Study of Porang Rice Purchase Intention: Moderating Role of Price Sensitivity

Study of Porang Rice Purchase Intention: Moderating Role of Price Sensitivity

Fitria Dwi Puspita^1*, Abdul Wahib Muhaimin², Silvana Maulidah³

¹Postgraduate of Agribusiness, Universitas Brawijaya, Malang, Indonesia

^2,3Department Socio Economics, Universitas Brawijaya, Malang, Indonesia

*Corresponding Author

DOI: https://dx.doi.org/10.47772/IJRISS.2024.801194

Received: 29 December 2023; Revised: 08 January 2024; Accepted: 11 January 2024; Published: 24 February 2024

ABSTRACT

Food diversity become a way to gain food stability. Indonesia needs to diversify its staple food to gain food security. Porang rice as the analog rice can be a healthier paddy rice alternative for its lower glycemic index. Its electronic word of mouth (eWOM) as online promotion marketing can affect consumer’s attitude which in turn affects porang rice purchase intention based on the Theory of Planned Behavior. This research aims to investigate the eWOM influence on attitude; and consumer’s attitude towards porang rice purchase intention; and test the moderating effect of a price sensitivity towards the relationship of attitude and purchase intention. 160 respondents’ data was collected through online questionnaires and then analyzed using structural equation modeling (SEM) Warp-PLS 7.0. The research results show a significant positive influence of eWOM on attitude, as well as attitude towards porang rice purchase intention. A price sensitivity doesn’t have a significant moderation effect on the relationship between attitude and purchase intention.c

Keywords: porang rice; purchase intention; Theory of Planned Behavior; price sensitivity; online customer review

INTRODUCTION

Indonesia has a high dependency on paddy rice as Indonesian staple food. The import of paddy rice keeps increasing yearly based on the 2020 report from BPS. The government tries to decrease its dependency by finding a local staple alternative to paddy rice, such as porang rice. To achieve food diversification, the government through the Food Security Agency of the Ministry of Agriculture is targeting a reduction in rice consumption of at least 1.5% per capita per year. However, based on data on developments in rice consumption from BPS in 2020, it is known that average rice consumption has only decreased by 0.73%. The Indonesian authorities have stated that Porang (Amorphophallus muelleri Blume) has an opportunity to be an Indonesian meals in the future [1]. Nowadays, porang which is a native Indonesian plant, is used as the main ingredient to produce analog rice.

Analog rice is an artificial rice that can be made of some type of starch flour such as Arrowroot (Maranta arundinacae L.), sago (M. sagu), (Gracilaria sp.) puree, and also porang [2] [3]. Indonesian people’s habit of consuming paddy rice causes the difficulty of people switching to new types of staple food. Analog rice can be used as an alternative to paddy rice because its shape looks like the grains of paddy rice [3]. Food diversification by increasing the consumption of porang rice can reduce the consumption of paddy rice. 40.6% of respondents are willing to consume porang rice as a diet menu, and 49.3% of respondents might be willing to consider Porang rice as a diet menu [1]. One of the obstacles to food diversification [4] is that non-rice food promotion is still limited. Consumers need the marketing information of analog rice products can be reached offline or online [5]. One of the strategy to increase customer interest by explaining the good quality of porang rice is by using social media and e-commerce as a promotional platform [6].

Indonesia’s majority productive age is the millennials who are close to digital media such as Instagram, YouTube, TikTok, etc. So, it would be more appropriate to introduce porang rice as an alternative staple food other than rice to this generation by using digital marketing communications, such as electronic word of mouth (eWOM). Consumer’s online discussion about some service, product, or brand on any social media contributes to eWOM [7]. 92% of consumers are looking for other reviews of a product (Online Customer Review/OCR) before they buy it. OCR in terms of eWOM helps increase consumer’s confidence and reduce their disappointment risks of products [8].

Indonesia as a developing country is sensitive to the product price [9]. Research within moderating variables is valuable in consumer behavior research as the dynamic socio-economic environment over time. In terms of the current study, very little research about porang rice, specifically in the context of marketing and consumer behavior research.

This research aims to gain better insight into (1) examining the influence of e-WOM OCR on consumer attitudes; (2) investigating the influence of attitude on porang rice purchase intention; and (3) exploring the role of price sensitivity in measuring porang rice purchase intention. The next section will be the literature review including the development of the research hypothesis, and then after the research methodology, there will be results and discussion followed by conclusion.

