Consumers' attitude and intention to purchase organic goods in Cambodia.

Kouy, Sothea ; Sangkumchaliang, Parichard ; Aditto, Satit 等

ABSTRACT

This research investigation was conducted in Phnom Penh City which is the capital of Cambodia to uncover the main aspects influencing the intention to buy organic goods. This was done through 456 structured questionnaires based on the pioneering integrated models of empirical work embracing seven major issues: ethical lifestyles, health consciousness, price perspective, food safety concerns, product attributes, product availability, and consumers' trust through factor analysis and multiple regression analysis. The results show that health consciousness is the foremost potential theme to target consumption; product availability and convenience significantly influence consumption known as the second prime mover. However, ethical lifestyles and food safety are less likely to provide a correlation between intention to buy and these factors while price has negatively affected intention. As such, it is clear that consumers believe organic goods are a premium products aimed exclusively at the wealthy. Thus, marketers should set up policy concerning health awareness and goods placement to generate more consumption volumes.

JEL Classifications: M310, Q130

Keywords: organic goods; multiple regression; intention to buy; Cambodia; Phnom Penh City

I. INTRODUCTION

In today's world there is ever increasing pressure to produce more food to feed the growing global population. In agriculture there is heavy use of chemicals to produce more output to fulfill market demand. To some it can seem an inevitable trend. Cambodia is no different in this aspect and has seen the proliferation of chemical fertilizers and pesticides in search of greater yields. Typically, around a hundred chemical pesticides are available on the market and farmers have used more than 3,200,000 liters per year (Cambodia organic agriculture association [COAA], 2009).

However, organically produced food--agricultural products grown without the use of chemicals and where animals are raised in more natural conditions, without regular use of drugs--offer many advantages to both producers and consumers in regards to healthy lifestyle, social benefits, animal welfare, environmental preservation and environmental friendliness. Organic vegetables provide numerous vitamins, minerals and anti-oxidants (Soil Association, 2013). There is global growth and widening interest in the sector. Even though sales of organic foodstuffs are relatively low, when compared to conventional products, they have continued to outperform the non-organic grocery market. Many consumers' around the world are willing to purchase organic food. The UK, Italy, Belgium, Denmark, France and Australia are mentioned in the following research papers: (Denver and Jensen, 2014; Dinnella et al., 2014; Fernqvist and Ekelund, 2014; Hoefkens et al., 2010; Janssen and Hamm, 2012; Kavaliauske and Ubartaite, 2014; Lobo et al., 2013; Michaelidou and Hassan, 2010; Ozguven, 2012; Pieniak et al., 2010; Schleenbecker and Hamm, 2013; Shafie and Rennie, 2012; Zanoli and Naspetti, 2002), while in Asia the number of researches on organic consumer is less, for example Thailand, Taiwan, and Malaysia (Chen, 2007; Hsu and Chen, 2014; Roitner-Schobesberger et al., 2008; Voon et al., 2011).

Recent research has reported organic food consumption intention among Thai-Cambodian cross-border consumers (Pomsanam et al., 2014). However, there is no research about organic consumers' intention to purchase organic goods in the Cambodian capital, Phnom Penh. The information about organic targets in Cambodia has been very limited in the scientific world, especially information regarding organic consumers' perceptions, which are still lacking; there is little evidence available since it is quite different in terms of demographic characteristics, education, standard of living, concepts, stereotypes and the cultural environment; therefore, further investigations are necessary.

The aim of this research is to uncover the main impact factors affecting organic consumers' purchasing power in Phnom Penh city based on the pioneering integrated models of Torjusen et al. (2001), Michaelidou and Hassan (2010), Voon et al. (2011), Shafie and Rennie (2012), Ozguven (2012), Lobo et al. (2013), Dinnella et al. (2014), Pomsanam et al. (2014), and Kavaliauske and Ubartaite (2014). The model and theory examines in depth the major effects of consumers' intention to purchase organic goods as following an ethical lifestyle, health consciousness, price perspective, food safety concerns, product attributes, product availability, and consumers' trust in purchasing organic goods.

