genetic engineering: the public’s point of view

GENETIC ENGINEERING: THEPUBLIC’S POINT OF VIEW

Joanna Gamble, Sue Muggleston, Duncan Hedderley1,Terry Parminter2, Nicola Richardson-Harman3

February 2000

Report to Stakeholders

Joanna GambleSue MugglestonMT ALBERT RESEARCH CENTREThe Horticulture & Food Research Institute of New Zealand LtdPrivate Bag 92169AucklandTelephone: 09 815 4200Facsimile: 09 815 4201

HortResearch Client Report No. 2000/249Contract No. 4540

1Statistics Research and Consulting Centre, Massey University2AgResearch, Ruakura3Mt Albert Research Centre, The Horticulture & Food ResearchInstitute of New Zealand Ltd

This report has been prepared by The Horticulture and Food Research Institute of NewZealand Ltd (HortResearch) which has its Head Office at Batchelar Research Centre, PrivateBag 11 030, Palmerston North.

CONTENTSPage

EXECUTIVE SUMMARY ....................................................................................................1

Consumer focus groups ......................................................................................................1

Product attribute manipulation using conjoint analysis........................................................2

National Survey..................................................................................................................3

Part One – attitudes to genetic engineering in food production........................................3

Part Two – Intention to purchase or avoid: tomatoes genetically modified to reduce theneed for pesticides; or jeans using genetically modified cotton to reduce the need forartificial dyes. .................................................................................................................4

Conclusions........................................................................................................................5

Future Research..............................................................................................................6

INTRODUCTION..................................................................................................................7

STAGE ONE: CONSULTATION WITH STAKEHOLDERS................................................8

Delphi Technique ...............................................................................................................8

Methodology ......................................................................................................................8

Results................................................................................................................................9

STAGE TWO: DATA COLLECTION................................................................................. 11

STUDY 1A. FOCUS GROUPS........................................................................................... 11

Introduction...................................................................................................................... 11

Aims of the Research........................................................................................................ 11

Methodology ....................................................................................................................12

The 'Mood' of New Zealand Consumers Regarding Genetic Engineering.......................... 12

Food Safety .................................................................................................................. 12

Knowledge and Understanding ..................................................................................... 12

Perceived Risks and Benefits ........................................................................................ 13

Labelling ......................................................................................................................13

Trust............................................................................................................................. 14

Conclusions...................................................................................................................... 14

STUDY 1B. GROWER WORKSHOPS............................................................................... 16

Aims of the research......................................................................................................... 16

Focus group construction.................................................................................................. 16

Results.............................................................................................................................. 16

Factors Influencing the Use of Plant Breeding Technologies......................................... 16

GMO Decision Attributes............................................................................................. 17

Negative Attributes....................................................................................................... 18

Information Sources ..................................................................................................... 19

Conclusions...................................................................................................................... 21

Discussion of Focus Group Findings ................................................................................ 22

STUDY 2. CONJOINT ANALYSIS.................................................................................... 23

Conjoint Analysis ............................................................................................................. 23


Methodology ....................................................................................................................24

Results.............................................................................................................................. 24

Chocolate Biscuits ........................................................................................................ 25

Tomatoes...................................................................................................................... 25

Comparison of Chocolate Biscuit and Tomato Clusters................................................. 26

Discussion........................................................................................................................ 27

Conclusion ....................................................................................................................... 29

STUDY 3. NATIONAL SURVEY...................................................................................... 30


Methodology ....................................................................................................................31

Results.............................................................................................................................. 32

The Public’s Attitude to Genetic Engineering in Food Production................................. 32

Public’s attitude to tomatoes genetically modified to reduce the need for pesticides...... 34

Underlying Beliefs........................................................................................................ 37

Public’s attitude to jeans made from cotton genetically modified to reduce the need forartificial dyes. ...............................................................................................................38

Underlying Beliefs........................................................................................................ 40

Comparisons between the two products ........................................................................ 41

Discussion........................................................................................................................ 43

Criticism of Methodology............................................................................................. 44

Future Research............................................................................................................ 45

APPENDICES .....................................................................................................................46

Appendix A. Consumer Focus Groups............................................................................. 46

Appendix B. Grower Focus Groups................................................................................. 47

Appendix C. Conjoint Analysis ........................................................................................ 67

Appendix D. National Survey.......................................................................................... 70

REFERENCES .................................................................................................................... 73

Sensory & Consumer Research Team

EXECUTIVE SUMMARY

Genetic Engineering: The Public’s Point Of View

This report outlines the findings from a three year research programme, funded by theFoundation for Research, Science and Technology, investigating the New Zealand public’sperceptions of transgenic plant products. The research was carried out by HortResearch, incollaboration with AgResearch, Auckland University and Massey University.

Because the public are necessary participants in the inherently subjective socio-politicalprocess of risk assessment of a new technology, it is essential for New Zealand to put a highpriority on evaluation the public perceptions of this expanding technology. Thus the aim ofthe project was to scientifically measure and explain the perceptions that New Zealandershave about genetic engineering.

A three stage approach was taken. Focus groups provided an in-depth understanding of theissues among consumers, growers and handlers. A product attribute manipulation studyassessed the influence of genetic engineering on consumers’ purchase intention. Finally, anational survey was used to measure and explain the attitudes of a representative sample ofNew Zealanders.

Consumer focus groups

A total of 6 focus groups were held with three types of respondents: ‘general consumers’(n=15), those with affiliation to environmental (n=11) and religious (n=20) groups. However,there was subsequently found to be very little difference in issues raised between the variousgroup types.

The following are key issues identified in these discussion sessions:

• Genetic modification is strongly associated with perceived 'unsafe' treatments of foodsuch as pesticides and additives. This is of particular concern in the context of food suchas fruit and vegetables that are bought for their nutritional contribution to the diet.

• Desire for labelling depends on product category, occasion and consumer. For example,consumers purchasing a ‘healthy’ item for their family were more likely to be interested inlabels than if they were purchasing a chocolate bar as a snack for themselves.

• There are concerns about the unknown short and long-term risks on health and theenvironment.

• There is a perceived lack of choice and control over consumption of genetically modifiedfood, due to the lack of labelling regulations at the time the focus groups were conducted,resulting in the perception of being 'part of an experiment' without having given consent.

• Big businesses are perceived to have a monopoly over the distribution of information, andpolicy/regulation formation. There is a perceived lack of regulations and objectiveinformation available to the consumers.

• Awareness of the issue of genetic engineering is very high, but most people admit theyunderstand very little about it. To alleviate a sense of ‘information overload’, informationhas to be very simple and easily accessible.


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• Because consumers are reliant on particular groups (ANZFA, governmental) to providethem with the required information, a high degree of trust in those groups is required forthe information to be believed.

Focus groups are an excellent tool for exploring underlying issues involved in a poorlyunderstood concept. However, they cannot provide an indication of the prevalence of opinionamong a population, nor the strength with which it is held. Quantitative research thuscomplements this approach. The quantitative research was only conducted with consumers.

Product attribute manipulation using conjoint analysis

Conjoint analysis is a research method that systematically manipulates the attributes of aproduct to determine the relative importance of those attributes in the overall purchasedecision. It also allows for identification of various segments of consumers in the market.Three attributes (price, benefit and technology) were evaluated on two product categories(health food (tomatoes) and snack food (chocolate biscuits)) by 115 respondents in Auckland.

Although there were similarities in the patterns of behaviour and decision-making strategiesamong those presented with the tomatoes or chocolate biscuits, there were also someinteresting differences between the two.

These people fall into four clusters:

• Cluster one (7-13% of the sample, depending on the product) are very price sensitive,preferring a cheap genetically modified product over an expensive organic product. Inaddition, the members of this group tend to be relatively happy to try new products, havelower environmental concern, and are less likely to see negatives associated with geneticengineering. Few of these respondents object to, or worry about gene technology.

• The second cluster (25-40%) are also price sensitive, but not sufficiently so to compensatefor the way the product is produced. As with the above group, members of this cluster seerelatively few negatives associated with genetic engineering and are less likely to say theyworry about, or object to the technology.

• The third cluster (21-30%) is strongly anti-genetic modification, preferring organic or all-natural products. Neither price nor benefit can compensate for the production method.They are less likely to believe the technology is beneficial and many of these consumerspersonally worry about, and object to the technology.

• The fourth cluster (11-12%) is similar, but prefer specific guarantees that the product isnot genetically modified. Members of this group tend to be relatively neophobic (averseto new products or situations). This could well reflect the desire by these members forreassurance, and a willingness to pay more for this.

For some respondents however, decision-making strategy differs between the two productcategories. Interestingly, there are two groups of respondents for whom benefit makes more ofa difference to the rankings than does price, although not enough to overcome the influence oftechnology. Members of these clusters (11% and 7%) have a preference for pesticide-freeproducts. Both clusters contain members who perceive genetic engineering relativelynegatively, and are more likely to be male. In addition, some members provide relativelyhigh environmental concern scores. Not surprisingly, these clusters only appear whenpresented with tomatoes.

Benefits are not important for any of the clusters identified when presented with chocolatebiscuits. This was even the case for lower fat biscuits. However, it could be that people buybiscuits because they satisfy other needs. If this was the case, the nutritional content may beentirely irrelevant to the consumer.


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The presence of a group for whom price does play a minor role suggests that increasing theprice differential (it is comparatively small in this study) may result in a larger price-sensitivegroup, and a smaller moderately price-sensitive group.

National Survey

While product attribute manipulation can serve as a predictive tool in terms of the willingnessof consumers to accept or reject genetic modification, it makes no attempt to measure orexplain the consumer’s attitudes. A survey was developed as part of a European Unionproject to do this.

1600 surveys were sent out nationally as part of an omnibus survey distributed by CMResearch. Respondents were contacted by random digit dialling, and, to ensure a good crosssection of people were interviewed, the person who last had their birthday was recruited.Respondents were quota-sampled on the basis of age, gender and region. 908 completedsurveys were returned.

Part One – attitudes to genetic engineering in food production

A total of 64 questions were asked, and respondents were required to rate their opinion on ascale of 1 to 7.

• Over half the respondents indicate some negativity to genetic engineering in foodproduction (giving a rating of 1-3), with a quarter feeling extremely negative (giving arating of 1). Women are more likely to feel this way than men, as are people agedbetween 35-44 and over 65. In comparison, depending on the question wording, only 10-18% feel positive (gave a rating of 5-7) to any degree about the technology (men andthose aged between 18-24). A third are undecided (giving a rating of 4).

• The extent to which a respondent agrees that there are benefits is the main determinant ofwhether the respondent will accept the technology in food production. Such benefitsinclude:

• Increased product choice (13% agree, 27% disagree)

• Environmental solutions (11% agree, 32% disagree)

• Reduced price (11% agree, 32% disagree)

• Improving standard of living of self/family (9% who agree, and 36% whodisagree) and future generations (4% who agree, and 47% who disagree)

• Better quality (5% agree, 45% disagree)

• Improved healthiness (4% agree, 47% disagree)

• Typically, a far greater proportion of respondents tend to disagree that there are benefitsthan agree. This suggests that either the respondents do not believe that the technologycan offer benefits, or they are not yet aware of the benefits.

• Risks assessed include:

• Unknown long term consequences on environment and human health (63% whoagree, and 5% who disagree)

• Unnatural (52% who agree, and 10% who disagree).


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• Interference with wild species in nature (38% who agree, 11% who disagree)

• Environmental hazards (30% who agree, 14% who disagree)

• Threat to human health (29% who agree, 18% who disagree)

• Allergies (19% who agree, 17% who disagree)

• The fact that the respondent agrees that there are risks (for instance, that the technologywas a threat to human health) does not make the respondent less accepting of thetechnology. Rather, it affects the likelihood of whether they agree there are benefits of thetechnology (for instance, improving health).

• Those who think they personally know little about the technology (37%), those who thinkauthority (science, government and industry) is knowledgeable (5%), and those who scorerelatively low on the attitude to nature scale (2%) are more inclined to believe geneticengineering offers a number of benefits, and are less inclined to believe in the risks.

• Those who perceive themselves to be knowledgeable (2%), those who think authority isunknowledgeable (27%), and those who have a high degree of environmental concern(53%), are more likely to perceive risks associated with genetic engineering, and are lessinclined to believe in the benefits.

• Actual knowledge of food technology issues is reasonably high, with more than half of therespondents scoring over 75% correct (6-8 correct out of 8 questions). In comparison, 9%scored less than 50% correct (1-3 correct). Those who really are knowledgeable areslightly more likely to see benefits of the technology, but the influence is less than that ofperceived knowledge.

• Perceived and actual knowledge are relatively poorly correlated.

Part Two – Intention to purchase or avoid: tomatoes genetically modified to reduce theneed for pesticides; or jeans using genetically modified cotton to reduce the need forartificial dyes.

A further 34 questions were asked about tomatoes or jeans. Once again, respondents wereasked to rate their opinion on a scale from 1 to 7.

• Attitudes towards specific products that offered a benefit become more positive than whenasked in general terms. Depending on wording between 36-44% express some negativitytowards GM tomatoes (compared to 58% in general terms), and 27-37% to GM jeans.Similarly, between 18-25% and 16-30% express some positivity towards tomatoes andjeans respectively, compared to between 10-16% in general.

• Just under half (42-45%) of the respondents say they would probably not purchase the gmtomatoes, and around third (30-37%) say they probably wouldn’t purchase the jeans. Incomparison, depending on wording between 20-28% and 23-31% respectively say theyprobably would buy the products.

• In considering whether to purchase or avoid genetically engineered tomatoes or jeans,people are strongly influenced both by their own moral judgement of that behaviour, andby how they think society would judge their behaviour.

• The ability to identify a product as genetically modified plays an important part inpredicting attitudes towards buying tomatoes, but not towards buying jeans.


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• Rural people are more inclined than urban people to believe that they could purchase oravoid genetically modified products if they chose.

• Respondents were asked how strongly they agreed or disagreed with a number of outcomestatements. The majority of respondents feel that genetically modified tomatoes, andjeans made from genetically modified cotton would be unfamiliar (41% and 57%respectively). The issue of most concern for both products is the unknown long termconsequences for the environment and health (63% and 49% respectively). Thenaturalness of the product is also an issue, with around a third agreeing that each productinterferes with nature, is unnatural and goes against their basic principles. Never-the-less,around a third also feel that the products would offer good quality.

Before making comparisons between the responses given for tomatoes and jeans, it should benoted that there are age differences in those who responded to the two products. Significantlymore 18-24 year olds, and significantly fewer 65+ year olds said they bought jeans. This isperhaps not surprising. People 65 or older have demonstrated a greater degree of negativitytowards the technology in general than those in the 18 to 24 group, so we would expect thatoverall, there would be greater acceptance of jeans made from genetically modified cottonthan genetically modified tomatoes, and this is indeed what we have seen. We thereforeremoved the two extreme age groups, and found that the majority of significant differencesdisappeared. Remaining significant differences include:

• A marginal difference for the statement, “I am against/for buying these…’ where tomatoesare more likely to elicit a strongly negative response.

• Those responding to the jeans feel more able to decide whether to buy them

• In terms of the ability to avoid the product, those who replied to the jeans survey are morelikely to feel this would be very easy.

While jeans made from genetically modified cotton may find less resistance in the market,this is probably not due to inherent greater acceptability, but rather their appeal to a group ofpeople who have fewer concerns about the technology used to produce them.

ConclusionsConsumers in New Zealand are still cautious in their acceptance of genetic engineering infood production. The results overall suggest two processes are used in forming attitudestowards the technology. The first is a risk-benefit trade-off analysis. Consumers are currentlyunaware, or disbelieving in the existing (as opposed to potential) benefits, meaning that risksare perceived to outweigh the benefits. The balance of this trade-off may well move towardsacceptance when relevant benefits are presented to consumers. One very relevant benefit toconsumers may well be price. The forced segregation of crops resulting from the need tolabel will potentially increase prices of non-genetically modified products, making geneticallymodified alternatives more attractive.

In more specific terms, if the consumer has few personal objections to the technology,perceives society to be accepting of it, and believes they could identify a product asgenetically modified, their intentions to purchase that product would be much more likely.However, taking away the ability to identify a genetically modified product as such wouldmake them feel more negative about buying the product. This is an interesting finding, sinceit also has implications for labelling and perceptions of choice.


