The relevance of origin information at the point of sale

Food Quality and Preference 26 (2012) 1–11

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

The relevance of origin information at the point of sale Adriano Profeta a,⇑, Richard Balling b, Jutta Roosen c a

Cluster Food, Hofer Straße 20, 95326 Kulmbach, Germany Bayerisches Staatsministerium für Ernährung Landwirtschaft und Forsten, Ludwigstraße 2, 80539 München, Germany c Technische Universität München, Marketing and Consumer Research, Alte Akademie 16, 85350 Freising, Germany b

a r t i c l e

i n f o

Article history: Received 25 March 2011 Received in revised form 28 February 2012 Accepted 3 March 2012 Available online 14 March 2012 Keywords: Country-of-origin Point-of-sale Discrete-choice Consumer behaviour PDO PGI

a b s t r a c t Recently, Liefeld (2004) questioned both the importance of a product’s country of origin (CO) in consumer purchase decisions and the core findings in this area of study. He criticised CO studies for relying on obtrusive attitude measures of independent and dependent variables in non-purchase contexts. Therefore, he offered the following conclusion: ‘None of the published CO research reports what consumers do, when choosing between product alternatives’. In this study, we followed the recommendations of Liefeld (2004) and applied his ‘knowledge test approach’ for packaged meat, dairy products and beer in four outlets of the largest German food retailer, EDEKA. To this end, purchasers were intercepted as they exited the cash register with a purchase. In this study, we aimed to determine whether origin plays a role in consumer decisions to purchase food and whether there are differences in consumer awareness of the origin of different product categories. As a second step, a Controlled Store Test (CST) with the protected geographical indication (PGI) of Bavarian beer was conducted to highlight the assumption that origin is important, even in real market scenarios. The results of the ‘knowledge test approach’ demonstrated that origin may play a role in the choice among available packaged meat, dairy products and beer for approximately one-fifth of the consumers in this survey. Furthermore, the CST revealed that consumers are willing to pay an additional € 2.00–€ 2.60 per crate of beer if such crates are labelled with the GI Bavarian beer designation. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction In this study, we apply the ‘knowledge test approach’ of Liefeld (2004) to determine whether origin plays a role in consumer decisions to purchase food and beer and whether there are differences in consumer knowledge regarding the origins of different food categories. Additionally, we present a Controlled Store Test (CST) for the geographical denomination of Bavarian beer to verify the assumption that origin is important in the real market. Over the last few decades, various studies have been conducted to investigate the influence of product origin on consumer product evaluations and purchase intentions (Alfnes, 2004; Han & Terpstra, 1988; Papadopoulos & Heslop, 2002; Roth & Romeo, 1992; van Ittersum, 2001; Verlegh & Steenkamp, 1999b). Recently, Liefeld (2004) questioned the importance of the country of origin (CO) in the decisions of consumers and the core findings in this area of study. He criticised CO studies for relying on obtrusive attitude measures of independent and dependent variables in non-purchase contexts. Therefore, he concluded the following: ‘None of the published CO[P] research reports what consumers do, when ⇑ Corresponding author. E-mail addresses: [email protected] (A. Profeta), richard.balling@ stmelf.bayern.de (R. Balling), [email protected] (J. Roosen). 0950-3293/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.foodqual.2012.03.001

choosing between product alternatives’. As a consequence, he noted that such studies have serious limitations, such as external validity and generalisability issues. To test his hypothesis of CO overestimation, Liefeld (2004) conducted a survey in US and Canadian stores in both shopping malls and general merchandise and hardware outlets, such as Wal-Mart, Home Depot and Canadian Tire. Consumers were asked directly behind the register about the origin of the non-food products that they had purchased. Only 8 per cent of the consumers leaving the cash register were aware of the CO of the purchased products. CO played a role in the product choices of only 33 per cent of those customers (2.6 per cent of the total sample group). In addition to presenting these empirical results, Liefeld (2004) argued that the reality of the marketplace does not correspond to the findings and conclusions of academic researchers regarding the importance of CO in consumer choice. As an example, he referred to low-priced imports that have saturated the American market and shifted production capacities to foreign countries. Furthermore, he cited several meta-analyses that found that the research in this area has provided little generalisable knowledge (Obermiller & Spangenberg, 1989; Peterson & Jolibert, 1995; Verlegh & Steenkamp, 1999a). As a first step in this paper, we follow the recommendation of Liefeld (2004) to replicate his methodology for other product types,

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such as packaged food and alcoholic beverages. Kemp, Insch, Holdsworth, and Knight (2010) previously applied an approach that is similar to the approach of Liefeld (2004) to study fresh products in Britain. In their study, 17.1 per cent of the respondents indicated that their knowledge of the CO had influenced their purchase decisions, and 8.8 per cent of the respondents stated that they had intentionally chosen British products. These results suggest that the CO or region of origin (RO) may have greater relevance in the food sector than in the non-food sector. Furthermore, in Europe, origin-labelled products represent a sizable share of the total turnover in the food sector (Profeta, Enneking, & Balling, 2006). For many of these products, consumers are willing to pay premium prices (Arfini, 2003). Additionally, with regulation (EC) 510/06, the EU created special legislation that protects geographical indications (GIs) in the food sector against misuse by producers that are located outside of a defined production area (Profeta, 2006; Profeta & Balling, 2007, 2009; Profeta, Balling, Schoene, & Wirsig, 2010; Profeta et al., 2006). In 2010, the number of protected GIs in the food sector exceeded 1000 denominations. For more than 15 years, the European Union (EU) has been expanding the register of protected GIs (PGIs) and protected designations of origin (PDOs) for agricultural and food products. Both denominations represent the names of regions or specific places that are used for agricultural products or foodstuffs that originate from the respective region or place. For PDOs, regulation (EC) 510/06 requires that the production, processing, and preparation (i.e., all of the steps that are necessary to make a product) must occur in a defined geographical area, whereas for PGIs, it is only necessary that one of these steps occurs in a specific area. This registry and the underlying European Community regulation (EC) 510/06 (replacing European Economic Community (EEC) regulation 2081/92) are two of the major instruments of active quality policy and consumer protection (Bayerisches Staatsministerium für Landwirtschaft und Forsten (BStMLF, 2008; Josling, 2006; Profeta, 2006; Profeta et al., 2006). More than 90 per cent of the registered PDO/PGI denominations describe a regional origin rather than a country of origin. According to regulation (EC) 510/06 Article 2(1) (a) and (b), a geographical indication or a designation of origin refers to the name of a region, a specific place or, in exceptional cases, a country that is used to describe an agricultural or food product. Thus, the CO is a rarely used exemption in this legal framework. The encouragement of such designations, which indicate aboveaverage quality under the regime of regulation (EC) 510/06, has become an important part of the transition of the Common Agriculture Policy from a bundle of instruments to support commodity markets (generic products) to a policy that enables producers to market goods (differentiated products) that satisfy consumer tastes. Furthermore, this legal framework allows consumers to make their own informed decisions. According to Josling (2006), this shift toward quality and marketable goods was promoted by public policy and resulted from a growing awareness among farmers and the food industry that the market for undifferentiated commodities is declining. Currently, there is a Greenbook discussion regarding modification of the quality and labelling rules of the EU in the food sector (http://ec.europa.eu/agriculture/quality/policy/index_de.htm, 15/08/10). Furthermore, the mandatory origin labelling of all raw material ingredients is discussed by the stakeholders (http://ec.europa.eu/agriculture/quality/policy/consultation/contributions/summary_en.pdf, p. 12, 15/08/10). Despite progress in methodology (Alfnes, 2004; Bonnet & Simioni, 2001; Kim, Veemann, & Unterschultz, 2000; Mtimet & Albisu, 2006; Perrouty, Hauteville, & Lockshin, 2006; Profeta, 2006; Profeta, Enneking, & Balling, 2008; Scarpa, Philippidis, & Spalatro, 2003; Ward, Briz, & Felipe, 2003), even today, most consumer studies of CO and RO, as mentioned above, are primarily

