EcoPremium or EcoPenalty? Ecolabels, quality and knowledge in the organic wine market (working paper March 2011) Magali Delmas (UCLA) Neil Lessem (UCLA) Abstract Eco‐labels are intended to signal to consumers the environmental attributes of a product and thereby elicit increased demand for products perceived as environmentally favorable. This eco‐product price premium is essential to defray the higher cost of improved environmental management practices. However a profusion of eco‐labels can confuse consumers over their meaning, eroding or destroying the eco‐label premium. In our study we examine two similar eco‐labels, one associated with a potential quality reduction and the other not. We show that quality concerns over one eco‐label are transferred onto another by consumers who are unaware of the difference between the two labels. This results in an eco‐label penalty for high price, high quality products of both types. This eco‐label penalty is absent amongst consumers who understand the difference between the two label types. In the context of the wine industry we show that even though environmentally minded consumers have a preference for eco‐labeled wine, they associate it with low quality and will not buy higher priced eco‐labeled wine. This goes for both organic wine which can be of a lower quality and wine made from organic grapes which is not. This incorrect eco‐penalty on wine made from organic grapes does not hold for the minority of consumers who are aware of the difference. Keywords: organic wine, eco‐label, eco‐premium, Discrete choice analysis; Wine choice behavior
1. Introduction Eco‐labels are parts of a new wave of environmental policies that emphasize information provision to elicit more cost‐effective private market and legal forces (Delmas, Montes, & Shimshack, 2009). Eco‐labels signal to consumers the environmental attributes of a product. The goal of eco‐labels is to provide easily interpretable information and thereby elicit increased demand for products perceived as environmentally favorable. Examples of eco‐labels include the organic label for agricultural products, the Energy Star label for energy appliances, and the Forest Sustainable Stewardship label for lumber. The value of eco‐products on the market and the number of new eco‐label programs are growing rapidly. For example, retail sales of organic foods increased from US$3.8 billion in 1997 to US$26.6 billion in 2010 (Organic Trade Association, 2010). The number of eco‐label programs has grown from a mere dozen worldwide in the 1990s to more than 377 programs today (see www.ecolabelindex.com). One of the conditions for effective eco‐labels is that customers be willing to pay a price premium that helps defray the higher cost of improved environmental management practices. However, circumstances under which eco‐labels can command price premiums are not fully understood. Many previous studies use contingent values regarding the hypothetical purchase of eco‐labeled products rather than actual or simulated purchases (Leire & Thidell, 2005; Loureiro & Lotade, 2005). Looking at the wine industry in particular, Delmas and Grant (2010) conduct a hedonic analysis of wine price on wine characteristics (including quality) and find that within their wine sample, eco‐labeled wines do not command a price premium. This raises an interesting puzzle – if consumers are willing to pay premiums for eco‐labeled products, why does this not extend to the wine industry? We propose a simple model of wine choice where environmentally minded consumers prefer eco‐labeled wines, but also have perceptions over the quality of such wines. Consumers making a choice over wine, make quality inferences based on the price of the wine, the appellation, the brand name and the eco‐label. In the US there are two predominant eco‐labels for wine: “made from organic grapes” and “organic”.1 Wine made from organic grapes is wine made from grapes that have been grown without pesticides. Organic wine is also made with organic grapes but prohibits sulfite use in the wine‐making process. This distinction is important because sulfites affect the quality of the wine. Sulfites act as a preservative. Eliminating sulfites can reduce the quality of the wine because the wine is not as stable and cannot be kept very long. There is no such problem for wine made from organically grown grapes, which constitute the vast majority of eco‐certified wines because sulfites are used in the wine‐making process. Unfortunately, most consumers are unaware of this distinction (Delmas 2008), and perceive all eco‐labeled wines to be of lower quality. In our model eco‐conscious consumers have to balance out their desire for organic products versus this quality tradeoff. We then test this model using a discrete choice exercise, where almost 900 survey respondents 1 There is also the privately administered “Biodynamic” eco‐label, administered by the Demeter Association. This standard is less common and so we omit it from our analysis
from across the United States make repeated hypothetical purchase choices over different groupings of wine bottles. To simulate a real‐world setting, wine bottles are represented graphically and respondents have the option of choosing to purchase none of the wines shown. Unlike the real world however, we are able to randomly vary price, region, brand name and organic certification in a manner that allows us to identify consumer preferences over wine attributes. This was combined with a survey that allows us to control for attitudes, demographics and behavior. We evaluate this using a mixed logit model that allows us to combine both product and individual attributes into the choice decision. We find that consumers prefer eco‐labeled wines at low prices and non‐eco‐labeled wines at higher prices. This is consistent with a model where eco‐labels are valued, but obscure the quality‐signal given by wine price. This eco‐label versus quality tradeoff should only be applicable to organic wines, not wine made with organic grapes. However, most consumers are unaware of the difference between the two. When we split the sample into those who are informed of the difference and those who are not, we obtain telling results. Uninformed consumers treat organic wine and wine made with organic grapes identically, whereas informed consumers (who are a minority group) act very differently – treating wine made with organic grapes the same as non‐organic wine. These results shed light on the wine eco‐premium puzzle: environmentally friendly consumers are willing to pay a premium for eco‐labeled wine. But they also are aware of the eco‐label quality tradeoff. This has important policy implications in terms of how eco‐labels are utilized. Firstly, makers of organic wines need to find additional credible methods of communicating quality on their wine labels. Secondly and more importantly misinformation threatens to destroy the potential market for high quality wine made with organically grown grapes, since for the most part consumers are unwilling to buy expensive wines of this type. Reacting retroactively to this problem, the only solution is public education to inform consumers of the difference in eco‐label types. Looking at a more general pro‐active prescription for eco‐labels, policy makers need to make sure that eco‐labels are clear and informative. To do this, policy makers should minimize eco‐label categories, to avoid confusion across types. Finally, they need to ensure that the eco‐label is associated with a price‐premium that outweighs any quality concerns to ensure that the eco‐standard is financially sustainable amongst producers. The remainder of the paper proceeds as follows. In the Eco‐Premium versus Eco‐Penalty section we discuss eco‐labeling and how it pertains to the wine industry followed by an examination of why such labels can generate price premiums or penalties amongst consumers. In the Model section we present a model of wine choice, where consumers choose amongst unknown brands. In the Survey section we discuss the online survey and discrete choice exercise and some of the descriptive statistics thereof. In the Econometric section we present the mixed logit model that we use to evaluate the model. In the Results section we present our empirical estimation results. We conclude the paper with a Discussion and Conclusion Section.
