Abstract
This study evaluates the competitiveness of 12 leading coffee-producing nations – Brazil, Colombia, Ethiopia, Guatemala, Honduras, India, Indonesia, Mexico, Nicaragua, Peru, Uganda, and Vietnam – by analyzing their comparative advantages across five product categories: (1) green coffee (excluding roasted/decaffeinated), (2) decaffeinated coffee (excluding roasted), (3) roasted coffee (excluding decaffeinated), (4) roasted and decaffeinated coffee, and (5) coffee by-products (husks, skins, substitutes). Using trade data from 2001 to 2021 (UN Comtrade, HS codes 090111–090122), we employ three quantitative indices: revealed comparative advantage (RCA), relative import advantage (RMA), and relative trade advantage (RTA). The RCA identifies export competitiveness, the RMA assesses import reliance, and the RTA combines both to measure net trade performance. Thresholds of >1 (RCA/RMA) and >0 (RTA) indicate competitiveness. The findings reveal that most countries (10 of 12) exhibit strong competitiveness in green coffee exports (HS 090111), except India and Nicaragua. Mexico and Vietnam show emerging advantages in decaffeinated coffee (HS 090112), but no nation competes in roasted coffee or by-products. This pattern reflects structural constraints in downstream processing, validated through robustness checks comparing RTA trends across sub-periods. The study underscores the need for policies to upgrade value chains, emphasizing industrialization, technological adoption, and diversification into higher-value coffee products to enhance export revenues and sustainable development.
1 Introduction
Coffee is among the most significant tropical products, with economic impacts at every stage of the worldwide supply chain that connects producers to customers. The coffee business benefits the economies of both exporting and importing nations. Coffee cultivation offers a living for approximately 25 million workers and their dependents at the origin [1]. Parties throughout the global value chain (GVC), whether merchants, roasters, retailers, their staff, or other stakeholders, gain substantial economic advantages, with opportunities for coffee producers to connect to GVCs and approach long-established and new potential coffee-consuming marketplaces to boost their profitability [1].
GVCs significantly impact international trade, output, and employment, shaping how enterprises from emerging nations integrate into the global economy, but achieving domestic development, infrastructure improvement, and job creation requires effective competition within these chains [2]. The global coffee industry integrates 25 million smallholder farmers concentrated in the “coffee belt” into GVCs, offering potential for income enhancement and poverty reduction. However, the coffee value chain is characterized by buyer market power, creating an imbalance in producer–purchaser negotiations [3]. The key players and processes within this chain, from production to consumption, are illustrated in Figure 1.
The coffee value chain encompasses several key stages, beginning with Farming and Cultivation, primarily on smallholder farms (about 80% of global coffee) in tropical regions [6,7]. This delicate process, influenced by altitude, rainfall, and temperature, focuses on optimizing the cultivation of coffee cherries from two main species: Arabica and Robusta [1]. Logistical challenges at this stage involve ensuring timely access to inputs like seeds and fertilizers, though this stage represents a lower-value segment of the chain [6]. Harvesting and processing follow involving the extraction of beans and processing via wet or dry methods, each imparting unique flavor profiles [5]. Efficient transportation and storage are crucial to prevent spoilage and maintain quality [6], adding moderate value. Milling transforms parchment coffee into green coffee beans for export, involving hulling, grading, and sorting to ensure quality [7]. Proper storage is essential at this stage, adding moderate value through enhanced marketability [3]. Exporting involves logistics, documentation, and managing the supply chain to international markets [6], adding moderate value as prices depend on global market conditions [2]. Roasting transforms green beans into roasted coffee with distinct flavors [5], requiring careful inventory management and packaging to maintain freshness [6], adding significant value. Branding and Packaging in the coffee value chain critically shape consumer perception and market differentiation through strategic design, emotional engagement, and logistical efficiency [6], enhancing perceived value and improving competitiveness [7]. Finally, distribution and retail bring the product to consumers through various channels requiring effective inventory management and logistics [5], adding substantial value through enhanced consumer experience and brand perception.
Traditional trade theories explain trade specialization based on each economy’s specific characteristics, resulting in relative cost disparities, known as comparative advantage. The concept of “comparative advantage” in Ricardian theory refers to a country’s tendency to export goods it can produce more efficiently, at a lower opportunity cost than other countries. Through trade, a country can import goods it lacks a comparative advantage in producing, acquiring them at a lower opportunity cost than domestic production would require [8]. The Heckscher–Ohlin model attributes specialization to differences in factor endowments (e.g., labor, capital), with countries exporting goods that intensively use their abundant resources [9]. While newer theories since the 1980s incorporate economies of scale, comparative advantage remains central to explaining trade flows, as economies prioritize producing and exporting goods in which they are relatively most efficient, based on cost advantages [10].
The revealed comparative advantage (RCA) indicator displays a clear view of trade specialization. The notion of RCA, developed by Balassa, currently recognized as the “Balassa index” [11], avoids the challenging and time-consuming computation of production costs. According to this theory, trading structure indicates cost and non-price element disparities, which reveal the economies’ comparative advantage. The Balassa index is the ratio of a country’s proportion of global exports in a particular sector divided by its proportion of global trade overall [8]. If the ratio is smaller than one, it is assumed that the economy has a comparative disadvantage in the specified industry, while a ratio above one indicates that the country has a RCA in that industry [8].
The Balassa index is one of the most extensively utilized trade performance indicators due to its simplicity of computation in empirical studies. Initially, Balassa restricted his research to manufacturers because many primary goods were subject to quotas and subsidies [9]. Nonetheless, the measure has been implemented in other sectors, such as agriculture [12] and services [13,14]. Thus, RCA and its variations are an excellent approach to measure comparative advantage, which can show specialization tendencies [11]. Yeats [15] investigated irregular trade patterns caused by trade restrictions, applying the relative trade advantage (RTA) index, a modification of the RCA index, to assess regional export orientation and expenses in trade flows for the Mercosur group of nations. Fertö and Hubbard [16] adopted four indicators of RCA to examine the competitive strength of Hungarian agriculture compared to the EU, applying the original Balassa index, RTA, relative export advantage, and relative competitiveness. Pilinkiene [17] attempted to assess global competitiveness in the Baltic States of Lithuania, Latvia, and Estonia utilizing three indicators of RCA, using import and export statistics for key industry sectors from 1998 to 2012. It was found that the Baltic States’ competitiveness may suffer due to globalization impacts and increased competition from other growing economies, and depend on their capacity to undertake structural reforms, strengthen economic and investment standards, and enhance labor market effectiveness and flexibility.
Employing four indicators of RCA from 2000 to 2015, Kostoska and Hristoski [9] investigated Macedonia’s industry specialization and competitiveness compared to the EU members. Their results demonstrated that Macedonia’s comparative advantage pattern had shifted slightly during the reviewed period, with a decline, as reflected by the Balassa index. Maqbool et al. [18] evaluated Pakistan’s international competitiveness in the cotton industry by a collection of RCA ratios, including RCA, Vollrath index, revealed symmetric comparative advantage (RSCA) index, relative import advantage (RMA) index, Net export index (NEI), and relative trade advantage (RTA) index, using the data from the International Trade Center’s during 2003 to 2017. The study’s findings indicated that, for the cotton industry, Pakistan had a comparative advantage in exports while a comparative disadvantage in imports, with a net competitive advantage in this business. Ali et al. [19] demonstrated the long-term RCA of Bangladesh in the textiles sector over 38 years (1980–2017), against the five largest rivals in the North American region. The study by Halife [11] investigated the competitiveness of Turkish textile manufacturing in the international market, by RCA, comparing India, China, Hong Kong, Pakistan, South Korea, Vietnam, Turkey, and the United States during the 20 years from 2010 to 2019. The results of the RCA study conclude that export volume may not be an effective indicator for assessing the competitiveness of a particular industry.
Yet, the competitiveness of coffee-producing nations remains uneven, shaped by disparities in productivity, processing capabilities, and value-chain integration. While traditional trade theories attribute specialization to comparative advantage, empirical studies often treat coffee as a homogeneous product, obscuring critical variations in competitiveness across categories [9,10]. The RCA index, a cornerstone of trade competitiveness analysis [20], has rarely been applied to disaggregated coffee product categories, despite their distinct market dynamics. While the method has been applied to other agricultural sectors, no comprehensive RCA analysis exists for the world’s top 12 coffee exporters, who dominate global trade. Existing studies applying the RCA framework have predominantly focused on non-coffee sectors such as textiles [11], cotton [18], and regional trade blocs [17], leaving coffee-specific competitiveness analyses underexplored. While classical trade theories (Ricardo, Heckscher–Ohlin) and RCA methodologies [20] are well-established, no study has systematically applied these to evaluate competitiveness across distinct coffee product categories. This homogenization hinders insights into how countries specialize in high-value niches, despite evidence that competitiveness varies significantly across these categories [21]. The oversight limits policymakers’ ability to design targeted strategies for value-added niches. Additionally, no study comprehensively evaluates the 12 largest coffee exporters. This omission prevents cross-country benchmarking and obscures strategic lessons for producers aiming to optimize export portfolios.
