Assessing the market potentialfor a local food product

Evidence from a non-hypothetical economicexperiment

Faical AkaichiDepartment of Agricultural Economics and Agribusiness,

University of Arkansas, Fayetteville, Arkansas, USA

Jose M. GilCREDA-UPC-IRTA, Polytechnic University of Catalonia, Barcelona, Spain, and

Rodolfo M. NaygaDepartment of Agricultural Economics and Agribusiness,

University of Arkansas, Fayetteville, Arkansas, USA

Abstract

Purpose – The purpose of this paper is to analyze the market potential of a locally produced and highquality food product (i.e. white bean “Mongeta Ganxet” (MG)) from Catalonia, Spain. Consumers’willingness to pay (WTP) for the product is elicited using a non-hypothetical economic experiment andthen the sensitivity of WTP values is analyzed with regard to additional information provided toparticipants that includes reference prices, leaflets and tasting. Finally, a sample-selection model isestimated to assess the factors that significantly affect consumers’ WTP for the product.

Design/methodology/approach – To elicit the willingness to pay a premium for the local foodproduct, 90 subjects were invited to participate in a random nth price experimental auction. Beforeauctioning the product, participants were asked to complete a questionnaire about consumer attitudesand purchase habits.

Findings – Only 7 percent of participants are willing to pay a price higher than the minimum pricefrom which the MG product may be purchased directly from a producer or the local producing market.Also, it was found that providing reference prices of substitute products (both conventional andalternative high quality white beans) positively affects WTP for the MG. Interestingly, however,provision of information on organoleptic, nutritional and cooking characteristics of the MG andproduct tasting do not significantly influence WTP. Finally, the level of consumption, the degree ofknowledge about the product and the participants’ previous experience increase the purchasingintention for the MG.

Originality/value – In contrast to traditional market research studies that use hypotheticalmethods, the authors use non-hypothetical elicitation mechanism to elicit consumers’ valuation for animportant local food product in Catalonia, Spain. Since actual products and cash were used in theexperiments, the authors provided the respondents with an incentive to reveal their true preferencesand valuation for the product of interest. The authors also tested the effect of provision of certain typesof information on WTP and analyzed the factors that significantly influence consumers’ WTP for theproduct.

Keywords Spain, Food products, Prices, Consumer behaviour, Willingness to pay, Market research,Experimental auctions, Random nth price, Reference prices, Mongeta Ganxet, Sample selection model

Paper type Research paper

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0007-070X.htm

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Received February 2010Revised May 2010

Accepted May 2010

British Food JournalVol. 114 No. 1, 2012

pp. 19-39q Emerald Group Publishing Limited

0007-070XDOI 10.1108/00070701211197347

1. IntroductionThe agro-food sector is continually seeking ways to differentiate products throughperceived quality and innovative design or by considering environmental or safetyissues. This strategic orientation is not aimed at increasing production, but rathertowards diversifying the food supply by exalting those attributes or benefits, whichmay be valued by the consumers, and thereby, differentiate the product fromcompetitors. The so-called “typical” or “local” food products have occupied apreferential place within the agro-food sector because their particular identity issupported by the quality and origin of its raw materials, as well as the peculiarity ofthe production method used. “Typical” food products can include both non-processedand processed products. Within the former, the level of quality and differentiation hasbeen determined either by the land’s natural characteristics and/or climatic conditionsor by specific farming systems. Yet, for the initially processed products, the typicalityresults from the posterior production method, permitting the raw materials to beimported from other areas (Caldentey and Gomez, 1996). The close link betweentypicality and territory likely explains why “typical” food products are usually referredas Origin Labeled Products (OLPs), even when there is no specific legal instrumentprotecting their name. Within food quality policy, the European Union has recentlystrengthened its action to protect OLPs, in particular through EC Regulation 2081/92,by introducing Protected Designations of Origin (PDOs) and Protected GeographicalIndications (PGIs) as two legal instruments for protection.

At the end of 2005 in Spain, 138 PDOs and PGIs were officially registered (excludingwines), of which 17 (12 percent) were located in Catalonia (North-East region in Spain,where Barcelona is the main city) (MAPA, 2005). Each year new “typical” products arebeing recognized as PDO or PGI, such as the “Mongeta Ganxet” from the “VallesMaresme”, the food product we are analyzing in this paper. “Ganxet” is a traditionalvariety of beans (leguminous). The plant has white flowers and its seeds are white, flatand kidney-like in shape (ganxet means small hook in the Catalan language). Althoughthis variety provides a much higher percentage of proteins and a lower percentage ofstarch than other varieties (Casanas et al., 1998; Santalla et al., 2001), it is not farmed inany other parts of the world.

In the last ten years, intensive research has been undertaken to recover this varietyas well as its organoleptic characteristics and to allow for a controlled productionsystem. Quite recently, the Association of Producers of the “Mongeta Ganxet” (MG)was created whose early task was to request from Spanish authorities the designationof a PDO. However, a lot of effort is still needed in the existing production systems tomeet the regulations requested by the PDO. It is also necessary to obtain informationabout the market potential or how consumers would value this variety in the market.

This paper aims at analyzing the market potential of the MG in Barcelona, witharound 4 million potential consumers, and located between 30 and 50 km from theproduction area. We assess the market potential by calculating, through anon-hypothetical economic experiment, consumers’ willingness-to-pay (WTP) a pricepremium for this variety over the conventional counterpart. Unlike other hypotheticalvaluation methods, such as contingent valuation, where the surveyed persons tend tooverestimate the valuation of the product, we use experimental auctions to simulate areal market situation by offering the participants real products and allowing anexchange of real money. This way, the participant will incur real costs if he or she

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deviates from his or her equilibrium strategy (i.e. non-truthful valuation byrespondents can provide them a loss of benefits).

