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Article

Analysis of the Impact of Information Behavior on the Marketing and Fertilization Strategies of Small Cocoa Producers in the Provinces of Guayas and Los Ríos in Ecuador

by
Ivonne Soraya Burgos Villamar
,
Luis Eduardo Solís Granda
,
Jorge Fabricio Guevara Viejó
and
Juan Diego Valenzuela Cobos
*
Centro de Estudios Estadísticos, Universidad Estatal de Milagro (UNEMI), Milagro 091050, Ecuador
*
Author to whom correspondence should be addressed.
Agriculture 2025, 15(8), 858; https://doi.org/10.3390/agriculture15080858
Submission received: 8 January 2025 / Revised: 18 February 2025 / Accepted: 20 February 2025 / Published: 15 April 2025

Abstract

:
The main barriers faced by small-scale cocoa producers in Ecuador are the limited access to and the use of information technologies, which affects their efficiency in production and marketing. This study evaluated the impact of information behavior on the fertilization and marketing strategies of small cocoa farmers in two Ecuadorian provinces that have presented outstanding performance at the national level in order to identify the main factors that cause information gaps. For this purpose, a structured survey was conducted between May and June 2024 on 150 cocoa producers farming up to 10 hectares to collect demographic data and analyze their information-use patterns in relation to agricultural market strategies. The survey included five dimensions: information sources, information evaluation, informational, social and economic. In addition, soil chemical analyses were conducted in 50 plantations managed by the same farmers to determine the affinity between fertilization practices and the nutritional needs of the crop. The results indicated that farmers in Guayas showed a more developed information behavior, with a greater knowledge of their information needs and an active interest in collecting data on agricultural markets. In contrast, farmers in Los Ríos made less use of the media as a source of information, which limited their impact on social and economic aspects. In soil chemistry, both provinces presented favorable conditions for the crop; however, low nitrogen and potassium concentrations could affect yields. In Guayas, the analyses revealed averages of 0.34 cmol(+)/L aluminum, 3.03 cmol(+)/L magnesium and 0.33 cmol(+)/L potassium, values that mostly meet the nutritional standards for cocoa. In Los Rios, the analyses reflected average values of 0.68 ± 0.46 cmol(+)/L aluminum, 2.98 ± 1.13 cmol(+)/L magnesium and 0.34 ± 0.11 cmol(+)/L potassium. Based on the findings of this study, in order to improve the competitiveness of the sector, it is suggested to design accessible public policies and training programs oriented to the use of digital tools and sustainable practices that promote access to markets and optimize the production chain.