Furthermore, existing research also fails to reconcile RCA findings with classical theories, limiting policymakers’ ability to design strategies that align productivity (Ricardo) or factor endowments (Heckscher–Ohlin) with market realities. Therefore, this study will try to address these gaps by conducting the first RCA analysis of coffee across distinct product categories, benchmarking the 12 largest exporters, and integrating findings with classical trade theories to deliver actionable policy recommendations for enhancing value-chain competitiveness. This research aims to assess the competitiveness of the world’s 12 top coffee exporting countries, Brazil, Colombia, Ethiopia, Guatemala, Honduras, India, Indonesia, Mexico, Nicaragua, Peru, Uganda, and Vietnam, using the RCA technique [22,23]. The authors address the question: how is the competitiveness of the world’s major coffee producers appraised via the lens of RCA, using the symmetric RCA index to standardize comparative advantage measurements?
This article has value in the fields of industry and economic growth as it reveals a clearer picture of coffee-producing countries’ competitiveness. Furthermore, the article makes a contribution by proving the coffee industry’s level of global competitiveness, which may assist governments and other market players in releasing new policies for improving their country’s coffee industry. The research also compares three trade competitiveness indices in its analysis: RCA index, relative import advantage (RMA) index, and RTA index to see whether they lead to the same conclusion or show a different picture about competitiveness. The RCA index measures export specialization, RMA specifically accounts for import penetration effects, while RTA incorporates both export and import components. This tripartite methodological approach allows a comprehensive assessment of competitiveness patterns.
2 Materials and methods
In this article, we used secondary data to identify the top 12 major coffee-producing countries, covering 88.36% of global output and 83.1% of total global coffee green bean exports in 2020 [24]. They are Brazil, Colombia, Ethiopia, Guatemala, Honduras, India, Indonesia, Mexico, Nicaragua, Peru, Uganda, and Vietnam. Five commodities were compared over the period from 2001 to 2021. The first one is HS 090111, coffee, excluding roasted and decaffeinated. This refers to raw coffee beans, excluding roasted or decaffeinated products. This is the primary form traded globally before industrial processing. The second one is HS 090112, decaffeinated coffee (excluding roasted), referring to unroasted beans that have undergone caffeine removal, but not roasting. The third commodity is HS 090121 as roasted coffee (excluding decaffeinated), referring to beans roasted to develop flavor, excluding decaffeinated varieties. The fourth commodity is HS 090122 as roasted, decaffeinated coffee, that is, beans that are both roasted and caffeine-free. Finally, the fifth commodity is HS 090190, referring to coffee husks and skins and coffee substitutes containing coffee in any production, and this includes husks, skins, and alternative products containing coffee (e.g., coffee blends with substitutes like chicory). These data are retrieved from the International Trade Center Database from 2001 to 2021 [25].
Three types of comparative advantage indices are applied, listed below.
The RCA index calculates the comparative advantage based on export figures, as
where 0 < RCA ij < ∞, X ij represents country i’s export of product j; X it represents country i’s total export (measured either in value or in quantity); similarly, X wj represents the export share of product j in the world; and X wt represents the total export of the world, with the same measurement units. RCA > 1 indicates country i has a comparative advantage in the production of product j. The difference or change in RCA provides a useful measure to determine the competitive position of any nation or industry. A higher index value indicates a stronger advantage, and vice versa.
The RCA index is adopted due to its empirical robustness and reliability in trade analysis, offering a straightforward calculation that directly reflects a country’s export performance relative to global trade patterns. Although RCA has been criticized for some weaknesses, such as the asymmetric distribution that skews RCA values toward positive outcomes, the sensitivity of the index to aggregate trade imbalances which can distort interpretations of competitiveness, and its inability to account for import competition, its extensive validation and application in empirical research have established it as a reliable framework for analyzing trade patterns [26].
In contemporary international trade, a country may quite often export and import significant amounts of the same commodities at the same time, and it is not unusual that the imported product will be further exported. This phenomenon cannot be captured by RCA clearly. The introduction of RMA, therefore, provides a way of evaluating a country’s import performance, and RTA, as the difference between these two index values allows better insight into a country’s two-way trade competitiveness [28].
The RMA index uses a similar formula to the RCA index with corresponding import M values:
where M ij represents country i’s import of product j; M it represents country i’s total import; M wj represents the import of product j of the world; and M wt represents the total import of the world. The interpretation of this index is reversed from that of the RCA. RMA < 1 indicates that country i has a comparative advantage in the production of j; the less the index, the stronger the advantage, and vice versa.
The RTA index is computed by deducting the RMA index from the revealed comparative (RCA) advantage index as
The value RTA > 0 indicates a revealed comparative trade advantage, and vice versa. It is worth noting that RTA can have a positive value not only with RCA > 1 and RMA < 1, but with RCA < 1 if RMA < RCA < 1, suggesting an export-based disadvantage together with an import-based advantage. Similarly, the opposite case of RCA > RMA > 1 also reflects RTA, in the presence of an export-based advantage and an import-based disadvantage, too. Therefore, RTA can reveal more complex patterns of trade competitiveness than RCA and RMA separately.
To standardize the data at the same scale, we use the symmetric formula for RCA ij and RMA ij [27,28,29,30]:
By making the value symmetric, the score will be between −1 and +1. The interpretation is analogous to RCA ij and RMA ij , i.e., a positive RSCA indicates a comparative advantage, while a negative relative symmetric import advantage (RSMA) signals a comparative disadvantage.
The following analysis will employ RSCA, RSMA, and RTA.
3 Results
Among various agricultural products, coffee stands out as one of the most globally consumed commodities [31], primarily produced by developing nations located along the equatorial belt in tropical climates, including the 12 countries discussed in this article. Coffee beans are typically commercialized in their green or dehydrated form but can also be sold as processed products [32]. The coffee processing industry generates a significant quantity of byproducts with the potential for utilization as functional ingredients within the food industry [33].
The analysis of RSCA shows (see Figure 2) that all coffee-producing countries have comparative advantages (RSCA > 0 values) for commodity HS code 090111 as coffee (excluding roasted and decaffeinated), except India and Nicaragua. Mexico is the only country with a comparative advantage in commodity HS 090112 – decaffeinated coffee (excluding roasted).
![Figure 2
The RSCA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_002.jpg)
The RSCA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].
There are 3 countries that have comparative advantages for commodity HS 090190 – coffee husks and skins and coffee substitutes containing coffee in any production in at least 3 consecutive years: Indonesia (2001–2004), Ethiopia (2003–2006) and Uganda (2007–2011), but the trends are not pertaining. No countries have a significant comparative advantage for commodity HS 090121 – roasted coffee (excluding decaffeinated) nor for HS 090122 – roasted, decaffeinated coffee.
Although Brazil dominates the global green coffee market in terms of production volume; yet, Germany – a non-coffee-producing country – leads the premium roasted coffee segment [31,33]. This contrast highlights Brazil’s persistent challenge in capturing higher value within the coffee supply chain. While the country excels as a commodity producer, its limited presence in roasted markets underscores the need for targeted investments in processing infrastructure, technology, and branding to transition into higher-value segments [34].
Although the 12 major coffee-producing countries are globally recognized for their significant contributions to coffee production, they face several challenges that prevent them from exporting processed coffee, such as ground or roasted coffee. These challenges are multifaceted, involving both internal and external factors. The reasons range from market structure and export dynamics to infrastructure and logistical challenges, as well as social-economic factors, and systemic issues such as policy and institutional support. Multinational corporations control the processing and marketing of coffee in consuming countries, prioritizing the import of raw beans, leaving local producers at the lower end of the value chain with limited opportunities for value addition [35,36,37].
Ethiopia and Uganda predominantly export green coffee beans, with minimal processing conducted domestically [37]. Indonesia exhibits a growing interest in specialty coffee; however, the majority of its coffee exports still consist of unprocessed beans [38]. Vietnam, the world’s largest producer of robusta coffee, also prioritizes green bean exports, with limited domestic processing infrastructure [39]. Brazil, the largest coffee producer globally, primarily exports green coffee, with only a small percentage of its coffee undergoing domestic processing [40]. Colombia and Peru have historically focused on raw bean exports [35], and Guatemala and Honduras also face challenges as their coffee sectors are increasingly controlled by large exporters who prioritize raw bean exports over processed coffee products [7].
