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A comparison of consumer sensory acceptance, purchase intention, and willingness to pay for high quality United States and Spanish beef under different information scenarios¹

M. J. Beriain^*,2, M. Sánchez^* and T. R. Carr

^* Escuela Técnica Superior de Ingenieros Agrónomos, Universidad Pública de Navarra, Campus de Arrosadía, 31006 Pamplona, Spain; and College of Agricultural, Consumer and Environmental Sciences, University of Illinois, Urbana 61801

	Abstract

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Tests were performed to identify variation across consumer evaluation ratings for 2 types of beef (Spanish yearling bull beef and US Choice and Prime beef), using 3 information levels (blind scores; muscle fat content + production conditions; and all production data including geographical origin) and 3 consumer evaluation ratings (hedonic rating, willingness to pay, and purchase intention). Further testing was carried out to assess the extent to which expert evaluations converged with those of untrained consumers. Taste panel tests involving 290 consumers were conducted in Navarra, a region in northern Spain. The beef samples were 20 loins of Pyrenean breed yearling bulls that had been born and raised on private farms located in this Spanish region and 20 strip loins from high quality US beef that ranged from high Choice to average Prime US quality grades. The Spanish beef were slaughtered at 507 ± 51 kg of BW and 366 ± 23 d of age. The US beef proved more acceptable to consumers and received greater ratings from the trained panel, with greater scores for juiciness (3.33), tenderness (3.33), flavor (3.46), and fat content (5.83) than for Spanish beef (2.77, 2.70, 3.14, 1.17). The differences in sensory variable rating were more pronounced for the Spanish beef than for the US beef, always increasing with the level of information. The variation in the ratings across different information levels was statistically significant in the case of the Spanish beef, whereas the variation observed in the ratings of the US beef was highly significant in the willingness of consumers to pay a premium. Consumers who appreciated greater quality were also more willing to pay for the additional level of quality.

Key Words: beef • consumer • hedonic rating • information scenario • willingness to pay

	INTRODUCTION

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
The predominant intrinsic cues for consumers are tenderness, juiciness, and flavor, which, after color, have the most impact on the acceptability of beef (Dransfield, 1992; Bello and Calvo, 2000; Mannion et al., 2000; Nielsen and Jeppesen, 2001; Killinger et al., 2004a,b; Brewer and Novakofski, 2008). Among the extrinsic cues for beef quality, researchers have identified price, geographical origin, and brand name as the most important (Bello and Calvo, 2000; Bower et al., 2003; McEachern and Schröeder, 2004; Barrena and Sánchez, 2009). Other quality attributes that are important to consumers today are credence cues such as food safety, traceability, the type of livestock production system, animal welfare, and organic production methods (Nielsen and Jeppesen, 2001; Verbeke, 2001; Bernués et al., 2003; Umberger et al., 2003; McEachern and Schröeder, 2004; Caswell and Joseph, 2007; Loureiro and Umberger, 2007).

It is also important to note that a slight increase in palatability occurs when marbling increases above 3%, with further thresholds occurring at 5 and 7% (Savell et al., 1987). The correlation between sensory attributes evaluated by a group of trained judges and acceptance by consumers allows the estimation of market demands and expectations (Issanchou, 1996; Moskowitz, 1996; Caspia et al., 2006). Intrinsic and extrinsic attributes have been evaluated for their role in determining preferences in purchase intention for beef. The most salient research interrelates sensory product ratings with willingness to pay (WTP) for given extrinsic attributes (Killinger et al., 2004a,b; Tonsor et al., 2005).

More recent studies have attempted to explore the effect of hedonic scores, WTP, and buying intention when considering different levels of product information (Lange et al., 2002; Stefani et al., 2006; Resano et al., 2007; Roosen et al., 2007). Our research fits into this recent trend and differs from previous studies by presenting i) 3 levels of information (blind scores; fat content + production conditions; and all production data including geographical origin) and ii) 3 consumer evaluation ratings (hedonic rating, WTP, and buying intention). Thus, the aim of this study was to identify differences in consumer ratings across different stages of the consumption decision. An additional objective was to assess the extent to which expert ratings converge with those of untrained consumers.

	MATERIALS AND METHODS

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
A total of 20 Pirenaica yearling bulls were born and raised in the region of Navarra (northern Spain). Animals were raised under the Protected Geographical Indication Ternera de Navarra, which is included in the Register of Protected Designations of Origin and Protected Geographical Indications of the European Union (EEC, 2004), and they were slaughtered and dressed in an officially approved slaughterhouse (EEC, 1995). Animals were transported approximately 60 km from each farm the same day of slaughter, and they were slaughtered upon arrival. After the yearling bulls/steers were slaughtered, carcass grades for conformation and fatness according to the official European standards (European Commission, 2006) were assigned.

