Abstract
Labeling strategies are often discussed in the context of local food purchase. Substantial research has been undertaken to discern buyers’ preferences for different labeling strategies associated with a production practice or a geographic location. Some studies have also emphasized the substitution or complementarity effects that may occur across these different labels. Using a large choice experiment with 1820 respondents across six US southern states, this research evaluates buyers’ preferences for co-labeling strategies, focusing on the association of a production practice and certifications (USDA Organic and Certified Naturally Grown) alongside six different production locations, ranging from local to imported sources. We focus on pint baskets of cherry tomatoes, chosen due to their popularity among purchasers of fresh produce. Based on the results provided by a Bayesian Mixed Logit model, we derived the respondent-specific posterior distribution of the partworths associated with each production location and regressed each of those against demographic indicators. Our findings highlight that most buyers substitute between USDA Organic and Certified Naturally Grown (CNG), and a minority consistently opt for the same production practice option. In addition, we underscore that price, or an indication of origin predominantly guides nearly half of buyers’ choices. We find that the premium for CNG is slightly superior to the organic one. Last, older respondents and respondents with a higher degree of education value produce grown within their state over neighboring states and more distant origins.
Sales of local food commodities saw a notable increase of $9 billion between 2015 and 2020 [US Department of Agriculture, National Agricultural Statistics Service (USDA NASS) 2016, 2022]. Direct-to-consumer sales accounted for 33% of this total (USDA NASS 2022) in 2020. The onset of the COVID-19 pandemic resulted in shutdowns and shortages in produce supplies, leading to a surge in at-home meal preparation, which, in turn, drove an 8.5% rise in total food-at-home expenditures compared with 2019 (USDA Economic Research Service 2023). Several studies, such as Thilmany et al. (2021), have highlighted the impact of the pandemic in boosting consumers’ interest in local purchase in 2020 and early 2021. Conversely, other studies (Vecchi et al. 2022) suggest that the spike in local purchases was mainly led by a lack of supply and was short-lived.
The future trend of local food purchases has been and remains a key question when it comes to small farms’ long-term economic performance, and this ultimately depends mainly on the volume of sales and the size of the price premium they receive (King et al. 2010 in Martinez and Park 2021). Substantial research has focused on buyers’ preferences for attributes leading to price premiums. In the context of direct-to-consumer marketing, indications of origin and production practices have become a proxy for value-added, which comprise the major attributes explaining buyers’ willingness to pay (WTP). More specifically, studies have shown price premiums attributed to specific labeling strategies, such as the organic certification (Batte et al. 2010; Haghiri et al. 2009; Jensen et al. 2019; Li and Kallas 2021; Meas et al. 2015; Yiridoe et al. 2005), “pesticide-free” (Baker 1999), “non-GMO [genetically modified organism] verified” (McFadden and Lusk 2018), “sustainably grown” (Maples et al. 2018), “natural” (Lang and Rodrigues 2022) or various geographic levels of origin such as “Country of Origin Labeling” (COOL) (Loureiro and Umberger 2003; Lusk et al. 2006; Mabiso et al. 2005; Umberger 2004; VanSickle 2008), “State branding” like Arizona Grown, South Carolina Grown, or Georgia Grown (Carpio and Isengildina-Massa 2009; Grebitus et al. 2016; Naasz et al. 2018), or “region-of-production branding” such as Vidalia (Carter et al. 2006; Deselnicu et al. 2013).
Although there is no clear definition or regulating body in place to monitor locational designations (Moser et al. 2011), the broad concept of “local” has also been subject to a lot of attention (Carpio and Isengildina-Massa 2009; Darby et al. 2008; Feldman and Hamm 2015 for a review; Grebitus et al. 2013; Hu et al. 2012; Onken and Bernard 2010; Shi et al. 2016). Surveys conducted in different US regions converged in demonstrating that buyers’ WTP does generally fall as distance to product origin increases—thus indicating a preference for local production. Moser et al. (2011) concluded more than a decade ago that the attribute “local” is generally relevant to the decision to buy fresh fruits and vegetables. It is accepted that buyers recognize the perceived benefits associated with local such as quality and freshness, better tasting, supporting nearby rural areas, and short transportation distances (Roininen et al. 2006). Most importantly, locally grown products may enhance the trust of consumers who personally know the producers of their fruits and vegetables (Midmore et al. 2005; Rodriguez-Ibeas 2007; Thilmany et al. 2008). Confirming this finding, Bond et al. (2006) identified “locally grown” as the most important production attribute by “direct primary purchasers,” emphasizing in passing the growing popularity of local food systems.
