An Open Mind Wants More: Opinion Strength and the Desire for Genetically Modified Food Labeling Policy

Radas, Sonja, Teisl, Mario F., Roe, Brian, The Journal of Consumer Affairs

Two opposing viewpoints exist in the literature; some suggest consumers are unconcerned and do not desire any genetically modified labeling, while others indicate the opposite. The mixed results may be because consumers make finer distinctions than surveys have called for, and have evaluation schemes sensitive to information about the benefits and risks associated with genetically modified foods. We find consumers are quite nuanced in their preferences for genetically modified labeling policy. Unexpectedly, consumers with less-defined views desire mandatory labeling of the most stringent type, while consumers with stronger viewpoints (either pro- or con-genetically modified) are more relaxed in their labeling requirements.

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There are two opposing viewpoints regarding consumers' acceptance of genetically modified (GM) foods and their desire for the labeling of these foods. Industry leaders believe consumers accept these foods because the public shows a willingness to consume them. For example, most milk in the United States is produced with the use of bST hormone, even though bST-free milk is available, clearly labeled, and advertised. In fact, except for recent limited gains, initial sales for bST-free milk were so weak it almost disappeared from the market (Webb 2006). In addition, some national surveys indicate that consumer concerns toward GM foods are low and few individuals desire any GM labeling (IFIC 2007). In contrast, as indicated by Noussair, Robin, and Ruffieux (2004), most of the academic literature indicates people are highly concerned about the GM technology (e.g., Huffman et al. 2002; Loureiro and Bugbee 2005), are willing to pay to avoid GM foods (e.g., McCluskey et al. 2003), and would like to see GM foods labeled (e.g., Teisl et al. 2003a).

One problem is that many GM labeling studies (and potentially some current labeling policies) approach the issue as one where the consumer's sole desire for information about GM foods is whether they are, in fact, genetically modified (Teisl and Caswell 2002). This approach may work well for consumers who have lexicographic preferences where the process of GM production must first be resolved before the consumer considers any other quality attributes (Kaye-Blake, Bicknell, and Saunders 2005). However, because the use of biotechnology in food production can have multidimensional effects on product quality (Caswell 2000), consumers who want to know about some or all of the changes in product attributes may find that such a labeling program provides information that is inadequate, irrelevant, or that impedes their decision making (Roe et al. 2001).

Another problem is that many studies often refer to the GM technology in imprecise terms, whereas consumers appear to be capable of making finer distinctions; hence, it is hard to interpret the attitude levels being reported (Fischhoff and Fischhoff 2001). For example, early willingness-to-pay studies commonly assumed that the genetic modification only provided benefits to consumers by lowering prices; only recently have studies (e.g., O'Connor et al. 2005; Onyango and Govindasamy 2005; Hossain and Onyango 2004) looked at situations where individuals may derive nonprice benefits (e.g., improved nutritional characteristics). In turn, it is not surprising that survey respondents would respond negatively to GM content because new technologies are often viewed as having long-term risks. Indeed, when studies include a GM-related benefit, consumers are often willing to buy these foods (e.g., Boccaletti and Moro 2000; Verdurme, Gellynck, and Viaene 2001; Teisl et al. 2003b).

Because consumer acceptance of GM foods is linked to the perceived risks and benefits of these foods (Boccaletti and Moro 2000; Chen and Li 2007; Curtis and Moeltner 2006; Lusk and Coble 2005; Moon and Balasubramanian 2004; Rosati and Saba 2000; Subrahmanyan and Cheng 2000) and because consumers are heterogeneous in how they weigh these risks and benefits (Kaye-Blake, Bicknell, and Saunders 2005), recent authors have focused on segmenting consumers by how they evaluate GM foods (e.g., Baker and Burnham 2001; Ganiere, Chern, and Hahn 2004; Jan, Fu, and Huang 2007; Kontoleon 2003; O'Connor et al. 2005; Rigby and Burto 2005; Roosen, Thiele, and Hansen 2005; Verdurme, Gellynck, and Viaene 2001; Vermeulen 2004). Although Verdurme and Viaene (2003) segment consumers to examine differences in demand for information about GM foods, to our knowledge no one has examined whether consumers' views on GM labeling policy differs across segments.

