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iForest - Biogeosciences and Forestry
vol. 8, pp. 707-713
Copyright © 2015 by the Italian Society of Silviculture and Forest Ecology
doi: 10.3832/ifor1339-007

Collection: COST Action FP0905
“Biosafety of forest transgenic trees and EU policy directives”
Guest Editors: Cristina Vettori, Matthias Fladung

Research Articles

Exploring the potential behavior of consumers towards transgenic forest products: the Greek experience

Lambros Tsourgiannis (1)Corresponding author, Vassiliki Kazana (2), Valasia Iakovoglou (2)

Introduction 

The global consumption of forest products, such as wood, paper and woody biomass energy, has been rapidly expanding between 1965 and 2007. For example, the annual average rate for consumption of paper products increased approximately by 3% in the above period. With the global economic crisis started in 2008, the consumption of paper products declined by 2-3% in countries like the USA, Canada and the EU ([19], [31]), while it increased by 5-10% in Russia, China and other countries of South America. Further, econometric models indicated that the demand for paper products in the latter countries will keep rising in the future ([19]).

Forest wood biomass is an important renewable resource that addresses multiple energy needs in the form of firewood, chips, charcoal, briquettes and pellets, as well as feedstock for the biofuels industry ([18], [26], [17]). However, economically feasible long-term utilization of forest wood biomass for energy production depends mainly on its productivity, that should reach 8-10 dry tons acre-1 year-1 for industrial energy applications ([18]). Such high rates are largely higher than those currently obtainable from extant forests. As a consequence, a debate is currently ongoing among academics and the industry on the potential use of transgenic forest trees to meet the projected increased demand of forest products ([14], [32], [5], [25], [26], [12], [10], [11], [34], [17]).

Transgenic forest trees are Genetically Modified (GM) through the insertion/deletion of specific exogenous DNA sequences in order to manifest specific traits (⇒ http:/­/­⇒ www.­forestguild⇒ .­org), such higher growth rates, lignin reduction and increased resistance to herbicides or forest pests. Despite the extensive research carried out on GM trees in the past 20 years, there is no currently market input for transgenic trees in Europe, the USA or other parts of the world, with the only exception of China ([15]).

Public acceptance and the behavior of consumers towards forest products from GM trees mainly reflect people’s concerns on the establishment of plantations of transgenic forest trees. Some concerns involve the potential spread of antibiotic and/or herbicide resistance genes from GM trees to other non-target species, the potential for long-distance pollen spread from long-lived trees, as well as the potential adverse, unexpected and unpredicted effects on biodiversity ([14], [25], [10]). An additional concern is that GM forest plantations might generate profit for private companies, while poorer communities might become further marginalized ([27]).

Although numerous studies have been carried out on public attitudes towards GMOs, no investigations have been carried out in Europe on the potential behavior of consumers towards products from transgenic forest plantations. Previous studies conducted in the USA indicated that consumers are concerned about purchasing final wood products from GM trees, though they generally show a positive attitude towards transgenic forest trees ([24]). Moreover, empirical studies showed that the public attitudes towards forest products are influenced by factors such as cost and availability ([8]). Also, purchasing behavior is influenced by many factors including information, social and cultural norms, beliefs, values and perceptions ([2], [3], [4]). Therefore, information that consumers receive through labelling, branding or other promotional and marketing efforts could influence their response towards GM forest products ([28], [2]).

Although it is unlikely that products from GM forest trees will be marketed in the next 10 to 15 years ([24]), scientifically based information on consumers’ attitudes is extremely important both for developers and policy makers. Indeed, for the developers investments are unlikely to be forthcoming without the expectation of viable markets, while for the policy makers, there is a need to respond adequately through regulation tools and programs ([1]).

This paper aimed at surveying the attitude and the potential purchasing behavior of Greek consumers towards products derived from transgenic forest tree plantations. The profile of potential consumers according to their demographic characteristics and their response towards the establishment of such plantations has been also investigated.

