The influence of subjective and objective knowledge ...

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The influence of subjective and objective knowledge on attitude, motivations and consumption of organic food Joris Aertsens, Koen Mondelaers, Wim Verbeke, Jeroen Buysse and Guido Van Huylenbroeck

The influence of knowledge on attitude 1353 Received June 2009 Revised June 2010 Accepted June 2010

(Information about the authors can be found at the end of the article.) Abstract Purpose – Although the organic market has expanded in recent years, it remains small. Some researchers argue that consumers’ lack of knowledge concerning organic food is an important factor slowing down growth. This paper aims to focus on the factors influencing objective and subjective knowledge with regard to organic food production and the relationship between both types of knowledge and consumer attitudes and motivations towards organic food and its consumption. Design/methodology/approach – A literature review is presented, relating to the impact of knowledge on behaviour in general and, more specifically, on organic food consumption. Several hypotheses are formulated concerning the relationship between objective and subjective knowledge, attitudes and organic food consumption and these are tested on organic vegetable consumption in Flanders (Belgium). Multiple regression models, a probit model and an analysis of variance are applied to a sample of 529 completed questionnaires (response rate ¼ 44 per cent). The respondents were selected in January 2007 using a convenience sampling technique. Socio-demographic variables are used to check representativeness. Findings – In the sample, the level of objective knowledge regarding organic vegetables is high. Attitudes towards the consumption of organic vegetables are generally positive. The strongest motivations for consuming organic vegetables are that they are produced without synthetic pesticides, are better for the environment, healthier, of higher quality and taste better. The strongest perceived barriers are overly high prices and lack of availability. Objective and subjective knowledge with regard to organic food production show a positive correlation. Higher levels of objective and subjective knowledge concerning organic food are positively related to a more positive attitude towards organic food, greater experience of it and a more frequent use of information. Membership of an “ecological organisation” (VELT) is also related to higher levels of knowledge. Some variables have a significant positive relationship with subjective knowledge, but not with objective knowledge. Attitude is significantly and positively influenced by subjective knowledge, VELT-membership, norm, motivations and female gender. Perceived barriers have a significant negative influence on attitude. The likelihood of consuming organic vegetables is significantly and positively influenced by VELT-membership, subjective knowledge, attitude, motivations and the presence of children in the household. Whilst objective knowledge, norm and female gender have a significantly positive influence on attitude towards organic vegetables, they have no significant influence on the likelihood of actually consuming organic vegetables. Originality/value – Whilst several researchers argue that knowledge may be a very important factor in increasing organic food consumption, few have studied the mechanisms behind it. To the authors’ knowledge this is the first paper describing the impact of knowledge on organic food consumption in such detail. By assessing the impact of knowledge, as well as other factors, on organic food consumption, greater insight is gained with regard to organic food consumption behaviour. Keywords Objective knowledge, Subjective knowledge, Consumer behaviour, Attitudes, Organic, Food, Theory of planned behaviour, Values theory, Expectancy value theory, Belgium Paper type Research paper

British Food Journal Vol. 113 No. 11, 2011 pp. 1353-1378 q Emerald Group Publishing Limited 0007-070X DOI 10.1108/00070701111179988

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1. Introduction In Western Europe and the USA the consumption of organic products has increased substantially over the last ten years (Sahota, 2007). However, the overall market share of organic food still remains low. Whilst most consumers have a positive attitude towards buying organic products (Saba and Messina, 2003), they are often constrained by important barriers. One of these barriers is uncertainty as to the characteristics of organic food. In this paper, the factors that influence organic vegetable consumption are studied, whilst focusing in particular on the potential role of (self-rated) knowledge. Several researchers have reported that greater awareness and additional knowledge concerning organic food has a positive influence on attitudes towards organic food and levels of consumption (Chryssochoidis, 2000; Padel and Foster, 2005; Bonti-Ankomah and Yiridoe, 2006; Gracia and De Magistris, 2007; Stobbelaar et al., 2007). Thøgersen (2007) found that uncertainty about organic food has a direct negative impact on the intention to buy organic food and also a negative impact on the translation from intention to purchase organic food into the actual purchase itself. Demeritt (2002) reports that lack of knowledge and awareness are considered the main reason for consumers not buying organic food. The processes behind these mechanisms are still unclear. We test related hypotheses on data from 529 valid questionnaires from Flemish users and non-users of organic vegetables. The focus on organic vegetables is defended, because for many consumers fruit and vegetables are their main entry point into the organic market (Organic Centre Wales, 2004; Padel and Foster, 2005) and because organic fruit and vegetables make up a high proportion of the total organic produce consumed. In Flanders, with 33 per cent of all consumers having bought organic vegetables at least once in 2007, vegetables rank first amongst organic food categories, followed by dairy products (24 per cent) and fruit (22 per cent). With on average 3.50 euros per capita being spent on organic vegetables in Flanders in 2007, it is the main category, followed again by dairy (e2.70), fruit (e2.40) and bread (e2.40). In Flanders the average expenditure per capita on fresh organic products amounted to 16.00 euros in 2007, (Samborski and Van Bellegem, 2008). The paper is structured as follows. In section 2, a review of the relevant literature is presented, which serves as a theoretical framework. This section concludes with a model and hypotheses that focus on the relationship between knowledge and consumption of organic food. In section 3 the research methodology is explained, whilst in section 4, a descriptive analysis is given of the relevant variables in the model. In section 5 the importance of the different factors in organic food consumption are estimated applying multiple regression models, a probit model and an analysis of variance. We end with some conclusions. 2. Theoretical framework 2.1 The role of knowledge when modelling organic food consumption Both the Values Theory (Rokeach, 1973; Schwarz, 1992) and the Theory of Planned Behaviour (TPB) (Ajzen, 1991; Ajzen, 2006) are valuable frameworks for explaining the consumption of organic food (Chen, 2007; Gracia and De Magistris, 2007; Gotschi et al., 2007; Thøgersen, 2007). Values theory is often used to study the link between values and consumer behaviour. Values are generally understood to be extremely stable constructs, and therefore values can serve as predictors of behaviour over extended periods of time (Krystallis et al., 2008).