2. EcoPremium versus EcoPenalty 2.1.
Ecolabeling in the wine industry
Green products are credence goods; consumers cannot ascertain their environmental qualities during purchase or use. Customers are not present during the production process of the product and therefore cannot observe environmental friendliness of production. The objective of eco‐labels is to reduce information asymmetry between the producer of green products and consumers by providing credible information related to the environmental attributes of the product and to signal that the product is superior in this regard to a non‐labeled product (Crespi & Marette, 2005). The implicit goal of eco‐labels is to prompt informed purchasing choices by environmentally responsible consumers (Leire & Thidell, 2005, p. 1062). Although the goal of eco‐labels is to reduce information asymmetry between the producer and the consumer regarding the environmental attributes of a product, the lack of credibility or the lack of understanding of some eco‐labels might lead to consumer confusion or even negative reactions toward eco‐labels (Delmas, 2008; Hamilton & Zimmerman, 2006; Ibanez & Grolleau, 2008; Mason, 2006). As Weil et al. (2006) have shown in the context of information policies, whether and how information is used depends on its incorporation into complex chains of comprehension, action, and response. For example, the presence of competing eco‐labels might lead to consumer confusion (Leire & Thidell, 2005). In addition, because it is often difficult to identify with accuracy the true attributes of product environmental impacts, the credibility of the eco‐labeling process is important to facilitate consumer choices of green products (Mason, 2006). In some cases, eco‐labels are issued by independent organizations that have developed transparent environmental criteria and are third‐party verified. In other cases, eco‐labels just represent claims made by manufacturers related to some environmental friendliness (Cason & Gangadharan, 2002; Ibanez & Grolleau, 2008; Kirchhoff, 2000)2. The presence of the second type of eco‐label may produce some confusion in the mind of consumers over the credibility of eco‐labels. These unsubstantiated claims can result in adverse selection if some producers provide false or misleading labeling about environmental attributes and underlying production practices, causing consumers to choose products that do not in fact have the attributes implied by the label (Grodsky, 1993; Hamilton & Zimmerman, 2006; Ibanez & Grolleau, 2008). For example, in April 2007, the U.S. Organic Consumers Association launched a boycott of two leading U.S.‐based organic brands Aurora and Horizon for mislabeling products “USDA Organic” when milk was coming from factory farms. 3 As a result, eco‐labels with confusing or non‐credible messages might affect negatively the reputation of companies that carry them. Such eco‐labels can also indirectly damage the reputation of companies adopting other more credible but related labels. As we will describe with the case of wine eco‐labels, a lack of 2 Ibanez and Grolleau (2008) suggest three dimensions that distinguish eco‐labels: (a) the way the standard underlying the eco‐label is defined, (b) the way the claim is verified, and (c) the way it is signaled to consumers. Kirchhoff (2000) distinguishes endogenous labeling issued by the company itself from exogenous or third‐party labeling provided by an independent labeling authority. 3 (http://www.ethicalconsumer.org/Boycotts/currentUK boycotts.aspx).
understanding of the production process of eco‐labeled wines could lead to confusion about the quality of the product and might deter some consumers from purchasing eco‐labeled wines. In the wine industry, there are several competing eco‐labels related to organic certification and to biodynamic certification that are still not well recognized and understood by consumers. Organic certification follows the U.S. National Organic farming standard, which defines a farming method prohibiting the use of additives or alterations to the natural seed, plant, or animal including, but not limited to, pesticides, chemicals, or genetic modification.4 In addition, labeling standards were created based on the percentage of organic ingredients in the product: • Organic labeled products must consist of at least 95% organically produced ingredients and may display the USDA Organic seal. • Made with organic ingredients labeled products are those that contain at least 70% organic ingredients.5 Looking specifically at wine, the USDA has two eco‐label standards: “wine made from organically grown grapes” and “organic wine.” Wine made from organic grapes is wine made from grapes that have been grown without pesticides. Organic wine is also made with organic grapes but prohibits sulfite use in the wine‐making process.6 This distinction is important because sulfites affect the quality of the wine. Sulfites act as a preservative. Eliminating sulfites can reduce the quality of the wine because the wine is not as stable and cannot be kept very long. There is no such problem for wine made from organically grown grapes, which constitute the vast majority of eco‐certified wines because sulfites are used in the wine‐making process. In addition to the two USDA eco‐label categories, a third privately administered category also exists – biodynamic. Biodynamic agriculture is a method made popular by Austrian scientist and philosopher Rudolf Steiner in the early 1920s. Often compared to organic agriculture, biodynamic farming is different in a few distinct ways. Biodynamic farming prohibits synthetic pesticides and fertilizers in the same manner as certified organic farming. However, whereas organic farming methods focus on eliminating pesticides, growth hormones, and other additives for the benefit of human health, biodynamic farming emphasizes creating a 4 The U.S. National Organic Standards law was passed in 2001. Regulations require organic products and operations to
be certified by a U.S. Department of Agriculture (USDA)–accredited entity to assure consumers that products marketed as organic meet consistent, uniform minimum standards.