The underlying competitive disadvantage faced by most countries in Latin America is exacerbated by insufficient financial resources and limited technological expertise to invest in advanced processing facilities [40]. In contrast, Brazil and Vietnam have invested heavily in processing infrastructure and technological advancements, allowing them to gain a competitive edge in the global coffee market [35]. The persistence of raw coffee bean exports perpetuates unequal economic gains along the value chain, benefiting consuming countries.
Inadequate infrastructure represents a critical barrier, poor transportation networks, and limited access to processing facilities significantly hinder smallholder farmers’ ability to add value to their coffee at the local level [40,41,42,43]. For instance, while Colombia is renowned for its strong coffee brand identity, it lacks the advanced processing infrastructure of countries like Italy and Switzerland, which enables them to add substantial value through roasting and blending before re-exporting [34,38]. The high costs of transporting coffee from rural production areas to processing facilities and export ports reduce the profitability of processed coffee exports. Logistical inefficiencies in Nicaragua, Uganda, and Vietnam, like poor transportation facilities, also hinder the movement of coffee from rural areas to processing centers, leading to increased costs and reduced global competitiveness [39,43,44,45]. These challenges are particularly pronounced in rural areas, where many smallholder farmers operate and often lack access to centralized processing facilities. This situation is further compounded by the geographical diversity of coffee-growing regions, which increases logistical complexity and limits scalability [41].
The RSMA analysis (Figure 3) reveals that nearly all coffee-producing countries hold a comparative advantage (i.e., RSMA < 1) in the commodity classified under HS code 090111 – coffee (excluding roasted and decaffeinated), with the exceptions of Nicaragua and Colombia. Uganda exhibits a declining trend in competitive advantage. Brazil has shown a lack of comparative advantage in recent years for commodity HS 090112 – decaffeinated coffee (excluding roasted), a trend that is similarly observed for Uganda and Colombia. In contrast, Guatemala, Honduras, India, Indonesia, and Nicaragua demonstrate a comparative advantage for this commodity. There are four countries that maintain a comparative advantage in commodity HS 090190 – coffee husks and skins, and coffee substitutes containing coffee in any form: Brazil, Colombia, Mexico, and Peru. India, Indonesia, and Vietnam demonstrate an upward trend in competitive advantage in this category. Furthermore, India, Ethiopia, Guatemala, Honduras, Indonesia, and Peru have a substantial comparative advantage for commodity HS 090121 – roasted coffee (excluding decaffeinated). Colombia’s comparative advantage trend in this commodity is increasing, while Brazil’s trend is moving in the opposite direction. Only three countries show a comparative advantage for HS 090122 – roasted, decaffeinated coffee: Colombia, India, and Vietnam.
![Figure 3
The RSMA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_003.jpg)
The RSMA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].
A significant driver behind coffee imports in major coffee-producing nations is the rapid growth in domestic coffee consumption, which often exceeds the capacity of local production. For instance, Brazil, while being one of the world’s largest coffee exporters, is also the second-largest consumer of coffee globally [42]. The increasing demand for diverse flavors and high-quality coffee has necessitated imports to meet evolving consumer preferences that may not be fully satisfied by domestic production alone [46,47,48,49,50]. The same is true for Colombia [51] and Peru [52]. In India, Indonesia, and Vietnam, the evolution of coffee culture has resulted in a growing demand for specialty coffees and diverse blends that cannot be entirely satisfied by domestic production [53,54].
Ethiopia, with its rich coffee culture and an increasing domestic consumption, is facing the rising demand for specialty coffees and unique blends, necessitating imports of high-quality coffee from abroad. Uganda, Guatemala, Honduras, and Nicaragua are experiencing similar trends, too [55,56,57]. Similarly, Mexico, where coffee is a staple beverage, has turned to imports to meet demand for organic and specialty varieties, which are not always readily available through domestic production [57].
Economic considerations serve as a significant driver of coffee imports. The global coffee market is inherently unstable, characterized by frequent price fluctuations and supply chain uncertainties, which encourage economic actors to prioritize efficiency and stability through imports [58,59].
Brazil exemplifies the dual role of a major coffee exporter and importer, having developed a robust coffee trade infrastructure that supports both activities. This duality allows Brazil to maintain market stability and competitiveness in addressing domestic consumption needs despite being a leading producer [35,46,60].
Trade agreements and bilateral partnerships also play a pivotal role in facilitating access to a wider range of coffee derivatives. These agreements enable countries to acquire products that may not be economically feasible or viable to produce locally, such as specialty varieties or derivatives requiring advanced processing techniques, paying attention to specific issues like genetically modified organisms (GMOs) [7,60,61,62]. Together, these economic factors underscore the strategic importance of coffee imports in stabilizing supply chains and meeting evolving consumer preferences. Based on Figure 4, it can be observed that certain countries, such as Brazil, Ethiopia, Guatemala, Honduras, and Peru, continue to demonstrate a comparative advantage in trading the HS 090111 coffee commodity. Conversely, Nicaragua no longer holds a comparative advantage in international trade for this commodity. In contrast, for the HS 090112 commodity, Mexico maintains a comparative advantage, while Vietnam exhibits a positive trend, signaling an increasing comparative advantage. However, for the remaining three commodities – HS 090121, HS 090133, and HS 090190 – none of the countries analyzed display a significant comparative advantage.
![Figure 4
The RTA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_004.jpg)
The RTA index in the 12 countries in 2001–2021. Source: Authors’ computation based on ITC [25].
The analysis showed that the strongest comparative advantage exists in green coffee bean exports, which are based on good production facilities. Therefore, the study investigates the correlation between RSCA and key production metrics. Correlation was computed between RSCA and coffee production, and between RSCA and harvested area by country. High positive correlation coefficients suggest that trade advantages are underpinned by production capacity, or the allocation of large land resources to coffee production. This correlation analysis enables a deeper understanding of how comparative advantage in the coffee sector is shaped not only by trade performance but also by agricultural productivity and land-use efficiency. Table 1 shows consistently robust positive correlations between the revealed symmetric comparative advantage (RSCA) index and coffee production levels for the countries with high RSCA: Brazil, Columbia, Ethiopia, Guatemala, Honduras, and Uganda, and to a lesser extent, Indonesia and Nicaragua. Countries with higher RSCA values in coffee exports typically exhibit rather high production volumes, underscoring their ability to effectively capitalize on their comparative advantage [28]. This relationship is driven by optimal climatic conditions, advanced agricultural practices, and strategic investments in coffee cultivation technologies, bolstering production capacity, enhancing export competitiveness, and reinforcing the global position of these countries in the coffee trade. RSCA, however, does not correlate strongly with production in India, Vietnam, Peru, and Mexico; in these countries, good yields do not readily lead to better export positions.
Correlation between RSCA and coffee production and harvested area by country
No | Countries | RSCA vs production | RSCA vs harvested area |
---|---|---|---|
1 | Brazil | 0.5356 | −0.6400 |
2 | Colombia | 0.6936 | 0.4711 |
3 | Ethiopia | 0.3298 | 0.4023 |
4 | Guatemala | 0.2861 | −0.6817 |
5 | Honduras | 0.5611 | −0.4121 |
6 | India | 0.0961 | −0.4609 |
7 | Indonesia | 0.5977 | −0.6881 |
8 | Mexico | −0.6750 | −0.4241 |
9 | Nicaragua | 0.5405 | 0.9843 |
10 | Peru | 0.2872 | 0.3680 |
11 | Uganda | 0.9194 | 0.9319 |
12 | Vietnam | 0.2088 | 0.1419 |
Source: Authors’ computation based on ITC [25].
The correlation between RSCA values and the harvested area of coffee is noteworthy. Expanding coffee cultivation areas often enables countries to achieve economies of scale, thereby improving production efficiency and reducing per-unit costs. This operational advantage is reflected in 6 of the 12 countries in elevated RSCA values, signaling enhanced competitiveness in international markets [22]. A negative correlation between the RSCA and the harvested area of coffee can be attributed to a variety of factors, including the quality versus quantity trade-off, the impact of technological inputs, economic pressures, environmental conditions, and strategic market dynamics. These factors highlight the complexity of agricultural production and competitive advantage in the coffee sector, suggesting that a focus on quality and efficient practices can lead to enhanced competitiveness even with a reduced area under cultivation.
