Abstract
Existing research based on labels, risks and benefits, and cultural differences has focused on consumers’ preferences for genetically modified (GM) food products. Limited attention has been paid to the attitudes toward the source who developed the biotechnology. Because there may be trust issues associated with large multinational firms that are often involved in the development of biotechnology, it remains an unexplored question whether consumers consider who produces the technology when forming opinions about food produced with biotechnology. This study investigates consumers’ attitude toward the source of biotechnology using a choice experiment with GM oranges. The study involved participants from three major orange-consuming countries (United States, Germany, and Spain). Results reveal that participants from all three countries were less willing to pay for GM oranges when the technology originated from multinational agribusiness corporations, compared to public universities and small companies. Further examining the effect of consumers’ perceptions, we found consumers’ perception of corporate distrust and environmental concern negatively influence their attitude toward the source of biotechnology, but their technology acceptance positively affects the attitude. By understanding consumers’ attitudes about the source of biotechnology and factors that may improve the consumer reactions, communication and promotion of new biotechnology food products to improve acceptance from existing and potential consumers are discussed.
1. Introduction
Genetically modified organisms (GMOs) have been present within the food industry since the 1980s. Most commercial genetically modified (GM) food products are used as food ingredients and are not available for direct consumption. There are only a few applications of biotechnology in fruits and vegetables, but with these products entering the market and new ones being researched, questions about the impacts of genetic engineering technologies on demand remain important (Lucht, 2015).
Despite the scientific support identifying benefits and safety of GM foods, resistance and concern about the use of biotechnology in food production exists among consumers worldwide (Huffman, 2011; Lusk et al., 2018; National Academies of Sciences, 2016; Zilberman et al., 2018). Part of the reason for consumers’ concern is due to negative media coverage that often propagates the idea that GM foods are dangerous, unnatural, and unreal, with headlines such as ‘The food industry: son of frankenfood’ and ‘GMOs: up from the dead’ contributing to the negative perception of the use of GM biotechnology in food production. Consumers may have concerns over the unknown long-term effects on the environment and human health of the GM (transgenic) method (Zilberman et al., 2018).
CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats), a newer gene engineering biotechnology, has gained much attention (Hu et al., 2022; Muringai et al., 2020; Wang et al., 2019). Unlike many existing genetically modified products, CRISPR does not introduce foreign genes, and gene editing techniques involve fewer risk factors. Recent research indicates CRISPR is likely to be more accepted by consumers than transgenesis and cisgenesis (Globus and Qimron, 2018; Hu et al, 2022; Muringai et al., 2020). Changes to the way products are developed could lead to changes in who is involved in the production (i.e. the source of biotechnology), thus leaving an open question as to how consumers incorporate this information into their acceptance of food produced using biotechnology.
Consumers’ attitude (i.e. trust or distrust, support or opposition) toward the source of biotechnology is a significant factor when determining their acceptance and willingness to pay (WTP) for GM foods (Lucht, 2015; Lusk et al., 2018; Muringai et al., 2020). This subject is of interest, as it may explain some attitudes and preferences for GM foods. For example, if there is general mistrust of the institution conducting the research, it stands to reason that this would impact consumers’ acceptance of the final product. However, only a few studies have examined the consumers’ attitude on the source of biotechnology, and focused only on one country. To our knowledge, there has been no study on the across country comparison of the attitude toward the source (i.e. EU countries vs USA). More importantly, the effects of perceptional and socio-economic factors that may influence consumers’ attitude toward the developer of biotechnology remain unknown. Understanding whether this is part of the dynamics of different countries’ consumer opinion can inform policymakers and industry to make informed decisions and provide policy implications about how to improve overall acceptance through influencing consumers’ heterogenous attitudes and preferences for biotechnology developed by different institutions.
To contribute further to the literature, this study investigated consumers’ attitude toward the source of biotechnology when they select GM food products in three countries (USA, Germany, and Spain). We applied a choice experiment approach and implemented surveys to understand consumers’ acceptance of GM oranges. Specifically, we examined consumers’ attitude (willingness to pay) toward different sources of biotechnology that developed biotechnology for oranges. In addition, we examined the factors (perceptional and socio-economic factors) that may influence the attitude. Three perceptional factors (i.e. corporate distrust, technology acceptance, and environmental concern) were applied to reveal how consumers’ perceptions influence their attitudes toward the source of biotechnology.
