September 5, 2010

5th ICBMR: Marketing Impact of Halal Labelling toward Indonesian Muslim Consumer’s Behavioral Intention Based on Ajzen’s Planned Behavior Theory: Policy Capturing Studies on Five Different Product Categories

Filed under: Marketing,Proceeding — Tags: — imams @ 10:15 pm

Please Cite: Salehudin, I. and Luthfi, B.A. (2010) Marketing Impact of Halal Labeling toward Indonesian Muslim Consumer’s Behavioral Intention Based on Ajzen’s Planned Behavior Theory: A Policy Capturing Study in Five Different Product Categories. Proceeding of 5th International Conference on Business and Management Research (ICBMR), Presented 4th August 2010, Depok-Indonesia.

Title:
Marketing Impact of Halal Labelling toward Indonesian Muslim Consumer’s Behavioral Intention Based on Ajzen’s Planned Behavior Theory: Policy Capturing Studies on Five Different Product Categories

Author:
Imam Salehudin, SE                     Bagus Adi Luthfi, SE
University of Indonesia             University of Indonesia

gsimam@gmail.com ; imams@ui.ac.id
Research Abstract:
Purpose – Indonesia is the biggest Muslim country in the world. Attention on the importance of Halal labeling in Indonesia is now growing. Halal-conscious consumer segment is getting bigger and the Halal Product Protection Act is being drafted. Understanding purchase behavior of Muslim consumer regarding Halal Labeling is imperative for marketer doing business in a Muslim country. The purpose of this paper is to test the applicability of the theory of planned behavior (TPB) in explaining the intention to switch from products without certified Halal labels within a wide array of purchase context, especially in the purchase of food and medicine products.

Design/methodology/approach – A policy capturing questionnaire was used to elicit responses from consumers using a convenience sampling technique. A total of 7500 responses were obtained from 150 participating respondent in 50 different scenario cases. Data is analyzed using Multi-Group Structural Equation Modeling.

Findings – The findings is that Theory of Planned Behavior (TPB) is not completely valid to explain both the behavioral intention of Muslim consumers in Indonesia to seek information about the Halal certification of a product and to cancel their purchase if the product did not have Halal certification.  Differences in magnitude and significance of causal relationships exist between different product categories.

Research limitations/implications – The study employs a limited population, thus this research has weak external validity. However, because this research is using quasi-experimental method, this research has strong internal validity in return. Thus, relationships among variables can be explained, even though a generalization to field conditions still needs further research.

Practical implications – The results will be primarily beneficial to marketers of food and medicine product sold in Muslim countries by offering an insight into the intentions of consumers to cancel purchases of products without Halal labeling.

Originality/value – The paper extends the understanding of the behavior of Muslim consumer toward products without Halal labeling within a variety of purchase context.

Keywords:  Purchase Behavior, Halal Label, Muslim Consumer

A. Background and Literature Review

Indonesia, country with the largest number of Muslims in the world, is also a large potential market for consumables such as foods, drinks and OTC medicine products. Foreign marketer of these products, however, must have good understanding of the local consumers and operate carefully in order to avoid offending the locals and obtain good foothold in the market.

Islam is not only a religion, but also a way of life. Muslims have strict commandment regarding what they consume. Allah Subhanahu Wa Ta’ala commands Muslims to consume only things that are good and Halal (Al Qur’anul Karim, 16:114; 23:51). Halal, which is the opposite of haram, is a term to say that something is not forbidden to be consumed by the scriptures of Qur’an, by the saying of the prophet or by the ijma’ (consensus) of the ulama’. His Prophet, Muhammad Shollallohu Alayhi Wa Sallam, also forbids his ummat to avoid consuming things that are ambiguous whether it is Halal or haram (HR Bukhari and Muslim, Al-Arba’in An-Nawawiyyah).  These commandments regulate the lives of Muslims worldwide and its compliance is mandatory. Of course, the actual compliance to this commandment differs between individuals depending on their own religiosity (Susilowati, 2010).

In order to protect the rights of Muslim consumers to obey their commandment in consuming only Halal products, certification institutions emerged in several countries around the world to provide certifications to different food, drinks and medicine products that it is free of haram components. One such institution emerged in Indonesia, under the MUI (Indonesian Ulama’ Assembly), called LPPOM-MUI. Halal certification from LPPOM-MUI is also recognized internationally (Republika Online, 2009).

The desire to comply to the commandment in consuming only Halal products could create consumer involvement and influence consumer’s purchase decision in choosing what product they consume. The Halal certification provided by LPPOM-MUI can provide these Muslim consumers with the assurance they can rely on. Thus, attention on the importance of Halal labeling in Indonesia is now growing. Halal-conscious consumer segment is getting bigger and the Halal Product Protection Act is being drafted (Sucipto, 2009).