Interestingly, most of these studies uncover the puzzling finding according to which local attribute outranks indication of production practice such as organic or naturally grown despite a well-documented list of benefits attributed to these. With regard to organic, the motives for consuming organic food are manifold. Well-documented benefits given by buyers would include health, nutritional value, taste, animal welfare, ethics, and environmental protection (Bourn and Prescott 2002; Fotopoulos and Krystallis 2002; Makatouni 2002; Truong et al. 2021; Zanoli and Naspetti 2002). Consequently, a key assertion lies in the fact that many consumers perceive benefits of local foods to be rather similar to expected benefits from organic foods (Denver and Jensen 2014; Hempel and Hamm 2016a, 2016b; Wägeli and Hamm 2016). Another key assertion can be made in that consumers balance the potential benefits and costs of organic products (Bezawada and Pauwels 2013). Costs would typically be represented by organic foods being more expensive than conventional products and more difficult to find in the exact form, flavor, and quantity the consumer prefers (Michelsen et al. 1999), giving a competitive advantage to locally grown commodities. Compared with organic and the local attribute, and to our knowledge, reasons to buy CNG are not very well referenced in the literature. This fairly new certification (founded in 2002), based on peer inspection and less burdensome requirements than USDA organic certification, has gained a lot of traction among producers and buyers according to recent case studies and surveys we conducted in the southeastern region. In addition, in the few studies comparing organic and “natural” (Chen et al. 2020; He et al. 2020; and the following studies cited in Lang and Rodrigues 2022: Abrams et al. 2010; Anstine 2007; Chambers et al. 2018; Gifford and Bernard 2011), findings suggest that consumers associate “naturalness” with both labels as well as healthiness and quality pointing out a substitution effect between the two.
Consequently, numerous studies highlight a potential substitution or complementarity effects (e.g., Adams and Salois 2010; Campbell et al. 2014; Chen et al. 2015; James et al. 2009; Meas et al. 2015; McFadden and Huffman 2017; Onozaka and Thilmany-McFadden 2011; Yue and Tong 2009) and suggest that “local” often overlaps with other informative labeling such as organic, naturally grown, sustainably grown, or non-GMO, in buyers’ minds. Curtis et al. (2014) illustrated this potential substitution with a study showing that products grown conventionally in Utah (“locally”) outweighed either organically or conventionally grown of unknown origin. McFadden and Lusk (2018) pointed out that in the presence of a non-GMO material label, organic is not necessarily valued, that is, buyers are not willing to pay more for both labels as their perception is that organic does not include GM material. “Local has become the new organic” (Meas et al. 2015). However, other research found a strong positive interaction effect (Adams and Salois 2010; Hasselbach and Roosen 2015), finding that the premium for organic was markedly higher, if the product was also local.
In the context of this debate and based on recent studies (Lang and Rodrigues 2022), we argue that most studies evaluate each production label separately and that little research has been focused on how buyers interact with origin and different production practice labels concomitantly. Therefore, our objective is 2-fold. In terms of advertising strategy, there is a need to understand more specifically what precise geographic level is associated with the attribute local in the context of buying fresh produce. We also need to clarify how it plays into buyers’ preferences and willingness to pay a premium when this indication of origin is associated with a production certification such as USDA-Certified Organic or CNG. Agribusinesses with limited market reach and attributes of differentiation should benefit from the understanding of co-labeling strategies that would best attract and retain their buyers.
Data and Methods
An online survey was administered equitably in six US southern states (Alabama, Florida, Georgia, North Carolina, South Carolina, and Tennessee) in December 2021. Participants were recruited using Qualtrics, panel provider, that streamlined the process of recruiting targeted survey participants, managed the survey distribution, and ensured the quality of survey responses. Participants were informed that the purpose of the study focused on the purchase of fresh produce. Quotas were applied on demographic variable such as gender (60% female, 40% male), geographic location (N = 300 per state), age and income representative of the southern population, and the purchase of fresh produce in the last month from the state they live in (50%). The final sample comprised 1820 respondents. General questions were related to point of purchase, amount of the expense on a weekly basis, responsibility of grocery shopping, and frequency of purchase. Table 1 presents the demographic information of our sample.
Demographic composition of the sample population (N = 1,820).
The sample exhibits a higher proportion of female respondents (57.6%) compared with male, reflecting the prevalent understanding that women in American households typically take on a greater role in procuring of food and beverages. Various age groups are well represented, with 52.7% of respondents born on or after 1981 and 47.3% born before 1981. Lower-income individuals were oversampled compared with the southern population. This is attributed to the panel’s characteristics in which lower income shows greater willingness to participate in a survey for monetary incentives. In addition, rural and suburban areas are slightly overrepresented compared with the national statistics in terms of living areas.
Respondents to our online survey (N = 1820) were asked general questions about their buying behavior regarding produce. Among the primary sources for purchasing produce (multiple choice), major supermarket is the primary source with 70.2% of our sample, then grocery stores with 58.3%; 27.9% checked local farmers’ market, 6.4% online farmers’ market, and 3.9% Community Supported Agriculture (CSA); 12.8% get their produce at a convenience store, and 11.2% mentioned that they grow their own produce.
To the question: “How much does your household spend weekly on fruits and/or vegetables?” most respondents (37.6%) spend between $25 and $49; 31.3% spend less than $25, 24.1% between $50 and $99, and 7.2% spend $100 or more; 75.3% declared they were primary shoppers and 19% shared the grocery shopping equally.
Some respondents were eliminated from the sample because of pervasive inconsistencies or lack of response. Most who were dropped checked the “opt-out” option in more than half the scenarios. The final sample yielded 1725 respondents.
Survey design.