A great deal of research focused on consumers’ acceptance of biotechnology. Early research found that consumers prefer GM to non-GM products (Loureiro and Bugbee, 2005) and later studies indicated that non-GM is preferred to GM products (Edenbrandt et al., 2018; Gao et al., 2019; Lusk et al., 2004; Noussair et al., 2004). In addition to base acceptance, research also focused specifically on how labels, knowledge, and perceived benefits impact consumers’ willingness to accept GMOs. For example, Heng et al. (2021) explored factors that drive consumers’ willingness to purchase fresh fruit produced with biotechnology. They found environmental awareness, self-reported healthiness and habits of eating away from home enhance the willingness to purchase of biotechnology producted fruit. Rose et al. found a positive relationship between perceived knowledge and willingness to accept, but mixed results for the relationship between factual knowledge and acceptance (Rose et al., 2019). Other research has found that as positive GM food product information becomes more available, consumers increase preferences for GM food products (Edenbrandt et al., 2018; Huffman and McCluskey, 2017). In terms of the new gene editing technology, Hu et al. (2022) found consumers are willing to pay more for CRISPR orange juice than GM orange juice with more information and Muringai et al. (2020) found that Canadian consumers are more accepting of the gene editing technology than the GM technology.
Biotechnologies originate from different sources/institutions, and multiple expert groups and organizations have been involved in the revolutionary breakthroughs (Lang and Hallman, 2005). Since the 1990s, many products with biotechnology have been developed and commericialized by large multinational agribusinesses (e.g. Monsanto). With the fast development of genetic engineering, public organizations such as universities have also been involved. More recently, and in part due to the lower investment cost in technologies like CRISPR over GM, small high-tech companies are entering the arena. For example, Caribou Bioscience is a pinoneer in genome editing in agricultural biotechnology. However, the understanding of how consumers’ attitidue toward the source of biotechnology is limited. Only a few studies focused on the important factors that influence consumers’ acceptance of GM products – the developer of the biotechnology (Lusk et al., 2018; Moon & Balasubramanian, 2003; Muringai et al., 2020; Siegrist et al., 2012). Previous studies have shown consumer opposition to GM foodes developed by multinational corporations (Moon and Balasubramanian, 2003; Lucht, 2015; Lusk et al., 2018), but support for university (Lucht, 2015), government and other agribusiness firms (Lusk et al., 2018; Muringai et al., 2020). Moreover, only few revealed how support/opposition for developers affect consumer acceptance of GM products (Lusk et al., 2018; Muringai et al., 2020). Lusk et al. (2018) found the more consumers supported the developer, the less concerns about the safety of the genetically engineered food. Muringai et al. (2020) studied consumer WTP for different developers of genetic technologies and found Canadian consumers preferred the government as the developer, despite the biotechnology.
Consumers’ existing perception may influence consumers’ preference for GM foods (Costa-Font et al., 2008; Frewer et al., 2013; Spendrup et al., 2021). Consumers’ attitudes toward the source of biotechnology may also be influenced by consumers’ perception. For example, trust in the organizations may be an important component in influencing consumers’ preferences in general for GM food products, and particularly for the source of biotechnology. Existing literature reveals that consumer trust in organizations has a strong impact on the perceived risks and benefits associated with GM biotechnology (Siegrist, 1999). If individuals believe that the biotechnology industry conducting the research prioritizes the interest of the general population, fewer risks and more benefits are perceived by the public; hence public trust is high (Siegrist, 2003; Siegrist et al., 2012). Conversely, the lack of trust can be an important obstacle to the acceptance of GM food products. Trust issues are often associated with large multinational firms that are involved in the development of biotechnology. Issues associated with acceptance of GM food products may also include distrust in other entities associated with GM food products, such as the federal government, grocers, and the food industry (Lang and Hallman, 2005). The effects of trust on consumers’ preferences can vary depending on the different types of organizations (McFadden and Huffman, 2017; Oehlmann and Meyerhoff, 2017). Moreover, based on prior research, consumers’ environmental concern influences their acceptance of GM food products (Heng et al., 2021) and consumers with a positive attitude towards technology may show positive attitudes toward biotechnology (Boser et al., 1998).
A better understating of the correlation between consumers’ perception and their preference can be used to improve consumers’ acceptance of biotechnology and encourage consumption of GM food products. Therefore, in addition to examine consumers’ attitude toward the source of technology, the aformentioned findings motivated us to further examine the effects of consumers’ perception on their attitude toward the source of biotechonology and how it varies depending on the different types of organizations. Three perceptional factors (i.e. corporate distrust, technology acceptance, and environmental concern) were included to develop a deeper understanding of the relationship between general consumer attitudes and GM products.