Not only in Indonesia, the awareness for Halal certification among Muslim consumers in neighboring Muslim country of Malaysia is also growing and Muslim consumers are getting more sensitive to those issues (Sadek, 2001). Muslims in Malaysia are beginning to question and avoid products with no Halal certification, especially foreign products (Aliman and Othman, 2007). Understanding purchase behavior of Muslim consumer regarding Halal Labeling is therefore imperative for marketer doing business in a Muslim country.

In order to understand how the Halal certification label influence the behavior of Muslim consumers, a theoretical framework is necessary. Lada, Tanakinjal dan Amin (2009) discovered that the theory of reasoned action (TRA) is applicable to explain the intention of Muslim consumers in Malaysia to choose products with the Halal label. TRA was developed by Fishbein and Ajzen to explain the psychological process in regard of how under the assumption that every conscious behavior starts from a behavioral intention, an individual’s beliefs about the outcome and the social pressures of a certain behavior would influence their intention to perform the said behavior thus influencing the behavior itself. TRA was further developed into the theory of planned behavior (TPB) by Icek Ajzen by adding a third belief to increase its domain of explanation (Ajzen, 2004). The third belief added was called Perceived Behavioral Control, which in essence is the self efficacy of the individual regarding a certain behavior.

Thus, the purpose of this paper is to test the applicability of the theory of planned behavior (TPB) in explaining how the Halal certification label influence the behavioral intention of Muslim consumers within a wide array of purchase context, especially in the purchase of food, drink and over the counter medicine products in Indonesia. There are two behavioral intention of the Muslim consumers in which the model will be tested, one is the intention of Muslim consumer to seek information regarding the Halal certification of a certain product (i.e. looking for it in the packaging; asking the proprietor, etc.) and the other is the intention to cancel the purchase of certain products without Halal certification labels.

B. Methodology

Research Design

This research is designed as a quasi experimental research using the policy capturing method. Kline and Sulsky (1995) elaborate the main research question in policy capturing studies: “What decision would individuals take with the available information?” Policy capturing is performed by exposing the respondent to a series of stimulus in the form of situational scenarios and measuring their response for each scenario. Researchers would then use regression analysis to measure the effect of each stimuli to the response measured (Aiman-Smith, Scullen & Barr, 2002).

This method is more commonly used in the field of human resources, such as researches in how personal and organizational characteristics influences recruitment and selection process (Graves, & Karren, 1992), performance appraisals and reward allocation decisions and satisfactions (Hobson & Gibson, 1983; Beatty, McCune, & Beatty, 1988; Deshpande, & Schoderbek, 1993; Zhou & Martocchio, 2001; Hu, Hsu, Lee & Chu, 2007; Law & Wong, 1998; Barclay & York, 2003) or how job-seeker chooses the company they intend to work in (Aiman-Smith, Bauer & Cable, 2001; Williamson, Cope, Thompson & Wuensch, 2002; Slaughter, Richard & Martin, 2006).

Policy capturing is also used in marketing research, even though much less often, such as in consumer product selection (Brinberg, Bumgardner & Daniloski, 2007). In this research, policy capturing is used to capture the decision of consumers to seek information regarding Halal certification of a certain product and to cancel the purchase if no Halal certification is found.

Population and Sampling of Respondent

This research uses quasi-experimental design in which internal validity is more paramount than external validity, thus probabilistic sampling design is less essential to the methodology. Subjects were recruited using non probabilistic cluster sampling from the Muslim undergraduate students currently studying in the University of Indonesia. During the data collection period, 150 subjects were recruited to participate in the data collection. All subjects recruited were participating voluntarily in this research.

Data Collection

The data used in this research was gathered in a period of five days, between 5th and 9th July 2010. Data collection was conducted by two assistant supervised by a researcher. Data collection was performed by giving each subject a set of questionnaire consisting of 4 questions about subject profiles, 20 items measuring individual beliefs, 17 items measuring actual Halal literacy, 10 scenarios measuring Halal information seek intention, and 40 scenarios measuring purchase cancel intention. Verified questionnaires were then inputted to Microsoft Excel for further analysis using advanced statistical tools. The list of variables used in the questionnaire is displayed below.

