Beef traceability: are Greekconsumers willing to pay?

Olga Kehagia, Michalis Linardakis and George ChryssochoidisAgricultural University of Athens, Laboratory of Agribusiness Management,

Athens, Greece

Abstract

Purpose – This paper seeks to explore two issues, namely: whether Greek consumers are interestedin information provided to them for beef meat through systems of traceability, and whether they arewilling to pay in order to acquire specific information for beef meat.

Design/methodology/approach – The approach is taken is discrete choice modeling with amultinomial logit approach treating 11 different types of information.

Findings – Consumers are generally willing to pay higher for traceable beef, but not all variableshave equal and/or positive importance for consumers. For instance, brand is an importantdistinguishing factor only for higher educated respondents, but information on animal health providesnegative utility for all respondents.

Practical implications – Marketing strategy issues are raised, as the importance and utilityconsumers attach to traceability systems’-based information varies.

Originality/value – This paper provides further evidence on what information traceability systemsshould contain.

Keywords Agriculture, Greece, Consumers, Consumer behaviuor, Meat, Production control

Paper type Research paper

Introduction and extant literatureConsumer preferences for food quality and safety, and particularly the informationthey seek in food products, have been a constant concern of the scientific communitywhich studies consumer behavior in the food market. Following the food crises in the1990s and the emergence of the notion of traceability in the food sector and legislationthis decade, some research has been conducted which focused on consumer preferencesfor traceability. In the present paper, an effort is made to extend further on thesepreferences and derived consumer utilities.

Qualitative (focus group) and quantitative research conducted by Giraud andAmblard (2003) among consumers in France, concerning the way consumers interpretthe term traceability, has shown that the term traceability causes confusion to thosewho are not in a position to define and fully comprehend it. High income consumersattach a more technical meaning to the term, while smaller income consumers a moregeneral one. Moreover, income is positively connected to seeking information relevantto the origin and processing of meat. Another important finding of the study inquestion is the connection between the notion of traceability and the outlet where themeat is purchased. Thus, consumers who shop at a super market seem to be the leastinterested in traceability, while the most more interested appear those who shop inspecial meat shops. Those who shop at the local butcher’s in their neighborhood seemto particularly trust his advice. Furthermore, as these authors explained, consumers donot seem to connect traceability with the price of food (Giraud and Amblard, 2003).

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EuroMed Journal of BusinessVol. 2 No. 2, 2007

pp. 173-190q Emerald Group Publishing Limited

1450-2194DOI 10.1108/14502190710826040

Research conducted among Belgian consumers in Belgium defined two groups oftraceability attributes, the functional attributes and processing attributes (Gellynckand Verbeke, 2001). The former are the inherent attributes of the system which refer tothe ability of a more effective management of the supply chain, the possibility ofcontrol by the authorities as well as the apportioning of blame if necessary. Theseattributes can be considered as the minimum requirements of the system. The latterrefer to the production process, and mainly represent an extended version of thesystem with the ability to provide information relevant to the production of theproduct. The majority of Belgian consumers regarded the functional attributes oftraceability as more important and necessary while a part of consumers consideredthem necessary. Consumers seem to regard as the most important aspect of traceabilitythe element of control, safety and the most effective management of the chaintraceability offers, rather than that it provides the opportunity for receiving moreinformation concerning the production process.

Using a discrete choice experiment Dickinson and Von Bailey (2002) offeredsandwiches containing red meat (veal and pork) products to consumers in Utah USA.The attributes on the basis of which consumers were asked to decide if they would buythe product or not, was the guaranteed information on production processes (includinghow the animal was handled, the guaranteed security through indications of additionalcontrols etc.), traceability (as the ability to trace the product back to the breeding unitof the animal it came from) and finally all these attributes together. The results of theexperiment showed that the sampled US consumers were willing to pay a relativelyhigher price for traceability, but they were much more willing to pay for the othercharacteristics, namely the guarantee for safety and the way the product was made.Willingness to pay increased even more when these three attributes are combinedtogether (Dickinson and Von Bailey, 2002).

This experiment was also conducted in other countries, such as Canada (Hobbs,2003; Hobbs et al., 2005) and the UK (Dickinson and Von Bailey, 2002). Similar resultscame out in these countries too. Consumers seem to be willing to pay for traceability,but are willing to pay more when this is also combined with guarantees. Theseparticular experiments based on preferences therefore illustrate that consumers ideallycombine traceability with safety and quality guarantees. These in turn are primarilycertified by state authorities and second by independent private certificationcompanies (Hobbs, 2003). The guarantee allows increase in consumers trust.