5 The principal display panel can list up to three organic ingredients or food groups; however, the USDA seal cannot be
used anywhere on the package.
As wine harvesting and production requires specific handling and processing methods, the USDA developed explicit regulations regarding sulfite use for organic wine and other alcoholic beverages. Sulfites are a natural byproduct of fermentation and are often added to wine for preservation purposes. Added sulfites are prohibited in 100% organic wines and in organic wines (95% organic) and are regulated by 7 CFR 205.605 in wines made with organic ingredients. According to the USDA’s National Organic Program, an organic wine has been defined as “a wine made from organically grown grapes and without any added sulfites.”
self‐sufficient and healthy ecosystem. In 1928, the Demeter Association was founded in Europe to support and promote biodynamic agriculture. The United States Demeter Association certified its first biodynamic farm in 1982. 7 In addition to the vineyard agricultural requirements, Demeter provides a separate set of wine‐making standards for biodynamic wine. Since very few California wines are biodynamically certified, we omit this category from our analysis.
Wine ecopremium drivers
Green products have been defined as “impure public good” because they yield both public and private benefits (Cornes & Sandler, 1996; Ferraro, Uchida, & Conrad, 2005; Kotchen, 2006). They consist of a private good, such as the pleasure of drinking wine, jointly produced with a public good, like biodiversity protection due to organic farming. On the private good side, consumers may buy eco‐labeled wine for the perceived health benefits. Organically grown grapes are free from pesticides and other potentially harmful chemicals. Organically produced wines have no added sulfites.8 Organic wines have no added sulfites. Sulfites in wine have long been associated with various health problems such as asthma (Valley & Thompson 2001) and nasal blockages (Anderson et al 2009). Emerging research indicates that consumers are more likely to purchase green products if the certified practices provide them additional private benefits. For example, Magnusson, Arvola, Koivisto Hursti, Aberg, and Sjoden (2001) found that the most important purchase criteria for organic products were related to quality rather than the environmental attribute. These include criteria such as “taste better” and “longer shelf‐life.” Miles and Frewer (2001) reported that organic foods were viewed as healthier than conventional products. Several other studies showed that health concerns were a major reason, along with environmental concerns, why people choose organic food products (Davies, Titterington, & Cochrane, 1995; Tregear, Dent, & McGregor, 1994; Wandel, 1994; Wandel & Bugge, 1997). On the public good side, we might envisage that organic certification may appeal to the altruistic values of environmentally aware consumers who would like to promote sustainable agriculture. Altruistic customers may want to purchase eco‐wine as a substitute for donations to an environmental organization (Kotchen, 2005). The traditional account given for pro‐social actions (as opposed to pro‐self) is “warm glow” altruism, whereby people get a pleasant feeling or “warm glow” from altruistic activity (Andreoni 1990). Warm glow altruism has been shown to be a significant motivator of eco‐consumption amongst environmentally minded consumers (Clarke et al, 2003; Kotchen & Moore, 2007; Kahn & Vaughn, 2009). If the pro‐social behavior takes place in the public realm, people may also engage in altruistic order to gain a positive 7 To achieve Demeter certification, a vineyard must adhere to requirements concerning agronomic guidelines,
greenhouse management, structural components, livestock guidelines, and postharvest handling and processing procedures. See Demeter USA Web site: www.demeter‐usa.org (2006). 8 All wine contains some sulfites as part of the natural fermentation process
reputation as a pro‐socially minded individual. In the realm of green products, “conspicuous conservation”, has been shown to be a significant motivator of conspicuously environmentally friendly products (Griskevicus et al, 2010; Lessem & Vaughn, 2011). In conclusion, consumers may be willing to pay a premium for eco‐labels if they perceive there to be private health benefits, if they are environmentally minded, or if they can conspicuously consume the good in the public realm.
Wine quality and ecopenalty
Organic wine may deliver private benefits in terms of health, but for the most part it will offer less private benefits in terms of diminished quality. This is because organic wine prohibits sulfite use in the wine‐making process. Eliminating sulfites can reduce the quality of the wine because the wine is not as stable and cannot be kept very long. There is no such problem for wine made from organically grown grapes. However, consumers may not recognize the difference between the two eco‐labels. In our survey of 940 respondents, we find that even though 82% of respondents were familiar with “organic wine” and 54% had knowledge that they had tasted organic wine, only 33% were familiar with the difference between organic wine and organically grown grapes. Similar results were obtained in a survey of consumer attitudes towards organic and biodynamic wines conducted at the University of California (UC), Santa Barbara in 2006 (Delmas 2008). Because the distinction between organic wine and wine made from organic grapes is not readily known, people might associate both with lower quality. In addition, consumers may associate both of the USDA eco‐labels with biodynamic wine. In the same survey mentioned above, Delmas (2008) found that few respondents actually understood what the term biodynamic meant, and most (77%) had an initial negative reaction to the term9. This negative association in the minds of consumers could be carried over to wine eco‐labels in general. Finally because some of the early generations of eco‐labeled products were associated with lower quality products, some consumers might still associate eco‐labels with lower quality products and be reluctant to purchase them (Galarraga Gallastegui, 2002; Peattie & Crane, 2005).
9 Before being presented with any information about biodynamic farming practices, individuals were asked what word came to mind about “wine from biodynamically grown grapes.” Among the respondents who had never heard of wine from biodynamically grown grapes, the single most common response was related to genetic engineering or genetic modification of the grapes (Delmas, 2008).