Our objective here is to identify if consumers differ in their risk/benefit evaluation of GM foods and how these differences may translate into different preferences for GM labeling policy.

Examining this issue is important both in terms of policy and research. First, with respect to policy, consumers' attitudes toward GM foods appear to be quite sensitive to information about the potential benefits and risks associated with these foods (Brown and Qin 2005; Huffman et al. 2003c, 2007; Lusk et al. 2004), especially when they are uniformed (Huffman et al. 2007); a condition illustrated across countries (e.g., United States: Hallman and Hebden 2005; James 2004; Shanahan, Scheufele, and Lee 2001; Italy: Boccaletti and Moro 2000; Hungary: Banati and Lakner 2006; China: Li et al. 2002; Belgium: Verdurme, Gellynck, and Viaene 2001; Greece: Arvanitoyannis and Krystallis 2005). Because consumer attitudes toward GM foods and the demand for information about these foods are related to how informed the consumer is (Costa-Font and Mossialos 2005), it is likely that preferences for GM labeling are linked to attitudes toward GM foods. Documented consumer heterogeneity in these attitudes suggests that a similar heterogeneity exists in preferences for GM labeling policy. However, because it is difficult for labeling policies to differ across consumers (i.e., labeling policy is practically restricted to "one size fits all"), differences in labeling preferences could lead to conflicts across consumer groups.

In addition to policy concerns, consumer heterogeneity could provide two reasons why the literature is mixed in terms of preferences for GM foods and GM labeling policy. First, as mentioned, consumers appear to be quite sensitive to information about GM foods and possibly to the framing of survey questions (Cormick 2005). For example, many polls and studies are similar by only asking simple yes/no questions about labeling but differ in how they frame the question (Do you want GM foods labeled?; Do you want mandatory labeling of GM foods?; Do you support U.S. Food and Drug Administration's [FDA]s policy of voluntary labeling of GM foods?). It is unclear from the literature whether respondents who are heterogeneous in their preferences toward GM labeling view these questions as asking different things. Second, mixed views on labeling policy could be explained if consumers who are heterogeneous in their preferences for labeling are also likely to differ in how likely they are to respond to a survey. For example, after reviewing twenty-five studies on GM food preferences, Lusk et al. (2005) indicate that a major factor explaining differences in results is the characteristics of the consumer sample.

For all the above reasons, paraphrasing Rigby and Burton (2005), knowing the "average" preference for labeling is less important than understanding how preferences differ across consumer segments and the relative sizes of these segments.

METHOD

During the summer 2002, we administered a mail survey to a nationally representative sample of 5,462 U.S. residents and an additional oversample of Maine (710 individuals) residents. The samples were purchased from a frame maintained by InfoUSA. The InfoUSA database contains information about 250 million U.S. residents (more than 95 percent of U.S. households). The address information is continually updated using the U.S. Postal Service's National Change of Address system, allowing InfoUSA's address list to maintain a 93 percent accuracy rate.

The survey was administered with multiple mailings and with an incentive paid for returned completed surveys (incentives were experimentally manipulated and consisted of either a $1 bill, a $2 bill, a $2 value phone calling card, or a $5 phone calling card; for further information about the incentive scheme, see Teisl, Roe, and Vayda 2006). The oversample of Maine residents was added to provide representative results for Maine state policy makers (the Maine Agriculture and Forest Experiment Station provided some of the funding for this research).

In total, 375 Maine residents and 2,012 U.S. (non-Maine) residents responded to the survey for a response rate of 53 and 37 percent, respectively. The overall response rate of 39 percent is marginal, suggesting that individual survey results may not be a valid representation Of the knowledge, practices, and attitudes of the U.S. adult population. However, our purpose here is not to extrapolate our survey results to the aggregate population but to examine differences in labeling preferences across different types of consumers.

