Halal Food Products Adoption in Bangladesh: a Study Based on The Theory of Reasoned Action

Halal Food Products Adoption in Bangladesh: a Study Based on The Theory of Reasoned Action

Md. Mahabub Alom*

“*Associate Professor, Department of Business Administration, Manarat International University, Gulshan -2, Dhaka, Bangladesh.”

ABSTRACT

The key objective of this study is to measure the influence of the factors of the Theory of Reasoned Action (TRA) on the adoption of halal-certified food products among Bangladeshi Muslim consumers. Based on data from 558 respondents in Dhaka shopping malls, the researcher has identified the key findings regarding the adoption of Halal food products in the context of Bangladesh. The study reveals that the adoption of halal-certified food is significantly and positively influenced by attitudes and subjective norms as a component of the TRA model. Eventually, the study’s results can help a marketer come up with a way to take advantage of Bangladesh’s hugely promising and growing market by introducing a variety of halal product brands that appeal to the country’s growing population.

KeyWords: Halal Food Products, Adoption, Attitude, Subjective norms, Bangladesh

INTRODUCTION

Islam, Sariah, Halal are not simply a money-making concept or fancy commercial terms. All these are the religious, universal, and classical phenomenon. But the use of these religious terms can overwhelm the Muslim consumers to make their purchase decision due to a strong emotional and spiritual attachment for the quest of spiritual incentive with worldly benefit in everyday life (International Trade Center, 2015). 148.6 million Muslim people of Bangladesh which represent 90.4% of the country’s total population (Nisha & Iqbal, 2017) has validated this trend through welcoming and responding positively towards Islam, Shari‘ah Halal, Amanah, Sadiq and other religious terms in banking, food and beverage, products, healthcare, education, pharmaceuticals, tourism, fashions, and other business fields. Halal food products is an important aspect of the food industry in Bangladesh, as the country has a large Muslim population. According to Thomson Reuters (2022), Bangladesh was the 2^nd halal food products consumer market and valued $125.1 billion and in 2023-2024, valued $137 billion which is increasing.

Top five Halal food products consumer markets

State of the Global Islamic Economy Report (2022 p.49,2023/2024 p.97)

The increasing demand for halal food products in Bangladesh is driven by consumer awareness of the benefits of halal certification, such as food safety and quality (Zafar et al., 2024). Despite this growing trend, the halal food industry continues to struggle with positioning and is unable to figure out how to entice people to ensure consistent patronization; the factors that might stimulate adoption are still ambiguous. However, in Bangladesh, the food industry is faced with several challenges, including food adulteration and weak enforcement of regulations, that can create a negative perception of the food industry among consumers. In this context, understanding consumer intentions to adopt halal food products in Bangladesh is crucial for the development and promotion of the halal food product industry. Note that the idea of a consumer wanting to buy halal-labeled food in Bangladesh is fluid and changes over time due to many factors. The goal of this study is to look into the factors that affect consumer wanting to buy halal-labeled food in Bangladesh, including the effects of the theory of reasoned action model on the adoption of halal-certified food in Bangladesh.

Objective Of The Study

The main objective of this study is to examine the adoption of halal-certified food products among Bangladeshi Muslim consumers. The specific objectives are as follows:

• To examine the impact of key factors from the Theory of Reasoned Action on the adoption of halal-certified food in Bangladesh.
• To offer recommendations for promoting the adoption of halal-certified food in Bangladesh.

LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

Halal food products in Bangladesh

The adoption of halal food products in Bangladesh has been increasing recently due to growing consumer awareness. Halal products comply with Islamic laws and principles, ensuring ethical, health, and quality benefits. The demand for halal products is rising globally, particularly in Muslim-majority countries like Malaysia and Indonesia. Bangladesh, with a predominantly Muslim population, presents a large market for halal products. According to the 2022 census, Muslims constitute 91.04% of Bangladesh’s population, creating a substantial market for halal products (Population and Housing Census 2022). Awareness of halal certification is expanding beyond food to include cosmetics and pharmaceuticals. The growing demand for halal food in Bangladesh is driven by religious adherence, health consciousness, and ethical considerations. Halal food is increasingly viewed as a symbol of quality and ethical consumption in Bangladesh. A study by Nekmahmud (2016) indicates that halal is not just a religious obligation but also a quality standard. Research by Jannat and Islam (2019) highlights factors influencing Bangladeshi consumers’ purchase intentions toward halal-certified foods. The halal food market in Bangladesh is still underdeveloped, presenting significant growth opportunities. Currently, the market mainly focuses on meat and poultry, but there is potential for expansion into processed foods, snacks, and beverages. The Bangladeshi government has introduced policies to facilitate halal certification for food, pharmaceuticals, and cosmetics. Despite opportunities, challenges include inadequate halal certification and consumer mistrust due to unclear labeling. Limited research on the halal market in Bangladesh creates difficulties for businesses in targeting the right consumers. Businesses and marketers now view halal certification as a competitive advantage (Yeo et al., 2016). Undoubtedly, Halal-certified products are a new marketing wave. Since consumer concerns on the subject of halal cosmetics vary from country to country (Fathi et al., 2016), it is essential to conduct some empirical work in Bangladesh due to its existing position and potentiality (Abd Rahman et al., 2015; Musa, 2014). Even though there are several research studies performed in other nations throughout the world, they were not performed in Bangladesh. Eventually, to bridge the contextual gap in the literature, researchers need to do studies in an Islamic country like Bangladesh (Ali et al., 2016). Numerous studies have focused on the Islamic banking industry while investigating issues in a wider context. Studies on halal food products in Bangladesh remain scarce, despite increasing interest in the sector. More empirical research is needed to explore halal adoption beyond food, including cosmetics, finance, and pharmaceuticals. Addressing gaps in research will help better understand consumer behavior and market potential in Bangladesh’s halal industry.

Theoretical Framework

According to Fishbein and Ajzen’s (1975) Theory of Reasoned Action (TRA), human conduct is characterized by purpose, impacted by attitudes, and subjective norms. Several studies have examined consumer purchasing decisions through the lens of this theory, which states that attitudes and subjective norms impact behavioral intentions (Koraag et al., 2024; Wilujeng et al., 2019; Garg & Joshi, 2018; Lada et al., 2009; Fahmi, 2017). In the context of halal food products, attitudes reflect personal evaluations, while subjective norms indicate social pressure to comply with halal standards. People widely use TRA to understand their purchasing decisions for ethical products, including halal goods. Studies in Malaysia, Indonesia, and other Muslim-majority countries confirm its effectiveness in predicting consumer behavior in halal markets.The objective of this study is to examine the factors influencing the adoption of halal products in Bangladesh, which is grounded in the widely applied Theory of Reasoned Action (TRA) model. The present research deals with the behavioral intention of halal product adoption, which is one of the disciplines in social science.  The proposed model expresses the adoption of halal products as the dependent construct and includes two determinants—attitude and subjective norms—as independent constructs. The primary goal of this research framework is to streamline the study by determining what variables are impacting the widespread adoption of halal food options in Bangladesh.

The role of attitude for adoption of halal food products

Attitude, the first construct in the TRA model, plays a decisive role in the adoption of halal food products in Bangladesh. According to Lada et al. (2009), Bonne et al. (2007), and Mukhtar & Butt (2012), “If a Muslim consumer has a positive attitude towards halal products based on his or her positive and strong beliefs, then the consumer is more likely to buy halal-labeled food.”  Additionally, numerous studies have noted that studying the behavior and attitudes of Muslim consumers regarding halal products from diverse cultures and nations is an essential and vital subject for exploration and study (Bonne et al., 2007). The many studies that have looked into the connection between attitude and adoption are as follows: Koraag et al., 2024; Ardiyanto et al., 2024; Wibowo et al., 2024; Puspita, 2023; Nurkhin et al., 2023; Hasyim & Purnasari, 2021; Vanany et al., 2020; Bashir et al., 2019; Jannat & Islam, 2019; Ashraf, 2019; Wilujeng et al., 2019; Fahmi, 2017; Lada et al., 2009. A person’s attitude towards adopting halal food items reflects how positively or negatively they feel about consuming halal food.According to the findings of the study, the perspectives of customers are significantly impacted by their beliefs regarding the safety, ethics, and quality of halal food items, which in turn influences the manner in which they accept these sorts of products. This study posits that Muslim consumers with strong positive attitudes are more likely to adopt halal food products, which in turn shapes their actual behavior. Therefore, investigating consumer attitudes is essential for understanding adoption behavior and forms the basis for the study’s hypotheses.