According to TPB, behaviour is based on the “intention to perform the behaviour” in combination with “(Perceived) Behavioural Control”. Intention is in turn influenced by three constructs “Attitude towards the behaviour”, “Subjective Norm” and “Perceived Behavioural Control (PBC)”. For more details on TPB we refer to Ajzen (1991, 2006). Aertsens et al. (2009) propose a framework that integrates Values Theory and TPB to explain organic food consumption. They refer to the Expectancy Value Theory (Ajzen, 2001; Ajzen and Fishbein, 2008; Fishbein and Ajzen, 1975) to explain how beliefs, combined with values, determine attitudes. An individual’s attitude towards organic food (A) is the sum of the salient beliefs (b) concerning the attributes of organic food, multiplied by the value (v) attached: A ¼ Sbi vi . Beliefs and attitudes are less stable than values. New knowledge may change people’s beliefs and thus also their attitude. This inspired us to present a model that relates both objective and subjective knowledge, with attitude and motivations towards organic vegetables and their consumption. The model is presented in Figure 1. In the model, TPB can easily be recognised: Intention and Perceived Behavioural Control, as important components of TPB, have been indicated by a dotted line, to show that they have not been taken into account explicitly in our analysis. The same is true for “Values” and “Beliefs” as components of Expectancy Value Theory. In this context it is important to understand which values are important in relation to organic food consumption. Literature indicates that the value “security” (and related motivations concerning health) is the strongest argument for purchasing organic food (Baltussen et al., 2006; Botonaki et al., 2006; Makatouni, 2002; Mintel, 2003; Millock et al., 2004; Padel and Foster, 2005; Zanoli and Naspetti, 2003). The value “universalism”, which Schwartz (2006) explains as “understanding, appreciation,

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Figure 1. Relationship between objective and subjective knowledge concerning organic food, attitude and motivations towards organic food consumption and consumption itself

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tolerance, and protection for the welfare of all people and for nature” is often found to be an important driver behind organic food consumption (Dreezens et al., 2005; Lea and Worsley, 2005). Other values such as “hedonism”, “stimulation”, “self direction”, “conformity” and “benevolence” can also stimulate organic food consumption (Aertsens et al., 2009) but are less influential. 2.2 Knowledge and its influence on (consumption) behaviour Brucks (1985) makes a distinction between three categories of consumer knowledge relevant to consumer behaviour: (1) subjective knowledge (i.e. what individuals perceive that they know, also indicated as perceived or self-rated knowledge); (2) objective knowledge (i.e. what an individual actually knows); and (3) prior experience. This scheme is followed by many researchers (Flynn and Goldsmith, 1999). According to Brucks (1985) and Selnes and Gronhaug (1986), differences between subjective knowledge and objective knowledge occur when people do not accurately perceive how much or little they actually know. Subjective knowledge incorporates the individual’s degree of confidence in his/her own knowledge (Brucks, 1985). It is likely that subjective and objective knowledge relate to information search and decision-making behaviour, although probably in different ways (Brucks, 1985). A low level of subjective knowledge, resulting from a lack of confidence in current knowledge, may motivate the search for additional information, whilst a high level of subjective knowledge increases reliance on previously stored information (Brucks, 1985; Ruddell, 1979). Objective knowledge facilitates deliberation and the use of newly acquired information (Ruddell, 1979; Selnes and Gronhaug, 1986). Objective knowledge positively affects the number of attributes considered by an information searching consumer (Park and Lessig, 1981; Brucks, 1985). Results from a meta-analysis by Bamberg and Moser (2007) underline the role of knowledge with regard to environmental problems as an important indirect determinant of pro-environmental behaviour. Knowledge is associated with the internal attribution of responsibility, social norms, and feelings of guilt. Knowledge also directly influences the degree of Perceived Behavioural Control and attitudes toward pro-environmental behaviour. Thøgersen (2009) has found that issue relevant knowledge has a positive influence on the adoption of new eco-labels. Selnes and Gronhaug (1986) and Feick et al. (1992) mentioned that subjective knowledge is a stronger motivation for purchase-related behaviours than objective knowledge. In line with this, House et al. (2004) have found that higher levels of subjective knowledge are significantly and positively related to the willingness of consumers to eat Genetically Modified food, whilst they did not observe this relationship for objective knowledge. Ellen (1994) has found that subjective knowledge is positively associated with commitment to recycling, source reduction, and political action, whilst objective knowledge is only significantly related to the first of these. These findings indicate that subjective knowledge is not only positively related to an individual’s confidence in their knowledge, but also with stronger attitudes towards a product or behaviour. It would also appear that subjective knowledge has a stronger positive relationship with attitude and behaviour than objective knowledge.

2.3 Relationship between objective and subjective knowledge Reported correlations between subjective knowledge and objective knowledge often fall in the range 0.3 to 0.6 (Carlson et al., 2009; Klerck and Sweeney, 2007; Feick et al., 1992; Brucks, 1985). Findings from Selnes and Gronhaug (1986) and Klerck and Sweeney (2007) indicate that objective and subjective knowledge are far from perfectly correlated. Selnes and Gronhaug (1986) and Klerck and Sweeney (2007) recommend that one should pay attention to the differences between both measures, as each has different effects on information processing and subsequent consumer behaviour. Researchers have sometimes neglected this. Selnes and Gronhaug (1986) propose that objective measures are preferable when research is focused on ability differences, whilst subjective measures should be used when concentrating on motivational aspects of product knowledge. 2.4 Objective knowledge concerning organic food and its influence on consumption Several studies have highlighted the lack of knowledge and confusion amongst European consumers surrounding the term “organic food” (Aarset et al., 2006; Grunert and Kristensen, 1992; Peattie, 1990). Midmore et al. (2005) found that, in general in Europe organic product knowledge remained relatively low, although there was considerable variation between European countries. Somewhat in contrast, Hutchins and Greenhalgh (1997) found that, in a survey of 100 consumers using an open-ended question on the interpretation of the term “organic farming”, all respondents replied that it means “without chemicals”. Other associations made were “without growth hormones”, “not intensively”, and “naturally”. They argue that consumers are therefore largely correct in their interpretation of organic products given these are defined by the Oxford English Dictionary as “produced without artificial fertiliser or pesticides”. However less than 10 per cent of the respondents recognised the symbols that distinguish organic food in the UK. Beharrel and MacFie (1991) and Hill and Lynchehaun (2002) found that most consumers understand the key attributes associated with organic farming, but many do not actually understand organic farming practices and the costs incurred. Several authors stress the importance of knowledge and awareness for the further development of the organic food market. Bonti-Ankomah and Yiridoe (2006) delimit two specific consumer segments for which this is very relevant: the first segment constitutes those consumers who are as yet uninformed about organic foods; the second segment of potential consumers comprises those who have a general knowledge about organic foods but insufficient detailed information to clearly differentiate the unique attributes of organic from conventional food, and therefore do not currently consider buying them. Demeritt (2002) reports that lack of knowledge and awareness is considered to be the main reason for consumers not buying organic food in the USA – 59 per cent of respondents indicate that they have never considered organic products because they did not know about them. In Greece, Fotopoulos and Krystallis (2002), make a clear distinction between unaware consumers (18.5 per cent), aware non-buyers (73.1 per cent), and aware buyers (8.1 per cent). Padel and Foster (2005) argue that if consumers were more aware of the reasons behind the price premium for organic products, they would be more willing to buy them. The Taylor Nelson Sofres report (Organic Centre Wales, 2004) states that 14 per cent of non-buyers of organic food mention that insufficient information to justify the higher price is the main reason for not buying organic food. Denver et al. (2007) who studied the impact of providing information on consumers’ “Willingness To Pay” only found a single study covering this topic in relation to organic products. In this study, Underhill and Figueroa (1996) have found that there is a positive and significant effect


