Consumer Attitudes Towards Genetically Modified Food
This section reviews the various tools and constructs that can be employed to analyse the consumer attitudes towards the different nuances of genetically modified foods. The research design, research strategy, data collection and methods of analysing the collected data. The methods and constructs are borrowed from the best statistical practices of the chosen variables.
This research intended to define the consumer attitudes towards genetically modified foods based on the litany of research and theoretical conceptualization of this construct in its various operational variables. Hyde classifies such research as deductive rather than inductive, as it aims at testing hypothesis against existing theoretical models supplemented by empirical data (85). Alternatively, an inductive research aims at validating theoretical constructs rather than testing hypothesis (Gray 16).
This research followed the design of a descriptive study as it intends to vividly illustrate the factors that diver the attitudes of consumers regarding genetically modified foods. Such a design is suitable for determining the relationship between defined and measurable variables in relation to a demographically defined population (Dhawan 42). As such, subject matter covered a marsh of quantitative and qualitative operational proxies; however, the design of the data collection and analysis largely focused on the quantitative aspects of the data as it would lead definitive conclusions with minimal theoretical nuances behind the analysis. Moreover, Creswell encouraged the conservation of time in deciding about a research method, and quantitative measures are relatively faster as seconded by various researchers (29). As is necessary in this case, Saunders, Phillip and Adrian convey that reliable scheduling was more likely with quantitative methods rather than the unpredictable and relatively longer schedules with qualitative research methods. The academic setting within which this research was being conducted provided a limited time frame within which it could be conducted; therefore, quantitative methods were the logical option to timely project scheduling.
Moreover, this research would adopted an explanatory research design as the variables in themselves underwent regression analyses to comprehend the relationship between the different facets of the wide topic that is under research (Robson, 2002).
Since the research purposed to answer a “what?” question, Yin (2009) favours the survey strategy that was then used to conduct the research. Not to be confused by archival analysis owing to their overlapping subject area in various topics, survey strategies are meant for descriptive studies that approximate statistical conclusions for specific populations from primary data. Luckily, the survey had enough quorum within Hatfield to offer their participation.
Both primary and secondary data were utilized for this study.
Genetically modified foods were introduced in 1994 with the ground-breaking FLAVR SAVR tomato that had an extended shelf life. Thereafter, there have been numerous transgenic plants developed and planted across the world for various reasons like pest and insect resistance, weather resistance and numerous others. As of 2014, 18 million farmers located in 28 countries plant around 181.5 million hectares of GM crops which is approximately 13% of the available arable space (Lucht 4254). With GM crops, the performance of the agriculture industry has grown significantly. Profits have increased, crop production is soaring and pesticide expenses have dwindled considerable. However, these figures mostly applied to developing countries vis-a-vis developed countries. These advantaged afforded by GM foods to farmers and consumers are only applicable in these areas because of their lack of convenient alternatives. These foods are largely fed to animals across the world. However, despite the high trade volumes, GM foods receive significant policy regulations to ensure their labelling is apparent to consumers.
Global crop production has significantly reduced over the past few decades. This drastic drop in crop production was attributed to actions of pathogens, parasites, global warming due to carbon dioxide emission and excessive use of inorganic fertilizers. A study that was conducted by Key, Ma, and Drake (290-298) established that the use of GMOs will increase food production as some of the GMs are pest resistant. In their report, Key et al. noted two commercial GM crops that were resistant to insecticides (296): Bacillus thuringiensis and the virus-resistant GM papaya. The two GM has been tested in the US and they have been successful. For example, the country has grown over 10.6 million hectares of maize where 35% of GMO based. The investigators further observed that the laboratory report of both the GM and Non-GMO from the American maize fields showed that the former was more resistant (290-296).