based on hypothetical data from purchase experiments that often lack generalisability. Therefore, in this study, we applied the ‘knowledge test approach’ of Liefeld (2004) for packaged meat and dairy products and beer in four outlets of the largest German food retailer, EDEKA. For this purpose, consumers were interviewed as they exited the cash register with a purchase. We conduct a test to determine whether origin plays a role in consumer decisions to purchase packaged meat and dairy products and beer and whether there are differences in the awareness of consumers regarding the origin of these analysed product categories. We do not distinguish between CO and RO in the analysis. As a second step, to verify the assumption that origin is important in the real market, we present the results of a Controlled Store Test (CST) of the PGI Bavarian beer. The CST occurred two years prior to the knowledge test, and both studies were originally conducted independently of one another. Nevertheless, we consider the presentation of the corresponding results within a single paper to be reasonable because the CST confirms a priori the findings of the knowledge test under more realistic market conditions. Rather than conducting discrete choice experiments that are based on hypothetical decisions (stated preferences), we chose to conduct a CST directly at the point of sale, where the price, labelling or packaging is varied according to an experimental design plan. This approach enables us to observe and analyse consumer purchase behaviours in a real market situation (revealed preferences). The CST can be applied to measure the true effects of price, packaging or origin labelling variations and the corresponding willingness to pay for these characteristics. For this reason, we attempted to measure real purchase behaviour rather than origin awareness. It would be possible to conduct a hedonic price analysis by examining the labelling and prices of origin-labelled products in the market, but for this type of data, the necessary price variation in the market is often missing, and this absence of variation causes multicollinearity problems. Because of the experimental design, no such problems occur for the CST. In contrast with hypothetical discrete choice analyses with stated preferences, CST is also advantageous because this approach does not result in problems related to the underestimation of the price parameter due to missing budget restrictions (Harrison & Rutström, 2008, chap. 81; List & Gallet, 2001). Therefore, in this study, we employ a (non-hypothetical) store test to analyse the influence of the Bavarian beer RO label. Before the methodologies and results of the two studies are presented in detail, the economic relevance of our findings is discussed, and an overview of CO/RO theory and some empirical origin studies is given. These studies examine or attempt to explain why the CO/RO effect varies across different product groups. This section will explain why origin may be more important in the food sector and identify food product groups that are of special interest for the applied knowledge test approach that is used in this study.

2. The potential economic relevance of origin labelling and the reasons that origin effects may vary by product category To determine the economic relevance of our findings, we first considered the product categories in which general private consumer expenses are made. We agree with Liefeld (2004) that household expenditure data (in Germany as in the US) reveal that the majority of household expenditures are in product categories in which CO/RO cannot play a role in the choice process (e.g., food that is purchased away from home, housing, household operation, vehicle operation, public transportation, healthcare, personal care, education, personal taxes, personal insurance and pensions, and charitable donations). Liefeld stated that approximately 20 per cent of total household expenditures in the US and Canada are in

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expenditure categories in which some proportion of the goods that are available in the marketplace are imported; thus, CO/RO could be used as a criterion in the choice process. For Germany, this value is higher (approximately 40 per cent) if we consider the product groups of food and non-alcoholic and alcoholic beverages, including spirits and wine (see Table 1). In this context, it is interesting to note the results of the study of Schneider and Holzberger (2006), who argued that in some food product categories, Austrian consumers have strong preferences for foreign products (e.g., Swiss or Greek feta cheese and French or Californian wine) that account for 5–10 per cent of the total turnover of food in Austria. Furthermore, these authors estimated that Austrian consumers have the opportunity to choose between Austrian and foreign food products for an additional one-third of their consumption. If one also considers that consumers in the food sector can both distinguish between food from their home country and food from other countries and differentiate between different regional origins within their own home country, then it becomes clear that origin may play a more decisive role in purchases in the food sector than was found by the estimations of Liefeld (2004) for non-food product categories. Regarding the CO literature, some empirical studies have assessed the differences in CO effects among products (Hampton, 1977; Nagashima, 1970, 1977; Yaprak, 1978). However, Obermiller and Spangenberg (1989) were the first researchers to present a theoretical framework for the measured differences. From our perspective, their considerations can also be transferred to regional origins.

Table 1 Private consumer expenses in CO-relevant categories in billions of euros. Product category

Food and alcohol-free beverages Spirits Wine Beer Alcoholic soft drinks (vol.% <6) Tobacco Cloth Clothes Shoes and shoe accessories Furniture, interior design, and carpeting Home textiles Large electronic household devices Small electronic household devices Glass-, crystal- and tableware Flatware, cutlery and silverware Kitchenware and household appliances Motor-driven tools and devices Gardening tools and hand tools Consumer items for housekeeping Purchase of motor vehicles Telephone and fax devices Devices for reception, recording and replay in sound and vision Photographs, photo equipment, optical devices and accessories Data processing devices Image and sound carriers P Tot. exp. in CO-relevant categories

Expenses

Proportion of CO-relevant categories (%)

141.83 5.64 6.68 7.58 0.08 23.21 0.54 51.64 10.22 36.12 6.69 8.60 2.06 1.77 0.83 4.58 1.91 5.43 8.74 72.97 1.48 9.19

33.67 1.34 1.59 1.80 0.02 5.51 0.13 12.26 2.43 8.57 1.59 2.04 0.49 0.42 0.20 1.09 0.45 1.29 2.07 17.32 0.35 2.18

2.67

0.63

6.69 4.13 421.28

1.59 0.98 100

38.41

Proportion of CO-relevant categories of total consumer expenses in Germany (%) Total consumer expenses in Germany

1289.77

Source: Federal German Office for Statistics (DESTATIS), 2010.

