How do consumer hedonic ratings for extra virgin olive oil relate to quality ratings by experts and descriptive analysis ratings?

Food Quality and Preference 22 (2011) 213–225

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Food Quality and Preference journal homepage: www.elsevier.com/locate/foodqual

How do consumer hedonic ratings for extra virgin olive oil relate to quality ratings by experts and descriptive analysis ratings? Claudia Delgado, Jean-Xavier Guinard ⇑ Department of Food Science and Technology, University of California, Davis, United States

a r t i c l e

i n f o

Article history: Received 12 May 2010 Received in revised form 24 September 2010 Accepted 22 October 2010 Available online 2 November 2010 Keywords: Consumer preferences Consumer attitudes Sensory properties Extra virgin olive oil Segmentation

a b s t r a c t A consumer study was conducted to evaluate preferences and attitudes regarding extra virgin olive oil (EVOO) in an emergent market, the US. A generic descriptive analysis was used on 22 samples of EVOO in order to identify the drivers of liking for this consumer population. Results showed that, for the majority of consumers, bitterness and pungency were negative drivers of liking. Properties that drove positive ratings were fruity (green and ripe), nutty, and tea-like flavors. A panel of EVOO experts provided quality ratings for the products and these were correlated to the hedonic ratings by consumers, revealing some disconnection between consumer preferences and expert evaluations. Cluster analysis and preference mapping of the consumer hedonic ratings revealed segmentation of preferences. The EVOO’s price, available information, and reputation were key factors that drove purchases in this consumer population. Ó 2010 Elsevier Ltd. All rights reserved.

1. Introduction While olive oil is a staple food for most countries in the Mediterranean region (i.e. Spain, Italy, and Greece), it is a relatively new product in areas outside of it. In the US in particular, however, interest in and consumption of olive oil has been growing exponentially during the last 20 years. The US ranks fourth in olive oil consumption, after Italy, Spain and Greece. US consumption went from 88,000 tons in 1990 to 260,000 tons in 2009, an increase of 228% (International Olive Council, 2008). Despite being the most important market outside the Mediterranean basin (Zampounis, 2006), the US produces less than 1% of the world’s EVOOs, which is not enough to cover domestic demand and leaves imports making up 99% of the oil consumed in the US (Vossen, 2007). New olive oil consumers are interested in olive oil for two main reasons: health benefits and flavor (Santosa, 2010). Because of olive oil’s particular chemical composition and rich supply of antioxidants, consumption has been associated with health benefits such as lowering the risk of coronary decease, preventing certain kinds of cancer, and reducing inflammation (Bendini et al., 2007; Medeiros & Hampton, 2007; Servili et al., 2004; Trichopoulos & Lagiou, 2007; Tripoli et al., 2004). Volatile compounds impart oils’ particular and complex set of aromas, while phenolic compounds provide their bitter and pungent flavors (Andrewes, Bush, Joode, Groenewegen ⇑ Corresponding author. Address: Department of Food Science and Technology, University of California, One Shields Avenue, Davis, CA 95616-8598, United States. Tel.: +1 530 754 8659; fax: +1 530 752 4759. E-mail address: [email protected] (J.-X. Guinard). 0950-3293/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodqual.2010.10.004

& Alexandre, 2003; Angerosa, Mostallino, Basti, & Vito, 2000; Beltrán, Ruano, Jiménez, Uceda, & Aguilera, 2007; García-Mesa, Pereira-Caro, Fernández-Hernández, García-Ortíz Civantos, & Mateos, 2008). Over the past 20 years, there have been numerous attempts to define a methodology for the evaluation of olive oil in terms of its sensory qualities, consumer preferences, and chemical composition, with most of the work being conducted on volatile compounds and their possible relationship to extra virgin olive oil flavor (Aparicio, Morales, & Alonso, 1996; Aparicio, Morales, & Alonso, 1997; Caporale, Policastro, Carlucci, & Monteleone, 2006; Morales, Alonso, Rios, & Aparicio, 1995). Other researchers have explored consumer response to olive oil as a way of measuring quality in terms of customer satisfaction (Krystallis & Ness, 2005; Sandalidou & Baourakis, 2002). Matsatsinis, Grigoroudis, and Samaras (2007) compared responses of distributors and olive oil consumers, and found that perceived quality is important to both segments, with perceived quality defined in terms of sensory properties: taste, aroma, color, appearance, texture, etc. Finotti, Bersani, and Bersani (2007) developed a quality index based on chemical parameters that are related to EVOO’s microbiological/chemical safety, nutritional and technological aspects; however, they did not consider sensory characteristics in their model. More recently, Dekhili and d’Hauteville (2009) have studied the effect of region of origin on EVOO’s perceived quality, measuring perceived quality in terms of the price that a consumer is willing to pay. Despite all these endeavors, no method has yet provided a comprehensive way of examining the drivers of liking and quality in extra virgin olive oil.