Consumers’ attitudes toward the source of biotechnology may differ across regions and countries. Early literature indicates that geographic location and cultural differences influence consumers’ willingness to accept biotechnology in food production. Multinational studies have compared USA and European consumers, and while both groups show reluctance to accept biotechnology, the magnitude varies with Europeans valuing non-GM goods more than their USA counterparts (Lusk et al., 2005). In a study comparing USA and UK consumers, although UK consumers required a lower price, both groups were willing to purchase GM cereal if a perceived benefit was evident (Moon and Balasubramanian, 2003). When comparing USA and Italian consumers, both groups showed a reluctance toward GM food products. Italian consumers were much less likely to purchase GM goods compared to USA consumers (Harrison et al., 2004). Xie et al. (2013) found that information affects WTP similarly in the USA, Germany, and Spain, with positive benefit information improving consumers’ WTP for GM food products. In another study, Lusk et al. (2004) showed French consumers reacted negatively to benefit information. Accordingly, this study incorporates results from countries that have shown different levels of acceptance to determine whether the source of biotechnology can explain some of these differences.
This study is based on a project investigating consumers’ preferences for genetically modified oranges in three countries, i.e. USA, Spain, and Germany.1 Oranges were chosen because of the high rate of production and consumption worldwide. The USA is one of the top orange producers in the world, producing about 4.7 million tonnes of oranges in 2019/2020 (USDA Foreign Agricultural Service, 2021). The European Union produced around 6.2 million tonnes of total citrus in 2019/2020 (USDA Foreign Agricultural Service, 2021). In addition, oranges are an important part of fruit consumption in the USA, Spain, and Germany. Oranges are ranked first in total fruit consumption in the USA, and among the top five fruits consumed in Germany. Approximately 40 pounds per capita are consumed annually in Spain (USDA Foreign Agricultural Service, 2017). More important, the orange industry is experiencing reduced production from a disease (citrus greening) that has received public attention, for which one potential solution is biotechnology, making very timely the choice of oranges as a focal product to be examined.
In this study, we hypothesize that consumers will require discounts to purchase oranges produced with biotechnology developed by different organizations. We further hypothesize consumers will be more accepting of technologies produced by public universities and small family companies compared to multinational firms. Additionally, we hypothesize that the level of consumer distrust in organizations will have a significant impact on the attitude toward the of biotechnology. Consumers with higher distrust in organizations in general may be more skeptical of GM oranges from large companies than from smaller companies. This is distinctly different from trust in technology itself as it is tied to trust in the producer of the technology. We also hypothesize that consumers’ environmental concern will positively influence their attitude towards the source of biotechnology and the acceptance of GM food products. Lastly, we hypothesize that consumers general attitude towards technology will translate to a positive impact on the attitude toward the source of biotechnology.
2. Methods
2.1. Choice experiment design
A discrete choice experiment (CE) was applied to reveal consumers’ attitude toward different sources of biotechnology for GM oranges. Following the recommendations of Johnston et al. (2017), the choice experiment was developed with nine choice scenarios, and participants were asked to select between two options of purchasing GM oranges in unit weight (pounds in USA and kilos in Europe), and a no-purchase option. The no-purchase option was included to reduce the hypothetical bias. Prior to beginning the CE, participants were asked to think about the decision as if they were in a store to purchase the oranges. In each choice scenario, the oranges were described by three attributes: (1) price, (2) presence of seeds and (3) the source of biotechnology for the GM oranges (i.e. multinational agribusiness corporation [MNC], public university [UNIV], or small company [FAM]). Attribute levels are shown in Table 1. The unit price for each country was in local currency. The choice experiment was constructed to maximize D-efficiency (SAS9.4). An example choice scenario is shown in Figure 1.
Orange attributes and levels.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
Choice scenario example for purchasing GM oranges with different perceptions.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
2.2. Data collection
The data were collected through online surveys in April and May of 2016, and participants were recruited from the panel provided by Toluna, Inc. (Norwalk, CT, USA) In total, the number of complete observations used in the analysis were 2,061 from the USA; 1,997 from Germany; and 1,996 from Spain. A brief summary of participants’ sociodemographic information is illustrated in Table 2.
Summary of demographic statistics.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
Participants also answered a series of questions that included the three scales to measure their perceptions: the corporate distrust (CD) scale (Adams et al., 2010), the new ecological paradigm (NEP) scale (Dunlap et al., 2000), and the technology acceptance (TA) scale (adopted from the PATT-USA questionnaire) (Boser et al., 1998). The CD scale, adapted from Adams et al. (2010), measured participants’ trust/distrust in corporations. A higher score means that a participant is more likely to not trust corporations (Adams et al., 2010). The NEP scale is widely used as a measure for environmental concern and pro-environmental orientation. In this study, we used a revised version similar to Dunlap et al. (2000) and a higher score indicates a more pro-environmental attitude. The TA scale adapted from the PATT-USA questionnaire (Boser et al., 1998) assessed participants’ general perception and acceptance toward technology, again with a higher score indicating a more accepting attitude toward technology.