Screening of Panelists

Taste panel testing was conducted in Navarra, a region in northern Spain. The distribution of the consumer panel means for the random, age-stratified sample of 290 consumers resembled that of the population of the region in terms of sex, age, and household income level (Spanish National Institute of Statistics). The consumers reported to the Meat Laboratory of the Public University of Navarra. In overall terms, meat consumption in the study sample was relatively high, with over 80% of those surveyed consuming beef once a week or more. The remainder reported occasional consumption. Beef consumption throughout the province is close to the Spanish national average [Spain, 7.18 kg·capita^–1 and Navarra, 7.38 kg·capita^–1 (Fuentes, 2008)]. Low, lower middle, and middle-class males over the age of 50 with an elementary education reported greater frequency of weekly beef consumption (more than once per week) than upper-class females under the age of 50 with greater education (once per week). This is in line with standard consumption patterns in that geographical context.

Consumer Information Scenarios Design

The evenly distributed sessions were of 3 types, each with a different information level or experimental marketing scenario: 1) blind scores; 2) animal feeding and muscle fat content information; and 3) animal feeding, muscle fat content, and geographical origin information [one of the meats was from Pyrenean breed yearling bulls (Ternera de Navarra protected geographical indications certification)] and the other was imported from the United States (Certified Angus Beef specifications). Twenty Pyrenean breed intact bulls were born (April, 2006) on private farms located in the region of Navarra (Northern Spain). After weaning at approximately 6 mo of age, the calves were fed the following concentrate ration: 85% barley, 10% soybean meal, 3% protected fat, and a 2% commercial supplement that included minerals and vitamins. Animals were fed concentrate and straw ad libitum and were slaughtered and dressed in an officially approved slaughterhouse. The research was performed under the highest standards of humane care and use of animals. Animals were transported approximately 20 km and slaughtered upon arrival at 521 kg of BW and 351 d of age, using standard methods of stunning and dressing (average carcass weight 323 kg; dressing percentage about 64%).

The effect of the presence or absence of certain details of product information on the consumer ratings was investigated from different perspectives. The 3 types of product information given to or withheld from the evaluators were muscle fat content, type of production method, and geographical origin.

In terms of procedural details, consumers i) hedonically tested the product after receiving information as per the scenario in which they were involved [blind, medium (muscle fat content and production conditions), and full information (geographical origin plus muscle fat content and production conditions)]; ii) were then asked to state their purchase intention for the beef they had tested; and iii) rated their WTP a premium for US beef vs. Spanish beef. At the end of the process, consumers were asked details of their socio-economic profile, their beef purchase frequency, and the key attributes guiding their choice of product. The 3 types of product information provided or withheld from the evaluators were muscle fat content, type of production method, and geographical origin.

Beef Source and Preparation

After chilling for 24 h at 3°C, carcasses were sectioned at the 12th thoracic rib. The left carcass side was transported to the Meat Science Laboratory of the Public University of Navarra (Pamplona-Spain) and sliced into 2-cm-thick steaks. Chops were aged under vacuum for up to 7 d. Mean fat content in the LM from the Pyrenean breed was 1.17 (SD = 0.55). Percentage of intramuscular fat on the LM was calculated by the Soxhlet method (ISO 1443, 1973) for the Spanish and US beef. This is the standard commercial type of carcass produced in Spain from young bulls slaughtered for beef consumption. The US meat was obtained from 20 boneless strip loins (IMPS 180) purchased from MetaFoods (Atlanta, GA). The carcasses originated from beef cattle that were commercially slaughtered at an EUC-approved meat processing plant. The 20 boneless strip loins came from A maturity carcasses that ranged from high Choice to average Prime quality grades, and were delivered in a frozen state to the Public University of Navarra, Pamplona, Spain, June 1, 2006.