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It is not clear what motivates consumers to purchase EVOOs. Some authors emphasize the oil’s region of origin, focusing on the influence of PDO (Protected Denomination Origin) designation and the degree to which an oil typifies the characteristics of the particular region as the main motivators behind consumption. Consumers who are experienced, local, or familiar with a particular region of origin tend to consider region a key factor that drives purchasing and preference, while these factors do not seem to influence urban, less knowledgeable, and less experienced consumers (Caporale et al., 2006; Fotopoulos & Krystallis, 2001; Stefani, Romano, & Cavicchi, 2006). Other authors focus on EVOO’s health benefits and flavor (including its use to enhance the taste of recipes) as main motivators for olive oil consumption, but still second in importance behind packaging, price and size (Krystallis & Ness, 2003; Martínez, Aragonés, & Poole, 2002; Sandalidou & Baourakis, 2002). The applicability of these studies to consumers in the US and other emergent markets is debatable, however, since many of these studies have been conducted in European markets, where European consumers, especially those in the Mediterranean region, have greater exposure to extra virgin olive oil and tend to use it on a daily basis. The present research was intended to uncover the main drivers of liking and disliking among US (Northern California) consumers, and the correlations between consumer hedonic scores, on the one hand, and experts’ quality ratings and descriptive analysis measurements on the other. Experts’ quality ratings were based on well-established, internationally used methodology that was developed by the International Olive Council for establishing the commercial grade (i.e. extra virgin) of the product. However, because olive oil is a growing and relatively new product for many Americans, there is no data showing how expert ratings may influence consumer preferences. Another aim of the research was to discover the factors that motivate the purchase and consumption of olive oil by consumers in an emergent market (the US), and to determine whether there were any relationship between hedonic scores and demographic and usage characteristics. 2. Materials and methods 2.1. Samples Twenty-two commercial extra virgin olive oils (EVOO) were used for this research. Fifty percent of the samples were produced Table 1 Extra virgin olive oils used in this study – country of origin and olive variety. ID #

Country of origin

Variety

S1 S2 C1 C2 I1 I2 I3 I4 A1 GS GI U1 U2 U3 U4 U5 U6 U7 U8 U9 U10 U11

Spain Spain Chile Chile Italy Italy Italy Italy Australia Spain Italy USA (California) USA (California) USA (California) USA (California) USA (California) USA (California) USA (California) USA (California) USA (California) USA (California) USA (California)

Picual Hojiblanca Picual Arbequina Frantoio Taggiasche (Late harvest) Taggiasche Picholino Hojiblanca Generic Brand (Oils from several countries) Generic Brand (Oils from Italy) Arbequina Blend Arbequina/Arbosana/Koroneiki Sevillano Frantoio Mission/Manzanillo/Sevillano/Barouni/ Ascolano Manzanillo/Mission Blend Arbequina Frantoio/Leccino/Pendolino/Coratina Mission

locally, in California (n = 11), and the other 50% were imported. The country of origin and the variety of the olives are shown in Table 1. For the descriptive analysis and expert panels, the samples were served at room temperature (25 °C) in transparent olive oil glasses (Libbey 1965 model, 4 3=4 oz capacity, 2 in diameter, those dimensions corresponds to the glass recommended by the COI Doc.5), with 15 mL of oil poured in each glass, and covered with a transparent plastic lid (Solo Cup model PL2 2-oz). For the consumer test, samples were served at room temperature in soufflés plastic cups (Solo cup model B200) with 10 mL of oil poured in each cup and covered with a transparent plastic lid (Solo Cup model PL2 2-oz). White bread (Classical White Wonder) was provided as a sample carrier. A commercial brand was selected in order to prevent variation in bread taste or quality. In the three experiments (descriptive analysis, experts’ quality ratings, and consumer test) the samples were codified using random 3-digit numbers and poured at least 30 min before the tasting. Water, previously filtered in the Millipore Milli-QÒ water filtration system, slices of granny smith apple and unsalted crackers were provided as palate cleansers. 2.2. Descriptive analysis A panel of 18 judges (14 women and 4 men) with an average age of 29 years for women and 30 years for men was assembled for this study. A generic descriptive analysis (Lawless & Heymann, 1998) was used to develop the language and methodology for the evaluation of extra virgin olive oil. Each panelist completed 10 training sessions (development of the language, concept alignment, agreement). FIZZ software (Biosystèmes) was used to build an automated session. A total of 22 attributes were defined by the panel and were evaluated using a continuous unstructured line scale of 10 cm, ranging from low to high intensity. EVOOs were evaluated in triplicate, with 5 samples evaluated per session. The order of presentation of the samples was randomized using a Latin square design provided by the FIZZ software. More details about the methods can be found in Delgado and Guinard (submitted for publication-a). 2.3. Experts panel and quality rating definition Twenty-three experts drawn from the California Olive Oil Council (COOC) Taste Panel, the University of California’s Extension Panel in Santa Rosa, and the Los Angeles International Olive Oil Competition Taste Panel evaluated sensory quality using a 100points scale, where 0–30 was inedible and 90–100 was excellent quality. The order of presentation of the samples was randomized using a Latin square design provided by the FIZZ software. More details regarding the method can be found in Delgado and Guinard (submitted for publication-b). 2.4. Consumer test Consumers were recruited in supermarkets, at farmers markets, and through internet sources such as the email directory of the University of California, Davis and Craigslist. They were screened according to their consumption patterns and interest in extra virgin olive oil. The FIZZ software was used to construct an automated session. The experimental design was a Williams Latin square design provided by the FIZZ software. The consumer sample size was determined using the Kastenbaum simplification of Tang method which determines sample size (N) from tables for a given values of s, a and b. The value of s is obtained from the following formula (s) = (lmax lmin)/r. In this case a = 0.05 and b = 0.1 (Power of 90%), assuming a standard deviation of 2 and the detectable difference among samples of 1 unit in the 9-point hedonic scale. The value of tau was determined as