Total scores for each of the three scales were calculated to show participants’ sentiments regarding corporate distrust, environmental concern, and technology acceptance, respectively. A visual summary of the three perceptional/attitudinal scales with the mean and standard deviation is shown in Figure 2.2 Participants from Spain had a relatively high score for corporate distrust, followed by Germany and the USA (70.3, 66.5, and 64.1, respectively). In terms of the environmental concern, USA participants had a statistically lower NEP score (70.3) compared to Germany and Spain (76.6 and 74.4, and the two European countries were not statistically different). For the last perceptional factor, technology acceptance, there was no statistical difference among all three countries.
Boxplot of the three scales, corporate distrust (CD), technology acceptance (TA), and environmental concern (NEC), for three countries (USA, (US), Germany (GER), and Spain (SP), respectively). Full score: CD = 91, Tech = 35 and NEP = 105.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
2.3. Econometric model
■ Random parameter logit model
To reveal consumers’ attitude toward the source of biotechnology and examine the effects of the three perceptional factors on the attitude, the analysis was divided into two stages: a random parameters logit (RPL) model and a seemingly unrelated regression (SUR) model. The RPL model was used to estimate preference and account for preference heterogeneity in the choice probability component. The RPL model divides an individual’s utility into an observable component and an error term that is independently and identically distributed (iid) extreme value. In the random utility model, the utility level of the ith product for the nth participant given choice occasion t is written as:
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
where xnit and znit are vectors of observed variables related to alternative i.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
Where
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
where
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
where the numerator is the coefficient of the non-price attribute, and the denominator is the price coefficient. WTP estimates were computed based on the linear form of the utility function used and were estimated over the parameter distribution (e.g. normal distribution). Hence, the WTP per unit of oranges is calculated for the three sources of biotechnology (MNC, FAM, and UNIV), and for the seedless attribute.
■ Seemingly unrelated regression model
The second stage of the analysis examined how consumers’ prior perceptions affect their attitude towards the source of biotechonology. The SUR-model was applied to evaluate the effect of participants’ perceptions (CD, TA, and NEP) on individual WTP for the different sources of biotechnology. We followed a method used in Bi et al. (2016) and Zhang and Khachatryan (2021), in which the posterior estimation of individual-level parameters was applied (Train, 2009). The SUR model is a commonly used linear regression model with multiple equations; further details about it can be found in Greene (2012). The SUR model is shown as:
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
The dependent variable in the SUR model was the individual level WTP estimates obtained from post-estimation of the RPL model, with socio-economic variables being controlled. WTPi are individual WTP estimates for each of the attributes; CD, TA, and NEP are individual scores of the three perceptional factors. Age is the age of the respondent; Kid is a dummy variable if children are in the home; Mincome and Hincome are medium and high income level, respectively; and Graduate School and College compares those groups to respondents with a high school education or less. Retired and Student represent the employment status of retirement and full time student, with full/part-time employed as the base. Although there might be potential endogeneity issue between the perception variable and participants’ response, by chosing the general perception scales (not specifically related to biotechnology), the impact of endogeneity was minimized.
3. Empirical results
3.1. Consumers’ attitude toward the source of biotechnology
Participants’ attitude toward the source of biotechnology was analyzed and compared across USA, Germany, and Spain. The mean WTP estimates were calculated using the estimated coefficients obtained from the RPL model (the estimated coefficients are reported in Supplementary Table S2. Since both the currency and the prices of oranges differ across countries, the mean WTP estimates were illustrated by each country’s currency (Table 3). To make the results comparable across countries, the WTP estimates are shown as the percentage rate over the prevalent non-GM orange price in the country (results can be read as the percent change in price compared to the average non-GM orange price by country). As expected based on prior research, participants preferred non-GM oranges to GM oranges. With the non-GM orange as the baseline, a negative percent indicated that participants required a discount to purchase GM oranges in relation to non-GM oranges.
Willingness-to-pay estimates for three countries based on source of GM biotechnology.1,2
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0103
Participants’ attitude toward different sources of biotechnology varied, but discounts were required for all sources, across all countries, compared to oranges produced without the biotechnology. The attitude toward the three sources followed the same pattern across the three countries, with least preferred source of multinational agribusiness corporations (discounts of 51.7, 83.1, and 68.7% for USA, German, and Spanish participants, respectively), followed by the source of public universities (discounts of 33.7, 48.2, and 47.6% for USA, German, and Spanish participants, respectively), and relatively preferred source of small high-tech companies (discounts of 26.1, 19.0, and 36.0% for USA, German, and Spanish participants, respectively). Compared with participants from two European countries, USA participants required lower discounts, implying a relatively more accepting view of biotechnology from different sources. Although biotechnology in food production tended to reside with universities and large companies due to high investment costs, innovations such as CRISPR have made it more possible for small high-tech companies to compete in this sector, with relatively better consumers’ acceptance.