II. LITERATURE REVIEW

The theory of planned behavior can explain and predict how behavior is formed. There are three different processes of behavior, behavior attitude, subjective norms, and perceived behavior control. The key premise is that if a person first plans to do something then they are more likely to do it (Ajzen, 1991; Fishbein and Ajzen, 2011). In the example of consuming organic goods, when a person perceives eating organic foods to be enjoyable and believes it to be beneficial intermingled with favorable members of that person's social group who already eat organic goods and have motivated the person to do likewise. Ultimately, if the person feels that he or she has the ability to meet the demand, the person will form a strong intention and are more likely to engage in that behavior.

Consumer behavior is the process of receiving information of goods, the circumstance to purchase, and deposing of goods or services (Blackwell et al., 2007). Based on previous research in Malaysia behavior attitudes were mapped out as follows: health concerns, environmental concerns, confidence in organic food, and quality of food. These factors were considerably significant on consumers' willingness to purchase. Moreover, most organic consumers declared that they bought the products with respect for health benefits, food safety, environmental anxiety, food components, appearance, and sensory attributes (nutritive value, taste, and freshness) (Shafie and Rennie, 2012). Regarding the scientific breakthrough in Taiwan based on regulatory focus theory carried out by Hsu and Chen (2014) confirmed that consumers' characteristics played an essential element in consumers' purchasing intention.

When considering organic food health becomes the initial image coming to mind in consumers' perception, but they might have different ideas of health regarding their experiences and level of information (Zanoli and Naspetti, 2002). According to the scientific work of Lobo et al. (2013) rising incomes, lifestyle, and growth of health awareness have driven organic demand. In Switzerland respondents reported that physiological health and consumer confidence were statically significant on willingness to purchase functional food (considered beneficial to health), especially in the older consumers (Siegrist et al., 2008); hence, to attract more consumers' interest in organic goods, information related to health and environmental benefits should extended widely (Kavaliauske and Ubartaite, 2014).

Lobo et al. (2013) reported that almost 50 percent of organic consumers are motivated by health. Manuela et al. (2013) also verified that health was highly appreciated by organic consumers besides quality, authenticity, and naturalness in food. In Italy, organic consumers also confirmed that they definitely appreciated the value of organic food. The results were very similar to the previous work of Zanoli and Naspetti (2002). Notwithstanding the health aspect, Michaelidou and Hassan' s (2010) research revealed that health benefit was less valued in raising consumption, but was positively significant in affecting consumer usage (Kavaliauske and Ubartaite, 2014). Based on the aforementioned literature discrepancy, this study hypothesized that consumers worry about their health, which has influenced positively on the intention to purchase organic goods.

Ethical concern is a basic issue comprising of product safety, health concerns, product composition, price, and product availability. It becomes the priority reason in organic food consumption where people consider healthy and environmentally friendly food (Kavaliauske and Ubartaite, 2014). About 23 percent of consumers consider that consumption of organics will enable them to help and protect the environment as well as encouraging local produce (Lobo et al., 2013). Notably, consumer personality traits were examined to significantly affect consumers' ethical beliefs with regard to 545 Taiwanese consumers (Lu et al., 2015). Referring to an empirical investigation about consumers' attitudes toward organic food in Bangkok defined that environmental friendliness was the major driver to the purchase of organic food, and became a hot topic for them (Roitner-Schobesberger et al., 2008). To sum up, favorable factors toward organic goods are likely to be positive and strengthened with a sympathetic ethical lifestyle. There is a discrepancy here. It is therefore hypothesized that consumers' ethical issues have a noteworthy impact on the intention to buy organic goods.