A choice experiment was used to collect information on respondents’ stated preferences and WTP for different attributes associated with direct purchases of produce. USDA Organic, CNG, and Unspecified Production Practice (UPP) were established as the three invariable alternatives regarding production practice for each choice set. Choosing the term “unspecified” over conventional or traditional wording in production practice descriptions aims to prevent any preconceived notions or misconceptions that respondents might have regarding these practices. A distinctive aspect of our design involves setting the production practices in the same order across all choice sets presented to each respondent. In doing so, our aim was to assess which combinations of attributes respondents would associate with their preferred production practices. We assumed that although some respondents would consistently choose a particular alternative regardless of other factors, others might be more inclined to switch based on the additional attributes presented, beginning with a specific origin.
We added a variation of six different origins going from “grown in my metro area or county” to “imported.” Average prices for the different production labels were calculated based on observed data in local stores, online, at farmers markets, and supermarkets that represent the typical places of purchase. Then, a 12.5% rate was applied to make prices vary around the average for each production label. This approach is in contrast to randomly assigning prices because purchasers logically expect price premiums for specialty produce. Setting the production attributes while making the origin and price attributes vary should give a better understanding of how consistent buyers’ preferences are. In terms of product, we presented a pint basket of cherry tomatoes because these are popular items among purchasers of fresh produce (Table 2).
Attribute and levels used in the choice experiment.
Our final design was established using SAS (mkt commands) and maximizing D-efficiency (93.1085), whereby D-efficiency allows for comparison of the orthogonal balance of the design with design efficiency (Kuhfeld 2003, 2010). The 36 choices were then divided into three blocks to limit respondent fatigue. Each respondent was asked to choose among the four alternatives (three production practices and the opt-out option) offered across 12 choice sets randomly presented. Before prompted to select their preferred option, respondents were given some information illustrated by Fig. 1.
Example of a set of attributes presented to the respondents using Qualtrics.
Citation: HortScience 59, 6; 10.21273/HORTSCI17769-24
Model specification.
To evaluate the WTP and utility of co-labeling alternatives, we used a choice experiment method, a widely used technique to understand consumer preferences for attributes of agricultural produce (e.g., Maples et al. 2018). We estimate a Bayesian Mixed Logit model (Train 2009) to analyze the choices of the respondents. Briefly, we specify the utility obtained by the nth respondent from the jth alternative (j = 1, 2, …, i, …, J) for choice experiment task t (t = 1, 2,…, T) to be Unjt = xnjtβn + εnjt, where x is a 1xk vector of attributes, εnjt is iid extreme value, and for the random coefficients we have βn ∼ N(b, D). If the observed choice for the nth respondent at the tth task is alternative i, this implies the respondent is maximizing utility in the sense that Unit>Unjt for all j ≠ i.
We estimate a Bayesian Mixed Logit model (Train 2009) to analyze the choices of the respondents. Allenby et al. (2005, p. 2) state that the “Bayesian method is a useful tool for modeling multi-faceted, non-linear phenomena such as those encountered in marketing.” They note that this choice is particularly relevant when the analyst wants to focus on individual behavior, and they claim that the Bayesian approach is ideally suited for this. A hierarchical Bayes mixed logit procedure identifies each person’s βn by specifying the prior distribution for b as normal and the prior distribution for D as inverted Wishart. The posterior distributions of βn and b are normal and inverted Wishart for D. These are termed the layers of the Gibbs sampling mechanism. The Bayesian Mixed Logit model differs from the maximum simulated likelihood method in that the βn are considered parameters to be estimated along with b and D. Because the βn are individual-level parameters, they describe each respondent’s tastes given the respondent’s choices and the population parameters b and D.
We use the Bayesian Mixed Logit model of Train (https://eml.berkeley.edu/Software/abstracts/train1006mxlhb.html) and on convergence of the Bayesian estimator, bn can be considered as the mean of the posterior distribution of βn, so that the individual-level random coefficients can be estimated. In our study, these individual-level coefficients are interpreted as partworths that can be associated with individuals and their characteristics.
Choice Results
The following segment of analysis is based on the results of the choice experiment using different attributes: price, origin, and production practices labels. The Bayesian Mixed Logit model was estimated using the USA origin as the base case. The full variance-covariance matrix (D) of the random parameters was estimated because this allows accounting for scale heterogeneity (Hess and Train 2017). Only the price parameter was not specified to be random. This was done for two reasons. First, because our focus is on the distribution of the partworths across the respondents for the production practices and locations, a fixed price coefficient provides a cleaner interpretation of the partworths. Second, as Train explains, identification of all parameters of a Bayesian Mixed Logit model is often impossible unless one or more parameters are specified as fixed. Given that we are estimating the additional 28 covariances of the random parameters, this stabilizes the results. Before retaining draws, a 10,000-iteration burn-in was conducted. Then a total of 40,000 iterations were performed using 4000 draws. The estimation results are presented in Table 3.
Bayesian Mixed Logit regression results for the population parameters.
The estimated premium, calculated as the ratio of the attribute’s coefficient to the price coefficient, for a CNG pint of cherry tomatoes is slightly higher than for the organic version, respectively $3.25 and $2.71, compared with a UPP that appears to have less value (−$1.06). Literature usually calculates the organic premium (Dentoni et al. 2009; Greene and Dimitri 2002; Onozaka and Thilmany-McFadden 2011; Sackett et al. 2016; Zepeda and Leviten-Reid 2004, cited in Maples et al. 2018) and most buyers expect higher prices when it comes to organic produce, which constitutes a potential explanation of these higher premiums. However, to our knowledge, a handful of studies have specifically compared organic and CNG (Chen et al. 2020; He et al. 2020) highlighting an overall higher WTP for organic compared with CNG and local. Therefore, our finding that these premiums are comparable may be an indication of substitution between organic and CNG.
These results can be more easily interpreted by calculating the distribution of draws in the population implied by b and the estimated D. This takes into account both sources of variation in the partworth parameters.
The results in Table 4 clearly show that respondents have widely varying assessments of the values of all the attributes. For each partworth, its standard deviation generally exceeded the (absolute) value of its mean. With regard to production practice, 10.3% of respondents reveal a negative partworth for organic and 3.6% reveal a negative partworth for CNG. We interpret this result as suggesting that a portion of respondents are price sensitive and consequently are not willing to pay the price premiums for the organic and CNG options. More interesting, ∼61% of the respondents have a negative partworth for the UPP.
Estimated posterior mean and variation of individual-level partworths.
Estimates for origin show an association between close geographic location to the respondent, such as grown in a nearby area or county, grown in my metro area or county, and grown in my state with implied values of $0.50, $0.55, and $0.52, respectively. However, grown in a neighboring state or imported has less value than grown in the USA with −$0.18 and −$1.56, respectively. A large proportion of respondents reveal a negative partworth (83%) when the origin of the cherry tomatoes indicates they were imported, followed by “grown in a neighboring state” (56%) compared with “grown in the USA.” Other studies have pointed out the importance of state branding programs in advertising agricultural products (Naasz et al. 2018) and also highlighted that a foreign indication of origin tends to dissuade buyers (Campbell et al. 2014).
Beyond the indication of preferences, clearly a substantial variation in the values of the partworths across individual respondents needs to be underscored. In looking at patterns in the respondents’ choices we can see important variation among respondents and the inconsistency in choosing the same production label (Table 5).
Classification of the sample based on choice pattern regarding the production practice.
These variations seem to indicate three buyers’ profiles. For nearly half of our sample (45.5%), substitution between options mainly occurs between organic and CNG. For 42.5% of our respondents, we found a great variation in their choices between the different production practices and the opt out. Last, 12% always chose the same option with a higher response rate for CNG (7.6%) compared with organic (2.7%) and UPP (1.4%). The pattern of choice for our first profile seems to align with the substitution among production labels highlighted in the literature (Ditlevsen et al. 2020; Lang and Rodrigues 2022; McFadden and Huffman 2017) where consumers’ perceptions of benefits are similar for organic and naturally grown. We corroborate these conclusions about organic and CNG. Our second profile of respondents who had a greater variation of their choices among the four options were clearly influenced by price or origin attributes. These results may support Lee and Yun (2015) studies explaining a substitution effect involving organic by consumers’ misperceptions or lack of awareness. Buyers who consistently chose the same production practice (100% organic, 100% CNG, or 100% UPP) pertain to our third profile. As mentioned before, they represent a much smaller sample, which we interpret as evidence of how multifactorial the purchase of fresh produce can be.
Although the considerable variation in the partworths precludes unambiguous statements of preferences, it does permit analysis at the individual level. Because the mean partworths of each respondent are calculated, we can associate them with individual-level characteristics. The attraction of this approach stems from the fact that individuals’ observed patterns of choices shape their partworths—not a survey or some other elicitation method to infer their valuations of the attributes. The following (Table 6) are regressions with the mean of the respondent-specific posterior distribution of the partworth associated with location and production practice as the dependent variable and demographic measures as the explanatory variables (all self-explanatory except for $F&V, which measures the average amount of dollars spent for all fruits and vegetables on a weekly basis).
Results of regressions of individual-level partworths on each individual’s demographic variables.
Adding sociodemographic variables such as age, gender, location of residence, education degree, and average amount spent weekly on fresh produce, we identify significant results. Older generations put more value on cherry tomatoes that were grown within a closer geographic range (i.e., their county, neighboring counties, or their state). They tend to put less value if the product comes from a neighboring state or if it is imported. Respondents with a higher level of education generally put more value on cherry tomatoes grown at the neighboring county level. Interestingly, imported products appear to be more attractive than the locally grown version (more specifically neighboring county) for buyers with a higher average amount of fruit and vegetable expenditures. Regarding production practices, the value of USDA organic cherry tomatoes is strongly associated with higher amounts of purchase and an urban location of residence. Although the organic attribute is associated with a negative coefficient on age, organic tends to be more valued by younger respondents compared with older respondents. The pattern is different for CNG and UPP with both having a positive coefficient on age pointing out that older respondents put more value on those two. Moreover, the coefficient on area of residence shows that respondents located in suburban areas seem to put value on CNG cherry tomatoes.
Conclusion
Following the disruptions caused by the COVID-19 pandemic, local food sales saw a surge as traditional retail operations struggled with shortages in their supplies. However, as markets resumed to normal operation, local sales encountered heightened competition. Numerous studies have shown that premiums can be expected through labeling strategies that indicate the origin of production, such as regional or state branding, or specific production practices like USDA-Certified Organic or CNG. These labeling strategies can help products stand out in a competitive market and appeal to buyers seeking locally sourced or sustainably produced goods. However, these studies also underscore the ambiguity that surrounds buyers’ interpretation of the different production practices labels and between production practice and origin. As noted by Hasselbach and Roosen (2015), the potential to get a higher premium might also emerge from the combination of a local origin and the indication of production practice.
Our study is the first, to our knowledge, to show that respondents value CNG at a slight premium over USDA Organic. Our results also suggest that these two certifications may be perceived as substitutes. Evidence from our choice experiment analysis suggests three distinct buyer profiles explained by their preferences for production practices. Nearly half of our sample seems to substitute organic and CNG, whereas a much smaller sample consistently chooses one or the other. The last profile is characterized by buyers whose choices are mainly influenced by price and origin. Further, our findings suggest that the purchase of organic cherry tomatoes is associated with younger generations and those living in urban areas. If cherry tomatoes are grown in a close geographic location such as county, nearby county, or state, older respondents valued them more than when they are from a neighboring state or imported.
This study contributes to the ongoing discussion about the value of information conveyed by labeling. Expanding on prior research, we contend that the combination of an indication of local origin and a reputable production practice certification such as CNG or USDA Organic seems to yield higher premiums compared with alternatives solely focused on one or the other, and set origin against production practice. Furthermore, correlating these findings with younger demographics residing in suburban areas with higher disposable incomes, we gain insights into their preferences, which indicate an inclination for an origin within their state borders combined primarily with CNG, and to a lesser extent, USDA Organic. In a competitive environment, it is crucial to implement effective labeling strategies that differentiate specific standards of production and origin. These strategies merit consideration to enhance the patronage and expenditure of buyers, particularly younger and newer ones.
References Cited
Abrams KM, Mayers CA, Irani TA. 2010. Naturally confused: consumers’ perceptions of all-natural and organic pork products. Agric Hum Values. 27:365–374. https://doi.org/10.1007/s10460-009-9234-5.
Adams DC, Salois MJ. 2010. Local versus organic: A turn in consumer preferences and willingness-to-pay. Renew Agric Food Syst. 25(4):331–341. https://doi.org/10.1017/s1742170510000219.
Anstine J. 2007. Organic and all natural: Do consumers know the difference? J Appl Econ Policy. 26(1). https://kentuckyeconomicassociation.org/journalofappliedeconomicsandpolicy/wp-content/uploads/2021/01/JAEP-Spring-2007-Publication-26-1.pdf#page=20. [accessed 8 Oct 2023].
Allenby GM, Rossi PE, McCulloch RE. 2005. Hierarchical Bayes models: A practitioner’s guide (January 2005). http://dx.doi.org/10.2139/ssrn.655541. [accessed 8 Oct 2023].
Baker GA. 1999. Consumer preferences for food safety attributes in fresh apples: Market segments, consumer characteristics, and marketing opportunities. J Agric Resour Econ. 24(1):80–97. https://www.jstor.org/stable/40987009.
Batte MT, Van Buren FN, Hu W, Woods T, Ernst S. 2010. Do local production, organic certification, nutritional claims, and product branding pay in consumer food choices? Selected paper prepared for presentation at the Agricultural and Applied Economics Association 2010 AAEA, CAES, and WAEA Joint Annual Meeting, Denver, CO, USA, 25–27 Jul 2010.
Bezawada R, Pauwels K. 2013. What is special about marketing organic products? How organic assortment, price and promotions drive retailer performance. J Mark. 77(1):31–51. https://doi.org/10.1509/jm.10.0229.
Bond JK, Thilmany D, Bond CA. 2006. Direct marketing of fresh produce: Understanding consumer purchasing decisions. Choices. 21(4):229–235. https://www.choicesmagazine.org/2006-4/produce/2006-4-06.htm.
Bourn D, Prescott J. 2002. A comparison of the nutritional value, sensory qualities, and food safety of organically and conventionally produced foods. Crit Rev Food Sci Nutr. 42(1):1–34. https://doi.org/10.1080/10408690290825439.
Campbell BL, Khachatryan H, Behe BK, Dennis J, Hall C. 2014. US and Canadian consumer perception of local and organic terminology. Int Food Agribus Manag Rev. 17(2):21–40. https://ifama.org/resources/Documents/v17i2/Campbell-Behe-Dennis-Hall.pdf. [accessed 8 Oct 2023].
Carpio CE, Isengildina-Massa O. 2009. Consumer willingness to pay for locally grown products: The case of South Carolina. Agribusiness. 25(3):412–426. https://doi.org/10.1002/agr.20210.
Carter C, Krissoff B, Zwane AP. 2006. Can country-of-origin labeling succeed as a marketing tool for produce? Lessons from three case studies. Can J Agric Econ. 54(4):513–530. https://doi.org/10.1111/j.1744-7976.2006.00064.x.
Chambers E, Chambers E IV, Castro M. 2018. What is “natural”? Consumer responses to selected ingredients. Foods. 7(4):65. https://doi.org/10.3390/foods7040065.
Chen X, Gao Z, McFadden BR. 2020. Reveal preference reversal in consumer preference for sustainable food products. Food Qual Prefer. 79:103754. https://doi.org/10.1016/j.foodqual.2019.103754.