1. Introduction

Cocoa (Theobroma cacao L.) is a shade-tolerant tropical tree grown in regions with specific climatic conditions characterized by constant humidity and temperatures [1]. This crop is found mainly in the humid tropics, between latitudes 10° N and 10° S, covering the continents of America, Africa, Asia and Oceania [2]. Considered “God’s drink” (Theo = God, Broma = drink), its historical and economic relevance has grown significantly in recent decades, propelling Ecuador to position itself as the fourth largest global producer. With a population of approximately 18 million people and a gross domestic product (GDP) per capita of 6533 USD, the country has established itself as the leader in the production of fine aroma cocoa, which in 2021 meant a contribution of 8.19% to the national GDP [3,4]. In addition, in 2023, 609,750 hectares of planted area dedicated to this crop were registered in national territory [5], demonstrating the relevance of the production of this crop for the Ecuadorian economy and its positioning in the global market.
Despite its economic importance, cocoa production in Ecuador faces challenges that limit its international competitiveness [6,7]. The lack of traceability in cultivated varieties makes it difficult to guarantee the quality demanded by specialized markets, and climate change has intensified pests, affecting yields. In addition, the mixture of fine aroma cocoa beans with CCN51 in the initial stages of marketing prevents producers from accessing the premium prices that characterize gourmet markets [8]. In addition, the lack of technical knowledge and organization among small farmers undoubtedly reduces productivity and makes it difficult for them to enter high-value international markets [9].
In response to these difficulties, the Government of Ecuador and other strategic actors have implemented initiatives such as the National Plan for the Rehabilitation of Cacao Fino de Aroma and certification and traceability programs that seek to guarantee sustainable agricultural practices and deforestation-free exports. These actions, although necessary, have not completely overcome structural problems such as the geographic dispersion of production units, the informality of marketing processes and the limited access to fixed markets.
In recent years, digitalization has emerged as a fundamental tool for the modernization and integration of the agricultural value chain. Information and communication technologies (ICTs), such as cell phones, e-commerce applications and digital platforms, have great potential to improve agricultural practices and trade strategies by mitigating information asymmetries and overcoming geographic barriers [10,11]. These tools not only facilitate the transfer of technical knowledge related to fertilization, pest control and marketing strategies but also contribute to improving the productivity and sustainability of the sector [12]. Globally, developing countries are increasingly adopting advanced technologies to address the agricultural challenges posed by climate change and growing sustainability demands [13]. However, in Ecuador, issues related to accessibility and technical training remain major obstacles, particularly in rural areas [14].
The objective of this study was to analyze the influence of information behavior on the transformation of marketing and fertilization strategies of small cocoa producers in Guayas and Los Ríos, two provinces that have outstanding performance in the national agricultural panorama of the Cacao Complejo Nacional variety [15]. Los Ríos has a population of 1898 inhabitants, while Guayas, with 4.3 million inhabitants, is the most densely populated province in the country and leads the production of this variety. In comparison with other regions of the country, both show a balance between high population density and agricultural capacity. This study will help identify gaps in the information access capacity of smallholder cocoa farmers according to their geographic location. In addition, it will analyze how digitization, through the dissemination of technical agricultural information, can reduce these gaps, strengthen the sustainability of the cocoa sector and improve competitiveness in international markets, thus promoting sustainable agricultural development.
This research was guided by the following questions:
-
To what extent does information behavior, structured along five dimensions (information sources, information evaluation, informational, social and economic), influence the effectiveness of marketing strategies of smallholder cocoa farmers?
-
How do current fertilization practices align with efficient practices in soil fertilization processes for cocoa cultivation?
-
Is there a relationship between access to technical agricultural information and competitiveness indexes in the production and commercial processes of small cocoa producers?
This article is structured to address the topic in a comprehensive manner. First, a documentary review of the cocoa sector was conducted, with emphasis on the social and technological aspects that influence farmers’ knowledge networks. Then, a survey was applied to capture the farmers’ perception of the influence of the media on the sale of their products and the adoption of sustainable agricultural practices. Finally, a soil analysis was carried out in different cocoa farms to evaluate the dynamics of fertilization and relate the efficiency of these processes to the information capacities present in the rural sector.

2. Review and Theoretical Perspectives of the Cocoa Sector in Ecuador

2.1. Historical References of the Cocoa Value Chain

The cocoa sector in Ecuador has played a crucial role in the economy since the 19th century. Between 1860 and 1920, the country consolidated its position as the world’s leading exporter of cocoa, thanks to a socioeconomic structure characterized by the use of low-cost labor, low capital requirements and growing demand in international markets. This period was key to establishing the cocoa value chain, which included the creation of important export houses and their participation in markets dominated by companies such as Nestlé and Cadbury.
Subsequently, factors such as the emergence of crop diseases, such as monilia and witches’ broom, together with global market saturation, led to a decline in production. In response, Ecuador diversified its agriculture, especially with the cultivation of cocoa. Despite these challenges, cocoa maintained its relevance in the national economy, with a rebound in prices in the 1970s and a focus on high-quality varieties such as Cocoa Nacional Sabor Arriba [16].
Currently, there are two types of cocoa, the “Nacional”, which is recognized worldwide under the classification Fino de Aroma for having a very short fermentation and giving a smooth chocolate with good flavor and aroma, and the CCN-51, which is an improved variety of Ecuadorian origin with high productivity compared to the Fino de Aroma. Cocoa processing is concentrated in a small group of agroindustries, and marketing is carried out mainly through intermediaries, with minimal state intervention. Although this model is traditional, it faces challenges related to the need to adapt to global market dynamics and sustainability demands. Figure 1 shows the characterization of cocoa cultivation in the national territory during the year 2023.

