journal of Bank Marketing, 31(1), 6–23.
Moises Jr, C. (2020). Online data collection as adaptation in conducting quantitative and qualitative research during the COVID-19 pandemic. European Journal of Education Studies, 7(11).
Nienhaus, V. (2021). Digital Transformation of the World Economy by AI: Some Moral, Ethical and Sharīʿah Concerns. Bait Al-Mashura Journal, 16.
Olan, F., Suklan, J., Arakpogun, E. O., & Robson, A. (2021). Advancing consumer behavior: The role of artificial intelligence technologies and knowledge sharing. IEEE Transactions on Engineering Management, 71, 13227–13239.
Olsen, C., & St George, D. M. M. (2004). Cross-sectional study design and data analysis. College Entrance Examination Board, 26(03), 2006.
Park, H., & Blenkinsopp, J. (2017). Transparency is in the eye of the beholder: the effects of identity and negative perceptions on ratings of transparency via surveys. International Review of Administrative Sciences, 83(1_suppl), 177–194.
Rejeb, A., Rejeb, K., & Zailani, S. (2021). Are halal food supply chains sustainable: a review and bibliometric analysis. Journal of Foodservice Business Research, 24(5), 554–595.
Sheard, J. (2018). Quantitative data analysis. Research Methods: Information, Systems, and Contexts, 429–452.
Shin, D. (2021). The effects of explainability and causability on perception, trust, and acceptance: Implications for explainable AI. International Journal of Human-Computer Studies, 146, 102551.
Solaiman, I., Brundage, M., Clark, J., Askell, A., Herbert-Voss, A., Wu, J., Radford, A., Krueger, G., Kim, J. W., & Kreps, S. (2019). Release strategies and the social impacts of language models. ArXiv Preprint ArXiv:1908.09203.
Subeh, I. (2020). BLOCKCHAIN AS A TECHNOLOGICAL IMAGINARY: MEDIA FRAMING AND THE VIEWS OF BLOCKCHAIN PROFESSIONALS IN THE ARAB WORLD.
Tolonen, H., Laatikainen, T., Helakorpi, S., Talala, K., Martelin, T., & Prättälä, R. (2010). Marital status, educational level and household income explain part of the excess mortality of survey non-respondents. European Journal of Epidemiology, 25(2), 69–76.
Yang, M.-H., Lin, B., Chandlrees, N., & Chao, H.-Y. (2009). The effect of perceived ethical performance of shopping websites on consumer trust. Journal of Computer Information Systems, 50(1), 15–24.
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