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of providing additional information on product labels, in terms of increasing the likelihood of purchasing products with the labels “Organic”, “Certified Organic” and “Grown with IPM (integrated Pest Management)”. The information effect was much greater for the label “Grown with IPM”. This is due to the fact that consumers’ ex-ante knowledge concerning this label was much lower than for the organic labels. Stobbelaar et al. (2007) found in an experiment amongst adolescents of 15-16 years that more knowledge results in a more positive attitude towards organic food. As the knowledge levels of the adolescents in their sample was low, with half of them initially having no knowledge about organic food, just making them read a definition of organic food triggered a shift from mostly neutral towards a (fairly) positive attitude. Bredahl and Thøgersen (2004) have found that regular consumers of organic foods exhibit more complex knowledge structures for organic food than non-users. They identified this by carrying out laddering interviews with consumers in Germany, Great Britain, Denmark and Spain. However not all studies have found a positive link between knowledge and organic food consumption. Gotschi et al. (2007) measured (objective) knowledge of organic products and labels by questioning Austrian high school students as to which characteristics relate to organic products. However, no significant relationship with attitudes and behaviour was observed. 2.5 Subjective knowledge regarding organic food and its positive relationship with intention and behaviour Chryssochoidis (2000) and Gracia and De Magistris (2007) observed that the intention to purchase organic food is positively influenced by a higher level of subjective knowledge. Gracia and De Magistris (2007) argue that this is the case because knowledge is the only instrument that consumers have to differentiate the attributes of organic from conventional products and to form positive attitudes toward these products. Chryssochoidis (2000) argues that weak perceived self-competence is likely to keep consumers away from organic food since they will feel incapable of making a good choice. This is confirmed by Thøgersen (2007) who found that uncertainty has a direct negative impact on the intention to buy organic food and on the translation from intention into the actual purchase of organic food. 2.6 Factors influencing knowledge in relation to organic food Gracia and De Magistris (2007) found that information on organic food products available in the market has a significant and positive influence on (subjective) knowledge about organic food. They also refer to Bigne´ (1997) who indicates that organic food knowledge is influenced by information provided by the public administration, mass media, ecological associations and shopping sites. Park et al. (1994) found that subjective knowledge about CD-players is more strongly influenced by product-related experience (59 per cent) than by stored product information (33 per cent). Stored product information is a more important determinant of objective, rather than subjective knowledge, whilst product-related experience is a more important determinant of subjective rather than objective knowledge. Several researchers have found that higher levels of education are positively related to higher levels of knowledge with regard to organic food (Gracia and De Magistris, 2007; Stobbelaar et al., 2007; House et al., 2004; Storstad and Bjørkhaug, 2003; Bigne´, 1997; Ellen, 1994)

Ellen (1994) examined the relationship between knowledge, pro-ecological attitudes and behaviours and found that younger age and higher income are significantly and positively related to both subjective and objective knowledge. Bigne´ (1997) reported a significant relationship between income and organic knowledge. House et al. (2004) observed that subjective knowledge about Genetically Modified Foods is influenced by religion and country of origin. Gracia and De Magistris (2007) and Bigne´ (1997) have found that lifestyle (e.g. vegetarian, additive free) and values are sometimes significantly related to knowledge about organic food. 2.7 Model and research hypotheses In Figure 1 we present a model that relates objective and subjective knowledge with attitudes, motivations and consumption behaviour, based on findings from the relevant literature. In this paper our research is exploratory and therefore the model in Figure 1 mainly serves as a framework to structure our reasoning. Future research will be necessary to verify the causality between the different parameters in this model. Based on the literature review summarised in the previous sections, we formulate the following hypotheses relating to knowledge, and its influence on attitudes and organic food consumption. These will be tested in the empirical part of the paper: H1. Objective and subjective knowledge in relation to organic food production have a positive correlation, but not a very strong one. H2. Both objective and subjective knowledge with regard to organic food are positively related to higher levels of education, younger age, higher levels of income, more information received through media, more positive attitudes towards organic food and more experience with organic food. H3. On average men are more confident about their knowledge than women. In other words they will have a higher score for subjective knowledge, ceteris paribus. H4. A more positive attitude towards organic food is correlated with a higher objective knowledge score. H5. A more positive attitude towards organic food is correlated with a higher subjective knowledge score. H6. Higher levels of objective and subjective knowledge are positively correlated with higher consumption of organic food. 3. Methodology and data 3.1 Data collection Data were collected, in Flanders (Belgium), via a survey in January 2007. Subjects, selected from users and non-users of organic products numbering 1,200 (see further) were personally contacted and asked to complete a self-administered questionnaire, which took approximately twenty minutes for respondents to complete. By the imposed deadline of February 11, 2007, 553 questionnaires had been received (46 per cent), of which 529 were fully completed (44 per cent) and these have been used for further data analysis. Data from the questionnaire have also been used by Mondelaers et al. (2009) and Hoefkens et al. (2009). In order to achieve a good response from medium and heavy users of organic vegetables, 50 per cent of the questionnaires were distributed amongst randomly


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chosen members of the ngo VELT, a Flemish organisation that promotes ecological lifestyle and consumption. This subsample was correctly expected to incorporate a high proportion of heavy users. In total 266, (50.6 per cent) of the 529 usable questionnaires are from members of VELT. Questionnaires were distributed amongst non-VELT members using a convenience sampling technique, during which efforts were made to maintain representativeness for the Flemish population. Table I gives a detailed overview of the socio-demographic characteristics of the sample. In comparison with the Flemish population, the sample has a slight overrepresentation of the age group 40-50 years and of better educated people, because of their greater willingness to participate in surveys in general, and their higher level of involvement in food purchase. There is also an overrepresentation of people from the provinces “Vlaams-Brabant” and “Oost-Vlaanderen”, mainly resulting from the close proximity of Ghent University. However, for the purposes of our research, which is to explore main drivers, rather than presenting a conclusive segmentation of the population, this causes no difficulties. 3.2 Measurement of the relevant variables 3.2.1 Objective knowledge concerning organic vegetables. Objective knowledge can be measured by open-ended or closed-ended questions. The first has the disadvantage of being time consuming and subject to bias in data processing. The second may lead to biased results if guessing is not taken into account in some way (Carlson et al., 2009). Therefore, we have chosen an approach with closed-ended questions, which also takes account of guessing. The respondents had to indicate how certain they were of their response for each item. Objective knowledge scores for respondents who were less certain of their answer for a specific item or who were, in other words, (partly) guessing have been evaluated lower than for people who indicated that they were (more) certain of their answer. To measure objective knowledge, the questionnaire uses a construct of four statements, the validity of which has been checked and confirmed by experts. This is in line with the methodology proposed by Park et al. (1994). The respondents had to indicate whether they thought the statements were true or false and to assess their certainty of the answer on a scale from 1 (uncertain) to 5 (certain). This construct is presented in Table II, at the left side of the vertical grey bar. The results indicate that our approach enables us to keep track of guessing because a clear relationship exists between certainty and the correctness of the results. For all four items considered together, when respondents gave a certainty score of 5 (¼ certain), 4, 3, 2, and 1 (¼ uncertain), respectively 96 per cent, 90 per cent, 80 per cent, 78 per cent and 70 per cent of their answers were correct. Based on the above insights we have chosen to calculate the objective knowledge score as follows: a wrong answer with a certainty of 5, resulted in a score of 0; a wrong answer with a certainty of 4, in a score of 1; a wrong answer with a certainty of 3 in a score of 2, and so on; a correct answer with a certainty of 1 resulted in a score of 5; a correct answer with a certainty of 2, in a score of 6, and so on. The maximum score is thus given to a correct answer with a certainty of 5, which results in a score of 9. The total objective knowledge score is then calculated by summing the scores on each of the four statements and these therefore range between 0 and 36. The Cronbach’s Alpha score was calculated to be 0.610, which indicates that there is a sufficient degree of consistency between the four measures.

% Gender Male Female

46.9 53.1

Age (years) #25 26-40 41-50 51-65 .65

8.9 22.3 32.1 26.7 10

Education Did not finish secondary school Secondary school ($ 18 years) Higher education Province (region) Vlaams-Brabant Antwerpen Limburg West-Vlaanderen Oost-Vlaanderen Net income (e per month) .3,000 2,500-3,000 2,000-2,500 1,500-2,000 ,1,500 Children in the household Yes No Age of children ,12 12-18 .18 Number of children 1 child 2 children .2 children Profession Independent Employee Worker Housewife (m/f) Student Teaching Retired VELT member 266 Non-VELT member 263


5.9 34.2 59.9 24.1 15.5 5 18.4 36.9 27.4 16.1 15.5 12.7 12.8 76.4 23.6 30.1 21.2 48.7 16.9 41.5 41.5 10 35.4 6.1 9.3 6.8 11.8 14.7 50.3 49.7

Table I. Socio-demographic characteristics of the sample

Organic farmers do not use synthetic pesticides

2.

Organic farmers may use synthetic fertilisers

3.

Organic farmers may use genetically modified seeds

4.

Organic vegetables may be irradiated to improve conservation

Total score

True (%)

False (%)

87

Indicate the degree of certainty you have All VELT Uncertain Certain Mean Mean

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Table II. Questions used to measure objective knowledge and the average response scores Below we presented statements concerning organic food and farming, please indicate whether they are true or false