Chen X, Gao Z, House L. 2015. Willingness to pay for niche fresh produce across the states: Why are consumers willing to pay more for the less favorite? In 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia, no. 196901. Southern Agricultural Economics Association. http://dx.doi.org/10.22004/ag.econ.196901.
Curtis KR, Gumirakiza JD, Bosworth R. 2014. Consumer preferences and willingness to pay for multi-labeled produce at farmers markets. Food Distribution Research Society. 45(1):14–20. https://doi.org/10.22004/ag.econ.164547.
Darby K, Batte MT, Ernst S, Roe B. 2008. Decomposing local: A conjoint analysis of locally produced foods. Am J Agric Econ. 90(2):476–486. https://doi.org/10.1111/j.1467-8276.2007.01111.x.
Dentoni D, Tonsor GT, Calantone RJ, Peterson HC. 2009. The direct and indirect effects of ‘locally grown’ on consumers’ attitudes towards agri-food products. Agric Resour Econ Rev. 38(3):384–396. http://dx.doi.org/10.22004/ag.econ.59252.
Denver S, Jensen JD. 2014. Consumer preferences for organically and locally produced apples. Food Qual Prefer. 31(1):129–134. https://doi.org/10.1016/j.foodqual.2013.08.014.
Deselnicu OC, Costanigro M, Souza-Monteiro DM, McFadden DT. 2013. A meta-analysis of geographical indication food valuation studies: What drives the premium for origin-based labels? J Agric Resour Econ. 38(2):204–219. https://doi.org/10.22004/ag.econ.158285.
Ditlevsen K, Denver S, Christensen T, Lassen J. 2020. A taste for locally produced food - Values, opinions and sociodemographic differences among ‘organic’ and ‘conventional’ consumers. Appetite. 147:104544. https://doi.org/10.1016/j.appet.2019.104544.
Feldmann C, Hamm U. 2015. Consumers’ perceptions and preferences for local food: A review. Food Qual Prefer. 40:152–164. https://doi.org/10.1016/j.foodqual.2014.09.014.
Fotopoulos C, Krystallis A. 2002. Purchasing motives and profile of the Greek organic consumer: A countrywide survey. Br Food J. 104(9):730–765. https://doi.org/10.1108/00070700210443110.
Gifford K, Bernard JC. 2011. The effect of information on consumers’ willingness to pay for natural and organic chicken. Int J Consumer Stud. 35(3): 282–289. https://doi.org/10.1111/j.1470-6431.2010.00929.x.
Grebitus C, Lusk JL, Nayga RM Jr. 2013. Effect of distance of transportation on willingness to pay for food. Ecol Econ. 88:67–75. https://doi.org/10.1016/j.ecolecon.2013.01.006.
Grebitus C, Peschel A, Hughner RS. 2016. Drivers of demand for specialty crops: The example of Arizona-Grown Medjool dates. No. 235545. Agricultural and Applied Economics Association 2016 Annual Meeting, Boston, MA, USA, 31 Jul–2 Aug. http://dx.doi.org/10.22004/ag.econ.235545.
Greene C, Dimitri C. 2002. Recent growth patterns in the US organic foods market (No. 777). US Department of Agriculture, Economic Research Service. https://www.ers.usda.gov/publications/pub-details/?pubid=42456. [accessed 19 Mar 2024]
Haghiri M, Hobbs JE, McNamara ML. 2009. Assessing consumer preferences for organically grown fresh fruit and vegetables in eastern New Brunswick. Int Food Agribus Manag Rev. 12(4):1–20. https://ifama.org/resources/Documents/v12i4/Haghiri-Hobbs-McNamara.pdf. [accessed 8 Oct 2023].
Hasselbach JL, Roosen J. 2015. Consumer heterogeneity in the willingness to pay for local and organic food. J Food Prod Mark. 21(6):608–625. https://doi.org/10.1080/10454446.2014.885866.
He C, Shi L, Gao Z, House L. 2020. The impact of customer ratings on consumer choice of fresh produce: A stated preference experiment approach. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie. 68(3):359–373. https://doi.org/10.1111/cjag.12222.
Hempel C, Hamm U. 2016a. Local and/or organic: A study on consumer preferences for organic food and food from different origins. Int J Consum Stud. 40(6):732–741. https://doi.org/10.1111/ijcs.12288.
Hempel C, Hamm U. 2016b. How important is local food to organic-minded consumers? Appetite. 96(1):309–318. https://doi.org/10.1016/j.appet.2015.09.036.
Hess S, Train K. 2017. Correlation and scale in mixed logit models. J Choice Modelling. 23:1–8. https://doi.org/10.1016/j.jocm.2017.03.001.
Hu W, Batte MT, Woods T, Ernst S. 2012. Consumer preferences for local production and other value-added label claims for a processed food product. Eur Rev Agric Econ. 39(3):489–510. https://doi.org/10.1093/erae/jbr039.
James JS, Rickard BJ, Rossman WJ. 2009. Product differentiation and market segmentation in applesauce: Using a choice experiment to assess the value of organic, local, and nutrition attributes. Agric Resour Econ Rev. 38(3):357–370. https://doi.org/10.22004/ag.econ.59248.
