Introduction
The European market for organic food is the biggest market for organic food worldwide. The market volume in 2006 was estimated to be between 13 and 14 billion Euros with a growth rate of approximately 10% compared to 2005Reference Willer, Yussefi-Menzler and Sorensen1. Within Europe, the German organic market is by far the largest with an annual turnover of 5.3 billion Euros in 2007 and a growth rate of 15% compared to the previous yearReference Hamm and Rippin2. Recent studies suggest that 91% of all German households consume organic food products3. In Germany, certified organic products are widely available in regular supermarkets as well as in organic food stores, in drugstores and at farmers' markets.
Most organic products sold in Germany carry the well-known governmental organic label (‘Bio-Siegel’), which indicates compliance with the EU Regulation (EEC) No. 2092/914. In addition, the German organic market is characterized by a relatively large number of private organic certification standards that exceed the EU Regulation (e.g., Demeter, Bioland and Naturland). Consequently, a variety of organic labels and standards can be found on food products, with many products carrying both the governmental as well as a private organic label together with a company's brand. In this respect, the German organic market is unique compared to other European countries. In addition to certified organic products, other kinds of products are found on the food market: conventional producers increasingly launch products incorporating single aspects of organic production systems, such as lower inputs of pesticides, food additives or concentrated animal feed. These products do not comply with organic standards and are referred to as low-input products in this paper. While there are many examples of low-input products (e.g. free-range eggs, the products by the British company ‘innocent’, the yogurt line ‘Natur rein’ by the German company ‘Bauer’), the authors do not know of any published data on the market share and growth rate of low-input products.
Previous studies from Germany on consumer preferences regarding product attributes indicate that consumers rate the overall system of organic farming as less important than individual aspects incorporated in the system, such as animal welfare and the abandonment of the use of GM technologies, pesticides and antibioticsReference Stolz, Hess and Rahmann5, Reference Kuhnert, Feindt, Wragge and Beusmann6. Studies from other European countries moreover suggest that consumers are not well informed about organic production and how certification worksReference Hoogland, de Boer and Boersema7–Reference Aarset, Beckmann, Bigne, Beveridge, Bjorndal, Bunting, McDonagh, Mariojouls, Muir, Prothero, Reisch, Smith, Tveteras and Young9. A scientific study on consumer perception of low-input products revealed a similar pictureReference Conner, Campbell-Arvai and Hamm10: While consumers expressed great interest in pasture-raised livestock products, it also turned out that many consumers believed, almost certainly erroneously, that they had already bought such products. Overall, previous studies thus indicate that consumers seem to lack knowledge about organic standards and farming practices in generalReference Stolz, Hess and Rahmann5–Reference Conner, Campbell-Arvai and Hamm10.
Numerous studies have been conducted on consumer preferences for organic foodReference Hughner, McDonagh, Prothero, Shultz and Stanton8. However, it remains unclear how the organic sector is affected by the emerging competition imposed by low-input products. The present study was designed and conducted to analyze how consumers perceive low-input products that are otherwise produced in a conventional way. By means of purchase simulations with subsequent personal interviews, we investigated how consumers react to low-input products in relation to certified organic and conventional products. In this paper, we identify whether low-input products substitute organic or conventional products, and determine whether low-input represents an ‘intermediate choice’. In order to identify factors that influence consumer preferences regarding organic, low-input and conventional food, the participants are grouped into four consumer segments according to their buying behavior by means of a cluster analysis. The consumer segments are then characterized in terms of product preferences, attitudes toward food quality and safety and socio-demographic variables.
Methods
Our study combined two methods of data collection. The buying behavior of consumers was surveyed by purchase simulations. In subsequent face-to-face interviews, factors that influence the product choice were investigated. A cluster analysis was conducted to identify groups of participants with similar buying patterns. The following sections describe the methods of data collection and the survey design as well as the procedure of data collection and the method of data analysis.