32.66

3

Obermiller and Spangenberg (1989) named four product groupspecific factors that influence the importance of GI labelling in choices, namely product category heterogeneity, country brand heterogeneity, the clarity of the CO label and the availability of other information. In their model, product category heterogeneity indicates the magnitude of the variation of the products (brands) within a product category in relation to the most important characteristics that are relevant to a purchase. In this context, this consideration is not limited to a single country; rather, it extends across countries. An example is the worldwide production of beer. In several countries or regions of the world, numerous producers brew beer with different qualities and tastes. For example, in Bavaria, barley or wheat malt is typically used (Bavarian Purity Law). In the US or Asia, maize, rice and sugar are sometimes used as starch sources for the fermentation process. Therefore, there is a high level of product category heterogeneity in worldwide beer production. Such heterogeneity in the purchase-relevant characteristics of a product group is necessary. If such heterogeneity were not present, then the CO, brand or other attributes could not be an indicator of product quality because quality or taste differences would be negligible (Johansson, 1988). It is plausible that when production technology is standardised and markets are homogeneous (thus, products are undifferentiated), there would be little need for customers to explore CO factors. In this context, Manrai, Lascu, and Manrai (1998) conducted an empirical study of 18 product groups and 21 countries and demonstrated that product category heterogeneity often exists, especially in product markets (e.g., luxury cars and food specialties) that are characterised by high levels of fragmentation (Guiles, 1989). Conversely, many categories are commonly characterised as homogenous (Jones, 1994). For example, compact disc players are found in a category in which brands have numerous common attributes. Stereo reviewers tend to evaluate these products as essentially similar (Consumer Reports., 1989). According to Cordell (1992), the same similarity holds for shoes, in which consumers perceive only small differences in the ability of various countries to produce these products with different levels of quality. In the study that was conducted by Liefeld (2004), the aforementioned product groups (shoes and electronic entertainment devices, such as compact disc players), which belong to rather homogenous product groups, accounted for approximately 20 per cent of the analysed product sample group. In contrast with product category heterogeneity, the second factor (country brand heterogeneity) relates to the degree of variation in the purchase-relevant characteristics of the different brands of a product category within a country. For new products, the CO effect might superimpose the brand effect such that the technology is no longer firm-specific but becomes country-specific (Cordell, 1992). In the beer example, because of the Bavarian Purity Law and the compulsory specification of the code of practice for the PGI Bavarian beer (http://ec.europa.eu/agriculture/quality/door/document/ Display.html?chkDokucment=285_1_en, 15/08/10), which allows only barley, wheat, malt, water and hops in the brewing process, this GI has resulted in a high level of regional brand homogeneity. In general, product category and country brand heterogeneity depend on the aggregation status of a specific product group. For example, for fruits or vegetables that consist of many different products, the country brand homogeneity would not be as high as, for instance, that of bananas or apples (Balling, 2004). According to Obermiller and Spangenberg (1989), a certain level of country brand homogeneity, which exists for the above-mentioned Bavarian beer, is important for CO (or RO) perceptions because consumers will use origin as a choice indicator only when the variation between the brands of a product group within a country or region is low. If there is a high level of country or regional

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brand heterogeneity, then the information content of an origin label is reduced due to a loss of clarity. Individuals use the information that can be most rapidly identified to evaluate quality (Bruner, Goodnow, & Austin, 1956). A loss of clarity in origin labels due to a high level of heterogeneity in country or regional brands results in the origin no longer serving as a quick identification symbol of the quality of a product; therefore, other information that is simpler to interpret is used. In the interplay of the two aforementioned constructs, the largest origin effect can be expected for a product group in which there is a high level of brand homogeneity for a certain country or region and a high level of product category heterogeneity across countries or regions. ‘Unless all countries cover all the niches, the made-in label will carry significant information’ (Johansson, 1988). For the food sector, regulation (EC) 510/06 contributes to the clarity of PGIs. Because every PGI must fulfil high mandatory quality standards and process requirements that apply to an entire protected production area, there exist high levels of regional brand homogeneity. The clarity of a PGI is enforced by the prohibition of the misuse of the designations through inexpensive imitation and branding with an official EU logo. No similarly strong legal framework for GI exists in the non-food market. In addition to product category heterogeneity and country brand homogeneity, which determine CO/RO clarity, the importance of information pertaining to origin also depends on the availability of additional information. Consumers will rely on origin labels only if no better indicator to evaluate the product is available (Obermiller & Spangenberg, 1989). If additional extrinsic characteristics, such as brands and quality labels, or intrinsic key characteristics are available, then these characteristics will be considered only if they are better suited for determining the value (quality) of a product (Wheatley, Chiu, & Goldman, 1981). Consistent with this finding, Kühn (1993) and Balling (1995) established that RO effects are particularly likely to appear when specific market (e.g., brand) and price information is absent. In this context, it is interesting to consider the textile product group, which accounted for more than 25 per cent of the product sample in the study of Liefeld (2004). According to Ettenson, Wagner, and Gaeth (1988), CO is unimportant in apparel purchase decisions, and there is an array of product attributes that have greater weight than this characteristic. The same result was obtained by Gipson and Francis (1991) regarding sweater-purchasing decisions. The attributes of fit and colour or the coordination of a sweater with one’s existing wardrobe is of the greatest importance, whereas the relevance of the country of origin is negligible. As previously shown, the availability of additional information can be considered a product group-specific factor. In the food sector, some product categories have few or no well-known brands (e.g., meat products in Germany). In contrast, some product groups (e.g., soft drinks) are dominated by strong brands that can be used in the evaluations of such products. Additional information pertaining to origin may be less important for well-known brands than for less well-known brands (Schaefer, 1997). In this context, even brands can be interpreted as origin cues; thus, brand and origin effects are sometimes mixed (Liefeld, 2004; Profeta et al., 2010). Especially for agricultural products, less processed food (e.g., beef) and generics in general, it is often difficult and costly for a producer to highlight its own product quality with a brand (Roosen, Lusk, & Fox, 2003). When one considers the product differentiation in Germany for beef, it is clear that well-established brands in this sector are only of marginal importance. Roosen et al. (2003) stated that brands in Germany are not important for consumer purchases of beefsteaks, whereas origin is the most important characteristic in comparisons of extrinsic and intrinsic product characteristics. The same observation applies to milk products. In a recent empirical consumer study that was conducted

by the Technical University of Munich (Profeta, 2009), origin was found to be the most important factor in purchase decisions, followed by expiration date and price, and brand information was ranked the lowest in importance. The given overview of the reasons for the CO effect differences among product groups shows that a high percentage (20 per cent + 25 per cent = 45 per cent) of the product sample of the Liefeld (2004) study consisted of products that are perceived as rather homogenous across countries. We assumed the same reasoning for the remaining product groups that were analysed by Liefeld (2004), but we could not find empirical results to support our assumption. In this situation, the theory of Obermiller and Spangenberg (1989) predicts no or only negligible effects from CO labelling. In contrast with this prediction but consistent with the theory described by Obermiller and Spangenberg (1989), there are differentiated food product groups, such as PGIs, and less processed foods for which greater effects from CO (RO) labelling can be expected. On this basis, we selected the product groups of beer, meat and milk for the following knowledge test approach in this study. Furthermore, to determine whether there is a willingness to pay for the RO in the real market, we chose the PGI Bavarian beer for a store test. 3. Methods 3.1. Knowledge test approach Consistent with the study that was conducted by Liefeld (2004), this study initially employed the ‘knowledge’ approach to discover whether consumers acquired or possessed information regarding the origin of a product that they had recently purchased. The survey was conducted directly behind the cash register where the buyers were intercepted. The following question was posed first: ‘When you were shopping for _____ (name of product category), what did you consider or take into account?’ Inquiries (e.g., ‘‘anything else?’’) were made until the consumers ceased to mention any additional ‘things’ that they considered when choosing the product. In situations in which consumers did not mention the origin of the purchased product, they were asked the following question: ‘Do you know where the ____ (name of purchased product) was made?’ If they did not know where the product was made, then the question ‘Did you look at the label to find out where it was made?’ was posed. If the buyers stated that they had not sought this information, then they were asked ‘why not?’ If, by this time, the consumers did not identify any country or provide origin information pertaining to their purchase, then they were asked the following questions: ‘How do you know it was made in ____?’ and ‘What does being made in _____ (name of country) tell you about the product?’ If a consumer indicated that he/she knew the product origin and offered a country or region name, then the interviewer asked the consumer whether he/she could read the package/box to verify the correctness of the consumer’s origin identification. 3.2. Controlled Store Test (CST) The main goal of the study was to test the influence of an origin label under real market conditions. For this purpose, different distribution channels were selected for a store test experiment. In the CST, we used two brands (Scheible and Fürsten) that were unknown to the consumers in the survey region. Neither brand had been previously sold at the eight survey locations. Nevertheless, for one of the survey locations (Amerdingen in Bavaria) that is near the small Bavarian town of Wallerstein (3396 inhabitants), the words ‘Fürstliches Brauhaus Wallerstein’, which was displayed