Price is a fundamental matter, it has a higher correlation with consumers' intention to purchase (Ozguven, 2012). Presumably, consumers are willing to pay a premium price depending on their experience or purchasing frequency (Janssen and Hamm, 2012). It does not really matter to organic consumers since they consider organics to be affordable (Kavaliauske and Ubartaite, 2014). In principle, consumers have high expectations regarding the superiority of organic over non-organic produce, meaning they do not mind paying a higher price (Denver and Jensen, 2014). Certainly, pro-organic consumers are willing to pay higher prices due to the perceived health and nutritional benefits. In contrast disinclined consumers are reluctant to buy organic on account of the additional price and unclear information about labeling. Organic skeptics moreover still have doubts about the price (Lobo et al., 2013).

Shafie and Rennie (2012) in their paper concerning consumer perception towards organic food suggest that price has negatively affected consumption. In spite of the problematic expense, organic consumers continue to pay premium prices in terms of perceived organic benefits while non-organic consumers do not because they believed that buying and eating organic fare does not make any difference (Roitner-Schobesberger et al., 2008). As a result, this research has assumed that price impacts significantly on the intention to buy organic goods.

Food safety encompasses consumers' concerns over healthiness, natural farming methods, clean and chemical free food. Ethically produced food raises consumers' awareness and perception of purchasing organic produce (Lobo et al., 2013). Indeed, more than 50 percent of consumers worry about pesticide residue on the food they purchase while 10 percent are extremely concerned about genetically modified organisms (GMOs). The majority consumers of organic food are concerned about freshness and taste (Roitner-Schobesberger et al., 2008). Kavaliauske and Ubartaite (2014) have observed that consumers pay attention to product composition. Some consumers of organic food worry, not only about this issue, but also production methods, labeling, and insufficient information which can force them to avoid organic produce (Roitner-Schobesberger et al., 2008).

According to the previous work in Izmir realized that organic consumers seemed not fully trust organic benefits such reducing stress and weight even they had consumed organic produce. Further results minimized the view that consumers purchased it in accordance with low chemical residue, high quality and food safety. Among these factors, quality was the highest correlation (Ozguven, 2012). In line with this, food handling practices and food safety public concerns, recommended that food safety information should be published intensively to local people (Ergonul, 2013). In this regard, this research is formalized on the hypothesis that consumers' worry about food safety has a positive impact on consumers' intention to buy organic goods.

Product attributes (credence attributes) comprising of search attribute (price and color) and experience attribute (taste and durability) have been paid much attention (Janssen and Hamm, 2012). With regard to 637 Danish consumers proved that tastiness of organic food was known as the main attribute, and consumers evaluated positively in regard to color (Denver and Jensen, 2014). Consumers are looking for either tasty or nourishing products (Zanoli and Naspetti, 2002). In addition, there is a value placed on food appearance and labeling (Ozguven, 2012). Recent research on the sensory attributes and consumer traits for freshness in Italy detected that consumers valued highly the freshness of salad, its shelf life, as well as the appearance (Dinnella et al., 2014). This was confirmed by Ogden (2011), who presented that food appearance, odor, and taste were known as sensory properties and were an important tool to determine consumers' choice. Therefore, it is hypothesized product attribute has a significant impact on the intention to buy organic goods.

Shafie and Rennie (2012) illustrate that the availability of food can push and pull consumers' purchasing power. Blackwell et al. (2007) have ascertained that product availability is the main thrust for organizations to reinforce their sales. Hence, this research hypothesized that product availability has significantly influenced consumers' intention to buy organic goods.

To push consumers in selecting one product, consumers need to be aware of the product, trust, standards and control systems. Consumers will place more faith in the provenance of the product if there is a government organic certification, due to subjective knowledge rather than objective fact (Janssen and Hamm, 2012). Consumers generally have poor understanding about labeling, but they tend to trust it in cases where the government is involved in a certification system (Ergonul, 2013; Schleenbecker and Hamm, 2013). The studies of Janssen and Hamm (2012) and Ergonul (2013) also suggest that consumers' trust organic labels rather than none and governmental logos on products will attract a premium price tag. Mostly, consumers believe in product labeling, media, product quality, and company reputation because putting an organic label is not restricted (Voon et al., 2011). Hsu and Chen (2014) note that market messages might raise consumption patterns such as promotions, trust propensity, and self-confidence. Further results showed that communication messages had a great effect on consumers' intention to purchase in case match their regulation. The main effective media such as TV and radio might assist in distributing information to consumers because consumers' understanding about organic logo certification of each product is limited (Lobo et al., 2013). This research hypothesizes that trust has a positive impact on consumers' intention to purchase organic goods.