H1. Consumer’ more favorable attitude towards halal food products, the higher likelihood to adopt halal food products in the context of Bangladesh.

The role of subjective norms for adoption of halal food products

The second predictor of the TRA model, subjective norm, refers to social influences on an individual’s decision-making (Ajzen, 1991). It reflects perceived pressure from family, friends, colleagues, and community members to adopt certain behaviors (Charsetad, 2016; Sukato, 2008; Hee, 2000). Subjective norm reflects social pressure to adopt or avoid behaviors (Awan et al., 2015) and is shaped by informative and normative influences (Kuan et al., 2014). Muslim families prioritize collectivism over individualism, fostering integration (Daneshpour, 1998). In Bangladesh, societal norms, including religious and cultural collectivism, play a crucial role in adopting halal-labeled products. Muslim consumers prioritize subjective criteria to align with Shariah principles (Mohd Suki & Abang Salleh, 2018). The influence of religious scholars and social circles is particularly strong, making subjective norms a key factor in the adoption of halal cosmetics. Muslim consumers prioritize subjective criteria to align halal cosmetics with Shariah principles (Mohd Suki & Abang Salleh, 2018; Azmi et al., 2010). A good number of researchers have explored the relationship between attitude and adoption in various studies (Ardiyanto et al., 2024; Wibowo et al., 2024; Puspita, 2023; Nurkhin et al., 2023; Hasyim & Purnasari, 2021; Vanany et al., 2020; Bashir et al., 2019; Jannat & Islam, 2019; Ashraf, 2019; Wilujeng et al., 2019; Garg & Joshi, 2018; Fahmi, 2017; Lada et al., 2009). In Bangladesh, subjective norms strongly influence halal product adoption, driven by social pressure from family, friends, religious leaders, and community figures. In such a scenario, the significant indicator may be the subjective norm, and Bangladesh’s Muslim customers would be more likely to adopt halal cosmetics if they perceive other people follow.

H2. Consumers’ higher influence of Subjective norms towards halal food products, the higher likelihood to adopt halal food products in the context of Bangladesh.

METHODOLOGY

This study utilized a quantitative research approach. A questionnaire, designed based on relevant literature and expert input, was used for data collection. The survey employed a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree) to ensure reliability and validity (Weijters et al., 2010; Sullivan & Artino, 2013; Habidin et al., 2018). The unit of analysis was individual buyers from various shopping malls in Dhaka, Bangladesh. The target population comprised male and female buyers purchasing halal products. Due to the large population size, a convenient mall intercept sampling technique was adopted (Rice & Hancock, 2005) and data was collected from different supermarkets from different locations.  The questionnaire measured attitude (five items), subjective norms (five items), and halal product adoption (five items). These measures were adopted and adapted from Loussaief et al. (2024), Jannat and Islam (2019), Briliana and Mursito (2017), Al-Hajla (2017), Ayuniyyah et al. (2017), and Prerna & Joshi (2018). The minimum sample size should be more than 45 (3×10+15), coming from the well-established formula (10*number of variables+1*number of items) for this study as recommended by Hair et al. (2012). Moreover, according to Roscoe (1969), sample sizes that are larger than 30 and less than 500 are appropriate for most studies. The analysis concluded with a total of 558 responses. Data analysis included both descriptive analysis and hypothesis testing. PLS-SEM 4.0 was used to check for measurement reliability, convergent validity, discriminant validity, model explanatory power, predictive power, and collinearity. SPSS 23.0 was used for descriptive analysis. Finally, model testing was conducted to evaluate the hypothesized relationships.