Survey design
In our study, purchase simulations were conducted to analyze consumers' choices between certified organic, low-input and conventional products. The design of the purchase simulations resembled the method of data collection that is used in consumer choice experiments. However, we focused on creating a realistic buying situation in the purchase simulations. While in many studies with choice experiments, the participants are presented with pictures or descriptions of products and are required to make repeated choices in the same product category (e.g., see the studies by Lusk and SchroederReference Lusk and Schroeder11, Lockshin et al.Reference Lockshin, Jarvis, d'Hauteville and Perrouty12, Mtimet and AlbisuReference Mtimet and Albisu13, Loureiro and UmbergerReference Loureiro and Umberger14, Barreiro-Hurlé et al.Reference Barreiro-Hurlé, Colombo and Cantos-Villar15, EnnekingReference Enneking16, Hu et al.Reference Hu, Hünnemeyer, Veeman, Adamowicz and Srivastava17), we used three-dimensional products and the participants only made one purchase decision per product category. The product categories investigated in our study were milk, yogurt and apples. These product categories were chosen in order to investigate the buying behavior for both animal and plant products as well as processed and unprocessed food products. Each participant was asked to make three consecutive purchase decisions, one each for milk, yogurt and apples. In each product category, the choice set contained three different product alternatives: conventional, low-input and organic. In addition, the no-choice option was offered. The organic alternatives were labeled with the German governmental organic logo (‘Bio-Siegel’). The low-input products were labeled with respective product information, which is shown in Table 1. The choice sets regarding milk and yogurt comprised product packages that were created by a design company for the purpose of this study. The packages contained all relevant product information but no brand name. All apples in one choice set came from the same delivery so that they looked similar. The product prices were displayed on laminated price tags. To avoid a hypothetical bias, the participants had to pay for the chosen products.
Table 1. Low-input products tested in the purchase simulations.
Across the sample, the price levels of the products varied. In total, four different combinations of prices were tested. Among the three competing product alternatives, the conventional products were always the cheapest and the organic the most expensive. The low-input products were offered at in-between price levels and were either priced right in the middle between the two others or closer to the organic products. The actual prices for the conventional and the organic alternatives were selected on the basis of market prices in autumn 2007 when the study was carried out.
After the purchase simulations, face-to-face interviews based on a standardized highly structured questionnaire were conducted to shed light on factors influencing the buying behavior. First, all participants were asked which of the two remaining alternatives they would have chosen if the preferred product had not been available. Secondly, attitudes toward food quality and safety were explored by 18 Likert-scaled statements. This section was included in the questionnaire since previous research showed that consumer attitudes toward topics such as health, nutrition, protection of the environment and lifestyle influence the propensity of organic food consumption (e.g., see Hughner et al.Reference Hughner, McDonagh, Prothero, Shultz and Stanton8, Zanoli and NaspettiReference Zanoli and Naspetti18, Loureiro et al.Reference Loureiro, McCluskey and Mittelhammer19, Wier et al.Reference Wier, Andersen, Millock, Russell and Krarup20, Hill and LynchehaunReference Hill and Lynchehaun21). Thirdly, the participants were asked in an open-ended question which kind of milk, yogurt and apples (conventional or organic) they usually buy. Finally, socio-demographic variables were recorded.
The target group for this study were occasional consumers of organic food. These consumers purchase both, conventional as well as organic food, and are thus not fully committed to either of the two, which is why this consumer group was chosen for this study. To identify occasional consumers, a standardized screening questionnaire was used. The questionnaire included an organic index that was based on the buying frequency of organic products in several product groups (see Table 2). People with an organic index between two and nine points (out of a maximum of 14 points) were considered occasional buyers. In this context, we would like to point out that even though non- and fully committed buyers were excluded, there is still a considerable range of organic consumption propensities among the participants of the study.
Table 2. Excerpt from the screening questionnaire.
1 The recruiters repeated this question for each product group listed in the table and marked the respective answer. Afterwards, the recruiters calculated the total score by summing up the points of the answers.
Data collection
The survey was conducted in three cities in central Germany in October and November 2007. The purchasing power of the three administrative districts (99.6, 94.0 and 90.8, respectively) is relatively close to the German average (100.0)22. The participants for the purchase simulations were recruited based on quota sampling for age and gender using a standardized screening questionnaire. The recruiters approached people in public places like shopping malls, pedestrian areas and in front of supermarkets. People who fulfilled the screening criteria were asked to participate in the study and were given an appointment for the actual survey which, on average, took place two days later. The participants were informed that they would take part in a European study on consumers' preferences for food. No particular reference to low-input food was made. The purchase simulations and interviews were conducted in seminar rooms of the local universities or the YMCA, respectively. Upon arrival at the survey location, participants were given standardized information on the course of the survey. After the interviews, the participants were informed that the product packages in the purchase simulations had been designed for the purpose of the study.