In the same study, Key et al. noted that the primary cause of global plant loss was the abiotic stress that results from unfavourable conditions such as salinity, increase in temperatures (global warming), and drought (290-295). It is projected that by 2050, salinity and drought will cause serious reduction of the arable land as a result of desertification. Therefore, scientists and economists have identified GMO technology as a viable means to ensure crop survival in these extreme conditions. Although not all crops have been tested, GMO rice has been successful in saline conditions in Bangladesh and Malaysia. Collard, et al. (169-173) Through the use of DNA molecular maker, rice germination tolerance levels have been improved through the use of Quantitative Traits Loci (QTLs). Consequently, other cereals are being tested on where their modified seedlings will do well in unfavourable conditions. However, scientists are optimistic that GMO is one of the short-term solutions to food security in the current environment that is characterized by pollution and other activities that cause environmental degradation.
In their study, Baker and Burnham are representative of a building array of research that looks into consumer attitudes towards genetically modified foods (387). They looked into the acceptance of genetically modified (GM) corn flakes in the US and found that 30 percent of consumers were keen to note the GM inclusion in foods. These findings back the cognitive constructs that influence consumer behaviour such as tastes, beliefs and awareness. Ducoffe postulated the constructs of informativeness, entertainment, credibility and familiarity as the attitude defining variables of consumer attitudes in his study about attitudes towards mobile advertising (21).
Mendenhall and Evenson found that sociodemographic variables such as income level and literacy level were poor variables in correlating against consumer behaviour in relation to GM foods (59). The only construct that showed significant correlation was gender (female) and their concern for safety in regards to GM foods. Furlow and Knott also found this health information-seeking behaviour of women when it comes to food labels and others. This correlation is an extension of Dutta-Bergman’s finding of health behaviours, attitudes and cognition regarding health-seeking behaviour.
Shrum et al. tracked consumer awareness against environmental performance of companies with varying results (71). Chase and Smith reported the means of confiding the environment performance of a company or a product (S-12). An overwhelmingly positive environmental performance rating breeds contempt from consumers as organizational CSR performances are rarely factual or promising. Similarly, the environmental benefits that arise from GM foods have been documented; however, there has been significant cynicism surrounding its perquisites as consumers believe it is too good to be true. Therefore, consumer attitudes are askew across a subjective population with different consumer attitudes and behaviours. Moreover, Loureiro and Bugbee already found that consumers would not pay extra for GM foods even if they have better flavour and nutritional value. These negative receptions follow the protests that occurred in California and around the world. Consumers were showing an awareness of GM foods as they picketed insisting on the labeling of GM food. They claimed it was a violation of the consumer rights as companies were not under any pressures to distinguish GM and non-GM foods (Linnhoff et al. 3).
Also, a significant amount of research suggests that American consumers accept GM foods more than their European counterparts (Le Marrea et al. 97; Colso and Rousu 29). This framework is utilized in various researches in assessing consumer attitudes across the nations.
In spite of the above advantages of GMOs, the public has not accepted these foods fully. In fact in some countries, GMOs are not legalized. Reluctance in accepting the GMO is caused by the public ignorance about the safety of these genetically modified foods. Indeed various biologists and agronomists have done research on the safety of GMOs and established that they safe for consumption (Magaña-Gómez and Calderón de la Barca, 1-16). However, their production has to be closely monitored to evaluate their risks assessment. For instance, GMOs that are produced in the US and European countries are safe due to close monitoring by Food and Drug Agency and European Food Safety Authority respectively. In this regard countries that have no infrastructure to develop and analyse the content of the GMOs will have to use those from the developed countries. Generally, GMOs undergo extensive testing for safety before they are released for commercial use hence it can be argued that they are safe for consumption. Moreover, in the US, GMOs have been consumed over 15 years and there are no reported cases on the negative effects of GMOs to the consumer. However, there is little evidence that has been documented to show that GMOs are potentially harmful although studies are being carried in this area. However, there exists a report that was published in 1999 showing that GM potatoes that were fed to rats showed gene for the lectin Galanthus nivalis which led to the animals suffering agglutinin damage (Magaña-Gómez and Calderón de la Barca, 1-16).