3. A Model of Wine Choice Imagine a consumer going to a store and having to choose from a number of bottles of wine they have never seen or tried before. They do not recognise any of the brands, nor have they read reviews on any of the bottles. For many wine consumers this is the exact scenario they face every time they buy a bottle of wine (Chaney, 2000)10. These consumers will make a decision based on a combination of price and the bottle’s label, which will have both information about the wine and an aesthetic appeal. The utility that such a consumer expects to obtain from a bottle of wine will depend on the wine’s quality and its price. If the consumer is “green” they will get added utility if the wine is organic. Thus the utility for consumer i of bottle j is: U ij = γ i ∗ O j + q j − α i p j where: O j is a dummy for organic
p j is the price of the bottle.
α i is a measure of price sensitivity γ i is an indicator for green consumer. If the consumer is green then γ i > 0 , otherwise γ i = 0. q j is the quality of the wine
To make a decision the consumer will need to make an inference about the quality of the wine from its label. To simplify our analysis, we abstract away from wine descriptions and differentiated label aesthetics, and focus purely on price, eco‐label and region. Region refers to the region where the wine was produced, otherwise known as the appelation. Numerous studies find region to be a significant indicator of quality and price (Bombrun & Sumner, 2001; Ling & Lockshin, 2003). Thus expected wine quality qj will be: q j = q − βO j + f ( p j ) + λ j r j 10 Chaney found that consumers undertook very little external search prior to entering a store to purchase wine, with point of sale materials and wine labels ranking as the two most important information sources
where: β enters in negatively, since organic wine is perceived as being of lower quality p j is a signal of quality, but this signal diminishes with price, so that f ' ( p j ) > 0 and f '' ( p j ) < 0.
r j is a regional dummy λ j is premium or discount Price has been shown to be a reliable indicator of quality (Bombrun & Sumner, 2001; Delmas & Grant 2010).11 We are interested in the case, where at low enough prices, the increased quality from a change in price outweighs the disutilty of having to pay the price. Thus we restrict the model so that f ' ( p j ) > α i ∀p j < p i . This assumption essentially says that there are decreasing marginal quality returns to price, which seems intuitively reasonable when one thinks of an increasing marginal cost curve. We are also interested in positive eco‐label premiums thus we will assume that for the segment of the market that we label green γ i > β Substituting quality into our utility function we get: U ij = (γ i − β ) ∗ O j + f ( p j ) − α i p j + λ j r j Since organic enters into the utility function linearly, this model predicts that those whose taste for organic produce outweighs the quality signal will prefer to buy organic regardless of the price. This is shown graphically in figure 1.
In the additive model we assumed that organic effects quality equally at every price level. However, there are numerous situations where organic may dilute the price‐quality signal. For example if organic farming and production increase costs, this will be reflected in a higher price. Or if ecolabels do collect a price premium (amongst wine drinkers unaware of quality differences), this will increase price withouth a change in quality. To reflect this, we can interact organic with price, such that:
11 If price is an indicator of quality, one may be inclined to think that profit motivated wine producers can produce low quality wines under a variety of labels and sell them over and over again to unknowing consumers at high prices. This would perhaps be possible if consumers purchased wine directly from the producers. However, most consumers buy their wine from third parties such as wine stores or supermarkets, who will have specialized wine buyers who decide whether the wine is price‐bracket appropriate.
Figure 1: Additive model of utility
Figure 2: Multiplicative Model of Utility Utility
q j = q − βO j + f ( p j ) − βO j ∗ f ( p j ) + λ j r j Therefore : U ij = (γ i − β ) ∗ O j + f ( p j )(1 − βO j ) − α i p j + λ j r j In this multiplicative model, environmental consumers prefer organic at all prices less than ^
pi but prefer non‐organic at all higher prices, where pi : (1− β ) f ' ( p j ) > α i ∀p j < p i . This is illustrated graphically in figure 2, above.
In the models presented above, we assumed that the regional premium was the same whether the wine was organic or not. In reality, the reputation of the region is likely to have an effect on how consumers interpret the quality signal given by the wine being organic. However, it is not clear a priori which direction such an interaction would go in. A prestigious region’s reputation for quality could be so strong that the negative signal given by organic is attenuated. Alternatively, the less prestigious regions reputation could have such a strongly negative signal that organic status matters less relatively. Putting in such an interaction into the multiplicative model yields: U ij = (γ i − β + τ j r j ) ∗ O j + f ( p j )(1 − β O j ) − α i p j + λ j r j Where the sign of τ j is uncertain a priori.
Data on consumer choices, behaviors, attitudes and demographics were collected using an online survey. Preceding the survey was a discrete choice, or choice‐based conjoint (CBC) exercise. CBC is a useful analytic technique for evincing consumer preferences in that it mirrors real‐world choices as closely as possible. CBC is a hypothetical choice exercise, where consumers are shown descriptions or even images of several real or hypothetical products and asked to choose between them. Consumers can also choose not to purchase any of the products on display, again making the exercise more realistic (Louviere et al. 2000). Along with this real‐world functionality, CBC allows the experimenter to randomize across prices and product attributes in a way that is not possible with real‐world data. Moreover, the experimenter can abstract away from extraneous attributes to focus on those most relevant to the study at hand. A very similar experiment is conducted by Lockshin et al (2006) who examine consumer sensitivity to brand, region, price, and awards in wine choice. In our survey, respondents were asked to complete seven choice tasks. In each choice task the respondent was asked to imagine that he/she was attending a seated dinner party with family and friends and needed to choose a bottle of wine to bring along for the occasion. Respondents were then presented with images of four different bottles of wine, each with a different price. The images were truncated to put focus on the wine bottle labels. Subjects were asked to choose which bottle of wine they would purchase, with the option of choosing to purchase none of them. Respondents selected their prefered option by clicking on it. An example of a choice task is shown in figure 2 below. Figure 2: Wine choice task
Attributes used in the experiment
Each bottle of wine had four attributes: brandname, price, type, region. Brandnames were randomly made up using a list of popular French lastnames. None of these names corresponded to existing wine brands. Four different brands were used, Chesnier, Challoner, Rutherfields, and Louis Devere. Prices ranged from $8 to $29 in discrete $7 intervals. These bands were chosen after a brief survey of the wine buying behavior of UCLA Anderson business school faculty and students. Type consisted of organic, made with organic grapes and not organic. Only the organic and made with organic grapes wines were labelled as such. Two Californian wine regions were used: the prestigious and well known Napa Valley and the lesser known and less‐prestigious Lodi. To simplify the analysis, all bottles were of the same varietal ‐ cabernet sauvignon. We selected caberbet sauvignon since it is the leading red wine varietal in US sales of Californian wine (Wine Institute, 2010). We wanted a red wine, since the eco‐label quality tradeoff would be more pronounced than for a white wine since red wines are typically kept longer before drinking.