The RSCA index emerges as a critical tool for assessing a country’s comparative advantage in coffee production and export. The observed positive correlations between RSCA and both coffee production volumes and harvested areas emphasize the strategic significance of leveraging comparative advantages through investments in sustainable agricultural practices, technological advancements, and land management. This highlights the pivotal role of targeted policy interventions and resource allocation in sustaining competitiveness in the global coffee trade.
Table 2 The overall results of the computations.
Summary of comparative advantages by index and commodity
Commodities | Index | Brazil | Colombia | Ethiopia | Guatemala | Honduras | India | Indonesia | Mexico | Nicaragua | Peru | Uganda | Vietnam |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Green coffee (excl. roasted/decaffeinated) | RSCA | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ||
RSMA | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ↓ | ≡ | |||
RSTA | ≡ | ≡ | ≡ | ≡ | ≡ | ||||||||
Decaffeinated coffee (excl. roasted) | RSCA | ≡ | |||||||||||
RSMA | ↓ | ↓ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | ↓ | ≡ | |
RSTA | ≡ | ↑ | |||||||||||
Roasted coffee (excl. decaffeinated) | RSCA | ||||||||||||
RSMA | ↓ | ↑ | ≡ | ≡ | ≡ | ≡ | ≡ | ≡ | |||||
RSTA | |||||||||||||
Roasted and decaffeinated coffee | RSCA | ||||||||||||
RSMA | ≡ | ≡ | ≡ | ||||||||||
RSTA | |||||||||||||
Coffee by-products (husks, skins, substitutes) | RSCA | ≡ | ≡ | ≡ | |||||||||
RSMA | ≡ | ≡ | ↑ | ↑ | ≡ | ≡ | ↑ | ||||||
RSTA |
Notations: ≡: strong and stable advantage, ↑: increasing advantage; ↓: decreasing advantage.
4 Discussion
In agreement with production statistics presented before, regarding coffee (excluding roasted and decaffeinated), all the 12 countries, except India, had comparative advantage by RSCA, while all, except Nicaragua and Colombia, had comparative advantage by RSMA. According to RTA, Nicaragua is the only country with no comparative advantage. With respect to decaffeinated coffee (excluding roasted) only Mexico had a comparative advantage by RSCA, while Guatemala, Honduras, India, Indonesia, and Nicaragua had a comparative advantage by RSMA. According to RTA, Mexico and Vietnam had definite comparative advantage, the picture is mixed for the rest of the countries.
Regarding the remaining three commodities (i.e., coffee husks and skins and coffee substitutes containing coffee; roasted coffee, excluding decaffeinated; roasted and decaffeinated coffee), none of the countries demonstrated a significant comparative advantage by RSCA, nor by RTA. However, by RSMA, Brazil, Colombia, Mexico, Peru, India, Indonesia, and Vietnam show a stable or increasing comparative advantage in coffee husks and skins and coffee substitutes containing coffee. Regarding roasted coffee (excluding decaffeinated), nearly all countries show stable or increasing comparative advantage, except Brazil and Nicaragua. Finally, regarding roasted, decaffeinated coffee, Colombia, India, and Vietnam show strong comparative advantage.
These results demonstrate that the RSCA, RSMA, and RTA indicators capture different aspects of comparative advantages. These differences may be explained by the production technology, including varieties, farming practices, and financial resources allocated to production and processing, as well as by market structures and government support provided to coffee farmers.
Environmental challenges add significant complexity to coffee production in many producing nations, exacerbating existing vulnerabilities. Climate change, combined with the prevalence of pests and diseases, has profoundly impacted coffee yields and quality, with negative projections for the near future [56,63]. Importing coffee derivatives serves as a buffer against the unpredictability of domestic production shortfalls caused by these environmental factors, mitigating the risks associated with declining yields and preserving market stability for both producers and consumers [64,65].
The analysis of comparative advantage through the relative trade advantage (RTA) framework provides valuable insights into export and import dynamics, serving as a critical tool for shaping trade policy, guiding investment decisions, conducting market analysis, and informing trade negotiations. Policymakers, identifying industries with strong RTAs, can prioritize resource allocation and strategic development, as high RTA indicates growth potential and profitability, attracting both domestic and foreign investments. For countries engaged in trade negotiations, a strong RTA can be leveraged to advocate for more favorable terms of trade, such as reduced tariffs or improved market access, thereby enhancing export capabilities and strengthening their position in global markets.
The analysis of trade competitiveness indices provides a nuanced understanding of the position of coffee-producing nations in global trade dynamics. While RSCA underscores the degree of specialization and comparative advantage in the export of green coffee beans, RSMA highlights the asymmetry in import competitiveness, particularly for processed coffee derivatives, and RTA offers a composite measure of overall trade competitiveness. Together, these indices reveal the structural imbalances between unprocessed and processed coffee products, highlighting key inefficiencies in value chain integration.
Global coffee production has increased by 2.26% from 2001 to 2020, from 7.3 million tons to 11.2 million tons, and the top 12 producers increased their overall share from 76% in 2001 to 85% in 2020 (Figure 5).
![Figure 5
The share of coffee production in (a) 2001 and (b) 2020. Source: Authors’ computation based on FAO [66].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_005.jpg)
The share of coffee production in (a) 2001 and (b) 2020. Source: Authors’ computation based on FAO [66].
Figure 6 illustrates that most coffee-producing countries exhibit a positive harvested area trend during the last 20 years, except for Brazil, Indonesia, and Mexico. As shown in Figure 7, although Brazil experienced a significant harvested area decline due to the replacement of coffee plants with other crops such as sugarcane, oranges, and soybeans [67], it eventually increased production with an average growth rate of 7.25% because of mechanization, improved agronomic techniques, and crop management innovations. Mexico experienced a loss not only in the harvested area but also in total production. Over the past 20 years, Colombia has recorded the highest production growth at 6.68%, followed by Nicaragua and Uganda with growth rates of 6.05% and 5.99%, respectively. It is possible that Colombia may surpass Ethiopia and Indonesia in the future by leveraging its favorable natural conditions while aggressively investing in technological upgrades, fostering sustainable practices, and revitalizing supportive policy environments [68,69]. In contrast, Vietnam achieved a remarkable 14.62% growth in coffee production and cultivated area during the 1990s was driven by two fundamental categories of factors. First, government-led economic interventions provided crucial support through direct farmer subsidies, substantial infrastructure development in coffee regions, enhanced credit accessibility for smallholders, and comprehensive training programs that collectively established a favorable growth ecosystem [70,71]. Second, agricultural advancements and market forces accelerated development, including the strategic transformation of suitable land with ideal climatic conditions for coffee farming, implementation of efficient pest management systems [67], and widespread adoption of sustainable practices that earned premium market prices – creating powerful incentives for farmers to expand their sustainable cultivation areas [72,73,74]. These dual drivers – policy support and agricultural/market innovations – synergistically propelled Vietnam to achieve a dominant competitive position in the global coffee trade.
![Figure 6
The trend of coffee harvested areas in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_006.jpg)
The trend of coffee harvested areas in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].
![Figure 7
The trend of coffee production in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_007.jpg)
The trend of coffee production in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].
Figure 7 highlights the trend of production in the 12 major coffee-producing countries, providing valuable insights into the interplay of land use and productivity in the agricultural sector. This is true for Brazil, where production increased together with a decrease in harvested area. This divergence indicates an increase in average land productivity of 33.4% between 1984 and 2016 [75].
An opposite trend is seen in Mexico, where, despite an increasing harvested area for coffee in the 1990s, coffee production has followed a downward trajectory. The combined effects of pest outbreaks, aging plantations, economic volatility, and diminished government support have led to a persistent decrease in production [76,77]. It can be concluded that the harvested area is not the only determinant of production levels; other factors, including exogenous (climate, diseases, government intervention) and endogenous (technology, farm structure, farmers’ skills and knowledge) influences, may also play significant roles.
Figure 8 illustrates the trends in coffee yields across the 12 major coffee-producing nations. In Brazil, despite a decline in the harvested area, coffee yields have consistently increased, surpassing those of the other eleven coffee-producing countries, which can be attributed to the adoption of new technologies, mechanization, chemical inputs, breeding programs aimed at developing high-yielding cultivars, and supportive governmental policies [75,78].
![Figure 8
The trend of coffee yield in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].](/document/doi/10.1515/opag-2025-0457/asset/graphic/j_opag-2025-0457_fig_008.jpg)
The trend of coffee yield in the top 12 main coffee-producing countries. Source: Authors’ computation based on FAO [66].