Jonas-Dwyer and Pospisil also concluded that young people have a higher likelihood of favouring technologically-enhanced GM foods as they are invested in technology. Despite being the architects of damaging demonstrations against GMO, their issues were just a single aspect of the facets used to determine their attitudes for the products; informativeness. As such, GM-producing entities are implored to publish facts and research publications on their online platforms, media releases and other functions to mitigate the unfounded negative consumer perception that needs to witness the credibility of the products to develop an interest in them. The political vocalization of the issues surrounding GM foods by opposes have brewed concern among consumers. All the while, scientists and regulatory bodies already issues the green light on GM foods that have since been mitigating global hunger issues. Castle appreciates the turn of the tide with regulatory boies and public opinion shifting towards embracing GM foods.
Moreover, a fourth facet of Duscoffe’s constructs for consumer attitudes is entertainment. Interaction with such foods is rarely an entertainment-worthy moment; however, the presentation of products has to have a relatable aspect of it that makes entertaining. Shao, Cai and Chen believe that consumers and retailers alike do not comprehend the essence of GM foods; hence, the low public acceptance. Phillipov developed a framework of developing consumer trust based on how key supermarkets mitigate the negative perspectives of their food ethics, market regulation and supply chain. Developing trust with the consumer till they enjoy the product – hence, the entertainment value – is a crucial milestone for GM foods.
However, conducting surveys to understand the impact of such presentation to consumers with their subjective backgrounds is still elusive (Lusik et al.). Consumer behaviours in actual shopping scenarios are yet to be estimated by the available constructs. Knight et al. conducted market research on organic, GM and conventional fruits around Europe and found that GM foods had market share of 20% without price competitiveness. The novelty of GM foods does not assist in its study as most of Europe is yet to engage with these foods regularly. Consumer attitudes towards genetically modified food are thus instantaneous and subjective depending on the social setting that one encounters it. However, various experiments have revealed that the market share for these products is not dismissible despite its relatively lower proportion than other food categories (Sleenhoff and Osseweijer 165). Subsequently, the poor performance GM foods in European markets is not the substance of universal rejection by consumers; rather, the systemic marketing flaws by GM food growers, manufactures and retailers (Aerni 1129). Hess et al. note that the European market is keen on the potential risks and ethical ramifications of testing the bounds of science with genetic manipulation. This context contributes to the earlier discussed framework of the US being more receptive to GM food products as their surveys rarely have such deep focus on the vices of technology. As such, as intended in this research, there is the challenge of overwhelming the sceptical attitude of Europe by assaying other measures of consumer attitude rather than ethics. Indeed, Chase and Smith, as in this case, rightly suggested that an overkill in perceived CSR was less productive to the overall agenda of consumer attitudes and behaviours. There are other aspects such as product details to inform consumers, its portfolio to enhance its credibility, and creative marketing to spark interest of the product (Ducoffe 21). Therefore, a questionnaire should follow such a structure that entirely addresses the constructs that consumers draw from when assessing products.
However, to topple unwarranted consumer attitudes to an industry of its qualitative substance, GM food has to topple the status quo defined by Lefevre in his research showing that people would pay extra for products with health perquisites such as organic or non-GMO foods. The basis of this argument makes the probable prevailing attitudes towards GM food obvious at the onset; nevertheless, for the vast business structure that has failed to reach its peak, the public opinion has to be changed.
The project management team assembled various operational proxies constructed from the theoretical and conceptual frameworks that informed the synthesis of the hypothesis. They held a workshop that reviewed pre-existing studies on consumer attitudes and the measurable constructs of GMO foods that can be assessed. With these arsenal, the project management team intended to create a questionnaire that met the following objectives:
Does the population know to distinguish genetically modified foods from non-GMO foods?
To identify the primary attitudes towards GMO foods across different demographic groups across the Hatfield populations.
To determine the characteristics of consumers of GMO foods across the population.