Materials and methods 

The conceptual model

A conceptual model was developed to place key concepts into an identifiable framework (Fig. 1) aimed at investigating: (i) the relationships between factors affecting the potential purchasing behavior of Greek consumers towards the products from transgenic forest trees; and (ii) the consumer groups who exhibited a specific purchasing behavior. The model also explored the linkage between consumers who exhibited a specific purchasing behavior and their opinion towards the establishment of transgenic forest plantations.

Fig. 1 - The Conceptual Model used for the classification of the potential purchasing behavior of Greek consumers towards products derived from transgenic forest trees.

The starting null hypotheses for this study were:

  • H01: consumers cannot be classified into groups according to their potential purchasing behavior towards products from transgenic forest trees;
  • H02: opinions of consumers towards the establishment of transgenic forest plantations are not related to a particular potential purchasing behavior (i.e., group of consumers with potential similar purchasing behavior);
  • H03: demographic characteristics of consumers are not significantly related to their potential purchasing behavior.

Methodology

A survey with individual face-to face interviews have been carried out throughout Greece. Cluster sampling was used to form a representative sample of the whole Greek population. To obtain a geographically-balanced representative sample, nine out of the thirteen existing regions of Greece were selected for sampling, according to the methodology proposed by Oppenheim ([21]). One prefecture in each administrative region was randomly selected and a surveying site was established in supermarkets and/or malls located at the capital/seat of each prefecture. A total of 50 consumers at each surveying site were selected based on a random systematic sampling, i.e., the sixth person approaching the surveying sites was interviewed ([20]). The above sampling design allowed to obtain a representative sample of the whole Greek population, whose characteristics did not differ from those derived from the Census of 2011 ([6], [29], [9]).

A pilot survey was also conducted preliminarily to test if the questionnaire was properly designed to match the research objectives ([30]). Consumers were asked for answering questions on the Likert scale from 1 to 5 regarding the factors that would affect their potential purchasing behavior of products from GM forest trees and their opinion on the establishment of transgenic forest plantations.

The main survey was conducted on November throughout December 2011 by interviewers from each selected prefecture. The sample size was adjusted based on the indications obtained from the pilot study, following the methodology proposed by Siardos ([23]). In particular, the proportion of consumers (p) in the pilot survey who were willing to purchase at least once a product from GM trees (e.g., woody biomass energy or woody product) was 86%. Thus in order to achieve a representative sample, the sample size should have been at least 420 consumers (to have z=3 and d=5% according to [23]). Moreover, a power analysis (β = 0.95) was carried out on pilot data using the software package G*PPXFS 3.1 ([13]), obtaining a minimum sample size of 132 consumers for a medium effect size ([7]). The effect size was calculated as (mean of experimental group - mean of control group)/standard deviation, where a correlation greater than 0.5 is large, 0.5-0.3 is moderate, 0.3-0.1 is small, and anything smaller than 0.1 is trivial ([7]). Based on the above analysis, a sample size of 450 consumers has been considered as fully representative of the whole Greek population.

To extract the key information from the dataset made up with the responses of 418 consumers, multivariate analysis techniques were applied. Principal Component Analysis (PCA) was used to identify those variables accounting for the largest amount of variance within the dataset. To search for the smallest set of such variables, redundancy between variables was checked by applying the Bartlett’s test of sphericity and the Measure of Sampling Adequacy (MSA) to the correlation matrix. Variables showing a high proportion of large absolute correlation values and an MSA index < 0.5 were discarded from further analyses.

An orthogonal rotation (varimax method) was conducted and standard criteria (eigenvalue = 1, scree test and percentage of variance) were used in order to determine the factors in the first rotation ([16]). Different trial rotations were attempted, and factor interpretability was used to compare the eight variables (from PCA) related to the purchasing behavior of consumers with a smaller set of underlying factors.

PCA scores obtained from the above analysis were subjected to cluster analysis to classify the consumers with similar purchasing behavior into homogeneous groups. Both hierarchical and non-hierarchical methods were applied ([16]) on all 418 observations.

