Artificial Intelligence in Marketing for Halal Supply Chain Management: Leveraging Technology for Strategic Growth in Malaysia

Artificial Intelligence in Marketing for Halal Supply Chain Management: Leveraging Technology for Strategic Growth in Malaysia

Afizan Amer¹, Irwan Ibrahim²

¹Senior Lecturer, Department of Marketing & Management, Faculty of Business and Management, university Technology MARA, Rembau, Negeri Sembilan, Malaysia.

²Associate Fellow, Malaysia Institute of Transport, University Teknologi MARA, Malaysia.

^1,2Department of Technology and Supply Chain Management Studies, Faculty of Business and Management, UiTM Puncak Alam, Selangor, Malaysia.

*Corresponding author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.9010253

Received: 14 January 2025; Accepted: 17 January 2025; Published: 17 February 2025

ABSTRACT

In recent times many sectors have been making use of various Artificial Intelligence (AI) and it has changed the landscape of marketing, enabling companies to provide better customer satisfaction than ever before, improve processes and gain wider market reach. The Halal supply chain in the country is still in an early stage but the advent of AI driven marketing can have a dynamic impact on the marketing, promoting, and delivering of Halal products. This research highlights the adoption of the artificial intelligence in marketing strategies in Halal supply chains focusing on how AI can facilitate businesses to acquire a competitive advantage in the global Halal industry. The paper highlights its importance in increasing consumer engagement, improving product traceability, personalising customer experiences, and building brand loyalty by means of a literature review, case studies and empirical study. This study also identifies challenges and opportunities in applying AI in the marketing aspect of Halal supply chain in Malaysia.

Keywords: Artificial Intelligence, Halal Supply Chain, Consumer Engagement, Brand Loyalty, AI-driven Marketing.

INTRODUCTION

In recent years, Halal products have gained tremendous popularity around the world, with Malaysia playing a significant role in the Halal supply chain. The Halal industry in Malaysia has grown consistently (Ibrahim et al., 2024), positioning the country as an important player in global Halal product’s market. This growth is driven by a growing population of Muslim consumers and an increased awareness of Halal standards among non-Muslim communities. Halal global market is poised to surpass USD 3 trillion by the year 2025, with the food and beverage, cosmetic, and pharmaceuticals sector accounting for the largest share (Sarbani et al., 2024 & Hassan et al., 2020). With its strategic efforts in developing the Halal sector in terms of regulatory frameworks, innovation and infrastructure (Goh et al., 2021), the country, which is known both for being a leader in Halal certification, stands to benefit from this growth.

The use of Artificial Intelligence (AI) in marketing is an emerging trend that could change the way Halal businesses manage their supply chains and customer engagement. It serves as a core tool for elevating business functions by leveraging advanced technologies such as machine learning, natural language processing, predictive analytics, etc. It is these technologies that enable organizations to manage large volumes of data, simplify the decision-making process, and anticipate market direction with extraordinary accuracy (Idris et al., 2024 & Wamba et al., 2017). The incorporation of AI into marketing has significant potential for customer relationship management, product personalisation, and demand forecasting in the Halal supply chain. Real-time analysis of consumer behaviour and preferences helps direct market implementation in a way that addresses not just consumer needs for Halal products but also their ethical and religious values (Senathirajah, 2024 & Nguyen et al., 2021).

Moreover, AI can significantly improve supply chain efficiency of organisations by automating every important process such as inventory management, quality control, and supplier assessment that ensure certification standards are being maintained (Ali et al., 2020). Leveraging machine learning algorithms, organisations can predict future shifting consumer demand for Halal products, optimise product placement decisions, and adjust product offerings accordingly to ensure that they meet the quality standards inherent to Halal products whilst also catering to the needs of a diverse and dynamic market (Osman et al., 2024 & Grewal et al., 2019).