Conversely, coffee yields in Indonesia and Mexico rank among the lowest globally, primarily due to a range of challenges, including pests and diseases [79,80], aging plantations, or shifts in temperature and precipitation leading to a reduction in suitable areas for coffee cultivation, and to lower yields [80]. The strategies like replanting old coffee plantations, enhanced pest control, or climate adaptation policies could be a solution to these problems. These tools are applied by the Indonesian government to support smallholder coffee producers, who provide more than 90% of all coffee produced in the country [81], while in Mexico, the utilization of local traditional knowledge of producers also contributes to the solution [80].
5 Conclusion
This study presents a nuanced assessment of the comparative advantage of 12 leading coffee-producing nations, emphasizing a pronounced specialization in unprocessed coffee, particularly green coffee beans, as indicated by the RSCA index. However, this advantage does not extend to processed coffee derivatives – such as roasted and decaffeinated coffee, coffee husks and skins, and coffee substitutes – due to structural constraints. These include inefficiencies in market organization, logistical and infrastructural barriers, socio-economic challenges, and limited institutional and policy support, which collectively impede competitiveness in higher-value segments of the coffee market. Specifically, distinguishing which constraints are more critical in different regions. The structural constraints limiting value-added coffee processing exhibit distinct regional patterns: in Latin America (e.g., Brazil, Colombia), logistical bottlenecks such as port inefficiencies and high domestic transport costs present the primary barrier to value-added processing, compounded by weak vertical integration between farms and processors [46]. African producers (e.g., Ethiopia, Uganda) face fundamentally different challenges, where socio-economic gaps, including limited access to credit and smallholder fragmentation, critically hinder investment in roasting facilities, exacerbated by unstable export policies that amplify market risks [82]. Meanwhile, Asian coffee economies (e.g., Vietnam, Indonesia) struggle most acutely with technology deficits in processing equipment that restrict quality upgrades, alongside market failures in branding and certification schemes that limit premium capture [83,84].
The analysis further highlights a consistent comparative advantage in green coffee beans, supported by the RSMA index, but notes a diminishing advantage in coffee by-products. Domestic coffee consumption, which often outpaces local production, drives significant imports even in coffee-producing nations. Global market volatility, trade dynamics, and cost considerations also influence domestic reliance on imported derivatives. Moreover, the underutilization of coffee by-products presents a missed opportunity to enhance value creation in the global coffee value chain. Coffee pulp is rich in nutrients and can be processed by a simple procedure into delicious and healthy drink products. Cascara is a tea made from dried coffee pulp, and has become a popular new drink in the United States and Indonesia. Coffee husk is rich in proteins, carbohydrates, minerals, soluble fibers, and other valuable chemicals useful for the food industry and pharmacy, while the coffee silver skin contains high amounts of phytochemical and bioactive compounds that contribute to high antioxidant capacity [85]. The possible utilization of these is a promising area to generate additional income for coffee producers.
Notably, the RSCA index correlates positively with coffee production but shows no link with harvested area, signaling the complex interplay of factors that influence production efficiency and competitiveness. This underscores the importance of technological innovation, advanced processing techniques, and integration within the value chain. Nations with sophisticated production systems and strategic alignment with global demand for high-quality, sustainable coffee are better positioned to capture greater value and strengthen their standing in the global coffee market. Optimizing production, yield, and harvested area holds significant potential for enhancing both economic outcomes and bargaining power.
To break the cycle of dependency on low-margin green coffee exports, coffee-producing countries must prioritize three key strategies: first, investing in processing infrastructure by establishing local roasting, grinding, and packaging facilities – as demonstrated by Colombia’s successful “Coffee Parks” program supporting small-scale roasters and exporters – to reduce reliance on foreign processors [86]; second, advancing technology and skills development through adoption of innovative processing techniques (like freeze-drying and precision fermentation) coupled with comprehensive farmer training in quality control [87]; and third, implementing sustainability-linked branding strategies that leverage certifications (such as fair trade and organic) to premiumize processed exports and capture greater value in international markets [88].
The economic gains from value addition must be equitably distributed to ensure inclusive growth, beginning with farmers who can capture greater value through vertical integration – such as Ethiopia’s Sidama Coffee Farmers’ Union [89], which exports roasted coffee directly – though challenges like limited access to capital and market linkages persist. Mid-chain actors, including local processors and exporters, stand to benefit from higher margins but require targeted policy support, such as tax incentives for domestic value addition [90]. Meanwhile, to counterbalance the disproportionate profits captured by multinational roasters (e.g., Nestlé, Starbucks), coffee-producing nations should adopt strategies like domestic branding (e.g., “100% Guatemalan Roasted Coffee” labels) to retain local value and implement trade policy reforms [91], such as export restrictions on raw beans (akin to Indonesia’s palm oil policies), to incentivize domestic processing and rebalance power dynamics in the GVC. To strengthen coffee value chains, country-specific interventions should be implemented across infrastructure, market access, and sustainability. Brazil and Colombia could establish tax-incentivized Coffee Industrial Zones and adopt freeze-drying technology [92] through the Brazilian Agricultural Research Corporation (EMBRAPA) partnerships, while Vietnam and Indonesia should mandate 30% local processing for exports [93] and develop cascara by-product facilities. Ethiopia and Peru would benefit from Origin Protection Funds and the European Union Geographical Indication certifications [94], with Central American nations pursuing tariff reductions under the Central America-Dominican Republic Free Trade Agreement (CAFTA-DR). All producing countries should adopt United Nations Industrial Development Organization (UNIDO)-backed waste-to-energy programs and carbon credit schemes [95], while Africa implements East African Community (EAC) tariffs on green coffee exports and duty-free roasting equipment imports, and India provides subsidies for soluble coffee plants [96].
Implementation should follow a phased approach: short-term (1–3 years) focusing on tax credits and export reforms [97,98] in Vietnam, Indonesia, and Brazil; medium-term (3–5 years) developing cooperatives and renewable energy solutions [99] in Ethiopia, Colombia, and Peru; and long-term (5+ years) establishing regional coffee exchanges and blockchain traceability systems across all producing nations [100]. This comprehensive framework addresses immediate processing bottlenecks while building sustainable, value-added coffee industries tailored to each region’s competitive advantages.
While offering valuable insights, the study is subject to certain limitations. It primarily relies on RSCA and RSMA indices, which may not fully encapsulate the microeconomic and macroeconomic factors affecting competitiveness. Additionally, the roles of technological innovation, environmental sustainability, and socio-political factors remain underexplored. Future research should address these dimensions by examining the influence of innovation, sustainability certifications, and consumer preferences on the comparative advantage of coffee derivatives. Investigating regional trade agreements, global trade policies, and country-specific dynamics would further enhance strategies to overcome existing constraints and improve the positioning of coffee-producing nations within the global coffee value chain.
Acknowledgments
We would like to thank the Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, for funding this research.
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Funding information: This study is supported by the Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal. All authors have read and agreed to the published version of the manuscript. Conceptualization, MIM and DMN; methodology, MIM and ZB; software, MIM; validation, DMN, ZB and NB; formal analysis, MIM, ZB, and NB; investigation, MIM and ZB; resources, MIM, ZB; data curation, MIM, NB; writing – original draft preparation, MIM and DMN; writing – review and editing, MIM, DMN, ZB, and NB; visualization, MIM; supervision, ZB and NB; project administration, ZB and NB; funding acquisition, MIM, DMN, ZB, and NB.
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Conflict of interest: Authors state no conflict of interest.
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Data availability statement: The data were downloaded from the publicly available data of the International Trade Centre, https://www.trademap.org/Index.aspx.