Taste Sample Preparation and Consumer Panelists

While the consumers were arriving, taste panel samples were cooked in the test kitchen of the facility. Frozen steaks were thawed in a walk-in cooler or refrigerator (1°C) for approximately 24 h and cooked on a grill (Magefesa, Spain) using AMSA (2001) guidelines to an internal temperature of 70°C. Three 2.5-cm-thick steaks from each carcass were cooked [12 steaks (4 carcasses x 3 steaks)]. A total of 13 evaluation sessions, each involving 20 to 25 consumers, were held. An age and residence stratified random population sample was selected. The methods of identifying potential consumers as panelists were random telephone calls, students/faculty of the campus, and friends and family of investigators. Whole steaks were then wrapped in aluminum foil with an identification tag and kept in a heat-retaining container or waterless food warmer until the moment of serving. Steaks were then cut into 1.5 x 2 x 1.5 cm pieces, and a single piece was placed on a plate and served to each consumer. The evaluation sessions were held in the 25-booth tasting hall at the Public University of Navarra.

The evaluators were presented with samples of meat from strip loins of Spanish and US beef on a thermal platter to maintain a constant temperature. The steaks were randomly assigned in all comparisons. Panelists were asked to evaluate samples in the order in which they appeared in the questionnaire, which was designed to avoid the effect of order of presentation and first-order and carry-over effects (Macfie et al., 1989).

In the sensory analysis, the consumer panel assessed aroma, juiciness, tenderness, flavor/taste, oiliness, and overall acceptability of the samples on a 5-point scale: like very much, like moderately, neither dislike nor like, dislike moderately, and dislike very much.

Trained Panelists Test

A 7-member trained descriptive panel selected and trained as described by Cross et al. (1978) was used to perform the sensory analysis. Potential panelists were prescreened individually, as by Meilgaard et al. (1991), to determine their interest, availability, and ability to describe the sensory characteristics of several kinds of foods. A series of 9 triangle tests, carried out in individual booths under red lighting, were used in a sequential analysis procedure (Cross et al., 1978).Training was accomplished in 3 sessions (3 h per session) with the panel seated around a table for discussion. Panelists were familiar with the use of intensity scales. The definitions used for the different sensory attributes are listed in Gorraiz et al. (2000): juiciness (perceived amount of moisture released while chewing), toughness (force that must be exerted with the molars to cut through a given portion of meat), characteristic flavor (characteristic flavor of grilled steak), liver (liver-like taste noted in the flavor of cooked beef), and oiliness (sensation of grease in the mouth after swallowing) using a 150-mm unstructured line scale, with a mark 10 mm from the left representing low intensity and another mark 10 mm from the right representing high intensity. Samples were cooked to an internal temperature of 70°C, as described in the section on the consumer panelists. Samples from 3 Pyrenean and 3 US strip loins were compared on each plate, except in the first evaluation session, where 2 samples of each type of meat were evaluated. The steaks were randomly assigned in all comparisons. Samples were coded using randomized 3-digit numbers. The tasting evaluation took place in infrared-lit booths, with temperature and humidity control. The tasting hall meets UNE 87004 (1979) standard requirements for sensory trials.

Warner-Bratzler Shear Force Determination

For texture analysis at 24 h postmortem, the LM was removed from the left side of the carcass and sliced into steaks from the 13th rib. Three and one-half centimeter-thick steaks were cut for instrumental texture analysis, and three 2.5-cm-thick steaks were cut for sensory analysis. Steaks were vacuum packed using an EGARVAC machine (Tarrasa, Spain) with polyamide/polyethylene pouches (Vaeseen Schoemarket Ind., Barcelona, Spain) with a film thickness of 120 µm and O₂ permeability of 1 mL·m^–2·24 h, CO₂ permeability of 3 mL·m^–2·24 h, and N₂ permeability of 0.5 mL·m^–2·24 h measured at 5°C and 75% relative humidity. The water vapor transmission rate was 3 g·m^–2·24 h at 28°C and 100% relative humidity. The vicat softening point of sealing was reached at 97°C, and the pouches had dart drop strength of 1,300 x g.

After packaging, one steak was used for instrumental texture analysis and another for sensory texture analysis were aged for 7 d postmortem, before being frozen and stored at –18°C until required for analysis. Before analysis, the US and Spanish vacuum-packed meats were thawed at 2 ± 1°C for 24 h. For texture instrumental analysis, the vacuum-packed meat was cooked in a water bath at 70°C for 40 min. Samples with a cross section of 1 cm² were cut with the muscle fibers parallel to the longitudinal axis of the sample. A model TA-XT2i texture analyzer (Stable Micro Systems, Surrey, UK) was used. Maximum shear force was assessed using a Warner-Bratzler (WBSF) shearing device.