Data analysis
Apart from uni- and bivariate analyses, a cluster analysis was conducted using SPSS 15.0 to detect groups of participants with similar buying patterns across the product categories. The term ‘cluster analysis’ covers different methods for grouping objects (e.g., persons) according to certain characteristics, aiming at identifying homogeneous subgroups of objects within a heterogeneous populationReference Aaker, Kumar and Day23. In our study, the participants were grouped according to their buying behavior in the purchase simulations. An agglomerative hierarchical cluster analysis was used. The buying behavior was thereby measured by nine binary variables (three per product category). Six participants who had realized the ‘no choice’ option in one or more of the product categories were excluded from the sample as these cases determined outliers (reduced sample size n=143). The remaining participants were then grouped with the average linkage (within groups) method using the Russel and Rao coefficient as proximity measure. A four-cluster solution was selected based on the elbow criterion and considerations of interpretation and manageability.
In order to identify factors that influence the buying behavior of consumers, the four clusters were analyzed based on information collected in the interviews. First, the clusters were compared regarding their attitudes toward food quality and safety. For each statement, the mean ratings of the clusters were compared by an analysis of variance (ANOVA). Secondly, the clusters were analyzed by means of ANOVA and two-sided Z-tests, respectively, regarding differences in socio-demographic variables.
Description of the sample
The socio-demographic make-up of the sample is summarized in Table 3. Altogether, the sample consisted of 149 participants of which 71.1% were female. The sample thus corresponded to previous empirical studies indicating that women are predominantly responsible for the food purchase in German householdsReference Müller and Hamm24, Reference Spiller, Lüth and Enneking25. Two age groups were used in the quota sampling (18 to 44 and 45 to 75 years), and 49.7% of participants fell within the younger group. This share was almost identical with the proportion of this age group within the German population between 18 and 75 years old26. The average age of the participants was 42 years. The level of education was relatively high in the sample with 60.4% of participants holding a university or college degree, whereas among the German population above 20 years of age, a share of only 12.5% was reported in 200726. This could be ascribed to the target group of occasional organic consumers. Previous studies showed that, on average, consumers of organic food had a higher level of education than the rest of the populationReference Wier, O'Doherty Jensen, Andersen and Millock27, Reference Niessen28. Single person households were overrepresented in the sample. They accounted for 45.6% of all households compared to 37.5% in Germany26. About a quarter of the participants had children up to 18 years, which corresponded to the German average26. Regarding the propensity of organic food consumption, a relatively high organic index was measured with a mean of 6.6 and a median of 7. More than half of the participants reached a high index of 7 to 9 points indicating that they were frequent buyers of organic food. The remaining 47.0% were light to medium consumers with an index between 2 and 6 points.
Table 3. Summary statistics of the socio-demographic variables.
1 Percentages add up to more than 100%, as multiple responses were possible.
Results
The actual choices made in the purchase simulations are presented in Table 4. The organic products were bought most frequently by more than half of the participants in all product categories. For milk and yogurt, the low-input products accounted for the second highest shares of purchases, whereas the conventional products had the lowest shares. Regarding apples, the order was switched: conventional apples were bought slightly more often than low-input apples.
Table 4. Product alternatives bought in the purchase simulations.
Influence of price level on buying behavior
Across the sample, the product alternatives in the purchase simulations were offered at four different price levels. According to economic theory, the hypothesis to be tested was: the higher the relative price of an alternative, the lower the buying frequency. To determine whether an association existed between the price levels and the buying decision (organic, low-input or conventional), Chi-square tests of independence were applied. No significant associations could be detected (milk: χ2=5.902, df=6, P=0.434; yogurt: χ2=7.114, df=6, P=0.310; apples: χ2=7.491; df=6, P=0.278). The buying frequencies of the three alternatives were thus not influenced by the different relative prices. This result implies that price premiums close to those for organic products may be realized for low-input products.