Identify the level of awareness regarding the major themes surrounding GMO foods across the Hatfield population.
To establish the ideal the personal, community and global perceptions of the role of GMO in the society.
To extrapolate the findings of the collected data to the entire population of Hatfield and other regions with similar demographic characteristics.
To determine the ideal nutritional sources that the population expects from food providers and retailers.
22707607620Familiarity with genetically modified foods
Regularity of consumption
Awareness of genetically modified food
Familiarity with genetically modified foods
Regularity of consumption
Awareness of genetically modified food
10801351422401537335313055Consumer attitudes towards Genetically Modified Foods
Consumer attitudes towards Genetically Modified Foods
Figure 1 Conceptual Model and operationalization
The first part of the questionnaire was structured to collect the participant’s demographic instruments such as age group, gender, educational status and marital status. The second section had a primary focus on the familiarity with the production, manufacture and consumption of genetically modified food. This section sought to find the intention to consume and their behaviour in response to genetically modified foods. The questionnaire created a semblance of Ducoffe’s instruments that he used to measure the attitudes towards genetically modified foods that. They were irritation, informativeness, entertainment and credibility (21). These operational proxies were disambiguated into questions that sought to answer them in a measurable qualitative dimension. Tsang et al. used the same instruments to determine consumer attitudes towards mobile advertising with considerable success. This section of the questionnaire provided the data in a yes/no format. The questionnaire bore mostly bore close-ended questions in order to limit the range of variables that were collected in the analysis. A total of 42 questions were churned out of the various analogies of the operational proxies shown in figure 1.
The control variables were theoretically and empirically obtained from existing peer-reviewed literature. For instance, Magnusson et al. found that women were inclined to favour genetically modified foods than men (19). Moreover, people aged 18 to 25 were found to have more familiarity and positive attitudes towards genetically modified foods than elderly people. Wandel and Bugge provided this standard of research and concluded that young people’s nutritive choices are environmentally-conscience of their environment while the older generations are health-conscience (24). The level of education directly correlates to positive attitudes towards genetically-modified foods (Magnusson and Hursti 225). Therefore, age, gender and educational levels served as the control variables for this study.
The questionnaire was pretested to increase the comprehensiveness, accuracy and sensitivity of the data collection as recommended by Ghauri and Gronhaug. This process refines the framework of data collection. The college faculty availed their unrivalled expertise in testing the questionnaire against the developed conceptual model. 5 target respondents also filled the questionnaire to test its practicality in the field. Equivocal questions were plucked out until the questionnaire reliable and applicable.
This study surveyed a population of consumers within Hatfield, United Kingdom. A snowball and convenience sample was selected owing to the limited access and resources. A “drop-off and collect” strategy was employed to deliver questionnaires to 100 respondents’ households. These questionnaires were collected 3 days later after being filled by an adult of any age. All 100 questionnaires were retrieved and Table 1 below shows some of the demographic characteristics of the participating population. Give its randomization, it lacks stratification denying it the advantage of being representative of the Hatfield population. However, convenience sampling had the advantages of low cost and quickness.
Mathematically configured computer software is utilized to analyse the quantitative data collected (Bryman and Bell). The data was entered into SPSS software and analysed in in relation to the conceptual frameworks established for the study. Malhotra and Birks list all the analysis methods that are applied to this case including descriptive analysis, correlation analysis and regression analysis among others. Finally, the validity and reliability of the study were determined with the Pearson’s Correlation and Cronbach’s alpha.
A 42-question survey is conducted with a convenience sample of 100. The collected data was correlated to develop statistical relationships.
The data underwent frequency analysis, descriptive analysis and correlation to determine the various trends of consumer attitudes towards GM foods.
