Decomposing local: a conjoint analysis of locally produced foods.

Locally grown food is gaining increasing attention in a variety of arenas. The number of farmers markets, which largely purvey locally grown foods and goods, has grown dramatically in the United States, increasing 111% from 1994 to 2004. According to the 2004 National Farmers Market Directory (U.S. Department of Agriculture 2006), there are over 3,700 farmers' markets operating in the United States. Community Supported Agriculture (CSA) groups, where consumers "join" by purchasing a share of the total production of a single locally operated farm, has grown from a handful of model organizations in the 1980's to more than 1,000 such groups in 2006 (Tegtmeier and Duffy 2006). Whole Foods, the leading natural foods retailer in the United States, markets locally grown products, touting a variety of social, environmental, and quality benefits (Whole Foods 2006) whereas Wild Oats (2006), the third largest such retailer, features a "Choose Local" campaign that touts similar benefits. Forty-four state departments of agriculture administer programs that label and promote foods grown or processed within the state's borders. (1) The U.S. Department of Agriculture (USDA), through the Community Food Security Act, granted $22 million of support to 166 local food system initiatives from 1996 to 2003 (Tauber and Fisher 2002).

Clearly, there has been a ground swell of support for marketing products as "locally grown" over the past decade. Marketing products directly in local markets provides an opportunity for farmers to capture a greater share of consumers' food budgets and, because many of the marketing services are provided locally, better stimulates local economies. As the local food movement grows, however, several questions arise surrounding consumers' demand for locally produced foods, which may impact the margins obtainable by local producers.

One of the more vexing questions is how consumers define the term "local." The ability for firms to differentiate along the "locally grown" dimension depends crucially on the consumers' perception of what qualifies as locally grown--a perception that is not well understood. Furthermore, if many firms qualify as "local" in the eyes of consumers, then "locally grown" food becomes less scarce and, hence, the market may become saturated and premiums for such foods may diminish. Therefore, calibrating the geographic extent of the "locally grown" market is important for estimating the number of firms that could utilize such a marketing strategy and the likely margins that might accrue to implementing such differentiation as the local food movement continues to grow.

Another crucial question is how consumers value the "locally grown" aspect of a food product independent from other attributes that are often naturally confounded with such goods, including greater freshness and "anti-corporate" images that locally grown food purveyors often present. If consumers' willingness to pay (WTP) for local foods is largely driven by freshness and corporate image concerns, savvy marketers from national brands may find ways to better provide or document product freshness and project a more friendly corporate image that may cut into the margins obtained by locally produced foods. However, if distance between the production site and the consumer is the driving factor, it may be more difficult for national firms to compete against locally produced foods.

The purpose of this article is to begin to address these two issues surrounding consumer demand for locally produced goods. Using stated preference data from a choice-based conjoint analysis (CA) survey instrument, we estimate WTP for fresh strawberries that are differentiated with respect to the location of their production, the type of entity producing the product (corporate vs. noncorporate production), and the guaranteed freshness of the product. These estimates provide insight into the value that households place on each attribute, allow us to circumscribe the geographical extent of "localness" for the sample of consumers that participated in the study, and to decompose WTP for strawberries into the several components that may contribute to the value of locally produced food.

The rest of the article is organized as follows. The next section offers a brief review of the conjoint methodology and develops a utility-theoretic model of product choice from which a measure of compensating variation is derived. The section following this describes the sample, survey and experimental design, and the empirical model. The next section reports the results from the estimation of the utility model and the resulting compensating variation estimates. The final section concludes with a discussion of the implications of the results for the marketing of locally produced foods.

Conjoint Analysis

CA is a term given to a suite of stated preference elicitation methods in which the researcher identifies key attributes of a product of interest that are believed to influence respondent preferences, chooses different levels for each attribute representative of the variation that the researcher would like to explore, formulates numerous profiles of the product featuring permutations of the attribute levels that are chosen to satisfy an experimental design, prompts respondents to evaluate various product profiles, analyzes respondents' evaluations of the product profiles to draw inferences concerning preferences over attributes, and uses the estimated preference structure to evaluate scenarios of interest (Hensher, Louviere, and Swait 1999).

CA (Louviere 1988) was first used to assess the commercial appeal of consumer goods (for a review of such studies, see Green and Srinivasan 1990) and later was adopted by environmental and agricultural economists and formally embedded in a utility-theoretic framework to assess the welfare effects of altering nonmarket goods (e.g., environmental protection) and introducing goods with novel attributes (e.g., genetically modified ingredients). Our application of CA to food products is based upon a random utility framework and requires respondents to choose one of two experimentally generated product profiles. Because the profiles include attributes pertaining to the location of production, organizational format of the producer (corporate or not), product freshness, and price, we can derive discrete measures of WTP for each attribute.

CA and other constructed market techniques have been used to better understand consumer preferences for foods differentiated by the location of production, usually in the context of designating that production occurred "near" the consumer (e.g., country of origin labeling, or COOL, and Region of Origin Labeling, or RoOL) or in a region historically recognized for high-quality production of a specific good (protected designation of origin, or PDO, and protected geographical identification, or PGI).

In an experimental auction, Umberger et al. (2002) showed that 69% of consumers had positive WTP estimates for beef carrying a label indicating it was produced in the United States. However, in a related study, Loureiro and Umberger (2004) use CA to estimate WTP for CoOL versus other safety labels on beef. They show that CoOL labeling does not generate a positive WTP, whereas food safety certification and traceability certification do. Mabiso et al. (2005) used an auction experiment to show that the CoOL label garnered premiums for fresh produce. In the case of apples (tomatoes), 79 (72)% paid a premium with the average premium being $0.48 ($0.49).

Scarpa, Phillipidis, and Spalatro (2005) used CA to estimate WTP for the PDO label on olive oil as well as a CoOL label on oranges and table grapes. In the case of table grapes, they found WTP for these attributes to have about the same impact on preferences as more common characteristics such as color and ripeness. The CoOL label on oranges had nearly four times the impact of firmness and absence of imperfections. Loureiro and McCluskey (2000) cite cultural identification as well as perceived quality to account for premiums found using a hedonic model on PGI Galecian veal. Van der Lans (2001) isolates two reasons for WTP for RoOL on olive oil: the direct effect (i.e., cultural identification) and its indirect effect through perceived quality. Using conjoint techniques, the study shows that, whereas PDO labels only have the indirect effect, RoOL labels have the additional direct effect, especially for consumers from the same region.

Brown (2003) found that in response to the question, "Would you pay a price that was lower, the same, or higher for products labeled 'locally grown' versus unlabeled products of the same quality?" 58% of food consumers were unwilling to pay a premium for food products labeled as "locally grown" provided that the unlabeled products were of the same quality. However, 16%, 5%, and 1% said they would pay more than a 5%, 10%, or 25% premium, respectively.

Although several studies in this literature provide some decomposition of the natural confound between the location of a product's production and its quality, none attempt to also control for the "corporate" status of the firm producing the product. Furthermore, from the standpoint of the United States, 44 states currently provide state-level product designations, which have yet to be explored in the context of consumer perception of "local" production.

Conjoint Modeling

In formalizing our model of product choice, we assume the individual's indirect utility functions can be approximated as a linear function of net income, product attributes, and interaction terms: