Acceptability of genetically modified cheese presented as real product alternative

Food Quality and Preference 13 (2002) 523–533 www.elsevier.com/locate/foodqual

Acceptability of genetically modified cheese presented as real product alternative Liisa La¨hteenma¨kia,*, Klaus Grunertb, Øydis Uelandc, Annika A˚stro¨md, Anne Arvolaa, Tino Bech-Larsenb a

VTT Biotechnology, PO Box 1500, FIN-02044 VTT, Finland MAPP, The Aarhus School of Business, Haslegaardsvej 10, DK-8210 Aarhus V, Denmark c Matforsk, Osloveien 1, N-1430 A˚s, Norway d SIK, Box 5401, S-40229 Gothenburg, Sweden

b

Received 9 July 2001; received in revised form 14 November 2001; accepted 23 November 2001

Abstract European consumers, in general, have negative attitudes towards the use of gene technology in food production. The objective of this study was to examine whether taste and health benefits influence the acceptability of genetically modified (gm) products when they are presented as real product alternatives. Consumers in Denmark, Finland, Norway and Sweden (n=738) assessed two cheeses: one was labelled as genetically modified (preferred in an earlier product test) and the other as conventional (neutral in an earlier product test). A smaller control group received two cheeses with blind codes. Labelling decreased consumers’ intentions to buy the originally preferred gm-labelled cheese, but still the intentions were at the same level with the conventionally labelled option. Participants chose two gm cheeses out of five possible when given the option to take cheese home after tasting. Intentions to buy gm cheese could best be explained by respondents’ attitudes towards gene technology and perceived taste benefits. General health interest was also a reinforcer of intentions for gm cheese with reduced fat content. # 2002 Elsevier Science Ltd. All rights reserved. Keywords: Gene modification; Consumer attitudes; Acceptability; Cheese

1. Introduction Consumers in Europe have a strong negative attitude towards the use of gene technology in food production (Bredahl, 2001; Gaskell, Bauer, & Durant, 1998). Consumers’ perceptions of genetically modified (gm) foods are dominated by general worries about consequences on health and nature (Bredahl, 1999; Grunert & La¨hteenma¨ki, Nielsen, Poulsen, Ueland, & A˚stro¨m, 2001). Perceived benefits are believed to be crucial for the acceptance of any new products. Therefore it is important to study consumers’ responses to different applications of gene technology in food production. In earlier studies products have been presented as descriptions varying in possible benefits and/or risks. In a study by Frewer, Howard, Hedderley, and Shepherd (1997) seven benefits were associated with new cheese products, which were manufactured with three new processing technologies: genetic modification, protein engineering or traditional breeding of starter culture. The production method * Corresponding author. Fax: +358-9-455-2103. E-mail address: liisa.lahteenmaki@vtt.fi (L. La¨hteenma¨ki).

was a choice factor to most participants, but benefits dominated the reasons for purchase intents. A small group of respondents (12%) perceived enhanced flavour as the major advantage in presented new cheese products. Frewer, Howard and Shepherd (1996) studied how exposure to a variety of genetically engineered products affected consumers attitudes towards gm, but found no effect of exposure on attitudes. The different applications were presented as pictures of products and the used benefits were price, health, shelf life and environmental benefits. In Bredahl’s (1999) study beer and yoghurt were used as example products containing health, sensory, price and environmental benefits in comparison with their conventional counterparts. In both studies the conventional option was clearly preferred over the genetically modified options. Earlier studies have used a variety of product examples differing in their benefits, yet the type of genetic modification has not varied much. Grunert et al. (2001) constructed a design that varied the different applications of gene technology and the distance of gm in these applications from the consumer. The design consisted of product descriptions that had all genetically modified

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material removed during processing and of product examples that had viable genetically modified organisms present in the end product. The overall results were similar to earlier studies: the conventional options were clearly the most preferred, but an interesting finding was that consumers could also distinguish differences among the different applications of gene technology. The nature of the application, such as enzymes produced by genetically modified micro organisms or use of modified raw material, had no clear impact, but the distance of the application from the consumer had. Respondents found products that had both egoistic and societal benefits easiest to accept as genetically modified. The benefits used in earlier studies have not been strong enough to change consumers responses to genetically modified products (Bredahl, 2001; Frewer et al., 1996). The examples employed were descriptions of products and involved no tasting. In interview surveys reported by Hoban (1999), better taste was rated by 62% of the respondents as a possible reason for choosing products produced with modern biotechnology; in Japan this figure was 70%. Good taste referring to pleasant sensory experience is mentioned as one of the key factors behind food choices (Lappalainen, Kearney, & Gibney, 1998). The problem of giving taste as a reason for food choices in a survey is that judging taste within product categories requires direct experience and actual tasting. In experimental situations hedonic value of liking ratings has been a crucial predictor of intentions to buy a product when rated after tasting, especially if the product has been previously unfamiliar (Arvola, La¨hteenma¨ki, & Tuorila, 1999; La¨hteenma¨ki & Tuorila, 1998). Pleasant sensory characteristics are strong motivators for food choice as their rewarding value is based on direct experience delivering immediate reward which requires no previous knowledge. Based on these earlier findings, the objective in this study was to explore the role of experience-based good taste as the motivator for accepting gene technology in food production. Health is another issue frequently mentioned as a reason for food choices (Lappalainen et al., 1998), and emphasizing the role of health is a growing trend. Unlike good taste, health related characteristics are typically not directly observable from the product, instead they need to be conveyed through information. Any piece of information has to be processed in consumers’ minds and linked to the existing knowledge and attitude structure. Therefore, the attention received by any health-related information varies greatly depending on respondents earlier beliefs and motivational standpoints. Because of the strong cognitive component in health related messages they tend to be weak motivators for choices in comparison to taste benefits. People differ in their interest in health issues. General health interest (Roininen, La¨hteenma¨ki, & Tuorila, 1999) measures how important healthiness, in general, is

in food choices. The items in the scale refer closely to choosing options that are advocated in nutrition recommendations, and high scores on this scale reflect willingness to comply with the nutritional guidelines. When health benefits are achieved by the means of modern technology, such as gene modification, this may alter the value of nutritionally recommended characteristics such as low-fat content. Acceptability of gene technology in food production can also be related to several other attitudinal factors. First of all, use of gene technology in food production brings new kind of novelty to food products. Although the end product may be the same as the conventional product, highly specialized technological expertise is needed in production. Food neophobia-scale (Pliner & Hobden, 1992) measures individuals’ willingness to taste new foods with distinctive sensory characteristics well, but the relationship between the scores on this scale and reported intentions to buy genetically modified products such as yoghurt or beer have been weak (Bredahl, 2001). Alienation from the market place was another attitude scale that was related to perceived risks of genetic modification in Bredahl’s (2001) study. Alienation from the market place-scale describes consumers separation from the norms and values of the market place (Allison, 1978). High scores in this scale mean that respondents feel distrust towards the usual channels through which new products are marketed. Attitude towards gene technology has been negatively associated with the general attitude to nature (Bredahl, 2001). In studies based on interviews, applying gene technology in food production has been regarded as unnatural and risky for the nature. Therefore, high regard towards nature should make people more suspicious towards gene technology. Attitude to technology reflects respondents’ belief in the ability of technological progress to solve the world’s problems in the future. As gene technology is one sub category of technology, overall attitudes towards gene technology have correlated positively with the positive disposition to technology in general (Bredahl, 2001). The aim of this study was to examine how consumers respond to genetically modified products when they are presented as real product alternatives and contain both experience-based taste benefits and knowledge-based health benefits. The aim was also to study the role of different attitudes in the acceptance of these genetically modified products.

2. Methods 2.1. Overall design The study consisted of two sessions which were organized 2–3 weeks apart. In the first session eight cheeses

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were assessed in a product test and, based on the results of the first session, two of these cheeses were selected for the second session. In the second session the selected two cheeses were labelled as either conventional or genetically modified. 2.2. Respondents Respondents (17 years or over) were recruited from Denmark, Finland, Norway and Sweden with the target of 200 participants from each country. In Finland and Norway, the recruiting was done in co-operation with sports clubs by promising them a fee around 12 Euros for each recruit. In Sweden, the participants were recruited through a research agency and in Denmark a consumer panel was used. Despite the differences in the recruitment process, which caused some differences in socio-demographic background of respondents, the results from the four Nordic countries are almost identical and therefore the data are analysed across countries in one set. Recruits were told that the study is part of a product development test and in addition there are some general questions on factors that influence food choices. A total of 738 respondents took part in the two sessions the study required. Sixtyone per cent of the participants were women and 39% were men. Their age varied from 17 to 76 years, mean was 40 years. Participants were relatively well educated as less than 15% had only secondary school education and 42% had university or college degrees. Minority of participants lived on their own (7%), and 68% had children under age of 18 living in their household. 2.3. Samples Hard yellow cheese was selected as a model food for the study. Based on earlier findings (Grunert et al., 2001) cheese was believed to be more sensitive with respect to genetic modification than foods of plant origin but still more acceptable than meat or fish. Also cheese has a lot of product variety and it is a comparatively easy material to handle in tasting tests. Eight brands of cheese were selected for the study. They were all typical cheeses eaten in Nordic countries, thus providing respondents more and less familiar options in each country. Some of the cheese samples were low-fat options. From the study point of view, the aim was to provide a variety of tastes so that each respondent could find those options they preferred and those they felt neutral about in a product test. 2.4. Procedure The first session was carried out like a product test with eight different cheese samples to taste. The liking

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for the cheese was assessed on a nine-point category scale anchored from the ends (1=I do not like at all; 9=I like a lot; please note that in Scandinavian languages word dislike as an opposite of like does not exist). Correspondingly, the willingness to buy the cheese was evaluated with a scale ranging from 1=I will not buy to 9=I will certainly buy. The eight cheese samples were cut into cubes (approximately 1.51.51.5cm) and presented with three digit constant codes in randomized order for each respondent. Randomly chosen constant codes were used to help the practical arrangements. After the tasting task, the participants filled in a questionnaire that contained several attitude measurements and questions on socio-demographic variables. The attitude scales included in the first part were Food neophobia (Pliner & Hobden, 1992), General health interest (Roininen et al., 1999), Alienation from the market place (Allison, 1978), and involvement in cheese as a product category. Attitude items were rated on seven-point category scales (1=strongly disagree; 7=strongly agree). Socio-demographic questions were gender, year of birth, level of education, number of persons in the household, number of children under age of 18, and level of income. Also the use frequency of regular and low-fat yellow hard cheeses was asked. The respondents returned to the second session about 3 weeks after the first session. The second session consisted of three tasks: (1) tasting task including choosing cheeses, (2) rating 16 product descriptions and (3) answering a questionnaire with attitude items. The respondents were divided into three groups: two experimental ones and a control group. In the tasting task respondents were presented with two cheese alternatives. A short description of cheese production was included in the rating sheet. The description stated that a starter culture containing micro organisms is used to create the texture and flavour of cheese during maturation, and that typically this starter culture dies out during storage, but it is possible that some are viable in the end product. After this, in the experimental groups the alternatives were labelled conventional and genetically modified either without or with a health benefit (see Table 1 for the experimental setting). The two cheeses were individually picked up from the first session so that the cheese labelled as conventional was rated neutrally among the eight alternatives and the gm-cheese was a liked option (Table 2). The preferred cheese was selected as the cheese having the highest liking rating for each respondent. The neutral cheese was selected by first calculating the distance between the best and the least liked options, and then adding a third of this distance to the least liked score, and finally selecting the option that was closest to this value. The purpose of this calculation was to avoid clearly not liked cheese

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Table 1 Experimental design and labelling of the samples in the second session

Experimental group 1 (n =332) Gm with taste benefit Experimental group 2 (n=313) Gm with taste benefit+health benefit

Control group (n=86)

Table 2 Cheese options chosen as liked and neutral options for the second session Cheese option 1 2 3 4 5 6 7 8 Total

Liked option (%)

Neutral option (%)

14 15 11 6 24 15 9 7

12 9 9 12 9 8 24 17

101

100

Mean hedonic rating (%)

SD

6.0 6.1 5.7 4.9 6.3 5.3 4.7 4.6

2.1 2.0 2.1 2.4 2.3 2.7 2.3. 2.3

options and to adjust the possible differences in the individual use of response scales. In the control group the cheeses were selected similarly, but they were presented with three digit constant codes. The conventional and gm-cheeses were equally often served as the first and the second sample in the test. The liking for the cheeses and willingness to buy them were rated on the identical nine-point scales as in the first session. Respondents were allowed the option to refuse to taste the cheeses if they wished. Only two participants refused to taste gm-cheese. At the end of the tasting task, in the experimental groups the respondents were asked about taking cheese home with them as a reward for taking part in the study. They were offered five pieces of cheese which they could combine freely from conventional and gm-cheese. This meant that they could choose from 0 to 5 gmcheese. They were also given the option not to take any home. After the tasting task, respondents were given descriptions of 16 product alternatives (both gm and conventional) that had varying health benefits and participants were asked to rate their willingness to buy these products, if available in shops. This part will be reported separately. At the end of the second session respondents filled in a questionnaire containing measurements of attitudes towards technology, gene technology and nature. Two

Preferred in session 1

Neutral in session 1

Produced with the genetically modified starter culture Produced with the genetically modified starter culture. Contains one third of the fat of regular cheese Three-digit random code

Produced with conventional starter culture Produced with conventional starter culture

Three-digit random code

attitude scales were used in this study to measure attitudes towards nature. General attitude to nature was a short version earlier applied by Bredahl (2001). In addition, the Natural product interest-scale was used to measure the importance of naturalness in food purchases. This scale measures individuals’ tendency to avoid additives and choose options that are grown and produced as naturally as possible (Roininen et al., 1999). High score on this scale means that the respondent opposes the use of artificial technologies and ingredients, and thereby should also have a negative attitude towards gene technology. General attitude towards the use of gene technology has been measured in several ways (Bredahl, 2001; Frewer et al., 1996; Hoban, 1999). In this study attitude to gene technology was measured by semantic differential approach using six items of bipolar attributes. Some of these attribute pairs (e.g. good–bad) reflected clearly the affective part of the attitude and some the more cognitive part (e.g. foolish–wise). In addition, the attitude scale contained two items on rennet (=chymosin) produced with the help of genetically modified micro organisms instead of using calf’s stomach, as this is the widely discussed gm application in cheese production. At the end of the session participants were given a piece of cheese as a reward and handed a one-page leaflet telling about the purpose of the study. The leaflet also informed participants that all the cheeses they had tasted during the study had been conventionally produced. A contact number for further queries was given in the leaflet. 2.5. Data analysis Data were analysed using SPSS for Windows release 10.0.5. The means of rated intentions to buy and liking for cheeses were calculated, and the differences between the experimental and control group were tested with multivariate anova models. Time (random coded vs. labelled) and type of product (preferred/gm-labelled vs. neutral/conventional labelled) were within subject factors and experimental groups (plain gm-label vs. gm-label & reduced fat vs. control group) were between subject factors. Statistically significant interactions were further

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tested with simpler ANOVA models and contrasts were build to compare differences between experimental groups and control group and within the experimental groups. Contrast tests not assuming equal variances were used when appropriate. Frequencies and means were calculated for the choices of genetically modified cheese. The effect of gender (women vs. men), age (3 groups), education (3 groups) and experimental condition (3 groups) on intentions to buy gm-labelled cheese or choose gmcheeses were tested with four-way ANOVA model. Attitude scales were constructed from separate items by first reversing the coding for those items that were negative and then by calculating the sum of item scores (Table 3). The reliability of the scales was good when assessed with Cronbach’s alpha. Hierarchical regression analysis was used to explain the intentions to choose the labelled cheeses and choices of gm-cheeses. In the first model, only attitude towards gene technology was entered, and then in the second model the rest of the attitude scores were forced to the regression equation as their intercorrelations were moderate. After this, in the third model, taste benefit which was operationalized as the difference in liking between gm-labelled and conventionally labelled cheese, was added to the regression equation.

3. Results 3.1. Liking ratings in the first session The respondents’ liking for the eight cheese options varied widely in the first session (Table 2). Although the means (range from 4.6 to 6.3 on a nine-point scale) were rather close, the high deviations of ratings reflected the wide differences among the respondents. Therefore all options could be used both as neutral and preferred options for the second session, thus balancing any effects which may be caused by single cheeses. The means of liking and intention ratings both for the preferred and neutral options, were in the same level in all

study groups, and there was a clear difference in the ratings between the preferred and neutral options (see Fig. 1, ratings of random coded samples). 3.2. Liking for and intentions to buy the labelled cheese in the second session When only two cheese options were tasted, the liking ratings converged strongly [F(1, 729)=576,5; P < 0.001; Fig. 1)]. The trend was similar whether presented with three digit codes in the control group or with gm and conventional labels in the experimental groups (interaction group, time and type of product; F(2, 729)=2.5; P=0.082). Similarly to liking ratings, intentions to buy converged when only two options were presented (Fig. 2), but the degree of convergence differed among groups (interaction between group, time and type of product; F(2, 724)=6.1; P=0.002). The difference came from responses to originally preferred cheese labelled as gm, whereas the originally neutral cheese labelled conventional, did not differ among experimental groups before or after labelling. The intentions to buy the originally preferred cheese after gm-labelling were lower in experimental groups than in the control group without labelling (contrast test; df=123,1; t= 5.3; P < 0.001), but still the intentions were at the same level with the conventional cheese. The experimental group tasting allegedly reduced fat cheese rated intentions to buy gm cheese slightly higher than the group that had plain gmcheese (contrast test; df=624,4; t= 2.0; P=0.049). Gender, age and level of education had very little impact on intentions to buy gm-cheese. The only effect approaching statistical significance was education (F(2, 723)=3.0; P=0.051). When examined more closely, those with university degrees were less willing to buy gm-cheese than other respondents in experimental condition where the cheese was labelled plain gm without the health benefit. When the gm-labelled cheese had reduced fat content no difference among educational levels was found.

Table 3 Attitude scales used in the study

Food neophobia General health interest Alienation from the market place Attitude to nature Attitude to technology Natural product interest Attitude to gene technology

Theor. Min.

Theor. Max.

Range

Mean

SD

Item-adjusted mean

Reliability Cronbach alpha

10 8 5 6 5 6 8

70 56 35 42 35 42 56

10–61 8–55 6–35 17–42 5–35 6–42 8–56

29.6 35.3 18.8 33.0 21.7 27.6 25.1

9.4 8.7 4.6 5.4 5.2 7.1 9,5

3.0 4.4 3.8 5.5 4.3 4.6 3.1

0,74 0,76 0,47 0,59 0,72 0,79 0,85

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Fig. 1. Liking ratings of cheese samples before and after labelling.

Fig. 2. Intentions to buy ratings of cheese samples before and after labelling.

3.3. Choices of genetically modified options When respondents were offered five pieces of cheese to take home after finishing the study, they showed clear curiosity towards gm-cheese. Two thirds (68.4%) of the respondents wanted to take at least one gm option and 41.8% wanted to take at least three (=over half ) of the cheeses as gm alternatives. In total, 12.9% wanted to have all pieces of cheese as gm. Respondents who were exposed to gm-cheese with low fat content were more willing to take gm-cheese home with them compared to those

respondents who tasted cheese labelled simply gm (2.2 vs. 1.8 pieces out of 5; F(1, 649)=8.6; P=0.003). Like intention ratings, socio-demographic background variables could explain only marginally the number of gm-cheeses chosen in the choice task. Gender and education interacted with the type of cheese tasted in experimental conditions (P=0.041 and P=0.044, respectively), but none of the means differed significantly between men and women or among the educational groups from each other when using bonferroni test within experimental groups.

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3.4. Attitudes measurements and willingness to use gmcheese As expected based on the earlier findings, the respondents’ attitudes towards the use of gene technology were rather negative (Table 3). The mean rating was below the midpoint of the used response scale (item-adjusted mean in Table 3) thus representing the negative poles of attribute pairs used in the attitude measurement. Consumers had rather low food neophobia-scores, and they did not feel strongly alienated from the market place. General health interest-scores were moderate as was attitude towards technology. Scores on both attitude towards nature and natural product interest-scales were rather high although these two measures correlated only moderately. Correlations among attitude measurements were in the expected direction so that attitude towards gene technology correlated positively with the technology attitude and negatively with the attitudes towards nature or natural product interest (Table 4). With some exceptions, correlations among attitude scales were moderate, which means that they measured different phenomena and could hence be used as independent variables when intentions were explained (Fig. 3). 3.5. Predicting intentions to use and choices of gmcheeses with attitudes and differences in liking ratings For intentions to buy gm cheese attitude towards gene technology was the best predictor that could, in its own, explain 21% of the intentions in experimental group 1 and 14% in the experimental group 2 with reduced fat cheese (Fig. 3). Other attitudes had a very minor impact in intentions. When gm-cheese had reduced fat content general health interest-score had a positive impact and natural product interest-score a negative impact on intentions. Taste benefit (operationalized as the difference in liking between gm and conventional option) added the explanatory power of the model considerably, but still less of the intentions to buy gm cheeses could be

explained than of the intentions to buy conventional cheeses, which were explained only by the taste benefit. Similarly intentions to buy blind coded cheeses in the control group could be explained by the taste benefit. When gm-choices were predicted likewise, attitude towards the use of gene technology was the best predictor explaining 29% of the choices in experimental group 1 and 20% in group 2. Taste benefit increased the predictive power of the equation significantly. The gm choices could be explained better by the regression model, and the attitude towards gene technology had a bigger role in explaining choices than in explaining intentions to buy. 3.6. The role of product exposure on attitudes towards gm As attitudes towards gm were measured after the tasting, it is possible that the exposure to gm-labelled products also influenced the attitudes. Therefore the means of attitudes were compared among the three experimental conditions. Although attitude to gene technology was more negative in the control group (mean 22.4; item-adjusted mean 2.8) than in those groups that tasted gm (mean 25.4, item-adjusted mean 3.2), this difference cannot explain the differences in responses to gm-products within experimental conditions. The intentions to buy genetically modified cheese or choices of gm-cheese made in the experiment increased considerably when the attitudes turned less negative (Fig. 4).

4. Discussion The general attitude towards the use of gene technology in food production was negative in this study, as it has been in earlier studies (Bredahl, 2001; Gaskell et al., 1998). In previous studies consumers’ willingness to choose or use gm-options have been clearly lower than their willingness to choose the conventional options when product descriptions have been used (Bredahl, 2001; Frewer et al., 1996; Grunert et al., 2001). This study

Table 4 Correlations among attitude scores in combined data—all countries Food Neophobia Neopho GHealthI. Nature NatProductI Alienation Technology GM * P <0.05 ** P <0.01 *** P <0.001

1.00 0.02 0.13*** 0.13*** 0.11** 0.04 0.07

General Health Interest 1.00 0.05 0.37*** 0.04 0.12** 0.09*

Attitude to Nature

1.00 0.25*** 0.09* 0.33*** 0.16***

Natural Product Interest

1.00 0.12** 0.30*** 0.48***

Alienation from the market place

1.00 0.19*** 0.08*

Attitude to technology

Attitude to gene technology in food production

1.00 0.28***

1.00

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Fig. 3. Predictive value (R2 adjusted) in hierarchical regression models explaining intentions to buy cheeses in both experimental and control group and genetically modified (gm) choices in experimental groups. In level 1, only gm attitudes are included in the model, then in level 2 other attitudes are added, and finally in level 3, the taste benefit.