References
[1] Sette J. Coffee development report 2019 - Overview. London: International Coffee Organization; 2019.Suche in Google Scholar
[2] Görlich D, Hanley A, Liu W, Semrau FO, Global C, Chain V. Fostering the development of the coffee global value chain. Kiel: Kiel Institute for the World Economy; 2020.Suche in Google Scholar
[3] Boudreau L, Cajal-grossi J. Global value chains in developing countries: A relational perspective from coffee and garments. J Econ Perspect. 2023;37(3):59–86.10.1257/jep.37.3.59Suche in Google Scholar
[4] Ponte S. The ‘Latte Revolution’? Regulation, markets and consumption in the global coffee chain. World Dev. 2002;30(7):1099–122. 10.1016/S0305-750X(02)00032-3.Suche in Google Scholar
[5] Van Keulen M, Kirchherr J. The implementation of the Circular Economy: Barriers and enablers in the coffee value chain. J Clean Prod. 2021;281:125033. 10.1016/j.jclepro.2020.125033.Suche in Google Scholar
[6] ICO. Beyond coffee: Towards a towards a circular economy. 2024. [Online]. https://www.icocoffee.org/documents/cy2024-25/coffee-development-report-2022-23.pdf.Suche in Google Scholar
[7] Utrilla-Catalan R, Rodríguez-Rivero R, Narvaez V, Díaz-Barcos V, Blanco M, Galeano J. Growing inequality in the coffee global value chain: A complex network assessment. Sustainability. 2022;14(2):1–27. 10.3390/su14020672.Suche in Google Scholar
[8] Bhattacharyya R. Revealed comparative advantage and competitiveness: A case study for india in horticultural products. J Eur Econ. 2012;11(Special Issue):22–37.Suche in Google Scholar
[9] Kostoska O, Hristoski I. Trade dynamics, revealed comparative advantage, and international competitiveness: Evidence from Macedonia. Econ Ann. 2018;LXIII(218):23–59.10.2298/EKA1818023KSuche in Google Scholar
[10] de Benedictis L, Tamberi M. Overall specialization empirics: Techniques and applications. Open Econ Rev. 2004;15:323–46. 10.1023/B:OPEN.0000048522.97418.99.Suche in Google Scholar
[11] Halife H. Competitiveness analysis of textile industry of Turkey: Revealed comparative advantage approach. Int J Glob Bus Compet. 2022;17(s1):25–30. 10.1007/s42943-022-00062-y.Suche in Google Scholar
[12] Bojnec Š. Trade and revealed comparative advantage measures: Regional and Central and East European agricultural trade. East Eur Econ. Mar. 2001;39(1):72–98. 10.1080/00128775.2001.11040990.Suche in Google Scholar
[13] Hisanaga M. Revealed specialization: Evidence on U.S. international services. Int Trade J. Oct. 2008;22(4):378–414. 10.1080/08853900802191413.Suche in Google Scholar
[14] Seyoum B. Revealed comparative advantage and competitiveness in services. J Econ Stud. Oct. 2007;34(5):376–88. 10.1108/01443580710823194.Suche in Google Scholar
[15] Yeats AJ. Does Mercosur’s trade performance raise concerns about the effects of regional trade arrangements? World Bank Econ Rev. Jan. 1998;12(1):1–28. 10.1093/wber/12.1.1.Suche in Google Scholar
[16] Fertö I, Hubbard LJ. Revealed comparative advantage and competitiveness in Hungarian agri–food sectors. World Econ. Feb. 2003;26(2):247–59. 10.1111/1467-9701.00520.Suche in Google Scholar
[17] Pilinkiene V. Evaluation of international competitiveness using the revealed comparative advantage indices: The case of the Baltic States. Mediterr J Soc Sci. 2014;5(13 Spec. Issue):353–9. 10.5901/mjss.2014.v5n13p353.Suche in Google Scholar
[18] Maqbool MS, ur Rehman H, Bashir F, Ahmad R. , Investigating Pakistan’s revealed comparative advantage and competitiveness in cotton sector. Rev Econ Dev Stud. 2019;5(1):125–34. 10.26710/reads.v5i1.570.Suche in Google Scholar
[19] Ali M, Qun W, Hossain ME. Revealed comparative advantage of textile and clothing industry of Bangladesh in the North American market revealed comparative advantage of textile and clothing industry of Bangladesh in the North American market. J Bus Manag Econ Res. 2019;3(1):28–43. 10.29226/TR1001.2018.Suche in Google Scholar
[20] Balassa B. Trade liberalisation and ‘revealed’ comparative advantage. Manch Sch. 1965;33(2):99–123. 10.1111/j.1467-9957.1965.tb00050.x.Suche in Google Scholar
[21] ICO. Annual review, Stronger partnerships: Solutions to overcome regulatory and market challenges. Annual Review 2022/2023. 2023. https://icocoffee.org/annual-review/ (accessed Oct. 28, 2024).Suche in Google Scholar
[22] Maulida S, Fikri AAHS. Determinants of coffee experts of Bandar Lampung Province in the international market for the period 2004-2022. J World Sci. 2023;2(12):1980–99. 10.58344/jws.v2i12.511.Suche in Google Scholar
[23] Apriani D, Marissa F, Subardin M. Revealed comparative advantage in indonesian coffee commodity in the international market. 2020;142(no. Seabc 2019):114–9.10.2991/aebmr.k.200520.020Suche in Google Scholar
[24] Bacsi Z, Fekete-Farkas M, Ma’ruf MI. Coffee yield stability as a factor of food security. Foods. 2022;11(19):3036. 10.3390/foods11193036.Suche in Google Scholar PubMed PubMed Central
[25] ITC. Trade statistics for international business development. 2024. https://www.trademap.org/Index.aspx.Suche in Google Scholar
[26] Brakman S, Garretsen H, Van Marrewijk C, Van Witteloostuijn A. Cross-border merger & acquisition activity and revealed comparative advantage in manufacturing industries. J Econ Manag Strateg. 2013;22(1):28–57. 10.1111/jems.12007.Suche in Google Scholar
[27] İzgi F, Kavacık M. Analyzing global competitiveness of Turkish air conditioning industry. Turk. J Eng. 2024;8(2):209–34. 10.31127/tuje.1372141.Suche in Google Scholar
[28] Pawlak K. Importance and comparative advantages of the EU and US Agri-food Sector in World Trade in 1995-2015. Zesz Nauk SGGW w Warszawie - Probl Rol Światowego. 2017;17(4):236–48. 10.22630/prs.2017.17.4.100.Suche in Google Scholar
[29] Kılıçarslan Z. Comparative analysis of the competitiveness in the steel sector: The case of top 10 steel-producing countries. Erciyes Üniv Iktis ve İdari Bilim Fak Derg. 2021;60:755–73. 10.18070/erciyesiibd.971378.Suche in Google Scholar
[30] Danna-Buitrago JP, Stellian R. A new class of revealed comparative advantage indexes. Open Econ Rev. 2022;33(3):477–503. 10.1007/s11079-021-09636-4.Suche in Google Scholar
[31] da Cruz Correia PF, dos Reis JGM, de Souza AE, Cardoso AP. Brazilian coffee export network: An analysis using SNA. In: Ameri F, Stecke K, von Cieminski G, Kiritsis D, editors. Advances in production management systems. Production management for the factory of the future. APMS 2019. IFIP Advances in Information and Communication Technology, vol. 566. Cham: Springer; 2019.10.1007/978-3-030-30000-5_19Suche in Google Scholar
[32] Nolasco A, Squillante J, Esposito F, Velotto S, Romano R, Aponte M, et al. Coffee Silverskin: Chemical and biological risk assessment and health profile for its potential use in functional foods. Foods. 2022;11(18):2834. 10.3390/foods11182834.Suche in Google Scholar PubMed PubMed Central
[33] Gemechu FG. Embracing nutritional qualities, biological activities and technological properties of coffee byproducts in functional food formulation. Trends Food Sci Technol. 2020;104(June):235–61. 10.1016/j.tifs.2020.08.005.Suche in Google Scholar
[34] Barros F Jr, Ferreira AL, Marcondes RL. Coffee exports and industrialization in Brazil. Appl Econ Lett. 2018;26:1–5. 10.1080/13504851.2018.1489498.Suche in Google Scholar
[35] De Gois TC. Behind a cup of coffee: international market structure and competitiveness. Compet Rev. 2023;33(5):993–1009. 10.1108/CR-10-2021-0141.Suche in Google Scholar
[36] Mitiku F, Nyssen J, Maertens M. Certification of semi-forest coffee as a land-sharing strategy in Ethiopia. Ecol Econ. 2018;145(Sept 2017);194–204. 10.1016/j.ecolecon.2017.09.008.Suche in Google Scholar