Additionally, we analyse the sensitivity of the WTP to additional informationprovided to participants. This information includes reference prices, leaflets, and tasting.Finally, we also estimate a model to assess the main determinants of consumers’ WTP.Taking into account the previously mentioned objectives, the contribution of this paperis threefold. First, it is one of the first attempts in Spain to use non-hypothetical economicexperiments (i.e. experimental auctions) to elicit the WTP for a food product[1]. Second,although this paper applies established methods in the experimental protocol (the nthrandom price auction, the introduction of referenced prices and the release of additionalinformation during the experiment, including tasting), it is the only one, to ourknowledge, that combines the three elements. Finally, this paper is unique in the analysisof the experimental data in the sense that it provides a modelling framework todetermine the main factors affecting consumers’ WTP.

2. Experimental auctions as an instrument to measure the willingness to payThe estimation of WTP for a food product has generated an extensive literature. Ingeneral terms, four alternative methods have been used: hedonic prices, contingentvaluation, conjoint analysis – choice experiments, and experimental auctions. The lastmethod values the attributes of a good in terms of consumers’ revealed preferences,while the first three methods are generally based on stated preferences[2].

During the last decade, the use of experimental auctions (EA) has gainedrecognition among economists as a tool for valuation of private and public goods. Theauctions are defined as a market institution for determining prices and assigninggoods. Auctions have a set of rules that determine, according to the bids presented bythe participating bidders, the winner of the auctioned good and the price to be paid(McAfee and McMillan, 1987). Experimental auctions try to simulate a real marketsituation in which the consumer makes the decision to buy and makes the purchase;thus offering to participants real products and allowing for exchange of real money.Hence, the auction participant can incur real costs if he or she deviates from anequilibrium strategy (Lusk and Shogren, 2007).

Experimental auctions are said to elicit more accurate estimates of WTP than othermethods because it is based on actual behaviour (not on individual intentions)involving real products and money (Lee and Hatcher, 2001). The EA:

. permits the control of possible deviations from true values and strategicbehaviour of participants;

. obtains the WTP of each individual, which enables us to make parametricassumptions regarding the form of the demand curves of the market;

. allows the modelling of the determinants of the WTP; and

. enables the participant to incorporate the “feedback” from the experimentalauction regarding his or her bids, just like in the real market (Lee and Hatcher,2001; Lusk and Hudson, 2004).

Despite these interesting advantages and almost half a century of empirical literatureon the use of experimental auctions, various authors have noted some potentiallimitations. First, the implementation of auctions is a costly task that generates

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geographical and regional restrictions in the selection of subjects. At the same time, ithas been shown that the amount of money participants receive (participation fee) ascompensation for participation in the auction may generate biases in their bids. Finally,it is quite common to observe null bids, generally due to the lack of interest by thebidders for the auctioned good (Lusk and Hudson, 2004). In any case, many of theselimitations can be overcome with a rigorous process of sample selection, recruiting andauction design and implementation, aspects, which we have taken into account in thisstudy.

3. Design and implementation of the experimental auction3.1 Sample, auctioned good and questionnaireTo conduct the experiment, we contracted with a company with experience in carryingout sensory analysis. This agency randomly selected the participants from a list ofpeople from Barcelona and its metropolitan area that were responsible for foodshopping in their household, using a quota system to guarantee that the samplerepresented the appropriate population age distribution. The people who participateddid not have previous information about the goal of the study, the product beinganalyzed or the conditions of the research. In total, 90 subjects participated in theexperiment. Table I shows the socio-demographic and economic characteristics ofparticipants in the experiment. We conducted the experimental auction in one of thecompany’s tasting rooms. The auctioned good was 1kg of the “Ganxet” white bean,stored in a cloth bag. The retail market price for the good in the production area is 11.60euros while the price in bulk at the farm is around 6 euros per kg.

Before auctioning the product, participants were requested to fill out a questionnaireabout various aspects related to the MG with the purpose of characterizing the sampleand analyzing their attitudes and purchase habits. This information was then used todetermine the major factors that influence their willingness-to-pay a premium for theGanxet PDO white bean. Taking into account the results of the literature onconsumer’s WTP for food product in general, and typical food products, in particular,we structured the questionnaire in four parts. The first part was intended to capturethe purchasing and consumption habits related to white beans. We included thesevariables in the analysis not only to assess their effect on consumers’ WTP but also tohelp control for some unobservable factors such as inventory effect. The second partincluded various questions that intended to capture specific aspects related to theMongeta Ganxet. The third part attempted to obtain information regarding theattitudes that the participants had towards various aspects related to food. Specifically,they were asked about:

(1) The role of food in their life.

(2) Main attributes participants consider when purchasing or consuming food.

(3) The role that prices play in food purchase decisions.

(4) The fourth part asked questions related to participants’ socio-demographiccharacteristics and lifestyles[3].