Quadratic Discriminant Analysis (QDA) was performed to assess whether the key factors identified through the factor analysis could accurately predict and discriminate cluster membership. Furthermore, the Friedman’s one-way test was performed to identify the relationship between the consumers’ opinion regarding the establishment of transgenic forest plantations and their particular purchasing behavior. Finally, the chi-square analysis and the Fisher’s exact test were carried out on contingency tables using the software package SUAUJCUJDA® (StatSoft Inc., Tulsa, OK, USA) to test for differences in demographic characteristics among the groups of consumers identified. Finally, the most frequent profile of each group of consumers based on their demographic characteristics was obtained.

Results and discussions 

Multivariate analysis was used to identify the key information from the 418 responses to the questionnaire used in the survey. The list of variables affecting the potential purchasing behavior of Greek consumers towards products from GM forest trees are reported in Tab. 1, along with the eigenvalues and the percentage of variance accounted for by each variable considered. The eight main key factors affecting the purchasing behavior of consumers analyzed in this study are listed in Tab. 2.

Tab. 1 - Results of the principal component analysis carried out on the responses of 418 Greek consumers, with the variables affecting their potential purchasing behavior towards the products from transgenic forest trees.
Tab. 2 - Key factors and dimensions affecting the potential purchasing behavior of Greek consumers towards the products from transgenic forest trees.

Based on the cluster analysis carried out on PCA scores, consumers appeared to split into four groups according to their purchasing behavior towards products from GM trees (Tab. 3). Those groups were: (a) consumers who are interested in the quality of products (“Prod. Quality”); (b) consumers who are orientated towards lower prices (“Lower Prices”); (c) consumers who are influenced by labeling and curiosity issues (“Curiosity/Labeling”); and (d) consumers who are interested in health safety issues and the environmental impacts (“Health/Environ.”).

Tab. 3 - Classification of consumers according to their purchasing behavior towards products from transgenic forest trees. (Prod. Quality): Consumers interested in the product’s quality; (Lower Prices): Consumers orientated towards lower prices; (Curiosity/Labeling): Consumers influenced by curiosity and labeling issues; (Health/Environ.): Consumers interested in health safety issues and environmental impact.

The consumers interested in the quality of products from GM trees (group a) comprised 12 % of the respondents and were mainly influenced by the quality of the products and their advertisement. They were also interested in the potential negative environmental impacts of transgenic forest plantations, as well as in labeling issues regarding the indication of the transgenic origin of products. The consumers orientated towards lower prices (group b) comprised 30% of the sample. The potential low prices of such products, their advertisement and brand name, as well as health safety issues were the main factors affecting their potential behavior in purchasing the products of GM forest trees. Consumers influenced by labeling and curiosity issues (group c) were about 35% of the respondents. Most of these consumers declared that they were willing to purchase the products from GM forest trees mainly for curiosity reasons. However, they would like the transgenic origin of products to be indicated on labels. The potential low prices and the brand name of the transgenic products have a significant impact on the purchasing decision of these consumers. Finally, 23% of the respondents could be grouped as consumers who are interested in health safety issues and the possible negative environmental impacts (group d). No other factors were found to affect their potential purchasing behavior towards the products of transgenic forest trees.

Discriminant analysis was performed on the scores from the factor analysis carried out to assess the reliability of the groups obtained by the cluster analysis. A summary of such cross-validation analysis is presented in Tab. 4. It is evident that the eight variables identified could accurately predict and discriminate the group membership of consumers. Therefore, our first starting hypothesis H01: “Consumers cannot be classified into groups according to their potential purchasing behavior towards products from transgenic trees” could be rejected.

Tab. 4 - Summary of the discriminant analysis carried out on PCA scores for cross-validation purposes (total N = 418, N correct = 409, proportion correct = 97.8%). For the labels of the groups of consumers, see Tab. 3.