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on the crate for the brand Fürsten, may have been associated with this Bavarian town. The unfamiliarity of the customers with a brand reflects the reality for many small- and medium-sized Bavarian breweries that distribute their beer outside of their home region, including other parts of Bavaria, northern Germany and foreign countries such as Italy (Brauwelt, 2007). In the Bavarian market, some breweries currently use origin information in their marketing communication policies, whereas other breweries rely solely on their brands. Among the 600 Bavarian breweries, approximately 100 of these companies use the label for PGI Bavarian beer, and other breweries use Bavarian elements in their advertisements (LfL, 2011; Profeta, 2006). Thus, consumers are accustomed to both origin and brand labelling. The German food labelling regulation (http://bundesrecht.juris.de/lmkv/index.html) stipulates that labels must contain manufacturer address information, but such addresses are typically written in small letters and are not in plain view on the package. Therefore, one can generally assume that this labelling is not predominantly perceived as origin labelling. The assumption that shoppers do not possess knowledge regarding each of the 600 Bavarian breweries does not suggest that they perceive any previously unknown brand on the shelf as being imported. Furthermore, competition among brands is intense, and the number of retailer brands in the German beer sector is increasing (Statista, 2011). For this reason, finding a new beer brand on the shelf is normal. In addition, product price variation is not unusual. Special offers constitute a central marketing instrument for many retailers (Blattberg & Neslin, 1990) and account for the majority of price changes in the food sector (Hoffmann & Loy, 2009). From our perspective, a perceived price variation would not be interpreted as an ongoing (price or buying) experiment by shoppers. The store test proceeded as follows. Two completely identical (wheat) beers with different branding (Scheible and Fürsten) were placed beside one another and offered to consumers at the point of sale (POS). One of the brands was marked with the origin label Bavarian beer (Scheible), whereas the other brand (Fürsten) was not marked with any origin label. The origin labels were placed on each bottle and beer crate (see Fig. 1). To test for a bias surrounding the names Scheible and Fürsten ex ante, we conducted a simple hypothetical choice experiment with 82 students on the Campus of the Technical University of Munich at the Freising location. In this test, only the two brand names (without any additional labelling) and the prices were displayed. Both brands were always offered for the same price (€ 9.99 per crate), and the students were asked to decide which one they would purchase. Because 39 students chose the Scheible brand and 43 chose the Fürsten brand, we assumed that the biases associated with these brand names were negligible. Furthermore, 20 students evaluated the beer crates and bottle designs of the Scheible and Fürsten brands. For this purpose, the actual physical beer crates and bottles that were used in the CST were shown to the interviewed students. These interviewees were asked to evaluate the design (‘How would you evaluate the design of the beer crate and the bottles?’) on a 10-point scale from 1 (poor) to 10 (good). The means were 6.40 (Fürsten) and 6.65 (Scheible), and a paired t-test showed that there was no significant difference in the evaluations of the beer crates and bottle designs. In the CST, both types of beer were placed among all available wheat beers and featured no additional positioning in the markets, as illustrated in Fig. 2. No specifications were made for the beers that were situated to the right and left of our analysed brands. The Scheible and Fürsten brands were offered in a beer crate that contained 20 0.5-L beer bottles. Initially, 20 crates of each brand were placed beside one another at every POS in the survey. The prices of both brands were varied according to an experimental

design plan to allow for the calculation of a price premium for Bavarian beer. A price of € 6.99 per crate represents the upper limit of the lowest price category, and a price of € 9.99 per crate represents the upper limit of the middle price category based on data from the GfK ConsumerScan (Brauindustrie, 2007, chap. 8). A price of € 12.99 per crate represents the premium price category. To calculate a price premium for the Bavarian beer PGI, we offered the Scheible brand for either the same price or for a price that was three or six euros more expensive than the Fürsten brand. In the various survey locations, the initial prices were changed immediately after the first 20 crates of one of the brands were sold (see Tables 2 and 5). Before the price variations were implemented, the crates that were sold were replaced to ensure that the customers again encountered 20 crates of each brand. The test was immediately concluded after all 20 crates of one of the brands in the second price level were sold. Between 11 and 24 weeks (a time period from 09/01/2006 to 03/ 31/2007) were necessary to sell the 40 crates for the study, and 6– 14 weeks were necessary to sell the first 20 crates. Therefore, individual shoppers may have had multiple exposures to the products in the experiment. Nevertheless, the possible resulting bias should be marginal because retailers provide special offers on a daily basis. Thus, we did not expect consumers to become conscious of the existence of the experiment. Furthermore, through the division of the price changes among the survey locations, it was necessary to change the price for only one brand at each survey location. Nevertheless, we cannot completely eliminate the possibility that the price changes were perceived as being part of an experiment. The purchases were recorded at the cash register, and a conditional logit model was applied to estimate the effects of price and origin on purchase decisions. The chosen model was based on the popular multinomial (conditional) logit model (McFadden, 1974):

eV in Prin ¼ PJ eV in ;

j ¼ 1; :::J; j – I

ð1Þ

j¼1

In this model, Prin is the probability of individual n choosing alternative i. Vin is the systematic (measurable) utility, which is a function of Xin and bi and is an unknown parameter vector to be estimated. In this study, Xin represents the different levels of our attributes of price and the Bavarian beer label, which were presented to the purchasers (n) via choice alternatives (i.e., buying options (i)) according to the previously mentioned experimental design. The preference parameters bi depict the effects of the analysed attributes on buying (choice) probability. The parameters were estimated using a maximum likelihood estimation based on the preference data that were revealed by the CST. In most practical applications, Vin adopts a linear-in-parameters additive form. In this study, the vector Vin is defined as follows:

V in ¼ b1  pricein ; þb2  Bavarian beerin

ð2Þ

where pricein represents the price level that pertains to choice i by purchaser n. The corresponding parameter b1 shows the estimated effect of the price attribute. In this study, the attribute Bavarian beer was dummy coded; thus, the Scheible brand, which was labelled as Bavarian beer, was coded with the value of one, whereas the nonBavarian labelled brand Fürsten was coded with the value of zero. Based on statistically significant estimates of the attribute coefficients, implicit prices for the Bavarian beer origin labelling can be calculated. The maximum willingness to pay (WTP) for a change in one level of the attribute Bavarian beerin (‘marginal’ WTP) is equal to the ratio of the respective coefficients b2 and b1 of the monetary attribute pricein:

mWTPðBavarian beerÞ ¼ 

b2 b1

ð3Þ

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Fig. 1. Beer crates and bottles in the CST.

Fig. 2. Display of the beer crates in the CST.