Expanding further, Verbeke and Ward (2006) examined the information thatBelgian consumers consider important concerning beef. The conclusion drawn fromtheir research was that consumers show little interest for indications which are directlyrelated to traceability as well as information which derives from it, whereas they aremuch more interested in easily recognizable indications of quality such as qualitylabels and also obligatory data such as the expiry date. The data that attractconsumers’ attention in a label of beef is mainly the expiry date, the type, the label ingeneral, the labels and quality guarantees, while the information concerning thecountry of butchering and cutting and the identification numbers come last (Verbekeand Ward, 2006).

In research conducted in three European countries (Italy, Spain and Scotland),focusing on the information sought by consumers on the labels of beef, Bernues et al.(2003) ascertained that the most important pieces of information are the expiry date

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and the country of origin. Yet, there were differences between these countries asregards the information concerning the production system, traceability and qualitycontrol. Consumers in southern countries, mainly in Italy, seem to regard thisinformation as important, in contrast with consumers in Scotland according to whomthis information is not important. Nevertheless, the majority of consumers in all threecountries do not regard the brand of the product as important information (Bernueset al., 2003). Research focusing on consumer preferences concerning labels on beef,conducted by Roosen et al. (2003) in three countries, France, Germany and the UK, hasshown that consumers are particularly interested in the country of origin of theproduct. In France and Germany this information is more important than the productbrand and seems to be the most crucial purchase factor, in contrast with the UK wherefactors such as the color of the meat, fat, and the price seem to be far more important.The great majority of consumers in all three countries demand that an indicationshould be necessarily included on the labels in case the animal that the meat came fromhas been fed with genetically modified organisms. Consumers did not object to paying2 per cent more for a product which would provide this information on its label (Roosenet al., 2003).

In other relevant research, Davidson et al. (2003) found out that consumers inScotland are considerably interested in the country and region of origin of the beef,while issues such as price, the animal living conditions and environmental issues seemto be of less importance (Davidson et al., 2003). Dimara and Skuras (2005) have foundout that consumers in Greece are interested in information concerning the origin ofquality products such as wine, but are also interested in certification with labelsindicating origin such as PDO. Indications of origin, quality and traceability seem tointerest more consumers of a higher educational level who live by themselves (Dimaraand Skuras, 2003, 2005). Research carried out among German consumers showed thatthey are willing to pay a higher price for a meat product of a well known brand, whichcomes with a label guaranteeing safety and quality, whereas, if the product is not wellknown but nevertheless bears such a label, they are willing to pay a lower price(Enneking, 2004). During research focusing on consumer preferences regarding thecertification of beef in the USA and the UK, it was ascertained that in both countriesconsumers seem to be confused as to what exactly is certified concerning meat safetyand other factors such as environmental factors etc. In any case consumers in the USAseem to trust more certification by state authorities and the middleman brand, whileconsumers in the UK seem to trust more the certification by independent privateorganizations and the brand name of the retailer (Christensen et al., 2003). Finally,research conducted by Loureiro and Umberger (2003) among consumers in the USAshowed that they are willing to pay a higher price for traceability in meat products butmuch more for a certification of safety. They would pay the lowest price for a productbearing a label with the indication of origin, even less than for the attribute of meattenderness (Loureiro and Umberger, 2003).

To sum up the results of the various relevant researches, current evidence givesindications that consumers comprehend to a degree what traceability is and haveformed preferences for its basic components. Consumers seem to attach moreimportance to traceability as a function which contributes to the more effectivemanagement of the food supply chain and safety in case something goes wrong, ratherthan a function that provides them additional information on the food products they

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buy. In any case, it is obvious that the information sought in food is mainly the basic,such as the expiry date or/and country of origin etc. Nevertheless, there are quite a fewconsumers who, for specific products such as meat, would also like to have informationwhich pertains to the production process, the animal diet, its living conditions etc.These are mainly consumers of a higher educational level and income. Nevertheless,the system of traceability alone does not seem to suffice. They regard guarantees andcertifications as essential to the safety and quality of food products, which ideallyappear together with a system of traceability.