But even though the benefits of AI in marketing are obvious, the integration of AI in the Halal supply chain has some challenges. The collision between advanced technology and spiritual principles gives rise to unique ethical and regulatory problems. Ensuring that AI systems are aligned with Islamic principles and comply with Halal certification standards is one of the key challenges of deploying AI for Halal supply chains. These systems must maintain transparency and avoid actions that could inadvertently compromise the Halal status of products (Toloie et al., 2024 & Ahmad et al., 2021). Moreover, given that it also involves the handling of consumer information, such practices should be aligned with Islamic principles that advocates for privacy and protection of personal data (Kshetri, 2018). These initial costs of using AI technologies, in particular, will act as a significant entry barrier for small and medium enterprises within the Halal industry of Malaysia (Zhou et al., 2022).

The purpose of this paper is to explore the opportunities provided by AI in improving marketing of Halal supply chains in Malaysia as an avenue for businesses to embrace new technologies while remaining compliant with Islamic guidelines. This article will go on to discuss specific applications of artificial intelligence in this context, such as customer segmentation and AI-driven product recommendation systems and demand forecasting. This article will showcase the major benefits of adopting AI, including improved operational efficiency, enhanced consumer engagement, and increased profitability. In the end, this will guide the challenges faced by the industry in the adoption of AI at the operational level while focusing on the regulatory compliances, ethical challenges and technological readiness of the Halal industry in the region. This research provides a strategic insight for enterprises interested in adopting AI as a means of enhancing growth, innovation, and competitiveness in the Halal supply chain industry.

LITERATURE REVIEW

The Role of AI in Supply Chain Management:

The use of Artificial Intelligence (AI) has rapidly become an integral part of modern-day Supply Chain Management (SCM), with capabilities ranging from demand forecasting and inventory management to logistics optimisation. Making use of machine learning, deep learning, predictive analytics, and other technologies, huge volumes of data are analysed, enabling companies to better predict demand and optimize their supply chain use (Choi et al., 2020). For instance, artificial intelligence algorithms can analyze previous data to foresee alterations in consumer behaviour, which provides a more accurate estimate of trends in future demand. This allows organizations to adequately manage stock levels, avoiding overstocking and stockouts (Wamba et al., 2017).

Artificial intelligence also offers potential additional benefits to Halal supply chains, as it can enable systematic verification and validation of the Halal status of raw materials, production stages, and distribution routes, which have a key role in ensuring compliance with Halal (Zhou et al., 2022). AI applications can monitor all steps of the supply chain to remain consistent with Halal certification measures. AI allows to improve the selection of suppliers of Halal products and services, therewith increasing cost-effectiveness (Ali et al., 2020). Moreover, the use of AI in the field of real time customer analytics is increasing as well, allowing business to collect and analyze data on consumer behaviour. It enables the generation of targeted marketing campaigns, customer segmentation, and delivery of personalized content (Kshetri, 2018). Customisation in this intensity enhances the customer experience immediately as well as the effectiveness of promotional campaigns by adapting communications to specific needs and interests.

Halal Supply Chain Management (HSCM) and Marketing

Halal supply chain management (HSCM) is defined as the processes associated with the production, processing, distribution, storage, and consumption of halal products, based on Islamic laws and regulations. There are also prohibitions of certain products or ingredients, such as pork and alcohol (Al-Qudah et al., 2020). At every stage of the supply chain, the Halal industry must be stringently monitored to ensure that the goods comply with the religious obligations of Muslim consumers. Halal products administration means following the Islamic guidelines in addition to strong marketing methods that establish consumer trust by being direct and real (Hassan et al., 2020). In this case, to market Halal products you must make sure that the supply chain is Halal-wise adhered to the principles of Sharia law. Thus, businesses must develop robust traceability systems and convey certification effectively to consumers.

Artificial Intelligence plays a crucial role in the optimization of HSCM marketing strategies. Companies that are utilizing advanced AI systems such as chatbots, targeted advertising, and automated content distribution systems can meaningfully engage with their clientele according to Halal specifications. As one example, AI-powered advertising solutions can instantly adjust digital advertisements and marketing content to account for consumer perception and cultural context, providing the right message at the right time in the right culture (Ladhari & Souiden, 2015). In the field of Halal marketing, this uniqueness is even more important as consumers look for Halal products that align their preferences with their religious and ethical standards.