2.2. Fertilization of Cocoa Areas

Fertilization of cocoa (Theobroma cacao L.) growing areas in Ecuador is a crucial component to ensure healthy plant growth, increase production and improve the quality of cocoa beans [2]. In 2023, with Ecuador being one of the main exporters of cocoa worldwide, INEC recorded a cultivation area of 609,750 ha, 26.4% concentrated in the province of Los Ríos [18].
Adequate fertilization not only improves crop yield, showing in the number and weight of cobs, but also influences grain quality, particularly its fat and solids content. In addition, effective nutritional management contributes to plant resistance to diseases such as moniliasis and witches’ broom. These benefits underline the importance of implementing sustainable strategies that enhance cocoa crop productivity and preserve ecosystem health [12].
Considering this, research projects play a key role in improving agricultural practices related to fertilization and the search for solutions to problems such as cadmium (Cd) contamination. Among the initiatives proposed are the use of organic amendments, soil pH adjustment, and the application of microorganisms that facilitate the immobilization of Cd. The selection of cocoa genotypes that absorb lower amounts of this metal is also promoted, together with the development of biological products that increase plantation yields. These actions, combined with integrated nutrient management in humid tropical soils, will contribute to strengthening the cocoa production chain in the context of sustainable agriculture [19]. Figure 2 presents information on the annual frequency of fertilization, the applications made and the average fertilizer used in the cultivation areas at the national level.

2.3. Information Management for Agricultural Decision-Making

The majority of cocoa producers in Ecuador, approximately 70%, are small producers, while 20% are medium-sized producers and only 10% are large producers. This structure highlights the importance of small farmers in the production chain, who face significant barriers related to access to information, proper post-harvest management and marketing [20].
Producers are often unaware of global market fluctuations, which prevents them from negotiating fairly with intermediaries. These actors, who play a predominant role in marketing, set low prices for the product, obtaining higher profits to the detriment of farmers. They also lack quality certifications, which limits their ability to participate in specialized markets [21].
Access to and effective management of information is critical to the success of farmers, especially smallholders, who represent a significant proportion of the agricultural sector in many countries. These farmers rely on formal and informal knowledge networks, such as farm advisors, subsidy programs and cooperatives. These networks not only facilitate knowledge transfer and innovation but also support the diversification of agricultural activities, such as agro-tourism, which has proven to be an effective strategy in regions such as Europe [22].
In addition, cooperatives play a crucial role in providing access to extension services, training and high-quality agricultural resources. They also strengthen farmers’ bargaining power, helping them to obtain better prices and reduce their dependence on middlemen [23]. However, in some regions, such as Thailand, information management practices have been identified as limited, affecting productivity and making it difficult to solve crop problems [24].
The use of technological tools, such as sending text messages with information on market prices and personalized weather conditions, has proven useful for improving agricultural decision-making, as was the case in Colombia. However, these advances must be complemented by more robust support structures to maximize their impact, especially in terms of marketing and fertilization [25].

2.4. Digital Traceability in Agricultural Production

ICTs have become essential tools for transforming smallholder agriculture, including the cocoa sector, by facilitating access to vital information and improving production and business practices. According to ECLAC, these technologies are fundamental for boosting development, competitiveness and economic sustainability in key sectors, particularly in rural areas. Smallholder cocoa farmers face challenges such as high-quality standards and the need for continuous access to market and weather information. The incorporation of ICTs helps overcome these barriers and promotes more efficient crop management [22].
Several international experiences reinforce this vision. In Ecuador, Peru and the Dominican Republic, ICTs have demonstrated their capacity to improve agricultural management through mobile applications that allow recording production and cost data. Initiatives such as REDAGROCLIMA and PLATICAR have offered climate warning and market intelligence services, reducing transaction costs and improving strategic decision-making [26]. In East Africa and South America, access to technologies such as smartphones and personalized messaging services has facilitated the optimal use of inputs, although barriers such as the cost of devices and the need for training persist [27].
In addition, ICTs promote integration and articulation in agricultural value chains, facilitating the exchange of information among actors and improving competitiveness in global markets. Projects in Costa Rica and Argentina, such as the use of interactive platforms and digital traceability systems, demonstrate the positive impact of these technologies on the quality and marketing of agricultural products. However, the effective adoption of ICTs requires overcoming limitations such as the digital divide, the lack of infrastructure in rural areas and high access costs.

