Abstract
Consumers are becoming increasingly concerned about the sustainability of their purchases. The coffee industry has been a leader in developing initiatives that promote the adoption of sustainable practices along the value chain. Labels on coffee packages that denote sustainable attributes are intended to inform the consumer and encourage sustainable consumption. The main objective of this study was to analyze consumers’ knowledge of, and preference for sustainable labels (Fairtrade, Organic USDA, Rain Forest Alliance, and 4C) on coffee in Honduras, a developing low-income and high-quality coffee exporting country. The study also evaluated the consumer’s visual attention to sustainable coffee labels. Data were collected using a questionnaire (including a choice experiment) from a sample of 450 consumers, as well as eye-tracking technology (a subsample of 65 consumers). Although Honduran coffee consumers have low levels of familiarity and knowledge about sustainable labels, they are willing to pay premiums for coffee with these labels (10% to 27% relative to average prices). Consumers pay more attention to the Organic USDA label, which is also the label with the highest willingness to pay value. Overall, the study’s results indicate that there is a domestic market for coffee produced sustainably in Honduras.
1. Introduction
The term ‘sustainable’ refers to a system that persists over time (Rodríguez Lacherre, 2013). Although much emphasis is placed on the production aspects of sustainability, consumption is an equally important component, as consumers’ decisions affect the environment (OCDE, 2002). Because these consumer-related effects tend to be negative, it has been argued that it is important to promote the consumption of sustainably produced goods to reduce the harm to human health and the environment (United Nations Environment Programme, 2015). In fact, one of the Sustainable Development Goals is responsible consumption, to protect planet earth, eliminate poverty, and promote peace and prosperity (United Nations Development Programme, nd).
The world population is expected to reach 9.3 billion by 2050. This level of population growth implies increased and competing demands for natural resources, food production, water consumption, and energy use (Bulege, 2013). Therefore, agriculture, an activity essential to human survival, must be able to play its part sustainably (Velten et al., 2015).
There are two potential approaches to sustainable agriculture, the first of which is economic. In this approach, market forces guide the farmers’ decision-making process. The second approach balances economic and social objectives with environmental goals, but often reaches a point where the farmers’ profitability is adversely affected (Shelef et al., 2018; DeClerck et al., 2016; James, 2006). In the first approach, the farmer engages in sustainable practices because it is profitable. This is where sustainable consumption is important. Consumers can send market signals to farmers by choosing sustainable products, which promote sustainable agricultural practices (Grunert, 2011). In the second approach, sustainable practices are usually enforced through regulations.
The coffee industry has been a leader in the agricultural sector in developing and implementing initiatives that promote the adoption of sustainable practices along the value chain (Miner, 2003). These initiatives are designed to improve livelihoods in rural areas, preserve biodiversity, and create market opportunities. For example, the International Coffee Organization (ICO) promotes awareness among coffee producers, and encourages them to produce sustainable coffee with a focus on environmental, social, and economic sustainability to achieve a reasonable standard of living for coffee farmers (International Coffee Organization, nd).
At the same time, consumers’ demand for healthy and sustainable food products has been increasing. As a result, sustainable programs have grown quickly in the coffee industry (Pierrot et al., 2010), and information about coffee products’ sustainability is presented to consumers on the products’ labels (Miner, 2003). These labels (and logos) on coffee packages are intended to inform the consumer, increase the value chain’s transparency, and promote sustainable consumption (Grunert et al., 2014).
This study was conducted in Honduras, which lies in the heart of the Central American isthmus. Honduras is the second largest country in the region with an area of 112,492 km2, and a population of 9,523,621 (Ministerio de Asuntos Exteriores, Unión Europea y Cooperación, 2022). Honduras real GDP has grown at an average annual rate of 3.1% over the last decade, but it is still considered one of the poorest countries in the Western Hemisphere. However, the government intends to promote more economic opportunities among those in the country who are the most vulnerable (The World Bank, 2022).
Coffee is one of the most important agricultural products in Honduras, and approximately 100,000 families, largely low-income, are engaged in coffee production. The coffee sector represents about 30% of the agricultural and 5% of the total GDP (Álvarez, 2018; INE, 2019). Furthermore, Honduras is the largest coffee producer in Central America, third in America, and fifth worldwide (IHCAFE, 2013). The country is also the fourth largest coffee exporting country (IHCAFE, 2019). Most of the coffee production in the country is destined for export markets, with only about 7% destinated for local consumption (INE, 2019). However, domestic consumption is rising because of increases in population and per capita income, mainly among the younger population (IHCAFE, 2013). The ICO estimates that each person consumes 2.39 kilos of coffee annually in Honduras, which means that every person consumes approximately 320 cups of coffee per year (US Department of Agriculture, 2022). Also, according to the US Department of Agriculture Report on 2022, ‘domestic coffee consumption shows a similar upgrowth pattern from 1 to 4% in roasted and soluble coffee consumption’. The growth in average personal income and education levels are also expected to increase the demand for higher-quality food products in the country (The Nielsen Company, 2017).
Sustainable coffee production is a relatively new concept in Honduras, as registration of differentiated coffees began only in the 2009–2010 harvest. While there are types of production systems that claim sustainability, not all of them guarantee it (e.g. organic, eco-friendly and Fairtrade). Many certifications possess sustainability standards for the coffee industry that are closely aligned with the balanced social, environmental, and economic requirements needed for sustainability. Moreover, despite sustainability being a credence attribute, some of certification schemes allow for verification. Because of this, the term ‘sustainable coffee’ is used in this paper as a shorthand description for certified coffee, without implying that non-certified coffees are not sustainable (Giovanucci and Koekoek, 2003). The primary sustainability certification schemes currently present in the Honduran markets are Fairtrade, Organic, Rain Forest Alliance, and 4C (Standard code of behavior for the coffee community) (4C Services GmbH, nd), with 41% of the total coffee exported certificated and specialty (Giovanucci and Koekoek, 2003; IHCAFE, 2019).