The seedless attribute was a benchmark for relative strength comparison of participants’ attitude toward the source of biotechnology across the three countries. Participants preferred the seedless attribute with positive WTP estimates as expected. The WTP estimates were positive and consistent across the three countries (9% for USA participants, 10.3% for German participants, and 2% for Spanish participants). This result was used to measure the relative strength of the consumers’ preference for the source of biotechnology, and indicated that participants required relatively larger discounts to avoid biotechnology compared to the premium they were willing to pay to avoid seeds.
3.2. Effect of consumer perceptions and attitudes
In the second stage analysis, we examined the effects of participants’ perception of corporate distrust, environmental concern, and technology acceptance on their attitude toward the source of biotechnology. Participants’ perceptional factors were linked with the individual WTP estimates of the different sources of biotechnology. In this case, WTP estimates were converted to $/lb. for each country to enable comparison of estimated results. Controlling the socio-economic effect, the results are shown in Supplementary Table S1.
It is worth noting that the seedless attribute was also included to compare relative strength of other attributes in this study. It was not expected that demographics or perceptions of corporate distrust, environmental concern, and technology acceptance would be significantly related to consumers’ preference for the seedless attributes. As expected, the effects of the three scales on participants’ WTP for the seedless attribute (Supplementary Table S1, columns 4, 8, and 12) were mostly insignificant (where it is significant, the marginal effect was almost negligible, less than one cent). The only exception was that for German participants; their technology acceptance significantly influenced their WTP for the seedless attribute by 2.6 cents (marginal effect).
The effects of the three scales on the attitude toward the source of biotechnology were significant and consistent across the three countries. Participants’ corporate distrust and environmental concern significantly and negatively impacts their preferences for the source of biotechnology as expected, and the impacts varied for the different sources. However, participants’ technology acceptance had a small but positive influence. The marginal effect of technology acceptance was not big enough to cover any negative effects from participants’ corporate distrust and environmental concern.
■ Corporate distrust
Although previous studies showed that trust in biotechnology did not vary much between USA and European participants (Frewer et al., 2013), when measured by the distrust scale for the attitude toward the source of technology, we found that participants’ distrust of corporations had significant negative impact and differed based on the source of biotechnology and country (Supplementary Table S1, row 1).
Specially, participants’ corporate distrust affected their attitude substantially toward the biotechnology developer as multinational agribusiness corporations. For participants from the USA and Spain, corporate distrust had the largest negative effect on multinational agribusiness corporations ($0.026/lb and $0.029/lb for participants from the USA and Spain), while the lower impact was seen for public universities ($0.006/lb and $0.011/lb) and for small high-techcompanies ($0.008/lb and $0.016/lb). Results for participants from Germany were quite different. In this case, the marginal effect of corporate distrust was more negative on the preference for small companies ($0.027/lb) than for multinational agribusiness corporations ($0.019/lb) or public universitites ($0.018/lb).
■ Environmental concern
Participants’ environmental concern also had significant negative impact on the attitude toward the source of biotechnology across the three countries (Supplementary Table S1, row 3). The results indicated that if the participants were more concerned about the environment, they would reduce their WTP for the biotechnology from all three sources. Specifically, the marginal effects of USA participants’ environmental concern on the WTP for all three sources of biotechnology were negative $0.014/lb (MNC), $0.012/lb (UNIV), and $0.007/lb (FAM). German and Spanish participants indicated overall greater concerns for the environment, and the impacts of environmental concern on the attitude were greater than USA participants. The marginal effects of German participants’ environmental concern were negative $0.039/lb (MNC), $0.011/lb (UNIV), and $0.017/lb (FAM), respectively, on the WTP for the biotechnology sources. For Spanish participants, the marginal effects were negative $0.028/lb (MNC), $0.023/lb (UNIV), and $0.018/lb (FAM), respectively. Participants linked environment consequence with all sources of the biotechnologiy in a negative way, and consumers’ environmental concern amplified the negative attitude toward the biotechnology developed by big corporations.
■ Technology acceptance
The third influence on the attitude toward the source of biotechnology is the general attitude toward technology. As such, a scale was used to determine if overall attitude toward technology influences the attitude toward the different sources. Technology acceptance is expected to have a positive relationship with WTP for GM oranges.
The results indicated that a higher technology acceptance score was positively associated with participants’ WTP for the sources of biotechonology across three countries (Supplementary Table S1, row 2). With a one unit increase in the score on the technology acceptance scale, marginal effects on WTP for the source of biotechnology ranged from $0.025/lb to $0.066/lb across the three countries. Interestingly, biotechnology developed by small high-tech companies received the largest positive effects from US and German participants ($0.035/lb and $0.054/lb), where biotechonology developed by public universities had the largest positive effect from Spanish participants ($0.066/lb).