The Friedman’s non-parametric test was used to explore the opinion of consumers on the establishment of transgenic plantations (Tab. 5). The results revealed that most consumers shared a similar opinions. In particular, most consumers interested in the quality of products (group a) believe that the establishment of transgenic forest plantations will increase job opportunities and the farmers’ income, and reduce the production cost and output losses. On the other hand, they also believe that the establishment of such plantations could have a negative impact on wild native species and, in general, could harm the biodiversity of ecosystems. Regarding the consumers orientated towards lower prices (group b), respondents think that plantations of transgenic forest trees will contribute to the reduction of costs and output losses of the production, and to the increase of job opportunities and farmers’ incomes. Furthermore, most consumers influenced by curiosity and labeling issues (group c) were of the opinion that the establishment of transgenic forest plantations may negatively impact wild species, harm the human health, reduce the production cost, increase the job opportunities, improve the income of farmers, improve the production of biomass and contribute to the reduction of production output losses. Finally, consumers interested in health safety issues and the environmental impacts (group d) mostly believe that the establishment of plantations of transgenic forest trees could represent a danger for human health and for the future of wild species, with negative environmental impacts on the biodiversity of ecosystems.

Tab. 5 - Consumers’ opinions towards the establishment of transgenic forest plantations. Numbers are the average ranks on the Likert scale adopted. For the labels of the groups of consumers, see Tab. 3.

Overall, the first three groups of consumers (a, b, c) paid more attention to the economic impacts of the products from GM forest trees, and were moderately concerned of the possible environmental impacts associated with their production. That is, these potential consumers are willing to buy transgenic forest products, because their purchasing behavior is mainly driven by economic issues, such as price, quality, labeling and branding. These findings coincide with the results of previous studies dealing with the purchasing behavior of consumers towards non-transgenic forest products ([8], [28]). Contrastingly, the last group of consumers (group d) were mainly focused on the possible negative impacts of the establishment of plantations of transgenic forest trees on the biodiversity and the environment, supporting the arguments of other authors ([22], [33], [14], [25]). Hence, our starting hypothesis H02: “Consumers’ opinions towards the establishment of transgenic forest plantations are not significant in relation to a particular potential purchasing behavior (group of consumers with potential similar buying behavior)” could be rejected.

In order to outline the most frequent profile of the respondents based on their demographic characteristics, chi-square and Fisher’s exact tests were also applied on each consumer group previously identified, with the aim of testing for possible differences among groups for each characteristic. Tab. 6 indicates that most consumers interested in the quality of products (group a) were 65 or older, retiree, did not have children and attended the high school. Instead, most consumers orientated towards lower prices (group b) were 30-44 years old, civil servants, had 1-2 children and a high school degree. Moreover, consumers mainly influenced by curiosity and labeling issues (group c) had a profile similar to that of group b (those orientated towards lower prices), with the only difference of having no children. Finally, consumers interested in health safety issues and environmental impact (group d) were 45-64 years old, had 1-2 children, a high school degree and work as free licensed.

Tab. 6 - Profile of each consumer group regarding their demographic characteristics. Data reported are the percentages of the total respondents. For the labels of the groups of consumers, see Tab. 3.

Thus, our starting hypothesis H03: “Consumers’ demographic characteristics are not significantly related to a potential purchasing behavior” could be rejected.

Conclusions 

This study contribute to better understand the potential purchasing behavior of consumers towards products from plantations of transgenic forest trees. In particular, our results indicated that there might be a potential market in Greece for products originated from transgenic forest plantations.

Four groups of potential consumers of products from GM trees with similar purchasing behavior were distinguished: (a) those interested in the quality of products; (b) those oriented towards lower prices; (c) those influenced by curiosity and labeling issues; and (d) consumers interested in health safety issues and environmental impacts.

In general, most potential consumers of transgenic forest tree products in Greece showed a purchasing behavior driven by economic issues (price, quality, labeling and branding). Therefore, there is the potential for market development of such products, that are not directly linked with human health impacts.

Although the products from plantations of transgenic forest trees are not expected to be commercialized in the nearby future, the scientifically-based information collected in this study on the anticipated attitudes of consumers may help future decision of both developers and policy makers dealing with transgenic forest tree products.

Acknowledgments 

This study was initiated within the frame of the EU COST Action FP0905 (⇒ http:/­/­www.­cost-action-fp09⇒ 05.­eu).