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follows: (s) = (lmax lmin)/r = (1)/2 = 0.5. Because of the high number of samples, the 22 samples were evaluated in blocks of 5 samples, so that k was equal to 5. From Table A-8 in Gacula and Singh (1984) the sample size corresponding to those parameters was approximately 100 consumers. The experiment was conducted at the RMI Sensory Building at the University of California, Davis. The study consisted of two sessions. During the first session consumers evaluated a total of 12 samples with a 15-min break taken after every 5 samples, and a 1-min break between each sample. In the second session consumers evaluated 10 samples and completed a brief survey (exit survey) that assessed their attitudes and beliefs about olive oil and collected their demographic information. Both the exit survey and the tasting questionnaire were pretested with a small group of consumers (n = 20) to determine whether all questions were clear, in order to avoid ambiguity and effects from wording. Consumers received a $10 dollar gift card for their participation in the study. 2.4.1. Tasting Different approaches were used to determine the acceptability of the oils among consumers. For each EVOO sample, consumers indicated their overall liking using the 9-point hedonic scale (Peryam & Pilgrim, 1957), their intent to purchase (5-point scale); the price they would be willing to pay for a 375 mL bottle of the product; their willingness to consume the product a second time (5-point scale); their evaluation on a Likert scale (5 points) of the EVOO’s quality, color, taste, aroma, and texture; and the strength of their recommendation of the product (5-point scale). For a description of each scale, see Table 2. 2.4.2. Exit survey: demographics, consumption and attitudes The variables included in the survey were as follows: frequency of olive oil consumption, reasons to consume olive oil, frequency of purchase, places where consumers buy olive oil, categories of olive

oil purchased, factors influencing olive oil purchasing and some attitudes regarding olive oil. Demographics such as gender, age, ethnicity, education level, household income, and marital status were also included. This information was obtained by an internet-based survey posted on Survey Monkey. The questionnaire followed standard guidelines for web-based surveys: it was self-administered, included multiple choice questions, used randomized answers when appropriate, and did not allow consumers to proceed to a new section until they had completed the preceding section. 2.5. Statistical analysis The majority of the statistical analyses were executed using SAS version 9.1 (SAS Institute, Cary NC). The level of confidence was set at alpha equal to 0.05. To measure the relationships among demographic and behavioral information, quality ratings by experts and the sensory properties of the EVOOs, univariate analysis, (correlation, analysis of variance, and Fisher’s LSD multiple mean comparisons), and multivariate analysis such as canonical variate analysis (CVA), MANOVA, and preference mapping, both internal and external, were performed. Market segmentation was determined using preference mapping and cluster analysis. Chi-squared was applied to classify the market segmentation clusters according to variables associated with demographics, attitudes, and habits. Cluster analysis was performed with XL-Stat Version 2009.3.02 (Addinsoft). The Unscrambler version 9.8 (Camo Software) was used to perform partial least square regression (PLS) analysis. 3. Results and discussion A total of 110 consumers completed the study. Most respondents were female (74%), with an average age of 40 years and of White/Caucasian ethnicity (75%). Educational level was distributed mostly across four categories, with 83% having attended college as

Table 2 Description of the scales used by consumers to evaluate each EVOO sample. (a) Nine-point hedonic scale h h Dislike Dislike Very Extremely Much

h Dislike Moderately

h Dislike Slightly

(b) Five-point purchase intent rating scale h h Definitely I would not buy it Probably I would not buy it

(c) Price consumers will pay for the EVOO sample h h h $0 $1–$5 $6–10

h Neither like nor dislike

h Neither would not buy it, nor would buy it

h $11–15

h $16-$20

(d) Five-point repeat consumption scale h h I would certainly not consume this I would probably not consume this EVOO again EVOO again

(e) Facts regarding the product – 5-point Likert scale Strongly disagree This EVOO is of high quality h I like the color of this EVOO h I like the taste of this EVOO h I like the aroma of this EVOO h I like the texture of this EVOO h (f) Recommendation to friends/relatives Not Likely Somewhat Unlikely h h

h Like Slightly

h Not sure or undecided

Somewhat disagree h h h h h

Uncertain h

h Like Moderately

h Like Very Much

h Probably I would buy it

h $21–25

h $26–30

h I would probably consume this EVOO again

Neutral h h h h h

h Definitely I would buy it

h More than $30

h I would certainly consume this EVOO again

Somewhat agree h h h h h

Somewhat Likely h

h Like Extremely

Strongly agree h h h h h

Very Likely h

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the majority of consumers, bitterness and pungency appeared as negative drivers of liking. These results disagree to some extent with the work of Caporale et al. (2006), who found that, from the consumer point of view, bitterness and pungency are appropriate sensory descriptors for certain typical oils; one of the reasons for the discrepancy might be the level of consumer expertise in extra virgin olive oil, with the latter study being conducted with Italian olive oil consumers and with very restrictive criteria (e.g., including only heavy EVOO users who came from a particular region in Italy). As a consequence those consumers might have identified bitterness and pungency more readily as positive qualities than did the consumer population in this study. Given that American consumers are relatively ‘‘new’’ consumers of EVOO, the rejection of bitterness and pungency is a natural reaction, in that poisonous or toxic substances tend to be bitter. Since humans acquire a taste for bitterness and pungency as adults and in response to learning or cultural processes (Drewnowski, 1997; Drewnowski & Gomez-Carneros, 2000; Kim, Breslin, Reed, & Drayna, 2004), consumers in emergent markets may not have enough exposure to the product to have learned to appreciate bitterness