Buying Intention and WTP: Origin and Other Meat Attributes

The present study analyzed differences in product evaluation ratings across different information scenarios. Purchase intention was measured on a scale of 1 to 10, where 10 was the maximum level of interest in the product according to the methods used by Bower et al. (2003), Thakor and Lavack (2003), and Fandos and Flavian (2006). Another approach to determining the relative importance of the role the various product attributes is to measure WTP for each separate attribute. Our precise option is the contingent valuation method (Hanemann, 1984), as adopted by Alfnes and Rickersten (2003), Umberger et al. (2003), Alfnes (2004), Dransfield et al. (2005), Stefani et al. (2006), and Caswell and Joseph (2007).

Statistical Analyses

The same model was applied to all the sensory attributes. Two fixed effects were considered (product origin and information level), and an ANOVA was performed using the following model:

[1]

where Y = the study variable; µ = the least squares mean; C = the type of meat (Spanish beef, US beef); S = the information level or scenario; and = random element.

Due to differences in scale usage across panel members, the data for the sensory analysis in this study did not include the taster effect, the statistical significance of which is generally accepted. Similarly, simple (Pearson’s linear) correlations were performed between the sensory variables obtained from the trained tasting panel and the consumers.

The ANOVA procedure was also used in the analyses conducted to measure the influence of the presence or absence of information about animal feeding, fat content and beef origin. Logistic regression models were used to estimate WTP a premium for the nondomestic (US) beef which had a greater production cost. First, an initial model (2, 3, and 4) was estimated. Hanemann (1984) showed how maximum WTP is given in this logistic model by the quotient between the opposite-signed parameter estimates for the constant (β₀) and the parameter estimate for variable A_i (base price, β₂) [4]. Then, in an extension of the standard logistic model provided by Hanemann (1984), a second model was used including the various information scenarios as dummy variables [5].

[2]

[3]

[4]

[5]

where logistic response takes a value of 0 if the consumer is unwilling to pay the proposed premium and 1 otherwise and A_i = stated bid amount; S = information scenario (S1: blind; S2: medium; S3 = full); and = random element. Finally, the relationship between purchase intention and WTP was analyzed using a single factor ANOVA.

	RESULTS

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Sensory Analysis and Information: Consumer Panel vs. Trained Panel

A general description of the consumer sample by information scenario is shown in Table 1, in which the socio-demographic profiles of the 3 subsamples are given. No statistically significant differences were found, apart from age and household size, which should not affect the obtained ratings. To minimize anchorage bias in the application of the contingent valuation method, this study used 2 premium price levels (10 and 20%) evenly distributed across the various information scenarios, as shown in Table 2, which also reveals them to be adequately distributed across consumer demographics. Observed differences by age and household size appeared only in scenario number 3 (full information), but these characteristics were not expected to affect ratings. In addition, an open-ended question was also used to obtain a final WTP estimate.

Table 4 presents the values of the CV between the sensory attribute ratings of the experts and those of the untrained consumer panels for each information scenario. In general, significant correlations (P < 0.05) were found between the juiciness ratings given by the consumer panel and all the sensory attributes evaluated by the trained panel, except for liver, for which no correlation was found. The beef judged to be juicier by the consumers was rated juicier (r = 0.584; P < 0.05, in full scenario), more flavorful (r = 0.69; P < 0.05 in blind scenario), and greater in oiliness by the trained panel (r = 0.57; P < 0.01). In all 3 information scenarios, juiciness ratings of the consumers showed an inverse correlation with the hardness ratings of the trained panel, and this inverse correlation was greatest under the full information scenario (r = 0.7; P < 0.01).

Strong significant correlations (P < 0.05) were also found between the tenderness ratings given by the consumer panels and all the attribute ratings given by the expert panel, except liver. The meat considered more tender by the consumer panel with no information had been rated by the trained panel as being juicier (r = 0.55; P < 0.05), less tough (r = –0.74; P < 0.01), more flavorful or beefier tasting (r = 0.65; P < 0.01), and greater in fat content (r = 0.54; P < 0.01).

When it came to the aroma of the beef, the consumers with no information showed a preference for a beefier taste, whereas those with full information preferred the aroma of the beef with the less fat content. The flavor ratings showed that the consumers with medium information and no information preferred the beefier tasting meat. Nevertheless, a significant correlation was found between the flavor and fat content ratings given by the consumers with no information (P < 0.05). The flavor ratings showed a significant inverse correlation with liver ratings given by the trained panel (r = –0.53; P < 0.05).