References

(1)
Aguilera J, Nielsen KM, Sweet J (2013). Risk assessment of GM trees in the EU: current regulatory framework and guidance. iForest 6: 127-131.
::CrossRef::Google Scholar::
(2)
Ajzen I (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes 50: 179-211.
::CrossRef::Google Scholar::
(3)
Ajzen I, Fishbein M (1980). Understanding attitudes and predicting social behaviour. Prentice-Hall, Englewood Cliffs, NJ, USA. pp. 278.
::Google Scholar::
(4)
Beckett A, Nayak A (2008). The reflexive consumer. Marketing Theory 8 (3): 299-299.
::CrossRef::Google Scholar::
(5)
Carman N, Langelle O, Perry A, Petermann A, Smith JD, Tokar B (2006). Ecological and social impacts of fast growing timber plantations and genetically engineered trees. Dogwood Alliance, Ashville, NC, USA, pp. 12.
::Online::Google Scholar::
(6)
Chen M (2007). Consumers attitudes and purchase intentions in relation to organic foods in Taiwan: moderating effects of food-related personality traits. Food Quality and Preference 18: 1008-1021.
::CrossRef::Google Scholar::
(7)
Cohen J (1988). Statistical power analysis for the behavioral sciences (2nd edn). Erlbaum, Hillsdale, NJ, USA, pp. 273-406.
::Google Scholar::
(8)
DuPuis EM (2000). Not in my body: BGH and the rise of organic milk. Agriculture and Human Values 17 (3): 285-295.
::CrossRef::Google Scholar::
(9)
ELSTAT (2014). Greek national accounts. Hellenic Statistical Authority, Web site.
::Online::Google Scholar::
(10)
FAO (2008). The potential environmental, cultural and socio-economic impacts of genetically modified trees. UNEP/CBD/SBSTTA/13/INF/6, Food and Agriculture Organization of the United Nations, Rome, Italy, pp. 17.
::Google Scholar::
(11)
FAO (2010). Forests and genetically modified trees. Food and Agriculture Organization of the United Nations, Rome, Italy, pp. 235.
::Google Scholar::
(12)
Farnum P, Lucier A, Meilan R (2007). Ecological and population genetics research initiatives for transgenic trees. Tree Genetics and Genomes 3: 119-133.
::CrossRef::Google Scholar::
(13)
Faul F, Erdfelder E, Buchner A, Lang A (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods 41 (4): 1149-1160.
::CrossRef::Google Scholar::
(14)
Gartland K, Crow R, Fenning T, Gartland J (2003). Genetically modified trees: production, properties, and potential. Journal of Arboriculture 29 (5): 259-266.
::Online::Google Scholar::
(15)
Häggman H, Find JM, Pilate G, Gallardo F, Ruohonen-Lehto M, Kazana V, Migliacci F, Ionita L, Sijacic-Nikolic M, Donnarumma F, Harfouche A, Biricolti S, Glandorf B, Tsourgiannis L, Minol K, Paffetti D, Fladung M, Vettori C (2012). Biosafety of genetically modified forest trees (GMTs). COST Action FP0905 - a common action of European scientists. In: Proceedings of the “2nd International Conference of the IUFRO Working Party 2.09.02”. Mendel lectures and Plenary MLP-3, IUFRO, Brno, Czech Republic, pp. 13.
::Google Scholar::
(16)
Hair JF, Anderson RE, Tatham RL, Black WC (1998). Multivariate data analysis. Prentice Hall Inc, New Jersey, USA, pp. 730.
::Google Scholar::
(17)
Harfouche A, Meilan R, Altman A (2011). Tree genetic engineering and applications to sustainable forestry and biomass production. Trends in Biotechnology 29 (1): 11-17.
::CrossRef::Google Scholar::
(18)
Hinchee M, Rottman W, Mullinax L, Zhang C, Chang S, Cunningham M, Pearson L, Nehra N (2009). Short-rotation woody crops for bioenergy and biofuels applications. In Vitro Cellular and Developmental Biology - Plant 45 (6): 619-629.
::CrossRef::Google Scholar::
(19)
Jonsson R (2012). Econometric modelling and projections of wood products demand, supply and trade in Europe. Geneva Timber and Forest Discussion Paper 59, EE/TIM/DP/59, UNECE/ FAO, Geneva, Switzerland, pp. 196.
::Google Scholar::