ANALYSIS AND FINDINGS

Descriptive Statistical Analysis

A summary of the gathered data is given by descriptive statistical analysis, which also sheds light on the sample’s characteristics. Table I displays the descriptive statistics for the variables employed in this investigation. PLS-SEM, being a nonparametric statistical approach, does not depend on distributional assumptions (Hair, Ringle, & Sarstedt, 2011). The statistical features allow for reliable model estimates whether the data follow a normal or significantly non-normal distribution (Hair et al., 2017; Reinartz, Haenlein, & Henseler, 2009).

Table I: Summary of Descriptive Analysis

PLS-SEM Analysis Results

Over the past decade, the volume of PLS-SEM applications has increased considerably (Hair et al., 2022). PLS EM analysis is divided into two distinct stages. In the first step, the researcher receives the measurement model output, which aids in evaluating the quality of the data in terms of internal consistency, reliability, and discriminant validity (Dijkstra & Henseler, 2015; Heseler et al., 2015). Initially, the researcher obtains the measurement model output, which facilitates the evaluation of internal consistency, reliability and discriminant validity (Dijkstra & Henseler, 2015; Henseler et al., 2015) to ascertain data validity. Subsequently, the significance and relevance of the path coefficients, along with the explanatory and predictive capabilities of the structural model, are assessed (Shmueli et al., 2016; Hair et al., 2020). The hypothesized model, developed using Smart PLS software version 4.0, is illustrated in Figure I below.

Figure I: Measurement Model

Reliability Test

Hair et al. (2022) assert that all constructs must have Cronbach’s alpha values over 0.70 for reliability, and composite reliability values should surpass the 0.70 threshold (Bagozzi & Yi, 1988). The permissible range for reliability metrics is 0.70 to 0.90, with a ceiling of 0.95 to prevent indication redundancy (Hair et al., 2019). As shown in Table II, all of the composite reliability and Cronbach’s alpha values are greater than 0.70, indicating excellent internal consistency and validating each of the study’s constructs.

Table II: Measurement Properties of PLS Measurement Model.

Convergent Validity

Based on the results of this study, the convergent validity of the data is checked using the factor loadings and the average variance extracted (AVE) of the variables. All of the AVE values in Table II are above 0.50, which means that the constructs are convergent because they meet the requirement of AVE > 0.50 (Sarstedt et al., 2021). Furthermore, item loadings of 0.60 or higher affirm the convergent validity of the study’s constructs.

Discriminant Validity

According to recent debates, the HTMT (Heterotrait-Monotrait Ratio) should be used to evaluate discriminant validity rather than the Fornell-Larcker criterion or cross-loadings (Franke & Sarstedt, 2019; Hair et al., 2022; Henseler et al., 2015). For a more accurate assessment of discriminant validity, Henseler et al. (2015) suggest to use the HTMT. A threshold value above 0.90 of HTMT indicates a lack of discriminant validity between conceptually similar constructs. For constructs that are conceptually distinct, a more conservative threshold of 0.85 is advised. As a result of the fact that the HTMT values ought to be lower than 0.85 for conceptually distinct conceptions, this research substantiates the criteria (Henseler et al., 2015; Franke & Sarstedt, 2019).

Table III: Discriminant Validity Assessment (HTMT ratio)

Coefficient of Determination (R²)

The most important phase in the examination of the structural model is to determine the extent to which the model can explain explanatory power. The coefficient of determination, also known as R², offers insight into the extent to which the exogenous factors are responsible for explaining the variance in the endogenous variables. For the purpose of this investigation, the R² value for the adoption of halal food products (AHF) is 0.579. The R² value of 0.579 indicates that the independent factors are responsible for explaining 57.9% of the variance in AHF. Based on established guidelines (Hair et al., 2011; Moosbrugger et al., 2009), an R² value of 0.75 indicates a strong impact, a value of 0.50 indicates a moderate effect, and a value of 0.25 indicates a weak effect. Consequently, the R² value of 0.579 in this study supports the moderate impact, indicating that the influence is sufficiently substantial.