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Over 50% of the consumers interviewed scored above 75% correct when asked basicquestions about food technology and science, indicating people should be able to understandfactual information presented to them. However, the low correlation between perceived andactual knowledge has implications for communication strategies. If people think they are wellinformed – even if they are not – they may not pay attention to public education campaigns.The same can be cautioned about those who think no-one knows very much about GMFs,since they don’t believe the organisations who distributed the information actually know whatthey are talking about.

Taken together, it suggests that products that are identified as genetically modified, and offerrelevant benefits to consumers may well be accepted quite readily, as long as the moralobjections to the technology are addressed.

Future Research

The current study has achieved the aim of gaining a measure and explanation of NewZealanders’ perceptions of transgenic plants and plant-based products. However, aconsiderable deal more work needs to be conducted to explore these attitudes in depth.

• Why did respondents feel they would be better able to identify genetically modified jeans?Is it because they think producers are more likely to label, because the jeans themselvesmight look different, or because they are not ingesting the jeans, and are therefore morerelaxed about the information they require from the labelling?

• How do other benefits compare to price (for example, improved sensory qualities)?Further exploration is needed in terms of benefits offered, and their perceived relevance toconsumers.

• The research also highlighted a potential problem in educating people, since there waslittle relationship between perceived and actual knowledge. This has implications forcommunication strategies. What forms of education are most effective?

• The gene technology explored in this project involved moving or manipulating genes.Other gene technologies such as marker assisted selection do not necessarily involve theseprocesses. What understanding do consumers have of this technology. What associationsdo they have with words such as ‘markers’, ‘gene-splicing’, etc?

One final important note to make is that consumer attitudes are still fluid, and unformed. Theincreasing profile of the technology is sure to have an impact, making monitoring ofconsumer attitudes imperative.

For further information contact: Joanna GambleHortResearchPrivate Bag 92169, AucklandPh: (09) 815 4200Fax: (09) 815 4201


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INTRODUCTION

Because the public are necessary participants in the inherently subjective socio-politicalprocess of risk assessment of a new technology, it is essential for New Zealand to put a highpriority on evaluating the public perceptions of this expanding technology. Thus, theimportance of understanding public perceptions of gene technology and the need to use suchinformation to guide public consultation on matters of policy such as food labelling, foodsafety, ecological and ethnic issues is widely recognised.

It is equally vital for public attitudes on this technology to be a driver of future developmentof transgenic products. Indeed, it is now well accepted that unless the public feel comfortableabout purchasing and consuming genetically modified products, the use of geneticmodification in food production is unlikely to increase.

This report outlines preliminary findings from a three year research programme, funded bythe Foundation for Research, Science and Technology, investigating the New Zealandpublic’s perceptions of transgenic plant products. The research was carried out byHortResearch, in collaboration with AgResearch, Auckland University and MasseyUniversity.

Stage One of the research involved consultation with 41 different stakeholder groups toensure that the information collected would be relevant and useful for policy and planningdecisions. The Delphi Consultation process was used to pool insights and ideas.

Despite the disparity of the 41 organisations and industries interviewed, consensus was gainedvery quickly. Respondents requested information covering a wide range of issues, indicatinga need for some preliminary research prior to the initiation of any quantitative study.

A three-stage approach was agreed upon. Focus groups would provide an indepthunderstanding of the issues among consumers, and growers. A product attribute manipulationstudy would assess the influence of genetic engineering on consumers’ purchase intention.Finally, a national survey would measure and explain the attitudes of a representative sampleof New Zealanders.


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STAGE ONE: CONSULTATION WITH STAKEHOLDERS

Delphi Technique

In order to ensure that the information we collected would be relevant to New Zealand policymakers, research planners, appropriate public sector groups and industry, we used the DelphiProcess of Consultation.

The Delphi Consultation Process is a two-way feedback system that allows for opencommunication between experts. As a result, the process is a method of pooling insights andideas. Typically, the technique involves surveying experts initially using a series of open-ended questions. The results of the first round of surveying are tabulated, then sent back tothe participants for further comment, and reconsideration. In this manner, the issues at handbecome more clarified with each round of consideration. The process continues untilconsensus is made, or a clear pattern of conflict emerges.

Methodology

The first step was to identify experts willing to work with the project. These were people whowere required to make decisions for their organisation in terms of policy or regulations. Thenature of the issue indicated a need to have representatives from a broad range oforganisations and industries. Representatives from a total of 41 organisations or industrieswere recruited. These people fell into the following categories:

Industry/Organisation N=

Marketing 10

Research and Technology 19

Agriculture and Food Policy Makers 7

Retailing 2

Wholesaling 4

Exporting 12

Ethics or Consumer Rights 6

Maori Interests 4

Environmental Interests 7

Growing 9

Processing 8

Packing 3

Education 14

Medicine or Health 7

Theology 1

Other 7


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A literature review of existing studies was conducted to initially construct a draft list ofpossible issues the public might have with genetic engineering. All of the respondents werethen asked to indicate which of those issues would be of most relevance to their organisation.For instance, it was possible that environmental organisations would be most interested in thepublic’s concerns about the impact of the technology on biodiversity, or the creation of newweeds, whereas an ethics organisation might be more interested in the moral acceptability ofthe technology, or the perception that it was unnatural.

Information gained from the first round of consultation was tabulated, then sent out to therespondents for their consideration and response. Most of the following communication wasin the form of telephone calls to the researchers. Once the minor alterations to the list werecompleted, two presentations of the results were made to the respondents; one in Aucklandand one in Wellington.

We also took the opportunity while collecting responses in round one of the consultation toask some personal questions of the respondents. We asked them:

• who they thought could be trusted regarding policy making/legislation for geneticallymodified organisms,

• who they thought were the New Zealand public’s main sources of information on thetechnology,

• which form of labelling they personally felt was most appropriate, and

• how they thought genetically modified organisms might effect their industry ororganisation.

Results

Despite the disparity of the organisations and industries interviewed, consensus was gainedvery quickly (HortResearch Internal Report, 1998). Only two rounds of consultation wereneeded, and very little disagreement was apparent at the seminars. Respondents requestedinformation covering a wide range of issues, from perceived health and environmental risksand benefits, to ethical and moral concerns, to trust issues and labelling. The wide range ofissues selected indicated a need for some preliminary research, prior to the initiation of anyquantitative study. Focus groups with a wide range of consumers, growers and handlers wereidentified as a means by which an in-depth understanding of the issues could be gained.

The importance of quantitative research was also recognised and two methodologies wereagreed upon. A product attribute manipulation study using conjoint analysis would beconducted to determine the influence of genetic engineering on consumer purchase intentions,while a nation-wide survey would allow measurement and explanation of the attitudes of asample of New Zealanders.

Personal Beliefs In terms of whom the stakeholders would trust in policy and legislation formation, ethicscommittees were the most frequently selected (68% of the total). However, representatives ofthe medical or health industry also identified well-informed colleagues (71% of thoserepresentatives).


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TV documentaries and current affairs, TV news, and quality newspapers were the sources ofinformation that the stakeholders predicted would be most frequently utilised by the generalpublic (each selected by 63% of respondents).

In terms of the most appropriate labelling, there was a considerable range of preference, evenwithin organisation or industry type. Overall, the opinion was that labelling was unnecessaryif the product no longer contained DNA. This was even the case for environmentalists, andrespondents representing ethics and consumer rights. However, respondents used their optionof making more than one selection, reflecting their belief that different applications requireddifferent forms of labelling.

Presentations in Auckland and Wellington The results of consultation rounds 1 and 2 were presented in Auckland and Wellington. Allstakeholders were invited to attend.

Attendees had the chance to meet with the researchers, and discuss the results. In addition,agreement was achieved as to the overall aims of the project. These were:

Consumers:

• How do consumers feel about genetically modified organisms, and what factorsinfluence their attitudes and perceptions?

• Does the fact that a product contains GMOs affect their purchase decision?

Growers:

• What influences whether a grower chooses to grow a GM product?

• Is it based on consumer, process or production considerations?

Handlers:

• how do handlers feel about working with genetically modified organisms, and whatfactors influence their attitudes and perceptions?

• Would it effect what company they worked for, or the work conditions they demand,etc?


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STAGE TWO: DATA COLLECTION

STUDY 1A. FOCUS GROUPS

Introduction

Although a base of knowledge has already been built in other countries throughout the worldregarding public perceptions of transgenic products, understanding of the New Zealand publicis relatively sparse. Because of this lack of depth in understanding, the aim of this primarystage of the research was to gain an understanding of the overall 'mood' of the New Zealandpublic concerning this technology. Since the following stages of research would build on theinformation uncovered, it was important that assumptions were not made about the issues ofconcern in New Zealand, simply based on information gathered elsewhere.

The focus groups were not designed to indicate the prevalence of the particular perceptionsand attitudes among the general population, but rather to explore the issues in some depth. Itis an excellent technique for building an understanding of the underlying emotive drivers thatinfluence consumers. A wide range of opinions offers an opportunity to discuss conflictingattitudes, and hence draw out the deeper issues. As such, it was important to inviteparticipants who would be willing and able to discuss issues that arose as a result of thediscussion.

We felt that given previous research, there was the possibility that issues may differdepending on cultural and religious affiliation, and on ‘environmental’ activity. We thereforeheld discussion with three types of respondents: Buddhists, the environmentally active, andthe ‘general’ consumer. Buddhists were chosen for several reasons. They are non-Christian(several members of the ‘general’ group were Christian), one of the fastest growing groups inNew Zealand, and have restrictions placed on their diet due to religious beliefs (New ZealandOfficial Yearbook, 1998).

It was desirable to conduct discussion groups with members representing Maoridom.However, despite repeated efforts, these groups did not eventuate. A new attempt will bemade early in 2000.

Aims of the Research

The aims of the focus groups were to explore a number of issues in depth:

• Where might genetic engineering sit among other factors such as price, taste ingredientcontent, quality, nutrition, and brand familiarity when deciding which food to purchase?

• Do people really look at labels, and if so, what information do they look for?

• What is the level of awareness and understanding of gene technology among New Zealandconsumers?

• What are the main risks consumers associate with this technology? What are the mainbenefits? Do they feel the risks outweigh the benefits, or vice versa?

• Who are exposed to the risks, and who gains from the benefits?

• Are some applications more acceptable than others, and why?


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• Is there enough information about genetic engineering available to the general consumer?What forms should this information take?

• Who would consumers trust to provide information about genetic engineering?

• Is there anyone whom consumers trust to 'look after' their best interests (i.e. developpolicy and regulations)?

• Does religious affiliation or involvement in environmental groups change awareness,knowledge or acceptability of genetic engineering?

Methodology

A total of 46 people were interviewed, falling into three categories. Demographic data areavailable in Appendix A.

- 15 general consumers (recruited from HortResearch's database),

- 11 environment group members (Greenpeace and Royal Forest and Bird) and

- 20 Buddhists (recruited from the Auckland Buddhist Centre)

Two focus groups were conducted for each category. Respondents were paid forparticipating.

In order to ensure respondents did not attend the sessions with any prior agenda, they wererecruited on the basis that they would be attending focus groups to explore issues that wereimportant to them when buying food. The subject of genetic engineering was only introducedsome way into the discussions (although for several groups, this topic was mentionedspontaneously, fairly early on).

The 'Mood' of New Zealand Consumers Regarding Genetic Engineering

Food Safety

An increasing emphasis is being placed on food safety. The respondents report usinglabelling to avoid certain ingredients in food such as additives, and artificial flavourings, andcomplain about the high use of pesticides. In addition, they feel that food is now so over-processed or artificially produced that they have lost their flavour and nutrients. This isparticularly important to them when purchasing ‘healthy’ foods such as fruit and vegetables,which are bought for their nutritional contribution to the diet.

Knowledge and Understanding

When questioned as to their response to a can of tomatoes that says ‘genetically modified’,New Zealand consumers’ responses are typically negative. A number of the focus groupparticipants associated the term ‘genetically modified’ with DDT, Zenical, Thalidomide, CJD,irradiation, animal organ transplants, computers, or food additives, most of which have fairlynegative connotations. However, few of the consumers can actually describe in any detailwhat genetic modification might be.


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Perceived Risks and Benefits

BenefitsRespondents are aware that there are some possible benefits to genetic engineering, (forinstance through medical applications, increased crop yield, or in terms of choice). For themost part however, it is the manufacturer who is seen to benefit most, rather than theconsumer. Altruistic changes such as improved vitamin content may be received much morepositively.

ConcernsConcerns with genetic modification appear to take several directions. At the deepest level arethe moral objections people placed on the technology. If the technology produces somethingthat would never form naturally (such as plants with animal genes, or animal to animaltransplants), then the end-product also isn’t natural, and is therefore not acceptable. Thosewith moral objections feel we are ‘playing God’, or ‘tampering with nature’.

There is also a fear that genetically modified foods might be harmful to their health, either inthe short or long term, or harmful to the environment. They feel that the research has beenmoving so quickly that science doesn’t yet know enough to allow the products to be growncommercially or sold on the shelves. This perceived lack of authoritative knowledge isproduced by conflicting stories in newspapers and TV, where one study says a product is safe,and another says it isn’t. Respondents also comment on the alarmist behaviour of activistgroups.

Consumers believe that they should be able to identify foods that contain genetically modifiedmaterial, so as to allow the them to take responsibility for their own moral and physicalwellbeing.

Finally, there is the belief that big business are preventing this from happening, because theyknow that if they have to identify their food as genetically modified, then consumers won’tbuy their products. Thus big businesses are preventing the consumer from making a choicevia pressure (financial or other) on government and scientific institutions. There is therefore alot of anger directed towards big business because they are perceived to be preventingconsumers from making choices. Consumers therefore feel they are being forced to be‘human guinea pigs’ without giving permission.

Labelling

Although labelling is not always utilised by consumers, it is a very important issue toconsumers since it gives them the perceived ability to control what they, and those they carefor, consume. The admission that the panellists in this study did not always use labelinformation is consistent with the findings of ANZFA in 1996 (Yann, Campbell, Hoare,Wheeler, 1996). That study indicated that people were less inclined to use label information iftheir purchase was habitual. Label information was more frequently consulted on the firstpurchase occasion of a new product, where the consumer sought information that wouldminimise the risk associated with trial of a new product.

The consumers in the present study admit they are less vigilant with labelling on certainproducts such as snack foods. This finding is also consistent with ANZFA’s, which found thatfood category played a role in the frequency with which a consumer consulted the label. Thelabelling on products for infants, perishables, or products with specific issues of concern weremore commonly read than staple foods such as rice and treats such as snacks.

A qualitative survey conducted in Canada (National Institute of Nutrition, 1999) explored theissue of voluntary labelling. Consumers wanted labelling that was simple, linked to nature,provided a benefit to the consumer, and was linked to government regulatory approval.


14

Consumers tended to respond negatively when unknown scientific terminology was used.Consumers did not think products should be labelled as ‘do not contain…’ as this wasperceived as putting down competitors. While the Canadian consumers saw labelling as veryimportant, they did not see it as a ‘panacea’ solution, suggesting that information be madeavailable in other ways such as through leaflets, or television.

Trust

Trust is a broad issue covering the sources of information people use to learn about thetechnology, the scientific organisations that produce that information and the regulatorybodies that are formed to ensure the technology is controlled. The consumers interviewed inthis study typically express a fair level of cynicism in all these areas. While they admit tounderstanding very little about the technology, they want to learn more about it. However,they also readily admit that there is too much information available, but just don’t have thetime or inclination to go through it all. Instead, they want independent and trustworthyadvisory groups who can filter and disseminate information in an understandable way.Government and industry are equally distrusted, while consumer organisations are mosttrusted. Science and research organisations are moderately trusted, but there is the perceptionthat due to the lack of funding by government, and the selling of state-owned enterprises,these organisations now rely on commercial funding. As a result, these organisations wereseen to be answerable to their funders, rather than the public.