3.2 Auction mechanismSeveral empirical studies have used the second price (Vickrey), the nth price, therandom nth price and the BDM (Becker et al., 1964) auction to elicit the

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willingness-to-pay a premium for a specific good (Lusk and Shogren, 2007)[4]. In thesecond price auction (SPA) the highest bidder wins, but the price paid is thesecond-highest bid. Theoretically, it has been shown that the SPA is a robust auctionmechanism (Krishna, 2002) in the sense that it is an auction mechanism where theoptimal bid strategy of a participant is to report a bid equal to his or her true valuation.Partly due to this reason, the SAP has been the most widely used auction mechanism inempirical applications. However, the literature has shown that the second price auctionhas certain limitations, especially when the researcher wishes to measure the demandcurve for a real product (Shogren et al., 2001). The major problem that the SPA presentsis that it tends to exclude those participants whose valuations of the auctioned good aremuch lower than the market price (i.e. off-margin bidders). These participants adopt aninsincere bidding behavior, since they do not believe they may win (Shogren et al.,2001). In this sense, an auction mechanism in which the market price is determined in a

Variables/categories Percentage sample Percentage population

GenderMale 21 47.3Female 79 52.7

Age18-34 39.4 35.535-49 32.3 35.150-66 28.3 29.3

Education levelNo formal education 2.3 11.5Primary school 17.7 19.5Secondary school 51.1 47.7University degree 28.9 21.3

Income/month (in e and after tax)Less than 1,000 13.71,000-2,000 46.22,001-3,000 21.3 NA3,001-4,000 13.8More than 4,000 5.0

ProfessionEmployee 60.0Entrepreneur 4.4 47.0Liberal professions 4.4Housewife 18.9 9.4Student 6.7 18.4Pensioner 3.4 20.4Unemployed 2.2 4.8

Household size1 7.8 40.72 37.8 29.03 25.6 22.34 17.8 6.25 þ 11.0 1.8

Table I.Sample

socio-demographic andeconomic characteristics

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random way may solve the SPA problem because, in that case, the probability ofwinning for all participants would increase, hence providing them more incentives tobid in a sincere manner.

To overcome such limitations, the BDM mechanism (where the market price isobtained randomly from a price distribution determined previously by the auctioneer)has been used in empirical work over the last two decades. However, this mechanismhas also been criticized mainly for two reasons: first, the exogeneity of the pricedistribution determines that the market price is unrelated to the valuations of theparticipants; and second, it has been shown that the type of distribution from which themarket price is obtained exercises a large influence on the bidding behavior of theparticipants (Ariely et al., 2002; Lusk et al., 2004a).

Shogren et al. (2001) proposed a new auction mechanism, called the random nthprice auction, which specifically addressed the incorporation of bidders with lowvaluations. This mechanism combines two key elements from the two classicmechanisms previously mentioned. In fact, in the random n-th price auction the price ofthe market is endogenous, as in the SPA, but it is determined in a random way, like theBDM mechanism. The price endogeneity guarantees the existence of a relationshipbetween market price and the valuations of the bidders, while its randomness aims toengage all bidders, even those with the lowest valuations.

In practice, the random nth price auction works as follows: each one of theparticipants offers a bid for the auctioned product. Then the auctioneer orders the bidsfrom highest to lowest and selects randomly a number n from a uniform distributionbetween 2 and k (k participants). The n 2 1 highest bidders are declared winners of theauction and the auctioneer sells them one unit of the auctioned good at the nth price.For example if n ¼ 4, the three highest bidders each will buy one unit of the auctionedgood priced at the fourth highest bid (Shogren et al., 2001). This is the auctionmechanism adopted in this paper.

3.3 Experimental treatmentsAn additional goal of our study is to analyze the sensitivity of the price premiumparticipants are willing-to-pay for the MG under different marketing strategies. Wetest two main effects:

(1) The potential presence of prices from substitute products (as a proxy of a realpurchase situation).

(2) The provision of additional information about the auctioned product during theexperiment.

With respect to the first effect, besides the priceless product to be auctioned, threedifferent levels of information were provided:

(1) Retail prices of conventional white beans.

(2) Retail prices of both conventional and high value (PDO) white beans.

(3) Control level: no information on prices[5].

Related to this issue, several empirical studies were carried out to explore the effect ofreference prices on the consumer WTP for product sold in auctions. Compeau andGrewal (1998) and Monroe (2003) found that the consumer WTP moves in the direction

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of a higher external reference price. Kamins et al. (2004), in eBay auctions, show thatthe consumer WTP is larger when a high external reference price is specified thanwhen the auctioneer specifies a low external reference price. They also found that whenthe auctioneer provided both high and low reference prices, the high reference priceinfluenced the WTP more and that the low reference price led to a lower outcomecompared to when an auctioneer did not communicate any reference prices. Whilethese studies considered the effect of a low or a high price specified by the auctioneeron the consumer WTP, the literature generally provides no concrete evidence on howprice of a real competitive brand of the auctioned product influences bids inexperimental auctions used to elicit home-grown values of individuals for goods. Soleret al. (2002) showed that the reference price of a conventional competitive productincreased the perceived value of the product. In the present work, we test the effect ofthe reference prices of conventional products as well as the effect of the reference pricesof high value products. Based on the literature, we expect that the consumer WTP forthe MG will be affected positively by the reference prices of high value products andnegatively by the reference prices of conventional products.

Regarding the second effect, three levels of information were again provided toparticipants:

(1) A promotional leaflet (manufactured by the association of producers of MG inSabadell) that includes information about the organoleptic and nutritionalcharacteristics of the product, as well as recipes of some typical plates based onthe MG.

(2) Product taste (cooked with salt and seasoned exclusively with olive oil).

(3) Control level: no information.