THEORETICAL FRAMEWORK

Online Customer Review

Electronic word of mouth (eWOM) is a part of marketing communication that can be either a positive or negative statement made by actual or potential customers on the internet as an open source for everyone [10]. Online customer review (OCR), as one form of eWOM, is an important part of e-commerce. When consumers want to buy something through e-commerce, they will need to find information about those products throughout OCR before making any purchase decision [11], [12]. Nowadays 92% of consumers read online reviews [13]. So, OCR can be defined as product evaluation made by consumers and then uploaded either to a company or third-party website such as e-commerce [14].

There are 3 commonly used as the antecedents of OCR. There are review quality, source credibility, and review quantity [15], [16]. Review quality and quantity are two antecedents of eWOM with the highest significant impact on eWOM [17], [18]. However, source credibility has an insignificant impact on eWOM [16], [19], [20]. Therefore, this study uses 2 variables of OCR characteristic, which are OCR quality and OCR quantity as shown in Fig.1.

Figure 1. Research Theoretical Framework

Theory of Planned Behavior (TPB)

TPB by [21] is one of the commonly used theory to elaborate consumer behavior. TPB can be used to predict whether someone will or will not perform a behavior, such as willingness to purchase or purchase intention. TPB can also explain consumer purchase behaviors [22]. TPB has 3 main variables, there are attitude, subjective norms, and perceived behavioral control. The attitude variable has the highest and significant impact towards foods purchase intention as in [23], [24]. Therefore, this study only uses attitude variable to represent TPB.

Elaboration Likelihood Model (ELM)

ELM is a model that explains the form of information persuasion, just like eWOM or OCR, where any different type of messages are able to influence the attitude and consumer purchase behaviors [25]. ELM becomes a helpful theory to elaborate on how OCR information processing can finally persuade a consumer at the end [26]. There are 2 processing routes of OCR. Argument quality, valence, relevance are processed in the central route, while source credibility, rating, consistency, and review volume are processed in the peripheral route [18]. Some studies also use ELM to learn about OCR persuasion [27]–[31].

OCR and Consumer Attitude

Through the Input-Process-Output of OCR, attitude is included in the output of OCR processing [26]. OCR as online persuasion can significantly change people’s attitudes [25], [32]. So, this research tries to examine the impact of OCR antecedents (Quality and Quantity) on consumer attitudes.

OCR Quality

eWOM information can be traced based on the argument quality [13]. OCR quality is the information clarity and relevancy to help customers interpret some products [33]. The quality of eWOM ensures that the information shared is valuable and trustworthy. In this research, OCR quality means the consumer’s perception of the OCR’s ability to provide accurate, relevant, and up-to-date information about porang rice. So, OCR can be measured by porang rice clarity information, detailed product description, attached photo or video, and negative product information [34], [35]. So, the first hypothesis of this research is:

H1: enhanced OCR quality enhances consumers’ attitude.

OCR Quantity / Quantity

OCR volume shows the review amount of a product. It’s not only the review amount but also the average evaluation score of a product. A higher volume of eWOM means more people are talking about a product and as social proof, indicating to potential customers that a significant number of people have had positive experiences with the product. Otherwise, a little extremely negative review will affect consumer’s trust (Mariani & Predvoditeleva, 2019). OCR volume objective is to minimize consumer risks of buying decisions (Yi & Oh, 2022). OCR quantity can be measured by the quantity or volume of OCR and OCR similarity to one another [36], [37]. Thus, the second hypothesis is:

H2: enhanced OCR quantity enhances consumer’s attitude.

Attitude and Purchase Intention

Many consumer behavior and marketing theories are used to examine the relationship between attitude and purchase intention. The Theory of Planned Behavior is the most popular one [21]. Consumers’ tendency to perform such behavior in this case as buying porang rice is influenced by their mindset [38]. So, attitude can be explained as a consumer’s positive or negative evaluation of performing the OCR reading before buying decision. Attitude and purchase intention show parallel relationships in some consumer behavior research areas [32], [39]–[42]. According to the research [43], consumer attitude that is influenced by social media influencers, also influence consumer purchase intention. So, the third hypothesis is:

H3: enhanced positive consumer attitude enhances porang rice purchase intention.