follows: some college (24%), bachelor degree (21%), some graduate work (14%), and master’s degree (24%). Income level was distributed evenly among the optional categories. Marital status showed 39% as single/never married, 21% as married or living with a partner with no children at home, and 25% as married or living with a partner with children at home. Overall liking was significantly correlated to the other variables included in the tasting survey (purchase intent rating; the price they would be willing to pay for the sample; willingness to consume the product a second time; ratings of EVOOs; and recommendation of the product) (Table 3). It was found that acceptability and perceived quality in EVOO by consumers were highly correlated to overall liking, which coincides with previous studies that found that perceived quality by consumers is a function of hedonic ratings (Cardello, 1995; Lawless & Liu, 1997). 3.1. Identification of general drivers of liking in EVOO External preference mapping (see Figs. 1a and b) allows the identification of both positive and negative drivers of liking. For

Table 3 Correlation of overall liking vs. alternative ways to ask for perceived quality by consumers.a,b OL

OL PIR Price C HQ Color Taste Aroma Texture RF

1 0.996 0.987 0.997 0.979 0.603 0.998 0.899 0.975 0.995

PIR

1 0.990 0.997 0.983 0.630 0.994 0.920 0.974 0.997

Price

1 0.988 0.985 0.628 0.985 0.916 0.966 0.987

C

1 0.983 0.599 0.997 0.906 0.972 0.996

Facts regarding the product

RF

HQ

Color

Taste

Aroma

Texture

1 0.689 0.974 0.929 0.978 0.984

1 0.570 0.799 0.687 0.635

1 0.891 0.967 0.993

1 0.895 0.919

1 0.976

a

1

Means over 110 consumers. Refer to Table 1 for a description of the scales. OL, overall liking; PIR, purchase intent rating; Price, expected price to pay for the product; C, willingness to consume of the product for a second time. Facts regarding the product (HQ, This is a high quality EVOO; Color, I like the color of this EVOO; Taste, I like the taste of this EVOO; Aroma, I like the aroma of this EVOO; and Texture, I like the texture of this EVOO). RF, willingness to recommend the product to friends and family members. b All correlation coefficients were significant p < 0.05. Pearson’s critical value (a = 5%; df = 20; two tailed) = 0.4227.

Fig. 1a. External preference mapping for 22 extra virgin olive oils and 22 sensory attributes, using the vector model (dimensions 1 & 2).

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Fig. 1b. External preference mapping for 22 extra virgin olive oils and 22 sensory attributes, using the vector model (dimensions 1 & 3).

Fig. 2. Preference cluster dendrogram (Ward’s method. Euclidean distance n = 110 consumers).

and pungency in olive oil. Similar responses have been obtained in evaluating green vegetables and beers, among others; consumers did not like products that were heavily bitter and/or ranked them as lower in quality than products with less bitterness (Guinard et al., 1996; Bech, Hansen, & Wienberg, 2009). However, bitterness and pungency are naturally present in EVOO, and the compounds associated with these sensory properties are also responsible for some of the health properties of EVOO; consequently, oils lower in bitterness and pungency may have reduced health benefits. Drewnowski and Gomez-Carneros (2000) indicated that in order to increase consumer acceptability

of bitter/pungent food products, some masking agents such as cyclodextrins or other chemical ingredients might need to be added to lessen the perception of those sensory properties while retaining the beneficial health properties, but in the case of EVOO, this is not possible since adding external ingredients would amount to adulteration of the product. However, EVOO might be deemed more acceptable when mixed with other food such as salad or bread and when used for cooking, which is another way of masking the bitterness and pungency. But more importantly, it is likely that increasing consumers’ exposure to EVOO and providing information regarding the association of these properties with high

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sensory quality and health benefits will increase consumers’ acceptability of bitterness and pungency, similar to what has been seen with the consumption of specialty beers and coffees. In general the positive drivers of liking were nutty, ripe fruit, green tea, butter, green fruit, and grassy attributes, although for some consumers, attributes that are characteristic of defective oils—rancidity, mustiness, fustiness and winey flavor—were drivers of liking. These consumers may not have been exposed to enough information regarding the properties of EVOO, or almost surely, they may have become used to these defects, either from keeping the same bottle of EVOO in their kitchen for a long period of time until the oil deteriorates, or simply from buying cheap, imported and mass-marketed olive oils, which are more likely to be defective. Figs. 1a and b show that only a few consumers liked oils with floral, minty, and tropical fruit characteristics; except for U11, the oils in this category came from Spain, indicating that consum-

ers in this study either were not familiar with Spanish oils or did not like the characteristics of those oils. There were a high number of consumers who seemed to like U11 the most. 3.2. Market segmentation Figs. 1a and b provide a general background regarding the products that most consumers preferred and both the negative and positive drivers of liking. However, consumers differed in their preferences for the EVOOs. Three clusters were identified (Ward’s Method, Euclidean distance) as shown in Fig. 2. There were significant differences among the three segments (ANOVA, p < 0.05). Tables 4 and 5 summarize the demographics, consumption habits, and purchasing habits of the consumers. Consumers did not differ significantly (p > 0.05) in their consumption and purchasing habits, likely because they had been screened previously based on their olive oil consumption. So