Nonetheless, still important aspects and product categories remainunder-researched. Beef meat needs for instance increased attention as a case of greatconcern for all consumers, state authorities and agro food complexes with issuespertaining to food safety such as the ovine spongiform encephalopathy or the dioxinesin animal feed. The stir caused by these crises to the European public opinion has ledthe European Union and the Member states to take global importance steps to securepublic health. Moreover, beef is classified among the food products with the highestconsumption in developed countries; in other words a prime case for the introductiontraceability and pertinent information systems. The latter has now become law for foodproducers in several continents including the USA (Bio-Terrorism Act) and EU(Regulation 178/2002 – see EEC, 2002).

Research questionsThe research questions of the present study are as follows:

RQ1. Are Greek consumers interested in information provided to them for beefmeat through systems of traceability?

RQ2. Which basic and which additional information is most useful and sought byGreek consumers when they buy beef meat?

RQ3. Which (increased) amount of money are Greek consumers willing to pay inorder to acquire specific information for beef meat?

MethodologyThe method of the discrete choice experimentThe method applied in order to investigate consumer preferences regardingtraceability and their willingness to pay for it, was a discrete choice experiment.This particular method constitutes a technique of the stated preference method set.According to these methods the information concerning preferences of individuals whomake a decision to buy a certain product, is elicited through the use of speciallydesigned hypothetical situations, such as comparison and evaluation among differentproducts. Consequently, the information gathered with methods of defined preference,derive from some decision experiment (Shen, 2005).

A study of discrete choice to analyze preferences manifested in real choices isimplemented in order to predict consumer choices between various alternatives. Thismethod is applied when consumers are able to choose between discrete situations, forinstance to buy brand A, brand B or none of these two. The most common applicationof this method in marketing research is for the purpose of investigating howconsumers choose between competitive products. Other methods, such as quality

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research, positioning research and segmentation research, only partly answer thequestion, “Why do consumers buy what they buy?” All these methods are inadequatewhen it comes to the point of practically predicting what exactly is going to happen inthe market in case of a competitive situation (Riedesel, 2001). A main advantage of thediscrete choice experiment method is that it is based on observing consumer choices, inother words it simulates the real behavior of the consumer. After all, what consumersdo is choose and the choice they make is what mainly affects the market. The more aresearch method tends to simulate and predict consumer choices, the more useful it isto marketing purposes. It should be mentioned that discrete choice models have beenwidely used in many diverse applications which include, among others, marketing (seefor example, Allenby and Rossi, 1999), econometrics (see for example, Louviere, 1984),transportation (see, for example, Linardakis and Dellaportas, 2003, Spanos et al., 1997)and health (see, for example, Ryan et al., 2001; Ryan, 2004).

This method is particularly useful to research focusing on price sensitivity. It can beused in a wide area of issues such as to calculate the price elasticity within the samecategory or to calculate whether price elasticity is different when different brands areconcerned, to clarify which product characteristics affect the real choice betweendifferent alternatives and to what degree, to investigate consumer willingness to paymore in order to acquire specific characteristics, to define the demand for a newproduct etc. An experiment of discrete choice uses a carefully designed series of choicesets to respondents. In each of these choice sets respondents are required to indicatetheir preference among various alternatives. Each preference is described on the basisof some basic attributes specializing at different levels (Table I). The formation ofattributes’ levels describing the alternative choices follow an experimental design andvary among choice sets. The data from answers do not only allow one to evaluate therelations among the levels of attributes and the possibilities of choosing an alternative,but also to evaluate marginal reasons for substitution among attributes (Riedesel, 2001;Shen, 2005).

The theory of stochastic utility and the Multinomial Logit Model (MNL)The main hypothesis incorporated in the discrete choice experiment approach is thatconsumers seek to (stochastically) maximize their utility. Thus, from a choice set givento them they will choose the one which maximizes their utility. Since the utility of analternative for a person U cannot be observed, a hypothesis is formed that it consists ofa systematic term V and a stochastic error term 1. Therefore, the utility a person jreceives from an alternative i can be illustrated as follows:

Uij ¼ V ij þ 1ij; ð1Þ

wherej ¼ 1; . . . ;N (N denotes the number of respondents),i ¼ 1; . . . ;K (K denotes the number of alternatives).