One more, the power of AI to simplify activities such as customer segmentation and lead generation allows for the better handling of large quantities of customer data, ensuring that marketing efforts reach the right audience while falling within Halal certification criteria (Nguyen et al., 2021). For instance, AI can analyse customer interactions, providing companies with useful insights regarding potential consumer behaviour, resulting in advantage at the market with pre-emptive marketing strategies that correlate with the unique nature of Halal consumer.

Importance of AI in Malaysia’s Halal Segment:

Despite the fact that Malaysia’s Halal industry had shown significant growth in the past few years, there are plenty of operational and strategic opportunities brought by the use of AI technologies. From an operational aspect, streamlining many labour-intensive processes in the Halal supply chain and with it, various tasks such as inventory management, supplier auditing, and product tracking can be optimized at a significant reduction in its cost and increased efficiency (Ali et al., 2020). For instance, applying predictive analytics helps businesses forecast demand more accurately, reducing waste and accelerating inventory turnover. In sectors like food production, where shelf life and stock rotation greatly matter (Choi et al., 2020), that is incredibly important.

Proper utilization of AI could provide immense opportunities for Halal businesses in Malaysia to thrive in the domestic and international landscape. Artificial intelligence powered marketing systems can help companies better understand market dynamics and consumer needs, as companies can better align their offerings with those of consumers. With the world rapidly transforming, AI-supported insights enable companies in Malaysia’s Halal industry to identify new market trends and adapt their marketing strategies accordingly. In addition, artificial intelligence could help companies expand into niche Halal markets by identifying underserved market segments and tailoring products to meet individual needs in these markets (Zhou et al., 2022).

In addition, the government has launched various programs to increase the growth of the Halal sector and positioned the country as an international leader in Halal certification. Such initiatives include: Establishment of the Halal Industry Development Corporation (HDC) to encourage the growth of Halal businesses with regulatory support, greater access to markets and innovation development. Utilizing AI strategically within the marketing and supply chain of Halal businesses serves national interests, especially in respect to competitiveness, operational transparency, and consumer trust (Goh et al., 2021). The integration of AI tools such as chatbots, recommendation systems, and sentiment analysis can markedly enhance customer engagement and loyalty, both of which are critical to the success of Halal companies domestically and internationally (Hassan et al., 2020).

With e-commerce seeing a growing number of consumers seeking to purchase Halal products online, the introduction of AI has significant potential to expand the reach of Halal businesses. Such AI-based platforms will continue to improve customer experiences through personalised suggestions, improved search algorithms for Halal-certified products, and optimized logistics for faster delivery, resulting in improved customer satisfaction levels (Grewal et al., 2019).

METHODOLOGY

The study adopts a qualitative approach using a case study methodology to explore AI integration in marketing for the Halal supply chain in the region. The case study design enables a comprehensive investigation of real-world cases whereby the investigator can study the complexity of this phenomenon and the intricacies and interactions of AI adoption in the unique context of Halal industry in Malaysia (Yin, 2018). This approach helps to understand the application of AI in marketing strategies and supply chain processes in a context that requires cultural and religious sensitivity like Halal certification.

Data Collection:

Preliminary and secondary sources are used to gather data. The primary data for the studies is collected via semi-structured interviews with key stakeholders in the Halal supply chain in Malaysia. Participants are marketing managers from Halal certified organisations, certifying body representatives, and AI technology experts in supply chain and marketing operations. Using a semi-structured approach affords flexibility to explore emerging ideas while maintaining awareness of the central research questions (Creswell, 2014). The interview questions are designed to uncover information about the current state of AI use in marketing, the challenges faced by companies trying to implement AI into their Halal supply chain processes, and the perceived benefits and risks of the technologies.