Switch-over to low-input products
A comparison between the buying behavior in the purchase simulations and the stated usual buying behavior was used to analyze whether low-input products substituted organic or conventional products. The low-input alternatives were offered at higher prices than conventional products but were cheaper than the organic alternatives. Given that higher prices for organic food are referred to as the main purchase obstacle in the literatureReference Hughner, McDonagh, Prothero, Shultz and Stanton8, it could be assumed that buyers of conventional products would not be willing to pay a price premium for low-input products. Buyers of organic products, in contrast, might be attracted by low-input products that are cheaper than organic yet offer one specific quality attribute. It was thus hypothesized that low-input products would primarily substitute organic products.
Interestingly, our results showed low-input products substituted conventional products to a much larger extent than organic products. Within the group of participants who stated that they usually buy the particular product in conventional quality, the share of people who chose the low-input alternative in the purchase simulations accounted for 31.1% for milk, 40.2% for yogurt and 27.3% for apples. Within the group of people usually buying the particular product in organic quality, the share of people who chose the low-input alternatives was significantly lower (based on two-sided Z-tests to compare column proportions) accounting for 13.6, 8.9 and 0.0% for milk, yogurt and apples, respectively. The conclusion can therefore be drawn that low-input products attracted people who usually buy the particular product in conventional quality.
Perception of low-input products as an intermediate choice
From the viewpoint of the production process, low-input products can be classified as an intermediate alternative between conventional and organic products. In our study, it was hypothesized that consumers share this view and perceive low-input as an intermediate alternative. To answer this question, the choices in the purchase simulations were compared with the stated ‘alternative choice’. The alternative choice refers to the product that the participants would have chosen if the preferred product had not been available. In all three categories, the great majority of participants who chose the organic product in the purchase simulations ranked the low-input alternative second. This also applies to the conventional buyers. Irrespective of the product category at hand, the low-input product was thus seen as the most favorable second alternative by both conventional and organic buyers. The rankings of the low-input buyers revealed a rather diverse picture across the three categories. For milk, about two-thirds of the low-input buyers chose organic and one-third conventional as their second alternative. For apples, the opposite ranking was observed. Here, more than three-fourth of the low-input buyers ranked the conventional alternative second. Yet for yogurt, the low-input buyers were split into almost equal groups regarding their second alternative. Altogether, it can be concluded that low-input was perceived as an alternative ‘in between’ conventional and organic by the great majority of participants.
Buying behavior across the three-product categories
In the purchase simulations, each participant made three consecutive purchase decisions and bought milk, yogurt and apples. Across the whole sample, the order of the three kinds of products (milk, yogurt and apples) rotated evenly. In the descriptive analyses above, results are presented for each of the three product categories separately. We also examined the ‘baskets of goods’ that people bought, in order to reveal particular buying patterns across the product categories. Initially, participants' buying behavior across the product categories was of interest: 30.9% of participants bought organic products in all three categories, whereas 2.7% each chose exclusively low-input and conventional products (see Table 5). The remaining 63.8% of participants bought ‘mixed baskets of goods’. This relatively high share of participants with mixed purchases was also reflected elsewhere in the data: taking into consideration all three purchase decisions per participant, the great majority (85.2%) of participants bought at least one organic product; about half (49.7%) of the participants chose at least one low-input product and around one-third (33.6%) bought at least one conventional product.
Table 5. Baskets of goods bought in the purchase simulations.
1 Number of organic, low-input and conventional products, respectively, in the ‘baskets of goods’.
2 Note that percentage values per column may not add to 100 due to rounding.
Grouping participants with similar buying behavior by cluster analysis
Buying behavior of the clusters (Fig. 1).
— Cluster 1 ‘Organic buyers’: Cluster 1 had the highest overall share of organic buyers. In all three-product categories, more than three-quarters of the cluster members chose the organic alternatives. Interestingly, if a product was not bought in organic quality, Cluster 1 members preferred conventional alternatives. These accounted for small shares of less than 20%, whereas low-input products played an almost negligible role. A high-organic affinity was also reflected in the mean organic index, which was the highest of all clusters (6.9 points). Similarly, the stated usual buying behavior for milk, yogurt and apples featured the highest shares of organic purchases of all clusters.