Table 4 Consumer demographics summarya (percentages are in parentheses for each cluster and the totals) from the exit survey.

a

Cluster 1 (n = 33)

Cluster 2 (n = 48)

Cluster 3 (n = 29)

Total (n = 110)

Gender Female Male CHISQ

19 (58%) 14 (42%) pb = 0.0336*

40 (83%) 8 (17%)

22 (76%) 7 (24%)

81 (74%) 29 (26%) pc < 0.0001*

Ethnicity Asian-Asian American White-Caucasian (Non Hispanic) Hispanic or Latino Mixed or Other CHISQ

3 (9%) 27 (82%) 1 (3%) 2 (6%) pb = 0.1021 NS

9 (19%) 36 (75%) 1 (2%) 2(4%)

4 (14%) 20 (69%) 5 (17%) 0 (0%)

16 (15%) 83 (75%) 7 (6%) 4 (4%) pc < 0.0001*

Educational level High School Diploma Some college Bachelor degree Some graduate work Master degree Professional degree PhD Prefer not to answer CHISQ

0 (0%) 6 (18%) 5 (15%) 5 (15%) 11 (33%) 1 (3%) 1 (3%) 2 (6%) pb = 0.1817 NS

2 (4%) 15 (31%) 10 (21%) 8 (17%) 10 (21%) 1 (2%) 2 (4%) 0 (0%)

1 (3%) 6 (21%) 6(21%) 3 (10%) 5 (17%) 4 (14%) 4 (14%) 0 (0%)

3 (3%) 27 (25%) 23 (21%) 16 (15%) 26 (24%) 6 (5%) 7 (6%) 2 (2%) pc < 0.0001*

Income Less than $25,000 $25,000–$49,999 $50,000–$74,999 $75,000–$99,999 $100,000 and over Prefer not to answer CHISQ

6 (18%) 5 (15%) 3 (9%) 3 (9%) 11 (33%) 5 (15%) pb = 0.0926 NS

18 (38%) 10 (21%) 4 (8%) 8 (17%) 4 (8%) 4 (8%)

4 6 3 8 6 2

(14%) (21%) (10%) (28%) (21%) (7%)

28 (25%) 21 (19%) 10 (9%) 19 (17%) 21 (19%) 11 (10%) pc = 0.0272*

Age 18–29 years 30–39 years 40–49 years 50–59 years More than 59 years

6 (18%) 11 (33%) 6 (18%) 7 (21%) 3 (9%)

23 (48%) 8 (17%) 4 (8%) 7 (15%) 6 (13%)

6 8 5 6 4

(21%) (28%) (17%) (21%) (14%)

35 27 15 20 13

CHISQ1

pb = 0.150 NS

Marital status Single never married Living with a partner or married no children at home Living with a partner or married with children at home Divorced Widow/widower Prefer not to answer CHISQ

11 (33%) 4 (12%) 12 (36%) 2 (6%) 0 (0%) 4 (12%) pb = 0.0568 NS

(32%) (25%) (14%) (18%) (12%)

pc = 0.0048*

25 (52%) 10 (21%) 6 (13%) 4 (8%) 1 (2%) 2 (4%)

7 (24%) 9 (31%) 10 (34%) 2 (7%) 1 (3%) 0 (0%)

43 (39%) 23 (21%) 28 (25%) 8 (7%) 2 (2%) 6 (5%) pc < 0.0001

*Significant at p < 0.05; NS, not significant, p > 0.05. The first p-value given in the table corresponds to the contingency table chi square, which measures the association between columns and rows, in this case between clusters and categories (i.e. female, male (rows) vs. clusters 1, 2 and 3 (columns)). With the exception of gender (p < 0.05) there was no association between clusters and each demographic variable. c The second p-value corresponds to the differences between the answers in each category. b

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C. Delgado, J.-X. Guinard / Food Quality and Preference 22 (2011) 213–225 Table 5 Olive oil frequency of consumption and purchasea (percentages are indicated in parenthesis for each cluster and the totals).

Consumption Once a year or less Less than once a month 1–3 times a month Once a week 2–6 times a week Every day CHISQ Purchasing Never Less than once a year Once a year Once every 6 months (2 times a year) Once every 4 months (3 times a year) Once every 2–3 months (4–6 times a year) Once a month (12 times a year or more) CHISQ Place of purchase d Farmers Market Supermarket Discount retail Warehouse Club Specialty store Winey Tasting Fairs Direct shipping from producer in US Direct import from overseas Overseas while traveling abroad Other CHISQ a b c d

Cluster 1 (n = 33)

Cluster 2 (n = 48)

Cluster 3 (n = 29)

Total (n = 110)

1 (3%) 1 (3%) 2 (6%) 5 (15%) 17 (52%) 7 (21%) pb = 0.9720 NS

1 (2%) 2 (4%) 5 (10%) 7 (15%) 23 (48%) 10 (21%)

0 (0%) 1 (3%) 4 (14%) 2 (7%) 14 (48%) 8 (28%)