Some studies have analysed the effect of releasing information about the auctionedproduct during the experiment on the consumers’ WTP (Umberger et al., 2003; Lusket al., 2004b; Nalley et al., 2005; Gil and Soler, 2006; etc.). In all cases, results showedthat positive information increases consumer WTP while negative informationdecreases WTP. The empirical evidence on the effect of tasting on WTP is morelimited. In any case, among the few studies that has analysed such an effect, theconclusion is not clear. While Lusk et al. (2001) and Drichoutis et al. (2008) found apositive relationship; Lund et al. (2006) showed that tasting reduces consumers’ WTPin the case of apples. Table II shows the nine experimental treatments (sessions)derived from the combination of levels of the two effects considered (roughly tenparticipants per treatment).

3.4 Steps followed in the experimentThe process to obtain the relevant information in this study consists of four steps. Instep 1 and after taking a seat and given a welcome, each participant received anenvelope, which contained 15 euros as compensation for their participation, his or hernumber of identification, ten bidding cards and a questionnaire which have to becompleted before the beginning of the experiment. One of the main determinants ofsuccess in experimental auctions is a good understanding by the participants of thefunctioning and the incentive compatibility of the auction mechanism. To achieve thisgoal, in step 2, participants were given an oral explanation supported by someexamples in the board on the operating procedure of the random nth price auction.

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During the explanation, participants were totally free to ask questions to dissipate anydoubts about the process. Given the importance of this step, we informed participantsthat it is very important that they fully understand the auction mechanism. We alsodemonstrated to them how they could lose money if they deviate from their truevaluations. We moved to the next step only after being sure that all participants fullyunderstood how the auction mechanism worked. Before doing the actual auction, wealso carried out a training session, auctioning a 330 ml of bottled water for threerounds.

In step 3, participants were requested to come close to a table where a few units ofMG (cloth bags of 1 kg. or 2.2lbs.) were placed along with or without other brands ofpriced-white beans, depending on the treatment. Participants were then provided anopportunity to closely examine the auctioned product. Once all participants hadfinished inspecting the product, each one had to report how much he or she would bewilling-to-pay for the offered product. After the first round was finished, the biddingcards were collected and ordered, n was randomly selected from a uniform distributionand the winner(s) was (were) then announced. The same process was repeated for threeadditional rounds. In step 4, the auction was interrupted after the fourth round, whenthe additional information was granted, and consequently the next four rounds weremade until completing a total of eight rounds. However, participants in the controltreatment were not given additional information and the experiment was made just asmentioned in step 3, during the eight rounds involved in the experiment. At the end ofthe eight rounds, one round was chosen randomly to determine the winner(s). Thewinner(s) of such round was (were) appointed as the winner(s) of the auction. Once theresults were announced, the experiment ended by handing the product to the winner(s)who had to pay the corresponding market-clearing price.

Depending on the objective that we are tackling, three techniques were carried outto analyse the data obtained from both the questionnaire and the experimental auction:ANOVA, Factorial analysis and a sample selection model. To check the effect ofreference prices, we first tested the equality of mean bids between the three groups ofparticipants using the t-test and then checked the dependence of the three groups ofmean bids using the Benferroni (ANOVA) test. To examine the effect of theinformation provided in the leaflet or the taste of the product on participants’ WTP for

Session 1 (n ¼ 9) Session 2 (n ¼ 11) Session 3 (n ¼ 11)No reference onproducts’ pricesNo information

Reference on conventionalproducts’ pricesNo information

Reference on conventional and PDOproducts’ pricesNo information

Session 4 (n ¼ 11) Session 5 (n ¼ 10) Session 6 (n ¼ 9)No reference onproducts’ pricesLeaflet

Reference on conventionalproducts’ pricesLeaflet

Reference on conventional and PDOproducts’ pricesLeaflet

Session 7 (n ¼ 11) Session 8 (n ¼ 9) Session 9 (n ¼ 9)No reference onproducts’ pricesTaste

Reference on conventionalproducts’ pricesTaste

Reference on conventional and PDOproducts’ pricesTaste

Note: n: Number of participants in each session

Table II.Experimental treatmentsconsidered in the study

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the MG, we performed a t-test. As mentioned in the previous sections, our secondobjective is to assess the determinants of participants’ WTP for the auctioned product.To deal with this issue, we first carried out a factor analysis. This technique was usedin order to reduce the information on participants’ attitudes toward the MG into fourfactors (F11, F12, F21 and F22; see Table III for a description of these factors). Thesefactors were considered with other explanatory variables to estimate a sample selectionmodel. This model allows us to first assess the factors determining the decision to payor not to pay a price premium for the MG and then the determinants of the amount ofthe price premium participants are willing to pay. Therefore, in the next section wefirst discuss the results obtained from the ANOVA and the t-test analysis and thenreport the results from the estimation of the sample selection model.

4. ResultsThis section is divided into two sub-sections. In the first one, we gather the results fromthe experimental auction, paying special attention to the effect of the two controlvariables introduced: reference prices and additional information provided toparticipants. In the second part, we analyze the market potential of the auctionedproduct and the main factors that determine the participants’ willingness-to-pay a pricepremium for MG.

4.1 Effect of the presence of reference prices and the provision of additional informationabout MG characteristics on the willingness-to-pay for the MGAs mentioned earlier, in this study we tried to measure the sensitivity of theparticipants’ WTP a price premium for MG with respect to two types of informationprovided to them. The first type of information provided were reference prices: threepriced-brands of conventional white beans were provided to one third of participants;three priced-brands of conventional and two priced-PDO white beans were provided toanother third of participants (see footnote 4); and no information was provided to thelast third (control group). As in the previous case, we considered the participants’average bids during the last four rounds. Results from the different groups are shownin Table IV.

As can be observed, the presence of PDO priced-substitutes significantly increasesparticipants’ valuation of the MG; the average price that participants are willing-to-paywhen prices for PDO white beans are provided is significantly higher than in the othertwo cases. Second, provision of prices of conventional white beans and provision of noinformation on prices do not significantly change WTP (the average WTP is 2.86 and2.76 euros for cases without providing reference prices and providing onlyconventional products’ reference prices, respectively).

As can be observed in Figure 1, providing information about the organoleptic,nutritional and gastronomical characteristics of the MG seems to not have any effect onconsumer WTP for the MG. This result is statistically confirmed by the informationshown in Table V that exhibits the comparison of the average bids made byparticipants in the first four rounds and in the last four rounds under the threescenarios considered. As shown, there are no significant differences in mean valuesand therefore neither the leaflet information nor the taste, have an effect on the WTPfor the MG.

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Dependent variables Name Description

Willingness to pay DWTP Binary variable that take the value 1 if participant iswilling to pay a price premium; and 0 otherwise

Price premium PWTP Quantitative variable censured below at 0

Independent variablesPurchase frequency ofthe MG

FREQMG Dummy variable that takes the value 1 if the participant isan regular purchaser of MG; and 0 otherwise

High knowledge level HIGHKNOW Dummy variable that takes the value 1 if the participantanswers correctly to more than eight out of eightstatements about MG; and 0 otherwise

Medium knowledge level MEDKNOW Dummy variable that takes the value 1 if the participantanswers correctly to more than six or seven out of eightstatements about MG; and 0 otherwise

Low knowledge level LOWKNOW Dummy variable that takes the value 1 if the participantanswers correctly to less than six statements out of eightabout MG; and 0 otherwise

White bean consumption CONSUMP Continuous: quantity purchased in the last three monthsGender GENDER Dummy variable that takes the value 1 if the participant is

male; and 0 if it is femaleAge ELDER Dummy variable that takes the value 1 if the participant is

between 50 and 66 years old; and 0 otherwiseADULT Dummy variable that takes the value 1 if the participant is

between 35 and 49 years old; and 0 otherwiseYOUNG Dummy variable that takes the value 1 if the participant is

between 18 and 34 years old; and 0 otherwiseIncome HIGHINC Dummy variable that takes the value 1 if the participant’s

income is more than 3000e/month; and 0 otherwiseMEDINC Dummy variable that takes the value 1 if the participant’s

income is between 1,000 and e3,000/month; and 0otherwise

LOWINC Dummy variable that takes the value 1 if the participant’sincome is lower than e1,000/month; and 0 otherwise

Household size HOUSESIZ Dummy variable that takes the value 1 if the householdsize is higher than four members; and 0 otherwise

Profession PROFESS Dummy variable that takes the value 1 if the participant isemployed or self-employee; and 0 otherwise

HOUSWIFE Dummy variable that takes the value 1 if the participant ishousewife; and 0 otherwise

STUDENT Dummy variable that takes the value 1 if the participant isstudent; and 0 otherwise

PENSION Dummy variable that takes the value 1 if the participant ispensioner; and 0 otherwise

UNEMPLOY Dummy variable that takes the value 1 if the participant isunemployed; and 0 otherwise

Education level EDUCAT Dummy variable that takes the value 1 if the participanthas a university degree; and 0 otherwise

SECOND Dummy variable that takes the value 1 if the participanthas a secondary degree; and 0 otherwise

PRIMARY Dummy variable that takes the value 1 if the participanthas a primary degree; and 0 otherwise

(continued )

Table III.Variables used in thespecification and theestimation of the sampleselection model

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Dependent variables Name Description

Price perception HIGPRICE Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the price a score. ¼ 8; and 0 otherwise

MEDPRICE Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the price a scorebetween 5 and 7; and 0 otherwise

LOWPRICE Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the price a score ,5;and 0 otherwise

Texture HIGHTEXT Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the skin texture ascore . ¼ 8; and 0 otherwise

MEDTEXT Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the skin texture ascore between 5 and 7; and 0 otherwise

LOWTEXT Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the skin texture ascore ,5; and 0 otherwise

Smell HIGHSMEL Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the smell a score. ¼ 8; and 0 otherwise

MEDSMELL Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the smell a scorebetween 5 and 7; and 0 otherwise

LOWSMELL Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the smell a score , 5;and 0 otherwise

Creaminess HIGCREAM Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the creaminess ascore . ¼ 8; 0, and 0 otherwise

MEDCREAM Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the creaminess ascore between 5 and 7; and 0 otherwise

LOWCREAM Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the creaminess ascore , 5; and 0 otherwise

(continued ) Table III.