[37] Kudama G, Wana H, Dangia M. The adoption of bundled sustainable farm and environmental practices by coffee farmers in Southwest Ethiopia. Sci World J. 2021;2021:9954230. 10.1155/2021/9954230.Suche in Google Scholar PubMed PubMed Central
[38] Apriani D, Bashir A, Marissa F, Mukhlis. The structure-conduct-performance of Indonesian coffee processing industry. KnE Soc Sci. May 2024;9(5):100–20. 10.18502/kss.v9i14.16096.Suche in Google Scholar
[39] Resende IA, Machado MVC, Duarte CR, Barrozo MAS. An experimental analysis of coffee beans dynamics in a rotary drum. Can J Chem Eng. 2017;9999:1–10. 10.1002/cjce.22961.Suche in Google Scholar
[40] Zanetti WAL, Silva Marques M, Amaral AMS, Silva AB, Queiroz Barcelos JP, Putti FF, et al. Analysis of the technological evolution of coffee production in Brazil. J Agric Stud. 2021;9(3):352. 10.5296/jas.v9i3.18971.Suche in Google Scholar
[41] Hartatri DFS. Influence of quality improvement activities and direct selling through mediated partnership model on supply chain, farm-gate price and Indonesian households specialty coffee farmers’ income. Pelita Perkeb (a Coffee Cocoa Res Journal). 2016;32(1):43–51, http://www.ccrjournal.com/index.php/ccrj/article/view/175.10.22302/iccri.jur.pelitaperkebunan.v32i1.175Suche in Google Scholar
[42] Chemura A, Mudereri BT, Yalew AW, Gornott C. Climate change and specialty coffee potential in Ethiopia. Sci Rep. 2021;11(1):1–13. 10.1038/s41598-021-87647-4.Suche in Google Scholar PubMed PubMed Central
[43] Bitzer V, Glasbergen P, Arts B. Exploring the potential of intersectoral partnerships to improve the position of farmers in global agrifood chains: findings from the coffee sector in Peru. Agric Hum Values. 2013;30:5–20. 10.1007/s10460-012-9372-z.Suche in Google Scholar
[44] Higuchi A, Moritaka M, Fukuda S. The impact of socio-economic characteristics on coffee farmers’ marketing channel choice: Evidence from Villa Rica, Peru. Sustain Agric Res. 2012;1(1):13–8. 10.5539/sar.v1n1p13.Suche in Google Scholar
[45] Baffes J. Restructuring Uganda’s coffee industry: Why going back to basics matters. Dev Policy Rev. 2006;24(4):413–36. 10.1111/j.1467-7679.2006.00332.x.Suche in Google Scholar
[46] da Cruz Correia PF, Mendes dos Reis JG, Amorim PS, da Costa JS, da Silva MT. Impacts of Brazilian green coffee production and its logistical corridors on the international coffee market. Logistics. 2024;8(2):1–12. 10.3390/logistics8020039.Suche in Google Scholar
[47] Jarvis LS. How Brazil transferred billions to foreign coffee importers: The international coffee agreement, rent seeking and export tax rebates. Working Paper 03-002, 2003, Department of Agricultural and Resource Economics, University of California, Davis. 10.22004/ag.econ.11967.Suche in Google Scholar
[48] Sousa AG, Da Costa THM. Usual coffee intake in Brazil: Results from the National Dietary Survey 2008-9. Br J Nutr. 2015;113(10):1615–20. 10.1017/S0007114515000835.Suche in Google Scholar PubMed
[49] McCook S. Environmental history of coffee in Latin America. Oxf Res Encycl Lat Am Hist. 2017;(July 2017):1–25. 10.1093/acrefore/9780199366439.013.440.Suche in Google Scholar
[50] de Sousa JR, de Cássia RCAA, Zandonadi RP, Botelho RBA. Breakfast characterization and consumption by low-income Brazilians: Food identity and regional food. Sustainability. 2020;12(12):4998. 10.3390/su12124998.Suche in Google Scholar
[51] Muzykiewicz-Szymańska A, Nowak A, Wira D, Klimowicz A. The effect of brewing process parameters on antioxidant activity and caffeine content in infusions of roasted and unroasted arabica coffee beans originated from different countries. Molecules. 2021;26(12):3681. 10.3390/molecules26123681.Suche in Google Scholar PubMed PubMed Central
[52] Dávila-Guamuro J, Llanos-Pérez J, Cabanillas-Pardo L. Secador solar tipo túnel con microclima auto controlado para Café (Coffea arabica) Honey de alto valor en taza. Rev Agrotecnol Amaz. 2022;2(1):1–10. 10.51252/raa.v2i1.227.Suche in Google Scholar
[53] Upadani IGAW, Saputra KSA, Krisnawan GNA. Marketing strategy of Arabica coffee products on Harapan Maju Group in Kintamani, Bali, Indonesia. SEAS (Sustain Environ Agric Sci). 2023;7(2):99–108. 10.22225/seas.7.2.7735.99-108.Suche in Google Scholar
[54] Yulia M, Analianasari A, Widodo S, Kusumiyati K, Naito H, Suhandy D. The authentication of Gayo Arabica green coffee beans with different cherry processing methods using portable LED-based fluorescence spectroscopy and chemometrics analysis. Foods. 2023;12(23):4302. 10.3390/foods12234302.Suche in Google Scholar PubMed PubMed Central
[55] Duguma H, Chewaka M. Review on coffee (Coffea arabica L.) wet processing more focus in Ethiopia. Acta Sci Agric. 2019;3(11):11–5. 10.31080/asag.2019.03.0676.Suche in Google Scholar
[56] Bilen C, El Chami D, Mereu V, Trabucco A, Marras S, Spano D. A systematic review on the impacts of climate change on coffee agrosystems. Plants. 2023;12(1):1–20. 10.3390/plants12010102.Suche in Google Scholar PubMed PubMed Central
[57] Le Q, Jovanovic G. From crisis to specialty coffee the case of Nicaraguan smallholder cooperatives and jesuit business education for sustainability and justice. J Manag Glob Sustain. 2019;7(1):105–30. 10.13185/jm2019.07105.Suche in Google Scholar
[58] Tampubolon J, Ginting A, Nainggolan HL, Tarigan JR. Indonesian coffee development path: Production and international trade. Asian J Agric Ext Econ Sociol. 2023;41(12):316–28. 10.9734/ajaees/2023/v41i122335.Suche in Google Scholar
[59] Karki SK, Jena PR, Grote U. Fair trade certification and livelihoods: A panel data analysis of coffee-growing households in India. Agric Resour Econ Rev. 2016;45(3):436–58. 10.1017/age.2016.3.Suche in Google Scholar
[60] Fouly A, Alnaser IA, Assaifan AK, Abdo HS. Developing PMMA/coffee husk green composites to meet the individual requirements of people with disabilities: Hip spacer case study. J Funct Biomater. 2023;14(4):200. 10.3390/jfb14040200.Suche in Google Scholar PubMed PubMed Central
[61] Bala DM, Padigapati Venkata NS, Yannam P. Global and regional trading blocs of coffee and tea: Outlook, trading signals, and policies. World Food Policy. 2020;6(2):119–56. 10.1002/wfp2.12018.Suche in Google Scholar
[62] Pangestika IW, Susilowati A, Purwanto E. Genetic diversity of coffea canephora pierre ex a. Froehner in Temanggung District, Indonesia based on molecular marker RAPD. Biodiversitas. 2021;22(11):4775–83. 10.13057/biodiv/d221109.Suche in Google Scholar
[63] Arciniegas-Grijalba PA, Patiño-Portela MC, Mosquera-Sánchez LP, Guerrero-Vargas JA, Rodríguez-Páez JE. ZnO nanoparticles (ZnO-NPs) and their antifungal activity against coffee fungus Erythricium salmonicolor. Appl Nanosci. 2017;7(5):225–41. 10.1007/s13204-017-0561-3.Suche in Google Scholar
[64] Watson K, Achinelli ML. Context and contingency: The coffee crisis for conventional small-scale coffee farmers in Brazil. Geogr J. 2008;174(3):223–34. 10.1111/j.1475-4959.2008.00277.x.Suche in Google Scholar
[65] Zambolim L. Current status and management of coffee leaf rust in Brazil. Trop Plant Pathol. 2016;41(1):1–8. 10.1007/s40858-016-0065-9.Suche in Google Scholar
[66] FAO. Crops and livestock products. 2024. https://www.fao.org/faostat/en/#home.Suche in Google Scholar
[67] Trinh Pham T, Giang BL, Nguyen NH, Dong Yen PN, Minh Hoang VD, Lien Ha BT, et al. Combination of mycorrhizal symbiosis and root grafting effectively controls nematode in replanted coffee soil. Plants. 2020;9(5):555. 10.3390/plants9050555.Suche in Google Scholar PubMed PubMed Central