2.5. Digitalization as a Driver for Sustainable Strategies and Green Marketing

2.5.1. The Role of Digital Marketing in Attracting Agricultural Investment

Farming and food systems have been shaped and reshaped by significant large-scale agricultural investments (LSAI). Land acquisition in the latest wave has involved leases of 50 to 99 years and purchases in excess of 10,000 hectares. As of 2009, more than twelve dozen African nations, including Ethiopia, have awarded millions of hectares of farmland to investors, with the expectation that LSAI would facilitate rapid agricultural development and serve as a solution to persistent rural poverty. Other terms for land grabbing include ‘new land colonization’ and ‘green colonization’ [28].
Investment attraction is the first phase of the investor’s life cycle [29]. During this stage, the project is structured, different locations are analyzed and the most suitable one is chosen. Marketing strategies include sector studies, comparative analysis and development of promotional materials. In addition, advertising campaigns, public relations and dissemination in social networks and media are carried out. Participation in trade fairs, exhibitions and seminars also helps to attract investors [30].
The use of digital marketing strategies has transformed the process of attracting investment in the agricultural sector (Figure 3). Digital platforms, marketing strategies and promotional campaigns act as the main mechanisms for generating visibility and communicating the added value of agricultural projects. These tools are channeled through social networks, websites, emails and mobile applications, which function as outreach media to connect investors with potential business opportunities in the agricultural sector. The information provided through these channels directly influences the decision-making process of entrepreneurs and agricultural producers, who evaluate projects and determine their viability. As a result of this process, farmers can make informed decisions about adopting new strategies or digitally promoted technologies, which in turn generates an increase in income, with an ecosystem where digitization and investment complement each other to drive the development of the agricultural sector [26].

2.5.2. Balancing Business Sustainability and Natural Resources in the Digital Era

Access to land and water continue to be the most fundamental natural resources for the rural population. However, the rights of small producers, pastoralists and indigenous peoples have been progressively threatened due to their acquisition by other actors, acquisitions often driven by state policies that favor land concentration [32].
Various studies on large-scale agricultural investments have found adverse effects on local livelihoods, food security and access to natural resources. Contrary to government expectations, evidence shows that leases of large tracts of land, including forest areas and common property resources, have compromised both ecosystems and the livelihoods of local communities. This is because many of the lands transferred to large industries have historically been used by local communities for agriculture and livestock grazing under customary systems. In addition, crops produced by large companies tend not to be traded in local markets, and therefore, do not contribute to increasing the availability of food in those markets [33].
The sustainable management of these natural resources in agriculture is a critical challenge. Overexploitation of soil and inefficient use of water have generated problems of environmental degradation and reduced agricultural productivity. In response to this, strategic policies have been developed for the conservation of natural resources, including the implementation of regenerative agricultural practices and the use of digital technologies for soil and crop monitoring [34].
For corporate social responsibility (CSR), the strength of a company lies not only in the application of innovative solutions but also in the promotion of responsible attitudes among consumers, the environmental education of new generations and the promotion of collective initiatives for the preservation of biodiversity. In this sense, the adoption of circular economy strategies and resource use optimization has been promoted by several companies in the agroindustrial sector to minimize their environmental impact [35].
The advance of digital transformation has brought with it new tools to ensure the efficient and sustainable management of natural resources in the business environment. Recent research highlights that companies that have integrated digital technologies into their environmental management models have managed to reduce their ecological footprint and improve operational efficiency, ensuring a balance between profitability and ecological impact [36].
Business development is closely linked to the conditions of its stakeholders since society’s quality of life, education and well-being have a direct impact on consumption habits. Therefore, companies are interested in incorporating into their actions activities that are part of sustainable development [37].
Strategic regulation and governance of natural resources play a key role in this context. A study on strategic resource management in the European Union highlights that countries have implemented concession and control policies to avoid the depletion of minerals, groundwater and fertile soils [38].
The incorporation of digital technologies in agriculture will be decisive in ensuring its sustainability in economic, environmental and social terms. The digital transformation has impacted the entire agricultural value chain, from production to consumption, which requires more innovative business models that are adaptable to the new demands of the sector [39].
The evolution towards precision agriculture has been based on the development of process automation, applications and information systems, cyber-physical platforms and tools for the collection and analysis of large volumes of data. A recent study on sustainable digital transformation highlights the importance of strategic management and environmental impact monitoring through advanced technologies such as artificial intelligence and big data, which has enabled companies to make more informed decisions and reduce their operational waste [40]. So far, digitalization has been focused on improving production efficiency, but its role in the future will be even more diverse; agriculture should become an attractive activity in the market, with greater scope for opening new agricultural enterprises, generating new jobs and increasing the competitiveness of farms [41].