Jensen JD, Christensen T, Denver S, Ditlevsen K, Lassen J, Teuber R. 2019. Heterogeneity in consumers’ perceptions and demand for local (organic) food products. Food Qual Prefer. 73:255–265. https://doi.org/10.1016/j.foodqual.2018.11.002.
King RP, Hand MS, DiGiacomo G, Clancy K, Gomez MI, Hardesty SD, Lev L, McLaughlin EW. 2010. Comparing the Structure, Size, and Performance of Local and Mainstream Food Supply Chains, ERR-99, US Department of Agriculture, Economic Research Service. https://www.ers.usda.gov/publications/pub-details/?pubid=46407. [accessed 3 Oct 2023].
Kuhfeld WF. 2003. Marketing research methods in SAS. SAS Institute Incorporated, Cary, NC, USA.
Kuhfeld WF. 2010. The macros, p 803–1211. In: Kuhfeld WF (ed). Marketing research methods in SAS. MR-2010. SAS Institute Inc., Cary, NC, USA.
Lang M, Rodrigues AC. 2022. A comparison of organic-certified versus non-certified natural foods: Perceptions and motives and their influence on purchase behaviors. Appetite. 168:105698. https://doi.org/10.1016/j.appet.2021.105698.
Lee HJ, Yun ZS. 2015. Consumers’ perceptions of organic food attributes and cognitive and affective attitudes as determinants of their purchase intentions toward organic food. Food Qual Prefer. 39:259–267. https://doi.org/10.1016/j.foodqual.2014.06.002.
Li S, Kallas Z. 2021. Meta-analysis of consumers’ willingness to pay for sustainable food products. Appetite. 163(1):105239. https://doi.org/10.1016/j.appet.2021.105239.
Loureiro M, Umberger W. 2003. Estimating consumer willingness to pay for country-of origin labeling. J Agric Resour Econ. 28(2):287–301. https://www.jstor.org/stable/40987187.
Lusk JL, Brown J, Mark T, Proseku I, Thompson R, Welsh J. 2006. Consumer behavior, public policy, and country‐of‐origin labeling. Appl Econ Perspect Policy. 28(2):284–292. https://econpapers.repec.org/RePEc:oup:revage:v:28:y:2006:i:2:p:284-292.
Mabiso A, Sterns J, House L, Wysocki A. 2005. Estimating consumers’ willingness-to-pay for country-of-origin labels in fresh apples and tomatoes: A double-hurdle probit analysis of American data using factor scores. American Agricultural Economics Association Annual Meeting, Providence, RI, USA, 24–27 Jul 2005. http://dx.doi.org/10.22004/ag.econ.19418.
Makatouni A. 2002. What motivates consumers to buy organic food in the UK? Results from a qualitative study. Br Food J. 104(3/4/5):345–352. https://doi.org/10.1108/00070700210425769.
Martinez SW, Park T. 2021. Marketing practices and financial performance or local food producers: A comparison of beginning and experiences farmers, EIB-225. Washington, DC: US Department of Agriculture, Economic Research Service, Economic Information Bulletin. http://dx.doi.org/10.22004/ag.econ.327367.
Maples M, Interis MG, Morgan K, Harri A. 2018. Southeastern consumers’ willingness to pay for environmental production attributes for fresh tomatoes. J Agric Appl Econ. 50(1):27–47. https://doi.org/10.1017/aae.2017.18.
McFadden JR, Huffman WE. 2017. Willingness-to-pay for natural, organic, and conventional foods: The effects of information and meaningful labels. Food Policy. 68:214–232. https://doi.org/10.1016/j.foodpol.2017.02.007.
McFadden BR, Lusk JL. 2018. Effects of the National Bioengineered Food Disclosure Standard: Willingness to pay for labels that communicate the presence or absence of genetic modification. Appl Econ Perspect Policy. 40(2):259–275. https://doi.org/10.1093/aepp/ppx040.
Meas T, Hu W, Batte MT, Woods TA, Ernst S. 2015. Substitutes or complements? Consumer preference for local and organic food attributes. Am J Agric Econ. 97(4):1044–1071. https://www.jstor.org/stable/24476540.
Michelsen J, Hamm U, Wynen E, Roth E. 1999. The European market for organic products: Growth and development. Universität Hohenheim - Stuttgart Hohenheim. Organic Farming in Europe: Economics and Policy, 7. https://projekte.uni-hohenheim.de/i410a/ofeurope/organicfarmingineurope-vol7.pdf. [accessed 8 Oct 2023].
Midmore P, Naspetti S, Sherwood AM, Vairo D, Wier M, Zanoli R. 2005. Consumer attitudes to quality and safety of organic and low input foods: A review. Report of EU-funded project Improving Quality and Safety and Reduction of Cost in the European Organic and ‘Low Input’Food Supply Chains. Univ. Wales, Aberystwyth, UK.
Moser R, Raffaelli R, Thilmany-McFadden D. 2011. Consumer preferences for fruit and vegetables with credence-based attributes: A review. Int Food Agribus Manag Rev. 14(2):121–142. https://doi.org/10.22004/ag.econ.103990.
Naasz E, Jablonski BBR, Thilmany D. 2018. State branding programs and local food purchases. Choices. 33(3):1–6. https://www.choicesmagazine.org/UserFiles/file/cmsarticle_653.pdf.