The oiliness ratings given by the consumers with full information were greater for the beef that was rated more flavorful by the trained panel, with a significant correlation being found between the oiliness scores of the consumer panel and the fat content scores of the trained panel (r = 0.71; P < 0.01). This might help to account for the fact that the US beef, which was rated greater in fat content and oiliness by both panels, also scored greater in the sensory ratings. In summary, the consumer acceptability of the beef and the ratings given by the trained panel were greater for the US meat, which presented a greater degree of juiciness, tenderness, flavor, and fat content; no link could be established between acceptability and liver rating (P > 0.05).

Table 5 presents the values of the coefficients of correlation between the sensory attribute ratings given by the consumer panel and the WBSF values, with high correlation values being found for all sensory attributes except aroma (P > 0.05). Greater shear force values suggest less juiciness and tenderness (P < 0.001), less flavor (P < 0.05), less oiliness (P < 0.001), and poorer overall acceptability (P < 0.01).

Table 6 gives the parameter estimates of the logistic model with dummy variables used to estimate consumer WTP under the different information scenarios for the product with greater production costs, that is, the US beef. The results provide statistically significant support for the impact of information on WTP because the information scenario parameters and the iteration of these with price are statistically significant (especially the second scenario over the third S2 and S2_A_i). Significance was also found for variable A_i (base price). Ratings, therefore, differ according to the amount of information received by the evaluator. For the logistic model and the open-ended question specifically, Table 7 gives the WTP estimates for the whole sample and all 3 information levels.

View larger version (13K): [in this window] [in a new window]   Figure 1. Relationship between willingness to pay and purchase intention toward US beef. Correlation coefficient value: 0.412 (P < 0.001). Willingness to pay scale (1 to 10) means as follows: 1 = never to be appointed to buy, 10 = always to be appointed to buy. % overprice = taking into account the beef Spanish beef price.

	DISCUSSION

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

Consumers informed of the origin of the meat, animal details (animal characteristics, breed, etc.), and the presence of Ternera de Navarra PGI certification of origin showed greater purchase intention toward the Navarra beef, despite having given it lower sensory ratings than the US beef. The anchorage factor and the subjective image of the beef seem to hold more weight than its sensory attributes. Consequently, we can detect the well-known halo effect, by which perception of the intrinsic attributes of the product improves in the presence of certain information. This effect has been linked with awareness of origin (Loureiro and Umberger, 2003; Wirthgen, 2005). It is worth noting, however, that acceptance levels of US and Navarra beef differed more widely among uninformed consumers, whose judgments were based solely on sensory cues, the difference being in favor of the US beef (Lange et al., 2002). Some authors have reported similar findings. Killinger et al. (2004b) found that 60% of surveyed US citizens from cities preferred domestic (US) beef and were even willing to pay more for it than those who preferred Argentine beef (16 to 19%). Those consumers in the present study who were given information regarding the characteristics and origin of the meat samples showed, through greater ratings, a preference for the Spanish beef samples. Conversely, Oliver et al. (2006), using a panel made up of German, Spanish, and British consumers to evaluate the sensory quality of beef produced under different production conditions, found that consumers who had no information regarding the origin of the beef did not show a preference for the domestic beef to which they were accustomed. However, no such effect was found in our study, where the US beef received similar ratings across all information scenarios. Roosen et al. (2007) also found that differences do not necessarily emerge in the intrinsic attribute ratings and may become apparent only in purchase intention.

Furthermore, as noted by Dransfield (1992), this study found the most influential attributes in acceptance of beef by the consumers to be juiciness and tenderness. The US beef samples were observed to have a mean muscle fat content of 5.83% compared with 1.14% for Spanish beef, which would explain why they were rated more highly for juiciness and tenderness. This is consistent with the positive effect of fat on the palatability and acceptability of meat. The marbling of the US beef may have influenced the results, given that fat stimulates the salivary glands and thus increases apparent juiciness (Savell and Cross, 1988). The intensity of the liver flavor, a note evaluated negatively by consumers in the flavor of meat, was judged to be stronger in the meat from the European carcasses, in contrast to findings published by Díez et al. (2006), who found aroma and flavor to be more intense in meat from heavier, older, and fatter carcasses. The results obtained in this study (significant high inverse correlation between the liver taste detected by the trained panel and the flavor ratings of the consumers) revealed that less fatty meats from younger animals presented a more intense liver taste, which reduced their acceptability. The ratings of uninformed and fully informed consumers showed highly significant correlations between oiliness and tenderness, between oiliness and juiciness, and also between oiliness and acceptability. This demonstrates the influence of the presence of fat in food, both from the nutritional perspective and at the moment of purchase (Brewer et al., 2001; Killinger et al., 2004b).