Choice sets The choice out of which the respondent is required to choose one or noneAlternatives The objects among which the choice is madeAttributes The variants which describe and made discrete the differences among alternativesLevels The different values the attributes take

Table I.Main elements of a

discrete choiceexperiment

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The systematic term V ij is the relation of Xij of a table of observable characteristicsand of b which is the vector (of dimension equal to the number of attributes) of theparameters that must be calculated (V ¼ Xb). Consequently, having made thehypothesis that the respondents choose the alternative which offers them themaximum utility, they will choose alternative i among a set of alternatives k whenUij . Ukj, i; k ¼ 1; . . . ;K , i – k. Given a dual variable yij which takes a value equal to1 when the individual j chooses the alternative i, then the possibility P for theindividual j to choose alternative i is:

Pð yij ¼ 1Þ ¼ Pð1ij . 2V ijÞ ð2Þ

In order to transform the theory of stochastic utility into a choice model, certainhypotheses should be made as regards the distribution of the stochastic term 1.Assuming that the stochastic term follows the Extreme Value Type I (EVI) distributionand is independently and identically distributed (IID among the alternatives andobservations), then the Multinomial Logit Model (MNL) is preferred. In the MNL theprobability that the ith alternative is chosen by the jth respondent is as follows:

Pij ¼emV ij

XK

i¼1

emVij

; ð3Þ

j ¼ 1; . . . ;N :

where m represents a scale parameter which defines the utilities scale which areproportional to the reverse of the stochastic term distribution (see McFadden, 1973, andTrain, 1986, for a detailed presentation of the MNL model). By replacing the stochasticterm V with its linear equivalent of V ij ¼ bXij, equation (3) is modified as follows:

Pij ¼embXij

XK

i¼1

embXij

ð4Þ

By using such a model the various alternatives are evaluated on the basis of theirattributes. When one of those attributes is price, the calculations of marginal utility canbe transformed into calculations of the consumers’ willingness to pay for changes atattributes level. Implicit prices (IP) are the marginal substitution ratios between thealternatives attributes and price, with a given linear utility relation which derives fromthe negative relation between non financial attributes and price. Thus this price is:

IPz ¼ Cz=Cm ð5Þ

where Cz is the coefficient of attribute z and is the Cm coefficient of financial attribute,in other words of price (Enneking et al., 2007; Shen, 2005; Wikstrom, 2003).

Design – the discrete products in the experimentConsumers who participated in the research were presented with hypothetical beefmeat and more particularly fresh beef of 1 kilo per pack. Current knowledge suggests

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this is the most commonly bought by consumers. The three alternative productsamong which participants were asked to choose one to buy were:

(1) An unpackaged product (A) bought at the local butcher shop.

(2) A packaged product (B) with some basic information provided.

(3) A packaged product (C) providing not only the basic information but also acertain amount of additional information.

Therefore, the differentiation among the three was based on the different levels oftraceability information provided by each beef product. An unpackaged product couldnot actually provide written traceability information. Product B which was packagedand can be bought at a food store or supermarket, provided some basic information theacquisition and provision of which did not necessitate the application of a complicatedtraceability system. Finally, product 3 is a packaged branded meat product which,through a well organized system of traceability, can provide additional information toconsumers.

The attributes of alternatives and their levelsThe attributes given to the alternatives of the experiment is a combination of basic andadditional information that a consumer could seek in a piece of fresh meat, as well assome basic elements of the product, such as its appearance and its texture and theprice. Eleven attributes-variables were formed in total.

First, price is the financial variable used to evaluate the respondents’ willingnessto pay to acquire specific information. The price varies at three different levels foreach product. It was assumed that product B will be more expensive than A and Cmore expensive than B, in other words the process was positively connected to theamount of information offered. In order to trace the general level of price, a briefprice research was conducted in meat shops and supermarkets and was found thatthe prices for 1 kilo of beef range from e6.5 to e9.5 a kilo. The prices selected forproduct A are e6, e8 and e10, for product B – e8, e10 and e12 and for C – e10, e12and e14. An “appearance” attribute was also created, due to its importance(Krystallis et al., 2007); this had two levels: “Pinky color, soft, with fat in the tissues,like stabled livestock” and “Dark red color, hard, with no fat at the tissues like freerange”. The former level gives consumer a sense of a more “manufactured” product,whereas the latter one of a more natural product. Five variables form the set ofadditional information found only in product C and have to do with informationthat can be offered by a well organized system of traceability. All attributes andtheir levels as well as the way they appear in the three discrete products areillustrated in Table II.