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Dependent variables Name Description

Cooking time HIGHTIME Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the cooking time ascore . ¼ 8; and 0 otherwise

MEDTIME Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the creaminess ascore between 5 and 7; and 0 otherwise

LOWTIME Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the creaminess ascore , 5; and 0 otherwise

Previous experience HIGHEXP Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the previousexperience a score . ¼ 8; and 0 otherwise

MEDEXP Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the previousexperience a score between 5 and 7; and 0 otherwise

LOWEXP Dummy variable that takes the value 1 if the participant,when valuing the different attributes of the white bean inan ordinal scale of 0 to 10, assigns to the previousexperience a score ,5; and 0 otherwise

Alimentation as culturaltie

F11 Continuous. First factor from a factor analysis carried outon a 16-item Likert scale to measure participants’ attitudesto food

Interest to cooking F12 Continuous. Second factor from a factor analysis carriedout on a 16-item Likert scale to measure participants’attitudes to food

Willingness-to-pay morefor higher quality food

F21 Continuous. First factor from a factor analysis carried outon a nine-item Likert scale to measure participants’attitudes to food prices

High importance of pricein food purchase

F22 Continuous. First factor from a factor analysis carried outon a nine-item Likert scale to measure participants’attitudes to food prices.

Leaflet LEAFLET Dummy variable that takes the value 1 if the participantreceived a written information on the characteristics of theMG; and 0 otherwise

Taste TASTE Dummy variable that takes the value 1 if the participanttasted the MG; and 0 otherwise

No reference prices NOPRICE Dummy variable that takes the value 1 if the participanthas not been exhibited to any price information; and 0otherwise

Prices of conventionaland PDO white beans

CHPRICE Dummy variable that takes the value 1 if the participanthas been exhibited to an information on both conventionaland high value white bean; and 0 otherwiseTable III.

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To discard the hypothesis that the no statistical significance of the difference inparticipants’ WTP before and after receiving the leaflet information or tasting theproduct is generated by the aggregation of data, we checked for a possible taste or leafletinformation effect at the individual level. Regarding the leaflet information effect wefound that 13 per cent of participants negatively responded to the leaflet information, 17percent of participants positively responded to the information included in the leaflet and70 percent did not change their WTP after receiving the leaflet information. However,neither the decrease nor the increase in the WTP was found significant. Concerning thetaste, we found that 31 percent of participants decreased their WTP after tasting theauctioned product, 38 percent of participants did not change their WTP after tasting theproduct and 31 percent of participants were affected positively by the product taste.However, neither the increase nor the decrease of the participants’ WTP generated bytasting the product was significant. This result can be explained by the learning effect,which seems to offset the effect of releasing new information. The learning effect hasbeen examined in Shogren et al. (1994, 2000) who showed that as the rounds go on,participants tend to significantly decrease their bids.

Treatment Mean Significance level

No reference pricesPrices of conventional white beansPrices of conventional and PDO white beans

2.862.763.63

0.004

Comparison of means: Bonferroni testTreatment Significance levelPrices of conventional and PDO white beans No reference prices

Prices of conventional white beans0.0180.006

Table IV.Sensitivity of bids to

reference prices

Figure 1.Average

willingness-to-pay in eachround for the MG

Mean Round 1 to 4 Mean Round 5 to 8 Significance level

No information 2.29 2.11 0.29Leaflet 2.75 2.46 0.35Taste 3.40 3.34 0.44

Table V.Sensitivity of bids for theMG to leaflet information

and taste

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4.2 Potential market and factors affecting the willingness-to-pay for the MGFigure 2 shows the distribution of frequencies for the average bids made byparticipants during the last four rounds, allowing for homogeneous comparisonsamong treatments[6]. As mentioned in the previous section, the additional informationon the auctioned product was provided at the end of the fourth round, enabling us alsoto compare the effects of the introduction of such information.

Considering the average market price for the conventional white bean shown infootnote 4, results from Figure 2 suggest that 53 percent of the participants are notwilling-to- pay an extra price for the MG. In general terms, the WTP is significantlydifferent (at 1 percent significant level) depending on the level or frequency ofconsumption. In this sense, regular consumers reveal an average WTP of 4.88 euros,while occasional consumers and non-consumers are only willing to pay 2.71 and 2.53euros, respectively, on average.

Of all participants 35 percent are willing to pay a price between 3 and 6 euros/kg.This price range is higher than the price for the conventional product, but is below theprice for the MG at bulk paid directly to the producer or in local markets, which isaround 6 euros/kg. In general terms, it is a segment of consumers heterogeneouslymixed between young and elder persons, frequent buyers of white beans (70 percent),and occasional consumers of MG. The majority are employed and 85% earn an averagesalary between 1,000 and 2,000 Euros per month. Taking into account the results fromthe questionnaire, this segment is willing to pay additional money if the productprovides them higher quality. In fact, participants in this segment assign (on a scalefrom 0 to 10) an average score of 8.70 to the phrase: “I’ll pay more if the product has aguaranteed quality” and 7.85 to the phrase: “I don’t mind paying more if the producthas more quality”.

Only 7 percent of the participants are willing to pay between 6 and 9 euros for theMG. In other words, this is the real market potential for the auctioned product as theprice premium is over the minimum market price you may purchase the MG directly tothe producer or usually in the local market, in bulk[7]. All members in this segment areregular consumers of MG. Around 50 percent are between 35 and 49 years old and havea university degree. All are employees and have monthly earnings between 2,000 and3,000 euros. At the same time, these are the consumers that provide a higher valuation(in a scale from 0 to 10) to the phrases: “ I’ll pay more if the product has a guaranteed

Figure 2.Average willingness topay for the MG (%)

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quality” and “I don’t mind paying more if the product has more quality” (9 and 8.25,respectively). The previous experience (score of 9.67), the product creaminess (9.50) andthe texture of the skin (8.75) are the principal attributes influencing their decision topurchase the MG white bean.