Previous research conducted by Frewer et al (1996) demonstrated that trust is made up of anumber of factors. Trust appears to be linked with perceptions of accuracy, knowledge andconcern with public welfare. One factor is linked with ‘knowledge bias’ and is associatedwith other characteristics such as truthfulness, trustworthiness, having a good track record,responsibility, accuracy and factualness. Another factor is linked with accountability, wheresources with moderate amounts of accountability are seen to be more trustworthy than thosewith either very low or high amounts of accountability.

Using this model as a basis for interpretation of our findings, industry and government couldbe seen as too ‘accountable’, therefore having vested interests in the information theydisseminate. In contrast, consumer organisations would be seen to score moderately onaccountability, and high on truthfulness, accuracy, and knowledgeability, making them verytrustworthy. Scientists would have different positions, depending on who they are seen towork for.

Conclusions

1. Fruit and vegetables are generally bought for their nutritional contribution to the diet. Assuch, the healthiness and safety of this food is of particular importance.

2. Pesticides and irradiation are perceived to be unhealthy/unsafe treatments on products thatare supposed to be healthy. Genetic modification is strongly associated with these other'unsafe' technologies in the minds of some consumers.

3. Labelling usage depends on product category, occasion and consumer.

4. There are three broad categories that concerns about genetic engineering fall into:

• Unknown short and long term risks on health and the environment


15

• Lack of choice and control over consumption of genetically modified food, due to thelack of labelling regulations, and the resulting perception of being 'part of anexperiment' without having given consent.

• The perceived monopoly big businesses have over the distribution of information, andpolicy/regulation formation, and hence the perceived lack of regulations and objectiveinformation available to the consumers. This adds to consumers' beliefs that they haveno control over what they purchase and consume.

5. While awareness of the issue of genetic engineering is very high, most people admit theyunderstand very little about it. They would like more information to be made available,but it has to be very simple and easily accessible, due to increasing ‘informationoverload’. Leaflets could be successful, if distributed an organisation (such as ANZFA)that people recognise as a 'watchdog' group, especially if accompanied by an 0800number.

6. Because consumers are reliant on particular groups to provide them with the requiredinformation, a high degree of trust in those groups is required for the information to bebelieved.

7. Few differences were apparent between group type - that is, religion or affiliation with anenvironmental group did not appear to influence level of knowledge, or acceptability ofthe technology.

Although the attitudes of consumers were the main focus of the research, other groups ofpeople also have contact with genetically modified organisms. These include the growers andhandlers in horticulture, agriculture and forestry. The attitudes of these people are importantto measure, since it is they who choose to plant or work with genetically modified organisms.The next two sections detail the results of focus groups with growers and handler in thehorticultural, agricultural and forestry sectors.


16

STUDY 1B. GROWER WORKSHOPS

Aims of the research

As identified in the stakeholder workshops, the main overall objectives of this research were:

• What influences whether a grower chooses to purchase a GM product?

• Is it based on consumer, process or production considerations?

More specifically, the research asked:

• How aware are growers of the various technologies used in plant breeding?

• Where do growers place these technologies on a continuum of low to highintervention?

• At what stage on the continuum do they no longer feel comfortable using thetechnology?

• What are the reasons growers perceive some technologies to be acceptable, and othersunacceptable (at a personal, business, and industry level)?

• Where do growers go to get information about genetic modification, and whichsources are most trusted?

Focus group construction

A total of seven focus groups were held with 60 growers from a range of horticultural andarable industries including kiwifruit (24), pip and stone fruit (21), berry fruit (7) and grain (6).Most of the participants were men between 40 and 60 years of age who owned and operatedtheir own properties. A quarter of them had tertiary qualifications. Almost half of theparticipants considered that genetic improvement was not very important to their enterprise atthe moment, and most of the rest thought it was highly important. A quarter of theparticipants thought that genetic improvement would be a lot more important to theirenterprise in the future than it is at the moment. Appendix B details the demographic make-up of the groups.

Results

Factors Influencing the Use of Plant Breeding Technologies

Growers identify a number of technologies that they associate with plant breeding. Thecategories of technologies are shown in Figure 1. Most of these technologies are common toall groups. Using these technology labels, growers in each workshop constructed a scale ofhigh to low levels of human intervention. In Figure 1 the technologies are shown in blocks.The blocks represent the lowest to highest quartiles of where each technology was placedalong the scale. The vertical line in each box represents the median position. The number oftimes each technology category was identified by individual growers is also shown.

Growers tend to think of plant breeding technologies in three groups:

• Low intervention: natural selection, grafting, cross breeding, and artificialpollination,


17

• Moderate intervention: trait selection and hybridisation, and tissue culture

• High intervention: irradiation, cloning, and GMOs

The growers then used their synthesised scale to indicate which technologies they were“comfortable” in using. Just over half of the growers in the study are not “comfortable” withhigh intervention technologies, and about a quarter of the growers are also not comfortablewith moderate intervention technologies. The remainder (just under half) are alreadycomfortable with using plant material from biotechnologies like GMOs on their properties(although only 32% specifically supported GMOs).

Figure 1. Plant Breeding Technologies and the Proportion (%) of Growers “Comfortable” inUsing Them (from left to right 100%,98,98,95,91,88,77,63,43,32%)

GMO Decision Attributes

In the study participants were asked to supply both the positive and negative attributes oftechnologies acceptable to them. They were also asked to supply both the positive andnegative attributes of technologies that were not acceptable to them. Table 1 shows the typesof attributes used by participants to make these decisions. Also in the table are the proportionof text units (i.e. the contributions from each person) categorised by the researchers. A largerproportion of text units indicates that a greater proportion of respondents selected thatattribute. A more detailed list of comments is available in Appendix B.

0

10

20

30

40

50

60

70

80

90100

Frequency

Natural se lection

Cross breeding and artificial pollination

Grafting

Trait selection & hybridisation

Tissue culture

Irradiation

Cloning

GMO's

n=32

n=34

n=48

n=30

n=11

n=11

n=6

n=42

Low Intervention High Intervention


18

The most commonly identified benefit from plant breeding technologies is increasedefficiency of plant breeding thus saving breeders’ time. The next most frequent attributes arethat they should assist growers to increase the productivity and profitability of their crop, andmake the management of their enterprise units easier.

Table 1. Attributes of Plant Breeding Processes Used by Growers to Determine Acceptability

Positive Attributes Proportion of Text Units (%)

215 total text units

more efficient plant breeding 18

greater enterprise productivity and profit 16

easier enterprise management 13

improved market access 13

greater consumer demand 11

copies natural plant breeding processes 10

proven and reliable results 8

less chemicals and better for the environment 7

lower production costs 5

feeds a hungry world 1

Negative Attributes

207 total text units

reduced consumer demand 20

the risk of the unknown and untested 19

more difficult market access 16

less efficient plant breeding 14

more difficult enterprise management 10

unnatural plant breeding processes 9

higher production costs 5

more chemical use and greater environmental threat 4

less control over plant breeding 2

The most common cause of negative grower attitudes towards plant breeding technologies isanything likely to cause consumers to purchase less of their product. There are also issuesregarding the risk of the unknown and difficult market access. The next most commonlyreported negative attributes are that they might reduce the efficiencies of plant breeding, andcreate greater trading difficulties.

Most of the groups have similar lists of attributes. However kiwifruit growers place a greateremphasis than other groups upon “market access” and “consumer demand”. One kiwifruitgroup and one pipfruit group have more emphasis upon “natural breeding processes”, and lessupon achieving “greater orchard productivity”.

Previous research at AgResearch has shown that different criteria are often used by decision-makers to decide to use a technology, from the criteria they use to reject a technology. InFigure 2 are the most common criteria (from the same data as Table 1) used by growers fordeciding upon acceptable and unacceptable plant breeding technologies.


19

Acceptable plant breeding technologies are those that have advantages for growers, in thatthey will increase production and profitability and also provide plants that are easier toestablish, will remain healthy and vigorous, and be easier to harvest. Growers also wanttechnologies that are perceived to be more suited to consumers needs.

Figure 2. Criteria Used for Acceptance and Rejection Decisions

Positives Negatives

Acceptance • increased production andprofitability

• easier enterprise management

• greater consumer demand

• copies natural processes

• inefficient plant breeding

• difficult management

Rejection • more efficient plant breeding

• improved market access

• requires less chemicals

• reduces costs of production

• increases consumer resistance

• risks from being unknown andunproven

• unnatural processes

Technologies are more acceptable if they “copy” natural breeding processes. These plant-breeding technologies are still acceptable even if the breeding process itself is slow andinefficient, or the plants produced make enterprise management more difficult by increasingthe variability of production.

Unacceptable plant breeding technologies are those with perceived increased risks from beingunknown and untested. They are also associated with increased consumer resistance andunnatural breeding processes. These technologies are still unacceptable even though theymight make plant breeding quicker and more efficient, and improve market access. Theycould also be still unacceptable even if they reduced the need for pesticides and reduced costsof production.

Growers were asked about whether they associated each of the attributes with their ownpersonal preferences or with benefits to their business or their industry. In most cases theirbusiness decisions are determined by their own preferences. The attribute of “naturalbreeding processes” is one of those associated by growers with their own preferences withoutdirect benefit to their business or their industry. However “improving breeding efficiency” isseen to have mainly industry benefit with little advantage for individual growers. Theattributes “reducing chemicals”, “improving market access”, and “reducing costs” areconsidered to be mainly of benefit to their businesses and are less associated with personalpreferences or industry benefit. The attributes “inefficient plant breeding” and “difficultmanagement” are associated with their industries and businesses respectively. When theseresults are applied to Figure 1 it would appear that the main drivers for growers deciding uponthe acceptability of plant material is their own personal preferences even at some cost to theirbusiness or their industry.

Information Sources

Growers were asked to identify the information sources they would use to find out GMOinformation (Table 2). Previous work in AgResearch has already indicated that informationsources are varied with the topic being considered. The growers then worked in groups to


20

build diagrams representing the degree of trust and frequency of use of these sources(summarised in Figure 3). The most frequently used information sources are the Foundationof Arable Research, media personalities, and the more general media. However, these sourcesare not necessarily the most trusted. Trust is greatest for the Foundation of Arable Research,Soil and Health Association, international research institutes, and the New Zealand Ministryof Health. Least trusted sources are media personalities, other growers, Greenpeace, andcommercial owners of plant material. Appendix B provides more detail.

Table 2. Information Sources About GMOs

Information Sources (from the most to leasttrusted)

Identifier Used in Figure 3

Foundation of Arable Research FAR

Soil & Health Association S&H

International research institutes Ires

Ministry of Health HD

HORT Research HortR

USDA, USFDA USD

Technology Transfer Agents TT

Ministry of Agriculture and Forestry MAF

Crown Research Institutes CRIs

ENZA ENZ

National growers associations GroN

ERMA ERM

Scientists working privately Psci

International growers associations GroI

ANZFA ANZFA

Consumer Institute CI

Plant Breeders Brdrs

Industry leaders Ind

Grower publications Gpub

Government departments Gov

News Media Nme

Technical Publications Tpub

Other growers Gwrs

Commercial Owners of plant material CO

Greenpeace GP

Media personalities MPers


21

Low

High Low

Figure 3. Trust and Frequency of Use of Information Sources

Conclusions

• Growers are not resistant to the potential benefits of GMOs, but do have some concernsthat limit their willingness to use them at this stage, particularly the response ofconsumers to the technology. A third of growers are already willing to apply GMOtechnologies on their own properties, and a relatively small shift in attitudes would lead toa higher proportion willing to use the technology.

• Growers are likely to be unresponsive if GMO material provides benefits to the industryrather than to themselves. This is particularly the case if other sectors of industry will bethe major beneficiaries e.g. plant breeders.

• The most popular benefits the technology could provide to growers would be those thatsubstantiate the financial benefits to growers, and link these through to both the results ofsystems experimentation and assessments of consumer demand. It would also describeclearly the technical processes involved so that growers can gain confidence in thebreeding process and how the material being produced is tested.

• Information that is trusted and accessible to growers comes from people and organisationswith experience in GMOs, who have shown that they are committed to their industry byworking with growers on an ongoing basis.

De gre e of Trust (high - low )

Fre

qu

en

cy

of

Us

e (

hig

h -

lo

w)

HD

IRes

S& H

FAR

HortR

US D

TT

MAFGroI

PS ci

ERM GroN

ENZ

CRIs

ANZF

CI

BrdrsGov

GPub

Ind

TPub

CO

GP

Gwrs

MPerNMed


22

Discussion of Focus Group Findings

Organisations such as the Foundation of Arable Research are highly trusted among growers,while consumer organisations and Greenpeace are far less trusted. In direct contrast, suchconsumer-oriented organisations are highly trusted among consumers, while supporters ofindustry are subject to much suspicion.

Among the growers, the attitudes of consumers towards the technology are a key concern.Analysis of the consumer focus groups indicates this is certainly valid, especially sinceconsumers currently feel it is the growers and manufacturers that benefit from the technology,rather than the consumers themselves. The data suggest that consumers will be moreaccepting of the technology with the introduction of second generation products that directlybenefit the consumer. Producing crops that benefit the consumer may therefore eliminate oneof the key concerns growers have in dealing with transgenics.

It is likely that growers would have lower acceptance of crops for whom other sectors ofindustry will be the major beneficiaries. Similarly, consumers are reluctant to purchase foodthat benefits only the producer or grower. Both consumers and growers expect that if they areto be any risks associated with genetically modified crops or products, they must also be theones to receive the benefits.


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STUDY 2. CONJOINT ANALYSIS

Conjoint Analysis

The members of the focus groups perceived that although they could identify many risksassociated with genetic engineering (i.e. their perceptions of risk, rather than the assessmentsof the risks by experts), few could identify any immediate benefits to themselves. Rather, itwas the producer, manufacturer, or farmer who would benefit. Therefore, the participants ofthe groups felt that there was no reason to expose themselves (or others) to the risks whenthey would not gain any benefits. However, second generation products offer direct benefitsto the consumer (such as nutritional benefits, or improved flavour), and people may wellrespond quite differently to these products.

The participants of the focus groups made it clear that labelling was a very important meansof gaining information about the way that a product was produced. Labelling enabled theconsumers to make a choice to avoid or purchase that product. Indeed, to a certain extent,this need has been recognised (NZ Herald, 5/8/99), with new regulations that dictate that allfoods containing genetically modified material (over a certain threshold) needs to be labelled.

Given that the focus groups revealed a reluctance to purchase any product produced usinggenetic modification, how will the labelling of a product as genetically modified interact withother attributes of that product (such as benefits to the environment, or the consumer), toinfluence the purchase decision?

Conjoint analysis allows for the fact that when a consumer makes a decision to purchase oneproduct or brand over another, they are influenced by a number of factors of the product. Inaddition, it acknowledges that the consumer may find it difficult to explicitly state how theymight decide between different benefits and costs. It therefore attempts to deduce the relativevalues (or ‘part-worths’) of those factors to the overall purchase decision by systematicallymanipulating selected factors. All the consumer is asked to do is state their overall opinion ofeach of the alternatives (Green & Srinivasan, 1978). Conjoint analysis typically aims toprovide predictive validity.

Consumers differ in terms of their preferences, and these can be explicitly accounted for byanalysis at an individual level. By asking the respondents to describe themselves using avariety of other personality and attitude questions, the researcher can build a profile of variousmarket segments.


With the recent decision by the New Zealand Government for mandatory labelling, a numberof questions are raised. We sought to answer some of these in the next part of the project.That is, how will the labelling of a product as genetically modified interact with otherattributes of that product to influence the purchase decision?

• How much influence does price have?

• Will preference change depending on the benefit the product offers? Which is moreimportant, benefits to the consumer, or to the environment?


24

• Will there be certain groups of consumers for whom one factor is more important than forother groups? If so, how large are these groups, and how can they be described? Forinstance, are there differences in concern with the environment, or level of neophobia(willingness to try new foods (Pliner and Hobden, 1992))?

• Will this differ depending on the product category (health or junk food)?

Methodology

Three factors were chosen for consideration: price, benefit and technology used to producethe product. Had all possible interactions been allowed for, 27 different combinations wouldhave had to be presented to each consumer for each product category. Instead, only atechnology-price interaction and a technology-benefit interaction were allowed for, meaningthat a matrix of only 18 combinations needed to be used (see Appendix C.).