2.5.3. E-Commerce as a Platform for Green Marketing and Negotiation Strategies

Electronic commerce, or e-commerce, has established itself as a digital network that facilitates interaction between buyers and sellers, enabling commercial transactions aimed at acquiring goods, services and information [42]. Within the digital context, consumers’ purchasing decisions on online platforms are influenced by various factors, including previous experience, familiarity with the brand, curiosity and, especially, reviews from other users. Reviews posted on e-commerce sites represent an important source of information validation, allowing potential buyers to assess the quality and reliability of products with which they have no prior experience. At the enterprise level, e-commerce adoption continues to expand globally; however, as organizations grow, managing their operations in digital environments becomes more complex, presenting new challenges in terms of size, logistics and competitiveness [43].
E-commerce companies have allocated significant resources to integrating big data into their operations in order to optimize their performance, gain competitive advantages and strengthen the sustainability of their businesses. The collection and analysis of data, both structured and unstructured, allow information to be transformed into more effective strategies. An essential aspect of this process is the personalization of marketing, where consumers’ preferences and buying habits help to adjust product offerings and improve the user experience [44]. A recent study highlights the use of the BG/NBD model for predicting customer behavior and calculating customer lifetime value (CLV) in e-commerce companies, which allows for the planning of more effective marketing strategies and reducing risks under uncertainty [45].
The growing demand for green products in e-commerce has been associated with the influence of changes in consumer behavior. Green purchasing is associated with a preference for sustainable products that generate environmental benefits and reflect a commitment to environmental protection [46]. The purchase intention in this segment is oriented to reduce unnecessary consumption and prioritize goods with lower environmental impact, being several factors that determine these decisions. Liu and Yi [47] point out that targeted marketing based on big data has boosted the sales of green products, outperforming conventional marketing in this area. In addition, personalized product recommendations have sparked greater consumer interest, increasing the likelihood of purchase. The ease of use of platforms also plays a key role in the purchase decision, including the acquisition of sustainable goods [48].
Finally, price remains a determining factor in purchase decisions within the green consumer market. In this context, dynamic pricing and differentiation strategies have allowed e-commerce companies to improve their competitiveness through market analysis and price optimization [49].

2.5.4. Sustainable Business Transitions and the Rise of Green Businesses

Green business represents a key evolution in global business strategy, combining profitability with environmental sustainability to generate responsible and resilient business models. Digitalization has driven this transformation by optimizing production processes, improving resource efficiency and facilitating the integration of green strategies in various sectors [50]. Sustainable business models based on the circular economy, fair trade and green financing have enabled companies from different industries to reduce their ecological footprint without compromising their competitiveness [51]. In addition, green trade has demonstrated its ability to energize the economy by generating employment in emerging sectors such as renewable energy and sustainable production while strengthening consumer confidence in environmentally committed brands [52].
However, the transition to sustainable business models faces challenges such as perceived high upfront costs, lack of clear regulations and resistance to change within organizations [53]. Despite these obstacles, more and more companies have managed to overcome these barriers through the implementation of strategic policies, access to sustainable financing and digital innovation. The integration of advanced technologies, such as artificial intelligence and data analytics, has enabled better decision-making in resource management, optimizing the environmental and economic impact of companies [54]. The evolution of commerce towards more sustainable practices not only responds to an ecological need but also opens up new economic opportunities, positioning companies that adopt green strategies as market leaders of the future.