Predictive Relevance (Q²)

A method called predictive sample relevance (Q²) is used in PLS-SEM analysis to check how well the model can predict the future (Stone, 1974; Geisser, 1974; Fornell & Cha, 1994; Chin, 2010). Using the blindfolding procedure, this study found a Q² value of 0.337 for the adoption of halal food products (AHP). Since the Q² value exceeds zero, it indicates that the model has predictive relevance (Moosbrugger et al., 2009).

Collinearity

Lower VIF values, like 3, can cause collinearity problems (Becker et al., 2015; Mason & Perreault, 1991). VIF values should ideally be less than or near 3. The study’s descriptive analysis, item loadings, composite reliability, AVE, and cross-loading all support the findings that the data are valid, reliable, and multicollinearity-free. As a result, we can move for hypothesis testing.

Assessment of Structural Model

After confirming the measurement model’s validity and reliability, the researcher moved on to the structural model using the PLS-SEM approach. For the purpose of hypothesis testing, this resulted in path coefficient estimates that reflect the proposed relationships between the variables. This study has considered standard errors, t-values, p-values, and path coefficients. A hypothesis is deemed accepted if it is significant at the 5% level (t-value > 1.96 or p < 0.05) (Henseler & Fassott, 2010).

Figure II: The Structural Model

Table IV displays the results of the structural model used for hypothesis testing, with the corresponding output also recorded in Table IV. Figure II also presents the PLS structural model. The researcher assessed the significance of the proposed relationships in the path model through the application of the bootstrapping technique for hypothesis testing. The bootstrap involved a total of 1,000 resamples (Chin, 1998). The total count of bootstrap cases corresponded to the initial number of observations to produce standard errors and derive t-statistics (Hair et al., 2013). A significance level of 5% (p < 0.05 or t > 1.96) was employed to accept any hypothesis (Hair et al., 2014).

Table IV: The Structural estimates

Note: At the 1% level, ***p<0.01 is significant.

The initial hypothesis investigates the positive and significant impact of attitude on the adoption of halal food products. Attitude has a positive and significant effect, as shown by a path coefficient (²) of 0.427 and a t-statistic of 9.426 (p < 0.01), which means it is significant at the 1% level. Therefore, we acknowledge that attitude positively influences the adoption of halal food products, thereby supporting H1.These findings align with previous studies (Koraag et al., 2024; Ardiyanto et al., 2024; Wibowo et al., 2024; Puspita, 2023; Hasyim & Purnasari, 2021; Vanany et al., 2020; Bashir et al., 2019; Ashraf, 2019; Wilujeng et al., 2019; Fahmi, 2017; Lada et al., 2009). The results indicate that consumers exhibiting a more favorable attitude are more inclined to adopt halal food products.The second hThe second hypothesis explores the significant and positive influence of subjective norms on the adoption of halal food products.s indicate that subjective norms exert a significant positive influence, evidenced by a path coefficient (β) of 0.403, a t-statistic of 8.927, and p < 0.01. This finding corroborates Hypothesis 2, which anticipated a significant correlation between subjective norms and the adoption of halal food products. As with other studies (Ardiyanto et al., 2024; Wibowo et al., 2024; Hasyim & Purnasari, 2021; Ashraf, 2019; Wilujeng et al., 2019; Fahmi, 2017; Lada et al., 2009), subjective norms are the social pressures that people think they are under that make them decide to buy halal food. In Bangladesh, a collectivistic society, subjective norms significantly influence consumer adoption interest, highlighting their role in shaping the adoption of Halal food products within this specific context.

CONCLUSION & RECOMMENDATIONS

The Theory of Reasoned Action (TRA) accurately forecasts the adoption intentions of Bangladeshi Muslim consumers regarding halal food products. The research establishes that both attitude and subjective norms significantly predict buying decisions.   Muslim consumers in Bangladesh are inclined to adopt halal products based on Islamic principles and values, moving beyond traditional concepts with strong aspirations. The findings provide valuable theoretical and practical insights for entrepreneurs, practitioners, policymakers, governments, and other stakeholders in understanding the size, dynamics, and drivers of this high-potential market. It is recommended that future studies investigate each predictor in further depth by making use of additional models, such as the Theory of Planned Behavior (TPB) and the Diffusion of Innovation (DOI), and in other areas like halal cosmetics, halal supply chains, etc.