115 consumers were recruited through HortResearch’s consumer database. Respondents wereaged between 18-60, and two-thirds were female (reflecting the predominance of women asthe household shopper). Consumers conducted their assessment of the products in isolatedsensory testing booths with daylight corrected lighting.

In order to ensure the consumers understood the task, each group was first briefed together,using ten cards with different fruit written on them. Each consumer then sorted the fruitfollowing the instructions that they would be given during the actual experiment. Once allconsumers understood the task, they were taken to the testing booths.

Once in their testing booths, consumers were presented either with a tomato, or a plate ofchocolate-chip biscuits together with a bag containing written descriptions of the 18 differentcombinations of product attributes (see Appendix C), and a half-page explanation of what‘genetically modified’ meant. Half the sample received the tomatoes first, and the other halfreceived the biscuits first.

The consumer was asked to first place the 18 combinations into five piles: ‘definitely wouldbuy it’, ‘probably would buy it’, not sure if I would buy it or not’, ‘probably wouldn’t buy it’,and ‘definitely wouldn’t buy it’. Consumers were told that they could have some groups thatwere empty, and could even place all 18 descriptions in one pile if they felt it to beappropriate. Once they were happy with their piles, they were instructed to rank thedescriptions in each pile, from most preferred to least preferred, then to write the codes of thedescriptions in the table provided.

Once this was completed, consumers were given several attitudinal questionnaires to fill out.The consumers then received the second product category, and repeated the ranking task.Finally, the consumers received a demographic survey.

Results

The SAS procedure PROC TRANSREG (SAS, 1993) was used to perform the conjointanalysis. The rankings allowed the researchers to determine the relative importance of price,benefit and technology for each respondent, and then group the respondents into clustersdepending on their decision-making strategy. Decision-making strategies were then


25

compared between the two product categories. SAS PROC CLUSTER was used to performheirarchical cluster analysis.

Chocolate Biscuits

Four clusters emerged. 12 people could not be clustered.

One small group (Cluster 1, n=8, 7%) is strongly influenced by price (70% of the variation),although within a price range, natural products are preferred to guaranteed non-geneticallymodified products. GM biscuits are least preferred (technology accounted for 12% of thevariation). Benefit also plays a role (18% of the variation), with less fat being preferred overno artificial flavouring. However, a product with reduced fat is not sufficient to overcome thefact that it is produced using genetic modification. Members of this group score lowest on theneophobia scale, indicating a relative willingness to try new foods. They also see fewernegatives of genetic engineering (although this does not mean they see more positives, forwhich there is no significant difference from the other clusters).

The remainder of the consumers are mainly influenced by technology, with geneticallymodified products always being least preferred. However, price and benefits play differentroles for consumers in this larger group.

The second group (Cluster 2b, n=46, 40%) are largely concerned about technology (69% ofthe variation), but are also sensitive to price (22% of the variation). However, although pricelevels have a considerable effect on ranking, a GM product even with the most favourableprice and best benefits will be ranked slightly lower than a non-genetically modified product.All-natural products are preferred over guaranteed genetically modified free. Members of thisgroup see relatively few negatives of genetic engineering, and relatively more positives. It ispossible that a larger price differential will compensate for the technology used.

The third group (Cluster 2a, n=34, 30%) are basically concerned about technology (97% ofthe variation), preferring all natural products to guaranteed non-genetically modified, and bothto genetically modified products, regardless of benefit or price. These consumers giverelatively higher neophobia scores, indicating greater reticence to try novel foods. They alsosee more negatives of genetic engineering, and fewer positives than do Cluster 2b members.

Unlike the other groups, the final group (Cluster 3, n=14, 12%), prefer products that areguaranteed to be genetically modified-free (technology accounts for 95% of the variation inranking) rather than all natural. Once again, genetically modified biscuits are least preferred.Neither price nor benefit can compensate for technology. Cluster 3 members give the highestneophobia scores, and see the most negatives of genetic engineering.

No significant differences are observed in terms of being a household shopper, frequency ofpurchasing chocolate biscuits, environmental concern, gender, age, income, religion orethnicity.

Tomatoes

Consumers behave in a slightly more complex manner when presented with tomatoes,resulting in 7 clusters. 13 people do not fit any cluster.

As with the chocolate biscuits, a small group (Cluster 2, n=15, 13%) of price consciousconsumers exist, where price makes up 66% of the variation, and technology, 21%. So,within a price category, organic produce is preferred, followed by guaranteed geneticallymodified free, with genetically modified last. Thus, a genetically modified product ispreferred over an organic tomato if the price drops by one category. These respondents give


26

the lowest neophobia and environmental concern scores, and see fewest negative aspects ofgenetic engineering. There are also a greater number of males in this group than are expectedby chance.

Price also plays a role in the second group (Cluster 1, n=29, 25%) accounting for 19% of thevariation in ranking, but is insufficient to counter the effect of technology (accounting for73% of the variation). This is the case even if the best benefit is also included. Geneticallymodified products are ranked lowest, with organic and guaranteed-genetically modified freeproducts ranked similarly. Like cluster 2, these consumers rate their environmental concernrelatively low, and perceive few negatives of genetic engineering.

The third cluster (Cluster 3, n=24, 21%) are almost totally driven by technology (96% of thevariation in ranking), with organic products rated most highly, and genetically modifiedproducts lowest. Price and benefit do not have any significant influence. Members of thiscluster give moderate scores for all the attitudinal tests.

The next cluster (Cluster 6, n=8, 7%) are also strongly affected by technology (95% ofvariation), but unlike the previous group, they prefer their tomatoes to have a guarantee ofbeing genetically modified-free, rather than being organic. Attitudinally, the members of thiscluster are very similar to cluster 3, providing moderate scores on all attitudinal tests.

A very small cluster (Cluster 8, n=4, 4%) are mainly influenced by technology (93% of thevariation), with organic products preferred over genetically modified products. However, asignificant technology*price interaction is observed (4% variation), whereby they prefer themost expensive guaranteed non-genetically modified products to cheaper examples. Theseconsumers give the highest neophobia and environmental concern scores, and see relativelyfew negatives associated with genetic engineering.

Two final clusters are identified (Cluster 4, n=13, 11% and Cluster 5, n=8, 7%). Like theother groups, technology plays a large role (80% and 87% respectively). Both clusters preferorganic produce to genetically modified, with guaranteed genetically modified-free productsrated closely to organic. Benefit also plays a role for both groups (11% and 5% respectively).Pesticide-free products are most preferred by both clusters, but cluster 5 prefers products thatprovide extra vitamin C to no benefit at all. In contrast, cluster 4 appears suspicious ofvitamin C, and prefers products with no benefit. Both clusters contain members who perceivegenetic engineering relatively negatively, and are more likely to be male. In addition, cluster5 members provide relatively high environmental concern scores.

No significant differences are observed in terms of being a household shopper, frequency ofpurchasing tomatoes, age, income, religion or ethnicity.

Comparison of Chocolate Biscuit and Tomato Clusters

Although the same respondents assessed both the biscuits and the tomatoes, they may not usethe same strategies for both. Analysis showed that while there were some people who werevery consistent, there were others who changed their strategies depending on the product.Appendix C details these findings.

Biscuit cluster 1 has far more members of Tomato cluster 2 than we would expect just bychance. This is reasonable, given the fact that both groups are particularly price sensitive. Inaddition, the members of these groups tend to have lower neophobia scores, lowerenvironmental concern, and are less likely to see negatives associated with geneticengineering. Particularly, these respondents don’t believe that genetic engineering isunethical, harmful, risky, unnatural, will have long term effects, or will have negative effectson welfare. They are also more likely to perceive the technology as necessary and beneficial


27

than the average respondent. In addition, few of these respondents personally object to, orworry about the technology.

Biscuit cluster 2b has more members of Tomato cluster 1 than chance would predict. Forthese consumers, price plays a secondary, but still considerable, role to technology in theirdecision making. However, the price differential is insufficient to compensate for a productbeing genetically modified. As with the above group, members of this group see relativelyfew negatives associated with genetic engineering and are less likely to say they worry orobject to the technology. They also have a low level of environmental concern. Increasingthe price differential may well lead to a change in the balance of the risk-benefit trade-off,whereby a cheaper product may compensate for the way in which the product is produced.

Biscuit cluster 2a has more members of Tomato cluster 3 than would be expected by chance.These consumers focus almost completely on technology, and neither price nor benefit makemuch of an influence on their purchase decision. They are less likely to believe thetechnology is beneficial and many of these consumers personally worry about, and object tothe technology.

Biscuit cluster 3 has more members of Tomato clusters 6 and 8 than we would expect bychance. While this is understandable given the preference of Biscuit cluster 3 and Tomatocluster 6 for specific guarantees of being non-genetically modified, the presence of asignificantly larger than expected number of Tomato cluster 8 members is more difficult toexplain. This could well reflect the desire by those members for reassurance, and awillingness to pay more for this. Indeed, members of all three clusters typically give highneophobia scores, and see more negatives associated with genetic engineering (particularlybiscuit cluster 3 and tomato cluster 8). In addition, they are more likely to disagree that thetechnology is beneficial.

For some respondents however, decision-making strategy differed between the two productcategories. Interestingly, there were two groups of respondents for whom benefit made moreof a difference to the rankings than did price, although not enough to overcome the influenceof technology. Members of these clusters had a preference for pesticide-free products. Bothclusters contained members who perceived genetic engineering relatively negatively, andwere more likely to be male. In addition, some members provided relatively highenvironmental concern scores. Not surprisingly, these clusters only appeared when presentedwith tomatoes.

Benefits were not important for any of the clusters identified when presented with chocolatebiscuits. This is perhaps not surprising, since the benefits offered by the biscuits were relatedto health – something that is not such an issue with snack foods.

Discussion

Price appeared to be a universal influence, and it is likely that price will be one of the mainattributes that differentiates genetically modified food from non-genetically modified food inthe future. Mandatory labelling requires manufacturers who wish to exclude geneticallymodified ingredients from their products to prove their claim. This means that they need to bewilling to conduct tests on their products, and source ingredients that are guaranteed to begenetically modified free. However, their sources (generally the farmers) must also prove thattheir produce is not genetically modified, requiring segregation of crops, and testing of theproduce they wish to sell. Generally, farmers have embraced genetically modified crops


28

because of the savings they make in production (e.g. fewer herbicides/pesticides, etc).Growing non-genetically modified crops therefore also increases these expenses. It isexpected that many of these costs will ultimately be passed on to the consumer, meaning thatfood guaranteed to be genetically modified-free may be more expensive to the consumer.

The issue of price ties in closely with the issue of labelling. People want labelling because itwill provide them with the information to make a choice. However, providing the proof thatthe product does not contain genetically modified material will simply serve to increase theprice of that product. To remove the cost of making such claims, manufacturers may simplysettle for a label that says the product may contain genetically modified material, resulting inthe removal of that choice.

Thus the issue of price elasticity is becoming increasingly pertinent. Namely, are consumersprepared to pay more for food that has not been tampered with at the genetic level? Ourresults show that only a small decrease in price (7-10%) can increase willingness to purchasegenetically engineered food (that is, they are not willing to pay more for non-geneticallymodified food). That would suggest that decreasing the price even more is likely to furtherincrease the proportion of consumers who are willing to put their concerns aside and purchasefood produced by this technology. Never-the-less, there will be a proportion of consumers forwhom price is a relatively unimportant issue. For these people, price cannot compensate fortheir concerns over the technology. For instance, organics are reported to be one of the fastestgrowing agricultural sectors in the UK, with demand increasing for organic produce andlivestock by as much as 40% in one year (CNN, 1999).

Indeed, the Organic Products Exporter Group in New Zealand believes that while in NewZealand the industry is growing by 20%, it’s ‘small-fry’ compared to the demand in placessuch as the UK, where the industry is expected to be worth $1600 million in 2000. The USorganic market is forecast to be worth some $90 billion dollars by 2006 (NZ Herald, 2000)

(http://www.nzherald.co.nz/storydisplay.cfm?storyID=15250).

Although some of our consumers exhibited a similar pattern of decision-making whenpresented with tomatoes or chocolate biscuits, others used different strategies for the twoproducts. One interesting example is that although none of the benefits presented forchocolate biscuits had a significant influence on any of the clusters, two groups ofrespondents rated benefit higher than price (though not as influential as technology) for thetomatoes. Members of these clusters (11% and 7%) had a preference for pesticide-freeproducts. They perceived genetic engineering relatively negatively, had relatively highenvironmental concern scores and were more likely to be male.

Health or environmental benefits are not currently sufficiently effective to compensate fortechnology. Corney et al (1996) examined consumers’ perceptions of food package labels,where health and nutrition claims were present or removed. Their results indicated thathealth and nutrition claims may not necessarily have a large impact on consumer buyingpatterns, with sensory attributes being given higher weightings by their respondents. Theauthors suggested instead that marketers should lead with a taste claim along with secondarypositive claims such as ‘low in fat’. If this is the case, we may find that claims of ‘extra sweettomatoes’ might prove more influential than claims of increased vitamin C.

A certain percentage of the respondents could be classified as neophobic, and price andbenefit offered by the product have no influence. Food neophobes view new food technologyas experimental, artificial and risky (Lee, 1989). Slovic (1987) found that the newness of riskplays a role in determining public fear of a technology. Taken together, this implies that asthe technology and the resulting products become more familiar, the neophobe’s fear of theproduct declines. In risk-benefit trade-off terms, the neophobe believes the risks associated

http://www.nzherald.co.nz/storydisplay.cfm?storyID=15250)


29

with the technology outweigh any benefits they might be offered, and therefore wish to avoidthe product. In contrast, the more adventurous consumer may believe that reduced price (forinstance) compensates for the risks, and is therefore willing to purchase the product. Overtime, if perceived risks do not eventuate, the neophobe may readjust their assessment of therisks, and tip the risk-benefit trade-off towards purchase.

Finally, our study revealed a significant proportion of respondents for whom neither price norbenefit had an effect because they had moral concerns about the technology. Such moralconcerns can be particularly influential, as illustrated in the 1996 Eurobarometer (ConcertedAction of the European Commission, 1997). Here they suggested that initiatives designed toalleviate concerns about risks would prove less successful than those designed toaccommodate moral concerns about the technology.

It must be remembered that the technique can only draw conclusions about the relativeimportance of the factors (price, technology and benefit) studied. Many other factors could betaken into considerations (eg brand, packaging, flavour, etc); however, the more factors whichare added to the study, the more product descriptions a respondent must assess. With just 3factors, each with 3 ‘levels’ (values, types of benefit, technologies) our respondents wouldhave had to assess 27 (3 x 3 x 3) descriptions. Adding another factor to the mix would at leastdouble this figure. The number can be reduced slightly, at the cost of some information (forinstance, here the number was reduced from 27 to 18) at the cost of not being able to saywhether the effect of price depended on the benefit offered). However, 20-30 descriptions areprobably the maximum that one person can rate at one go and still give sensible, reliableanswers.

Conclusion

Our results indicate that many people will accept the technology if the price is right. Inaddition, price currently plays a greater role than health or environmental benefit associatedwith the product. However, the study was limited to two types of benefit. Further explorationshould occur using a range of benefits to the consumer including sensory qualities.

A proportion of the population are neophobic, a trait that in this study correlates with lowacceptance of biotechnology. It is likely that acceptance of the technology among thesepeople will slowly increase, as has been the case with other fast moving technologies such ascomputers and the internet. However, acceptance among people with moral or ethicalconcerns may well continue to be low.


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STUDY 3. NATIONAL SURVEY

The focus groups conducted earlier in 1999 revealed some of the underlying issues peoplehave with genetic modification. However, the focus groups could not give any indication ofhow prevalent those beliefs are among New Zealanders. Nor could the groups provide aquantitative indication of the strength of those beliefs.

While the conjoint analysis study allowed us to identify different market segments, it did notgo far in exploring the beliefs and attitudes consumers hold toward the genetic engineering.The current national survey attempts to measure and explain the attitudes of a representativesample of New Zealand towards genetic modification in food production.