2(2%) 4 (4%) 11 (10%) 14 (13%) 54 (49%) 25 (23%) pc < 0.0001*

1 (3%) 0 (0%) 1 (3%) 4 (12%) 7 (21%) 13 (39%) 7 (21%) pb = 0.4485 NS

1 (2%) 3 (6%) 4 (8%) 8 (17%) 10 (21%) 20 (42%) 2 (4%)

0 (0%) 1 (3%) 4 (14%) 3 (10%) 4 (14%) 11 (38%) 6 (21%)

2 (2%) 4 (4%) 9 (8%) 15 (14%) 21(19%) 44 (40%) 15 (14%) pc < 0.0001*

19 (58%) 25 (76%) 5 (15%) 13 (39%) 22 (67%) 4 (12%) 7 (21%) 1 (3%) 0 (0%) 8 (24%) 4 (12%) pb = 0.4455 NS

16 (33%) 29 (60%) 5(10%) 16 (33%) 17 (35%) 3 (6%) 4 (8%) 1 (2%) 4 (8%) 3 (6%) 8 (17%)

12 (41%) 21 (72%) 6 (21%) 12 (41%) 16 (55%) 3 (10%) 7 (24%) 2 (7%) 1 (3%) 0 (0%) 2 (7%)

47 (43%) 75 (68%) 16 (15%) 41 (37%) 55 (50%) 10 (9%) 18 (16%) 4 (4%) 5 (5%) 11 (10%) 14 (13%) pc < 0.0001*

*, significant at p < 0.05; NS, not significant p > 0.05. The first p-value given in the table corresponds to the contingency table chi square, which measures the association between columns and rows. The second p-value corresponds to the differences between the answers in each category. For this question, consumers were asked to select ‘‘all that apply’’, hence percentages add up to more than 100.

Table 6 Motivationsa to consume olive oil.

Flavor Parents used Received as gift Olive oil tasting or sampling Condiment dipping bread at restaurant Health benefits Recipes cooking CHISQ

Cluster 1 (n = 33)

Cluster 2 (n = 48)

Cluster 3 (n = 29)

Total (n = 110)

20 (61%) 16 (48%) 1 (3%) 5 (15%) 17 (52%) 24 (73%) 24 (73%) pb = 0.9429 NS

16 (33%) 22 (46%) 3 (6%) 4 (8%) 31 (65%) 37 (77%) 29 (69%)

13 (45%) 13 (45%) 1 (3%) 4 (14%) 17 (59%) 20 (69%) 20 (69%)

49 (45%) 51 (46%) 5 (5%) 13 (12%) 65 (59%) 81 (74%) 73 (66%)

a Represents the number of consumers and percentage who reported the factor to be a reason to consume olive oil; the format of the question was ‘check all that apply’, hence percentages may add up to more than 100. b The p-value given in the table correspond to the contingency table chi square which measures association between columns and rows. There were no association between clusters and each frequency variable. NS, not significant (p > 0.05).

although they had different preferences, their consumption and purchase habits were pre-established before the study. The majority of consumers bought EVOO primarily at supermarkets (68%), specialty stores (50%) and farmer’s markets (43%), in contrast with the ways in which Mediterranean consumers most frequently buy their EVOOs. Fotopoulos and Krystallis (2001), for example, reported that 41% of Cretan consumers buy olive oil at the supermarket, while 38% buy in bulk directly from the producer or farm, and 21% make oil from their own orchards. In buying EVOO at supermarkets, consumers are not exposed to the sensory properties of the product, as they are in farmers markets or direct from producers or farms, and so their decisions are based on extrinsic factors such as packaging material, bottle material and label design. In contrast, when consumers buy the oil in bulk directly from the producer, they experience the properties of the oil and can make purchasing decisions based on sensory factors.

While American consumers tend to be aware of the health benefits and general flavors of olive oil, most have little information or opportunity to actually experience the product (Santosa, 2010). Table 6 shows the consumers’ motivations to consume olive oil for the population in this study. The main motivator was health benefits (74%), followed by use in cooking (66%). It is surprising that the third most important motivating factor was to use the oil as a condiment for the dipping of bread after experiencing this in a restaurant (59%); the influence of parents’ consumption of olive oil (46%) and oil flavor (44%) were the fourth and fifth leading motivators, respectively. The importance associated with these motivational factors concurs with previous research that showed health, taste and flavor, and curiosity for new recipes as the key drivers of consumption for UK consumers (Martínez et al., 2002). Greek consumers, who are experienced consumers, have indicated health, tradition, price, and special characteristics (sensory properties)

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Fig. 3a. Drivers of liking by preference cluster (dimension 1 vs. dimension 2). Biplot of EVOOs and consumers (Extra virgin olive oils are identified by a solid circle; Segment 1 (cluster 1 = 33 consumers) by a solid square, segment 2 (cluster 2 = 48 consumers) by a solid triangle, and segment 3 (cluster 3 = 29 consumers) with a star).