REFERENCES

1. Abd Rahman, A., Asrarhaghighi, E., and Ab Rahman, S. (2015). Consumers and Halal cosmetic products: knowledge, religiosity, attitude and intention. Journal of Islamic Marketing, 6(1), 148-163.
2. Ajzen, I. (1985). From intention to actions: a theory of planned behaviour’, in Kuhl, J. and Beckmann, J. (Eds.): Action Control from Cognition to Behaviour, pp.11–39, Springer, New York.
3. Ajzen, I. (1991). The theory of planned behaviour, organizational behaviour and human, Decision Processes, Vol. 50 No. 2, pp. 199-211. https://doi.org/10.1016/0749-5978(91)90020-T.
4. Ajzen, I. The theory of planned behavior. Organ. Behav. Hum. Dec. 1991, 50, 179–211.
5. Ali, S., Fairol, H., and Norzieiriani,A,, (2016). ‘The State of Halal Cosmetic Research on Consumer Behavior: A Systematic Review of the Literature and Future Research Directions, Journal of Marketing Management and Consumer Behavior, 1(4), pp. 40–51.
6. Ardiyanto, A. N., Lin, C. N., Maulidah, S., Rahman, M. S., & Shaleh, M. I. (2024). The Application Theory of Planned Behavior to Predict an Indonesian Muslim Student’s Intention to Buy Halal Foods in Taiwan. Habitat, 35(1), 79-95.
7. Aron, A., Coups, E., & Aron, E. N. (2013). Statistics for the Behavioral and Social Sciences: Pearson New International Edition: A Brief Course. Pearson Higher Ed.
8. Ashraf, M. A. (2019). Islamic marketing and consumer behavior toward halal food purchase in Bangladesh: An analysis using SEM. Journal of Islamic Marketing, 10(3), 893-910.
9. Awan, H. M., Siddiquei, A. N., & Haider, Z. (2015). Factors affecting Halal purchase intention – evidence from Pakistan’s Halal food sector. Management Research Review, 38(6), 640–660. https://doi.org/10.1108/mrr-01-2014-0022.
10. Ayuniyyah, Q., Hafidhuddin, D., & Hambari. (2017). Factors Affecting Consumers’ Decision in Purchasing MUI Halal-Certified Food Products. Tazkia Islamic Finance and Business Review, 10(2), 122–143
11. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models.
12. Bashir, A. M., Bayat, A., Olutuase, S. O., & Abdul Latiff, Z. A. (2019). Factors affecting consumers’ intention towards purchasing halal food in South Africa: a structural equation modelling. Journal of food products marketing, 25(1), 26-48.
13. Bonne, Karijn and Verbeke, Wim, (2007). Muslim consumer trust in halal meat status and control in Belgium. Elsevier Ltd. Meat Science 79 (2008) 113-123.
14. Briliana, V. and Mursito, N. (2017) ‘Exploring antecedents and consequences of Indonesian Muslim youths’ attitude towards halal cosmetic products: A case study in Jakarta’, Asia Pacific Management Review. Elsevier Ltd, 22(4), pp. 176–184. doi: 10.1016/j.apmrv.2017.07.012.
15. Charsetad, P. (2016). Role of religious beliefs in blood donation behaviour among the youngster in Iran a theory of planned behaviour perspective, Journal of Islamic Marketing, Vol. 7 No. 3, pp. 250-263.
16. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern Methods for Business Research (pp. 295– 358). Mahwah, NJ: Lawrence Erlbaum Associates.
17. Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655-690). Springer Berlin Heidelberg.
18. Daneshpour, M. (1998). Muslim families and family therapy, Journal of Marital and Family Therapy, Vol. 24 No. 3, pp. 355-368.
19. Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297‐316.
20. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106-121.
21. Fahmi, 2017). Fahmi, S. (2017). Halal labeling effect on Muslim consumers attitude and behavior. In 2017 International Conference on Organizational Innovation (ICOI 2017) (pp. 150-156). Atlantis Press.
22. Fathi, E., Zailani, S., Iranmanesh, M., Kanapathy, K., & Griffith, C. (2016). Drivers of consumers’ willingness to pay for halal logistics. British Food Journal, 118(2).
23. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Addison-Wesley.
24. Fornell, C., & Cha, J. (1994). Partial Least Squares (PLS) (Unpublished working paper, Ann Arbor: University of Michigan).