Price Sensitivity

Price has a significant impact on consumer evaluation towards some alternative products which will leads to affect consumer purchase intention [44]. Price has 2 roles in consumer assessment, which are as sacrifice in terms of money spent on certain products, and as information direction to the quality and status gained from product possession  [45]. The amount of product price fluctuation that influences consumer buying behavior is called price sensitivity [46]. Even if consumers show a positive attitude towards the environment, they might not buy eco-friendly products because of its price are higher than the traditional ones [47]. Based on the research of [48], when the organic product price is not more than 20% of the average price of agricultural commodities,  78% of the respondents have willingness to make a purchase. Study of [45] also shows the relationship between consumer attitude and purchase intention of green skincare is enhanced by the high price sensitivity. Indonesia as a developing country is sensitive to the product price [9]. Thus, the last hypothesis is:

H4: A price sensitivity moderates the relationship between consumer’s attitude and porang rice purchase intention

Research within moderating variables is valuable in consumer behavior research as the dynamic socio-economic environment over time. In terms of the current study, very little research about porang rice, specifically in the context of marketing and consumer behavior research.

METHODOLOGY

Data Collection and Sample

This quantitative research is explanatory research that aims to analyze causal relationships among two or more variables. Data for this research was gathered through an online survey in Google form. First, a pre-test questionnaire and review were conducted by 4 senior academics who are working in the consumer behavior area specifically in agribusiness. Some questions were modified based on their suggestion. The final questionnaire is distributed to the respondents of the research sample.

The research sample is working or married women aged 25-55 years old, who have buying experience through e-commerce (Shopee or Tokopedia), and also following @fukumi.id’s Instagram account. Fukumi is the producer and seller of porang rice in Indonesia. Research respondents were determined by non-probability sampling with the accidental sampling method. This research uses women as respondents because most family food-buying decisions were made by women. The sample size required was calculated by the inverse square root method [49]. Thus, this research uses 160 respondents as samples.

Measurement Development

The final questionnaire contains 2 segments. The first one collects respondent demographic information such as age, gender, marital status, and education as descriptive analysis. The second one was to measure construct items for hypothesis testing.

Independent variables of this research are OCR Quality and OCR Quantity. OCR Quality (OQL) consists of 4 items adapted from [34], [35]. 2 items measure OCR Quantity (OQN) [36], [37]. There are 2 dependent variables, consumer attitude (ATT) and porang rice purchase intention (PI).   ATT consists of 3 measurement items [27], [50], while PI uses 4 measurement items [50]–[52]. At the same time, price sensitivity (PS) as a moderating variable was measured by 1 item [45].

This research employs a 4-point Likert scale, where 1 = strongly disagree and 4 = strongly agree. There are two stages of analysis. The first one is analyzing the outer model to ensure the validity and reliability of each indicator. The second one is to analyze the relationship among latent variables. Data reliability was tested by using Composite Reliability and Cronbach Alpha. Convergent and discriminant validity were tested by Average Variance Extracted (AVE) and square roots AVE respectively. Collected data was analyzed using Structural Equation Modelling – Partial Least Square (SEM-PLS) with WarpPLS 7.0 software.

FINDINGS AND DISCUSSION

Respondent Characteristics

160 out of 169 accepted questionnaires from respondents fulfill sample criteria and can be analyzed. 100% of respondents are women as requested condition. 64% of respondents are in the age of 25-25 group, followed by the age of 36-45 and the age of above 45 as much as 31% and 5% respectively. 83% of respondents are married, and 17% of the respondents are single. The education of respondents is undergraduate, senior high school, postgraduate, and junior high school with respective percentages as follows 51%; 38%; 10%; dan 1%.

Reliability and Validity Assessment

The first stage is the evaluation of the research instrument’s reliability and validity. Table 1 presents the reliability tests (Composite Reliability and Cronbach alpha), while table 2 shows convergent validity tests (factorial loadings and AVE).

Table 1. Reliability Tests

The research uses 15 indicators for OQ, OQN, AT, PI, and PS. All of them show a loading factor >0.6 with Average Variance Extracted (AVE) for all variables above 0.5. Cronbach alpha gives a value above 0.6 and CR values for all variables are also above 0.7.

Table 2. Covergent Validity Test

Table 3 shows discriminant validity (square roots of AVE). Square roots AVE as the discriminant validity of each variable shows a higher value than correlation among other variables. Therefore, the research instrument can meet the requirement of convergent and discriminant validity, and also reliability.

Table 3. Discriminant Validity Tests

The next evaluation of the first stage is the model evaluation to ensure that the collected data suits the research model statistically. 3 commonly used  to test goodness of fit model based on [53] are average path coefficient (=0.349; P value <0.001); average R-Squared (= 0.404; p value < 0.001); and also average variance inflation factor (=1.302, ideally ≤ 3.3). next, to prove statistically that this research model has valid globally, needs to be evaluated through the index Goodness of Fit (GoF). GoF score on warpPLS is 0.548, which means the GoF is big because it is more than 0.36 [53]. So, it can be concluded that the research model (Fig.1) is feasible and good to be used to do the hypothesis testing.