Fig. 3b. Drivers of liking by preference cluster (dimension 1 vs. dimension 2). Biplot of attributes and consumers (segment 1 (cluster 1 = 33 consumers) is represented by a solid square, segment 2 (cluster 2 = 48 consumers) by a solid triangle, and segment 3 (cluster 3 = 29 consumers) with a star. Vectors represent attributes).

as key motivators in their consumption of olive oil (Krystallis & Ness, 2003, 2005; Sandalidou & Baourakis, 2002). The drivers of liking for each segment are characterized in Figs. 3 and 4. Cluster 1 (n = 33) differed from the other clusters in that the consumers in that cluster tended to like the majority of the products, giving the highest liking scores. Consumers in this cluster tended to like equally grassy, green fruit, and spicy characteristics in the oil but also they did not seem to find bitterness or pungency. This cluster is also not sensitive to the defects. For this cluster the positive drivers of liking were nutty, green fruit, buttery, and slightly fusty and rancid attributes. The drivers of liking for cluster 2 (n = 48) were buttery attributes as well as all the defective characteristics—mustiness, wineyness, fustiness and rancidity. For these consumers, bitterness, pungency and astringency were negative drivers of liking. On the whole they preferred Italian oils (I1, I2, I3, GI), while a few of them liked GS and U5. It is interesting that this group had established previously that health properties were a strong motivator in consumption, yet they favored oils that were defective and rancid. Perhaps this result indicates their need for more information regarding olive oil as well as more exposure to different kinds of

olive oils. The preference for buttery oils might be associated with the consumption of olive oil as a substitute for butter on their bread. Figs. 3 and 4 show this cluster’s strong preference for oil U11, which was characterized mainly by floral and herbal aromas. Cluster 3 (n = 29) differed from the other two clusters by favoring not only nutty, green tea, and ripe fruit characteristics but also green fruit, grassy, and green tomato properties as positive drivers of liking (see Figs. 3 and 4). These consumers tended not to like slightly minty, herbs, and tropical fruit aromas in their oils. The oils preferred by this cluster were U1, C2, U9, U4, U3, and, for a few of them, U5, I4, and I3. Oils U10, U8, S2 and S1 were not liked by most consumers, a result that can be explained by these oils’ strong bitterness and pungency. The highest mean hedonic score was obtained by I3, which can be explained by the fact that its sensory properties—buttery, nutty, with slight rancidity but no bitterness or pungency at all— appealed to all three clusters, The clusters also differed in terms of the factors that most influenced their decision to purchase olive oil. Fig. 5 indicates the importance that each cluster, on average, assigned to each buying factor. Demographically, clusters 1 and 3 were similar; however,

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Fig. 4a. Drivers of liking by preference cluster (dimension 1 vs. dimension 3). Biplot of EVOOs and consumers.

Fig. 4b. Drivers of liking by preference cluster (dimension 1 vs. dimension 3). Biplot of attributes and consumers.

Fig. 5. Principal component analysis of the factors (the importance of each factor was measured on a 5-point scale where 1 = Not important; 3 = Neutral; 5 = very important. Cluster 1 (n = 33) is identified by a solid square, cluster 2 (n = 48) by solid triangle, and cluster 3 (n = 29) by a solid diamond. Vectors represent purchase factors) that most influence the EVOO purchase decisions across preference clusters.

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Fig. 6. Principal component analysis of some attitudes (attitudes were measured using a 5-point Likert scale where 1 = completely disagree; 3 = neither agree, nor disagree; 5 = completely agree. Cluster 1 (n = 33) is identified by a solid square, cluster 2 (n = 48) by solid triangle, and cluster 3 (n = 29) by a solid diamond. Vectors represent attitudes toward EVOO) regarding EVOO across preference segments.

Fig. 7. PLS regression (correlations loadings between expert (n = 23) quality ratings and consumer (n = 110) hedonic scores) of expert’s quality rating scores and consumers’ hedonic scores.

they differed in income level, which was higher for cluster 1. For cluster 1 the most important factors in purchasing decisions were the awards an oil had won as well as its region of origin, appearance and color. In cluster 3 the key factors affecting their purchasing decisions were the information regarding the product, and, to a lesser extent, certification of its quality, their previous tasting experience with the oil, and its color and appearance. With experienced or local consumers, previous research has shown that region of origin is the key factor in purchasing decisions (Dekhili & d’Hauteville, 2009; Fotopoulos & Krystallis, 2001; Stefani et al., 2006; van der Lans, van Itters, De Cicco, & Loseby, 2001). Cluster 2 determined purchases by price, packaging attractiveness, and label design. To some extent they were influenced by friends’ recommendations, brand name reputation, experts’ recommendations, and nutritional content. To a lesser extent, they made decisions based on the volume of oil in the bottle, its designation as extra virgin, and the label’s sensory descriptors. This cluster had the lowest levels of income and education, which may explain their concern with product price.

That price is a factor in purchasing decisions concurs with previous surveys that have found that both price and promotions drive purchases of olive oil (Krystallis & Ness, 2005; Martínez et al., 2002; Sandalidou & Baourakis, 2002). In the study conducted by Krystallis and Ness (2003) among Greek consumers, price was found to be the least influential factor in consumers’ selection of EVOOs. This result can be explained by the fact that, as an olive oil-producing country with a very high demand for and consumption of olive oil, Greece has numerous producers and suppliers of olive oil; since a significant proportion of Mediterranean consumers buy olive oil in bulk and therefore do not pay a premium for marketing and packaging costs, price is reduced in its importance as a factor. In contrast, in America, there are relatively few producers and the cost of imports and third party distributors make oils more expensive, so cost becomes a more important factor to consumers. If the study conducted in the UK by Martínez et al. (2002) is any indication, consumers of extra virgin and virgin olive oil tend to be childless and to average about 35 years of age; from these