Our survey respondents are slightly older, more educated, and have higher incomes compared to the characteristics of the U.S. adult population (Table 1). Although our sample is more likely to be white, the stated differences in race may be reflective of a true underlying difference and/or may reflect differences in the way the race questions are asked across the two surveys. Specifically, our survey only allows respondents to choose one race from a list of five racial categories, while the U.S. Census allows respondents to choose multiple races from a list of fourteen racial categories. These differences in response categories and instructions could lead to differences in reported racial composition.

The survey instrument consists of questions used to elicit respondents' perceptions of various food technologies, knowledge of the prevalence of GM foods, perceptions of potential benefits and risks of GM foods, reactions to alternative GM labeling programs, and willingness to pay for or avoid GM foods. The content and wording of questions is based upon an analysis of issues raised in the labeling or consumer perception literature (e.g., Boccaletti and Moro 2000; Hallman and Metcalfe 1994; Hoban 1999; Huffman 2003a; Roe et al. 2001; Rousu et al. 2003; Teisl 2003), state and federal policy needs, and previous focus group research (Teisl et al. 2002). Further, they are based upon conceptualizations of consumer reactions to labeling information as presented in Teisl, Bockstael, and Levy (2001) and Teisl and Roe (1998).

As highlighted in the introduction, a reasonable condition for acquiring insight into consumers' attitudes toward the labeling of GM foods is to first gain an understanding of how consumers evaluate the risks and benefits associated with these foods. We then explore how heterogeneous consumers are in their risk/benefits evaluations and segment them into more homogeneous segments. After segmenting consumers and profiling the segments, we investigate their preferences for alternative GM labeling policies.

To gain an understanding of how consumers view the potential risks and benefits of GM foods, we provided respondents with a list of sixteen potential benefits and sixteen potential risks of GM foods and asked them to rate each one on importance. Ratings were coded on a Likert scale where 1 = not at all important, 3 = somewhat important, and 5 = very important. The potential benefits generally accrue to the consumer (e.g., lower food prices), while others accrue to the food producer (e.g., increased disease resistance in crops). The scope of the risks is broader; some primarily concern consumer health risks (e.g., unknown toxins produced), others concern producer risks (e.g., spread of disease resistance to weeds), while others are focused on environmental (e.g., risks to species diversity), social (e.g., control of agriculture by biotechnology companies), or ethical (e.g., ethical issues with genetic modification) problems.

We use factor analysis on the above benefits and risks to find the set of underlying factors influencing consumers' perceptions. Factor analysis is a data reduction technique used to investigate whether a group of variables have common underlying dimensions and can be considered to measure a common factor. Although the analysis can be used to summarize a larger number of variables into a smaller set of constructs, ultimately the analysis is not a hypothesis testing technique so it does not tell us what those constructs are (Hanley et al. 2005). In turn, the validity of naming the constructs is contingent upon researcher judgment and should be interpreted with some caution (Thompson and Daniel 1996).

For the factor analysis, we used principal components analysis followed by varimax rotation. As is typical, factors with eigenvalues less than one are dropped from further analysis as are variables with factor loadings of less than .6 as these are not considered statistically significant for interpretation purposes. To further verify the reliability of the factor analysis, we compute Cronbach's alpha on the original responses, aiming to have alphas greater than the minimum value of .70 suggested …

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Publication information: Article title: An Open Mind Wants More: Opinion Strength and the Desire for Genetically Modified Food Labeling Policy. Contributors: Radas, Sonja - Author, Teisl, Mario F. - Author, Roe, Brian - Author. Journal title: The Journal of Consumer Affairs. Volume: 42. Issue: 3 Publication date: Fall 2008. Page number: 335+. © 2009 American Council on Consumer Interests. COPYRIGHT 2008 Gale Group.

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