In terms of information levels, the consumers with most information found the Spanish beef more acceptable than the US beef, despite having given it lower ratings on the individual attributes. This may indicate either a strong contradiction in consumer behavior or a manifestation of commitment toward local products. Analysis of intrinsic factors alone can ensure neither market success nor market failure, since, as this study shows, extrinsic and environmental factors played a key role in consumer choice in the different stages of the consumer behavior process. On the other hand, sensory factors are still important because they undeniably play a key role in the overall ratings of products, such as food items (Lange et al., 2002). It should, nevertheless, act as a reminder of the important influence of attributes such as origin and production methods on purchase choice (Loureiro and Umberger, 2003; Caswell and Joseph, 2007; Resano et al., 2007).

Some researchers, such as Ahmed et al. (2004), have established that other attributes as well as origin influence consumer choice in low involvement goods, such as food products. Umberger et al. (2003) analyzed the WTP for domestic origin-certified US beef vs. Australian and Canadian beef, using a combination of sensory techniques and 4 attributes: flavor, juiciness, tenderness, and overall acceptability, finding greater differences between US and Australian beef, and fewer between US and Canadian beef. Using WTP methods and hedonic scores, they examined ratings of the precision with which product origin was defined and found that more precision in the definition reinforced origin as a quality cue and increased WTP.

As suggested by Caswell and Joseph (2007), attention must be paid to the voice of the consumer at all stages of the consumer behavior process. Furthermore, these differences in ratings were not found exclusively in relation to the sensory or intrinsic characteristics of the product; they also emerged in the final purchase choice and willingness to pay a premium. Few studies have focused on the relationship between sensory attribute ratings and WTP (Stefani et al., 2006) and fewer still in relation to the meat industry. The observed coherence between the intrinsic valuation and market interest of this product therefore holds a 2-fold appeal. First, intrinsic attribute ratings later translate into increased market interest in the product and greater WTP, suggesting that producers who are willing to put more effort into increasing quality will be rewarded with greater profits. Second, the consumer perceives a greater quality product and expects it to cost more.

Conclusions, Implications, and Limitations of the Study

This study set out, first, to demonstrate that the intrinsic attributes of beef and the commercial or external factors of the product play an important role in consumer ratings. A broader view therefore needs to be taken when investigating consumer beef evaluation ratings, by including variables such as consumer perceptions of color and intramuscular fat content at the moment of purchase or tenderness and flavor, which contribute to the sensory quality of the meat and have a decisive impact on the purchase decision.

Food producers contemplating product renewal or new launches should first try to find back-up through prior testing of end-consumer acceptance. Producers should take into account not only the intrinsic product attributes typically considered in such analyses, but also consumer acceptance of certain (extrinsic) marketing characteristics of the product.

A third finding, of interest from the production and marketing management point of view, has to do with the opportunities to be derived from information on product origin and the role of this information in the final product rating. It is sometimes possible to make up for deficiencies in the intrinsic properties of the product by focusing on extrinsic values, such as domestic origin. Nevertheless, improvements in the intrinsic characteristics of the product could also be exploited by linking them to the origin effect to put a wider range of quality on the market and thus make better use of variation in supply and increase the capacity to meet the potential range of existing demand.

Finally, the study has also shown that consumers who value better quality are also more willing to pay for the difference in quality that tends to result from a greater productive effort. The demand for quality therefore matches the monetary costs entailed. Customers are aware of this and are ready to pay more for it.

The limitations of this study lie in the fact that it is based on the comparison of beef from 2 different countries; therefore, it would be better to have data from more countries to compare results and to generalize the conclusions. Such data might include information regarding other breeds or consumer ratings from other countries or locations where the key extrinsic factors of the product may be different. It would also be interesting to perform a more detailed analysis to identify the socio-economic characteristics that may influence the results.

	Footnotes

 
¹ The authors thank Ministerio de Ciencia y Tecnología (PETRI 95-0703-OP) financial funds and the University of Illinois, Urbana, for funding this study and IGP Ternera de Navarra (Pamplona, Navarra, Spain) that contributed with meat samples from Pirenaica young bulls.

² Corresponding author: mjberiain{at}unavarra.es

Received for publication November 8, 2008. Accepted for publication June 5, 2009.

	LITERATURE CITED

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 


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