— Cluster 2 ‘Additive avoiders’: All members of Cluster 2 bought low-input yogurt without artificial additives. Regarding milk and apples, about 70% of cluster members chose organic and the others low-input products. With one exception, no conventional products were bought. Four people chose all products in low-input quality. For the majority of cluster members, organic quality was important for unprocessed products. Regarding fruit yogurt (a processed product), however, the absence of artificial additives seemed being sufficient to meet their needs. The great majority of Cluster 2 usually bought conventional yogurt, whereas the stated usual buying behavior for milk and apples showed considerable shares of organic buyers. Cluster 2 had the second highest mean organic index of the clusters (6.6 points).
— Cluster 3 ‘Concerned about animal welfare’: All members of Cluster 3 bought milk ‘from pasture-raised cows’. Also regarding yogurt, the buying behavior was (almost) unanimous: with one exception, all members bought organic yogurt. Only for apples, the choice varied with organic apples being bought most often followed by low-input. A comparison with the stated usual buying behavior revealed two-thirds of people substituted conventional milk with milk ‘from pasture-raised cows’, whereas the remaining one-third usually bought either organic, or one-half each organic and conventional milk. Regarding yogurt, almost half of the cluster members usually bought conventional products, which were substituted with organic yogurt in the purchase simulations. Similarly, the majority of cluster members usually bought conventional apples. In the purchase simulations, these were mostly substituted with low-input or organic apples. Cluster 3 had the third highest mean organic index (5.9 points).
— Cluster 4 ‘Conventional buyers’: Cluster 4 members exclusively bought conventional and low-input products in the purchase simulations. Accordingly, their stated usual buying behavior featured the highest shares of conventional buyers of all clusters. Cluster 4 had the second highest shares of low-input buyers for milk and yogurt of all clusters, whereas all members bought conventional apples. Cluster 4 had the lowest mean organic index (5.4 points).
Attitudes toward food quality and safety
The comparison of the four clusters regarding attitudes toward food quality and safety by means of an ANOVA revealed seven statements with high discriminatory power (see Table 6). Altogether, the most significant differences existed between ‘Organic buyers’ (Cluster 1) and ‘Conventional buyers’ (Cluster 4). According to our results, the ‘Organic buyers’ (Cluster 1) were consumers with a great interest in health, nutrition and organic food. They perceived GM food and artificial flavors and additives as harmful to human health. Of all clusters, they expressed the least trust in food from Germany. By contrast, the ‘Conventional buyers’ (Cluster 4) were rather carefree consumers. In accordance with their buying behavior, they found organic products too expensive. Cluster 4 members expressed lower concerns regarding GM food and artificial flavors and additives, and they generally trusted food produced in Germany. Clusters 2 and 3 represented less distinct groups that did not differ significantly from each other for any of the statements. Compared with Clusters 1 and 4, only a few significant differences could be detected. Most importantly, Clusters 2 and 3 expressed a more positive attitude toward organic food and cared more about animal husbandry than Cluster 4. Interestingly, no significant differences between the socio-demographic compositions of the clusters could be detected.
Figure 1. Buying behavior of the four clusters in the purchase simulations.
Table 6. Attitudes regarding food quality and safety.
* P<0.05; ** P<0.01; *** P<0.001.
1 Likert-scaled questions with 5=strongly agree, 4=slightly agree, 3=neither agree nor disagree, 2=slightly disagree, 1=strongly disagree.
Two of the original 18 statements were excluded from the analysis due to contradictions in understanding across the sample. These statements are not listed here.
2 The F-test was used for those statements for which equality of variances in the clusters can be assumed (based on Levene's test for equality of variances).
3 The Welch-test was used for those statements for which equality of variances in the clusters cannot be assumed (based on Levene's test for equality of variances).