There is still very limited academic literature that has explored consumer demand for sustainability attributes in coffee in Latin America, as existing studies have been conducted in importing countries, but not in coffee producing-exporting countries. Therefore, this study’s main objective was to analyze consumers’ knowledge and preference for coffee with sustainability themed labels (Organic USDA, Fairtrade, Rain Forest Alliance, and 4C) in Honduras, a developing coffee exporting country. The study also evaluated the visual attention to sustainable coffee labels.
2. Literature review
The literature review reflected that sustainable consumption is important. Several studies have explored the demand and perceptions of sustainable coffee products using various methods, including surveys, interviews, and experiments (Samoggia and Riedel, 2018). All previous studies were conducted in coffee importing countries and focused only on a limited number of sustainability-related labels.
This literature review is divided into two sections. First, the studies on the demand for sustainable coffee and labels is presented. Then, barriers to consumers’ selection of products with sustainable labels, focused on eco-labels in general, is presented.
Most research can be found on the more popular sustainability labels, such as Fairtrade, Organic and Rain Forest Alliance. All these labels were found in Honduras, with the exception of 4C, and many studies have compared consumer preferences and willingness to pay regarding purchase intentions (Anagnostou et al., 2015; Andorfer and Liebe, 2013; Van Loo et al., 2015; Yang et al., 2014). The Instituto Hondureño del café (IHCAFE) (2016) reported that certified coffee had increased its consumption, since ‘consumers currently showed great interest in the intrinsic social, economic and environmental characteristics, and the high quality that these represent’. The International Labor Organization (2020) supported the last statement stating that among the most important private initiatives for a sustainable coffee production in Honduras are Rain Forest Alliance, Fairtrade, Organic, Nespresso and C.A.F.E. Practices. Additionally, these certification systems work with other food products in Latin America, such as apples, soybean, pears, corn, cocoa, quinoa, chía, bananas, honey, rice, sugar, tea, sugar, vegetables, fruits and nuts (Fairtrade International, nd; Rain Forest Alliance, nd; USDA, nd). There is scant literature focused on consumer preferences for coffee sustainability attributes in developing countries. And none of them studied environmental, social and economic aspects at the same time.
Andorfer and Liebe (2013) evaluated whether price, budget restrictions, consumer identity, social and personal norms, social status, justice beliefs, and trust influence Fairtrade coffee’s consumption. The study was conducted in three supermarkets in Hanover, Germany, and the authors used a natural field experiment approach. The results indicated that the price was the only aspect that affects Fairtrade certified coffee consumption.
Anagnostou et al. (2015) evaluated consumers’ perceptions of coffee with sustainability labels, including Fairtrade and Organic schemes. The study was developed with a role-playing scenario in supermarkets in the Netherlands. The authors assessed consumers’ perceptions before and after exposure to coffee with sustainable labels. They found that when consumers were exposed to sustainable coffee, their perception of conventional coffee deteriorated.
Yang et al. (2014) explored Chinese consumers’ willingness to pay (WTP) for Fairtrade coffee. A total of 564 participants participated in a survey that asked questions about their coffee consumption habits, perceptions, WTP for sustainable coffee labels, and demographic information. The results showed that consumers would pay more for Fairtrade coffee than for conventional coffee.
Van Loo et al. (2015) explored the way visual attention affects consumers’ behavior toward coffee with sustainable labels, specifically Fairtrade, Organic, USDA, Rain Forest Alliance, and Carbon Footprint labels in Arkansas, United States. The authors measured visual attention using eye-tracking technology and analyzed its correlation with the different attributes used in a choice experiment. The results indicated that consumers valued coffee with sustainable labels more and gave special attention to sustainability labels when present.
As part of this study, it was decided to include a conceptual framework based on several factors that could affect human behavior. According to Grunert (2011), there are six barriers to consumers’ selection of food products with sustainable labels: (1) exposure; (2) perception; (3) understanding and inference-making; (4) decision-making; (5) awareness and credibility, and (6) motivation. The first barrier is related to the package label, which the consumer must at least notice. The second is when the consumer sees a sustainable label but is not interested in it. The third is related to inferences consumers make about the product, in which they identify, but misinterpret the label. The fourth includes the existence of other attributes that may be preferred over sustainability when consumers make purchasing decisions. The fifth is a lack of awareness, in which consumers may be unfamiliar with a particular label. Finally, the sixth barrier is lack of motivation, in which the consumer may not be motivated to favor a specific attribute (Grunert et al., 2014). This framework has been used in studies that have employed self-reported use or perceived importance of sustainable food attributes (Vanhonacker et al., 2013; Van Loo et al., 2015) In this study, we focus on the first four barriers using attitudinal and eye-tracking measures while consumers make coffee choices.
Finally, this study makes two main contributions to the literature. First, we analyze the demand for sustainable labels on coffee using a choice experiment in the context of a developing exporting country, which to the best of our knowledge has not been done. Second, we use eye-tracking technology to assess the effect of visual attention on information related to sustainability, which allows us to understand consumers’ visual attention when making a food choice (iMotions, nd).
3. Methodology and data collection
As stated above, two main data collection methods were used for this research: (1) a questionnaire and (2) eye-tracking measures to complement the choice data. The questionnaire collected data on consumers’ responses to a choice experiment, as well as their knowledge about sustainability labels, perceived importance of coffee attributes, and demographics (gender, age, children, marital status, education, employment status, and monthly household income). The eye-tracking experiment collected data on a sub-group of the participants’ visual attention to coffee packages through a without-contact device. The data collection was carried out from November 2021 (385 people answered the survey) to February 2022 (65 people used the eye tracking and answered the survey).