[68] Ovalle-Rivera O, Läderach P, Bunn C, Obersteiner M, Schroth G. Projected shifts in Coffea arabica suitability among major global producing regions due to climate change. PLoS One. 2015;10(4):1–13. 10.1371/journal.pone.0124155.Suche in Google Scholar PubMed PubMed Central
[69] Ceballos-Sierra F, Dall’Erba S. The effect of climate variability on Colombian coffee productivity: A dynamic panel model approach. Agric Syst. 2021;190(Feb 2020):103126. 10.1016/j.agsy.2021.103126.Suche in Google Scholar
[70] Thuy PT, Ho TMH, Burny P, Niem LD, Lebailly P. Which perennial crop farm approach generates more profitability? A case study in Dak Lak Province, Vietnam. Asian Soc Sci. 2019;15(9):1. 10.5539/ass.v15n9p1.Suche in Google Scholar
[71] Karyani T, Djuwendah E, Mubarok S, Supriyadi E. Factors affecting coffee farmers’ access to financial institutions: The case of Bandung Regency, Indonesia. Open Agric. 2024;9(1):20220297. 10.1515/opag-2022-0297.Suche in Google Scholar
[72] Trinh LTK, Hu AH, Lan YC, Chen ZH. Comparative life cycle assessment for conventional and organic coffee cultivation in Vietnam. Int J Environ Sci Technol. 2020;17(3):1307–24. 10.1007/s13762-019-02539-5.Suche in Google Scholar
[73] Yusuf ES, Ariningsih E, Ashari, Gunawan E, Purba HJ, Suhartini SH, et al. Sustainability of Arabica coffee business in West Java, Indonesia: A multidimensional scaling approach. Open Agric. 2022;7(1):820–36. 10.1515/opag-2022-0144.Suche in Google Scholar
[74] Nguyen KT, Craparo A, Nguyen PM, Turreira-García N, Talsma T, Deniau A, et al. ThIRST: Targeted IRrigation support tool for sustainable coffee production. Front Sustain Food Syst. 2023;7(Oct):1–10. 10.3389/fsufs.2023.1267388.Suche in Google Scholar
[75] Volsi B, Telles TS, Caldarelli CE, da Camara MRG. The dynamics of coffee production in Brazil. PLoS One. 2019;14(7):1–15. 10.1371/journal.pone.0219742.Suche in Google Scholar PubMed PubMed Central
[76] Ellis EA, Baerenklau KA, Marcos-Martínez R, Chávez E. Land use/land cover change dynamics and drivers in a low-grade marginal coffee growing region of Veracruz, Mexico. Agrofor Syst. 2010;80(1):61–84. 10.1007/s10457-010-9339-2.Suche in Google Scholar
[77] Velandia M, Trejo-Pech C, Rodríguez-Padrón B, Servín-Juárez R, Stripling C. Challenges and managerial strategies of coffee cooperatives from the Huatusco Region in Mexico: The perspective of leaders. Agrociencia. 2022;56(8):1558–91. 10.47163/agrociencia.v56i8.2741.Suche in Google Scholar
[78] de Brito Mateus MP, Tavanti RFR, Tavanti TR, Santos EF, Jalal A, dos Reis AR. Selenium biofortification enhances ROS scavenge system increasing yield of coffee plants. Ecotoxicol Environ Saf. 2021;209:111772. 10.1016/j.ecoenv.2020.111772.Suche in Google Scholar PubMed
[79] Siswanto S, Wardani KK, Purbantoro B, Rustanto A, Zulkarnain F, Anggraheni E, et al. Satellite-based meteorological drought indicator to support food security in Java Island. PLoS One. 2022;17(6 June):1–20. 10.1371/journal.pone.0260982.Suche in Google Scholar PubMed PubMed Central
[80] Ruiz-García P, Conde-Álvarez C, Gómez-Díaz JD, Monterroso-Rivas AI. Projections of local knowledge-based adaptation strategies of Mexican coffee farmers. Climate. 2021;9(4):1–17. 10.3390/cli9040060.Suche in Google Scholar
[81] Asmal S, Parenreng SM, Astutik W. Arabica coffee productivity improvement strategy with value chain analysis approach (Case study: Sapan Village, North Toraja. J Ind Eng Manag. 2022;7(3):225–31. 10.33536/jiem.v7i3.1243.Suche in Google Scholar
[82] Salami A, Kamara AB, Brixiova Z. Smallholder agriculture in East Africa: Trends, constraints and opportunities. Working Paper No.105. African Development Bank, Abidjan (Ivory Coast), April 2010. p. 52.Suche in Google Scholar
[83] Winarno ST, Harijani WS. Robusta coffee (Coffea canephora) value chain in East Java, Indonesia. Agron Mesoam. 2022;33(3):48082. 10.15517/am.v33i3.48082.Suche in Google Scholar
[84] Huynh T, Popova L. Dynamics and economic efficiency of digital transformation of Vietnam’s coffee industry. Reg Ekon Yug Ross. 2023;1:125–34. 10.15688/re.volsu.2023.1.12.Suche in Google Scholar
[85] Muzaifa M, Rahmi F, Syarifudin. Utilization of coffee by-products as profitable foods-A mini review. IOP Conf Ser Earth Environ Sci. 2021;672(1):012077. 10.1088/1755-1315/672/1/012077.Suche in Google Scholar
[86] Ramirez-Zuñiga EJ, Castro-Silva HF, Velásquez-Pérez T, Garcia-Cruz EK. Unveiling critical innovation factors in sustainable coffee production: A colombian perspective. Prod Eng Arch. 2024;30(4):431–41. 10.30657/pea.2024.30.41.Suche in Google Scholar
[87] Sandeep TN, Gopinandhan TN, Hiregoudar S, Nidoni U, Katti P. Recent advances in processing and value addition in coffee (Coffea). Futur Trends Agric Eng Food Sci. 2024;3(B. 15, 3):375–95. 10.58532/v3bcag15p3ch7.Suche in Google Scholar
[88] Barreto Peixoto JA, Silva JF, Oliveira MBPP, Alves RC. Sustainability issues along the coffee chain: From the field to the cup. Compr Rev Food Sci Food Saf. 2023;22(1):287–332. 10.1111/1541-4337.13069.Suche in Google Scholar PubMed
[89] Addisie G, Lika TM. Upgrading opportunities and challenges for small coffee producersin Sidama region of Ethiopia. Int J Rural Manag. 2022;19(2):234–52. 10.1177/09730052221080884.Suche in Google Scholar
[90] Oduori D, Robert OM, Josephat C. Effect of value added tax incentives on financial performance of export processing zone agro-processing firms in Nairobi County Kenya. J Finance Account. 2024;4(3):1–8.Suche in Google Scholar
[91] Quiñones-ruiz XF, Penker M. Can origin labels re-shape relationships along international supply chains? – The case of Café de Colombia. Int J Commons. 2015;9(1):416–39.10.18352/ijc.529Suche in Google Scholar
[92] Anandharamakrishnan C. Spray-freeze-drying of coffee. In: Caffeinated and Cocoa Based Beverages. Elsevier Inc; 2019, p. 337–66.10.1016/B978-0-12-815864-7.00010-6Suche in Google Scholar
[93] Nguyen TH, Nguyen DL. Sustainable development of agricultural product processing industry in Vietnam. E3S Web Conf. 2021;258:04003.10.1051/e3sconf/202125804003Suche in Google Scholar
[94] Engelhardt T. Geographical indications under recent EU trade agreements. Inst Innov Compet. 2015;46:781–818. 10.1007/s40319-015-0391-3.Suche in Google Scholar
[95] Andrea J, Gómez G, Marina L, Pardo F, Camila Y, Vargas L. Valorization of coffee by ‑ products in the industry, a vision towards circular economy. Discov Appl Sci. 2024;6:480. 10.1007/s42452-024-06085-9.Suche in Google Scholar
[96] Dada JT. Trade policy and environmental sustainability in Africa: An empirical analysis. In: Natural resources forum. Oxford, UK: Blackwell Publishing Ltd.; 2024. p. 1–25. 10.1111/1477-8947.12488.Suche in Google Scholar
[97] Sonjaya Y. Advances in taxation research analysis of the effectiveness of tax incentives on energy sector investments. Adv Tax Res. 2024;2(2):120–31.10.60079/atr.v2i2.308Suche in Google Scholar
[98] Jansen M. Managing the green transition: The role of the OECD export credit arrangement. Glob Policy. 2022;13(Aug):554–6. 10.1111/1758-5899.13138.Suche in Google Scholar
[99] Meygoonpoury E, Ghadim MK, Ziabakhsh-ganji Z. Results in engineering internationalization of renewable energy base businesses with a combined approach to networking and collaborative competition. Results Eng. 2024;21(Oct 2023):101726. 10.1016/j.rineng.2023.101726.Suche in Google Scholar
[100] Denktas B, Pekdemir S, Soykan G. Peer to peer business model approach for renewable energy cooperatives. 2018 7th Int. Conf. Renew. Energy Res. Appl. Vol. 5. 2018, p. 1336–9.10.1109/ICRERA.2018.8566735Suche in Google Scholar
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