Table 2 Experimental and survey design of the CST. Price level

Scheible price

Fürsten price

Location 1

1. Price level 2. Price level

€ 9.99 € 9.99

€ 9.99 € 6.99

Location 2

3. Price level 4. Price level

€ 12.99 € 12.99

€ 9.99 € 6.99

4. Samples 4.1. Knowledge test approach The cash register intercept interview was replicated at four locations in Germany for a total of 514 intercepts: Berlin (n = 122), Braunschweig (n = 199), Hannover (n = 103) and

Osnabrück (n = 90). For this purpose, the questionnaire that was developed by Liefeld (2004) was translated into German by a native English speaker, verified by a German native speaker and tested at two retailers (EDEKA and Rewe) in the city of Freising, where 20 shoppers were interviewed at each site. In each of the four survey locations, trained graduate students conducted the interviews during the period from the 2nd of November 2009 to the 6th of November 2009. The interviews were conducted at the cash registers of Germany’s largest food retailer, EDEKA. To obtain sufficiently large samples for the comparison of origin awareness among different product groups and to be able to verify the origins of the products, this study focused only on packaged meat (e.g., sausages), packaged dairy products (e.g., butter, milk, cheese, and yoghurt) and canned or bottled beer. The interviewer asked every third passing shopper if she or he was interested in participating in a survey. After providing their consent, only those shoppers who

A. Profeta et al. / Food Quality and Preference 26 (2012) 1–11

had purchased a product in one of the above-mentioned categories were interviewed with regard to their purchases. Table 4 provides a more detailed overview of the composition of the product groups. The shoppers were asked about only one product, even if they had purchased multiple products from the analysed categories, to maintain the brevity of the interviews. The main advantage of this approach is the avoidance of social desirability response bias in the interviewing process. A respondent could become aware of the interest of the research and its purposes after being questioned about a purchase. This awareness could bias any responses to subsequent questioning regarding other purchases within the same interview on the same topic (Schuman & Presser, 1996). The sample is a convenience sample of purchases and consumers. An analysis of the results by location/interviewer reveals few differences among the four locations. Consequently, the findings for all locations are combined in the following sections. Because this sample is a convenience sample, no claim is made regarding whether the sample is representative of the population. Regarding sociodemographic characteristics, the average age of the participants was 48.3 years (SD 15.5 years), 40.9 per cent of the participants were men and 59.1 per cent of the participants were women. Compared with the general German population, women and participants in the age category of 30–59 years were overrepresented (see Table 3).

4.2. Controlled Store Test The store test was conducted from the 1st of September 2006 to the 31st of March 2007. The study locations were four cities in Bavaria (Marktindersdorf, Amerdingen, Mitterfels, and Nürnberg) and two cities each in the German federal states of Hessen (Stadtallendorf and Fritzlar) and Thüringen (Erfurt and Schleusingen). Six of the survey locations were classical beverage specialist shops, whereas two of the Bavarian locations were EDEKA outlets with a beverage shop.

5. Findings 5.1. Knowledge test approach In the unprompted portion of the interview, 48 purchasers (9.3 per cent), who were unaware of the purpose of the study, cited the origin of a product as one of the ‘things’ that they considered when choosing the product that they had purchased. Four of these customers mentioned the origin twice; thus, there were a total of 52 mentions of this attribute. This value lies above the 5.6 per cent value that Kemp et al. (2010) found for fresh products in Britain. Twenty-five of these 48 respondents had read the origin information on the packaging, whereas 23 respondents had derived the origin from the brand name. In total, 25 of 514 consumers (4.9 per cent) had explicitly perceived origin information while shopping. The first five ‘things’ that the respondents mentioned that they had considered when making their purchases were recorded. Each item was coded into one of the following categories: price/cost, origin, brand, taste, freshness, extrinsic items, intrinsic items, and miscellaneous items. Table 4 presents the frequencies of these groups for the first through the fifth mentions. Similar to the findings of Liefeld (2004), the intrinsic properties (e.g., taste, quality, and freshness) of products were mentioned the most frequently. Price was the second most frequently mentioned property, whereas origin and brand were the third and fourth most frequently mentioned properties, respectively. The greater importance of intrinsic factors compared with price, brand and origin

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is consistent with the findings of other studies of consumers in pre-purchase situations (Liefeld, 2004; Zeithaml, 1988). When directly asked the question ‘Do you know where the _____ (name of purchased product) was made?’, 97 purchasers (20.8 per cent) named an origin for the product. In total, 145 (48 + 97) purchasers (28.02 per cent) perceived the origin of the purchased product while shopping or possessed this knowledge as a result of prior experience. After the product check verification, 116 purchases (80.0 per cent) in this group were found to be correct. Based on the full sample, 22.5 per cent of the respondents knew the correct origin of their purchased products. This value is similar to the result that was obtained by Kemp et al. (2010) for fresh products in Britain. In their study, 19.1 per cent of the respondents knew the correct origin of the food item that they had selected. As Kemp et al. (2010) noted, the differences in origin awareness that were found between the unprompted and direct questions (9.3 per cent vs. 22.5 per cent) may indicate a social desirability bias in operation. If the purchasers did not mention the origin of the product that they had purchased in their responses to the first two questions (n = 386), then they were asked the following question: ‘Did you look to see where the product was made?’; 385 respondents (99.9 per cent) indicated that they had not searched for this information. Of the 116 people who were aware of the correct product origin, 103 respondents (88.7 per cent) provided a response that indicated a positive relationship between the origin and their evaluation of the quality of the product. Twenty-one respondents (18.1 per cent) expressed ethnocentric tendencies by stating that they wished to support regional German products. As a result of some intersections among multiple responses, the number of respondents for whom origin was relevant was 113 (22 per cent of the total). This value is greater than that obtained by Kemp et al. (2010) for fresh products in Britain. In their study, 17.1 per cent of the sample group stated that knowledge of origin had influenced their purchase decisions. Nearly all (97.4 per cent) of the respondents who correctly named the origin of the product evaluated the origin attribute in a positive manner. The results demonstrate that origin played a role in the choice among available alternatives for approximately one-fifth of the interviewed consumers. For the following segmentation analysis, we refer to these 113 respondents as the group ‘origin matters,’ whereas we refer to the remainder of the sample of 401 respondents as the ‘origin does not matter’ group. When the importance of origin was evaluated for the three analysed product groups, origin was found to be more important for the beer sector (36.7 per cent) than for milk (17.0 per cent) or meat (23.5 per cent) products (see the last column in Table 5). Moreover, further subdivision according to the gender of the respondents revealed significant differences based on a chi-squared test for the beer category. For 45.0 per cent of all men who purchased beer, origin was relevant, whereas origin was relevant for only 10.5 per cent of the women who purchased beer. An additional t-test showed that the average age of the ‘origin matters’ group was significantly higher (51.4 years) than that of the ‘origin does not matter’ group (44.8 years). If we subdivide the three main product groups, then it becomes clear that there is a large variation across the different subcategories (see Table 5). For dairy products, the importance of origin is greater for more unprocessed products, such as milk, butter and yoghurt, than for cheese, which is a more processed product. 5.2. Controlled Store Test Table 6 shows the aggregated sales figures that were obtained at the different survey locations in the CST. The results clearly show that the Bavarian-labelled Scheible brand is strongly

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A. Profeta et al. / Food Quality and Preference 26 (2012) 1–11 Table 3 Sample description. Individual characteristics

Survey (%)

Germany (%)

Difference (%)

Gender

Male Female

40.9 59.1

50.5 49.5

9.6 9.6

Age (years)

15–19 20–29 30–39 40–49 50–59 >60

0.8 11.5 18.3 24.0 20.5 25.0

6.1 14.0 14.1 19.6 16.3 30.0

5.3 2.5 4.2 4.4 4.2 5.0

Source: Federal German Office for Statistics (DESTATIS), 2010.