Discussion and Conclusions
The cluster analysis showed interesting insights regarding low-input products. Most strikingly, low-input products attracted two different groups of buyers: first, people who usually buy mostly conventional products (Cluster 4), and secondly, people who usually buy conventional products in particular categories and organic in others (Clusters 2 and 3). More regular organic buyers (Cluster 1), in contrast, did not favor low-input products. Moreover, low-input products mainly substituted conventional products. Overall, the low-input alternatives of the three-product categories did not necessarily attract the same group of people. One striking result of our study was that we did not identify a consumer segment of ‘typical low-input-buyers’. This is not surprising, given that three very different attributes were tested, referring to aspects of animal husbandry for milk, food additives for yogurt, and the use of pesticides for apples. It is therefore hard to predict the potential success of individual low-input products in the market-place. Nevertheless, some general implications can be derived from our studies that are discussed in the following sections.
Characteristics of organic consumers
Similar to previous studiesReference Hughner, McDonagh, Prothero, Shultz and Stanton8, Reference Lin, Smith and Huang29, our data indicate that demographic characteristics alone do not sufficiently explain the propensity to buy organic. Our results furthermore confirm the findings by Hughner et al.Reference Hughner, McDonagh, Prothero, Shultz and Stanton8 in which occasional organic consumers are considered a heterogeneous group. First, we found different patterns in buying behavior across the sample. For example, some people bought organic yogurt but non-organic milk and others vice versa. Second, our findings are consistent with previous research showing that motivations and attitudes provide reasons for differences in buying behaviorReference Hughner, McDonagh, Prothero, Shultz and Stanton8,18–Reference Hill and Lynchehaun21. Most of the studies mentioned here differentiated between non, occasional and committed consumers. Our study focused on occasional consumers exclusively. While some statements turned out to have little discriminatory power, we still found a number of statements regarding attitudes toward quality and safety that varied between the clusters. We therefore suggest that more research on consumers' motivations, perceptions and understanding of organic production should be conducted, not only comparing committed with occasional consumers but also revealing differences among occasional consumers.
Strategic implications for organic product sales
A previous longitudinal study on household panel data revealed that organic budget shares of households fluctuate in the course of time, especially among not fully committed buyersReference Wier, O'Doherty Jensen, Andersen and Millock27. Apparently, consumers change their minds regarding organic products, and they are not necessarily loyal over time. The study suggests that consumers frequently switch between organic and conventional products. It is therefore not surprising that a considerable share of consumers switched to alternatives that they usually did not buy. Against the background of fluctuating organic budget shares, we suggest that low-input products can compete with organic products. Especially consumers with a lower propensity to buy organic purchase their organic products mainly at regular supermarkets and discount stores4, Reference Wier, O'Doherty Jensen, Andersen and Millock27, which are the same sales channels through which low-input products are distributed. In this consumer segment, low-input might therefore take away future market shares from both conventional and organic products. In comparison with low-input products, organic products incorporate not only one but also many special attributes. The low-input products in our experiments were not certified by an external body and yet they reached shares of 15–30% of the purchases. A concerted communication strategy focusing on tangible aspects of organic production as well as organic certification might be a successful strategy for the organic sector to gain new customers and to differentiate organic products from low-input products.
Limitations of the study
In our study, purchase simulations were conducted to analyze consumers' buying behavior. As with stated preference data in general, the results of the purchase simulations have to be interpreted with careReference Hensher, Rose and Greene30. Foremost, the buying frequencies of the three-product alternatives should not be used to predict market shares for the following reasons. By definition, only occasional consumers participated in the study, and the sample size was relatively small due to budget constraints and the complex design of the study. Furthermore, the offered products were not branded. It thus remains unclear how consumers would have reacted if conventional, low-input and organic products with well-known brands had been used in the purchase simulations. Nevertheless, stated preference data generally provide a good picture about overall trendsReference Louviere, Hensher and Swait31. While the success of the tested products in reality remains unknown, it is possible to derive general implications and reveal needs for future research from stated choice data.
Acknowledgements
We are grateful to three anonymous referees for their valuable comments on the manuscript. The authors gratefully acknowledge funding from the European Community's financial participation under the Sixth Framework Programme for Research, Technological Development and Demonstration Activities for the Integrated Project QualityLowInputFood, FP6-FOOD-CT-2003-506358. The views expressed in this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Neither the European Commission nor any person acting on behalf of the Commission is responsible for the use, which might be made of the information contained herein.