As mentioned in the introduction, in this study we are not only interested inknowing the willingness-to-pay a price premium for the MG, but also in analyzing thefactors affecting WTP. In this study, the price premium is measured as the difference(denoted by “y”) between the average bid for each individual in the last four roundsand the average price of the conventional brands of white beans used in theexperiment[8]. If the difference lies between the average and one positive or negativestandard deviation, we assumed that the WTP is zero. In our case, only 13 percent ofthe average bids were not statistically different from the average price of theconventional white beans.

Since the price premium is censored at zero and the decision with respect to the pricepremium each individual is willing-to-pay may be preceded by a decision to pay or notto pay, an extra price, a bivariate “Sample selection” model (also known as Tobit modelType II, see Amemiya (1984)) fits adequately for the purpose of this study. A briefdescription is provided in the following paragraphs.

As has been mentioned, it is assumed that each participant makes two sequentialdecisions:

(1) To pay or not to pay a price premium for the MG. This decision can berepresented by a dichotomous variable that equals 1, if the individual iswilling-to-pay a positive price premium, and 0, otherwise; that is:

d1;i ¼

1 if y*

1;i . 0

0 if y*

1;i # 0

8>>><>>>:

;i ¼ 1; :::N

being y *1,i the difference between the average bids made by each individual in

the last four rounds and the average market price of the conventionalcounterpart. This variable is not censored and can take both positive andnegative values.

(2) Once the participant has decided to pay an extra price (y *1,i . 0), he or she

decides what price premium is willing to pay. That is;

y2;i ¼

y*

2;i if y*

1;i . 0

0 if y*

1;i # 0

8>>><>>>:

;i ¼ 1; :::N

being y *2,i the overprice that he or she is willing to pay, that is observable if and

only if y *1,i . 0. Taking this into account, the Sample Selection model is defined

as the following:

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y*

1;i ¼ x1;ib1 þ 11;i

d1;i ¼

1 if y*

1;i . 0

0 if y*

1;i # 0

8>>><>>>:;i ¼ 1; :::N

y*

2;i ¼ x2;ib2 þ 12;i

y2;i ¼

y*

2;i if d1;i ¼ 1

0 if d1;i ¼ 0

8>><>>:

where xj;i ¼ x1j;i:::x

kj

j;i

� �j ¼ 1; 2 are vectors of explanatory variables corresponding to

each decision; bj ¼ bj;1:::bj;kj

� �‘[ R kj ; j ¼ 1; 2 are vectors of parameters to estimate;

and, finally 1j;i, which are assumed to be normally distributed ðN 0;s2j

� �; j ¼ 1; 2Þ such

that E 11;i12;i

� �¼ s12;i ¼ 1:::N . Model (1) is estimated by Maximum Likelihood (ML).

As can be observed, we described in both decisions the information we used todefine the dependent variables. However, the treatment of such information is differentin both equations. In both cases, as mentioned in the first paragraph of this section, wecomputed the average price premium participants are willing-to-pay for the MG.However, while in the first equation this information has been treated as a dichotomousvariable, the second one has only positive values.

Regarding the explanatory variables, and taking into account the informationobtained from the survey, they can be grouped in two main categories: socioeconomicand psychographic characteristics of participants, and purchasing and consumptionhabits related to both white beans and the MG. Most of the variables were transformedinto binary form in order to avoid the problems derived from the use of ordinal scalesin the regression analysis. Table III shows the description of all the variables that havebeen considered as having a possible influence on the willingness to pay a pricepremium for the MG.

Results from the estimated Sample Selection model are shown in Table VI. Amongall the variables included in Table VI, nine estimates were statistically significant.Before interpreting the estimated parameters, we note three previous considerationsabout the estimation procedure. The first one has to do with the estimation of the rparameter, which measures the correlation between equations. This parameter is notstatistically significant indicating that the selection bias is not a relevant problemwhen estimating the second equation. The second consideration we want to make isthat the interpretation of the magnitude of the estimated parameters in the firstequation has to be done with caution because of the qualitative nature of the dependentvariable. We consider only the signs of the parameters, not the changes in theprobability of paying a price premium, for the purpose of our discussion of the generalresults. Finally, note that none of the explanatory variables are simultaneouslyincluded in both decisions.

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In the decision whether to pay or not to pay a price premium (first equation),employment and the education level were the only socio-demographic variables thatsignificantly affect the probability of paying a premium for the MG. In the case ofeducation level, the negative sign of the parameter indicates that as the education levelof the participant increases, his or her probability to pay a price premium for the MGdecreases. This result has to be interpreted taking into account the nature of theauctioned product. The auctioned white beans require a minimum of two hourscooking. Participants with higher education levels have less free time for cooking and,hence, convenience becomes a relevant attribute[9]. As a consequence, theseparticipants have a lower probability to shop, which would explain the negativesign found in the estimated model. Regarding the employment effect, the positive signof the parameter shows that participants who are employed have a higher probabilityof entering the MG market than others.

As expected, the consumption level of white beans (the low knowledge about theauctioned product) positively (negatively) affects the probability to pay a pricepremium for it. In fact, as shown in Table VI, those participants that have declared inthe survey a higher consumption level of white beans have a higher probability to paya higher price premium. At the same time, those participants who have a higher level ofknowledge about the MG present a higher probability of paying a higher price for sucha product. This result suggests the need to provide more and better informationregarding the product from producers to consumers with the aim of increasing themarket potential for MG. In this sense, the mass media in Barcelona has recentlystarted to pay attention to current research aimed at improving the organolepticcharacteristics of the MG.

Among the MG attributes, two have resulted in having a significant effect on theprobability of participants’ willingness-to-pay a price premium. The first one is price.