A. Conceptual Framework

The purpose of this work is to examine the motives that define the intention to purchase organic goods in Phnom Penh, Cambodia. The aforementioned extensive scientific work has identified several factors leading to the purchase of organic goods namely health consciousness, ethical lifestyle, product attributes, product availability, price perception, food safety concerns, and consumers' trust as shown in Figure 1 below.

[FIGURE 1 OMITTED]

Conceptual framework

B. Research Hypotheses

H1: Consumers health concerns influence the intention to purchase organic goods.

H2: Consumers' ethical issues have a positive significant impact on the intention to buy organic goods.

H3: Price has impacted significantly on the intention to buy organic goods.

H4: Consumers' worries about food safety have positively influenced the intention to buy organic goods.

H5: Product attributes have impacted significantly on the intention to buy organic goods.

H6: Product availability has influenced significantly consumers' intention to purchase.

H7: Trust has impacted positively on consumers' intention to purchase organic goods.

III. METHODOLOGY

A quantitative survey associated with convenient sampling was done between June 2015 and July 2015 in Phnom Penh metropolis. Before obtaining data, an English version of the questionnaire was revised and translated to Khmer and vice versa, and the surveyors were trained to administer questionnaires beforehand. Four hundred and fifty-six Khmer revised questionnaires were distributed to respondents randomly outside a supermarket--purposive sampling in accordance with an unknown population (Ary et al., 2006; Cochran, 1963).

The target respondents of this study were the consumers who had previously bought or heard about organic goods and were willing to help based on their interest and availability. Consumers who had never heard of organic goods were excluded. In return for completing the survey, data providers received a bar of soap as a 'thank you'.

The questionnaires consisted of thirty questions measured in a 5 point Likert scale as 1 = strongly disagree to 5 = strongly agree. A modified statement version was developed through comprehensive literature searched from Torjusen et al. (2001), Michaelidou and Hassan (2010), Voon et al. (2011), Shafie and Rennie (2012), and Dinnella et al. (2014). The model specification comprised mainly of one endogenous-(intention to purchase (IT), 5 statements were measured) and seven exogenous variables (consumers' ethical lifestyle (EL), 4 statements were measured, health consciousness (HC), 3 statements were measured, price perspective (PP), 3 statements were measured, food safety concerns (FS), 4 statements were measured, product attribute (PA), 4 statements were measured, product availability and convenience (AC), 3 statements were measured, and consumers' trust (CT), 4 statements were measured).

Pertaining to pilot questionnaires, 30 items were developed based on 89 online respondents. Cronbach's Alpha showed that all the items were highly reliable, so the final questionnaire retained all 30 items. Finally, the data collected in structured questionnaires were preceded with exploratory factors analysis, reliability analysis, bivariate analysis, and multiple regression analysis using Statistical Package for Social Sciences (SPSS) version 22.

IV. Results and Discussion

Preliminary analysis and research instruments were scanned for completeness and abnormal pattern of respondents. Then raw data were carefully converted into a database. Afterward, univariate descriptive statistics were screened data. In addition, all statements were valued by a 5 point Likert-scale. If the mean value of expression was more than 3, it represented that respondents agreed with that statement. Among 30 statements, the mean of those ranged from 3.03 to 4.27 above midpoint, it can be implied that the respondents totally agree with all statements. Additionally, the standard deviations ranged 0.859 to 1.095 demonstrating that respondents' views match each other. They have similar views on these ideas and their values of choice are consistent.