Table 4 Factors that were mentioned as ‘considered’ or ‘taken into account’ in product purchase decisions.

a b

First mention (%)

Second mention (%)

Extrinsic items Price/cost Origin Brand Other Extr.

179 (34.8)a 10 (1.9) 15 (2.9) 10 (1.9)

126 (24.5) 20 (3.9) 19 (3.7) 9 (1.8)

Intrinsic items Taste Freshness Other Intr. Miscellaneous No mention

79 (15.4) 72 (14.0) 126 (24.5) 23 (4.5) 0 (0.0)

30 (5.8) 40 (7.8) 158 (30.7) 54 (10.5) 58 (11.3)

Third mention (%) 37 13 10 26

Fourth mention (%)

(7.2) (2.5) (1.9) (5.1)

2 7 0 4

19 (3.7) 16 (3.1) 64 (12.5) 14 (2.7) 315 (61.3)

(0.4) (1.4) (0.0) (0.8)

1 (0.2) 1 (0.2) 12 (2.3) 1 (0.2) 486 (94.6)

Fifth mention (%) 2 2 0 0

Total 346 (28.8)b 52 (4.3) 44 (3.7) 49 (4.1)

(0.4) (0.4) (0.0) (0.0)

1 (0.2) 0 (0.0) 1 (0.2) 0 (0.0) 508 (98.8)

130 (10.8) 129 (10.7) 361 (30.0) 92 (7.6)

Percentage of first mentions. Percentage of total mentions.

preferred over the Fürsten brand when their prices are equal. If the latter brand is offered at a price that is less by three or six euros, then consumer preferences change accordingly. The results that were obtained from the Amerdingen survey location may be biased because the buyers may have identified the Fürsten brand as a Bavarian brand, as mentioned in Section 3. Based on the sales figures in Table 6, a conditional logit model was calculated with the STATA 8.0 software. The logit calculation was based on the aggregated sales data (base = crate with 20 0.5–l bottles). Tables 7 through 9 display the estimation results for the full sample and display the results separately for the Bavaria and Hessen/Thüringen study regions. The models exhibit pseudo-R2 values of 0.11183 (full sample), 0.1840 (Bavaria) and 0.0570 (Hessen and Thüringen); thus, only the model for the Bavarian survey region demonstrates relatively strong performance (Table 5). According to Costanzo, Halperin, Gale, and

Richardson (1982), a pseudo-R2 value of 0.2–0.4 signifies a satisfactory level of model estimation. In all of the estimations, price had a significant, negative effect on purchase decisions, whereas origin labels positively influenced purchases. Based on the estimation results, a price premium of € 2.00 per crate was calculated for the study region of Bavaria, whereas this value was € 2.60 per crate for the Hessen and Thüringen locations (see Table 10).

6. Discussion The findings of this study demonstrate that origin plays a role in the choice among available food alternatives in the analysed categories for approximately one-fifth of the consumers who were interviewed. This value is approximately 10 times higher than that

Table 5 Relevance of origin according to product group and gender. Women (n = 304)

Men (n = 210)

Total (n = 514)

Origin matters

Origin does not matter

Origin matters

Origin does not matter

Dairy products (n = 282) Milk (n = 98) Yoghurt (n = 56) Cheese (n = 55) Butter (n = 17) Curd (n = 14) Cream cheese (n = 13) Cream (n = 11) Miscellaneous (n = 19)

27 (14.1%) 9 (14.1%) 5 (14.3%) 0 (0%) 6 (46.1%) 4 (30.8%) 2 (25%) 1 (11.1%) 0 (0%)

164 (85.9%) 55 (85.9%) 30 (85.7%) 37 (100%) 7 (53.9%) 9 (69.2%) 6 (75%) 7 (88.9%) 13 (100%)

21 (23.1%) 6 (17.6%) 10 (47.6%) 1 (5.6%) 0 (0%) 0 (0%) 2 (40%) 1 (33.3%) 1 (20%)

70 (76.9%) 28 (82.4%) 11 (52.4%) 17 (94.4%) 4 (100%) 1 (100%) 3 (60%) 2 (66.7%) 4 (80%)

48 (17.0%) 15 (15.3%) 15 (26.8%) 1 (1.8%) 6 (35.3%) 4 (28.6%) 4 (30.8%) 2 (18.2%) 1 (5.6%)

Meat products (n = 153) Meat (n = 75) Sausage (n = 59) Grilled Sausages (n = 11) Miscellaneous (n = 8)

23 (24.5%) 11 (23.1%) 8 (20.5%) 4 (80%) 0 (0%)

71 (75.5%) 35 (76.1%) 31 (79.5%) 1 (20%) 4 (100%)

13 (22.0%) 8 (27.6%) 3 (15%) 2 (33.3%) 0 (0%)

46 (78.0%) 21 (72.4%) 17 (85%) 4 (66.7%) 4 (100%)

36 (23.5%) 19 (25.3%) 11 (18.6%) 6 (54.5%) 0 (0%)

117 (76.5%) 56 (74.7%) 48 (81.4%) 5 (45.5%) 8 (100%)

2 (10.5%) 52 (17.1%)

17 (89.5%) 252 (82.9%)

27 (45.0%) 61 (29.0%)

33 (55.0%) 149 (71.0%)

29 (36.7%) 113 (22.0%)

50 (63.3%) 401 (78.0%)

Beer (n = 79) All products (n = 514)

Origin matters

Origin does not matter 234 83 41 54 11 10 9 9 17

(83.0%) (84.7%) (73.2%) (98.2%) (64.7%) (71.4%) (69.2%) (81.8%) (94.4%)

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A. Profeta et al. / Food Quality and Preference 26 (2012) 1–11

reported by Liefeld (2004) for non-food products in the US market. Nevertheless, with respect to the comparison of our knowledge test results with the studies of Liefeld (2004) and Kemp et al. (2010), it remains unclear whether the differences result from the chosen country, product category or point in time at which the surveys were administered. Furthermore, the general finding that origin did not play a role for 80 per cent of the interviewed German consumers suggests that the origin campaigns and the legal framework of regulation (EC) 510/06 have failed to exert a substantial effect on consumer choice. Additionally, the differences that were found in origin awareness between the unprompted and direct questions (9.3 vs. 22.5 per cent) may indicate social desirability bias in operation. Conversely, we conducted the study only at supermarket outlets of Germany’s largest food retailer and did not consider local butchers or bakeries and discounters. Many of the most frequently named small shops advertise their use of regional raw materials; thus, in these stores, the greater importance of origin may be emphasised, whereas a more predominant role of price can be expected in discount stores. However, the largest German discounter, Aldi, offers a relatively high percentage of PDO/PGI products. Therefore, new studies should consider different product distribution channels. Furthermore, in this study, customers who purchased a milk or meat product or beer were interviewed. Thus, in the knowledge test approach, we did not focus on particular food specialties. We hypothesise that origin is more important for special product categories, such as hard cheeses, wine or ham, for which numerous (PGI/PDO) specialties exist than for the chosen general product categories in this study (see Section 2). Because of the insufficient sample size, it was not possible to conduct a more detailed segmentation analysis of different types of food specialties. Therefore, we recommend the consideration of such products in the future. Regarding the more detailed analysis of the knowledge test, this study revealed that there are different levels of origin awareness for different product groups. In the beer sector, origin appears to be especially relevant in purchase decisions. Nevertheless, the relevance of origin in this product category appears to depend on product involvement; 45 per cent of all beer-purchasing men in this sample group recognised and positively evaluated the product origin, whereas only 10 per cent of the women recognised the product origin and provided such an evaluation. Because we did not ask the consumers whether the purchased products were consumed by the respondents themselves, it was not possible to determine whether most of the women made the beer purchase by proxy for men or vice versa. If this situation were applicable, then it could explain the low awareness of the women regarding the product origin compared with that of the men. Therefore, future studies that employ the knowledge approach should seek to determine who ultimately consumes the product in question.