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Fig. 8. Comparison of quality ratings (quality rating scale 0–100 (n = 23 experts)) by experts and hedonic scores (hedonic scale (9 point): where 1 = Dislike Extremely; 5 = Neither like nor dislike; and 9 = Like Extremely (n = 110 consumers). Cluster 1(n = 33), cluster 2 (n = 48), and cluster 3 (n = 29)) (overall liking) by EVOO consumers.

demographics, it can be concluded that they have time and the resources to treat themselves to gourmet products, including extra virgin olive oil. The price of EVOO might make it less appealing to persons of a younger age, who tend to not be as affluent, as well as to those who are older, whose eating habits, on average, tend to be conservative in trying new foods. Attitudes in regard to EVOO also differed by cluster (see Fig. 6). Consumers in cluster 1 considered imported oils superior to domestic oils, and liked EVOO because it is a natural food and enhances cooking. The second cluster felt that all oils tasted the same, but did believe that EVOO was a healthy food. Finally the third cluster preferred oils in glass bottles to those in plastic bottles, appreciated the taste that EVOO gives to salads, and considered it an environmentally friendly product, but at the same time, noted its expense as a cooking oil.

3.3. Relationship between experts’ quality ratings and consumers’ hedonic scores The following graphs explain the response of consumers to quality ratings given by a group of EVOO experts. The PLS regression analysis in Fig. 7 indicates that only in a few cases, consumers’ hedonic scores correlated with experts’ quality ratings, a result that might be explained by the background of those consumers and their degree of familiarity with olive oil compared with the rest of the consumers. For the majority of the consumer population in this study, however, hedonic scores did not match experts’ quality ratings. These results imply that quality ratings by experts are not a good predictor of consumers’ hedonic scores. Because of expertise and exposure to different olive oil profiles, experts are aware that bitterness and pungency are positive characteristics,

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in contrast to the majority of consumers, who did not favor these sensory properties in ‘new’ food products. It is fair to assume that as the number of official competitions and awards for extra virgin olive oils continues to grow worldwide, consumers will come to increasingly follow the opinions of the experts behind those events, much in the same way they do for wine. Fig. 8 represents the linear regression between the average liking scores by cluster and the average quality rating. None of the correlations was significant (p > 0.05, df = 20). The trend for each cluster and its relationship with the quality ratings are different; for instance, consumers in cluster 1 disagreed with experts’ ratings in that they tended to like the majority of the oils, even those that experts considered to be of very poor quality. However, they agreed in their positive ratings of oils U9, U3, U1, I4, and C2. The only oils that this group did not like were U2, S1, U8 and U10. Cluster 2 is the inverse of cluster 1; they tended to dislike the majority of oils, with the exception of I2, I3, U11, and A1. This segment is in complete disagreement with the experts in their assessment of what constitutes high quality in extra virgin olive oil. The third cluster had some agreement with experts in their assessment of high quality EVOOs. There was a positive relationship between the quality rating and the hedonic liking scores for most oils, with only U8 and U10 showing no agreement in assessments between this group of consumers and experts. 4. Conclusions Some segmentation was found in this consumer population. The three groups differed in some of their demographic characteristics, and also in their preferences, which were based for the most part on the sensory properties of the product. The three segments agreed in their rejection of bitterness and pungency as positive qualities, with these characteristics being more important for the second segment, which tended to like the slightly defective oils. The third segment preferred EVOOs with nutty, green tea, and ripe fruit characteristics, but did not like those with tropical fruit or herbal aromas. Finally, the first segment liked the majority of the oils in this study, showed less sensitivity to defects, and contained some people who did not object to bitterness and pungency in the oils. For cluster 1, the main driver of purchasing and attitudes regarding extra virgin olive oil was the reputation of the oil; they considered imported oils to be of better quality. For cluster 2, price was the main driver of purchase; they thought of EVOO as a healthy product but considered all of them to taste the same. Cluster 3 was influenced by the information available for the product, tended to use EVOO in salad dressings but considered it is too expensive as cooking oil. With the exception of cluster 3, there were discrepancies between consumers’ preferences and experts’ quality ratings of EVOOs. This points to the need to educate US consumers about the different styles of EVOOs and the wide range of sensory properties associated with them, most efficiently through increased exposure to the entire world of EVOOs, not just the mainstream, high-volume, import brands. Acknowledgments The authors thank Paul Vossen and Michael Bradley for their helpful suggestions and Dr. Hildegarde Heymann for her assistance with the SAS codes in the multivariate analyses. Experts Panel: Paul Vossen, Ramon Aparicio, Nancy Ash, Milagros Castro, Sarah Chironi, Thomas Curry, Elena Franceschi, Veronica Gaynor, Richard Gawel, Fran Gage, Luis Guerrero, Bruce Golino, Louie Gonzalez, John Hadley, Arden Kremer, Nancy Lilly, Julie

Menge, Marvin Martin, Frank Menacho, Jeffers Richardson, Deborah Rogers, Sandy Sonnenfelt, Dean Wilkinson. Olive oil donations: Corto Olive Oil; UC Davis Olive Center; Corti Brothers; The Olive Press; Hojiblanca; Golden Hill; Jovia Groves; Dos Colinas; McEvoy Olive Oil; Veronica Foods; Calolea; Sciabica’s Family.

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