The national survey was designed by members of the EU project (Bredahl, 1999) called CAD-GENETECH, led by MAPP (Centre for Market Surveillance and Research based inDenmark), and was built on consumer behaviour theory, and existing and comparableresearch in the field. Piloting and adjustment of the survey was carried out by Joanna Gamblein both the UK and New Zealand.

Part one of the survey attempts to explain consumer’s attitudes towards genetic engineering infood production. Fishbein’s Multiattribute Attitude model (Fishbein, 1963) dictates thatgeneral beliefs (and the strength of those) influence perceptions of benefits and risksassociated with genetic engineering. Such general beliefs include beliefs held about theenvironment, technology, science, food, and their own and others’ knowledge of thetechnology. In turn, perceptions of risks and benefits of genetic engineering influence theoverall attitude to genetic engineering in food production.

Part two of the survey aims to explain consumer’s buying behaviour using a departure fromAzjen’s Theory of Planned Behaviour (Azjen, 1988). Behavioural intention (to avoid orpurchase a genetically modified product) is predicted by the attitude the person holds towardsperforming that behaviour. This attitude is in turn influenced by perceptions of moralobligation to perform that behaviour, their perceptions of societal norms, and by theirperceptions of the control they have over performing that behaviour (both external, such asthe ability to identify something as genetically modified, and internal, such as the ability topay for a more expensive product). An additional factor is the general opinion the consumerhas about genetic engineering in food production.


The current national survey attempts to measure and explain the attitudes of a representativesample of New Zealand towards genetic modification in food production. The survey thusattempts to measure:

• General attitudes including food neophobia, attitude to technology, attitude to nature,perceived knowledge, and alienation from the marketplace,

• personal control over the technology,

• actual knowledge,

• perceptions of process and product related risks and benefits for self/family, futuregenerations, and the environment, and strength of those beliefs,


31

• general perceptions of risks and benefits associated with the technology, and strength ofthose beliefs,

• overall attitude to genetic engineering in food production, and strength of those beliefs,

• perceptions of moral obligation, subjective norms, perceived control and perceiveddifficulty, and the strength of which they hold those perceptions,

• attitude towards purchasing or avoiding genetically modified tomatoes or jeans,

• intention to purchase or avoid genetically modified tomatoes or jeans.

Methodology

The survey uses Fishbein’s multiattribute attitude model, and Azjen’s theory of plannedbehaviour as points of departure, and is made up of two parts. The first part assessedconsumers’ attitudes to genetic engineering in food production, and related this to othergeneral attitudes the consumer held (such as attitude towards the environment, or novel foods,etc.). The second part assessed attitudes towards genetic engineering of a specific product.Two products were used as examples; a genetically-modified tomato, and jeans made fromgenetically-modified cotton. The products were chosen so that although both products wereplant or plant-based, one was ingested while the other was not.

The respondents were given the same paragraph-long definition of genetic modification as theconjoint study. In the second part of the survey, the respondent was presented either with:

• a black and white image of a tomato described as “genetically modified to resist insectsand other pests without needing to be sprayed with pesticides. This means that fewerpesticides need to be sprayed into the environment”

• a black and white image of a pair of jeans described as “produced using blue geneticallymodified cotton. Because the cotton is naturally blue, we don’t have to use artificial dyesand bleaches to colour it, making the product less harmful to the environment”

The survey was included as part of an omnibus survey (called S4), sent out by the contractedmarket research company (CM Research) over September and October 1999. Becauserespondents were asked to fill in the omnibus survey over a period of a week, it was hopedthat the inclusion of our questionnaire in such a lengthy survey would not be undulyinfluenced by respondent fatigue. In addition, respondents were asked to complete the tomatoversion of the questionnaire if their questionnaire number was odd, and the jeans version ofthe questionnaire if their questionnaire number was even.

8000 calls were made to recruit 1600 participants, resulting in a 12% response rate - a figurethat is slightly lower than average for market research. However, given the size of theomnibus survey this is not surprising. Respondents were quota sampled based on age, gender,and region. See Appendix D for demographic details.

A total of 908 completed, usable surveys were returned, resulting in a completion rate of 57%.448 people answered the tomatoes section, while 461 answered the jeans section.


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Results

All respondents answered the questions in part one of the survey.

The Public’s Attitude to Genetic Engineering in Food Production

Three questions assessed the public’s overall attitude to genetic engineering in foodproduction:

• Applying gene technology in food production is…extremely bad-extremely good (AB1)

• Applying gene technology in food production is…extremely foolish-extremely wise(AB2)

• I am strongly against-I am strongly for…applying gene technology in food production(AB3)

Table 3. Proportion of respondents who rated themselves positively or negatively for thethree questions assessing public attitude to genetic engineering in food production.

(1)

(negative)

(7)

(positive)

(1-3)

(negative)

(5-7)

(positive)

Don’t

know (4)

N= % % % % %

AB1 839 26 2 58 11 31

AB2 850 30 2 58 14 28

AB3 828 31 2 57 15 28

Depending on the wording, 57-58% of respondents in general felt negatively towards the useof gene technology in food production, of which a quarter felt extremely negatively. Incomparison, only 10-15% felt positively. About a third of respondents were undecided.

More women than men said Extremely Bad (131 out of 426 women; 88 out of 413 men).There were significant differences between age groups in terms of the proportion saying'Extremely Bad', with the 35-44s and 65+s most likely to, and the 18-24s least likely to. Urbanand Rural dwellers did not differ significantly in the proportion supporting either extreme.

More women than men said Extremely Foolish (147 out of 426, as opposed to 104 out of 424men). There was a marginal difference between age groups (p=0.061) where the 35-44s and65+s were most likely to say 'Extremely Foolish' and the 18-24s least likely to. There wasalso a marginal Urban/Rural difference (p=0.063), whereby rural people were more likely tosay 'Extremely Foolish' than Urban people (102 out of 295 Rural people, as opposed to 149out of 555 Urban).

Women were also significantly more likely than men to say 'Strongly Against' (147 out of413 women; 111 out of 415 men). Age had no significant effect. There was a marginal(p=0.067) difference between support in Urban and Rural areas whereby 9 out of 289 Ruralrespondents said 'Strongly For', while only 9 out of 539 Urban respondents were strongly for.

Our study also shows some clear differences in perceptions of risks and benefits.


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Risks and Benefits

Table 4. Proportion of respondents who gave a rating of 1 or 2, or 6 or 7 to the overall risk(R) and overall benefit (B) measures, and specific risks (CR-process-related, PR-product-related) and benefit (CB-process-related and PB-product-related) measures.

Total

n=

1 or 2(disagree)

%

6 or 7 (agree)

%

Differencebetween %1/2

and %6/7

Overall Benefits

B1-beneficial 847 41.1 5.9 35.2

B2-great benefits 838 43.8 5.1 38.7

B3-advantageous 833 38.1 7.6 30.5

Overall Risks

R1-considerable risk 850 19.6 34.0 -14.4

R2-harmful 838 16.7 34.5 -17.8

R3-disadvantageous 833 12.8 35.5 -22.7

Product Related Risks

PR1-allergy 834 18.0 19.2 -1.2

PR2-threat to health 838 18.4 29.8 -11.5

Process Related Risks

CR1-environmental hazards 835 13.8 30.4 -16.6

CR2-interfere with wild species 834 10.6 37.5 -27.0

CR4-unknown long term consequences forhealth and the environment

837 5.3 63.1 -57.8

CR5-unnatural 835 10.4 51.7 -41.3

Product Related Benefits

PB1-improve standard of living of futuregenerations

848 36.4 9.2 27.2

PB2-increase own/family’s standard of living 842 47.1 3.7 43.5

PB3-healthier 837 46.8 3.7 43.1

PB4-better quality 836 45.3 4.5 40.8

Process Related Benefits

CB1-increased choice 833 26.9 13.4 13.4

CB2-solve environmental problems 830 31.8 11.1 20.7

CB3-reduce price 825 32.0 10.9 21.1

CB4-necessary 834 44.5 8.5 36.0

CB5-benefits producers. 834 14.0 38.4 -24.3


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Perceptions about the benefits of the technology followed similar patterns to the generalattitude measures. In terms of specific benefits, nearly half the respondents disagreed thatgenetic engineering was necessary, could improve quality or healthiness of food, or lead to anincrease the standard of life for themselves and their families.

The risks total was significantly affected by age, and marginally by gender (p=0.115),ethnicity (p=0.095), and household structure (p=0.054). Assessment of risk tended to risewith age, although the 35-44 age group was highest, followed by the 55-64 age group.Women tended to rate risks higher than men. Europeans rated risks highest, significantlyhigher than those in the ‘other’ ethnic group, with Maori placed in the middle. The types ofhousehold giving the highest risk ratings were single young people, young couples with nochildren, and families with school-aged children. The lowest ratings were from peopleflatting and from older couples with no children at home.

Responses to expected risks tended to be less extreme than those for benefits. Twoexceptions existed: just under two-thirds of respondents strongly agreed there were unknownlong term consequences to the environment and human health, and just over half agreedstrongly that the technology was unnatural.

Our respondents were fairly knowledgeable of the science underlying the use of genetechnology in food production. Over half (59%) correctly answered at least 6 of the 8knowledge questions correctly (75% correct or greater). Only 14% correctly answered 3 orless (less than 50% correct). Appendix D lists the questions asked.

Table 5. Distribution of correct responses to questions about basic food science. Number of Respondents % % Expected if Guessing

0 questions correct 61 6.7 0.4%









Total 908 100

Public’s attitude to tomatoes genetically modified to reduce the need for pesticides

Respondents who had a questionnaire with an odd number on the front of it were instructed tocomplete the section on genetically modified tomatoes.

Once again, three questions assessed the public’s overall attitude to genetic engineering oftomatoes:

• Buying these tomatoes would be…extremely bad-extremely good (AB1)

• Buying these tomatoes would be…extremely foolish-extremely wise (AB2)

• I am against-I am for…buying these tomatoes (AB3)


35

Table 6. Proportion of respondents who rated themselves as positive or negative abouttomatoes genetically modified to reduce the need for pesticides.

tomatoes (buy at least

once amonth)

(1)(negative)

(7)(positive)

(1-3)(negative)

(5-7)(positive)

Don’tknow (4)

N= % % % % %

AB1 268 17 4 36 25 39

AB2 266 18 2 36 18 45

AB3 263 26 3 44 18 38

Responses were more positive when presented with a genetically modified product thatoffered a benefit than when asked about Genetic Modification in general. With the specificproduct, between 36-44% were negative compared to 58% when asked about the technologyin general, and between 18-25% were positive about the tomatoes compared to 10-15% aboutthe technology in general.

Analysis of variance on total Attitude to Buying the Tomatoes (AB1+AB2+AB3) revealedthat men had more positive attitudes, on average, than women. There were no significantdifferences on the other demographic factors checked (age, ethnicity, urban/rural, householdstructure).

Three questions measured respondents’ desire to avoid or purchase tomatoes geneticallymodified to reduce the need for pesticides:

• If these tomatoes were available in the shops, I would intend to…definitely avoid them-definitely buy them (BI1)

• If these tomatoes were available in the shops, I expect I would…definitely avoid them –definitely buy them. (BI2)

• If these tomatoes were available in the shops, it is highly likely I would…definitely avoidthem – definitely buy them. (BI3)

Table 7. Proportion of respondents who thought they would buy or avoid tomatoesgenetically modified to reduce the need for pesticides.

tomatoes (at least oncea month)

Definitelyavoid (1)

Definitelybuy (7)

Probablyavoid (1-3)

Probablybuy (5-7)

Don’tknow (4)

N= % % % % %

BI1 269 23 6 44 28 29

BI2 266 25 4 42 24 34

BI3 265 25 2 45 20 36

Just under half of the respondents stated they intended to avoid purchasing the tomatoes, ofwhich a quarter would definitely avoid it. A third of the respondents were not sure what theywould do, and between 20-25% of respondents were, to some extent, willing to purchasethem.


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Again, simple exploratory analysis of the constructs mostly revealed how variable people'sattitudes were within demographic groupings. Unfortunately, for the tomato section of thesurvey, only 7 Maori responded and 17 other non-Europeans.

If These Tomatoes Were Available in the Shops I Would Intend To Definitely Avoid/ DefinitelyBuy Them. 91 of our 392 respondents (23.1%) said 'Definitely Avoid'; 23 (5.9%) said'Definitely Buy'. This did not differ significantly between men and women, between agegroups, or between types of household. There was a significant (p=0.047) difference betweenUrban and Rural responses: 52 of the 258 (20.2%) of Urban respondents said 'DefinitelyAvoid', compared to 39 of 134 (29.1%) of Rural respondents.

If These Tomatoes Were Available in the Shops, I Expect I Would Definitely Avoid/ DefinitelyBuy Them. 95 of our 385 respondents (24.7%) said 'Definitely Avoid'; 17 (4.4%) said'Definitely Buy'. This did not differ significantly between men and women, between agegroups, or between types of household. There was a significant (p=0.036) difference betweenUrban and Rural responses: 54 of the 253 (21.3%) of Urban respondents said 'DefinitelyAvoid', compared to 41 of 132 (31.1%) of Rural respondents.

If These Tomatoes Were Available in the Shops, It Is Highly Likely I Would DefinitelyAvoid/Definitely Buy Them. 96 of our 384 respondents (25.0%) said 'Definitely Avoid'; 9(2.3%) said Definitely Buy'. Women were more likely to say 'Definitely Avoid' than men(p=0.034): 37 out of 184 men (20.1%) and 59 out of 200 (29.5%) of women answered'Definitely Avoid'. There was no significant difference between age groups, nor betweendifferent household structures. There were significant differences between Urban and Ruralresponses (p=0.006 for 'Avoid', p=0.039 for 'Buy'): rural people had more extreme opinionsthan urban dwellers. 52 out of 252 (20.6%) urbanites replied 'Definitely Avoid', while 44 outof 132 (33.3%) rural people did; but at the other extreme, only 3 urbanites (1.2%) replied'Definitely Buy', while 6 (4.5%) rural people did.

Total Behavioural Intention (BI1+BI2+BI3) shows marginal differences based on Ethnicity(p=0.069) and Household Structure (p=0.061). Europeans were marginally less inclined topurchase the tomatoes than Maori or other non-European groups. Intentions were lowest forYoung Single People; next lowest were Families with Pre-School Children; the highestintentions were among Flatters, Young Couples with No Children, and Older Couples withNo Children At Home.


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Underlying Beliefs

Table 8. Proportion who agree (gave a rating of 6 or 7) or disagree (gave a rating of 1 or 2) foreach of the belief measures (tomatoes).

Total (buytomatoes monthly

or more)

1 or 2(disagree)

6 or 7(agree)

Differencebetween % 1/2

and % 6/7

N= % %

Outcome Beliefs

B1-unnatural 269 11.9 37.5 -25.7

B2-wholesome 268 25.0 19.0 6.0

B3-unfamiliar 264 7.6 40.5 -33.0

B4-no confidence 263 19.0 31.6 -12.5

B5-unknown long termconsequences

266 4.9 62.8 -57.9

B6-good quality and taste 260 11.2 35.0 -23.8

B7-benefits nature 264 36.0 9.1 26.9

B8-nice texture 264 9.5 28.8 -19.3

B9-easy to handle/use 261 8.4 31.4 -23.0

Control Beliefs

C1-too expensive 269 12.6 20.8 -8.2

C2-never available 261 34.1 12.6 21.5

Difficulty Beliefs

D1-easily distinguishable 266 47.7 5.3 42.5

D2-would notice if gm 264 31.4 15.5 15.9

Moral Obligation Beliefs

M1-morally wrong 265 15.5 29.4 -14.0

M2-against my basicprinciples

264 15.9 34.8 -18.9

M3-interferes with nature 264 11.0 38.3 -27.3

Subjective Norm Beliefs

N1-my family thinks Ishould avoid/buy

264 29.2 5.7 23.5


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Europeans had significantly higher moral obligation scores than Maori ((p=0.087) althoughthis is said with caution given the small Maori sample). There was also a significant ethnicdifference in terms of Subjective Norms where 'other non-European' group had higher Socialnorm values than the Europeans. In addition, a marginal Urban/Rural difference (p=0.067)and a marginal Gender*Urban/Rural difference (p=0.094) were apparent. Urban dwellers hadhigher Social norm values than Rural people; this difference was more marked among menthan women.