Table 7 Estimation results for the full sample set.

Price Bavarian beer

Coeff.

z-Value

0.39 0.89

7.21 4.90

Observations = 481; LR v2 = 77.57 (p = 0.0000); log likelihood = 289.07; pseudo R2 = 0.1183. ⁄ a = 0.01.

Table 8 Estimation results for Bavaria.

Price Bavarian beer

Coeff.

z-Value

0.53 1.06

5.90 3.72

Observations = 217; LR v2 = 55.36 (p = 0.0000); log likelihood = 122.73; pseudo R2 = 0.1840. ⁄ a = 0.01.

Table 9 Estimation results for Hessen and Thüringen.

Price Bavarian beer

Coeff.

z-Value

0.30 0.78

3.27 4.30

Observations = 264; LR v2 = 20.87 (p = 0.0000); log likelihood = 172.55; pseudo R2 = 0.0570. ⁄ a = 0.01.

Table 10 Willingness to pay for Bavarian beer based on study location.

Bavarian beer

Bavaria

Hessen and Thüringen

€ 2.00 per crate

€ 2.60 per crate

Source: This study.

The results of the CST show that GIs can have a positive effect on the decisions of consumers. In this study, an unknown brand benefited from origin labelling. This result is consistent with the ‘perceived risk theory’, which posits that consumers perceive greater risks with generic (no-name brands) than with branded (in this case, ‘origin’ branded) food items (Mitchell, 1998). The non-hypothetical store test demonstrated that there is a ‘real’ willingness to pay for the GI Bavarian beer. Nevertheless, the logit models exhibited only modest pseudo-R2 values. Several factors could have influenced this result. First, we did not control for the brands that were positioned to the right or left of the analysed

Table 6 Sales figures from the CST (unit = crate with 20, 0.5–l bottles). Survey location

Marktindersdorf (Bavaria) Mitterfels (Bavaria) Stadtallendorf (Hessen) Erfurt (Thüringen)

Amerdingen (Bavaria) Nürnberg (Bavaria) Fritzlar (Hessen) Schleusingen (Thüringen)

Sales Scheible price € 9.99

Fürsten price € 9.99

Scheible price € 9.99

Fürsten price € 6.99

20 20 20 20

5 6 7 11

9 13 19 17

20 20 20 20

€ 12.99

€ 9.99

€ 12.99

€ 6.99

11 6 16 19

20 20 20 20

2 5 7 8

20 20 20 20

10

A. Profeta et al. / Food Quality and Preference 26 (2012) 1–11

brands. Second, we did not control the prices or the number of brand alternatives. Third, we did not account for special price offers of nearby retailers or shops. These variables should be evaluated and incorporated into the logit models of future CST studies. Fourth, for the survey location of Amerdingen, we did not determine whether the Fürsten brand could be associated with the nearby small Bavarian town of Wallerstein, which may have biased the choice decision. Therefore, future studies should determine whether the analysed brands are associated with a certain origin and thus strive to use brand names that consumers do not associate with a certain origin. Furthermore, to minimise the risk of the purchasers becoming aware of the CST, researchers should ensure that prices do not change during the experiment. For this purpose, a sufficient number of survey locations must be utilised. Because field test experiments such as the reported study are limited to one or only a few product categories or brands, such experiments must be replicated numerous times using many additional product categories and brands to obtain generalisations across product categories (Wells, 2001). In the beginning of this paper, we stated that the CST was administered prior to the knowledge test and that both studies were originally conducted independently of one another. In future studies, both approaches should be applied simultaneously for the same products. More detailed insights into the relationship between willingness to pay and origin awareness can be gained using this approach.

References Alfnes, F. (2004). Stated preferences for imported and hormone-treated beef: Application of a mixed logit model. European Review of Agricultural Economics, 31(1), 19–37. Arfini, F. (2003). OLP characteristics, evolution, problems and opportunities. WP 5 Final Report of the EU-Project Development of Origin Labelled Products: Humanity, Innovation and Sustainability. Balling, R. (1995). Der Herkunftsaspekt als Erfolgsfaktor für das Lebensmittelmarketing. Berichte über Landwirtschaft, 73, 83–106. Balling, R. (2004). Regionalität als Marketing-Instrument. In O. Strecker, H.-J. Leyrer, & A. Elles (Eds.), Die Ernährungswirtschaft auf der Suche nach Spitzenleistungen (pp. 67–80). DLG-Verlag. Blattberg, R.C., & Neslin, S.A. (1990). Sales Promotion. Concepts, Methods and Strategies. Englewood Cliffs, New Jersey: Prentice Hall. Bonnet, C., & Simioni, M. (2001). Assessing consumer response to protected designation of origin labelling: A mixed multinominal logit approach. European Review of Agricultural Economics, 28(4), 433–449. Brauindustrie (2007). Brauindustrie – Trendbarometer. Brauwelt (2007). Brückenbauen wichtiger denn je. 6, 139. Bruner, J., Goodnow, J., & Austin, G. (1956). A study of thinking. New York: John Wiley and Sons. BStMLF (2008). Geographische Herkunftsangaben – Die Bayerische Initiative, Vol. 2008. Consumer Reports. (1989). CD Players: The new music medium (p. 165). Cordell, V. V. (1992). Effects of consumer preferences for foreign sourced products. Journal of International Business Studies, 23(2), 251–269. Costanzo, C. M., Halperin, W. C., Gale, N. D., & Richardson, G. D. (1982). An alternative method for assessing goodness-of-fit for logit models. Environment and Planning, A14, 963–971. Ettenson, R., Wagner, J., & Gaeth, G. (1988). Evaluating the effect of country of origin and the ‘‘Made in the USA’’ campaign: A conjoint approach. Journal of Retailing, 64(1), 10–11. Gipson, K., & Francis, S. K. (1991). The effect of country of origin on purchase behaviour: An intercept study. Journal of Consumer Studies & Home Economics, 15(1), 33–44. Guiles, M. G. (1989). Quiet ride ends for luxury-car makers as a crowded market befuddles buyers. Wall Street Journal, B1, B11. Hampton, G. M. (1977). Perceived risk in buying products made abroad by American firms. Baylor Business Studies, 53–64. Han, C. M., & Terpstra, V. (1988). Country-of-origin effects for uni-national and binational products. Journal of International Business Studies, 19(2), 235–255. Harrison, G. W., & Rutström, E. E. (2008). Experimental evidence on the existence of hypothetical bias in value elicitation methods. In R. P. Charles & L. S. Vernon (Eds.). Handbook of experimental economics results (Vol. 1, pp. 752–767). Elsevier.