The participants for this study were recruited from two groups. In the first, 385 participants completed an online survey that a market research company (Offerwise.com) distributed. The company sent the survey to individuals in their consumer research panel, which is representative of the population of Honduran shoppers. In the second group, 65 participants were recruited at the mini market of Zamorano University, located at km 30 on the Pan-American highway from Tegucigalpa to Danlí, Honduras. The mini market is open to employees, students, and the general public. Participants at the mini market completed the survey in front of the eye-tracker. All 450 participants were coffee consumers and lived in Honduras.
3.1 Choice experiment
In a choice experiment, participants are presented with a series of task choices from which they must select one alternative. In this research, participants had to choose among three alternatives: two coffee products (that differ in their characteristics) and a no-buy option. The coffee products consisted of a package of 350 g roasted ground coffee with different prices and four sustainability labels that Honduran farmers adopt most commonly: Fairtrade, Organic USDA, Rain Forest Alliance, and 4C (Standard code of behavior for the coffee community) (4C Services GmbH, nd). Each sustainability label had two levels: present or absent. The price attribute had four levels, L. 73.00 (USD 3.03), L. 139.00 (USD 5.76), L. 205.00 (USD 8.50), and L. 271.00 (USD 11.24). The prices were chosen based upon actual prices observed on a popular Honduran supermarket’s webpage. A fractional factorial optimal design was used that resulted in eight choice tasks. The software Ngene (ChoiceMetrics, Sydney, Australia) was used to identify the combination of attributes in the different alternatives, which were presented to the participants randomly. The choice tasks are shown in Table 1.
Description of the choice tasks used in the choice experiment.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
3.2 Biometric procedures and measures
The biometric method used a Smart-Eye AI-X eye-tracker (Smart Eye AB, Gothenburg, Sweden) and the iMotions Module-eye Tracking (iMotions, Boston, MA, USA). While the respondents completed the choice experiment’s survey section on the computer, their eye movements were recorded using the eye-tracker device connected to a high-resolution computer screen (27 inch). The device was calibrated for each individual subject with the eye tracker’s default nine-point calibration procedure. Thereafter, the participants’ eye movements were recorded at a 60 Hz rate while they were seated approximately 65 cm from the screen and eye-tracker.
While the eye-tracker records many metrics, only the fixation count, dwell (fixation) time, and time of first fixation were considered (Table 2). The fixation count measures the number of times each participant’s eyes are looking at specific areas of interest (AOI). The fixation time measures the total time the respondents spend fixating on the AOI. Finally, the time of first fixation is the time when the respondents fixate first on the AOI (iMotions, 2018). The AOI on each coffee package was the labels (Organic USDA, Fairtrade, Rain Forest Alliance, and 4C) and the prices (Figure 1).
Biometric measures summary statistics.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
Example of choice tasks used in the choice experiment and biometrics procedures.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
The eye-tracking measures were estimated for each AOI using the eye-tracking software iMotions v. 9.1.27722.4 © 2005–2021. Ten eye-tracking measures were obtained per respondent, including two for each of the four sustainability labels (Organic USDA, Fairtrade, Rain Forest Alliance, and 4C) and two for price. The mean of each pair of measures was used for the statistical analysis. Figure 2 shows an example of a heat map generated based upon the eye-tracking measures.
Example of heat map on a choice task used in choice experiment and biometrics procedures.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
3.3 Sustainability awareness, knowledge, and preferences questionnaire
After finishing the choice experiment and biometric study, the participants were asked to complete a survey on (1) knowledge about sustainable labels, (2) coffee attributes’ importance, and (3) demographics.
Familiarity was measured by showing the participants the label’s image, accompanied by the question: ‘Do you know the following label?’ Participants had to choose one of three options: ‘I am acquainted’, ‘I have seen it before’, and ‘I do not know.’ Their understanding of the labels’ meaning was evaluated using the question. ‘Which of the following statements best describes X certification scheme?’ Five multiple choice answers were given, including the correct answer, three incorrect answers, and an ‘I do not know’ option.
The consumers’ perceived importance of coffee attributes was measured using a 7-point-Likert scale that ranges from ‘not at all important’ (1) to ‘extremely important’ (7) for a set of 13 attributes: flavor; price; type of roast; in-store promotion; size of the package; brand; caffeine content; the appearance of the packaging; country of origin, and Organic USDA, Fairtrade, Rain Forest Alliance, and 4C certified (Van Loo et al., 2010, 2015). The final survey section collected information about gender, age, children, marital status, education, employment status, and monthly household income.
3.4 Statistical analysis of survey and choice experiment
The data were analyzed in three ways. First, all data collected were analyzed using descriptive statistics, including means, percentages, standard deviations, and Pearson’s correlations. Second, the visual attention data were analyzed using ANOVA and Bonferroni comparison mean scores. Finally, a mixed logit model was used to analyze the data obtained from the choice experiments. SAS® v. 9.4 (Cary, NC, USA) and JASP v. 0.14.1 (Amsterdam, the Netherlands) were used.
3.5 Choice experiment – model and estimation
A random utility model was adopted as the conceptual framework to analyze the Honduran consumers’ choices. According to the random utility theory, the utility individual i obtains from choosing alternative j in choice situation t can be represented as a function of observed product characteristics and a random error term (McFadden, 1974). A linear-in-parameters formulation of the (indirect) utility model (Uijt) can be written as:
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
in which i=1, …, I; j=1, …, J; t=1, …, T. zijt is a vector of observed attributes related to the alternative product j and individual i;
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
in which 
, in which ki is a scale parameter for consumer i (Train and Weeks, 2005). Dividing the utility equation 2 by the scale parameter ki has the benefit of not affecting the model and provides an error term with a constant variance for all consumers:
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
in which (
. Equation 3 can be reparametrized such that
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
As the marginal WTP for the non-price attributes is the ratio of these attributes’ coefficient to the price coefficient (
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
The model in WTP space provides direct estimates of WTP values, which are used as measures of consumers’ preferences (Scarpa et al., 2008). The model parameters were estimated using simulated maximum likelihood procedures and STATA® v. 16.0 (Garcia Chaclan, 2020; Hole, 2013; Revelt and Train, 1998) with 1,000 random draws (Palma et al., 2020). A lognormal distribution was selected for the price coefficient, and normal distributions were chosen for the non-price attributes’ coefficients (i.e. the WTP values).
3.6 Factors that affect consumers’ willingness to pay for coffee sustainability attributes
A two-step procedure was used to analyze the relation between consumers’ WTP values for the coffee sustainability attributes and consumers’ characteristics. First, individual consumers’ WTP values for each coffee sustainability attribute were estimated using simulation procedures with 1,000 draws (Hess, 2007). Second, the association between demographic characteristics and perceptions of coffee and the estimated WTP values was assessed using the following linear model (Campbell, 2007):
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
in which WTPia is the ith consumer’s WTP for coffee sustainability attribute a (e.g. Organic), ca and b are coefficients, hi is a vector of explanatory variables, un is a consumer-specific random error, and eia is an idiosyncratic error term. Variables in hi include consumers’ knowledge and understanding of the labels, sociodemographic characteristics (household income was asked as a categorical variable, the consumers chose a range, instead of an exact number related to the income information; this variable was included in the model selecting the mid-point of the range) and eye-tracking metrics (subsample of 65 participants) (Mennecke et al., 2007).
4. Results
4.1 Demographic characteristics
A total of 450 respondents participated in the study. Most were women between 25–34 years old (39.23%), married/living together (50.67%), and with children (58.45%). Most respondents (58.45%) had professional degrees (including advanced technician, bachelor’s, and graduate degrees) as well, and had some form of employment (78.88%). The median monthly household income was between USD 301 and USD 500 (Table 3).
4.2 Choice experiment: visual attention based upon eye-tracking measures
The mean fixation count (F=1.05; P=0.38) and time of first fixation (F=0.85; P=0.49) did not differ statistically significantly across all of the AOI, which included the four sustainability labels and prices (Table 2). However, it was found that for every time that a consumer fixates his/her view on Fairtrade and Rain Forest Alliance attribute, the person is willing to pay USD 1.029 more for coffee with the Fairtrade label and USD 0.273 more for a coffee with the Rain Forest Alliance than for coffee with no label. The attention that every person pays to specific elements of a coffee bag such as sustainable labels affect the WTP for this product (Supplementary Table S1).
In contrast, the mean fixation time did differ significantly (F=4.58; P=0.001) across the AOI. Participants took, on average, only 12,369.92 milliseconds, or 12.36 seconds to see each choice set. However, this is consistent with consumer behavior, as consumers at the supermarket make decisions under time pressure (Pieters and Warlop, 1999). Usually, they go to the supermarket seeking a particular basket of products. According to Bialkova et al. (2020), a product of a specific brand is expected to be looked at or bought only if included in the consumers’ plan or if they know about the brand.
Price was the AOI with the longest mean fixation time (903.25 ms), followed by the sustainable labels (Organic USDA, Rain Forest Alliance, Fairtrade and 4C label, in that order). Moreover, price differed significantly from all labels but the Organic USDA label. Thus, among the labels, respondents exhibited the longest duration of fixation time for the Organic USDA label, with an average of 866.88 ms (Table 2). This suggests that this was the sustainable label to which consumers paid more attention when evaluating the coffee bags and choosing one of the alternatives. On the other hand, the 4C label had the shortest duration of fixation time, with an average of 689.26 ms. However, the 4C fixation time did not differ significantly from the Fairtrade and Rain Forest Alliance certification labels. This result contrasts with that of Van Loo et al. (2015), who also used price and sustainable labels (Organic USDA, Rain Forest Alliance, and Carbon Footprint) as AOI and found no significant difference across fixation time in the AOI. However, the context is different, as the study by Van Loo et al. was conducted in a developed country where consumers may be less concerned about prices and more concerned and knowledgeable about quality. Clearly, when a person goes to the supermarket, the decision is taken under time pressure in many cases which suggests that consumers may not have enough time to collect all the information presented in a food product, and thus fixate less on sustainability attributes.
Demographics characteristics of the sample (n=450) and Honduran population.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
4.3 Familiarity and understanding of sustainability labels
Responses to the labels’ familiarity questions indicated that most respondents were not very acquainted with the labels, as the self-reported familiarity levels were all 13% or less. Organic and Rain Forest Alliance had the highest level of familiarity (13%) and Fairtrade the lowest (7%) (Table 4).
Familiarity and knowledge of coffee sustainability labels by Honduran consumers.
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
The responses to the question that evaluated consumers’ understanding of labels showed higher levels and heterogeneity than familiarity. More than 30% of the respondents selected the correct answer for Organic USDA and Fairtrade, suggesting that these labels may be self-explanatory. The percentage of respondents who chose the correct answer for Rain Forest Alliance was 23%, and only 13% for the 4C label. In addition, a large percentage of respondents chose the ‘I do not know’ answer (23% or more).