Priority, principal component analysis was undertaken with 30 variables to lessen the dimensionality of a large number of variables to fewer numbers of latent variables, and varimax rotation was executed. According to "a rule of thumb," about 456 samples provide good reliable factors. The scree plot also demonstrated the eight dominant factor solutions necessary to explain each scale, which were labeled as follows: (1) intention to purchase (IT), (2) health consciousness (HC), (3) consumers' ethical lifestyle (EL), (4) price perspective (PP), (5) food safety concerns (FS), (6) product attributes (PA), (7) product availability and convenience factor (AC), and (8) consumers' trust (CT). With respect to Bartlett Test of Sphericity was significant ([[chi].sup.2] (435) = 4505.406, p<0.0001), which indicated the strength of the relationship among latent variables simultaneously while Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy valued of 0.8 as meritorious was greater than 0.6, which exceeded the recommended threshold value for a satisfactory and acceptable factor analysis to proceed (Tabachnick and Fidell, 2001). All communalities extraction scores were loaded from 0.4 to 0.7 considered to be loading on factor and mostly were more than 0.5 was desirable. These factor solutions with eigenvalues greater than one which exceeded the acceptance criteria were explained by eight factor solutions was 62 percent of total variance which was loaded exceed the 50 percent minimum threshold and was satisfactory in social science work (Hair et al., 2006).

Reliability analysis was carried out with all variables both independent and dependent variables running independently with respect to factor solutions. The statistical reliability of the scales were undertaken entirely on the items by indicator of Cronbach's alpha coefficient ([alpha]) and Cronbach's alpha if item deleted. According to item analysis results, all eight dimensions Cronbach's alpha coefficient ranged from 0.6 to 0.8 which was reliably loaded more than the threshold of 0.5, it was concluded all Cronbach's alpha coefficient ([alpha]) and Cronbach's alpha if item deleted score indicated the variable scales were acceptably reliable and valid for further inferential analysis.

According to Pearson product-moment correlation coefficient between consumers' intention (IT) and its drivers were HC, EL, PP, FS, PA, AC and CT, respectively measuring the closeness of the relationship between variables, as shown in Table 1. Shortly after calculating the correlation of the scale dimension, correlation matrix showed that the IT dimension was statically significant correlated between HC, EL, PP, FS, PA, AC, and CT dimension at 0.01 level. HC had the greatest correlation on intention to purchase (r= 0.479) than other dimensions while the second ordered Pearson correlation was FS (r=0.465). The other component, 0.438 Pearson correlated between IT and EL, 0.169 Pearson correlated between IT and PP, 0.329 Pearson correlated between IT and PA while AC and CT were 0.452 and 0.430, accordingly. Further results show that all correlation dimensions were more than 0.3, which was a positively moderated correlation between independent and dependent variables. Based on the correlation matrix, there was no problematic multicollinearity since all independent variable correlations were not loaded more than the criteria point of 0.9 where extremely high correlation between independent variables were seen.

To verify multicollinearity with correlation matrix, Variance Inflation Factors (VIF) and tolerance scores were constructed, as shown in Table 2. Results showed that VIF dimensions were less than 5 (MAX VIF= 1.572), and tolerance levels were more than 0.6, which was larger than the 0.3 minimum threshold, so there was no indicative of problematic collinearity occurring between independent variables (O'brien, 2007).

After running correlational analysis, the initial step in multiple regression was undertaken on bivariate analysis conducted by scatter diagrams between independent variables and dependent variable, which showed visually the shape and degree of closeness. Then, a multiple linear regression was calculated to predict consumers' intention to purchase organic goods (IT) with respect to health consciousness (HC), ethical lifestyle (EL), price perspective (PP), food safety concerns (FS), product attributes (PA), product availability and convenience (AC) and consumers' trust (CT).