demonstrates that although general attitudes towards gene technology are negative, this negativeness is not expressed as strongly in product related responses and does not make specific products rejected. The willingness to buy gm-options stayed higher or at the same level as for the conventional option and they were clearly above the midpoint in the intention scale. Similar to Frewer et al. (1997) findings with product descriptions, the production method is just one reason behind choices, and product specific benefits have an impact as well. The negativeness of overall attitudes and the similarity in intercorrelations between attitude measures with earlier findings (Bredahl, 2001) indicate that these results are based on a population comparable with those studied earlier. The attitudes towards genetic modification were the best predictors of intentions to buy genetically modified products. Although, the overall attitudes were rather negative, the third of the respondents with most positive attitudes showed a clear interest in products produced with the help of gene technology. The other attitudes had very little direct impact on intentions and choices, which implies that the attitude towards genetic modification dominates the perception of these products. The attitude towards nature, for example, was linked to the attitude towards gene technology, and therefore has an indirect impact on willingness to try genetically modified products. Neophobia towards food or alienation from the market place, which both echo general distrust dimensions could not explain the negative attitudes towards gene technology. The low acceptance of genetically modified products has been explained by the fact that, sofar, the applications

have only benefitted the producers and agroindustry, not consumers. Consumers’ perception of benefits depend on their own motivation and expectations. Some attributes can be strong benefits for some consumers while others disgard them with little interest. In earlier studies, perceived benefits have been important to the acceptance of genetically modified foods to various extent. When familiar conventional counterparts have been presented among product descriptions, benefits have not influenced acceptance or attitudes towards genetically modified products (Bredahl, 2001; Frewer et al., 1996), whereas in the study by Frewer et al. (1997), comparing gm with two other new processing methods, benefits achieved by genetic engineering increased acceptability. Especially health and environmental benefits were strong motivators for reported purchase intents. According to our earlier study in Nordic countries, benefits that are both good for the individual and have societal importance may be the easiest to accept among gm products (Grunert et al., 2001). One of the strongest motivators behind repeated choices is hedonic pleasure derived from good taste (Arvola et al., 1999; Lappalainen et al., 1998). To achieve a real hedonic benefit, however, products have to be tasted. In this study, due to the known fact that gm is perceived very negatively, we wanted to have a very strong hedonic benefit by using individually tailored taste benefit. The taste benefit clearly helped the willingness to buy genetically modified products on the top of attitudes, although the part of the intentions and gmchoices that could be explained by the taste was smaller than it was for the conventional options. The acceptability

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Fig. 4. (a) Intentions (means and SD) to buy genetically modified-labelled cheeses according to attitude towards gene technology. (b) Choices (means and SD) of gm-cheese in choice task according to attitude towards gene technology. Respondents were divided into three equally sized groups according to their score on attitude towards gene technology.

of genetically modified products remaining at the same level with the conventional options is an exeptionally positive result for genetically modified products in consumers studies (Bredahl, 2001; Frewer et al., 1996; Grunert et al., 2001). Half of the respondents also had a health benefit in getting information about cheese being low fat. A health benefit was perceived as one of the strongest benefits in an earlier study by Frewer et al. (1997). The health benefit in this study was selected so that it would have relevance to many respondents and, at the same time, also contain a societal benefit, as an aid to reduce weight and thus improve national health. Combined societal and egoistic benefits were perceived positively in our earlier study (Grunert et al., 2001). However, reduced fat as a health benefit had only a marginal effect

on the acceptance. Although the effect was marginal it seemed to improve acceptance among those respondents who had the most negative attitudes towards genetic modification. Also the impact seemed to have a delay: if the tasted cheese had the additional health benefit, the choices made about taking genetically modifed cheese home were more positive than if only plain gm cheese was tasted. The exposure to genetically modified products seemed to influence the later attitude ratings by making them more positive towards genetic modification. The negative attitude towards genetic modification seems to be based on uncertainty of the consequences gene technology has on health and nature (Bredahl, 1999; Grunert et al., 2001). This uncertainty may be reduced by exposure in a similar way that any new food product can be made