Choice Experiment Design
Each respondent completed seven choice tasks. Increasing the number of choice tasks faced would have helped to better identify interactions between wine attributes. However, this would have come at the cost of greater attrition, especially since the respondents were unpaid volunteers. Instead, we offered four different versions of the survey, each with its own seven choice tasks and unique attribute combinations. This has the same effect as increasing the number of choice tasks (after we control for individual attributes). Each bottle of wine had one level of each of the four attributes. The levels of the attributes were randomized across the 28 different choice tasks (4x7) using Sawtooth Software’s Choice‐Based Conjoint Software. An algorithm was used to insure each level of each attribute appeared an equal number of times across all surveys, but did not repeat in the wine bottles within each choice task. This was done to make sure that the respondent did not see the same level, (e.g., the same price) across all the choices in one task. With complete randomization there is always the chance that almost identical concepts might appear together. To ensure that the choice set was not dominated by eco‐label wines, we doubled the number of non‐organic wines. Thus every choice set has one organic wine, one made with organic grapes wine and two non‐organic wines.
Survey questions were designed to capture knowledge, behaviors and demographic
information. Respondents were asked whether they knew the difference between organic wine and wine grown with organic grapes. They were asked about their habitual purchasing behavior of both wine and organic products. Finally, they were asked a number of demographic questions including age, gender, education, income and location. The survey questions followed the discrete choice exercise so as to not bias the discrete choice responses. The survey questions are more focused on existing behaviors than attitudes, thus there was less concern about biasing these results.
Research assistance on the survey and conjoint analysis was given by a team of undergraduate students at UCLA. This group of students was integral in both implementing the project and distributing the survey. Flyers advertising the survey were placed in seven wine stores across the greater Los Angeles area and advertisements were placed on Facebook wine interest groups with membership totaling almost 100,000 people. Multiple emails were sent by both the authors and research assistants to professional and social contacts, with 4,845 people directly contacted. These primary contacts were asked to forward the survey to secondary contacts, although quantifiable information on the success of this strategy was not available to the authors. To motivate respondents a case of fine wine was offered as a prize to a randomly drawn completed survey. Respondents were unable to take the survey more than once. Over 1,100 people attempted the survey, and after removing foreign respondents12 and incomplete surveys, we were left with 883 valid responses. Although the majority of responses were centered in Los Angeles County specifically (57 percent) and California in general (82 percent), the remaining respondents were drawn from 31 other U.S. states.
As could be expected given the survey distribution methodology, the survey sample is over‐represented by students. This can be seen in Table 1, below. This results in a lower average age for the sample than the population. The sample is also over represented by college graduates and in particular those with graduate or professional degrees. Given higher education levels, it is unsurprising that the average income in our sample is one third higher than that of the California population. This income‐education bias is possibly alleviated somewhat in that the true wine buying population of California is possibly wealthier and better educated than the population average. Some support for this is given by a 2009 Gallup poll that showed that a small majority of college grads preferred wine over beer, whereas the vast majority of those who did not attend college preferred beer to wine (Gallup 2009). Lockshin et al (2006) similarly find that the wine buying population in Australia is better educated than the general population. The same Gallup poll reported that 65 percent of Americans consumed some alcoholic beverage in the past week, which is comparable to the 65 percent of our sample 12 Foreign respondents were removed since it is uncertain what the dollar purchase prices mean to them
who report drinking wine at least once a week. Table 1: Summary Statistics
Looking further at wine buying behavior, we find that 93 percent of respondents spend less than $30 on average, with the majority (50 percent) spending in the $10 to $20 range. This can be seen in figure 3 (below). These numbers are in line with national averages: the average Californian bottle of wine, sold in the U.S. in 2009, retailed for just under $8. Wines produced in California accounted for 61 percent of the U.S. market by volume in 2009 (Wine Institute, 2010). Both the survey data and the national sales data accord well with the consumer choice exercise, where wines were priced from $8 to $29 in $7 increments. Figure 3: Average Expenditure on a Bottle of Wine Respondents report that on average they purchase organic products one out of every 50 three trips to the grocery store, with 36 percent of respondents purchasing organic products on 40 at least half of store visits. Similarly, about 20 percent of the sample reports being members 30 of an environmental organization. By the nature of the population (young, students) 20 respondents are probably more environmentally friendly or “greener” than 10 average, although it should be noted that green consumerism is an increasingly important trend 0 in the developed world. According to the 0 10 20 30 40+ Expenditure in $10 Increments Organization for Economic Co‐operation and Development (OECD), “27% of consumers in OECD countries can be labeled ‘green consumers’ due to their strong willingness‐to‐pay and strong environmental activism” (OECD, 2005). In the
U.S. retail sales of organic foods increased from US$3.8 billion in 1997 to US$26.6 billion in 2010 (Organic Trade Association, 2010). Finally, one third of respondents know the difference between organic wine and wine made with organic grapes. In conclusion, our sample population is most likely younger, richer, better educated and greener than the California wine buying population. These attributes will however be controlled for in the regression analysis.