Non-VELT Mean

1

2

3

4

5

7.1

7.6

6.6

82

1

2

3

4

5

6.9

8.0

5.8

86

1

2

3

4

5

7.2

8.0

6.5

93

1

2

3

4

5

7.3 28.5

7.7 31

6.9 25.7

3.2.2 Subjective knowledge concerning organic vegetables. Flynn and Goldsmith (1999) describe the development and validation of a short, reliable, and valid measure of subjective knowledge. We have applied their approach by including the following three statements in our questionnaire, for which the respondents had to indicate a score from 1 (totally disagree) to 7 (totally agree): (1) In comparison with an average person I know a lot about organic vegetables. (2) I know a lot about how to judge the quality of organic vegetables. (3) People who know me, consider me as an expert in the field of organic vegetables. The subjective knowledge score was measured by summing the scores on each of these three questions, and thus falls within the interval of 3 to 21. The Cronbach’s alpha score of 0.89 indicates a high degree of consistency between the three measures for subjective knowledge. 3.2.3 Attitudes towards organic vegetable consumption. We asked respondents to indicate their attitude towards the consumption of organic vegetables on six bi-polar “attitude scales” (1. good-bad; 2. unhappy-happy, 3. unpleasant-pleasant; 4. low spirited – high spirited; 5. terrible – great; 6. negative – positive). Each scale had seven progressive levels, where the value 1 represents the most negative attitude and the value 7 the most positive attitude. There is a high degree of consistency between these six measures, as indicated by the Cronbach’s Alpha score of 0.955. The scores for the six items where summed for each individual, theoretically leading to a minimum score of 6 (indicating an extremely negative attitude towards organic products) and a maximum score of 42 (an extremely positive attitude), and a neutral attitude with a score of 24. 3.2.4 Motivations and barriers. Our respondents were asked to score 17 possible motivations for buying organic vegetables on a seven-point scale from 1 ¼ “no or very low motivation” to 7 ¼ “very high motivation” (see Figure 2). The value 4 can be considered as the neutral point on this scale. Also a total motivation score was calculated by summing respondents’ scores for each of the 17 motivations. Similarly, respondents were asked to rate the importance of 12 potential barriers (see Figure 3), to purchasing organic vegetables using a seven-point bipolar scale from 1 ¼ “no barrier” to 7 ¼ “very high barrier”. Also a total barrier score was calculated by summing the respondents’ barrier scores. The seventeen motivation constructs are internally consistent as well as the twelve barrier constructs – as indicated by Cronbach’s Alpha scores of 0.90 and 0.84, respectively. 3.2.5 Importance of organic vegetable consumption. To measure the importance of organic vegetable consumption, respondents were asked: “On ten occasions when you consume vegetables, how often are these organic”. There were eleven possible responses going from 0, 1, 2 and so on up to 10. In fact this question measures both the proportion of organic vegetables consumed and the likelihood that consumed vegetables are organic. More specifically a respondent’s score of 6 out of 10 can be interpreted as “the proportion of organic vegetables consumed is 60 per cent” but also as “on ten separate choice occasions between organic and conventional vegetables, organic vegetables are chosen on six occasions and on four occasions they are not chosen”. 3.2.6 Norm. A norm indicator is derived from a seven point bipolar survey question asking respondents to indicate how ethical the consumption of organic vegetables is – ranging from “very unethical (1) to “very ethical” (7).


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Figure 2. Motivations for buying organic vegetables (ordered by decreasing importance)

Figure 3. Barriers for buying organic vegetables (ordered by decreasing importance)

3.2.7 Source of information. To test the possible impact of information sources on certain variables, we included a question regarding twelve different sources of information. Respondents were asked whether they use these sources often. They had to answer on a seven-point scale ranging from “never” (1) to “very often” (7). Information sources tested included the product tag, the organic label, newspapers, the internet, information at supermarkets, specialised organic shopkeepers, government information, consumer organisations, scientific reports, contacts with organic farmers and information from friends.

3.2.8 Education. To test the possible impact of a higher level of education on certain variables, the population was split into three groups: (1) no diploma from secondary school (n ¼ 31); (2) secondary school diploma but no higher education (n ¼ 181); and (3) higher education degree (n ¼ 317). A dummy variable for groups 1 and 3 was included as explanatory variables in the multiple regression analysis (see Tables III-V). 3.2.9 Dummy variables. Some respondents’ characteristics were translated in the models by applying dummy variables:, e.g. gender (male ¼ 1); Velt-membership (1 ¼ member); presence of children in the household (1 ¼ yes). In the results tables these variables are preceded by “D_”.

Unstandard. coeff. B Std. error Constant D_VELT (1 ¼ member) ATTITUDE source_product_tag source_organic_shop

19.71 3.87 0.14 0.39 0.26

1.19 0.55 0.04 0.13 0.14

Unstandard. coeff. B Std. error Constant D_VELT (1 ¼ member) source_product_tag objective knowledge source_organic_shop source_scientist source_org_farmer % ORGANIC D_GENDER (1 ¼ male) ATTITUDE

21.92 2.23 0.21 0.14 0.22 0.32 0.19 0.40 1.38 0.04

0.89 0.35 0.08 0.03 0.09 0.08 0.09 0.06 0.28 0.03

Unstandard. coeff. B Std. error Constant D_VELT (1 ¼ member) subjective knowledge NORM-ethics score BARRIERS_total score MOTIVATION_total

19.28 2.49 0.28 1.14 2 0.08 0.08

1.52 0.59 0.06 0.21 0.02 0.01

Stand. coeff. Beta

t

Sig.

0.31 0.16 0.12 0.09

16.57 3.41 3.00 2.02

0.000 0.000 0.001 0.003 0.048

Stand. coeff. Beta

t

Sig.

0.23 0.09 0.17 0.09 0.12 0.08 0.27 0.14 0.06

22.15 6.31 2.70 5.34 2.57 3.83 2.28 6.81 4.95 1.61

0.032 0.000 0.007 0.000 0.011 0.000 0.023 0.000 0.000 0.108

Stand. coeff. Beta

t

Sig.

0.18 0.19 0.20 20.14 0.22

12.70 4.21 4.34 5.52 24.02 5.41

0.000 0.000 0.000 0.000 0.000 0.000


Table III. Factors influencing objective knowledge in relation to organic food

Table IV. Factors influencing subjective knowledge in relation to organic food

Table V. Factors influencing attitudes towards organic food consumption

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3.3 Statistical techniques and models The data are analysed using different statistical techniques:, e.g. descriptive analyses, calculation of correlations, multiple regression and probit analyses. Data are processed using the statistical package SPSS 16. More detailed information on the models used to determine the influencing factors for the following variables are presented below: . objective knowledge; . subjective knowledge; . attitude, motivations and barriers; and . consumption of organic vegetables. 3.3.1 Determinants of objective knowledge. In order to analyse factors that may have an influence on the objective knowledge score, a multiple linear regression model was performed with “objective knowledge” as the dependent variable and with the following as explanatory variables: membership of VELT, level of education, information received through different media, attitude towards organic food, experience with organic food, age, income and gender. These factors are all hypothesised to have a potential impact on knowledge. 3.3.2 Determinants of subjective knowledge. In order to analyse the factors that may influence the subjective knowledge score another multiple linear regression model was run with “subjective knowledge” as the dependent variable and the same explanatory variables as in the previous model. However, objective knowledge is also included as an explanatory variable, as it is assumed that respondents with a higher level of objective knowledge, ceteris paribus, will also estimate that they have a higher level of subjective knowledge. 3.3.3 Determinants of attitude, motivations and barriers. To analyse the factors that may influence attitudes towards consuming organic vegetables a multiple regression model was tested with attitude as the dependent variable and including the following explanatory variables: . VELT membership; . the objective and; . subjective knowledge score; . the total motivation score; . the total barrier score; . the score representing “perceived norms”; and . some socio-demographic variables (gender, level of education, age). Similar models were used to analyse the factors influencing motivations and barriers – with the total motivation score and the total barrier score in turn as dependent variables. Attitude was added to the explanatory variables, and motivations and barriers were removed. 3.3.4 Determinants of organic vegetable consumption. Because the response categories for the proportion of organic vegetables consumed in relation to total vegetable consumption are limited to eleven and are truncated between 0 and 10, a PROBIT model, instead of a multiple regression model, is more appropriate for determining the factors that influence organic vegetable consumption. The probit model estimates the likelihood of organic vegetable consumption as a function of the explanatory variables identified earlier.