Rural people were more inclined to believe they would be able to avoid or purchase thetomatoes than urban people. They were also more likely to believe they would notice if theproduct was genetically modified.

As with genetic engineering in general, nearly two-thirds of the respondents strongly believedthere were unknown long-term consequences for the environment and health. 40 percent ofthe respondents felt that genetically modified tomatoes were unfamiliar. At least a third ofrespondents believed that while the tomatoes would probably be good quality and taste, theyalso had concerns that the technology interfered with nature, was unnatural, and went againsttheir basic principles.

Public’s attitude to jeans made from cotton genetically modified to reduce the need forartificial dyes.

Respondents who had an even number on the front of their questionnaire completed the jeanssection of the survey.

The same attitudinal questions were asked of genetically modified jeans.

• Buying these jeans would be…extremely bad-extremely good (AB1)

• Buying these jeans would be…extremely foolish-extremely wise (AB2)

• I am against-I am for…buying these jeans (AB3)

Table 9. Proportion of respondents who rated themselves as positive or negative about buyingjeans made from genetically modified cotton to reduce the need for artificial dyes.

jeans N=(purchase)

(1)

(negative)

(7)

(positive)

(1-3)

(negative)

(5-7)

(positive)

Don’t

know (4)

N= % % % % %

AB1 344 13 8 27 30 42

AB2 341 14 1 30 16 54

AB3 341 18 4 37 21 43

In contrast to the people who responded to the tomatoes, those who responded to the jeanswere less consistent in their responses, depending on the wording. Once again, responsesbecame more positive when presented with a specific product offering a benefit. Between 27-


39

37% were negative compared with 58% in general, while between 16-30% were positive,compared to 10-15% in general.

A marginally significant age effect was apparent for the construct measuring the attitudetowards buying the jeans. 18-24 year olds gave significantly higher scores than 35-44 yearolds (p=0.073). No other demographic differences were seen.

Three questions measured respondents’ desire to avoid or purchase jeans made fromgenetically modified cotton to reduce the need for artificial dyes:

• If these jeans were available in the shops, I would intend to…definitely avoid them-definitely buy them (BI1)

• If these jeans were available in the shops, I expect I would…definitely avoid them –definitely buy them. (BI2)

• If these jeans were available in the shops, it is highly likely I would…definitely avoidthem – definitely buy them. (BI3)

Table 10. Proportion of respondents who would buy or avoid jeans made from geneticallymodified cotton to reduce the need for artificial dyes.

Jeans N=

(purchase)

Definitely

avoid (1)

Definitely

buy (7)

Probably

avoid (1-3)

Probably

buy (5-7)

Don’t

know (4)

N= % % % % %

BI1 344 17 5 30 31 38

BI2 341 18 4 35 23 42

BI3 342 18 3 37 23 40

Only a third stated they intended to avoid purchasing the jeans (17-18% would definitelyavoid them), while between 23-31% said they would probably buy the jeans. Around 40%said they were unsure.

If These Jeans Were Available in the Shops I Would Intend To Definitely Avoid/ DefinitelyBuy Them. In terms of household structure, ‘older’ respondents were slightly more likely tobuy these jeans (11% compared to 5%). No other demographics had an influence.

If These Jeans Were Available in the Shops, I Expect I Would Definitely Avoid/ Definitely BuyThem. No significant differences were apparent among demographics.

If These Jeans Were Available in the Shops, It Is Highly Likely I Would DefinitelyAvoid/Definitely Buy Them. Age had a significant influence on ratings, with those agedbetween 18 and 24 less likely to say they would definitely avoid the jeans (3% compared to18%), and those aged between 35-44 (26%) and over 65+ (35%) more likely to say theywould avoid them.

Age was the only demographic factor that revealed significant differences in the BehaviouralIntention construct. Respondents aged between 18-24 gave significantly higher scores thandid those aged between 35-44 (p=0.053).


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Underlying Beliefs

Table 11. Proportion who agree (gave a rating of 6 or 7) or disagree (gave a rating of 1 or 2)for each of the belief measures (Jeans)

total 1 or 2(disagree)

6 or 7(agree)

Differencebetween % 1/2

and % 6/7

N= % %

Outcome Beliefs

B1 - unnatural 344 11.6 37.8 -26.2

B2 - unfamiliar 342 7.6 56.7 -49.1

B3 - no confidence 341 15.5 19.4 -3.8

B4 - unknown long termconsequences

341 9.7 49.3 -39.6

B5 - good quality 341 9.1 32.8 -23.8

B6 - benefits nature 332 33.1 16.9 16.3

B7 - good value for money 334 16.5 12.0 4.5

B8 - suitable to wear socially 335 13.4 21.5 -8.1

B9 - only benefits producer 336 10.7 30.4 -19.6

Control Beliefs

C1 - expensive 343 12.8 30.6 -17.8

C2 - never available 332 23.8 9.6 14.2

Difficulty Beliefs

D1 - easily distinguishable 339 38.1 8.3 29.8

D2 - would notice if gm 334 30.5 11.4 19.2

Moral Obligation Beliefs

M1 - morally wrong 343 16.0 28.9 -12.8

M2 - against basic principles 336 16.7 34.2 -17.6

M3 - interferes with nature 332 8.4 40.1 -31.6

Subjective Norms

N1 - friends would think Ishould avoid/buy

339 23.3 8.3 15.0

Differences between moral obligation scores were apparent for gender and age. Women hadmarginally higher moral obligation scores than men (p=0.069), while respondents in the 18-24age group gave significantly lower scores than those in the 35-44 age group (p=0.004) andmarginally lower scores than those in the 55-64 age group (p=0.082). Age also had an effecton social norm scores, with those in the 18-24 age group providing significantly higher socialnorm scores than the 35-44 age group (p=0.040).

While no significant differences were revealed regarding perceptions of control, ruralrespondents gave higher difficulty scores than urban respondents (p=0.020), meaning ruralrespondents felt more able to avoid the jeans if they wanted to.


41

Over half of respondents felt that jeans made from genetically modified cotton were anunfamiliar product, and consistent with the responses to tomatoes, the issue that mostconcerned respondents was the unknown long-term consequences for the environment andhealth. 40 percent of respondents believed the product interfered with nature, and a thirdbelieved the product went against their basic principles and was unnatural. However, similarto tomatoes, a third also felt the product would be good quality.

Comparisons between the two products

Were there any difference in the attitudes towards buying genetically modified food and non-food?

Unfortunately, our results are confounded by the influence of age, since those who said theybought tomatoes at least monthly tended to be older than those who said they bought jeans.That is, there was a greater proportion of 65+ respondents in the tomato group, and a greaterproportion of 18-24’s in the jeans group (see Appendix D). This is perhaps not surprising,since jeans tend to be bought by a younger generation. People 65 or older have demonstrateda greater degree of negativity towards the technology in general than those in the 18 to 24group, so we would expect that overall, there would be greater acceptance of jeans made fromgenetically modified cotton than genetically modified tomatoes, and this is indeed what wehave seen.

These two extreme age groups were removed from the jeans data and reanalysed.

As expected, the majority of differences disappeared, particularly in terms of attitude topurchasing genetically modified jeans and tomatoes, and in terms of behavioural intention.Nor were there any significant differences in terms of moral obligations, and perceived socialnorms. However, a few significant differences remained:

• A marginal difference was observed for the statement, “I am against/for buying these…’where tomatoes were more likely to illicit a ‘1’ (26%, ‘I am against’ compared to 19% forjeans) (p=0.093).

• Those responding to the jeans felt more able to decide whether to buy them (PC1,p=0.071, 56% compared to 48%; PC3, p=0.002, 43% compared to 29%)

• In terms of the ability to avoid the product, those who replied to the jeans survey weremore likely to feel this would be very easy (PD2, p=0.018, 32% compared to 22%; PD3,p=0.003, 26% compared to 15%).

These results provide a measurement of the attitudes of our respondents. However, someexplanation of how they relate to each other is needed. To accomplish this, structuredequation modelling was conducted. The Structural Equations Modelling Package, AMOS(SPSS), was used to validate the underlying theory. Detailed results will be provided in asupplementary report.

Model One – Attitudes to Genetic Engineering in Food Production All respondents answered the questions in part one of the survey. Respondents were asked torate how knowledgeable they perceived themselves to be about genetic engineering in foodproduction. They were also asked to answer a number of questions that pertained to basicfood science. Analysis revealed a relatively low correlation between the two (-0.086).Perceived self-knowledge and perceptions about the knowledgeability of authority (science,industry, and the government) were positively correlated (0.454).


42

Attitude to nature had the strongest influence on both perceived risks and perceived benefits,where those who rated themselves highly on this scale were less likely to see benefits, andmore likely to see risks. Neither neophobia nor marketplace alienation had any effect onperceived risks, but played a weak role in determining benefits.

Those who felt alienated from the marketplace were also more likely to rate highly on theattitude to nature scale (correlation=0.527), more likely to believe that authority didn’t knowmuch about the technology (-0.277), and be more neophobic (0.348). The strong correlationbetween the marketplace alienation scale and the attitude to nature scale initially suggestedthat the two were co-linear (measuring the same factor). However, when the attitude to naturescale was removed from the model, the fit of the model was worse. This suggests therealthough was some element of environmental concern which overlapped slightly with themore political aspects of Alienation, the attitude to nature scale was the best predictor ofoverall opinions of risks and benefits.

The overall risk measure correlated reasonably strongly with the overall benefit measure (-0.591), so that high risk scores correlated with low benefit scores. The overall benefitquestions produced a risk-benefit analysis, which was the best predictor of the overall attitudeto genetic engineering measure. That is, those who gave a high risk score and low benefitscore rated themselves negatively towards genetic engineering in food production.Conversely, those who gave a high benefit score and a low risk score rated themselvespositively towards genetic engineering in food production.

Model Two – Behavioural Intention to Purchase or Avoid a Genetically Modified Product Some similarities in structure were apparent for the two products. For both products,perceived moral obligation and social norm measures were very strongly correlated (-0.656for tomatoes, -0.729 for jeans), suggesting a single factor. These measures were the mainpredictors of the attitude to behaviour measure for both products. The perceived control and difficulty measures were also strongly correlated for both productsonce again indicating little independence of the measures (0.938 for tomatoes, 0.916 forjeans).

Because the perceived control and difficulty (of avoiding the product) measures were sostrongly correlated, it was difficult to determine the individual influence on behaviouralintention. A model was therefore run for tomatoes that excluded either the perceiveddifficulty or perceived control measure. Excluding the control measure led to a model inwhich difficulty did not have a significant effect on intention. Excluding the difficultymeasure produced a model where control only had a marginal effect on intention. In otherwords, perceptions of the ability to control purchase, or avoid the product had little directinfluence on behavioural intentions.

Experimentation with the models for tomatoes and jeans revealed two patterns. For tomatoes,perceived difficulty (of avoiding the product), attitude to genetic engineering in foodproduction, subjective norms and perceived moral obligations all served to predict theconsumer’s attitude towards buying the tomatoes, and hence indirectly, their behaviouralintentions.

The pattern was slightly different with the jeans. In this case, only the perceived moralobligation and subjective norms were significant predictors of attitude towards buying thejeans. The issue of perceived difficulty in avoiding the jeans did not play a role. Attitudetowards genetic engineering in food production played very little role, although it would notbe true to say that it was completely unrelated to the attitude towards buying jeans.


43

Discussion

Genetic Engineering in Food Production

In comparison to international findings (Bredahl, 1999), risks and benefits are not particularlywell explained by the general attitude measures. This suggests that there is some uniquefactor(s) that influence New Zealand consumers’ attitudes that has not yet been revealed.Certainly, our indigenous culture provides a unique perspective in terms of its world-view.As a fairly isolated country, we also have conflicting issues pertaining to both a desire to beon par with the rest of the world technologically, and yet retain our unique flora and fauna andclean-green image. Further research is required to identify possible determinants of NewZealander’s perceptions of risks and benefits of genetic engineering in food production.Further exploration may improve our ability to predict New Zealanders’ formation ofperceptions of risks and benefits.

Our results suggest that New Zealanders are currently cautious about use of the technology infood production, since over half the respondents stated at least some degree of negativity. Ofparticular note is the relatively high degree of disagreement that genetic engineering can offerspecific benefits. Such a finding suggests that either respondents don’t believe assertions thatthe technology can provide benefits, or they are currently unaware of the benefits.Interestingly, when gene technology is presented in the form of an actual product thatprovides a tangible benefit (the reduced use of pesticides or artificial dyes), negativity dropsslightly, with around a third of respondents indicating a willingness to purchase the product.This supports the hypothesis that introduction of second generation products with clearbenefits to the consumer will be better accepted than those currently on offer.

Previous studies in New Zealand have found little in the way of demographic differences inattitudes (Richardson-Harman, 1998). In contrast, the current study identified severaldemographic factors. Age was a significant factor, where younger respondents (18-24) weremore accepting of the technology in general, and perceived more benefits and fewer risks thanolder respondents (65+) and those aged between 35-44. Women consistently found thetechnology less acceptable than men, identified more risks, and fewer benefits, and were moreinclined to have moral concerns. Interestingly, a rural/urban difference was also observed,where rural respondents thought it would be easier to avoid or purchase genetically modifiedproducts if they wanted.

Both the neophobia and alienation to the marketplace measures were expected to play a role,since previous work has shown this to be the case. The results from the conjoint studysuggested that neophobics were less influenced by the benefits a genetically modified productcould offer, and expected specific guarantees that the product was not genetically modified.The relatively limited role that neophobia played in determining perceptions of risks andbenefits was therefore interesting. However, this may reflect the differences in abstract vsapplied situations. Thus neophobics are not willing to purchase a genetically modifiedproduct because it is an unfamiliar or novel product, rather than because they are nervous ofthe technology itself.

Similarly, the focus group work revealed that one of the concerns consumers had with thegenetic engineering was the role of big business. It would therefore be expected that thosewho were rated as highly alienated from the marketplace (had negative views of business)would be more inclined to see fewer benefits, and more risks of the technology. This was notthe case in the national study. However, those who felt alienated from the marketplace werealso more likely to rate highly on the attitude to nature scale, and were likely to believe thatauthority didn’t know much about the technology - both scales that did play a role in


44

determining perceptions of risks and benefits. Manipulation of the model demonstrated thaton its own, alienation played little role, but there was some element of environmental concernwhich overlapped slightly with the more political aspects of Alienation. Attitude to natureproved the best predictor of opinions of overall risk and benefit.

The low correlation between the self-assessed level of knowledge and the number of correctanswers to the food science questions (‘Actual Knowledge’) has implications for whetherpeople take advantage of information provided. If they think they are well informed – even ifthey are not – they may not pay attention to public education campaigns. These people areless likely to see benefits, and more likely to see risks. In the reverse, those who think no-oneknows very much about GMFs, might also ignore information put out, since they don’tbelieve the organisations who distributed the information actually know what they are talkingabout.

Over 50% of our respondents scored 75% or more on the questions assessing knowledge ofbasic food science. The high level of correct responses supports the repeated assertions (e.g.ESRC, 1999) that consumers do have a reasonable understanding of the underlying science ofthe technology, and should therefore understand information that might be made available tothem.

Specific Applications

Many studies have shown that a consumer’s attitude towards a technology is very muchdictated by the specific application. In this case, we used a food application and a cropapplication that was not going to be ingested. Initially, people seemed more willing topurchase jeans made from genetically modified cotton than genetically modified tomatoes.However, a younger population buy jeans, and it is this group who appears more willing toaccept the technology in general. Removing the younger and oldest age groups removed mostsignificant differences. Thus while jeans made from genetically modified cotton may find lessresistance in the market, this is probably not due to inherently greater acceptability, but rathertheir appeal to a group of people who have fewer concerns about the technology used toproduce them.