Data were collected and aggregated from sources, including industry reports, white papers, and peer-reviewed journal articles that provide key contextual and theoretical underpinnings for the study. This includes news about the rapid adoption of artificial intelligence in supply chain systems, AI-based marketing drives, and the importance of Halal certification in overseas markets. The use of secondary data enriches the insights derived from primary interviews, as it provides a broader context to the trends and issues associated with Halal supply chain industry (Yin, 2018).

Sampling:

Using purposive sampling, the study selects participants with adjustable experience and knowledge to employ AI within the Halal supply chain. This includes individuals involved in the design, implementation, and oversight of AI projects, and those responsible for ensuring Halal compliance in goods. Purposive sampling ensures that the data collected is relevant and insights drawn from the sample are knowledgeable in addition to being significant to solve the research queries (Palinkas et al., 2015).

Grounded in the idea of data saturation, the number of interviews is determined as the collection of data that leads to no new themes or insights (Guest, Bunce, & Johnson, 2006). The researcher conduct a total of 15 meetings with numbers are adjusted based on the saturation point.

Data Analysis:

A thematic analysis approach was used to analyse the data. Thematic analysis is a useful method for identifying, analysing and reporting patterns (themes) within data (Braun & Clarke, 2006). The analysis is carried out in a series of phases: (1) familiarisation with the data, (2) generation of initial codes, (3) searching for themes, (4) reviewing themes, (5) defining and naming themes, and (6) writing up. This methodology facilitates the identification of trends related to the implementation of AI within the Halal supply chain marketing context, including its impact on consumer behaviour, marketing techniques, compliance with Halal protocols, as well as the challenges faced by organisations in the process of integrating AI.

The coding process involves both inductive and deductive approaches. Inductive coding enables development of themes that emerge directly from the data while deductive coding is used for testing existing theories or premises related to the application of AI in marketing and supply chain management (Fereday & Muir-Cochrane, 2006). NVivo software will be used to systematically arrange and organise the data for a comprehensive analysis.

Ethical Considerations:

Ethics is important to this study, especially with regard to interviews and data collected from industry stakeholders. Informed consent will be provided to all participants to ensure they understand the nature of the study, their right to confidentiality and their right to withdraw at any time without repercussions. All data will be anonymised to protect the identities of participants and the research will adhere to the university’s ethical guidelines. In addition, the process will respect Halal certification standards, as well sensitive religious beliefs throughout the research process.

Validity and Reliability:

The study will use triangulation to ensure the credibility and dependability of the findings, that is comparing and contrasting different sources of data (interviews; secondary data) to ensure the results on time (Flick, 2018). Member checks will be conducted (where participants validate findings) to ensure the accuracy and authenticity of the interpretations (Creswell, 2014). Moreover, the findings of the mentioned study will be contextualised in the context of a bigger body of research on artificial intelligence in the marketing and supply chain management fields to provide a comprehensive and precise insight.

FINDINGS AND DISCUSSION

Application of AI in Marketing for Halal Supply Chains

Semi-structured interviews and secondary sources were used to gather qualitative data in order to identify the key application of Artificial Intelligence (AI) based marketing strategies in Malaysia Halal supply chain. Once the thematic analysis was run it was found that AI has a transformative role for customer engagement, demand forecasting and digital marketing. These are crucial for the businesses who need to conduct marketing without breaking Halal policies.