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more familiar to the consumer, namely tasting, information and association with familiar foods. The taste exposure is known to increase willingness to try a product (Tuorila, La¨hteenma¨ki, Pohjalainen, & Lotti, 2000), especially if it is a positive taste experience (Loewen & Pliner, 1999; Pliner, Pelchat, & Grabski, 1993). The responses to genetically modified food have earlier been studied in surveys and with product descriptions, which enable these foods to stay mere abstract concepts in consumers’ minds. In addition to tasting, the familiarity of genetically modified products can be increased by giving information about the product, but the effect of information has varied widely in making new foods more familiar (e.g. McFarlane & Pliner, 1997; Tuorila, Meiselman, Bell, Cardello & Johnson, 1994). Although the experimental design allowed the manipulation of individual taste benefits, it had some weaknesses and uncontrollable elements. Picking the two cheeses out of the product test with eight cheeses turned out to be a problematic solution, as the liking and intention ratings of the originally highly preferred and neutral options converged strongly also in the control group, similar to the experimental groups. One explanation for this convergence is the difference in the stimulus range and central tendency in responding (McBride, 1982; Poulton, 1977). Central tendency implies that the presented stimuli in a test will be rated around the midpoint of the used scale. In this study, when only two cheese samples were presented instead of the previous eight samples, the perceived differences in liking and use intentions of these samples could be rated with a smaller range using the scale close to the midpoint. Eight samples offered more variety and therefore a wider range of the scale was needed to express differences among them. Stimulus range is known to have an effect on hedonic responses (McBride, 1982; Riskey, Parducci & Beauchamp, 1979), but there appears to be no studies which have compared the specific effect of the number of alternatives presented to respondents on hedonic ratings. In our design the target was to have cheese samples that clearly differed in their pleasantness, in which we succeeded, and the control group allowed us to compare the effects of labelling with the situation were the cheeses were just tasted in the same manner for the second time. Tasting the gm cheeses seemed to shift the attitudes towards gene technology into a positive direction. The order of attitude measurements is another problematic issue in these kind of studies. In this study, we wished to have the behavioural responses to genetically modified products before we asked about attitudes, and thus evoked the possible negative attitudes consumers have in their minds. However, by doing this, we may have respondents who adjusted their attitudes according to their previous responses in behavioural tasks. The difference in attitudes towards gene technology between the control group and experimental groups was statistically significant, but

relatively small indicating that this effect was rather weak. To balance and measure these order effects, the study would have required a design where the participants had been divided into further two groups, which would not have been feasible without increasing the number of respondents. This kind of design also requires that participants are misled to some extent. As we had to let the respondents to believe that the cheeses we presented were gm, we could tell them only afterwards that the cheeses were just labelled gm. Respondents were clearly offered the option of not tasting the gm cheese, but very few used this option. Tasting allegedly genetically modified products seemed not to be a problem for respondents. This reflects the earlier findings that the worry about gm is based on its possible effects on the nature and undefined health concerns, which are both strongly cognitive factors rather than affective rejection of gm alternatives or disgust towards their origin. As gene technology is associated with uncertainty and undefined worry about health and nature, exposure to gm products probably made them more familiar and reduced the mystified unfamiliar component. Gene technology is a newcomer in the food domain and usual associations with genes are probably far from typical food concepts. Therefore, people may have difficulties in imagining the genetically modified options as concrete product examples instead of having abstract concepts in their minds. Adding familiar components to previously unfamiliar foods increase their familiarity, which should breed acceptance. Familiar sensory characteristics with a perceived taste benefit may have reduced the unknown component in genetically modified foods and thus increased the acceptance. This study shows that, although consumers have an overall negative attitude towards gene technology, this negative attitude does not cause consumers to reject genetically modified options if they are presented as real product alternatives. Taste benefit seems to be a strong promoter for genetically modified products, and health benefits are also perceived positively. Consumers with the most positive attitudes are curious about gm-products and exposure to these products also influenced responses of those with the most negative attitudes towards gene technology.

Acknowledgements The authors wish to thank Nordic Industrial Fund for partly financing this study with their grant P98098.

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