5. Econometric Specification We utilize a mixed logit model to analyse our discrete choice experiment data. The mixed logit model allows for both product specific and individual specific attributes and corresponds exactly to the consumer choice data that we generated. Consumer Choice Experiment Each subject was given 7 discrete choice tasks to complete ( C ∈1..7] ). In each task the subject was presented with 4 different bottles of wine, each with a different price. Subjects were asked to choose which bottle of wine they would purchase, with the option of choosing to purchase none of them. No bottles of wine were repeated for a given consumer. The ordering of the discrete choice tasks were randomized across consumers, although within a given choice task the four bottles always appear in the same order (which resulted from an initial randomization). Each bottle of wine is designated W jC , j ∈ [0..4, ], C ∈ [ A..G ], where j = 0 indicates the none option. Each bottle consists of a vector of four attributes, hence W jC = [W jnC,W jpC , W jtC , W jrC ] , where n is name, p is price, t is type and r is region. Utility Maximisation The aim of our econometric specification is to estimate how individual level attributes, product level attributes and the interaction between the two, influence the decision to purchase a particular bottle of wine. The outcome variable yijC , is a dummy variable indicating whether the bottle was purchased or not. Each subject, i has m attributes. These attributes form the vector X i , i ∈ [1..N ]. Thus X i = [
X i1 ,..., X im ]. The interaction between subject and product attributes is Z ijC = vec[W jC' X i ]' The utility subject i gets from bottle j is:
U ij = X i B'X + W jC BW' + Z ijC BZ' + ε ijC = VijC ,V + ε ijC Where
is an individual‐specific taste shock.
Each consumer faces seven choice tasks. In each choice task the consumer chooses between 4 different bottles of wine and the option of no purchase. We normalise the utility from no purchase to zero. A consumer will choose a bottle of wine (or the none option) if it yields a higher utility than the other four choices that are presented. Since there is a random component to utility we can estimate the probability that each of the five options is chosen: so the probability of choosing bottle j, in choice task c is: Pr ( y ijC = 1) = Pr (VijC + −ε ijC ≥ VikC + ε ikC ∀k ≠ j ) = Pr (VijC − VikC ≥ ε ikC − ε ijC ∀k ≠ j )) ~C
Let ε ikj = ε ikC − ε ijC and V ikj = VikC − VijC ~C
Therefore Pr ( y ijC = 1) = Pr (ε ikj ≤ − V ikj ∀k ≠ j ) ~C
If we assume that within choice C, ε ikj is i.i.d and distributed extreme value type 1, we get
Pr ( yijC = 1) =
where we have normalised the utility of the none option to zero so that exp(Vi C0 ) = 1 N
L = ∏ ∏ ∏( The likelihood function is thus: i =1 C =1 j = 0
exp(VijC ) 4
= ∏ ∏ ∏ ( pijC ) i =1 C =1 j = 0
Therefore maximimise: N
Ln( L) = ∑ ∑ ∑ y ln( p ) = ∑ ∑ ∑ y ∗ V − log[∑exp(VikC )] C ij
i =1 C =1 j = 0
i =1 C =1 j = 0
6. Results 6.1.
In the basic specification we pool together organic and organic grapes as ‘eco‐label’ wines. The product characteristics, W jC , we estimate are: W jC = [ price j , brandname j , region j , type j ]
Where: typej= eco‐label, no eco‐label pricej= cubic of price*type regionj= napa dummy*type Individual characteristics, X i , are all allowed to vary across type. The individual characteristics encompass demographics, income, education, wine drinking behavior and environmentalism. To obtain a measure of environmentalism we included the League of Conservation Voters (LCV) environmental rating for each state in 2010. The results from the basic specification are shown in table 2 below:
Table 2: Marginal effects of product and individual characteristics on probability of purchase.
Coefficients on the product characteristics do not vary across choices, except for the coefficents on the price polynomial and Napa. Coefficients on individual characteristics are all choice specific. Eco‐Label No Eco‐Label None Product Characteristics Price 0.138*** 0.0630*** (0.0156) (0.0154) Price squared ‐0.00815*** ‐0.00280*** (0.000959) (0.000903) Price cubed 0.000133*** 0.00003* (0.00002) (0.00002) Rutherfields 0.00195 0.00186 (0.00662) (0.00632) Challoner ‐0.00114 ‐0.00109 (0.00601) (0.00573) Louis Devere 0.00939 0.00896 (0.00664) (0.00633) Napa 0.0864*** 0.162*** (0.00972) (0.0103) Individual Characteristics Male ‐0.00592 0.00382 0.00445 (0.0114) (0.0115) (0.0185) Age 0.00004 ‐0.000833* 0.00155** (0.000479) (0.000468) (0.000625) College Graduate ‐0.0263 0.0293* ‐0.00452 (0.0162) (0.0173) (0.0268) Graduate degree ‐0.0510*** 0.0528*** ‐0.000725 (0.0165) (0.0174) (0.0275) Income ‐0.000461*** 0.000274*** 0.000391** (0.000100) (0.000102) (0.000157) Drinks wine frequently ‐0.0247* 0.0350*** ‐0.0189 (0.0129) (0.0123) (0.0209) Spends on wine ‐0.00348*** 0.00164** 0.00382*** (0.000667) (0.000671) (0.00102) Doesn't buy wine ‐0.115*** ‐0.0787** 0.386*** (0.0320) (0.0392) (0.123) Organic as percent of purchases 0.197*** ‐0.188*** ‐0.0284 (0.0200) (0.0208) (0.0285) Informed ‐0.00848 ‐0.00559 0.0281 (0.0131) (0.0132) (0.0202) Environmental Organization 0.0416*** ‐0.0455*** 0.00545 (0.0137) (0.0131) (0.0201) LCV Score 0.00000 0.000206 ‐0.000399 (0.000281) (0.000296) (0.000421) Observations 6181 6181 6181 *** p<0.01, ** p<0.05, * p<0.1 marginal effects reported unreported coefficents: missing income, missing lcv score
Since price is a cubic polynomial, it is difficult to interpret numerically. However, it is important to note that all of the coefficients on price are significant, and there is a significant difference between the eco‐label and non‐eco‐label coefficients for like terms. Figure 4: Probability of purchasing organic verse non‐organic wine
Purchase Probability .2 .3