These results are consistent with the findings of Annunziata et al. (2019). Their study reported that the sustainable Organic label was understood to a greater degree than the Fairtrade and Rain Forest Alliance labels. Further, Grunert et al. (2014) reported that consumers understand the Fairtrade label better than the Rain Forest Alliance and 4C labels.
Overall, these results indicated that Honduran consumers have a poor understanding and familiarity with sustainable labels. Not all consumers are familiar with or even understand the term sustainability. For example, Sánchez-Bravo et al. (2021) found that although the term is based upon three main factors (environment, economy, and society), many people believe that organic foods are the only sustainable products, which is consistent with the findings that the ‘Organic USDA’ label is one of the most familiar labels and the one that consumers understand better.
As Grunert et al. (2014) stated, one of the main barriers consumers face when they purchase sustainable products is understanding the labels, so more work is needed to educate Honduran consumers about sustainable labels’ meaning.
4.4 Coffee attributes’ importance
Flavor was the attribute with the highest mean importance rating, 6.37, which is near the highest ‘extremely important’ rating level (7.00). Price was the attribute with the second highest mean rating (5.70). Other intrinsic attributes, including type of roast and caffeine content, also ranked high in attribute importance (4th and 5th) (Table 5).
Descriptive statistics for the importance given to coffee attributes by Honduran consumers.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
The results of Honduran consumers’ perceived importance of coffee attributes are consistent with the results van Loo et al. (2015) obtained. Participants in their study also reported that flavor, price, type of roast, and in-store promotions were the most important to them. Further, the results are consistent with a Specialty Coffee Association (SCA) study (2016), which reported that flavor, roast type, and origin were the most important attributes for U.S. consumers. Therefore, price, flavor, and type of roast appear to be the most important coffee attributes for consumers in both developed and developing countries.
The relative importance of the sustainable labels varied from high to moderately important (Fairtrade, Organic USDA, and Rain Forest Alliance) to neither important nor unimportant (for 4C) (Table 4). In contrast, in the SCA’s (2016) study, U.S. consumers did not indicate that sustainability, as a concept overall, was important. This suggests that there is heterogeneity in the perceived importance of sustainability attributes in coffee across countries. In addition, the relative importance of sustainability may change over time.
4.5 Willingness to pay for sustainable attributes
All the mean WTP coefficients for sustainable attributes were positive and statistically significant, which indicates that Honduran consumers prefer coffee with sustainable labels to without them (Table 6). For example, the results indicated that Honduran consumers are willing to pay, on average, USD 1.94 more for coffee with the Organic USDA label than for coffee with no label. The mixed logit regression results also indicated a high degree of heterogeneity in consumers’ preferences, as the standard deviation coefficients were significant for all labels except 4C.
Results of the mixed logit model in willingness to pay space (USD) for sustainable coffee.1
Citation: International Food and Agribusiness Management Review 26, 4 (2023) ; 10.22434/ifamr2022.0126
ANOVA results suggested a significant difference between the Honduran consumers WTP (F=40.394, P<0.001). Post hoc testing using Bonferroni correction revealed that Organic USDA had a higher average WTP compared to the other attributes (P<0.001), the second one was Rain Forest Alliance (P<0.001) and no significant differences were found between Fairtrade and 4C.
The estimated WTP premiums for the sustainable labels ranged from USD 1.94 for a coffee with the Organic USDA label to USD 0.70 more for a coffee with the 4C label. These values are high considering that the average price used was USD 7.13, which indicates that consumers were willing to pay approximately 10 and 27% more than the average price depending upon the label on a coffee bag. Thus, Honduran consumers have strong preferences for coffee with sustainability labels.
Liu et al. (2019) found that consumers in Taiwan were willing to pay higher prices for Organic USDA and Rain Forest Alliance-certified coffees. Further, Veenarat et al. (2021) found that consumers in Thailand had a high WTP for sustainable coffee compared with conventional coffee (36% average premium or USD 2.41 for a bag of 25 g of coffee). Therefore, the literature has shown consistently that consumers are becoming aware of sustainability issues and are willing to pay premiums for coffee and food products with sustainable labels.
4.6 Consumers’ preferences as determinants of willingness to pay for sustainable attributes
Supplementary Table S2 presents the results of the linear regression models used to assess the association between individual WTP values for each of the four labels (Organic USDA, Fairtrade, Rain Forest Alliance and 4C) and consumers’ demographics and familiarity and knowledge of the sustainability labels. Consumers’ familiarity with Organic USDA, Fairtrade, and Rain Forest Alliance was associated with greater WTP for those labels. For example, familiarity with the Fairtrade label was associated with a USD 1 larger premium for this label. This highlights the importance of educating consumers about the labels (Aprile and Punzo 2022; Bastounis et al., 2021; USDA, 2017). However, the regression results did not reveal clear patterns in the associations between WTP values and sociodemographic characteristics, although gender, education, and income were associated with premiums for some labels. The WTP for Organic USDA label incremented USD 0.497 for having received education (advanced technician, bachelor and master/Ph.D.) more than for not having received education. On average, from eight to ten additional years of age after 18, there was a reduction in the WTP for Fairtrade label in USD 0.026. Women were willing to pay USD 0.117 more for a coffee with that Rain Forest Alliance label than men, while the converse was true with the Fairtrade label. Higher education levels and income were associated with higher WTP values for several sustainable labels, consistent with the expectation that higher income and education are positively associated with a greater demand for higher quality products.
4.7 Robustness check with a short non-hypothetical experiment
As the choice experiment was hypothetical, we ran a short experiment with real money using a dictator game to evaluate the robustness of the consumers’ estimated WTP values for sustainable labels. In an economic context, this type of game is played usually with real money in the belief that people behave differently and are more sincere if their actions have real monetary consequences (Ben-Ner et al., 2008). Thus, this experiment evaluated participants’ decision to donate any amount of money from an endowment from L. 0 (USD 0.00) to L. 200 (USD 8.30) to one of two recipients: (1) a conventional or (2) sustainable Honduran coffee growers’ association. They might choose to keep the money instead of making a donation. Only the 65 participants recruited in the mini market played the game. Donations to the sustainable Honduran coffee growers’ association were in average L. 75.69 (USD 3.14) and they are significantly larger (P<0.05) than those for the conventional association of 64.92 (USD 2.69). Consequently, this provides evidence that these consumers have a true intention to pay for sustainable coffee in a real context.
By paying a premium, the distribution of value added in the coffee chain could also be improved to the producer’s advantage. The robustness check is giving a different point of view on how sustainability attributes and their exposition in coffee bags are improved, sustainability initiatives could, as reflected on this study, facilitate a higher degree of ‘buyer-drivenness.’
5. Summary and conclusions
This study provides a general view of Honduran consumers’ knowledge and demand for sustainable attributes and labels in coffee. Consumers were exposed to coffee with sustainable labels with real certification schemes, and their familiarity and knowledge, visual attention to, and perceived importance of these labels were studied. The results indicated that Honduran consumers have little knowledge and familiarity with sustainable labels. Sustainable levels were identified as important attributes for coffee selection, but were not as important as intrinsic attributes. Honduran consumers also preferred and were willing to pay more for coffee with sustainable labels. Finally, consideration of consumers’ visual attention to sustainable labels provides insights into factors associated with their preferences. Consumers paid more attention to the Organic USDA label, which was also the label with the highest WTP value.
Although most Honduran coffee is being exported, there is remaining coffee sold in domestic markets and now we can better understand the differentiation characteristics, such +as sustainability attributes, that growers undertake for export markets and how they are valued by domestic consumers.
Overall, the results of our study indicate that there is a domestic market for sustainably produced coffee in Honduras, a developing producing-exporting nation. However, additional efforts are needed to educate local consumers further about the information sustainable labels convey. In addition, the industry needs to be aware that local consumers consider that intrinsic attributes are the most important in their coffee selection; thus, sustainable labels are likely to be more effective with coffee with good intrinsic attributes. At the same time, results from the visual analysis, choice experiments, and survey responses indicate that Honduran consumers also consider price a critical attribute, so pricing decisions must be studied carefully.
More research is needed to evaluate the demand for domestic coffee in general, and coffee with sustainable labels in particular in other regions or countries, given the fast-evolving nature of markets for sustainable products.
Supplementary material
Supplementary material can be found online at https://doi.org/10.6084/m9.figshare.23508216.
Table S1. Results of regression analysis for willingness to pay (WTP) for Organic USDA, Fairtrade, Rain Forest Alliance and 4C, labels with eye-tracking variables included in the study (65 consumers).
Table S2. Results of regression analysis for willingness to pay (WTP) for Organic USDA, Fairtrade, Rain Forest Alliance and 4C, labels with selected variables included in the study.
Acknowledgements
We would like to thank the Master’s program in Sustainable Tropical Agriculture (MATS) of Zamorano for the support with the research materials. In a very special way, we thank all the study participants. The research and development activities on which much of this project work is based were made possible thanks to support from the Nippon Foundation.
Conflict of interest
The authors declare to have no conflicts of interest when writing the manuscript.
References
4C Services GmbH. nd. Certification Scopes. Available at: https://www.4c-services.org/process/certification-scopes
Álvarez, M.A. 2018. Análisis de la cadena valor café en Honduras. Available at: https://www.iisd.org/system/files/publications/trade_state_sustainable_coffee.pdf
Anagnostou, A., P. Ingenbleek and H.C.M. van Trijp. 2015. Sustainability labelling as a challenge to legitimacy: spillover effects of organic fairtrade coffee on consumer perceptions of mainstream products and retailers. Journal of Consumer Marketing 32(6): 422-431. https://doi:10.1108/JCM-11-2014-1213
Andorfer, V.A. and U. Liebe. 2013. Consumer behavior in moral markets. on the relevance of identity, justice beliefs, social norms, status, and trust in ethical consumption. European Sociological Review 29(6): 1251-1265. https://doi:10.1093/esr/jct014
Annunziata, A., A. Mariani and R. Vecchio. 2019. Effectiveness of sustainability labels in guiding food choices: analysis of visibility and understanding among young adults. Sustainable Production and Consumption 17: 108-115. https://doi.org/10.1016/j.spc.2018.09.005
Aprile, M.C. and G. Punzo. 2022. How environmental sustainability labels affect food choices: assessing consumer preferences in Southern Italy. Journal of Cleaner Production 332: 130046. https://doi:10.1016/j.jclepro.2021.130046
Bastounis, A., J. Buckell, J. Hartmann-Boyce, B. Cook, S. King, C. Potter, F. Bianchi, M. Rayner and S.A. Jebb. 2021. The impact of environmental sustainability labels on willingness-to-pay for foods: a systematic review and meta-analysis of discrete choice experiments. Nutrients 13(8): 2677. https://doi:10.3390/nu13082677
Ben-Ner, A., A. Kramer and O. Levy. 2008. Economic and hypothetical dictator game experiments: incentive effects at the individual level. Journal of Socio-Economics 37(5): 1775-1784. https://doi.org/10.1016/j.socec.2007.11.004
Bialkova, S., K.G. Grunert, and H. van Trijp. 2020. From desktop to supermarket shelf: eye-tracking exploration on consumer attention and choice. Food Quality and Preference 81: 103839. https://doi.org/10.1016/j.foodqual.2019.103839
Bulege, W. 2013. Crecimiento demográfico y cambio climático. Apuntes de Ciencia & Sociedad 3(1): 4-5. https://doi:10.18259/acs.2013001
Campbell, D. 2007. Willingness to pay for rural landscape improvements: combining mixed logit and random-effects models. Journal of Agricultural Economics 58(3): 467-483. https://doi:10.1111/j.14779552.2007.00117.x
DeClerck, F.A.J., S.K. Jones, S. Attwood, D. Bossio, E. Girvetz, B. Chaplin-Kramer, E. Enfors, A.K. Fremier, L.J. Gordon, F. Kizito, I. Lopez Noriega, N. Matthews, M. McCartney, M. Meacham, A. Noble, M. Quintero, R. Remans, R. Soppe, L. Willemen, S.L.R. Wood and W. Zhang. 2016. Agricultural ecosystems and their services: the vanguard of sustainability? Current Opinion in Environmental Sustainability 23: 92-99. doi:10.1016/j.cosust.2016.11.016
Fairtrade International. nd. What is Fairtrade? Available at: www.fairtrade.net/about/what-is-fairtrade.