Figure 2. Research Structural Model

Hypothesis Testing

Table 4 shows the relationship between OCR quality and quantity to Attitude. Both of them have a p-value under 5% and a positive path coefficient. So, H1 and H2 accepted, that enhancing either OCR quality or quantity will enhance the consumer attitude. As stated in Figure 1, the R-squared of Attitude is 46%. It means 46% of attitude variables can be explained by both variables OCR quality and OCR quantity, the rest 54% were influenced by variables other than this research model. The influence of attitude on purchase intention is also significant with a p-value <0.001, which means under 5%. Therefore, H3 is accepted, that enhancing attitude results in enhanced porang rice purchase intention. The R-squared of purchase intention is 35%. So, 35% of purchase intention variables can be explained by attitude variables, and another 65% comes from other variables outside this model. Hypothesis testing for the moderating effect of price sensitivity in attitude to purchase intention shows a p-value of 0.44, which shows insignificant influence. From the above hypothesis testing can be concluded that H4 is rejected.

Table 4. Hypothesis Testing

DISCUSSION

This research aims to examine how OCR quality and quantity as a form of eWOM, affect consumers’ attitudes and consequently affect porang rice purchase intention. Moreover, this research also studies the moderating role of price sensitivity on porang rice purchase intention. Researchers [17], [18] found OQL and OQN to be the most influential eWOM characteristics on consumers’ attitudes, therefore this research only uses OQL and OQN as OCR characteristics.

OQL and OQN significantly influence consumers’ attitudes. The role of OQL is similar to eWOM quality in many eWOM research [32], [54], which shows the significant positive related to consumers’ attitudes. A clear and understandable OCR with sufficient reason to support the main opinion will be very helpful to consumers [55]. Furthermore, OQL usually called eWOM volume, has found to be significantly positively affect consumers’ attitudes [56]. The higher number of reviews available for certain products, which are considered non-commercial public opinions, will lead the consumer to gain more confidence about those products [55]. Therefore, with a positive attitude, a greater porang rice purchase intention will be generated.

Path coefficient results show that OQL has more influence on attitude rather than OQN. It can be caused by the eWOM processing route as on the Elaboration Likelihood Model, where eWOM quality is in the central route. So, consumers need to perform complex cognitive information processing because OQL is related to the OCR content information [18], [26]. While OQN or eWOM volume is in the peripheral route of ELM, which is simpler and does not need cognitive processing [18]. This result is related to the respondent’s education level, where 51% of them are undergraduates. Based on [57] that postulated a higher someone’s education, enhances literacy skills. Moreover, this research employs 100% women as respondents, and based on research [58] about the relationship between gender and critical thinking skills, women are likely to have higher critical thinking skills.

This study indicates that consumers’ attitudes significantly affect purchase intention. This is similar to another research [32] that shows that consumers’ attitudes have influenced consumers’ tendency toward purchase intention. According to findings [56], [59], a positive attitude enhances the intention to perform not only purchasing but also performing any behavior. Another research [43] has found that attitude has the largest coefficient and has the most important effect on purchase intention among other variables of TPB.

The findings of the study also show that price sensitivity doesn’t have a significant effect on moderating the relationship between attitude and purchase intention, which is the same as [60] that showed for new customers, they are still unsure about the product quality, so they are not price sensitive. Similar to this study, focusing on new or potential consumers of porang rice who are still not really confident in porang rice quality. But this result is somewhat in contrast with [61] which revealed price as a dominating factor for new consumers. This study is also different from studies conducted [45], [46] that found that joint moderation of a price sensitivity influences purchase intention behavior.

CONCLUSIONS

In summary, this study empirically checked that OCR quality and OCR quantity of porang rice significantly and positively influence consumers’ attitudes. It is because the OCR, either as its quality of the review and the amount of the review can provide information needed by the potential buyer of porang rice. Thus the customer gains more confidence about the porang rice because of the OCR.

Furthermore, a more positive consumer attitude enhances porang rice purchase intention. This is because the customer who has positive attitude tends to perform such behaviour, in this case is purchase intention behaviour. Finally, potential consumer who has high attitudes doesn’t have price sensitivity influence as a moderating effect on the purchase intention. Because in this study, focusing on new or potential consumers of porang rice who are still not really confident in porang rice quality so they aren’t price sensitive.

LIMITATIONS

This research collects data from potential buyer only. Therefore, it is necessary to carry out a comparative analysis of the porang rice purchase intention between potential and experienced consumers.

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