Figure 4 (left) gives a graphical representation of the average purchase probability at various prices. As can be seen, eco‐labels are preferred at lower prices, but no eco‐label at higher prices. This is congruent with the multiplicative model presented earlier, whereby the signal from organic attenuates the price‐quality signal. As stated earlier, differences in slopes are statistically significant. In the 8 15 22 29 Price theoretical model differences in the All Organic Not Organic price slope came about from perceptions of quality, however organic also affected the consumer utility directly. In the model we speculated that green consumers would get increased utility from eco‐labeled wine, whereas brown consumers would not. Looking at table 3, we can see that members of an environmental organization are more 4 percentage points more likely to buy a wine if it is organic. Likewise, someone who buys some organic products on every grocery trip is 19 percentage points more likely to buy an eco‐labeled bottle of wine than someone who never purchases organic products. Figure 5 below displays this graphically. If we interpret organic grocery purchases as environmentalism, then our theoretical predictions bear out nicely. Those less environmentally minded get no utility from eco‐labeled wine and only see its negative effect on quality. As environmentalism increases, so does the utility from eco‐labeled wine. Looking at other product characteristics, we can see that the wine brands have no significant effect on choice. This was the intention when designing the survey. The prestigious region Napa always has a large and significantly positive effect on the probability of purchase. However, this Napa premium is cut in half for eco‐label wines. One possible way to interpret this is that organic attenuates the Napa quality signal. In terms of other individual characteristics we can see that having a graduate degree and a higher income both significantly reduce the probability of purchasing organic wine. Those who spend more on wine are also less likely to buy organic and more likely to buy none. This is consistent with some of the comments we received from wine aficionados who felt that the price range we offered was not sufficient.
Figure 5: Probability of purchasing organic verse non‐organic wine by environmental behavior Often Purchases Organic
Occasionally Purchases Organic
Never purchases organic
Price All Organic
Organic wine undergoes a different production process to non‐organic wine often resulting in inferior quality. The same is not true of wine made with organic grapes. This wine undergoes the same production process as non‐organic wine, but is made with a superior quality input – organically grown grapes. Thus it should not suffer from the same quality penalty as organic wines. However, this will only be the case when consumers are actually aware of this difference. We call respondents who know the difference between organic wine and wine made with organic grapes ‘informed’. About one third of the sample is informed. In the specification below, we allow for three types of wine: organic, made with organic grapes and non‐organic. Once again we allow for separate price effects for each type. Our hypothesis is that amongst those who are informed, there will be no attenuation on the price signal for wine made with organic grapes, as is the case with organic wine. To test this, we allow the cubic on price to vary across those who are informed and those who are not for organic and made with organic grapes. The results are shown in table 3, below:
Table 3: Marginal effects of product and individual characteristics on probability of purchase Coefficients on the product characteristics do not vary across choices, except for the coeeficents on price and Napa. Coefficients on individual characteristics are all choice specific. Organic Product Characteristics Price: Informed Price: Uninformed Price squared: informed Price squared: uninformed Price cubed: informed Price cubed: uninformed Rutherfields Challoner Louis Devere Napa Individual Characteristics Male Age College Graduate Graduate degree Income Average zipcode home value Drinks wine frequently Spends on wine Doesn't buy wine Organic as percent of purchases Environmental Organization LCV Score
0.160*** (0.0435) 0.159*** (0.0317) ‐0.00928*** (0.00265) ‐0.00960*** (0.00194) 0.000156*** (0.00005) 0.000161*** (0.00004) 0.00498 (0.00702) ‐0.00217 (0.00634) 0.00766 (0.00679) 0.103*** (0.0132)
Organic Grapes Not Organic 0.0324 (0.0345) 0.148*** (0.0315) ‐0.00119 (0.00210) ‐0.00884*** (0.00195) 0.00001 (0.00004) 0.000142*** (0.00004) 0.00496 (0.00700) ‐0.00216 (0.00634) 0.00764 (0.00678) 0.0654*** (0.0121)
0.0618*** (0.0158) 0.0618*** (0.0158) ‐0.00272*** (0.000926) ‐0.00272*** (0.000926) 0.00003 (0.00002) 0.00003* (0.00002) 0.00486 (0.00687) ‐0.00212 (0.00620) 0.00748 (0.00663) 0.165*** (0.0104)
‐0.00259 ‐0.00899 0.00362 0.00456 (0.0150) (0.0161) (0.0118) (0.0188) ‐0.00110 0.00114* ‐0.000840* 0.00158** (0.000701) (0.000661) (0.000478) (0.000633) ‐0.00615 ‐0.0462** 0.0296* ‐0.00502 (0.0234) (0.0234) (0.0176) (0.0271) ‐0.0270 ‐0.0748*** 0.0532*** ‐0.00137 (0.0228) (0.0241) (0.0177) (0.0278) ‐0.000347*** ‐0.000587*** 0.000278*** 0.000395** (0.000132) (0.000134) (0.000104) (0.000160) ‐0.0324* ‐0.0181 0.0360*** ‐0.0193 (0.0181) (0.0171) (0.0126) (0.0212) ‐0.00428*** ‐0.00272*** 0.00163** 0.00384*** (0.000983) (0.000839) (0.000683) (0.00103) ‐0.124*** ‐0.106** ‐0.0815** 0.388*** (0.0346) (0.0430) (0.0401) (0.123) 0.176*** 0.222*** ‐0.191*** ‐0.0278 (0.0248) (0.0263) (0.0213) (0.0289) ‐0.223 0.506* ‐0.128 ‐0.0348 (0.196) (0.260) (0.0844) (0.0434) 0.0667*** 0.0191 ‐0.0471*** 0.00537 (0.0200) (0.0185) (0.0133) (0.0204) ‐0.000168 0.000118 0.000232 ‐0.000399 (0.000430) (0.000354) (0.000302) (0.000428) 6181 6181 6181 6181
Observations *** p<0.01, ** p<0.05, * p<0.1 marginal effects reported unreported coefficents: missing income, missing lcv score
Empirically we find some important differences between informed and ignorant respondents: For informed: • Price coefficients are statistically significantly different between organic and made with organic grapes • Price coefficients are statistically indistinguishable between made with organic grapes and non‐organic For ignorant: • Price coefficients are statistically indistinguishable between organic and made with organic grapes • Price coefficients are statistically significantly different between made with organic grapes and non‐organic This is displayed graphically in figure 6 below. Figure 6: Probability of purchasing organic wine, wine made with organic grapes and non‐organic wine Informed
.4 .2 0
Price Organic Not Organic
Thus consumers who know that wine made with organic grapes is produced in the same fashion as non‐organic wine do not put a quality penalty on wine made with organic grapes. Consumers who are unaware of this tend to treat organic wine and wine made with organic grapes similarly, imposing a perceived quality penalty on both.