Multiple regression analysis confirmed that a significant regression equation was found (F (7, 394) = 41.941, p<0.0001) with coefficient of determination ([R.sup.2]) of 0.427 this being a measure of the goodness of fit for a linear regression model. It indicated that 42 percent of the variability of consumers' intention to purchase (IT) was explained by HC, EL, PP, FS, PA, AC, and CT dimensions using this model. However, there was no linear relationship between PP and consumers' intention (IT) (t= -1.062, sig=0.289 > 0.05); therefore, Hypothesis 3 is rejected. The result suggests that price perspective negatively affected consumption. Whenever prices increase, the level of consumption will decrease as demand law specifies. The result in this study confirms with the work of Shafie and Rennie (2012) that price has an adverse direction on consumption. Product attribute (PA) was not statistically significant (t= 0.765, sig= 0.445> 0.05), consequently Hypothesis 5 is rejected. Therefore, a new phenomenon model was reformed by multiple regression, excluded PP and PA components.

A new significant regression equation was found (F (5, 396) = 58.502, p<0.0001) indicating that independent variables affected the dependent variable, as shown in Table 3. Pertaining to coefficient of determination ([R.sup.2]) of 0.425, this is measured as the goodness of fit for a linear regression model. It indicated that 42 percent of the variability of consumers' intention to purchase (IT) was explained by HC, EL, FS, AC, and CT variables using this model ([R.sup.2]=0.425, adjusted [R.sup.2]= 0.418). Therefore, 58 percent of the variation in the amount of consumers' intention to purchase was not explained by this model using these variables. According to Durbin-Watson values of 1.70 were between 1.50 and 2.50 threshold, so there was again no correlation between independent variables.

In this research, it was entirely expected that [R.sup.2] value (coefficient of determination) will be low since this research field is an attempt to predict human intention or behavior. Typically [R.sup.2] values will be lower than 50 percent in that people are simply too diverse to forecast than for example a physical process. In social science, coefficient of determination is acceptable at 0.20 to 0.30. The predictor variables are statically significant at 1 percent. Hence, multiple regressions can draw a vital conclusion about how variations in the predictor values are associated with changes in the response values. Regardless of [R.sup.2], the significant coefficient still embodies the mean changes in the response for one unit change in the predictor whereas holding other predictors in the model constant; this sort of statistic can be extremely valuable.

Therefore, based on this multipara metrical equation of consumers' intention to purchase organic goods is seen below, where those variables were coded as a 5 Likert scale:

IT = 0.575 + 0.217HC + 0.147EL + 0.137FS+ 0.170AC + 0.169CT

Consumers' intention to purchase increased 0.217 unit of each unit of health conscious (HC) (t= 5.251, p=0.0001) was positively statistically significant at 1 percent level. This denoted that the majority of Cambodian consumers are extremely concerned with their health; along with economic growth in the country in the last decade. Therefore, Hypothesis 1 is confirmed as empirical research of Lobo et al. (2013), which found that consumption in respect to health became the prime mover. In addition, Zanoli and Naspetti (2002) declared that consumers were more likely to rate the value of organic food than non-organic.

In addition, ethical lifestyle (EL) coefficient was positively and significantly correlated with intention weighed 0.147 unit (t=3.429, p=0.001). This implies that consumers who care about an ethical lifestyle are more likely anxious about the product whether it has an effect on the environment or not. Therefore Hypothesis 2 is confirmed. The result is consistent with Lobo et al. (2013) who reported that consumers thought that they could help conserve the environment and prevent destruction by choosing organic food. Outstandingly, ethical belief was found as another prime motivator to stimulate intention to buy organic goods (Lu et al., 2015).

Food safety concerns (FS) weighed 0.137 unit (t=3.146, p=0.002) was positively significant at 1 percent, which indicated that respondents were more likely to worry about the food element, food processing and be more interested in the quality of food. As a result, Hypothesis 4 is accepted. This result aligns with previous work confirmed by many researches that issues of food safety were important to consumers (Ergonul, 2013; Lobo et al., 2013; Roitner-Schobesberger et al., 2008).