Forum café. 2019. El café de Honduras. Reporte No. 79. Available at: https://orgprints.org/13292/1/State_of_Sustainable_Coffee-complete.pdf.
Garcia Chaclan, M. de J. 2020. Mexican consumers’ perceptions and preferences for U.S. and Texas beef. Master of Science, Texas Tech University. Available at: https://ttu-ir.tdl.org/bitstream/handle/2346/87636/GARCIA-THESIS-2020.pdf?sequence=1
Giovanucci, D. and F.J. Koekoek. 2003. The state of sustainable coffee: a study of twelve major markets. Colombia. Available at: https://orgprints.org/13292/1/State_of_Sustainable_Coffee-complete.pdf.
Grunert, K.G. 2011. Sustainability in the food sector: a consumer behaviour perspective. International Journal on Food System 2(3): 207-218. https://doi:10.18461/IJFSD.V2I3.232
Grunert, K.G., S. Hieke and J. Wills. 2014. Sustainability labels on food products: consumer motivation, understanding and use. Food Policy 44: 177-189. https://doi:10.1016/j.foodpol.2013.12.001
Hess, S. 2007. Posterior analysis of random taste coefficients in air travel behaviour modelling. Journal of Air Transport Management 13(4): 203-212. https://doi:10.1016/j.jairtraman.2007.03.004
Hole, A. 2013. Mixed logit modelling in stata – an overview. University of Sheffield, Sheffield, UK. Available at: https://www.stata.com/meeting/uk13/abstracts/materials/uk13_hole.pdf.
Holmes, T.P., and W.L. Adamowicz. 2003. Attribute-based methods. In: P.A. Champ, K.J. Boyle and T.C. Brown (eds.) A primer on nonmarket valuation. Kluwer Academic Publishers, Dordrecht, the Netherlands, pp. 171-220.
IHCAFE. 2013. Informe Estadístico Anual 2012-2013.
IHCAFE. 2016. Informe Estadístico Anual 2015-2016.
IHCAFE. 2019. Memoria Cosecha.
iMotions. nd. iMotions biosensor software platform – unpack human behavior. Available at: https://imotions.com/platform.
iMotions. 2018. Eye tracking: the complete pocket guide. Available at: https://imotions.com/blog/eye-tracking.
INE. 2019. Boletin Estadística Sobre El Café 2015-2019.
INE. 2021. LXXII Encuesta permanente de hogares de propósitos múltiples. Available at: https://www.ine.gob.hn/V3/imag-doc/2021/11/INE-EPHPM-2021.pdf.
International Coffee Organization. nd. Sustainable coffee. Available at: www.ico.org/mission07_e.asp?section=About_Us
International Labor Organization. 2020. Improving occupational safety and health in the global coffee value chain in Honduras: drivers and constraints. Available at: https://tinyurl.com/35k6d7f4.
James, H.S. 2006. Sustainable agriculture and free market economics: finding common ground in Adam Smith. Agriculture and Human Values 23(4): 427-438. https://doi:10.1007/s10460-006-9020-6
Liu, C., C. Chen and H. Chen. 2019. Measuring consumer preferences and willingness to pay for coffee certification labels in Taiwan. Sustainability 11(5): 1297. https://doi:10.3390/su11051297
McFadden, D. 1974. Conditional logit analysis of qualitative choice behavior. In: P. Zarembka (ed.) Frontiers in econometrics. Academic Press, New York, NY, USA, pp. 105-142.
Mennecke, B.E., A.M. Townsend, D.J. Hayes and L.M. Lonergan. 2007. A study of the factors that influence consumer attitudes toward beef products using the conjoint market analysis tool. Journal of Animal Science 85(10): 2639-2659. https://doi:10.2527/jas.2006-495
Miner, K.L. 2003. The sustainable consumption challenge: social marketing strategies targeting fair trade coffee. Thesis. University of British Columbia, Vancouver, Canada.
Ministerio de Asuntos Exteriores, Unión Europea and Cooperación. 2022. Honduras. Oficina de información diplomática. Available at: https://www.exteriores.gob.es/Documents/FichasPais/HONDURAS_FICHA%20PAIS.pdf.
OCDE. 2002. ¿Hacia Un Consumo Sostenible En Los Hogares? Available at: http://www.oecd.org/greengrowth/consumption-innovation/1938992.pdf.