Table 1: List of Variables and Their Operationalization

Independent Variables Operationalization
X1= Attitude toward Halal Compliance : Individual belief about the personal evaluation regarding the good compliance to the commandment about Halal consumption
X2= Subjective Norms regarding Halal Compliance : Individual belief about the social expectations regarding the good compliance to the commandment about Halal consumption
X3= Perceived Behavioral Control : Individual belief about the sufficiency of resources required to perform good compliance to the commandment about Halal consumption
X4= Actual Behavioral Control : Actual sufficiency of resources required to perform good compliance to the commandment about Halal consumption
Situational Variables Operationalization
X5A= Origin of the Product Imported or local product
X5B= Halal Labels Non-MUI* Halal label or no Halal label
X5C= Availability of Alternatives The availability of alternative product with the MUI Halal certification
Dependent Variables Operationalization
Y1= Halal Info-Seek Behavioral Intention Behavioral intention to seek information regarding the existence of Halal certification of a product
Y2= Halal Switching Behavioral Intention Behavioral intention to cancel purchase if no Halal label is found

*) Non-MUI Halal label is every Halal labels that came from the producer or other institution without the certification of MUI or accredited Halal certification institution.

C. Data Analysis

The method of analysis employed to test the hypotheses in this research is Multi-group Structural Equation Modeling (MG-SEM) using LISREL for WINDOWS 8.51 Full Version (Jőreskog dan Sőrbom, 2001). Structural Equation Modeling is an analysis method employed to test structural models that depicts structural relationships between latent constructs. Multi-group analysis is employed to compare model fitness and path coefficients of the structural model between groups of observation. In this case, the model will be compares across different product context.

Measurement Model

Testing the construct validity of the measurement used in this research is the first step of analysis required before the structural model can be tested. Good construct validity of the instrument must be established before any conclusion about the causal relationship among constructs can be determined.

The initial measurement model yields a chi-square value of 740.36 with degree of freedom as much as 588, thus a p-value of 0.00002 was obtained. This result showed a non-valid model and was modified in order to improve the chi-square. One item from Subjective Norms and nine items from Actual Behavioral Control were found not valid and excluded from the instrument. Modifications include adding error covariance between several items. There were two pairs of error covariance added between three items in the Attitude construct, while two pairs of error covariance were added between four items in the Perceived Behavioral Control construct.

The improved measurement model obtained from the modification yields a chi-square value of 246.08 with degree of freedom as much as 220, thus a p-value of 0.10961 was obtained. This result showed a valid measurement model and further analysis on the structural model can be resumed. The final valid measurement model is shown below.

Figure 1: Path Diagram of the Valid Measurement Model

Multi-Group Structural Model

The first hypothesis is that TPB can be applied to the behavioral intention to seek information (Y1) regarding the existence of Halal certification of a product for five different product contexts. The structural model testing yields a chi-square value of 2436 with degree of freedom as much as 1400, thus a p-value of 0.0000 was obtained. This result showed a non-valid model. This result is not usable, however, because the number of observation used in this testing is large (n=1500). Chi-square was found to be overly sensitive bias toward large number of n, thus even a very small number of chi-square could be rejected (Meuleman and Billiet, 2009). Thus, for model fit testing with large number of observation, RMSEA would be more reliable as measurement of fit. The structural model yields RMSEA of 0.050, thus because the RMSEA value is lower than 0.8 the structural model is considered to have good model fit. Summarized path coefficients and the path diagram of the structural model are shown below.

Table 2: Summarized Path Coefficient of Structural Model Y1

PROD1 PROD2 PROD3 PROD4 PROD5
X1 à Y1 SLF 0.50 0.47 0.65 0.71 0.45
T-Val 2.53 2.38 3.30 3.60 2.31
X2 à Y1 SLF 0.02 0.09 -0.02 -0.07 0.03
T-Val 0.11 0.46 -0.12 -0.34 0.14
X3 à Y1 SLF -0.23 -0.28 -0.27 -0.44 -0.27
T-Val -2.47 -3.00 -2.78 -4.54 -2.89
X4 à Y1 SLF 0.14 0.23 0.14 0.06 0.15
T-Val 1.64 2.75 1.70 0.68 1.77
X5A à Y1 SLF 0.01 0.00 -0.02 -0.07 0.18
T-Val 0.17 0.03 -0.31 -0.82 2.26
X1 à X3 SLF 0.32 0.32 0.32 0.32 0.32
T-Val 4.14 4.15 4.12 4.16 4.13
X4 à X3 SLF -0.07 -0.07 -0.07 -0.07 -0.07
T-Val -1.14 -1.14 -1.15 -1.15 -1.15

Figure 2: Path Diagram of Structural Model Y1

The second hypothesis is that TPB can be applied to the behavioral intention to cancel purchase if no Halal label is found (Y2) for five different product contexts. The structural model testing yields a chi-square value of 9158.72 with degree of freedom as much as 1619, thus a p-value of 0.062 was obtained. This result also showed a non-valid model. However, because the number of observation used in this testing is also large (n=6000) the chi-square result can also be ignored and substituted with RMSEA as explained in the above. Thus, the structural model yields RMSEA of 0.062, thus because the RMSEA value is lower than 0.8 the structural model is considered to have good model fit. Summarized path coefficients and the path diagram of the structural model are shown below.