In addition, product availability (AC) weighed 0.170 unit (t=4.747, p=0.0001) was positively significant at 1 percent. It can be replicated; therefore, Hypothesis 6 is accepted. In the Cambodian context, the intention to buy organic goods is identified predominantly by a positive attitude of consumers toward availability. Consumers, typically, are very busy, so they may think about the economic standpoint (eco-conscious) where they can spend less time and travelling costs to get the high-end goods they want. Consequently, the closer the shop, the more purchasing frequency occurs. This fundamental finding corresponds with Shafie and Rennie (2012) and Blackwell et al. (2007).

Consumers' trust (CT) weighed 0.169 unit (t=4.380, p=0.0001) was positively significant at 1 percent. The result suggests that trust worthiness plays an important role in enhancing consumption. Thus, it can be concluded that Hypothesis 7 is accepted; as the vast majority of academic research worldwide has recently found. A previous study of Janssen and Hamm (2012) reported that consumers were more likely to pick organic food with certified labels rather than unmarked. This result is similar to the finding of Roitner-Schobesberger et al. (2008) who announced that the presence of a third party certified label together with organic goods would raise consumers' confidence and subsequent consumption.

Consequently, each addition of HC leads to an increase of the IT by 0.217 unit holding other variables constant. If EL increases one unit, IT increases by 0.147 units holding other variables constant. For each 1 unit increase in FS, consumers were expected to increase their purchasing intention of 0.137 units. For each unit increase in AC, consumers' intention is expected to increase 0.170 units. Consumers' intention will increase on average by 0.169 unit each 1 unit increases in CT, net of the effect of change due to HC, EL, FS, and PA. For this, if all variables are zero, then intention to purchase is 0.575 units, which does not make any sense; this model is not applicable for all variables at zero. Regression analysis indicates that HC has the utmost impact on organic purchasing intention (t=5.251, p<0.01, [beta]= 0.236). AC is the second mandate of vital selected factor on intention (t=4.747, p<0.01, [beta]=0.211). The third impact factor is CT (t=4.380, p<0.01, [beta]=0.188) while EL and FS has a lower impact followed by (t=3.429, p<0.01, [beta]=0.153) and (t=3.146, p<0.01, [beta]=0.137), respectively.

During data collection, respondents were asked five statements about what influenced them to purchase organic goods. Based on respondents' age, three generations was defined: (1) generation Y aged 18 years to 35 years, (2) generation X aged 36 years to 50 years and (3) baby boomers aged 51 years to 64 years. The majority of respondents were generation Y (90%), generation X (7%) and baby boomers (3%), respectively. Pertaining to the five statements, about 92 percent of generation Y consumed organics for the purpose of healthiness. They thought that consuming organic products could offer better health benefits than non-organic products. The second reason behind consumers thinking concerned pesticide usage. Presumably, consumers believed that most agricultural products used chemicals to preserve the food or generate more output; however, they had a positive attitude to organic goods in that there was no pesticide used in the production process. While other reasons such as flavor, freshness, and eco-conscious (distance from shop to house) were subsequently rated. It can be implied that the main reason behind why consumers are now considering organic goods in Cambodia are health issues and the food being free of pesticides.

V. CONCLUSION

This research found that health consciousness is the most important issue in consumers' intention to purchase organic goods. The majority of Cambodian citizens are staying on at school because they need to achieve at least grade 12 as required by government policy. Subsequently, those who get a good education have the opportunity to get a good job with a fair salary. As higher earners their interest in healthy living also increases.

Product availability and convenience also have a significant influence on their consumption. If organic products are widely available and convenient, consumers will buy. If organics can be found in multiple local sources (rather than just specialist markets) this provides good incentives to purchase.

Consumers' trust is a commercial interest in organic goods. Most consumers trust the organization/brand reputation, especially non-government organizations. Surprisingly, ethical lifestyle and food safety concerns are least correlated with intention to buy; price has affected negatively on their intention to buy. As such, it is clear that people in Phnom Penh metropolis believe that organic goods are a premium product for high-end consumers only. In this context, marketers should set up policy concerning health awareness and placement to generate more consumption volume even if the price is a barrier.