25. Garg & Joshi, 2018).  Garg, P., & Joshi, R. (2018). Purchase intention of “Halal” brands in India: the mediating effect of attitude. Journal of Islamic Marketing, 9(3), 683-694.
26. Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.
27. Habidin, N. F., Hashim, S., Fuzi, N. M., and Salleh, M. I. (2018). Total productive maintenance, kaizen event, and performance. International Journal of Quality & Reliability Management 35 (9): 1853-1867.
28. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 3rd Edition. Thousand Oaks: Sage.
29. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: A comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45(5), 616–632.
30. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151.
31. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Editorial-partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12.
32. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
33. Hasyim, F., & Purnasari, N. (2021). Antecedent of halal food purchasing decision: A Theory of Planned Behavior (TPB) approach. Iqtishadia, 14, 107.
34. Hee, S.P. (2000). Relationships among attitudes and subjective norm: testing the theory of reasoned action across cultures, Communication Studies, Vol. 51 No. 2, pp. 162-175.
35. Henseler, J. and Fassott, G. (2010). “Testing moderating effects in PLS path models: an illustration of available procedures”, in: Esposito V. Vinzi, W. Chin, J. Henseler, H. Wang, (eds.), Handbook of Partial Least Squares: Concepts, Methods and Applications (Springer Handbooks of Computational Statistics Series, vol. II), (pp. 713‐735). Springer: Heidelberg, Dordrecht, London, New York.
36. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance‐based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115‐135.
37. International Trade Centre (ITC), Geneva, (2015). From Niche to Mainstream – Halal Goes Global, Doc. No. P259.E/DCP/OAS/15-X, ISBN: 978-92-9137-429-8, United Nations Sales No. E.15.III.T.4, pp2-6.
38. Jannat, M., & Islam, M. M. (2019). Consumers’ purchase intention towards certified Halal foods. International Journal of Islamic Marketing and Branding, 4(3-4), 228-248.
39. Koraag, S. T. G., Kasih, P. H., & Rahmawati, K. (2024). Halal Food Products: Do Religiosity Affect Consumers. In Proceedings of the 2nd International Conference on Advanced Research in Social and Economic Science (ICARSE) (Vol. 842, p. 75). Springer Nature.
40. Kuan, K.K., Zhong, Y., Chau, P.Y. (2014). Informational and normative social influence in-group buying evidence from self-reported and EEG data. J. Manage. Inform. Syst. 30 (4), 151–178.
41. Lada, S., Harvey Tanakinjal, G. and Amin, H. (2009), “Predicting intention to choose halal products using theory of reasoned action”, International Journal of Islamic and Middle Eastern Finance and Management, Vol. 2 No. 1, pp. 66-76. https://doi.org/10.1108/17538390910946276
42. Loussaief, A., Ying-Chao Lin, J., Phuc Dang, H., Bouslama, N., & Cheng, J. M. S. (2024). Eating halal: a serial mediation model for the effect of religiosity on the intention to purchase halal-certified food. Asia Pacific Journal of Marketing and Logistics, 36(1), 167-184.
43. Mohd Suki, N. and Abang Salleh, A.S. (2016). Does Halal image strengthen consumer intention to patronize Halal stores? Some insights from Malaysia, Journal of Islamic Marketing, Vol. 7 No. 1, pp. 120-132. https://doi.org/10.1108/JIMA-12-2014-0079.
44. Moosbrugger, H., Schermelleh-Engel, K., Kelava, A. U. G. U. S. T. I. N., & Klein, A. G. (2009). Testing multiple nonlinear effects in structural equation modeling: A comparison of alternative estimation approaches. Structural equation modeling in educational research: Concepts and applications, 103-136.
45. Mukhtar, A. and Butt, M. M. (2012) ‘Intention to choose Halal products: The role of religiosity’, Journal of Islamic Marketing, 3(2), pp. 108–120. doi: 10.1108/17590831211232519.