• Customer Relationship Management (CRM): AI-enabled CRM solutions were revealed as crucial technologies for enhancing customer engagement in the Halal supply chain. For example, AI tools using predictive analytics allow organisations to know customer behaviours, preferences, and spending patterns. A marketing manager from a beverage company that is Halal-certified even shared that they saw a 30% jump in retention after utilizing an AI-powered CRM that personalized the experience for customers. As an added benefit, AI chatbots were commended for being available around the clock to respond to consumer inquiries regarding Halal certifications and product ingredients, increasing trust and transparency (Nguyen et al., 2021).
• Demand Forecasting: Many interviewees had pointed out that machine learning algorithms had been able to predict the future demand for Halal products – this was crucial for managing inventory and production cycles. According to a senior manager at a Halal logistics company, AI-driven demand forecasting tools had resulted in a 20% reduction in stockouts and improved inventory turnover. These tools analyze past sales data with season (i.e. Ramadhan and Hari Raya) and regional trends to achieve more accurate demand forecasting (Goh et al., 2019). This helps businesses coordinate the supply chain with changing market demand and ensure the availability of products when they are needed.
• Digital Marketing & Personalization: The use of AI tools for creating digital marketing strategies was termed as a game-changing application for the Halal supply chain. Dynamic pricing, personalized recommendations, and targeted ads are all powered by AI algorithms. A participant from one of the largest Halal food retailers says that AI-based recommendation systems are driving their online sales growth up by 40%, as they effectively recommend products based on browsing history and purchase history. Moreover, AI was used to generate customized messages and media that recognized the cultural and religious beliefs of Muslim readers, thereby enhancing brand loyalty (Buhalis & Law, 2008).

HSCM challenges and barriers to implementation of AI

Though AI technologies are beneficial, the study revealed several challenges faced by businesses in integrating AI in Halal supply chains. These challenges are associated with data privacy, compliance with regulations, and high initial costs, rupturing the seamless integration of AI tools.

• Potential Data Privacy and Security Threats: This led to data privacy being identified as one of the main barriers to AI adoption, especially when it comes to sensitive consumer data. Several interviewees raised concerns about the potential misuse of personal data — including purchasing patterns, demographic information, and preferences — which are vital to AI-powered marketing strategies. “As we be utilizing AI for gathering consumer data for personalized marketing, we have to ensure that all data is secured in accordance with the specifications outlined in Personal Data Protection Act (PDPA) and Halal cert guidelines” (Ahmad et al., 2021). Data leaks or improper management of sensitive data may cause a loss of consumer confidence, particularly in a religiously sensitive market.
• Regulatory Compliance: Multiple stakeholders brought attention to the question of how AI tools can be assured to be compliant with Halal certification standards. “AI systems need to be tested rigorously to ensure that they do not inadvertently promote non-Halal products or violate any religious guidelines,” said one representative from a Halal certifying body. Product recommendation or advertisements generators AI systems—need to be monitor whether it is based on Islamic discuss and not misleading consumers (Al-Qudah et al., 2020). For Halal food and beverage businesses in particular, ensuring religious compliance can be a make-or-break factor when it comes to consumer confidence and brand integrity.
• High-Upfront Cost: The initial cost associated with the deployment of AI technology was pointing to be one of the barriers, particularly for small and medium enterprises (SMEs) in the Halal industry. Problem 1 — High Cost of AI-Powered Software: A small Halal packaging company interviewee, in our research mentioned that purchasing AI-driven software was a costly affair as it directly cost his company over RM200,000.00 and with the working infrastructure (hardware) it was prohibitively expensive for businesses with limited budgets. Moreover, operating AI tools requires skilled personnel that also entails additional costs (Grewal et al., 2019). AI is proven to be beneficial in the long run, as it improves efficiency over time and reduces costs. However, the high initial investment is a major hindrance for numerous SMEs.

Recommendations for Overcoming Barriers

In order to overcome these challenges, the study presents a number of recommendations to promote AI utilization across the Halal supply chain:

• Enhancing Data Security Structures: Companies must increase effective data security systems to obtain consumer data as well as conforms to native privacy legal guidelines For example, it could be suggested that the use of blockchain technology might share the potential of providing an immutable and transparent record of data that would secure trust in AI systems (Flick, 2018). Additionally, Halal supply chain companies must invest in cybersecurity practices to ensure sensitive information does not fall into the wrong hands.
• Establishing Framework Unifying Authorities for Advances in AI: Companies must work in collaboration with Halal certifying bodies and Islamic scholars for usage of the AI tools in compliance with halal. So, AI systems can be audited regularly to detect possible divergence.” As highlighted by one Halal certification representative, “there is a need for collaboration between technology providers, Halal authorities, and businesses to ensure that AI innovations harmonize with Islamic values” (Al-Qudah et al., 2020).
• Government Support for the Halal SMEs: In finance, to reduce the software and technology costs for the SMEs in the Halal supply chain sector, the Malaysian government can provide subsidy, tax incentives, or grants. Better still, we could establish public-private partnerships to enable access to low-cost AI solutions. Training and development programs for SMEs could also enable those in the sector to own and embrace AI tools without the need to hire external skills (Grewal et al., 2019).