(20)
McCluskey J, Grimsrud K, Ouchi H, Wahl T (2003). Consumer response to genetically modified food products in Japan. Agricultural and Resource Economic Review 32 (2): 222-231.
::Online::Google Scholar::
(21)
Oppenheim AN (2000). Questionnaire design, interviewing and attitude measurement. Continuum, New York, USA, pp. 303.
::Google Scholar::
(22)
Pajari B, Peck T, Rametsteiner E (1999). Potential markets for certified forest products in Europe. EFI Proceedings No. 25, European Forest Institute, Joensuu, Finland, pp. 352.
::Google Scholar::
(23)
Siardos G (1997). Methodology of agricultural sociological research. Ziti Publications, Thessaloniki, Greece, pp 367.
::Google Scholar::
(24)
Sedjo RA (2004). Transgenic trees: implementation and outcomes of the plant protection act. Resources for the Future, Washington, DC, USA, pp. 28.
::Online::Google Scholar::
(25)
Sedjo RA (2006). Toward commercialization of genetically engineered forests: economic and social considerations. Resources for the Future, Washington, DC, USA, pp. 46.
::Online::Google Scholar::
(26)
Sedjo RA (2010). Transgenic trees for biomass. The effects of regulatory restrictions and court decisions on the pace off commercialization. AgBioForum 13 (4): 391-397.
::Google Scholar::
(27)
Thomas S (2001). Ethical and social considerations in commercial uses of food and fiber crops. In: Proceedings of the “First International Symposium on Ecological and Societal Aspects of Transgenic Plantations: Tree Biotechnology in the New Millenium” (Strauss SH, Bradshaw HD eds). Columbia River George (OR, USA) 22-24 July 2001. College of Forestry, Oregon State University, Corvallis, OR, USA pp. 92-98.
::Online::Google Scholar::
(28)
Tokarczyk J, Hansen E (2006). Creating intangible competitive advantage in the forest products industry. Forest Products Journal 56 (7/8): 4-13.
::Google Scholar::
(29)
Tsourgiannis L, Eddison J, Warren M (2008). Factors affecting the marketing channel choice of sheep and goat farmers in the region of East Macedonia in Greece regarding the distribution of their milk production. Small Ruminant Research 79: 87-97.
::CrossRef::Google Scholar::
(30)
Tsourgiannis L, Kazana V, Karasavvoglouc A, Nikolaidisc M, Florouc G, Polychronidouc P (2013). Exploring consumers’ attitudes towards wood products that could be derived from transgenic plantations in Greece. Procedia Technology 8: 554-560.
::CrossRef::Google Scholar::
(31)
UNECE (2012). Forest products statistics 2007-2011. Timber Bulletin ECE/TIM/BULL/65/2, UNECE-FAO Forestry Department, web site.
::Online::Google Scholar::
(32)
Van Frankenhuyzen K, Beardmore T (2004). Current status and environmental impact of transgenic forest trees. Canadian Journal of Forest Research 34: 1163-1180.
::CrossRef::Google Scholar::
(33)
Vlosky R, Ozanne L, Fontenot R (1999). A conceptual model for US consumers willingness-to-pay for environmentally certified wood products. Journal of Consumer Marketing 16 (2): 122-136.
::CrossRef::Google Scholar::
(34)
Zhu J, Pan X (2010). Woody biomass pretreatment for cellulosic ethanol production: Technology and energy consumption evaluation . Bioresource Technology 101 (13): 4992-5002.
::CrossRef::Google Scholar::

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Tsourgiannis L, Kazana V, Iakovoglou V (2015).
Exploring the potential behavior of consumers towards transgenic forest products: the Greek experience
iForest - Biogeosciences and Forestry 8: 707-713. - doi: 10.3832/ifor1339-007
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Title Exploring the potential behavior of consumers towards transgenic forest products: the Greek experience
Authors Tsourgiannis L, Kazana V, Iakovoglou V
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