Onken KA, Bernard JC. 2010. Catching the ‘local’ bug: A look at state agricultural marketing programs. Choices. 25(1):1–7. https://www.choicesmagazine.org/UserFiles/file/article_112.pdf.
Onozaka Y, Thilmany-McFadden D. 2011. Does local labeling complement or compete with other sustainable labels? A conjoint analysis of direct and joint values for fresh produce claim. Am J Agric Econ. 93(3):693–706. https://econpapers.repec.org/RePEc:oup:ajagec:v:93:y:2011:i:3:p:689-702.
Rodriguez-Ibeas R. 2007. Environmental product differentiation and environmental awareness. Environ Resour Econ. 36(2):237–254. https://doi.org/10.1007/s10640-006-9026-y.
Roininen K, Arvola A, Lähteenmäki L. 2006. Exploring consumers’ perceptions of local food with two different qualitative techniques: Laddering and word association. Food Qual Prefer. 17(1-2):20–30. https://doi.org/10.1016/j.foodqual.2005.04.012.
Sackett H, Shupp R, Tonsor G. 2016. Differentiating “sustainable” from “organic” and “local” food choices: Does information about certification criteria help consumers? IJFAEC. 4(3):17–31. http://dx.doi.org/10.22004/ag.econ.244284.
Shi W, Halstead J, Huang JC. 2016. Consumers’ willingness to pay for locally grown produce: Comparison of New Hampshire and Massachusetts results. 2016 Agricultural and Applied Economics Association Annual Meeting, Boston, MA, USA, 31 Jul–2 Aug. http://dx.doi.org/10.22004/ag.econ.236109.
Thilmany D, Bond CA, Bond JK. 2008. Going local: Exploring consumer behavior and motivations for direct food purchases. Am J Agric Econ. 90(5):1303–1309. https://econpapers.repec.org/RePEc:oup:ajagec:v:90:y:2008:i:5:p:1303-1309.
Thilmany D, Canales E, Low SA, Boys K. 2021. Local food supply chain dynamics and resilience during COVID‐19. Appl Econ Perspect Policy. 43(1):86–104. https://doi.org/10.1002/aepp.13121.
Train K. 2009. Discrete choice methods with simulation (2nd ed). Cambridge University Press, New York, NY, USA.
Truong VH, Lang B, Conroy DM. 2021. Are trust and consumption values important for buyers of organic food? A comparison of regular buyers, occasional buyers, and non-buyers. Appetite. 161:105123. https://doi.org/10.1016/j.appet.2021.105123.
Umberger W. 2004. Will consumers pay a premium for country-of-origin labeled meat? Choices (4th Quarter):15–20. https://www.choicesmagazine.org/2004-4/cool/2004-4-04.pdf.
US Department of Agriculture, Economic Research Service. 2023. Food Expenditure Series. Food expenditures by final purchaser. Washington, DC: US Department of Agriculture, Economic Research Service. https://www.ers.usda.gov/data-products/food-expenditure-series/. [accessed 8 Oct 2023].
US Department of Agriculture, National Agricultural Statistics Service. 2022. Direct farm sales of food. Results from the 2020 Local Food Marketing Practices Survey, ACH17-27. Washington, DC: US Department of Agriculture, National Agricultural Statistics Service. https://www.nass.usda.gov/Publications/Highlights/2022/local-foods.pdf. [accessed 8 Oct 2023].
US Department of Agriculture, National Agricultural Statistics Service. 2016. Direct Farm Sales of Food. Results from the 2015 Local Food Marketing Practices Survey, ACH12-35. Washington, DC: US Department of Agriculture, National Agricultural Statistics Service. https://www.nass.usda.gov/Publications/Highlights/2016/LocalFoodsMarketingPractices_Highlights.pdf. [accessed 8 Oct 2023].
VanSickle JJ. 2008. Country of origin labeling for fruits and vegetables. Choices. 23(4):43–45. https://www.choicesmagazine.org/UserFiles/file/article_46.pdf.
Vecchi M, Jaenicke EC, Schmidt C. 2022. Local food in times of crisis: The impact of COVID‐19 and two reinforcing primes. Agribusiness. 38:850–873. https://doi.org/10.1002/agr.21754.
Wägeli S, Hamm U. 2016. Consumers’ perception and expectations of local organic food supply chains. Org Agric. 6(3):215–224. https://doi.org/10.1007/s13165-015-0130-6.
Yiridoe EK, Bonti-Ankomah S, Martin RC. 2005. Comparison of consumer perceptions and preference toward organic versus conventionally produced foods: A review and update of the literature. Renew Agric Food Syst. 20(4):193–205. https://doi.org/10.1079/raf2005113.
Yue C, Tong C. 2009. Organic or local? Investigating consumer preference for fresh produce using a choice experiment with real economic incentives. HortScience. 44(2):366–371. https://doi.org/10.21273/HORTSCI.44.2.366.
Zanoli R, Naspetti S. 2002. Consumer motivations in the purchase of organic food: A means‐end approach. Br Food J. 104(8):643–653. https://doi.org/10.1108/00070700210425930.
Zepeda L, Leviten-Reid C. 2004. Consumers’ views on local food. J Food Distr Res. 35(3):1–6. http://dx.doi.org/10.22004/ag.econ.27554.