Palma, M.A., D.V. Vedenov and D. Bessler. 2020. The order of variables, simulation noise, and accuracy of mixed logit estimates. Empirical Economics 58(5): 2049-2083. https://doi.org/10.1007/s00181-018-1609-2
Pierrot, J.D. and A. Kasterine. 2010. Trends in the trade of certified coffees. MPRA Paper No. 27551. Available at: https://mpra.ub.uni-muenchen.de/27551/.
Pieters, R. and L. Warlop. 1999. Visual attention during brand choice: the impact of time pressure and task motivation. International Journal of Research in Marketing 16(1): 1-16. https://doi:10.1016/S01678116(98)00022-6
Rain Forest Alliance. nd. About us. Available at: https://www.rainforest-alliance.org/about.
Revelt, D. and K. Train. 1998. Mixed logit with repeated choices: households’ choices of appliance efficiency level. Review of Economics and Statistics 80(4): 647-657. https://doi:10.1162/003465398557735
Rodríguez Lacherre, M. 2013. Sostenible o Sustentable. Sagasteguiana 1(2): 91-92.
Samoggia, A. and B. Riedel. 2018. Coffee consumption and purchasing behavior review: insights for further research. Appetite 129: 70-81. https://doi:10.1016/j.appet.2018.07.002
Sánchez-Bravo, P., E.V. Chambers, L. Noguera-Artiaga, E. Sendra, E. Chambers and A.A. Carbonell-Barrachina. 2021. Consumer understanding of sustainability concept in agricultural products. Food Quality and Preference 89: 104136. https://doi:10.1016/j.foodqual.2020.104136
Scarpa, R., M. Thiene and K. Train. 2008. Utility in willingness to pay space: a tool to address confounding random scale effects in destination choice to the Alps. American Journal of Agricultural Economics 90(4): 994-1010. https://doi:10.1111/j.1467-8276.2008.01155.x
Shelef, O., J.D. Fernández-Bayo, Y. Sher, V. Ancona, H. Slinn, and Y. Achmon. 2018. Elucidating local food production to identify the principles and challenges of sustainable agriculture. In: C.M. Galanakis (ed.) Sustainable Food Systems from Agriculture to Industry. Elsevier, Amsterdam, the Netherlands, pp. 47-81. https://doi.org/10.1016/B978-0-12-811935-8.00002-0
Specialty Coffee Association. 2016. 2016 SCA quantitative specialty coffee consumer study: Consumer behaviors, motivations, and perceptions. Available at: https://store.sca.coffee/collections/research/products/2016-scaa-quantitative-specialty-coffee-consumer-study-consumer-behaviors-motivationsand-perceptions?variant=34949715334
The Nielsen Company. 2017. Pockets of growth: Latin America, 2017. Available at: www.nielsen.com/wpcontent/uploads/sites/3/2019/04/latam-pockets-of-growth-report-june-2017.pdf.
Train, K. and M. Weeks. 2005. Discrete choice models in preference space and willingness-to-pay space. In: R. Scarpa and A. Alberini (eds.) Applications of simulation methods in Environmental and Resource Economics. Springer, Berlin, Germany, pp. 1-16.
USDA. nd. Organic integrity database. Available at: https://organic.ams.usda.gov/integrity.
USDA. 2017. Organic 101: Understanding the ‘made with organic’ label. Available at: www.usda.gov/media/blog/2014/05/16/organic-101-understanding-made-organic-label
USDA. 2022. Coffee annual: Honduras. GAIN. Available at: https://apps.fas.usda.gov/newgainapi/api/Report/DownloadReportByFileName?fileName=Coffee%20Annual_Tegucigalpa_Honduras_HO2022-0005.pdf.
United Nations Development Programme. nd. Objective 12: Production and responsible consumption. Available at: https://www.undp.org/content/undp/es/home/sustainable-development-goals/goal-12responsible-consumption-and-production.html.
United Nations Environment Programme. 2015. Consumo y producción sostenibles y los Objetivos de Desarrollo Sostenible. Programa de las Naciones Unidas para el Medio Ambiente. Available at: www.unep.org.
Van Loo, E., V. Caputo, R.M. Nayga, J.F. Meullenet, P.G. Crandall and S.C. Ricke. 2010. Effect of organic poultry purchase frequency on consumer attitudes toward organic poultry eat. Journal of Food Science 75(7): S384-S397. https://doi:10.1111/j.1750-3841.2010.01775.x
Van Loo, E.J., V. Caputo, R.M. Nayga Jr, H.S. Seo, B. Zhang and W. Verbeke. 2015. Sustainability labels on coffee: consumer preferences, willingness-to-pay and visual attention to attributes. Ecological Economics 118: 215-225. https://doi:10.1016/j.ecolecon.2015.07.011
Vanhonacker, F., E.J. van Loo, X. Gellynck and W. Verbeke. 2013. Flemish consumer attitudes towards more sustainable food choices. Appetite 62: 7-16. https://doi.org/10.1016/j.appet.2012.11.003
Veenarat U., L. Pai-Po and R. Chung. 2021. Willingness to pay for sustainable coffee: a case of Thai consumers. SAGE Open 11(4): 21582440211052956. https://doi.org/10.1177/21582440211052956
Velten, S., J. Leventon, N. Jager, and J. Newig. 2015. What is sustainable agriculture? A systematic review. Sustainability 7(6): 7833-7865. https://doi:10.3390/su7067833
The World Bank. 2022. Honduras: panorama general. Available at: https://www.bancomundial.org/es/country/honduras/overview#1
Yang, S.H., P.W. Qing and Y. Liu. 2014. Product information and Chinese consumers’ willingness-to-pay for fair trade coffee. China Agricultural Economic Review 6(2): 278-294. https://doi:10.1108/CAER-01-2013-0017
Corresponding author