The questionnaire had 44 questions, 4 of which were of a demographic nature, 24 questions in a yes/no format and the rest with fixed but arbitrary answers that addressed the subject matter squarely. There were a total of 46000 responses, 400 of which were deemed invalid. Therefore, 45,400 results informed the analysis that followed. Gender had 3 alternatives: male, female and undisclosed. There were 6 age groups with a range of 10 years to identify with from 18-29 years to 70 and above. The participants’ marital status was either single, married, widowed, divorced, separated or non-disclosed. Academic competence was categorized into primary education, secondary education, tertiary education, Bachelor’s degree, Master’s degree or a doctorate.
From the data collected from 100 Hatfield residents that participated in this study, 42% (n=42) were female, 52% (n=52) were male while 6% of the respondents did not identify their gender. 46 of them were in the 18-29 age group, 22 in the 30-39 age group, 10 in the 50-59 age group, 5 in the 70-69 age group and, finally, 3 in the above 70 years age group. As for education levels, 6 respondents had Doctoral-level education, 30 respondents had a Master’s-level education, 43 had a Bachelor’s degree, 13 attained secondary-level education and only 4 had Primary-level education. The illustrations of these demographic characteristics are represented in Tables 1 to 4 (see appendix).
The responses to question 14, 15, 16, 25, 28 and 29 informed the construct of interest that was to empirically quantify by the results of the questionnaire. Based on the yes/no questions, this data underwent frequency analysis as shown in table 5.
Based on these responses from these questions, it was apparent that most of the study sample’s interaction with genetically modified food was by chance. Even though 71% participants had bought genetically modified foods knowingly or unknowingly, only 39% were ready to indulge in genetically modified food. 57% of the participants thought that it genetic modification of foods would influence their intent to purchase. 68 percent of the entire sample note health reasons as the main deterrent to partaking in genetically modified food. However, only 32% of the sample would go out of their way to determine whether foods are genetically modified or not in case it is not indicated on food labels and packaging.
The next determination from the questionnaire is the informativeness of the consumers that forms part of the substance of their attitude towards genetically modified foods. Questions 13, 23, 24, 26, 27, 30, 32, 34, 35 and 36 provided enough data to provide a measure of the informativeness of consumers regarding genetically modified foods. 41% of the sample admitted to knowingly consuming genetically modified foods. However, only 8% had conducted their own research into the various nuances of this kind of food. An overwhelming 56% is convinced that genetically modified foods affects the health of consumers. This figure is high despite that only 18% of the sample population believes that the available information on genetically modified food is insufficient. As such, 84% of the participants favoured the presence of information on genetic modification of food stuffs on their labelling. This information is always read by 17% of the sample population, read frequently by 42% of the population, occasionally by 39% of the population while only 2% of the population do not read their food labelling (see table 7). Only 22% have a solid stand regarding the ethical and moral perspective of corporate giants patenting and mass producing genetically modified foods. To sum up the 299 responses collected from this conceptual construct, 70% of the respondents were not aware that genetically modified foods are yet to be put into production. Table 6 in the appendix illustrates all these figures.
Question 8, “Do you have concerns about Genetically Modified Organisms?” showed that up to 60% of the population is concerned with the issue of genetically modified foods. Questions 12, 17, 18, 19, 20, 21 and 31 formed the empirical basis for the construct of credibility that surrounds genetically modified foods and the results are represented in table 8 in the appendix. As a result, 66% of the study sample term genetically modified food as unnatural. Only 18% of the population thought that such foods are safe for the environment; moreover, only 23% believe that they are more beneficial than they are risky. Even less (21%) think that genetically modified foods should be justified on environmental conservation grounds. A discouraging 60% of the sample would agree to consume genetically modified food if it was verified as helpful. Even more (66%) would buy them if they were proven to be nutritious than naturally-nurtured foods. This is so despite almost 40% of the population assuming that genetically modified food is less nutritious than non-genetically modified food (see table 9). However, if genetically modified foods could reduce the chemical pollution exerted by fertilizers, only 42% of the sample would have supported this initiative. This variable relates to the 11% of the population that thinks that food produced with pesticides is safe to eat, while 51% of the populations disagrees to this and 38% remain neutral regarding this issue (see table 10).