The next step following the establishment of attributes and the determination oftheir levels is to create the particular choice sets from which respondents are requiredto select the products they prefer. This procedure is delicate, since it provides the toolfor data collection which will be introduced to the model of discrete choices and whichwill allow the evaluation of the attributes’ contribution to the relation of thealternatives’ utilities (Shen, 2005). Due to the large number of attributes and theirlevels, an orthogonal fractional factorial design was used to reduce the combination ofattributes to be needed in the experiment. Therefore, 32 choice sets with the threealternative products were created. Since it is a common practice to divide the total

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Table II.Attributes and levels ofthe experiment andproducts they appear

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number of the cards into pre-specified groups (since 32 cards are too many for a singlerespondent to answer), each consumer saw eight cards out of 32, so that a full run of thefactorial design to be covered with four consumers. A rotation was followed (cardsnumber 1, 5, 9, 13, 17, 21, 25, 29 for the first respondent etc). “None of these products”choice, was also included so as to extract this option. The choice sets were designed inthe form of experiment cards which were included in the questionnaires in groups ofeight thus forming the questionnaires main part (see Figure 1). Additionaldemographic info was also collected.

Figure 1.A sample of a card used

for this experiment

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ResultsDemographic features of the sampleThe random sample of 123 decision makers was collected using quotas for theeducational level. That is, 50 per cent of the sample were respondents of lower andsecondary education and the remaining 50 per cent were of higher educational level.This allowed us to have enough responses for separate analyses with respect to theeducational level of the decision makers.

The analysis of the respondents’ demographic features, as those are illustrated inTable III, showed that in terms of gender there are clearly more women, 58.1 per centcompared to 41.9 per cent men. This proportion results from the fact that the researchfocused on respondents who were responsible for buying food for their household.Table III shows the demographic features of the sample.

The consumers’ preferences in the experiment of choice and willingness to pay forspecific attributesThe 87 respondents of the sample provided a total of 688 cards of choices. Of thesecards, 55 were eliminated (since the choice was “None of the above”). The remaining633 valid cards of choices were used in the analysis. There were also 36 respondents(additional to the 87 respondents) who were eliminated from further analysis, sincethey provided lexicographic responses. A response is called lexicographic when thedecision maker does not take into account all the available information providedduring the decision process and his/her choices are based on a particular attribute – forexample, a decision maker always chooses product A from the butcher shop, no matterwhat the other attributes of the alternatives are. These respondents do not take intoaccount the trade off among attributes, which is a primary assumption of the discrete

Frequency Percentage

GenderMen 36 41.9Women 50 58.1

Ageup to 30 14 16.330-45 41 47.745-60 20 23.360 þ 11 12.8

Family income per month,e600 14 17.5e600-900 12 15.0e900-1,200 18 22.5e1,200-1,500 18 22.5e1,500-1,800 10 12.5.e1,800 8 10.0

Educational levelNone 1 1.1Secondary education 37 42.5Higher education 49 56.3

Table III.Demographic features ofthe sample

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choice models and, thus, their responses cannot be used for the estimation of the model(see Wardman, 1988).

A first descriptive approach to the consumers’ preferences can be made byexamining the frequency of the choices for each of the three products of the experiment.So, from the examination of this data, the conclusion is drawn that product A is theproduct chosen in most remarks; in particular, it has been chosen 276 timesrepresenting 40.1 per cent of the remarks. The next product in order of preference isproduct B, which has been chosen in 180 occasions or 26.2 per cent of the cards.Product C is the least chosen product, with 177 choices or 25.7 per cent of the total ofthe remarks (Table IV). At this point, it is worth reminding the discrete differentiationof the three products which is the following: product A is an unpackaged product ofbeef bought at local butcher shops and basically provides no information, product B isa packaged piece of meat which provides certain basic information and product C is abranded packaged product which always provides the basic information and may alsoprovide additional information. Therefore, based on this general but also pertinentdifferentiation, we can conclude that Greek consumers generally prefer to buy from abutcher shop, indicating lack of trust for a branded product.

The application of the MNL model to the experiment data resulted in the coefficientsof attributes – variables of the products that define the systematic term of the utilityrelation in a linear manner. The statistical significance of these coefficients estimatedwith a t test shows the significance of the variables to the selection of products by theconsumers (Table V). These coefficients show the changes of the utilities due to thespecific attribute (the base line utility is 0). It should be noted that, the discrete choice

A B C Total

Number of remarks 276 180 177 688Percentage (%) on the total 40.1 26.2 25.7Average of price (e) 7.21 8.99 10.87 9.47

Table IV.Frequency of the choices

and average of theseprices

Variable Coefficient St. error

p-value(significantattributes at

a¼10% in italic)