46. Musa, R. (2014). Factors Influencing Attitude towards Halal Cosmetic among Young Adult Urban Muslim Women: A Focus Group Analysis. Procedia-Social and Behavioral Sciences, 130, 129-134.
47. Nekmahmud, M. (2016). Use of Ethical and Halal Concept in Marketing of Consumer Products: What is Going, What Must do and What Must Not do in Bangladesh. Global Journal of Management and Business Research: E Marketing, 16(4)
48. Nisha, N. and Iqbal, M. (2017). Halal ecosystem: Prospect for growth in Bangladesh, International Journal of Business and Society, 18(S1), pp. 205–222.
49. Nurkhin, A., Mukhibad, H., & Daud, N. M. (2023). Determinants of halal food purchase decisions for Go Food and Shopee Food users. Innovative Marketing, 19(1), 113.
50. Population and Housing Census 2022, National Report (Volume I)p67
51. Puspita, A. T. (2023). Attitude, Subjective Norm, and Perceived Behavioral Control on Halal Food Purchasing Behavior: A Case in Indonesia. Applied Marketing and Sustainability, 1(1).
52. Reinartz, W., Haenlein, M., & Henseler, J. (2009). An empirical comparison of the efficacy of covariance-based and variance-based SEM. International Journal of Research in Marketing, 26(4), 332–344.
53. Rice, R. and Hancock, L., (2005). The mall intercept: A social norms marketing research tool. The Report on Social Norms, 4(7), pp.4-7.
54. Roscoe, J. T. (1969). Fundamental research statistics for the behavioral sciences (p. 239). New York: Holt, Rinehart and Winston.
55. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. E. Vomberg (Eds.), Handbook of Market Research (pp. 1‐47). Springer International Publishing.
56. Sekaran, U. & Bougie, R. (2010). Research methods for business: A skills building
57. Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The Elephant in the room: Evaluating the predictive performance of PLS models. Journal of Business Research, 69(10), 4552‐4564.
58. Stone,  M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society, Series B (Methodological), 111-147.
59. Sukato, N. (2008). Changes in male buying behavior in Thailand – the case of metrosexuals, The Management Case Study Journal, Vol. 8 No. 2, pp. 263-270.
60. Sullivan, G. M., and Artino, A. R. (2013). Analyzing and interpreting data from likert-type scales. Journal of Graduate Medical Education, 5 (4): 541-542.
61. Thomson Reuters (2022,2023/2024), State of the Global Islamic Economy Report , 2022 p.49,2023/2024 p.97.
62. Vanany, I., Soon, J. M., Maryani, A., & Wibawa, B. M. (2020). Determinants of halal-food consumption in Indonesia. Journal of Islamic Marketing, 11(2), 507-521.
63. Weijters, B., Cabooter, E., and Schillewaert, N. (2010). The effect of rating scale format on response styles: the number of response categories and response category labels. International Journal of Research in Marketing, 27 (3): 236-247.
64. Wibowo, C. P., Syahlani, S. P., & Haryadi, F. T. (2024). An implementation of an extended theory of planned behavior to investigate consumer behavior on hygiene sanitation-certified livestock food products. Open Agriculture, 9(1), 20220302.
65. Wilujeng et al., 2019. Wilujeng, I. P., Wahyudi, H. D., Juhariah, L., & Respati, Y. (2019). Predicting interest in buying Halal products using Theory Reason Action. International Journal of Business, Economics, and Law, 20(5).
66. Yeo, B. L., Mohamed, R. H. N. and Muda, M. (2016). A Study of Malaysian Customers Purchase Motivation of Halal Cosmetics Retail Products: Examining Theory of Consumption Value and Customer Satisfaction, Procedia Economics and Finance. Elsevier B.V., 37(June), pp. 176–182. doi: 10.1016/s2212-5671(16)30110-1.
67. Zafar, M.B., Abu-Hussin, M.F. and Ali, H. (2024), “Mapping the research on halal industry: a retrospective analysis”, Journal of Islamic Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JIMA-08-2024-0348