Variables Estimated value Pr . jtj *

First equation (DWTP)CONSTANT 0.598 0.30LOWKNOW 20.734 0.04CONSUMP 0.184 0.01PROFESS 0.763 0.07EDUCAT 21.280 0.01HIGHTIME 21.084 0.04HIGHEXP 1.005 0.02F21 0.473 0.02HIGPRICE 20.927 0.01

Second equation (PWTP)CONSTANT 1.066 0.02FREQMG 2.192 0.00LOWPRICE 0.392 0.44s22 1.287 0.00Rho 0.009 0.99Pseudo R 2 0.3125

Note: *The test statistic used is the t-test

Table VI.Estimated parameter of

the sample selectionmodel

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The negative sign indicates, as expected, that when the price of the product plays a keyrole in the consumer decision process, the probability of paying an extra price for theMG decreases, as this variety is relatively more expensive that other substitutes. Thesecond relevant attribute is “convenience”, which has a negative effect over theprobability of participants’ WTP. In other words, the participants who highly valuecooking time when purchasing white beans are less likely to buy the MG since itrequires more care cooking than the conventional counterpart.

Previous experience also plays a relevant role in purchasing decision. In this sense,participants that have given a higher score to this attribute are more likely to pay aprice premium for the MG. Finally, among the four attitudinal variables that have beenintroduced initially in the model, only the variable “willingness-to-pay more for higherquality food” has a significant effect. The positive sign indicates that participants whoare willing to sacrifice money in exchange for an improvement in the quality of thefood, are also more likely to pay more for the MG.

Once the consumer decides to pay an extra price for the MG, the second decision isto determine how much to pay with respect to the conventional product. The resultsobtained in the estimation of the model show that this decision is solely based on theparticipants’ experience with MG. That is, after deciding to participate in the market,being a usual or an occasional consumer is the main determinant of the WTP a pricepremium. The positive sign of the parameter indicates that the more experience theconsumer has (usually but not only associated to a better knowledge of market prices,as consumption away-from-home plays an important role in this case), the higher is theamount of money that he or she is willing to pay for the product.

5. Concluding remarksIn this study, we evaluated consumers’ WTP for a typical local food product, “MongetaGanxet of Valles Maresme” (MG) and the factors that influence their WTP using anexperimental auction in Barcelona. Results suggest that the market for MG is stillrelatively small considering that around half of the participants are not willing to pay aprice premium for MG, despite acknowledging the organoleptic quality of the product.Furthermore, only 7 percent of participants are willing to pay a price higher than theminimum price for which the MG may be purchased directly from a producer or in thelocal market. This segment consists of middle to high-income consumers who have ahigh degree of knowledge about the product. Results also suggest that thepsychographic characteristics of the participants are more relevant than theireconomic characteristics in influencing WTP. Moreover, as expected, the likelihood ofpurchasing the product increases with experience with the product. Results indicatethat a better knowledge about the product and more experience in the consumption ofMG increase the probability of paying a price premium for such product. This resultreinforces the necessity of developing promotional campaigns targeted at specificsegments of the population.

Interestingly, price and convenience attributes negatively affect the probability ofan individual paying more for MG. In relation to the first attribute, while in manystudies convenience plays a positive role (or, at the worst, no significant role) inexplaining the WTP for a high-value food product, in this study the relationship isnegative, perhaps due to the cooking time required for the product (which is aroundtwo hours with the need for constant inspection). As per the price, while in many

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studies prices of high-valued food products lie between one or two times the price of theconventional counterparts, the price of MG is around seven times more expensive thanthe price of conventional white beans. Hence, careful communication and promotionstrategies should be designed when explaining the reasons behind such pricedifferentials. Further research is also needed to improve the convenience attribute ofthe product as this will limit its potential to capture an increasing share of the market.

Notes

1. Gil and Soler (2006) is the only published work in this area.

2. A comparison of the alternative methods is out of the scope of this study as there is anelaborated debate in the literature about the advantages and disadvantages of each method.Cropper and Freeman (1991), Lee and Hatcher (2001), Bateman et al. (2002) and Lusk andHudson (2004), among others provide a good literature review on these issues.

3. The questionnaire is available from the authors on request.

4. For a definition of each one of these mechanisms and their implementation in practice, seeVickery (1961), Becker et al. (1964), Shogren et al. (2001) and Lusk et al. (2004). Actually,BDM is a lottery game rather than an auction. However, it does share with Vickrey andrandom nth price auctions the preference revealing property.

5. In order to determine reference prices, 1 kg package of three brands of conventional whitebeans and two PDO white beans were actually purchased for the purpose of the experimentin two supermarkets in Barcelona, with prices of 1.03, 1.92 and 2.62 euros, for theconventional beans and 12.14 and 14.75 euros, for PDO beans, respectively. The election ofthe purchased brands was made in a random form, without consideration of market share,but taking into account the retail price distribution.

6. We present the results in intervals from original values in order to facilitate theinterpretation of Figure 2.

7. In any case, no participant manifested paying the real market price for the auctioned productin a cloth bag, which was 11.60 euros/kg.

8. As we do not have a single reference price for the conventional product.

9. Results obtained from both a preliminary focus group and the implementation of the pilotquestionnaire indicated that among the different attributes consumers look for whenpurchasing white beans, respondents with higher education level ranked convenience amongthe highest valued attributes.

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Corresponding authorFaical Akaichi can be contacted at: fakaichi@uark.edu

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