2.6. Research Gap and Operational Framework for Information Behavior

Although online information-seeking behavior has become a global trend, studies focused on its use in agriculture are limited. Research in this area has been predominantly developed in more advanced countries, with Ecuador being one of the countries with the fewest studies in this area. Searching for agricultural information online is considered to have a positive influence on small farmers, as they are more likely to adopt better agricultural practices after accessing adequate information on crop management, fertilization and pest control. The lack of specific data at the local level, together with the absence of implementation models adapted to the particularities of Ecuadorian conditions, demonstrates the importance of developing lines of research aimed at analyzing the structural, economic and educational barriers that affect this group of producers. Based on this, a farmer demonstrates informative behavior as follows:
  • Information sources: ability to identify and locate available data sources.
  • Information evaluation: ability to judge the quality, relevance and usefulness of information, applying established criteria and standards.
  • Informative: ability to retrieve data for the purpose of repeated use.
  • Social: ability to interact with other individuals and share information.
  • Economic: ability to employ information as a means to improve related skills in job performance.
From the literature review on digital literacy skills, this study identified the indicators described in Table 1. These indicators are designed to facilitate the understanding of smallholder farmers’ information behavior, including their ability to locate available data sources, judge the quality of resources, retrieve data for reproducibility, share information with other individuals and use information as a means to improve job-related skills.
Based on these premises, the following hypotheses are formulated and the research model Figure 4:
Hypothesis 1 (H1).
The information behavior, framed in five main dimensions, contributes directly to the improvement of the commercialization of small cocoa farmers.
Hypothesis 2 (H2).
Current fertilization practices used by smallholder cocoa farmers present limited alignment with efficient practices in fertilization processes and vary significantly according to the geographical area of the farmers.
Hypothesis 3 (H3).
There is a positive relationship between access to agricultural technical information and productivity in the production and commercial processes of small cocoa farmers.

3. Research Methodology

3.1. Description of the Study Area

Cocoa production takes place in humid tropical zones located between latitudes 15° N and 15° S, with exceptions in subtropical regions between 23° N and 25° S [33]. In Ecuador, the main cultivation areas are located in the provinces of Guayas, Los Ríos, Manabí and Esmeraldas, which account for most of the national production [21].
This study was carried out in the provinces of Guayas and Los Ríos (see Figure 5), which were selected due to their relevance as the main cocoa-growing areas of the country. Both provinces share similar climatic conditions and concentrate a high density of producers, which makes them ideal areas to analyze information management in smallholder cocoa farmers. This approach makes it possible to evaluate how information capabilities impact production and marketing in areas of high productivity.
The province of Guayas, located in the coastal region, is bordered to the north by Manabí and to the south by El Oro and the Pacific Ocean. Its territorial extension is approximately 17,139 km2, with altitudes varying between 0 and 100 m above sea level. Its tropical climate has an average annual temperature of 25 °C, which favors the cultivation of cocoa.
Los Ríos, located in the central region of Ecuador, is bordered to the north by Santo Domingo de los Tsáchilas and to the south by Guayas. With an area of 7205 km2, this province has altitudes between 5 and 200 m above sea level. Annual temperatures range between 22 °C and 31 °C, conditions conducive to the optimal development of cocoa.