Table 11 represents the overall perspective of the sample population regarding the production and selling of genetically modified foods. The majority (37%) are neutral regarding this topic. However, more people disagree (29%) than agree (15%) to encourage the proliferation of genetically modified food in Hatfield.
Of the consumed genetically modified foods, meat and dairy, baby foods, fruits and vegetables and bakery products were favoured for consumption given vitamin content by 21%, 45%, 46% and 44% of the population respectively (see table 12). However, if prices were increased for genetically modified foods vis-a-vis non-genetically modified foods, meat and dairy products, baby foods, fruits and vegetables and bakery products would be consumed by 14%, 12%, 18%,and 14% of the sample population respectively (see table 13).
The demographic variables have a means ranging from 1.64 to 3.84. The combined population has a skewed age with the value at 1.101 (see table 14). Therefore, the error was kept down with the rest of the variables being within the acceptable range of skewness. Eliminating age as a probable demographic variable was the only option. The Kurtosis for the entire data is within acceptable range.
The variables for measuring interest in genetically modified foods had means ranging from 1.43 to 2.26 (see table 15). However, the skewness of question 14 (Have you purchased organically grown foods before?) and question 25 (Is the possibility of health effects as a result of Genetically Modified Foods something that worries you?) were outside the acceptable ranges (1.369 and 1.017 respectively); therefore, these questions were eliminated from the succeeding analyses. The Kurtosis of this data set was statistically viable.
The variables for measuring the construct of informativeness had means ranging from 1.51 to 2.67 (see table 16). The errors inculcated while analysing the data were significantly from the skewedness of question 23 (Have you conducted your own research into the effects of Genetically Modified Foods?) (-1.712) and question 32 (Were you aware that organic foods have not beengenetically modified/ engineered before this survey?) (1.134). These questions were removed from the measures of data utilized in estimating the informativeness of the respondents. The Kurtosis of the data set was within acceptable statistical ranges.
The means for variables assessing the credibility of genetically modified foods to consumers ranged from 1.58 to 2.29 (see table 17). The statistical error in this data was courtesy of the skewedness (1.060) of question 21 (If scientists could show that Genetically Modified Foods were more nutritious would you buy them?) that had to be removed from subsequent analysis of the empirical constructs. Moreover, the Kurtosis in this data set was within range.
The validity of the data sets was tested with between the variables under each construct that was being developed. In the variables for interest, Q15 (Does knowing the GM content of foods influence your choices?) statistically significant to Q28 (Should foods containing GMOs say so on the packaging?), p=0.000 (see table 18) and Q29 (If the packaging of a product shows it is genetically modified, would you purchase it?), p=0.019 (see table 19). The significance of Q15 and Q28 indicates a need for information by consumers; however, the need to distinguish GMO and other foods was not primary. Q16 (Would you ever be prepared to try Genetically Modified Foods) was statistically comparable to only Q28, p=0.01 (see table 21). This correlation shows a dominance of negative attitudes and lack of purchase intent.
As for informativeness, the remaining variables remained sparsely correlated. Q13 (Have you ever knowing consumed any Genetically Modified Food?) lacked significance with Q26 (Is the possibility of health effects as a result of Genetically Modified Foods something that worries you?) (p=0.315) and Q27 (Do you think the available information on Genetically Modified Foods is enough?) (p=0.621) (see table 22 and 23). This correlation shows that the sample does not worry about the health effects of GM foods, therefore, showing their moderate level of informativeness. Q24 (Have you conducted your own research into the effects of Genetically Modified Foods?) had a significant correlation to Q26, p=000 (see table 24) and non-significant one with Q27 (p=0.247). The Q2-Q6 relationship indicates a high level of informativeness with good consumer attitudes towards GM foods (confirms H2) Q30 (If products did not have to indicate their GM content, would you do your own research to find out?) had a p value of 0.147 with Q26 and 0.011 with Q27. (See tables 24 to 27).