As regards limitations, as far as we know, this is the first study carried out on this topic in Cambodia. As such it adds to the knowledge of organic food and drink consumption in an emerging market in Southeast Asia. To some extent for further researchers, we suggest investigation into the willingness to pay for particular organic goods taken together with product characteristics, or to find out why or/and what are the reasons when consumers are considering organic goods in Cambodia by using qualitative approaches (in-depth or focus group interview).

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Sothea Kouy (a), Parichard Sangkumchaliang (b), Satit Aditto (c)

(a) Department of Agricultural Economics, Khon Kaen University Khon Kaen, Thailand 40002 sotheakouy@gmail.com

(b) Corresponding author, Department of Agricultural Economics Khon Kaen University, Khon Kaen, Thailand 40002 parisan@kku.ac.th

(c) Department of Agricultural Economics, Khon Kaen University Khon Kaen, Thailand 40002 asatit@kku.ac.th Table 1 Descriptive statistics and bivariate Pearson correlation coefficient matrix No. Drivers Mean SD 1 2 3 1 IT 3.738 0.643 - 2 HC 3.929 0.698 0.479 (**) - 3 EL 3.491 0.666 0.438 (**) 0.400 (**) - 4 PP 3.258 0.795 0.169 (**) 0.103 (*) 0.188 (**) 5 FS 4.135 0.699 0.465 (**) 0.452 (**) 0.381 (**) 6 PA 3.373 0.761 0.329 (**) 0.259 (**) 0.356 (**) 7 AC 3.751 0.795 0.452 (**) 0.270 (**) 0.305 (**) 8 CT 3.493 0.713 0.430 (**) 0.308 (**) 0.373 (**) No. 4 5 6 7 1 2 3 4 - 5 0.279 (**) - 6 0.304 (**) 0.315 (**) - 7 0.358 (**) 0.461 (**) 0.340 (**) - 8 0.173 (**) 0.290 (**) 0.406 (**) 0.331 (**) Note: (**) indicates that correlation is significant at the 0.01 level (2-tailed) (*) indicates that correlation is significant at the 0.05 level (2-tailed) Table 2 Coefficients on factors that affect consumers' intention and collinearity statistics Unstandardized Standardized Items Coefficients Coefficients B Std. Error Beta t Sig. (Constant) 0.609 0.195 3.120 0.002 HC 0.213 0.041 0.231 5.129 0.000 (***) EL 0.145 0.044 0.150 3.315 0.000 (***) PP -0.036 0.034 -0.045 -1.062 0.289 (ns) FS 0.140 0.044 0.152 3.186 0.002 (**) PA 0.029 0.038 0.034 0.765 0.445 (ns) AC 0.176 0.037 0.218 4.723 0.000 (***) CT 0.163 0.040 0.181 4.072 0.000 (***) Collinearity Items Statistics Tolerance VIF (Constant) HC 0.716 1.396 EL 0.712 1.404 PP 0.820 1.219 FS 0.636 1.572 PA 0.723 1.383 AC 0.684 1.461 CT 0.738 1.356 R=0.653, R Square = 0.427, Durbin-Watson = 1.725, F (7, 394) = 41.941, p<0.0001 (***) indicates significant at the 0.001 level; (**) indicates significant at the 0.01 level; (*) indicates significant at the 0.05 level; (ns) Non significant Table 3 Finalized coefficients on factors that affect consumers' intention Unstandardized Standardized Item Coefficients Coefficients Beta Std. Error Beta t Sig. (Constant) 0.575 0.188 3.057 0.002 HC 0.217 0.041 0.236 5.251 0.000 (***) EL 0.147 0.043 0.153 3.429 0.000 (***) FS 0.137 0.043 0.149 3.146 0.002 (**) AC 0.170 0.036 0.211 4.747 0.000 (***) CT 0.169 0.039 0.188 4.380 0.000 (***) R=0.652, R Square = 0.425, Durbin-Watson = 1. 733, (F (5, 396) = 58.502, p<0.0001) (***) indicates significant at the 0.001 level; (**) indicates significant at the 0.01 level; (*) indicates significant at the 0.05 level