Not surprisingly, it appears that the best indicators of a consumer’s behavioural intentions arethe attitudes they hold towards that action. Measuring other factors, like moral obligations,social pressures, and attitudes towards the use of genetic engineering in food production helpto predict these attitudes. The ability to distinguish a food product also predicts attitudestowards that action (although this is not the case with the jeans). That is, if the consumer hasfew personal objections to the technology, perceives society to be accepting of it, and believesthey could identify a product as genetically modified, their intentions to purchase the productwould be much more likely. However, taking away the ability to identify a geneticallymodified product as such would make them feel more negative about buying the product.This is an interesting finding, since it has implications for labelling and perceptions of choice.

Criticism of Methodology

The most important criticism of this study should be the low response rate. What this meansis that we are only obtaining the opinions of those people who were contactable and wished toshare their opinions. We cannot predict the opinions of those who did not respond – asizeable proportion in this study. Unfortunately, New Zealand is one of the most over-researched countries in the world, meaning that many people are fed up with market researchcompanies contacting them. As a result we are only able to draw conclusions about thosewho participated in the study. In this sense, the statistical analyses undertaken here are


45

exploratory, and significance levels quoted should be viewed with caution. Never-the-less,comparisons made with other studies both overseas and in New Zealand can provide someindication of accuracy. It is encouraging to see that our participants followed similarprocesses to those in UK, Denmark and Germany.

Future Research

The current study has achieved the aim of gaining a measure and explanation of NewZealanders’ perceptions of transgenic plants and plant-based products. However, aconsiderable deal more work needs to be conducted to explore these attitudes in depth.

One aspect that needs more in-depth exploration is the difference in the perceptions of controlbetween the genetically modified jeans and tomatoes. Why did respondents feel they wouldbe better able to identify genetically modified jeans? Is it because they think producers aremore likely to label, because the jeans themselves might look different, or because they arenot ingesting the jeans, and are therefore more relaxed about the information they requirefrom the labelling?

Secondly, the conjoint analysis work indicated that benefits to the environment were onlyimportant to a segment of the population. The majority were more responsive to price. Howdo other benefits compare to price (for example, improved sensory qualities)? Similarly, thenature of the national survey meant that we could only look at a couple of applications.Further exploration is needed in terms of benefits offered, and their perceived relevance toconsumers.

The research also highlighted a potential problem in educating people, since there was littlerelationship between perceived and actual knowledge. This has implications forcommunication strategies. What forms of education are most effective?

The gene technology explored in this project involved moving or manipulating genes. Othergene technologies such as marker assisted selection do not necessarily involve theseprocesses. What understanding do consumers have of this technology. What associations dothey have with words such as ‘markers’, ‘gene-splicing’, etc?

One final important note to make is that consumer attitudes are still fluid, and unformed. Theincreasing profile of the technology is sure to have an impact, making monitoring ofconsumer attitudes imperative.


46

APPENDICES

Appendix A. Consumer Focus GroupsDemographic mix of consumer focus group respondents

Group 1(general)

Group 2(general)

Group 3(environmental)

Group 4(environmental)

Group 5(Buddhist)

Group 6(Buddhist)

N=8 N=7 N=5 N=6 N=10 N=10

Age (years) 60+ 0 0 0 0 3 150-60 1 0 1 0 4 440-49 5 2 1 0 2 230-39 2 3 2 2 1 3

Under 30 0 2 0 4 0 0

Gender Male 4 4 2 4 5 5Female 4 4 3 2 5 5

Ethnicity European 8 5 5 6 9 10

Australian 0 1 0 0 0 0Croatian 0 1 0 0 0 0Sri Lankan 0 0 0 0 1 0

HouseholdIncome

<$20,000 1 1 1 1 6 0

$20,000-40,000

0 0 1 4 1 0

$40,000-60,000

0 1 1 0 0 3

$60,001-80,000

6 4 1 0 0 1

$80,000-100,000

1 0 0 0 1 2

>$100,000 0 1 1 1 2 4

Responsiblefor shopping

Yes 6 4 5 4 8 3

No 1 3 0 1 1 0Share 1 0 0 1 1 7

Religion Catholic 2 2 3 0 0 0

Anglican 0 1 0 0 0 0OtherChristian

1 3 1 1 0 0

Buddhist 0 0 0 0 10 10None 5 1 3 5 0 0

Food Meat eater 6 6 3 5 0 1No red meat,but chicken,fish

1 1 0 0 0 1

No meat forhealth

0 0 1 0 1 0

No meat –unethical

1 0 0 1 9 8


47

Appendix B. Grower Focus GroupsDemographic mix of grower focus group respondents

Waikato(pipfruit)

Te Puke(kiwifruit)

Canterbury(arable)

AgriculturalContractor

AttendeesNumbers 27 30 8 20

GenderMale 24 24 8 15

Female 3 5 0 5

Age<20 0 0 0 0

21-30 2 1 0 3

31-40 5 2 2 3

41-50 10 6 4 5

51-60 9 14 1 3

>60 1 5 1 1

OccupationOwner-operator 20 17 6

Owner 3 8 2

Orchard Manager 1 1 0

Other 3 3 0

QualificationsPractical 18 19 8

Degree 4 3 0

Diploma 5 7 0

Certificate 4 4 0

Postgraduate 5 0 0

Off Farm Income% 53.6 63.4 58.75

Main incomesource

Kiwi fruit 1 23 0

Berry fruit 7 0 0

Pip fruit 18 0 0

Stone fruit 3 0 0

Other 8 7 0

Grain 0 0 6

Grass-seedpeas 0 0 4

Clover-seed 0 0 1

Other 0 0 7


48

Waikato(pipfruit)

Te Puke(kiwifruit)

Canterbury(arable)

AgriculturalContractor

How important isgeneticimprovement toenterprise

Currently: Not = 1 7 14 0 0

2 0 1 0 1

3 1 1 0 3

Mid = 3.5 3 0 1 5

4 3 1 3 1

5 2 5 2 1

Highly = 6 10 6 2 3

In the future: Not = 1 2 6 0 0

2 1 1 0 1

3 2 1 0 2

Mid = 3.5 5 2 1 5

4 2 4 3 1

5 3 5 2 1

Highly = 6 12 5 2 4

SELECTION CRITERIAThe following are the decision criteria provided by group participants, and which they used todetermine whether plant breeding technologies were acceptable to them or not. The criteriainclude both positive and negative technology attributes. These were categorised according towhether the effect was upon the decision maker personally, upon their business, or upon theirindustry.


49

Canterbury Arable group

1. For Yourself

Acceptable technologies

Positive criteria Negative criteria

Improved Management Possible trade barriers

Greater Production Market out look on GMO’s

History of use Too many beards (scientists) involved

Greater Profit Market resistance

More Simple Slow progress

Higher quality plants – production Extra time needed

Profitability for grower Less $

More Natural Not cutting edge

Greater Resistance to disease Not fast and efficient

More $ PVR legislation

Improved plants Improved varieties have undesirablecharacteristics

If ....... say they are alright its OK with me e.g., endophyte and stock health

More available Benefit not captured by growers

Improved plants Benefits not sustained in improvedvarieties

Improved Management Greater costs

Cheapness

Suit environment

Clean green image


50

Unacceptable technologies


Quick turnaround In new breeding Improved qualities not accepted byconsumer

Lower production cost No experience using them

Less diseases GMO consumer backlash

Save $ Cost savings may not be there for thefarmer

Faster Breeding Market resistance

Less Chemicals used in S.M.O. crops Clean green image

Cost savings PR people pocket $

Low cost More management problems

Feed the world $

Potential long term hazards (healthplant/human)

Marketing more different

Instability in improved plants Public opinion against them

Less customer acceptance

Greater commercial control

Not natural

Lack of farmer access to varieties

High cost

Consumer views are negative

Using cells from unrelated plants oranimals

Ethics


51

2. For your business



Not separable from self Lack of progress in plant breeding



High returns Lack consumer acceptance

Improved varieties Market resistance

Profitability Long term investment required

Profit No historical experience

Disease resistance Lack of customer acceptance

Less spray Lack of acceptance by customers

Smaller cost Market Limited

Greater profit possibilities Poor media profile

Faster breeding Lack of morality

Higher profit Negative consumer views

Less cost Media windup

Easier management


52

3. For your industry



More Jobs for plant breeders Lower returns

More tradable Higher cost of producing new plants

Easier access Reliance on older chemicals, technologyetc

Lower cost Moral points of view

Production of higher quality food

Health benefits from technologicallyproduced food

Less chemicals needed to control weedand pests

New markets

Keep farmers profit up

New industry process

Will lift plant breeding to a higher level

Greater returns

Less spray used



Greater access to technology Less consumer acceptance

Technology benefits Negative trade effects

Easy management Unforeseen results

Negative consumer perceptions

More trade barriers

Greater market resistance

Greater consumer resistance


53

Waikato Subgroup1

1. For yourself



More risk control Too much variability

Lower risk Requires large numbers of source material

Speed of plant production development Slow to get results

Increased profitability Time cost

Acceptable to customers To slow in improvements

Increased plant vigour Disease control hard to get

Increased production People time to get results

Rapid increases of plants Slow time for results

Improved yields Hit and miss results

Disease resistance

Accumulated experience

Natural way

Improved varieties still being produced



Less time to get result An unhealthy product

Rapid results Unsaleable product

Precise results End of the world

Quick results Not enough known about long termaffects

Stable results Negative side effects from results

Quick results in difficult projects More research required on unknowneffects

Greater disease resistance Not known side effects

Achieve results not otherwise available Public Resistance

Results tailored to demand Greater cost

Less time Large company control plant products

Quicker to develop new products, colours,sizes

Unknown side effects

Don’t know what you are going to havebeyond little plants


54

Work done with a narrow focus

2. For your Business



Same Same

Business/work/Personal are the same Unacceptable to the consumer

All the same Maybe acceptable to me, but unacceptable tothe market

Same Business/work/Personal the same

Same Unacceptable to the consumer

If a better product could be produced cheapere.g. less chemicals

Consumer not necessarily well informed

Same

Same

Same

3. For your Industry



Improvement for the environment To produce a much better product thanour competition

Cost cutting Keeping New Zealand’s Clean greenimage


55

Waikato Subgroup2

1. For yourself



Widely used Takes a long time

Well tested scientifically Very slow processes to get results

Less modification A long slow process

Natural process Low chance of success

A natural process Slow method for justifying improvements

Improved yields, quality Can be non cost-effective

Known results benefit industry Lots of variables i.e., somewhatuncontrollable

Easy to practice Very unpredictable results

Scientifically proven Not enough information on new technologies

Limited intervention by the breeder Likely slow rate of genetic improvement

Copying natural processes Limited existing resources to work with

Relative “safety” to environment of inter andintra specific hybridisation

Anyone can do it

I understand the practice of the methods Time consuming

Already proven Slow breeding

Natural process Outdated technology

Can do it myself if required Unsuited to present breeding needs

Improved qualities

Natural selection operates and removesunhealthy individuals


56

1. For yourself



Side effects possible Ethics DNA plants to animals

Rapid results Unpredictability of performance of GEplants outside the predicted environment

Environmentally advantageous Too many unknowns in gene manipulation

May be cheaper Lack of knowledge

May be more efficient Artificial method

Potential for more rapid geneticimprovement

Unpredictable outcome

Could get novel forms Side effects

Facilitate easier management for growere.g., through resistance introduction

Public perception

Less chemical use Market resistance

Better quality fruit Not enough info available

Low cost production Public reaction

New technologies could bring lesspesticide use

Superbug threat

Improved quality Expensive

Faster production of results Unknown variables

Improve quality less cost in production Little experience withtechniques/outcomes

Marketing Could be beneficial

Faster breeding process


57

Te Puke Subgroup1

1. For yourself


Positive criteria Negative criteria Increased production – decreasedworkload

Low production

Improves yield Breeding too much in one direction -colour taste

Quality of fruit Perhaps unsafe (GMs) More saleable product Quality Better taste and fruit Yield increases that reduce drought

tolerance (for example) Assured quality Unnatural Safe Trait improvements that also result in non

improvements of other traits Size Playing God Disease resistance Using poisons! Protein improvement Specialisation Natural/possible Cost Shape Superior strains for colour, taste andkeeping

Plant select for superior quality fruit Nutritional value Storage Yield Increases size and develops as newvarieties

As similar to nature as possible Increased production per ha To save wildlife habitat Improves taste Above average production Maintaining plants that breed on Increased production Increased yield New varieties with different fruit Natural Known accepted methods Safety Works Improved fruit characteristics Safe


58

1. For yourself



Finding new varieties by natural selection G.M.ing Plants

Faster progress to desired product Market Distrust

Ability to incorporate characteristics outsideKF genepool

Playing God

May be feed all or kill most Inbred insect resistance

Pest resistant plants Using Genes from other species

Less insecticide use Introduction of unknown results

Using Poisons

Transgenic manipulation

Unproven G.M.

Unsustainable

Inbred herbicide resistance

Loss of evolutionary features

Unnatural

Unnatural G.M

Business the same as self




Quicker variety improvements GE totally unacceptable

Even standards Lack of information on all aspects to givequalified comments

Pest resistant plants to reduce pesticide use GE totally unnatural

New varieties GE unproven

Herbicide resistant plants to reduce residualherbicides

GE unsustainable Unsustainable

New varieties to increase market share

Increased productivity


59

Te Puke Subgroup2

1. For yourself



Proven safety Selection slow

Original taste Change to natural fruit structure

Grafting the ability to graft a superior graftwood onto existing rootstock

Disease risk of plants all having samegenetic material

Biogro approval Unknown side effects

Known and not dangerous and lifethreatening

The unknown

Better strains Time

Original Taste Not all traits expressed

Original fruit Slow to change

Change is fast enough Long term effects ????

Safe to eat Risk of creation of new weed whichcannot be controlled

Market advantage GE not properly controlled

Better quality Slow development

Tried and proven systems Radiation dangers

Original shape

Relatively easy to do yourself

Increased products/production

Yield increased

Better keeping

Low risk

Quality improvement

The ability with strict guidelines to leadingahead more quickly

Natural process

Improved products

Proven

Produce variety of choice

Breeding is as nature intended

Selection natural process

In use for a long time

Hybridised improved varieties

Pollination natural

Grafting compatibility


60

1. For yourself



There are no positive aspects Poisonous dangerous untried

Increased yields Unscientific

Improved Quality Not controllable

Disease resistant Uncertainty

Large bulking of material possible Doing to nature what nature would never do

Tissue culture Environmental threat

Bigger scope for alterations Unknown effects

Will be widely used elsewhere Distrust of Monsanto

Expressing desirable consumer traits Environmental damage

Fast Insecure testing

Unknown flow on effects

Customer resistance

Market resistance

Being imposed onto customers

Society values against it

2. For Your Business



Less pesticide i.e. less spraying Market reaction

Consumer acceptability If we can’t sell it no point in growing it

Resistant to disease less spraying GE is not desired by the consumer

Ability to stay out in front with planttechnology

Loss of Bio-gro status

The unknown

Informed consumers do not want GE food

Industry image

The unknown effects on our vines

Customer reactions adverse


61

1. For your Business



Increased % of fruit sellable Consumer

Better fruit presentation (no virus)




None new Chemical companies trying to extract moremoney and to control the food supply

The industry will lose markets if they try tosell GE fruit


62

INFORMATION SOURCE The following table summarises the information sources that growers use and the degree oftrust they place in them and the frequency in which they contact them. The larger the trustnumber, the greater the more the information source is trusted. The smaller the contactnumber, the more frequently growers contact the information source.