The variables of the perceived credibility of genetically modified foods by consumers were statistically tested. Q12 (Would you consider it unnatural?) correlates with Q17 (In your opinion, are Genetically Modified Foods environmentally safe?) a significance of p=0.000. This significance confirms H1 as 41% of the sample has a bad attitude towards GM foods (Q12=YES; Q17=NO). Q21 and Q18 (Do you believe Genetically Modified Foods are more beneficial than they are risky?) have a significance of p=0.000. This confirms H3 and nullifies H2 as it affirms the sample’s perception of more harm than good from GM foods. This significance and its decriptive nature also confirm H1. Q12 and Q19 (Could the use of GM crops be justified on environmental grounds?) (p=0.018) have statistical significance too. Descriptively, it confirms H4 and nullifies H5. Q12 and Q20 (If scientists could prove that some ingredients in a Genetically Modified Crop were actually helpful, would you consume the crop or food?) lack statistical significance (p=0.279). Therefore, the relationship between consumer attitudes and health benefits of GM foods.
Q31 (Do you have a stand on the ethics and morality of big corporations patenting Genetically Modified Foods?) and Q17 have a significance of p=0.046 while Q18’s with Q30’s significance is statistical at p=0.000 shows that the population has a negative attitude towards GMO, affirming H1. Also, Q31 and Q19 (p=0.018) could be statistically compared while Q31 and Q20 have no correlation (p=0.279). Therefore, their quantitative correlation indicates that the sample lack moral standpoints regarding GM foods despite their negative attitude.
Reliability analysis was conducted and the Cronbach alpha for these data sets was 0.623.
The descriptive analysis has shown the suitability of the data for analysis. The frequency analysis has shown the major trends of consumer attitudes. The correlation analysis was crucial for identifying the statistically significant relationships.
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Table SEQ Table * ARABIC 1 Frequencies: Gender
Table SEQ Table * ARABIC 2 Frequencies: Age group
Table SEQ Table * ARABIC 3 Frequencies: Marital Status
Table SEQ Table * ARABIC 4 Frequencies: Education Level
Table SEQ Table * ARABIC 5 Frequency: Interest in genetically-modified foods
Table SEQ Table * ARABIC 6 Frequencies: Informativeness on genetically modified foods
Table SEQ Table * ARABIC 7 Frequencies: Reading food labelling (Q35)
Table SEQ Table * ARABIC 8 Frequencies: Credibility of genetically modified foods
Table SEQ Table * ARABIC 9 Frequencies: Nutritious value
Table SEQ Table * ARABIC 10 Frequencies: Safety of pesticides in food
Table SEQ Table * ARABIC 11 Frequencies: Support for the production and manufacture of genetically modified foods
Table SEQ Table * ARABIC 12 Frequencies: Product-based preference based on present vitamin content
Table SEQ Table * ARABIC 13 Frequencies: Product preferences based on price
Table SEQ Table * ARABIC 14 Descriptive statistics: Demographics
Table SEQ Table * ARABIC 15 Descriptive statistics: Interest
Table SEQ Table * ARABIC 16 Descriptive statistics: Informativeness
Table SEQ Table * ARABIC 17 Descriptive statistics: Credibility of genetically modified foods
Table SEQ Table * ARABIC 18 Chi-test
Table SEQ Table * ARABIC 19 Chi test
Table SEQ Table * ARABIC 20 Chi-test
Table SEQ Table * ARABIC 21 Chi-test
Table SEQ Table * ARABIC 22 Chi-test
Table SEQ Table * ARABIC 23 Chi-test
Table SEQ Table * ARABIC 24 Chi test
Table SEQ Table * ARABIC 25 Chi-test
Table SEQ Table * ARABIC 26 Chi-test
Table SEQ Table * ARABIC 27 Cronbach’s alpha
Table SEQ Table * ARABIC 28 Chi-test
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