Table 3: Summarized Path Coefficient of Structural Model Y2

PROD1 PROD2 PROD3 PROD4 PROD5
X1 à Y2 SLF 0.21 0.19 2.15 0.19 0.25
T-Val 2.51 2.22 8.77 2.21 2.88
X2 à Y2 SLF 0.18 0.25 -1.31 0.25 0.21
T-Val 1.89 2.58 -14.03 2.67 2.20
X3 à Y2 SLF -0.15 -0.20 -0.25 -0.18 -0.22
T-Val -3.79 -4.95 -5.01 -4.30 -5.28
X4 à Y2 SLF 0.12 0.15 0.12 0.10 0.16
T-Val 3.56 4.46 2.85 3.00 4.73
X5A à Y2 SLF -0.01 -0.02 -0.06 0.00 0.08
T-Val -0.43 -0.47 -1.32 0.05 2.16
X5B à Y2 SLF -0.45 -0.40 -0.49 -0.37 -0.43
T-Val -13.08 -11.44 -11.73 -10.57 -12.26
X5C à Y2 SLF 0.30 0.26 0.25 0.31 0.25
T-Val 8.55 7.56 5.89 9.03 7.10
X1 à X2 SLF 0.65 0.65 1.24 0.65 0.65
T-Val 11.37 11.36 8.24 11.37 11.38
X2 à X3 SLF 0.31 0.31 0.30 0.31 0.31
T-Val 8.08 8.08 7.92 8.09 8.05
X4 à X3 SLF -0.06 -0.07 -0.06 -0.06 -0.06
T-Val -2.07 -2.09 -1.95 -2.07 -2.07

Figure 3: Path Diagram of Structural Model Y2
D. Discussion and Conclusion

Based on the result of data analysis above, each structural model are valid in explaining their respective behavioral intentions. However, the analysis shows that different path coefficients exist between product categories and some path coefficients are even consistently insignificant across product categories.

The structural model for Y1 shows that Attitude (X1) is consistently significant in explaining behavioral intention (Y1) across product categories. Subjective Norms (X2), however, is consistently not significant in explaining behavioral intention (Y1) across product categories. Thus, the hypothesis that X2 influences Y1 is rejected outright. On the other hand, even though Perceived Behavioral Control (X3) is consistently significant in explaining behavioral intention (Y1) across product categories, the coefficient is negative. This negative sign is contrary to the theoretical framework thus this hypothesis is also rejected.

One possible explanation is that Perceived Behavioral Control, as the individual belief about the sufficiency of resources required to perform good compliance to the commandment about Halal consumption, is subjective. Thus it may be possible for individuals to overrate or underrate their own behavioral control. This explanation is also supported by the structural model. The structural model for Y1 shows that Attitude (X1) is consistently significant in explaining Perceived Behavioral Control (X3), while the Actual Behavioral Control (X4) is consistently not significant in explaining Perceived Behavioral Control (X3). This shows that individual perceived their behavioral control based on their attitude and not their actual capabilities. This bias would create overconfidence in individuals that increase their tendency to underestimate the importance of Halal label certification.

The structural model comparison for Y1 shows that differences of path coefficients exist between product categories. The path of Actual Behavioral Control (X4) in explaining behavioral intention (Y1) is only significant for Vegetable based Foods products, while the path of Product Origin (X5A) in explaining behavioral intention (Y1) is only significant for Fast Food Franchises.

The structural model for Y2 shows that Attitude (X1) is also consistently significant in explaining behavioral intention (Y2) across product categories. Subjective Norms (X2), however, is inconsistent in explaining behavioral intention (Y2) across product categories. X2 is only significant in explaining behavioral intention (Y2) for Vegetable based Foods, Over the Counter Medicines and Fast Foods Franchises while not significant for Animal/Meat based Foods and Packaged Beverages. Thus, the hypothesis that X2 influences Y1 is rejected because it can not be generalized over different product context.

Similar to the previous model, Perceived Behavioral Control (X3) also have consistently significant negative coefficient in explaining behavioral intention (Y2) across product categories. The previous explanation that individual tends to overrate or underrate their actual behavioral control is even further supported by the structural model.