In summary, the hypotheses were supported. Participants from three countries score differently in the perception scales, and the results showed that all the three perceptional factors were significantly correlated with participants’ attitude toward the source of biotechnology. For USA and Spanish participants, the perceptional factor with the largest influence was corporate distrust. For German participants, environmental concern has the dominant effect. Participants with higher levels of corporate distrust and environmental concern required much larger discounts to accept GM oranges using biotechnology from the three sources. Conversely, if consumers had higher level of technology acceptance, smaller discounts were required, suggesting that general technology acceptance (i.e. gene editing) could somewhat offset the negative effect from consumers’ perception of environmental concern and corporate distrust.
4. Discussion and conclusions
Genetic engineering technologies for fresh fruits and vegetables have had various levels of success. As new gene engineering biotechnologies emerge, understanding the underlying factors that may influence consumers’ attitude toward the developer and acceptance of GM food products continues to be relevant for the development of the biotechnology and related marketing strategies and programs to promote the GM food products. This study used a stated preference method with participants from three major orange-consuming countries to reveal consumers’ attitude toward the source of biotechnology when purchasing oranges. One major contribution to the literature is to relate consumers’ attitude toward the source of biotechnology with acceptance of GM orange and examine the perceptional factors that influence the attitude. Given the involvement of large, multinational companies (that sometimes associate with trust issues and attract negative reactions from consumers) and newly emerging small high-tech companies in biotechnology, it is an important, and yet unstudied question to understand how who produced the technology influences consumers’ preference and acceptance of GM food products.
Our results indicate that USA, Spanish, and German participants all preferred non-GM oranges and require discounts to purchase GM oranges. Our findings are consistent with the existing literature. Our results further reveal that the consumers’ attitude was quite consistent across the three studied countries, but with different levels of discounts required for the biotechnology developed by the different sources (i.e. multinational agribusiness corporations, public universities, or small companies). These results agree with the findings of previous studies (Lusk et al., 2018; Muringai et al., 2021), and we find that participants most prefer biotechnology developed by small companies, compared to public universities, and least prefer technology developed by multinational agribusiness corporations.
Consumers’ perceptions, i.e. corporate distrust, environmental concern, and technology acceptance significantly influence their attitude toward the source of biotechnology. The effects of the three perceptional factors were all significant. Consumers’ perception of general corporate untrustworthiness and environmental concern negatively affected consumers’ acceptance of biotechnology, while the consumers’ level of general technology acceptance increased acceptance of biotechnology. These impacts were amplified for multinational agribusiness corporations, compared to public universities and small companies.
The study provides several implications. First, it is important to address negative percetpions of biotechnology related to perception of negative environment and health consequences. Secondly, improve the image of the institutions and the trustworthiness in public view. In other words, improving the trust for the institutions could improve consumers’ attitude and acceptance for GM food products. Or at least it disentangles the connected trust issues between the institution and biotechnology. Second, multinational agribusiness corporations should be aware that many consumers have a stereotyped impression that creates a disadvantage for consumers to accept biotechnology from the institutions. They may consider increasing efforts to collaborate with universities or smaller companies for future biotechnology development to aid consumer acceptance of final products. Moreover, biotechnology developers and GM food producers may position biotechnology as a technological advance in the food industry to offset the negative concept of ‘Frankenfood.’ Overall, consumer awareness campaigns and educational programs for developing potential markets for GM food products can be used to improve both consumer trust and acceptance for biotechnology, including understanding of the source of the biotechnology.
Consumer acceptance of biotechnology in food production is an important component for GM products to be effectively implemented and marketed. By understanding the consumers’ attitude toward the source of biotechnology and factors that may potentially improve the consumer reactions, stakeholders in biotechnology-related industries, e.g. government, technology developers, companies in the GM food producers supply chain, etc., can effectively allocate resources to improve consumers’ perception and acceptance for GM food products. Our findings can guide marketing strategies and improve the efficacy of marketing programs, in terms of who produces the technology and what aspects of benefit information of biotechnology should be communicated to improve consumers’ acceptance for GM food products.
Conflict of interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work was partially supported by the Specialty Crops Research Initiative (grant no. 2016-70016-24833) from the USDA National Institute of Food and Agriculture.
Supplementary material
Supplementary material can be found online at https://doi.org/10.6084/m9.figshare.23508030.
Table S1. Marginal effects on individual level WTP estimated by SUR models (controlled socio-demographics).
Table S2. Items of the corporate distrust (CD) scale and score summary.
Table S3. Items of the technology acceptance (TA) scale and score summary.
Table S4. Items comprising the new ecological paradigm (NEP) scale and summary of the sample scores.
Table S5. Estimated coefficients by mixed logit models.