The study of AI in marketing based on the Halal supply chain in Malaysia has a great opportunity to create customer engagement marketing, supply chain management, and business performance in this supply chain. Yet, there are also challenges, including data privacy challenges, regulatory compliance obstacles, and elevated implementation costs that need to be overcome for the successful implementation of AI technologies. Halal supply chain businesses can navigate this balancing act by implementing measures like enhancing data security jurisdictions, adhering to regulatory requirements, and seeking governmental assistance for SMEs that operates in its Halal supply chain.

CONCLUSION

This research emphasises the groundbreaking capabilities of Artificial Intelligence (AI) in marketing, particularly within the Halal supply chain in Malaysia, showcasing notable advancements in customer relationship management, demand forecasting, and digital marketing strategies. Tools powered by artificial intelligence have demonstrated their capacity to improve customer interaction, tailor marketing strategies, and streamline inventory control, especially in contexts where following Halal guidelines is essential. Nonetheless, embracing AI comes with its own set of hurdles, especially in terms of safeguarding data privacy, adhering to regulations, and managing the significant initial investment required for implementation. It is essential to address these obstacles for enterprises to maximise the benefits of AI within the Halal supply chain.

RECOMMENDATIONS

The following recommendations are introduced to implementing AI technologies into the Halal supply chain:

Strengthening Cybersecurity: As halal supply chains become increasingly reliant on digital systems, businesses need to invest in robust cybersecurity measures to protect sensitive information and prevent ransom attacks. A more secure and transparent way of data transaction can be done by using technologies like blockchain (Flick, 2018).

Engagement with Regulatory Bodies: Organisations need to work closely with certification authorities and religious scholars to ensure that AI systems comply with religious rules. Regular assessments and collaboration can prevent slips from Halal practices (Al-Qudah et al., 2020).

Government Assistance for SMEs: The government should offer financial assistance via grants/tax subsidies to SMEs which need to pay a high upfront cost to integrate AI. Professionals agreed that collaborations between the public and private sectors could increase the access to cost-effective AI solutions and relevant training programs (Grewal et al., 2019).

By utilizing these strategies, companies in the Halal supply chain can successfully navigate the challenges of AI adoption, while also adhering to religious and ethical principles. We will achieve sustainable growth as well as become better competitors with this approach.