Price 20.0539 0.0326 0.0984Appearancea 0.6161 0.1040 ,0.0001Date of butchering and expiry date 0.7390 0.1820 ,0.0001Origin 20.1381 0.1009 0.1708Brand name 20.4030 0.1163 0.0005Certification 0.0153 0.1744 0.9301Information on the breeding farm 0.0657 0.1686 0.6965Information on the animal diet 0.2988 0.1674 0.0742Information on the animal health 20.5441 0.1736 0.0017Genetic origin and place of the animal birth 0.3518 0.1769 0.0467Information on the animal living conditions 20.1593 0.1877 0.3960

Notes: a Reference category: pinky color, soft, with fat in the tissues, like stabled livestock

Table V.Multinomial Logit model:

whole sample results

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models’ dependent variable is not directly observed; it is estimated through theindication of the choices (categorical vectors with elements either “chosen” withfrequency 1, or “not chosen” with frequency I-1, where I is the number of alternatives.The estimated model has a form of a standard multivariate multiple regression, onlyafter the utilities of all the alternatives by all the respondents have been estimated.Therefore, a standard residuals’ analysis of the model can not be performed.

In addition, it should be noted that, due to the use of unobserved responses asdependent variable, the estimated coefficients b of b of the model are equivalent to cb,where c is a positive value. To avoid identification problems, a common practice is toset the utility of the last alternative equal to 0 and to estimate the remainingcoefficients under this constraint. That is, the inference of the discrete choice modelsshould be based on relative values and ratios between the parameters, rather than theabsolute estimations of the parameters themselves.

The results show that price is weakly statistically significant (at a ¼ 10 per cent), itis important to the consumers’ choices but not more important than some otherattributes with respect to the product’s quality. The more the price increases the morethe products’ utility decreases, since the coefficient of the price has a negative sign(20.0539). The product appearance seems to be a highly important attribute for theconsumers’ choice (p , 0:0001 , 0:05), which shows the importance of externalquality features for the choice of beef meat. The positive sign of the coefficient (0.6161)shows that the less the meat looks treated through a processing facility the more theutility of the consumers increases (passing from level 0, which is “Pinky color, soft,with fat in the tissues, like stabled livestock” to level 1, which is “Dark red color, hard,with no fat at the tissues like free range”). The high coefficient (compared to thecoefficient of price) indicates its primary importance in consumers’ preference.

From the group of basic information that a product of beef can provide, the date ofbutchering, the expiry date and the certification are those that are of the higheststatistical importance and therefore play a substantial role in the consumers’ choices.The coefficient of these dates is highly significant (p , 0:0001), confirming this asanother primary importance element in consumers’ preferences. Surprisingly, brandname has a significant negative impact on the utility of the project, showing lack oftrust on branded meat, compared to unpacked product bought at the butcher’s shop.

As regards additional variables that specify information deriving from a certaintraceability system (information on diet), the genetic origin and place of the animal birthalso appear to be of positive and statistically significant importance for the consumers.Importantly though, information on the animal’s health is statistically significant butwith a negative sign, which means that this information, when it is given, reduces theutility of the product. The two remaining variables of the additional information namely,information on the breeding farm and animal living conditions deriving from a certaintraceability system do not appear to be of statistical importance.

If the coefficients of the alternative products attributes are divided by the coefficientof price, the result is the Implicit Price (IP) for each of these qualities. This price is infact the ratio of the substitution of price by the particular attribute, that is, the amountof money that consumers are willing to sacrifice in order to obtain this particularattribute. The value of this amount in euros is shown in detail in Table VI.

Thus, this value, in order to obtain a product with the appearance that satisfiesthem, is 11.43 e, that is, consumers are willing to pay this amount in order to purchase

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a product the appearance of which constitutes a positive indication of quality. In orderto know the date of butchering and the expiry date they are willing to pay 13.71 e,which shows the importance of the safety and quality information to the consumers. Inaddition, consumers seem to be very interested in the information on the animal dietand the genetic origin and place of the animal birth, since they are willing to pay 5.54and 6.53 e respectively, for this kind of information.

The impact of educationIt is also interesting to examine the data set into two parts; respondents of up tosecondary education and respondents of higher education. The results are given inTable VII. It is noteworthy that the expiry date is statistically significant only for theconsumers of higher education. Important similarities and differences exist. Thus, firstwe witness that appearance remains a positive importance irrespective of educationallevel. A similar negative importance is evidenced regarding provision of informationon animal health. Second, we witness that the two groups exhibit a difference for brandnames and for expiry date. The lower educated group singly perceives a negativeutility for the brand names which is not the case for the higher educated respondents.In contract, the higher educated group perceives a positive utility in the expiry datewhich is not matched by the lower educated respondents. Importantly andunexpectedly, the information on genetic origin loses significance when the sampleis split.

Variable – attribute Willingness to pay in e

Appearance 11.43Date of butchering and expiry date 13.71Information on the animal diet 5.54Genetic origin and place of the animal birth 6.53

Table VI.Willingness to pay for

significant attributes(at a ¼ 10 per cent)

Up to secondary educationallevel sample

Higher educational levelsample

Variable Coefficient St. error p-value Coefficient St. error p-value

Price 20.0817 0.0513 0.1109 20.0217 0.0467 0.6425Appearancea 0.3183 0.1698 0.0609 0.9201 0.1509 0.0000Date of butchering and expiry date 0.2377 0.2924 0.4162 0.8163 0.2560 0.0014Origin 20.1633 0.1668 0.3277 20.1324 0.1327 0.3184Brand name 20.4835 0.1851 0.0090 20.2523 0.1573 0.1087Certification 20.2210 0.2846 0.4374 0.2979 0.2409 0.2163Information on the breeding farm 20.1854 0.3370 0.5822 0.2892 0.2192 0.1871Information on the animal diet 0.3019 0.3300 0.3604 0.3027 0.2080 0.1456Information on the animal health 20.7480 0.3395 0.0276 20.7439 0.2288 0.0011Genetic origin and place of theanimal birth 0.4948 0.3257 0.1287 0.2410 0.2300 0.2946Information on the animal livingconditions 0.2696 0.3466 0.4366 20.1470 0.2471 0.5518

Notes: a Reference category: pinky color, soft, with fat in the tissues, like stabled livestockTable VII.

Multinomial Logit model

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Qualitative observationsAs already mentioned above, one of the reasons for choosing personal interviews forthe collection of data, was that this research method would enable us to make someadditional qualitative observations, concerning the reactions of the respondents whilecompleting the questionnaire. At this point some of the most significant of theseobservations are being presented.

Most of the participants in the research found the procedure of repetitive choices(eight in total) of similar products quite strenuous. The attributes-variables of theexperiment were numerous and their repetitive examination was tiring for therespondents. We got the impression that their answers were not always the result of afull examination of the alternatives attributes (i.e. the detail of secondary information).The additional information provided together with attributes only in product 3, such asinformation on the breeding farm, the animal diet etc., were seemed to be considered byparticipants as a single group of information. In contrast, several respondents spentmore time examining the meat “appearance” (color, texture, etc.) variable. Theseobservations may prove useful in order to improve the design of the experiment cardsand the experiment in general, so that similar research can be better carried out in thefuture with a larger sample.

ConclusionsWhat resulted from the analysis of this study was that consumers are interested inbasic information (i.e. date of butchering expiry date) that can appear on beef products,and in specific only sub-parts of additional information (i.e. health and diet) that maybe provided to them by a traceability system. An aspect which is crucial to the choiceof the beef food product is the visual sense of the consumer concerning its quality, asillustrated in the particular experiment through the variable of “appearance”.Regarding butchering dates and expiry dates they are also prepared to pay anincreased price. It seems that the dates appearing on the product packaging are aneasily perceived indication of safety, which consumers are familiar with and whichthey seek in food products. These dates, together with the appearence, are apparentlyconsidered as the safety guarantees by the consumers.

With respect to the additional information that product C can provide, the fact thattwo out of five variables are significant, leads to the assumption that consumers aregenerally interested in having information on production process of food products,such as the animal diet (probably seen as secondary safety and quality elements); yetconsumers do not want to have information on health aspects.

The results of this research tend not to fully corroborate with all previous research(Verbeke, 2005). It is confirmed that consumers are interested in specific informationderiving from a traceability system, and are interested to pay more to a degree for aproduct that provides them with such information. From the frequency of answers wesaw that only a quarter are accepting to pay e10.87 for the C card (with mostinformation) compared to another quarter accepting to pay e8.99 (for someinformation) against e7.21 for the base choice. Thus the bulk of the respondents(three quarters) appeared to be satisfied with basic at large information only (like in thestudy by Giraud and Amblard, 2003 and Bernues et al., 2003). At the same time, theidentified prices are equivalent to a major þ24 per cent and þ50 per cent respectively.These are important price differences compared to 2 per cent or more identified by

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Roosen et al. (2003). Is there a cultural dimension and the importance attributed bySouth Europeans to their food? This is highly probable. The present study has notexamined the issue of certification, so this aspect is not comparable with other studies(e.g. Dickinson and Von Bailey, 2002; Hobbs, 2003). The importance of animal diet is inline with the results in the study by Roosen et al. (2003) (although that study lookedmore on the use of genetic modification in feed), as well as origin corroboratingprevious research (Bernues et al., 2003; Davidson et al., 2003; Roosen et al., 2003;Dimara and Skuras, 2005).