4. Descriptive analysis In this section a descriptive analysis is given of the responses obtained from our sample on the main variables included in the model(s) presented above. We include objective and subjective knowledge, motivations, barriers and attitude.

The influence of knowledge on attitude

4.1 Objective knowledge 4.1.1 The objective knowledge scores. In the methodology section we explained how the objective knowledge score was calculated. In Table II the percentage of people giving the right answer is presented to the left of the vertical grey bar. The final three columns, to the right of the vertical grey bar, give the average response scores for the whole sample as well as separately for the VELT respondents and the non-VELT respondents. In Figure 4 the distribution of respondents for each objective knowledge score is presented for each of the four items used to measure objective knowledge. The general pattern for the four items is similar. Most respondents answered correctly (scores 5 to 9) and a high proportion of respondents with a correct answer are certain of their response (score 9). From the respondents who gave a wrong answer, the proportion of people who indicated certainty about their answer (score 0) is much lower, indicating the reliability of our construct. Assuming total ignorance of organic production and a random answer, it would be expected that approximately 50 per cent of the population would give the correct answer and the expected average score would be 4.5 for each response category and 18 for the total score. Therefore, the average response scores we obtained are high, particularly when compared to the low levels of knowledge of organic food observed in samples from other populations, such as reported by Peattie (1990), Demeritt (2002) and Hill and Lynchehaun (2002). The statements in questions 1 and 2 typically related to organic production systems and were expected to be relatively well known. Less expected were the high scores for the other two statements. Of course, the high scores for the whole group are influenced by the overrepresentation of VELT members. The mean objective knowledge scores for the VELT and non-VELT group are presented in the last two columns of Table II. Analysis of variance indicates that, for each of the four questions, the average score for VELT members is significantly higher

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Figure 4. Percentage of total respondents for each objective knowledge score

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(at 0.05) than that observed for the non-VELT group. This was expected, as VELT members receive a quarterly brochure with articles on ecological lifestyle and organic food. 4.1.2 Determinants of objective knowledge. As indicated in section 3.3.1, in order to analyse which factors may have an influence on the objective knowledge score, a multiple linear regression model was tested with “objective knowledge” as the dependent variable. This model explains 25 per cent of the variation in objective knowledge (R 2-adjusted of 0.253). The results are presented in Table III. It appears that VELT-members have a significantly higher objective knowledge score than non-VELT members. Also a more positive attitude towards organic food is significantly and positively related to higher levels of objective knowledge. A more positive attitude may result in a higher degree of interest and thus in a higher level knowledge. However, the relationship between objective knowledge and attitude should be interpreted with caution, as causality may work the other way around, in that more objective knowledge may lead to a more positive attitude. Future research could test the endogeneity of this relationship. Our analysis indicates that the only information sources with a significant (and positive) influence on objective knowledge were the product tag and information received by visiting specialist organic shops. The following factors that were expected to have an effect on objective knowledge did not prove significant: the level of education, the percentage of organic vegetables consumed. Also age, region, gender and income had no significant effect. The objective knowledge score for individuals who were responsible for food purchases in the household did not differ significantly from those who were not. 4.2 Subjective knowledge As indicated in section 3.3.2, a multiple linear regression model was also tested with “subjective knowledge” as the dependent variable. The adjusted R 2 for this model equals 0.59 indicating that 59 percent of the variation in subjective knowledge can be explained by the model based on the explanatory variables presented below. This is higher than for the objective knowledge model. The following factors, represented in Table IV, have a positive and significant influence on self-rated knowledge: VELT-membership, objective knowledge of organic vegetables, male gender, a higher reported use of several information sources and a higher proportion of organic vegetables consumed in relation to total vegetable consumption. These findings are discussed in more detail below. The results in Table IV indicate that attitude is positively, but not significantly, related to subjective knowledge. However, as there is a strong correlation between attitude and percentage of organic vegetables used, there is a degree of multicollinearity which might have an influence on this result. If the explanatory variable “ per cent organic” is discarded, attitude turns out to be significantly and positively related to subjective knowledge (a ¼ 0:001), indicating that respondents with a more positive attitude also believe they have a higher level of knowledge of organic food. As expected, subjective knowledge is positively and significantly correlated with objective knowledge. This relationship between objective and subjective knowledge for the whole population is illustrated in Figure 5. A Pearson correlation coefficient of 0.50 is found. The average subjective knowledge score is significantly (a , 0.001) higher for VELT members (12.9) than for non-VELT members (7.1), ceteris paribus. One could argue that this is expected as their objective knowledge was also found to be significantly greater and therefore they have reason to rate their own knowledge higher. But the objective


Figure 5. Correlation between subjective and objective knowledge in relation to organic food

knowledge variable is also included in the model and thus the higher VELT-scores indicate that there is an additional effect apart from the higher objective knowledge score for VELT members. One reason why VELT-members may perceive that they have a high level of knowledge on organic food could be that they receive more information such as the quarterly VELT-magazine which covers organic food topics. This factor may result in a high degree of confidence as to their knowledge of organic food. Subjective knowledge has a significant positive relationship with the intensity of use of information sources. Apart from more frequent use of information on product tags and in organic shops, which are also significantly positively correlated with higher levels of objective knowledge, the more frequent use of information provided by organic farmers, scientists and internet research also has a significant positive relationship with subjective knowledge. This indicates that people who use these sources more often believe that they have a higher level of knowledge concerning organic food, whilst this does not appear to be justified by the objective knowledge scores measured. Also men and people with a higher proportion of organic vegetable consumption have a significantly higher subjective knowledge score, whilst both variables are not significantly related to objective knowledge. This indicates that males and more regular consumers of organic vegetables, on average, are over-confident about their own knowledge of organic food. The following factors had no significant relationship with self-rated knowledge concerning organic food: the level of education, age, income, or region. The subjective knowledge score for individuals who are responsible for food purchases in the household does not differ significantly from those who are not. The percentage of organic vegetables that respondents consume is positively and significantly related to subjective knowledge, whilst we have already seen that this is not the case for objective knowledge. This confirms the findings of Park et al. (1994) who had already found that product-related experience is a more important determinant of subjective than of objective knowledge.