REFERENCES

1. Ahmad, S., Azmi, M., & Ibrahim, M. (2021). Data privacy and ethical implications in AI-driven marketing strategies in the Halal industry. Journal of Business Ethics, 174(3), 415-428.
2. Ahmad, S., Zailani, S., & Al-Mazrouei, H. (2021). Data privacy and security in the Halal supply chain: A review of ethical concerns and challenges. Journal of Islamic Marketing, 12(3), 345-362.
3. Ali, A., Khan, M., & Latif, A. (2020). Artificial intelligence applications in logistics and supply chains: Implications for Halal industries. International Journal of Logistics, 22(2), 200-212.
4. Al-Qudah, M., Al-Debei, M., & Al-Omari, Z. (2020). Halal certification and regulatory compliance challenges in AI systems. International Journal of Islamic Marketing and Branding, 5(1), 45-62.
5. Al-Qudah, M., Hussain, F., & Abdullah, S. (2020). Halal supply chain management: Challenges and strategies. International Journal of Supply Chain Management, 8(1), 35-48.
6. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101.
7. Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the Internet—the state of tourism research. Tourism Management, 29(4), 609-623.
8. Choi, T. Y., Zhao, X., & Lee, S. (2020). Supply chain management research and practices in the age of digital transformation. Journal of Business Logistics, 41(3), 248-268.
9. Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approach. Sage Publications.
10. Fereday, J., & Muir-Cochrane, E. (2006). Demonstrating rigor using thematic analysis: A hybrid approach of inductive and deductive coding and theme development. International Journal of Qualitative Methods, 5(1), 80-92.
11. Flick, U. (2018). An introduction to qualitative research (6th ed.). Sage Publications.
12. Flick, U. (2018). Blockchain technology in securing data in AI applications: A comprehensive review. Journal of Digital Innovation, 9(2), 153-168.
13. Goh, M., Lim, H., & Ang, W. (2021). Leveraging digital technologies for the Halal industry: Trends and prospects in Malaysia. Journal of Business and Technology, 33(1), 65-81.
14. Goh, M., Lim, A., & Tan, C. (2019). The role of machine learning in demand forecasting: Evidence from the Halal food supply chain. Journal of Supply Chain Management, 55(3), 17-30.
15. Goh, M., Yip, K., & Lee, K. (2019). Leveraging AI for demand forecasting in supply chain management. International Journal of Production Economics, 211, 13-23.
16. Grewal, D., Roggeveen, A. L., & Nordfält, J. (2019). The future of retailing and marketing with AI: A case study in retail sector integration. Journal of the Academy of Marketing Science, 47(3), 317-333.
17. Grewal, D., Roggeveen, A. L., & Nordfält, J. (2019). The future of retailing: Artificial intelligence in marketing and retail. Journal of the Academy of Marketing Science, 47(5), 719-740.
18. Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough? An experiment with data saturation and variability. Field Methods, 18(1), 59-82.
19. Hassan, R., Ali, F., & Syed, A. (2020). The economic impact of Halal industries: A strategic overview of Malaysia’s Halal supply chains. Asia Pacific Business Review, 26(2), 123-139.
20. Idris, R., Ibrahim, I., Othman, H., Ahmad Jamil, N., Amer, A., & Senathirajah, A. R. S. (2024). Examination Of the Impact of Service Quality and Customer Safety on The Satisfaction of Grab CustomerS. Journal Azbakia, 1(1), 1–11.
21. Idris, R., Ibrahim, I., Othman, H., Kasdi, S. A., Abdul Halin, I., & Senathirajah, A. R. S. (2024). Conceptualizing Adaptability in Malaysia Cities: Exploring the Intersection of Climate Change and Urban Policy. Journal Azbakia, 1(1), 1–14.
22. Ibrahim, I. (2024). Improving the Quality of The Operations Management Course (Opm549) Via Project-Based Learning: A Study at university Teknologi Mara, Puncak Alam, Selangor, Malaysia. NATURALISTA CAMPANO, 28(1), 794-802.
23. Ibrahim, I., Senathirajah, A. R. S., Nakamura, Y., Anah, L., & Ahmad Apandi, A. A. (2024). Enhancing The Efficiency of Artificial Intelligence Halal Warehouses for Manufacturing Innovation. A Conceptual Framework. African Journal of Biological Sciences, 6(12), 4177–4190. https://www.afjbs.com/uploads/paper/42fd5f6b0e6becb168d6f77bf0b4afd6.pdf