Education also plays an important role in line with Dimara and Skuras (2003, 2005)which impacts on the importance of brand names (similar to what was identified byBernues et al., 2003); and Roosen et al., 2003 for France and Germany). On the otherhand, it has been interesting to see that the utility identified by consumers regardinginformation on health remained negative irrespective of education, while informationon the genetic origin of the animal lost its significance when examined according toeducation.

Wider implications for marketing and the food industryModern companies should be orientated towards consumer needs and wishes, as this isthe only way they can cope with today’s highly competitive business environment.This does not exclude businesses of the food sector, particularly since this sector isvery competitive and has tight profit margins. The same applies to beef and beefproducts. Therefore, suppliers of such products should comprehend and respond to theneeds and wishes of their consumers in order to be able to survive in the near future.Traceability is now a legal requirement, yet companies still struggle with itsimportance and how beneficial it can be. Traceability is a crucial importance tool forachieving food safety and quality. Safety is achieved through monitoring everyingredient included in the final product, from the moment it is produced until it isplaced on the shelf of an outlet, and through the possibility of withdrawing the product,if necessary, regardless of the stage of the supply chain it has reached. Quality isachieved through better management of the beef supply chain and the accurateknowledge of the ingredients (or animal parts) used for the production of specificproducts. However, apart from needs, consumers also have wishes, the fulfillment ofwhich can become a competitive advantage for beef food product companies.According to the present research results, consumers do not simply rely onascertaining that they have consumed a safe product; they wish to know why a productis safe to consume when buying it. In doing so, they seek indications, particularly,dates of butchering and expiry dates, and appearance, followed by information onproduction process such as the diet of the animal and its origin. Consequently, if acompany fulfills such a consumer wish, and provides them with information on the dietof the animal the meat came from, for example, or the conditions in which it wastransported, it provides itself the opportunity to benefit further from the value added tothe product, by accompanying it with such information and increased prices. Providedthe cost of introduction of the traceability system is reasonable, companies can gainfrom offering additional information to consumers. Obviously, there is also still plentyto do regarding the likely impact of the “carriers” of such information (such asbarcodes or radio frequency indicators (RFIDs). In the future, based on thedevelopment and cost reduction of RFID technology, it is likely to be far easier and

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probably imperative because of competition to provide such information to consumers.Yet, overall, is it crucial for reasons of strategy, that companies explore now the issueof consumer information through traceability systems.

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About the authorsOlga Kehagia (B.Arts., Dip.Ed., M.Ed., Ph.D) is teaching at the Departments of Primary andKindergarten Education and Computer Engineering University of Thessaly, Greece. Shecompleted her PhD at King’s College London. Her work has mainly focused on revision changeswhen writing with word processors in English as a foreign language. Her work has appeared inComputer Assisted Language Learning Journal, European Conference on Educational Research,European Writing Conference Proceedings and European Computer Assisted Language LearningConference Proceedings. She is a reviewer in Computers and Composition Journal. She has runEuropean projects on e-competence and traceability and has worked on others. Olga Kehagia isthe corresponding author and can be contacted at: kehagia@aua.gr

Michalis Linardakis is an adjunct lecturer of Statistics, Department of Economics, Universityof Athens, and postdoctoral researcher, lab of Agribusiness Management, AgriculturalUniversity of Athens. He has a degree in Statistics from the department of Statistics, AthensUniversity of Economics and Business, MSc and PhD in Statistics from the same department. His

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PhD thesis is entitled “Extensions of latent variables models with applications on econometricand educational models”.

George Chryssochoidis (BSc, MSc, MPhil, PhD) is Ass. Professor in Food Marketing at theAgricultural University of Athens. His work has mainly focused on commercialization ofinnovations across international markets, marketing of food products and recently in foodconsumer behavior issues. He has published about 30 peer reviewed articles in the Journal ofProduct Innovation Management, Journal of Business Research, European Journal of Marketing,Journal of Global Marketing, European Journal of Innovation Management, and British FoodJournal, among others. He has participated or led 23 EU, national or industry funded projects.

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