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We can summarise that in relation to organic food, a higher objective knowledge score is correlated with a higher level of self-rated knowledge. However, there are also people that over- or underestimate their own knowledge, as proven by Figure 5. This implies that it remains interesting to test the impact of both objective and subjective knowledge on attitudes towards and consumption of organic food.

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4.3 Attitude Over the whole dataset, the average attitude score was 32.7, which is significantly higher than the neutral score of 24. This means that the population sample as a whole has a positive attitude towards organic vegetable consumption. This is partly due to the overrepresentation of VELT members. But also, in general, non-VELT members have a positive attitude towards organic products, as is proven by the fact that 97 per cent of the respondents have an attitude score of 24 or higher. From Table V, we can see that the following variables have a significant impact on attitude: VELT membership (þ ), subjective knowledge (þ ), norm (þ ), motivation score (þ ), perceived barriers score (2 ). As there is some correlation between the explanatory variables, one should be cautious about the estimated b-values. An interesting finding is the positive significant relationship between norm and attitude, which confirms earlier findings by Tarkiainen and Sundqvist (2005). Both subjective and objective knowledge are positively related to attitude towards organic food consumption. This is in line with hypotheses four and five. Given the high Pearson correlation coefficient of 0.50, there is a degree of multicollinearity between objective and subjective knowledge, making it impossible to differentiate clearly between the effects of both factors. When both are included simultaneously, only the positive correlation between “subjective knowledge” and attitude is significant. However when subjective knowledge is removed from the model, the positive relationship between objective knowledge and attitude becomes significant. This relationship is confirmed by a significant, positive, one to one correlation between objective knowledge and the total attitude score (Pearson correlation coefficient of 0.38 for the whole population). These findings point to the following causal relationship: increased objective knowledge strengthens subjective knowledge, which in turn engenders a positive attitude towards organic produce. The following factors have no significant influence on attitude towards organic vegetables: gender, level of education, age and whether the respondent is responsible for the purchases in the household. A further interesting finding is the negative correlation between attitude and perceived barriers. It is not illogical that higher perceived barriers towards organic vegetable consumption are negatively correlated with attitudes towards buying organic vegetables. In this case causality can go both ways: on the one hand people who perceive more barriers may have a negative attitude towards buying organic vegetables. On the other hand it may be that people with a relatively negative attitude towards organic food, will perceive barriers to be higher, e.g. distance to shops or higher prices are (perceived to be) more easily overcome by people with a more positive attitude. 4.4 Motivations Our respondents were asked to score different motivations for buying organic vegetables. The results are presented in Figure 2. We see that the five highest motivations for buying organic vegetables are:

(1) (2) (3) (4) (5) Other (1) (2) (3) (4) (5) (6)

The influence of knowledge on attitude

without pesticides; better for the environment; healthier; better quality; and better taste.

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motivations that score higher than neutral are: better for my children; greater food safety; without Genetic Modifications; better controlled; fresher products; and more animal friendly.

It is interesting to mention that whilst researchers more often find that the value “health” is the most important motivator (Aertsens et al., 2009), in our population the motivation “better for the environment” receives a slightly higher score than the motivation “healthier”. This also relates to the fact that a high proportion of “heavy users” and VELT-members are included, and regular users are reported to attach greater importance to the value “Universalism” of which environmental friendliness is a part (Zanoli and Naspetti, 2003; Mondelaers et al., 2009; Padel and Foster, 2005). As reported in Table VI, the following factors have a significant and positive influence on the total motivation score: . membership of VELT; . a more positive attitude; . a higher objective knowledge; . a higher subjective knowledge; and; . being a female respondent. We also found a significant positive relationship between objective knowledge and the total motivation score (Pearson correlation coefficient of 0.39 for the whole population). Unstandard. coeff. B Std. error Constant D_VELT (1 ¼ member) ATTITUDE objective knowledge subjective knowledge D_GENDER (1 ¼ male)

29.21 4.62 0.69 0.39 1.22 -5.45

4.50 1.84 0.13 0.14 0.20 1.43

Stand. coeff. Beta

t

Sig.

0.11 0.24 0.12 0.30 20.14

6.50 2.51 5.49 2.87 6.12 23.80

0.000 0.012 0.000 0.004 0.000 0.000

Table VI. Factors influencing motivations towards organic food consumption

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4.5 Perceived barriers In Figure 3, it can be seen that for the overall group, only the argument “too high prices” with a score of 4.4 exceeds the neutral score (4.0) and thus seems to be the most important barrier. “The lack of availability” with a score of 3.7, is the second highest barrier for the overall group. With eleven out of twelve barriers scoring lower than neutral, we can say that the barriers are rated rather low by the overall population. This is again partly due to the fact that our population comprises approximately 50 per cent VELT members, who have a significantly lower perception of barriers than non-VELT members. The following factors have a significant and positive influence on the total barrier score: . a more positive attitude; . membership of VELT; and . female gender. Objective and subjective knowledge have no significant impact on the total barrier score. 5. The influence of knowledge on the consumption of organic vegetables In this section we discuss the results from the probit model described in section 3.3.4 to determine the factors that influence organic vegetable consumption. An overview of the significant explanatory variables is presented in Table VII. As expected, members of VELT have a significantly higher likelihood for consuming organic vegetables than non-members. This was expected because we specifically incorporated approximately 50 per cent of respondents from VELT in order to achieve a high (over)representation of “medium” and “heavy users”. On average, the proportion of organic vegetables consumed by respondents from VELT is 69 per cent, with a standard deviation of 27 per cent. For non VELT-respondents the average equals 33 per cent with a standard deviation of 29 per cent. This difference is highly significant (for a ¼ 0:01). According to the Theory of Reasoned Action (Fishbein and Ajzen, 1975) and its extension, TPB, we observe the expected significant positive influence of attitude towards organic vegetable consumption on the consumption itself, as well as a significant negative influence on consumption behaviour, of perceived barriers such as “too high prices” and “insufficient availability”. The significant positive impact of motivations on the consumption of organic vegetables is also in line with expectations.