24. Ibrahim, I., Senathirajah, A. R. S., Nakamura, Y., Md Radzi, N. Z., & Ahmad Apandi, A. A. (2024). The Determinant Factor of Lean Management for Industrial Growth. A Case Study of Zuellig Pharma (M) Sdn. Bhd. African Journal of Biological Sciences, 6(Si4), 3321–3334. https://www.afjbs.com/uploads/paper/1fbdead63bbb33d25f445c5ab917e4da.pdf
25. Ibrahim, I., Senathirajah, A. R. S., Nakamura, Y., Md Radzi, N. Z., & Rahmat, A. K. (2024). THE Airport Operational Performance Quality Towards Infrastructural Development Passenger Satisfaction. The Case Study Of Kuala Lumpur INTERNATIONAL AIRPORT TERMINAL 2. African Journal of Biological Sciences, 6(Si4), 3283–3296. https://www.afjbs.com/uploads/paper/bc8a3eae7d8175df249d5f74a7e2f618.pdf
26. Kshetri, N. (2018). Artificial Intelligence and the Internet of Things: Opportunities and Challenges for Business and Marketing. Springer.
27. Ladhari, R., & Souiden, N. (2015). The role of marketing in halal business: A conceptual framework. Journal of Islamic Marketing, 6(2), 174-191.
28. Nguyen, B., Simkin, L., & Canhoto, A. I. (2021). AI in customer relationship management: A systematic review and research agenda. Journal of Strategic Marketing, 29(4), 350-371.
29. Nguyen, T., Le, T., & Zhang, Y. (2021). AI-driven customer relationship management in the Halal industry: A case study of beverage companies in Malaysia. Journal of Business Research, 128, 299-310.
30. Osman, Z., Senathirajah, A. R. B. S., Haque, R., & Ibrahim, I. (2024). A Structural Equation Modelling Approach on Determinants of Working Adults’ Choice to Further Study in Malaysian Online Distance Learning Higher Education Institutions. Educational Administration: Theory and Practice, 30(1).
31. Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hogwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544.
32. Sarbani, N. B., Abd Razak, A. H., Ibrahim, I., Senathirajah, A. R. S., & Ahmad Apandi, A. A. (2024). Robust Framework of Halal Supply Chain Management with Integration of Artificial Intelligence Application for Industrial Growth. African Journal of Biological Sciences, 6(14), 6235–6259. https://www.afjbs.com/uploads/paper/d4791c140d6d7792f8d23b44a655d8c2.pdf
33. Senathirajah, A. R. S., Ghazali, W. N. S., Sundram, V. P. K., Ibrahim, I., Nakamura, Y., & Jamil, N. A. (2024). Service Quality Improvement and Innovation of a Local Authority and Enforcement Organization in Malaysia. A Case Study of Tyt Authority. *Educational Administration: Theory and Practice,30*(5), 2865-2871.
34. Senathirajah, A. R. S., Nadzri, M. D. I. B., Sundram, V. P. K., Nakamura, Y., & Ibrahim, I. (2024). Analysis Of Product Supply and Demand Planning for Sustainable Supply Chain: A Study at Petmax Oil Company. Educational Administration: Theory and Practice, 30(5), 2841-2848.
35. Senathirajah, A. R. S., Sivan, S., Ghadiri, S. M., Sundram, V. P. K., Ibrahim, I., Nakamura, Y., & Kasdi, S. A. (2024). Resilient Infrastructure of Logistics Industry Towards Industrial Revolution 4.0 In Malaysia. Educational Administration: Theory and Practice, 30(5), 2776–2790. https://kuey.net/index.php/kuey/article/view/3345
36. Senathirajah, A. R. S., Zulkifle, N. N., Sundram, V. P. K., Ibrahim, I., Nakamura, Y., & Johan, Z. J. (2024). Applying The Plan-Do-Check-Action (Pdca) In the Vehicle Inventory Registration Process For Sustainable Transportation At Shasha Industries. Educational Administration: Theory and Practice, 30(5), 2811-2820.
37. Toloie Shelagh, A., Daneshvar, A., Peivandizadeh, A., S Senathirajah, A. R., & Ibrahim, I. (2023). Designing a Sustainable Model for Providing Health Services Based on the Internet of Things and Meta-Heuristic Algorithms. International Journal of Supply and Operations Management.
38. Wamba, S. F., Akter, S., & Edwards, A. (2017). Artificial Intelligence and Big Data analytics in supply chains: State-of-the-art and future research directions. International Journal of Production Research, 55(3), 618-632.
39. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage Publications.
40. Zhou, S., Yang, Z., & He, Y. (2022). AI applications in supply chain and logistics: Opportunities and challenges for Halal industries. Journal of Business Logistics, 43(1), 60-77.