7. Reputation Both the model that we presented and the discrete choice exercise are over wines that are unknown to the consumer. Previous discrete choice exercises such as Lockshin et al (2007) have focused on real, recognizable brand names. Since a discrete choice exercise generates wines with random attributes, this can be confusing to consumers familiar with the brands and they may make suppositions over attributes based on their own knowledge of the brand (e.g. it is an expensive bottle, therefore it must be part of the brand’s reserve collection). Thus we chose to use fictitious brands so as to better be able to infer consumer preferences over our chosen attributes. However brand names do raise a very interesting point when looking at eco‐labels and quality – reputation. Do brands well know for quality products have the capability to credibly introduce organic wine? Or will the poor quality perceptions of an eco‐wine contaminate the brand’s other offerings? Results that we obtain for our regional coefficients are suggestive of an answer to this question. Napa and Lodi appellations act like meta‐brands for all the wines in the region, giving an indication to consumers of quality. Napa is a strong indicator to consumers of quality, and we found that consumers are 16 percentage points more likely to buy a wine from Napa than Lodi (see table 2). Similar to the brand question above, we can ask, will a Napa wine have the credibility to signal that an organic wine is of high quality? In our regressions we find that this is not so. The Napa premium halves when the wine has an eco‐label. In regressions not shown we find that when we run separate price coefficients for Napa and Lodi, the slopes are similar across regions and different from non‐eco‐labeled wine. Thus the Napa brand alone does have the credibility to convince consumers that an eco‐labeled wine is of high quality. This result is likely shared to a greater or lesser extent with individual brands and thus additional credible information such as point of sale materials provided by a disinterested third party.
8. Discussion and Conclusion Eco‐labels act as a signal that goods have been environmentally friendly attributes. If an eco‐label is effective it will command a premium amongst environmentally minded consumers and thus allow manufacturers to recoup the additional costs of cleaner manufacturing practices. This will increase the share of green products in the market (Mason, 2008). However, there are many conditions under which eco‐labels can fail to produce an eco‐premium, even if consumers are willing to pay a premium for eco‐labeled goods. One such scenario is if there is an abundance of similar eco‐labels that confuse consumers. In the wine industry we find that most consumers are unaware of any difference between the eco‐labels “wine made from organic grapes” and “organic wine”. Wine made from organic grapes is wine made from grapes that have been grown without pesticides. Organic wine is also made with organic grapes but prohibits sulfite use in the wine‐making process. This distinction is important because sulfites affect the quality of the wine. Sulfites act as a preservative. Eliminating sulfites can reduce the quality of the wine because the wine is not as stable and cannot be kept very long. There is no such problem for wine made from organically grown grapes. We find that consumers have a
preference for organic wine, but also perceive it to of low quality. This results in the preferring it to non‐organic wines at low prices, but being unwilling to pay for it at higher prices. Even though the majority of eco‐labeled wines are made with organic grapes, consumers for the most part are unaware of any difference between the two and incorrectly associate wine made with organic grapes with low quality. This results in the high end of the market for wines being made with organic grapes being destroyed, since products in this space are essentially unsellable. This highlights the danger of creating unclear eco‐labels or of over‐filling the eco‐label space. The good news for this market is that informed consumers, who are aware of the difference between the two eco‐labels, do not incorrectly infer that wine made with organic grapes is low quality. Thus a remedy exists for this market in terms of education of the wine buying population about the distinction between the two labels. The lessons from the wine industry for other eco‐labeling initiatives are clear. An eco‐label premium is essential for an eco‐industry to sustainably exist. Thus any eco‐labeling initiative needs to ensure that it will deliver such premiums. Failure to do so can risk the viability not just of that eco‐product market, but also of associated markets. Moreover, eco‐labels need to be clearly differentiated to the general public to avoid confusion between standards. In the case of the wine industry we find that quality concerns over one eco‐standard contaminate another. Given limited attention spans by consumers, fewer labels may be better, even if it potentially eliminates classes of organic products. Our study has important policy implications. It shows the dangers of issuing eco‐labels that are misunderstood by consumers and can potentially lead to negative reactions. Our paper indicates that successful implementation of eco‐label programs requires complementary information instruments and complementary skills. Successful eco‐labels are programs with strong emphasis on marketing. This suggests that policy makers invest in marketing knowledge and tools, which were not traditionally part of the environmental policy tool kit.
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