Table VII. Factors influencing the proportion of organic vegetables consumed

D_VELT (1 ¼ member) ATTITUDE subjective knowledge objective knowledge score BARRIERS_total score MOTIVATION_total D_children (1 ¼ yes) Intercept

Estimate

Std. error

Z

Sig.

0.201 0.041 0.060 20.013 20.010 0.011 0.172 22.151

0.049 0.004 0.006 0.004 0.002 0.001 0.045 0.169

4.13 11.28 10.65 2 3.61 2 6.09 8.82 3.80 2 12.70

0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

95% Confid. interval Lower bound Upper bound 0.106 0.034 0.049 20.021 20.014 0.009 0.083 22.321

0.296 0.048 0.071 20.006 20.007 0.014 0.261 21.982

With regard to the knowledge variables, we find that a higher level of subjective knowledge leads to a greater likelihood for consuming organic vegetables, whilst it appears that a higher level of objective knowledge has a significant negative impact on the likelihood of consuming organic vegetables. However, the absolute effect of objective knowledge is much smaller than that of subjective knowledge. As already indicated, the effect may be biased owing to the high degree of multicollinearity between both variables. However the relationships found are not too surprising. Chryssochoidis (2000) has already shown that subjective knowledge could interfere with the translation of attitudes into behaviour; less confidence in an individual’s own knowledge may hamper actual behaviour. Further, Selnes and Gronhaug (1986) and Feick et al. (1992) found that subjective knowledge is a stronger motivator than objective knowledge for purchase-related behaviour and House et al. (2004) found a significant positive relationship between subjective knowledge and consumption of GM food, whilst for objective knowledge there was no such relationship. The presence of children in the household has a significant positive relationship with the proportion of organic vegetables consumed. Other researchers have found a similar relationship (Thompson and Kidwell, 1998, McEachern and Willock, 2004, Freyer and Haberkorn, 2008). Other variables included in the model were the income level of the household, the gender of the person responsible for food purchases, the age of the respondent, level of education, region (province) and profession. These have no significant effect on the proportion of organic vegetables consumed. 6. Conclusion In our sample, objective knowledge regarding organic vegetables is high. This is partly due to the overrepresentation of VELT members. However, the non-VELT respondents also have relatively high objective knowledge scores. Attitudes towards consumption of organic vegetables are also largely positive, with 97 per cent of all respondents having a neutral or positive attitude score. The strongest motivations for consuming organic vegetables are that they are produced without synthetic pesticides, are better for the environment, healthier, of higher quality and taste better. As found in other studies, the strongest perceived barriers are overly high prices and lack of availability. Our first hypothesis that “objective and subjective knowledge in relation to organic food production have a positive correlation, but not a very strong one” is confirmed, by the Pearson correlation coefficient of 0.50. Therefore, perceived knowledge is related to actual knowledge but other factors such as self-confidence also have an influence. In relation to the second hypothesis, we found that both a higher level of objective and subjective knowledge are positively related to a more positive attitude towards organic food, greater experience of it and a more frequent use of the information provided by the product tags and organic shops. Membership of VELT, an organisation that promotes an ecological lifestyle and provides its members with a quarterly magazine, covering organic food topics, is related to a higher objective and subjective knowledge score. An interesting finding is that some parameters have a significant positive relationship with subjective or perceived knowledge, but not with objective knowledge. These are male gender, higher proportion of organic food consumption and some sources of information (organic farmers, scientists). This confirms our third hypothesis that stated: “On average men are more confident about


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their knowledge than women”. In contrast to our second hypothesis, education, age and income have no significant relationship with objective or subjective knowledge. Our fourth hypothesis, which assumes that a more positive attitude towards organic food correlates with a higher objective knowledge score, appears to be confirmed. The Pearson correlation coefficient between both variables equals 0.38. However, due to multicollinearity between objective and subjective knowledge, the relationship between objective knowledge and attitude is masked when a multiple regression model is tested, with attitude as the dependent variable and subjective knowledge included as an explanatory variable. We mention that there may be a bi-directional cause-effect relationship between attitude and objective knowledge. On the one hand, people who hold a more positive attitude towards organic food may be more interested and search for more information, thereby increasing their objective knowledge. On the other hand, greater knowledge concerning organic food (production) may have a positive influence on attitude, because the principles of organic food production are linked by consumers in a positive way with values such as “security”, “hedonism” and “universalism”. It would be interesting to see whether future research could provide further insight into the nature of this relationship. Our fifth hypothesis, which indicates that a more positive attitude towards organic food correlates with a higher subjective knowledge score, is confirmed by our analysis. Attitude is also significantly and positively influenced by VELT-membership, norm, motivations and female gender. Perceived barriers have a significant negative influence on attitude. In relation to the sixth hypothesis, our data indicate that the likelihood of consuming organic vegetables is significantly and positively influenced by VELT-membership, subjective knowledge, attitude, motivations and the presence of children in the household. Whilst objective knowledge, norm and female gender have a significantly positive influence on attitudes towards organic vegetables, they have no significant influence on the likelihood of consuming them. The significant positive correlation between higher subjective knowledge scores and higher proportions of organic vegetables consumed is in line with other studies that found that weak perceived self-competence may keep consumers away from organic food, as they feel less capable of making a good choice. Thus, subjective knowledge may interfere with the translation of attitudes and motivations into behaviour(al intention). We conclude that as both objective and subjective knowledge are clearly different concepts and have a different impact on behaviour, it is important to distinguish them. Objective knowledge has a direct and significant positive impact on attitude and motivations towards organic vegetables, both of which have a positive influence on consumption behaviour. However, our findings indicate that objective knowledge has no direct effect on organic food consumption, in contrast to subjective knowledge, which incorporates an aspect of self-confidence that may help to translate attitude and motivations more strongly into (intention and) behaviour. It would be interesting to see whether future research could provide further insight into the relationships between the different variables modelled, as well as to test our findings on other datasets from other regions and on other forms of (consumption) behaviour. Future research could also investigate whether Expectancy Value Theory (Ajzen, 2001, Ajzen and Fishbein, 2008, Fishbein and Ajzen, 1975) is applicable to organic food consumption or, more specifically, how beliefs and values relating to organic food combine in the formation of attitudes and how knowledge may influence the formation of these beliefs.

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