References
Adams, J.E., S. Highhouse and M.J. Zickar. 2010. Understanding general distrust of corporations. Corporate Reputation Review 13(1): 38-51. https://doi.org/10.1057/crr.2010.6
Bi, X., L.A. House and Z. Gao. 2016. Impacts of nutrition information on choices of fresh seafood among parents. Marine Resource Economics 31(3): 355-372. https://doi.org/10.1086/686714
Boser, R. A., J. D. Palmer and M.K. Daugherty. 1998. Students’ attitudes toward technology in selected technology education programs. Journal of Technology Education 10(1): 4-19. https://doi.org/10.21061/jte.v10i1.a.1
Costa-Font, M., J.M. Gil and W.B. Traill. 2008. Consumer acceptance, valuation of and attitudes towards genetically modified food: review and implications for food policy. Food Policy 33: 99-111. https://doi.org/10.1016/j.foodpol.2007.07.002
Dunlap, R. E., K.D. van Liere, A.G. Mertig and R.E. Jones. 2000. New trends in measuring environmental attitudes: measuring endorsement of the new ecological paradigm: a revised NEP scale. Journal of Social Issues 56(3): 425-442. https://doi.org/10.1111/0022-4537.00176.
Edenbrandt, A.K., L.A. House, Z. Gao, M. Olmstead and D. Gray. 2018. Consumer acceptance of cisgenic food and the impact of information and status quo. Food Quality and Preference 69: 44-52. https://doi.org/10.1016/j.foodqual.2018.04.007
Frewer, L.J, I.A. van der Lans, A.R. Fischer, M.J. Reinders, D. Menozzi, X. Zhang, I. van den Berg and K.L. Zimmermann. 2013. Public perceptions of agri-food applications of genetic modification – a systematic review and meta-analysis. Trends in Food Science and Technology 30(2): 142-152. https://doi.org/10.1016/j.tifs.2013.01.003
Gao, Z. and T.C. Schroeder. 2009a. Effects of label information on consumer willingness-to-pay for food attributes. American Journal of Agricultural Economics 91(3): 795-809.
Gao, Z. and T.C. Schroeder. 2009b. Consumer responses to new food quality information: are some consumers more sensitive than others? Agricultural Economics 40(3): 339-346.
Gao, Z., X. Yu, C. Li and B.R. McFadden. 2019. The interaction between country of origin and genetically modified orange juice in urban China. Food Quality and Preference 71: 475-484. https://doi.org/10.1016/j.foodqual.2018.03.016
Globus, R. and U. Qimron. 2018. A technological and regulatory outlook on CRISPR crop editing. Journal of Cellular Biochemistry 119(2): 1291-1298.
Greene, W.H. 2012. Econometric analysis. 7th edition, Prentice Hall, Hoboken, NJ, USA.
Harrison, R., S. Boccaletti and L.A. House. 2004. Comparison of the risk perceptions of Italian and United States consumers for GMO foods. Paper presented at the 14th International Food and Agribusiness Management Association. Annual World Food and Agribusiness Symposium and Forum, College Station, TX, USA.
Heng, Y., S. Yoon and L.A. House. 2021. Explore consumers’ willingness to purchase biotechnology produced fruit: an international study. Sustainability 13(22): 12882.
Hu, Y., L.A. House and Z. Gao. 2022. How do consumers respond to labels for crispr (gene-editing)? Food Policy, 112: 102366. https://doi.org/10.1016/j.foodpol.2022.102366
Huffman, W.E. 2011. Consumer acceptance of genetically modified foods: traits, labels, and diverse information. Transgenic horticultural crops: challenges and opportunities 2010: 193-218.
Huffman, W. and J. McCluskey. 2017. Food labels, information, and trade in GMOs. Journal of Agricultural and Food Industrial Organization 15(1). https://doi.org/10.1515/jafio-2016-0038
Johnston, R.J., K.J. Boyle, W. Adamowicz, J. Bennett, R. Brouwer, T.A. Cameron and C.A. Vossler. 2017. Contemporary guidance for stated preference studies. Journal of the Association of Environmental and Resource Economists 4(2): 319-405.
Khachatryan, H., D.H. Suh, G. Zhou and M. Dukes. 2017. Sustainable urban landscaping: consumer preferences and willingness to pay for turfgrass fertilizers. Canadian Journal of Agricultural Economics 65(3): 385-407. https://doi.org/10.1111/cjag.12129
Krinsky, I. and A. Robb. 1986. On approximating the statistical properties of elasticities. The Review of Economics and Statistics 68(4): 715-719.
Lang, J.T. and W.K. Hallman. 2005. Who does the public trust? The case of genetically modified food in the United States. Risk Analysis 25(5): 1241-1252.
Loureiro, M.L. and M. Bugbee. 2005. Enhanced GM foods: are consumers ready to pay for the potential benefits of biotechnology? Journal of Consumer Affairs 39(1): 52-70.