The structural model for Y2 shows that Attitude (X1) is also consistently significant in explaining Perceived Behavioral Control (X3), while the Actual Behavioral Control (X4) have consistently significant negative coefficient in explaining Perceived Behavioral Control (X3). This shows that people with higher behavioral control may tend to underrate their own Halal literacy or people with low behavioral control may tend to overrate their own Halal literacy. Actual Behavioral Control (X4), however, have consistently significant positive coefficient in explaining behavioral intention (Y2). This finding further support the postulation that people with low Halal literacy tend to be overconfidence about their behavioral control and tend to underestimate the importance of Halal labels. This would negatively influence their behavioral intention to seek information regarding Halal labels and to cancel purchase if no Halal labels are found.

Similar to the Y1 model, the structural model for Y2 also shows that Product Origin (X5A) have positive significant coefficient in explaining behavioral intention (Y1) for Fast Food Franchises only. This shows that the impact of Halal label toward information seek and switching intention is greater for Fast food franchises, thus foreign franchises have greater importance in registering their product for halal certification than local franchises.

The interesting conclusion from structural model for Y2 is that Non MUI Labels (X5B) have consistently significant negative coefficient in explaining behavioral intention (Y2). This shows that even Halal labels without certification from the legitimate institution still have significant influence in reducing the switching intention of Muslim consumers. This could be dangerous if irresponsible marketer put Halal labels on product that contain haram substances.

On the other hand, the existence of alternative product with Halal label (X5C) would significantly increase the intention of Muslim consumer to cancel purchases in no halal label is found (Y2). This could be an important opportunity for competing products that wants to attract new customers and capture the market share of existing products that have no halal labels. The existing products that have no halal labeling would also need to cover this threat by certifying their own product to prevent the loss of market share because of this halal issue.

It can be concluded from the discussion above that Ajzen’s Theory of Planned Behavior is not fully applicable to explain the behavioral intention of Muslim consumers to seek information regarding Halal label (Y1) and to cancel purchase if no Halal label is found (Y2). Even though the structural models have good fit, differences in magnitude and significance of causal relationships exist between different product categories.

This shows that regarding the impact of halal labels, the same person might have different behaviors across different product categories. Thus further testing would be required to inquire whether the model can be generalized to wider context of products. Modifications to the model would also be of use, by adding multiple attitudes and behavioral control variables to explain behavioral intention. Further research on the negative effect of perceived behavioral control should also be of academic value.
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Appendix 1: Sample Questions for Independent Variables

Independent Variables Sample Questions Scale
X1= Attitude toward Halal Compliance Flesh that grows from foods and drinks that are haram (forbidden) will be touched by the fires of Hell 5 point Likert Scale
X2= Subjective Norms regarding Halal Compliance It is mandatory for every Muslim to check the halal certification  before they consume something 5 point Likert Scale
X3= Perceived Behavioral Control I am capable in identifying which product is halal and which product is haram 5 point Likert Scale
X4= Actual Behavioral Control To dine in restaurants that also serve alcohol is… True-False

(Halal-Haram-Don’t Know)

Appendix 2: Sample Policy Capturing Questions

Y1 Y2
Halal Info-Seek Behavioral Intention Halal Switching Behavioral Intention
If you are going to purchase a certain imported meat-based food product, how likely are you to check whether the product you are going to purchase have halal certification? If it so happens that the product that you are going to purchase have no halal certification, while alternative product with halal certification is available, how likely are you to cancel your intended purchase?
* *

Appendix 3: Descriptive Result of Responses Grouped By Categories

Y1: Halal Info-Seek Behavioral Intention

Product Meat-based Veggie-based Beverages OTC Meds Fast Foods
Imported? Yes No Yes No Yes No Yes No Yes No
Average 5.78 5.82 5.52 5.57 5.65 5.82 5.48 5.47 5.92 5.70
Std-Dev 2.00 1.87 2.00 1.99 1.97 2.85 2.05 2.06 1.90 1.91
n 150 150 150 150 150 150 150 150 150 150

Y2: Halal Switching Behavioral Intention

Product Meat-based Veggie-based Beverages OTC Meds Fast Foods
Imported? Yes No Yes No Yes No Yes No Yes No
Average 6.17 6.13 5.77 5.76 5.74 5.80 5.47 5.63 6.27 5.84
Std-Dev 1.57 1.65 1.84 1.85 1.79 1.78 1.94 1.93 1.63 1.71
n 600 600 600 600 600 600 600 600 600 600

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