Hoffmann, A., & Loy, J.-P. (2009). Sonderangebote und Preissynchronisation im deutschen Lebensmitteleinzelhandel. German Association of Agricultural Economists (GEWISOLA). Johansson, J. K. (1988). Determinants and effects of the use of ‘‘Made in’’ labels. International Marketing Review, 6(1), 47–58. Jones, M. Y. (1994). Differentiating new brands: Product category judgements as mediators of new product evaluation processes. In J. A. C. a. S. M. Leong (Ed.), Asia Pacific Advances in Consumer Research (pp. 17–21). Provo, UT: Association for Consumer Research Press. Josling, T. (2006). The war on terror: GIs as a transatlantic trade conflict. Journal of Agricultural Economics, 57(3), 337–363. Kemp, K., Insch, A., Holdsworth, D. K., & Knight, J. G. (2010). Food miles: Do UK consumers actually care? Food Policy, 35(6), 504–513. Kim, R. B., Veemann, M., & Unterschultz, J. (2000). Effects of product origin on millers choice of imported wheat for noodle market segments in Japan and South Korea. Chicago, Illinois: IAMA Agribusiness Forum. Kühn, R. (1993). Das ‘‘Made-in’’-Image Deutschlands im internationalen Vergleich. Marketing Zeitschrift für Forschung und Praxis (ZFP), 2, 119–127. LfL (2011). Available from: http://www.lfl.bayern.de/iem/herkunftsbezeichnungen/ 27852/linkurl_0_5_0_4.pdf. Liefeld, J. P. (2004). Consumer knowledge and use of country-of-origin information at the point of purchase. Journal of Consumer Behaviour, 4(2), 85–87. List, J. A., & Gallet, C. A. (2001). What experimental protocol influence disparities between actual and hypothetical stated values? Environmental & Resource Economics, 20(3), 241–254. Manrai, L. A., Lascu, D.-N., & Manrai, A. K. (1998). Interactive effects of country of origin and product category on product evaluations. International Business Review, 7(6), 591–615. McFadden, D. L. (1974). Conditional Logit analysis of qualitative choice behaviour. In R. Zambreka (Ed.), Frontiers in economics. Academic Press, pp. 105–142. Mitchell, V.-W. (1998). A role for consumer risk perceptions in grocery retailing. British Food Journal, 100(4), 171–183. Mtimet, N., & Albisu, L. M. (2006). Spanish wine consumer behavior: A choice experiment approach. Agribusiness, 22(3), 343–362. Nagashima, A. (1970). A comparison of Japanese and US attitudes toward foreign products. Journal of Marketing, 68–74. Nagashima, A. (1977). A comparative ‘Made in’ product image survey among Japanese businessmen. Journal of Marketing, 95–100. Obermiller, C., & Spangenberg, E. (1989). Exploring the effects of country of origin labels: An information processing framework. Advances in Consumer Research, 16, 454–459. Papadopoulos, N., & Heslop, L. A. (2002). Country equity and country branding: Problems and prospects. Journal of Brand Management, 9(4–5), 294–314. Perrouty, J. P., Hauteville, F., & Lockshin, L. (2006). The influence of wine attributes on region of origin equity: An analysis of the moderating effect of consumer’s perceived expertise. Agribusiness, 22(3), 323–341. Peterson, R. A., & Jolibert, A. J. P. (1995). A meta-analysis of country-of-origin effects. Journal of International Business Studies, 4, 883–890. Profeta, A. (2006). Der Einfluss geschützter Herkunftsangaben auf das Konsumentenverhalten bei Lebensmitteln – Eine Discrete-Choice-Analyse am Beispiel Bier und Rindfleisch. Hamburg: Studien zum Konsumentenverhalten. Profeta, A. (2009). Auswertung zur Umfrage für Präferenzen im Milchbereich. Freising: Technical University of Munich. Profeta, A. & Balling, R. (2009). Bedeutung von Herkunftsangaben und Gütezeichen in der Rindfleischkennzeichnung – Bekanntheit und Bedeutung des Zeichens, Geprüfte Qualität-Bayern aus Verbrauchersicht (Vol. 2–3, pp. 3.1–3.5). Schule und Beratung. Profeta, A., & Balling, R. (2007). Evaluierung der Übergangsregelung des Herkunftsschutzes bei Agrarprodukten und Lebensmitteln in Europa und Verbesserungsvorschläge für die anstehende Neumodifikation. Agrarwirtschaft, 4, 213–223. Profeta, A., Balling, R., Schoene, V., & Wirsig, A. (2010). Protected GIs and Designations of Origin: An overview of the Status Quo and the Development of the Use of Regulation (EC) 510/06 in Europe, with special consideration of the German situation. Journal of International Food & Agribusiness Marketing (22), 179–198. Profeta, A., Enneking, U., & Balling, R. (2006). Geschützte Herkunftsangaben – Status Quo und Entwicklung der Nutzung der Verordnung (EWG) 510/2006. Agrarwirtschaft, 8. Profeta, A., Enneking, U., & Balling, R. (2008). Interactions between Brands and CO Labels: The Case of ‘‘Bavarian Beer’’ and ‘‘Munich Beer’’ – Application of a Conditional Logit Model. Journal of International Food and Agribusiness Marketing, 20(3), 73–89. Roosen, J., Lusk, J. L., & Fox, J. A. (2003). Consumer demand for and attitudes toward alternative beef labeling strategies in France, Germany, and the UK. Agribusiness, 19(1), 77–90. Roth, M. S., & Romeo, J. B. (1992). Matching product category and country image perceptions – A framework for managing country-of-origin effects. Journal of International Business Studies, 23(3), 477–497. Scarpa, R., Philippidis, G., & Spalatro, F. (2003). Product-county images and preference heterogenity for Mediterranean food products: A discrete choice framework. Agribusiness, 21(5), 329–349.

A. Profeta et al. / Food Quality and Preference 26 (2012) 1–11 Schaefer, A. (1997). Consumer knowledge and country of origin effects. European Journal of Marketing, 31(1), 56–72. Schneider, F. & Holzberger, M. 2006. Lebensmittel Aus Österreich Eine volkswirtschaftlich-empirische Untersuchung für Österreich – Teil 2 (Vol. 2010). Presentation Linz. Schuman, H., & Presser, S. (1996). Questions and answers in attitude surveys: Experiments on question form, wording, and context. Thousand Oaks, CA: Sage Publications. Statista (2011). Handelsmarkenanteil im Lebensmitteleinzelhandel nach FoodWarenklasse in Deutschland in den Jahren 2009 und 2010. Nielsen. van Ittersum, K. (2001). The Role of Origin in Consumer Decision-Making and Choice. Unpublished Ph.D.-Thesis. Verlegh, P. W. J., & Steenkamp, J.-B. E. M. (1999a). A review and meta-analysis of country-of-origin research. Journal of Economic Psychology, 20(5), 521–546.

11

Verlegh, P., & Steenkamp, J. B. (1999b). A review and meta-analysis of country-oforigin research. Journal of Economic Psychology, 20, 521–546. Ward, R. W., Briz, J., & Felipe, I. (2003). Competing supplies of olive oil in the German market: An application of multinomial logit models. Agribusiness, 19(3), 393–406. Wells, W. D. (2001). The perils of N = 1. Journal of Consumer Research, 28(3), 494–498. Wheatley, J. J., Chiu, J. S., & Goldman, A. (1981). Physical quality, price and perceptions of product quality: Implications for retailers. Journal of Retailing, 2, 100–116. Yaprak, A. (1978). Formulating a multinational marketing strategy: A deductive crossnational consumer behavior model. Georgia State University. Zeithaml, V. (1988). Consumer perceptions of price, quality, and value. A means-end model and synthesis of evidence. Journal of Marketing, 52, 2–22.