Lucht, J.M. 2015. Public acceptance of plant biotechnology and GM crops. Viruses 7: 4254-4281. doi:10.3390/v7082819
Lusk, J.L., L.A. House, C. Valli, S.R. Jaeger, M. Moore, J.L. Morrow and W.B. Traill. 2004. Effect of information about benefits of biotechnology on consumer acceptance of genetically modified food: evidence from experimental auctions in the United States, England, and France. European Review of Agriculture Economics 31(2): 179-204. https://doi.org/10.1093/erae/31.2.179
Lusk, J.L., M. Jamal, L. Kurlander, M. Roucan and L. Taulman. 2005. A meta-analysis of genetically modified food valuation studies. Journal of Agricultural and Resource Economics 30(1): 28-44. https://doi.org/10.2307/40987259
Lusk, J.L., B.R. McFadden and N. Wilson. 2018. Do consumers care how a genetically engineered food was created or who created it? Food Policy 78: 81-90. https://doi.org/10.1016/j.foodpol.2018.02.007
McFadden, J.R. and W.E. Huffman. 2017. Willingness-to-pay for natural, organic, and conventional foods: the effects of information and meaningful labels. Food Policy 68: 214-232.
Moon, W. and S.K. Balasubramanian. 2003. Willingness to pay for non-biotech foods in the US and UK. Journal of Consumer Affairs 37(2): 317-339. https://doi.org/10.1111/j.1745-6606.2003.tb00456.x
Muringai, V., X. Fan and E. Goddard. 2020. Canadian consumer acceptance of gene-edited versus genetically modified potatoes: a choice experiment approach. Canadian Journal of Agricultural Economics, 68(1): 47-63. https://doi.org/10.1111/cjag.12221
National Academies of Sciences, Engineering, and Medicine. 2016. Genetically engineered crops: experiences and prospects. The National Academies Press. https://doi.org/10.17226/23395
Noussair, C., S. Robin and B. Ruffieux. 2004. Do consumers really refuse to buy genetically modified food? Economic Journal 114(492): 102-120. https://doi.org/10.1046/j.0013-0133.2003.00179.x
Oehlmann, M. and J. Meyerhoff. 2017. Stated preferences towards renewable energy alternatives in Germany – do the consequentiality of the survey and trust in institutions matter? Journal of Environmental Economics and Policy 6(1): 1-16.
Rose, K.M., E.L. Howell, L.Y.F. Su, M.A. Xenos, D. Brossard and D.A. Scheufele. 2019. Distinguishing scientific knowledge: the impact of different measures of knowledge on genetically modified food attitudes. Public Understanding of Science 28(4): 449-467. https://doi.org/10.1177/0963662518824837
Siegrist, M. 1999. A causal model explaining the perception and acceptance of gene technology. Journal of Applied Social Psychology 29(10): 2093-2106. https://doi.org/10.1111/j.1559-1816.1999.tb02297.x
Siegrist, M. 2003. Perception of gene technology, and food risks: results of a survey in Switzerland. Journal of Risk Research 6(1): 45-60. https://doi.org/10.1080/1366987032000047798.
Siegrist, M., M. Connor and C. Keller. 2012. Trust, confidence, procedural fairness, outcome fairness, moral conviction, and the acceptance of GM field experiments. Risk Analysis 32(8): 1394-1403. https://doi.org/10.1111/j.1539-6924.2011.01739.x
Spendrup, S., D. Eriksson and F. Fernqvist. 2021. Swedish consumers´ attitudes and values to genetic modification and conventional plant breeding – the case of fruit and vegetables. GM Crops & Food 12(1): 342-360. https://doi:10.1080/21645698.2021.1921544
Train, K.E. 2009. Discrete choice methods with simulation. Cambridge University Press.
USDA Foreign Agricultural Service. 2017. Citrus: world markets and trade. USDA Foreign Agricultural Service.
USDA Foreign Agricultural Service. 2021. Citrus: world markets and trade. USDA Foreign Agricultural Service.
Wang, T., H. Zhang and H. Zhu. 2019. CRISPR technology is revolutionizing the improvement of tomato and other fruit crops. Horticulture Research 6: 77.
Xie, J., K. Hyeyoung and L.A. House. 2013. Valuing information on GM foods in the presence of country-of-origin labels. International European forum on system dynamics and innovation in food networks 4(3): 96-109. https://doi.org/10.18461/pfsd.2013
Zhang, X. and H. Khachatryan. 2021. Effects of perceived economic contributions on individual preferences for environmentally friendly residential landscapes. Land use policy 101: 105-125.
Zilberman, D., T.G. Holland, and I. Trilnick. 2018. Agricultural GMOs – What we know and where scientists disagree. Sustainability 10(5): 1514. https://doi.org/10.3390/su10051514