INFORMATION SOURCE GROUP TRUST FREQUENCYOF CONTACT

Breeders & Owners of plant materials

Breeder W2 B 1654 128

Commercial owners, media, FIPIA W1B 2206 280

Companies owning plant material W3 A 2206 355

Companies owning plant material W3 B 8332 12

Companies owning plant material W3 C 2206 35

Companies, national, international C A 8332 169

Companies, national, international C B 2206 66

Monsanto TP A 661 16

Nurseryman W1C 8332 13

Science and Research

CRI W1 A 8332 116

CRI W1B 16513 40

CRI W1C 8332 100

HORT Research W2 A 8332 340

HORT Research C B 14448 191

HORT Research – grower collective W2 A 16513 176

International research agencies C B 16513 153

Research centres – New Zealand W3 A 16513 128

Research centres – New Zealand W3 B 8332 12

Research centres – New Zealand W3 C 16513 0

Research centres – Overseas W1C 8332 191

Research centres – Overseas W3 A 16513 51

Research centres – Overseas W3 B 16513 57

Research centres – Overseas W3 C 16513 120

Scientist Collective TP A 8332 182

Scientist Collective W1C 8332 115


63

INFORMATION SOURCE GROUP TRUST FREQUENCYOF CONTACT

Scientist Collective W2 A 8332 333

Scientists – privately funded C A 8332 162

Scientists – privately funded W2 A 2206 241

Scientists – public $, Crop & Food, AgR,MAF

C A 8332 61

Scientists – public $, Crop & Food, AgR,MAF

C B 8332 104

Tech Transfer Agents W1 A 8332 105

Tech Transfer Agents W1B 16513 48


64

Exporters/Processors

ENZA W1C 8332 132

ENZA W1B 8332 48

ENZA W1 A 8332 2

ENZA W2 A 8332 117

ENZA W2 B 6943 132

FAR producer boards C A 16513 18

FAR producer boards C B 16513 17

Producer Boards C B 8332 82

Importer W2 B 2206 315

Private Exporters W2 B 2206 223

Industry leaders W3 A 2206 39

Industry leaders W3 B 4166 70

Industry leaders W3 C 4166 95

Industry Organisations W1B 8332 40

Regulatory /government

ERMA W1B 8332 132

ERMA C A 8332 170

ERMA C B 16513 37

Government departments W3 A 10387 176

Government departments W3 B 4166 238

Government departments W3 C 4166 140

Health department W1 A 8332 175

Health department C A 16513 135

Health department C B 16513 70

Health department W2 A 8332 660

Health department W2 B 16513 480

MAF C B 8332 174

MAF W2 B 14448 261

MAF– RA W3 A 8659 189

MAF-RA W3 B 4166 238

MAF-RA W3 C 12384 52

USFDA / USDA W3 A 16513 149


65

USFDA / USDA W3 B 13513 355

USFDA / USDA W3 C 12384 315

USFDA, ANSFA, ERMA TP A 8332 202

Regulatory authorities, Healthdepartment, ERMA, ANZFA

W1C 16513 0

ANZFA (genetic modified materialrelease)

W3 A 2206 428


W3 B 8332 415


W3 C 6249 168

PSARST, Mae-Wan Ho, Soil & Health TP A 16513 83

Media and Influences

Simon Upton TP A 177 20

Sue Kedgley, Greenpeace W1C 2206 286

Sue Kedgely, Kim Hill C B 551 5

Tech Media/ Internet W1C 8332 110

Tech Media/ Internet W3 A 2206 238

Tech Media/ Internet W3 B 2206 434

Tech Media/ Internet W3 C 4166 193

News Media W1 A 4166 83

News Media C A 2206 18

Greenpeace W1B 2206 225

Greenpeace W1 A 16513 206

Growers Associations

Grower individual W2 A 2206 251

Grower publications W3 A 10387 86

Grower publications W3 B 2206 110

Grower publications W3 C 4166 0

Growers W2 A 2206 115

Growers W2 B 8332 114

International growers associations W3 A 10387 29

International growers associations W3 B 4166 195

International growers associations W3 C 8332 334

National growers associations W3 A 10387 18

National growers associations W3 B 4166 147


66

National growers associations W3 C 8332 129

Consumer Institute

Consumer Institute (CA) 8332 151

Consumer Institute (CB) 2206 190

CODES

Group SubgroupsWaikato1

• W1 A

• W1 B

• W1 C

Waikato2

• W2 A

• W2 B

Waikato3

• W3 A

• W3 B

• W3 C

Te Puke

• TP A

Canterbury

• C A

• C B


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Appendix C. Conjoint Analysis

Design for Tomato information

BENEFIT Tech Price

New! Increased Vitamin C Genetically Modified Tomatoes $4.60

New! Increased Vitamin C Genetically Modified Tomatoes $4.00

New! Pesticide Free! Genetically Modified Tomatoes $4.60

New! Pesticide Free! Genetically Modified Tomatoes $4.30

New! Genetically Modified Tomatoes $4.30

New! Genetically Modified Tomatoes $4.00

New! Increased Vitamin C Organically Produced Tomatoes $4.60

New! Increased Vitamin C Organically Produced Tomatoes $4.00

New! Pesticide Free! Organically Produced Tomatoes $4.60

New! Pesticide Free! Organically Produced Tomatoes $4.30

New! Organically Produced Tomatoes $4.30

New! Organically Produced Tomatoes $4.00

New! Increased Vitamin C Guaranteed Not Genetically Modified $4.60

New! Increased Vitamin C Guaranteed Not Genetically Modified $4.00

New! Pesticide Free! Guaranteed Not Genetically Modified $4.60

New! Pesticide Free! Guaranteed Not Genetically Modified $4.30

New! Guaranteed Not Genetically Modified $4.30



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Design for Chocolate biscuit information

Benefit Tech Price

New! 50% Less Fat Contains Genetically Modified Product $2.95

New! 50% Less Fat Contains Genetically Modified Product $2.55

New! No Artificial Flavourings Contains Genetically Modified Product $2.95

New! No Artificial Flavourings Contains Genetically Modified Product $2.70

New! Contains Genetically Modified Product $2.70

New! Contains Genetically Modified Product $2.55

New! 50% Less Fat All Natural Products $2.95

New! 50% Less Fat All Natural Products $2.55

New! No Artificial Flavourings All Natural Products $2.95

New! No Artificial Flavourings All Natural Products $2.70

New! All Natural Products $2.70

New! All Natural Products $2.55

New! 50% Less Fat Guaranteed Not Genetically Modified $2.95

New! 50% Less Fat Guaranteed Not Genetically Modified $2.55

New! No Artificial Flavourings Guaranteed Not Genetically Modified $2.95

New! No Artificial Flavourings Guaranteed Not Genetically Modified $2.70




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Comparison of Chocolate Biscuit and Tomato Clusters

ExpectedValues

Choc Cluster1

Choc Cluster3

Choc Cluster2a

Choc Cluster2b

Unclustered Total

Tom Cluster1

Expected

Actual

2.2

1.0

4.3

2.0

8.9

4.0

12.6

21.0 1.0 29.0

Tom Cluster2

Expected

Actual

0.9

5.0

1.8

0.0

3.8

1.0

5.4

6.0 3.0 15.0

Tom Cluster3

Expected

Actual

1.6

1.0

3.2

2.0

6.7

12.0

9.5

6.0 3.0 24.0

Tom Cluster4

Expected

Actual

0.9

0.0

1.8

1.0

3.8

6.0

5.4

5.0 1.0 13.0

Tom Cluster5

Expected

Actual

0.5

0.0

0.9

1.0

1.9

4.0

2.7

1.0 2.0 8.0

Tom Cluster6

Expected

Actual

0.6

0.0

1.2

5.0

2.5

1.0

3.6

2.0 0.0 8.0

Tom Cluster8

Expected

Actual

0.3

0.0

0.6

3.0

1.3

1.0

1.8

5.0 0.0 4.0

Unclustered Actual 1.0 0.0 5.0 5.0 2.0 13.0

Total 8.0 14.0 34.0 46.0 12.0 114.0

(O-E)^2/E Cluster 1 Cluster 3 Cluster 2a Cluster 2b

Cluster 1 0.6 1.2 2.7 5.6

Cluster 2 18.0 1.8 2.1 0.1

Cluster 3 0.2 0.5 4.2 1.3

Cluster 4 0.9 0.4 1.2 0.0

Cluster 5 0.5 0.0 2.3 1.1

Cluster 6 0.6 11.5 0.9 0.7

Cluster 8 0.31 9.24 0.06 1.80

chi squared 69.95

p= 4.56E-07


70

Appendix D. National Survey

Demographic profile of the respondents.

N= %

Gender Male 450 49.5

Female 458 50.4

Age 13-17 70 7.7

18-24 69 7.6

25-34 193 21.3

35-44 201 22.1

45-54 149 16.4

55-64 121 13.3

65+ 104 11.5

Not Answered 1 0.1

Ethnicity European 756 83.3

Maori 36 4.0

Polynesian 15 1.7

Chinese 15 1.7

Indian 5 0.6

Korean 2 0.2

Other 18 2.0

Not Answered 61 6.7

Urban/Rural Major Urban 589 64.9

Secondary Urban 68 7.5

Rural 251 27.6


71

N= %

Household Structure Young single 31 3.4

Flatting 73 8.0

Young couple, no kids 60 6.6

Family, preschool kids 110 12.1

Family, school-aged kids 228 25.1

Family, adult kids at home 106 11.7

Older couple, no kids at home 183 20.2

Older single, no kids at home 96 10.6

Not Answered 21 2.3

Socio-economic status High 83 9.1

2 85 9.4

3 235 25.9

4 74 8.1

5 50 5.5

Low 30 3.3

Housewife 32 3.5

Unemployed/retired/student 300 33

Not answered 19 2.1

Educational level Primary 142 15.6

Secondary 426 46.9

Tertiary diploma 135 14.9

Tertiary degree 72 7.9

Postgrad degree 50 5.5

Other 16 1.8

Trade qualification 49 5.4

Not Answered 18 2

Total 908 100


72

Questions asked to assess knowledge of food production and genetic engineering

Enzymes are used in all foods

All bacteria found in food is harmful

Some protein found in foods can be toxic

“Natural’ does not necessarily mean healthy

All processed foods are made using genetically modified products

We eat DNA everyday

To be healthy, food should be sterile before it is eaten

There are no laws or regulations on the use of gene technology in food production

Proportion of respondents who feel into each age group for tomatoes and jeans.

13-17 18-24 25-34 35-44 45-54 55-64 65+ Total

Tomatoes Count 15 12 73 65 45 33 29 272

% 5.5% 4.4% 26.8% 23.9% 16.5% 12.1% 10.7%

Jeans Count 21 38 87 83 62 36 18 345

% 6.1% 11.0% 25.2% 24.1% 18.0% 10.4% 5.2%

Total Count 36 50 160 148 107 69 47 617

% 5.8% 8.1% 25.9% 24.0% 17.3% 11.2% 7.6%

*(Significant (p=0.021) difference between age distributions)


73

REFERENCES

Azjen, I. (1988). Attitudes, Personality and Behavior. Milton Keynes: Open UniversityPress.

Bredahl, L. (1999) Consumer attitudes and decision-making with regard to geneticallyengineered food products. Centre for Market Surveillance, Research and Strategy.http://www.mapp.hha.dk/mapp/gen/pages/contents.html

Concerted Action of the European Commission (B104-CT95-0043) (1997) EuropeAmbivalent on Biotechnology, Nature, 387 (6636); 845-847

Coachman, P.K., and Fink-Jensen, K. (1990) Public Attitudes to Genetic Engineering in NewZealand. DSIR Research Report No. 138

Corney, M.J., Issanchou, S., Shepherd, R., Griffin, K., Nanayakkara, C., and Daillant, B.(1996). Effects of Food Label Health and Nutrition Claims on Consumer Perceptions.Creative Applications: Sensory Techniques Used in Conducting Packaging Research withConsumers. A. Gelinas (Ed). American Society for Testing and Materials; 3-15

CNN (08/11/99) Benjamin, T. Britain’s Organic Market is Healthy andGrowing.(http://cnn.com: 80/FOOD/news/9911/08/organic.foods/index.html).

ESRC Global Environmental Change Programme (1999) the Politics of GM Food: Risk,Science and Public Trust, Special Briefing No. 5, University of Sussex.

Fishbein, M. (1963). An Investigation of the Relationship Between Beliefs about an Objectand the Attitude Toward that Object. Human Relations, Vol 16; 233-239

Frewer, L.J., Howard, C., Hedderley, D., and Shepherd, R. (1996) What Determines Trust inInformation About Food-Related Risks? Underlying Psychological Constructs. RiskAnalysis, Vol. 16 (4); 473-486

HortResearch Internal Report. Gamble, J. (1998). Public Perceptions of Transgenic Plants –Feedback from Round 1 of the Delphi Consultation Process, Report No. 98-13

Green, P.E., and Srinivasan, V. (1978). Conjoint Analysis in Consumer Research: Issue andOutlook. Journal of Consumer Research. Vol 5; 103-123

Lee, K. (1989). Food Neophobia: Major Causes and Treatments. Food Technology (Dec);62-73.

Lyons, M. (2000) Labels could confuse GMO issue. Saskatoon StarPhoenix, Section C1,15/02/00

Macer, D., Bezar, H., Richardson-Harman, N., Kamada, H, Macer, N. (1997) Attitudes tobiotechnology in Japan and New Zealand in 1997, with international comparisons. EubiosJournal of Asian and International Bioethics, 7; 137-143

National Institute of Nutrition (1999). Qualitative Study Among Canadian Consumers onVoluntary Labelling of Foods. Office of Biotechnology, Canadian Food Inspection Agency,Ottawa, Ontario

New Zealand Herald (05/08/99). “Cop-out” Label on GE Rules.http://www.nzherald.co.nz/storydisplay.cfm?storyID=11287

New Zealand Herald (21/02/00). Stevenson, P., Name Your Poison –Organic of Course.http://www.nzherald.co.nz/storydisplay.cfm?storyID=15250New Zealand Official Yearbook (1998) Statistics New Zealand, GP Publications, Wellington,New Zealand.

http://www.nzherald.co.nz/storydisplay.cfm?storyID=11287

http://www.nzherald.co.nz/storydisplay.cfm?storyID=15250


74

Pliner, P. and Hobden, K. (1992). Development of a Scale to Measure the Trait of FoodNeophobia in Humans. Appetite, Vol 19; 105-120.

Richardson-Harman, N., Phelps, T., Mooney, P., and Ball, R. (1998) Consumer Perceptionsof Fruit Production Technologies. New Zealand Journal of Crop and Horticultural Science,26; 181-192

SAS Institute Inc., SASTechnical Report R-109 (1993), Conjoint Examples, Cary, NC: SASInstitute Inc.; 85 pp.

Slovic, P. (1987) Perception of Risk. Science Vol. 236; 280-285

Yann Campbell Hoare Wheeler (1996) National Consumer Survey on Food Labelling.Australian and New Zealand Food Authority. ISBM 0 642 256187

Further Reading

Cantley, M., Hoban, T., and Sasson, A. (1999). Regulations and Consumer AttitudesTowards Biotechnology. Nature Biotechnology, Vol 17 (Sup); 37-40.

Deliza, R., Rosenthal, A., Hedderley, D., MacFie, H.J.H., Frewer, L.J. (1999) TheImportance of Brand, Product Information and Manufacturing Process in the Development ofNovel Environmentally Friendly Vegetable Oils. Journal of International Food andAgribusiness. Vol. 10 (3).

Frewer, L.J., Howard, C., Hedderley, D., and Shepherd, R. (1997). Consumer AttitudesToward Different Food Processing Technologies Used in Cheese Production – The Influenceof Consumer Benefit. Food Quality and Preference, Vol 8 (4); 271-280

Green, P.E., and Rao, V.R. (1971). Conjoint Measurement for Quantifying Judgmental Data.Journal of Marketing Research. Vol 8; 355-363

Hoban, T. J., (1996) Trends in Consumer Acceptance and Awareness of Biotechnology.Journal of Food Distribution Research, Vol. 27 (1); 1-10

Kelley, J. (1995). Public Perceptions of Genetic Engineering: Australia, 1994. TheAustralian National University pp. 1-61

Lyons, M. (2000) Labels could confuse GMO issue. Saskatoon StarPhoenix, Section C1,15/02/00

Macer, D., Bezar, H., Richardson-Harman, N., Kamada, H, Macer, N. (1997) Attitudes tobiotechnology in Japan and New Zealand in 1997, with international comparisons. EubiosJournal of Asian and International Bioethics, 7; 137-143

Office of Technology Assessment (1987). New Developments in Biotechnology.Background paper 2, Public Perceptions of Biotechnology, US Congress Office ofTechnology Assessment, OTA-BP-BA-45. US Government Printing Office Washington DC

genetic engineering: the public’s point of view

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