3.2. Sampling and Data Collection Methodology

3.2.1. Producer Selection

To collect information, face-to-face interviews were conducted with small-scale cocoa producers in the provinces of Guayas and Los Ríos. The sample included a total of 150 participants, evenly distributed with 75 individuals in each group of interest (Figure 6), a sample size that allowed for an adequate characterization of the productive and socioeconomic conditions of the farmers. Following the classification of Lowder, Skoet and Raney (2016), small producers are defined mainly by the size of their farms, considering as a reference those with less than 10 hectares, a criterion adopted in this study [55]. The data were collected between the months of May and June 2024, strategically aligned with the period of greatest activity in the harvest of cocoa beans at the national level.
Data collection for this study was carried out through a structured survey applied in small plantations of Theobroma cacao L. located in the provinces of Guayas and Los Ríos. A non-probabilistic sampling method was used, selecting as participants owners managing plots of less than 10 hectares. The validity of the instrument was determined by calculating Crobanch’s alpha.
The questionnaire used consisted of two main sections. The first section aimed to collect demographic information from the farmers, including aspects such as gender, age, educational level, agricultural experience, variety of cocoa grown, time of agricultural activity and number of hectares planted. This format was designed taking as a reference a survey previously validated in the study by Quito et al. [56].
The second section of the questionnaire was oriented to evaluate the perception of producers regarding their access to and use of media in the marketing of cocoa. For this purpose, 16 items were adapted from an instrument validated in the study by Magesa et al. [57], structuring the analysis in five key dimensions: information sources, information evaluation, informative, social and economic dimensions. These categories were integrated with the purpose of evaluating the informational capabilities of the participants and analyzing their relationship with the marketing strategies implemented (Figure 7).
During the interviews, closed questions were asked, and five-point Likert-type scales were used to measure the respondents’ perceptions. This scale allowed assigning evaluations from 1 to 5, where 1 corresponded to “never”, 2 to “rarely”, 3 to “sometimes”, 4 to “frequently” and 5 to “always”, providing a consistent and systematic evaluation approach of the attitudes and perceptions of the producers with respect to the qualitative indicators analyzed.

3.2.2. Selection of Soil Samples

In addition to the survey, soil sampling was carried out in 50 selected plantations with the objective of evaluating the soil conditions on cocoa farms [58]. Twenty-five plantations were selected in the province of Guayas and 25 in the province of Los Ríos, whose managers actively participated in the study.
All the selected plantations were in the vegetative stage of growth. Sampling was carried out using the palín sampling method, and at each location, a systematic grid design was applied to determine the sampling points. The samples obtained at each point were combined to form a composite representative of each property analyzed.

Soil Nutrient Diagnosis

In order to evaluate the chemical characteristics of the soil in the provinces of Guayas and Los Ríos, a detailed nutritional diagnosis was carried out. This analysis was carried out at the facilities of the company Ecuahidrolizados SAS, located in the city of Guayaquil, Ecuador.

pH Concentration

Following the study of Loli [59], soil pH was determined using a potentiometer and a soil–water ratio of 1:2. This procedure involved mixing one part dry soil with two parts distilled water, stirring the mixture and resting before taking the measurement. This analysis allows evaluating the availability of nutrients, since cocoa has an optimal development in slightly acid soils, with an ideal pH in the range of 6.0 to 6.5.

Organic Matter (OM) Concentration

Organic matter was determined by Walkley and Black’s wet combustion method, which consists of the oxidation of organic matter using a solution of potassium dichromate (K2Cr2O2O7) in the presence of sulfuric acid (H2SO4) [59].

Total Nitrogen Concentration (N)

According to the study by Francisco et al. [60], the evaluation of total nitrogen was carried out using the Microkjeldahl digestion method. This procedure converted organic nitrogen into ammonium by digestion with sulfuric acid and catalysts. Subsequently, the generated ammonium was distilled and titrated to determine the total nitrogen concentration.

Concentration of Calcium (Ca), Magnesium (Mg) and Exchangeable Potassium (K)

The concentration of exchangeable calcium, magnesium and potassium was determined by extraction with 1 N ammonium acetate (AA) at pH 7, followed by their quantification using atomic absorption spectrometry (AAS) [61]. This method made it possible to evaluate the cations available to plants, which play a fundamental role in maintaining cell structure, facilitating photosynthesis and increasing disease resistance.

Available Phosphorus Concentration

The available phosphorus content was determined by Olsen’s method, which uses a solution of sodium bicarbonate (NaHCO3) at 0.5 M and pH 8.5 as an extractant. This analysis is fundamental to examine the availability of phosphorus in the soil, the main axis for root and fruit development [62].

Cadmium Concentration

Cadmium was analyzed using the atomic absorption spectrometry (AAS) technique. For this purpose, soil samples were digested with the strong acid HNO3, which helped to release the chemical element, and subsequently quantified through the spectrometry equipment.

Exchangeable Aluminum (AI) Concentration

The concentration of exchangeable aluminum was determined by Yuan’s method, using 1 M potassium chloride (KCl) solution as the extractant agent. Subsequently, the aluminum content in the extract was quantified by titration [63].

Copper and Iron Concentration

The amount of copper and iron was determined using the DTPA (diethylenetriaminepentaacetic acid) extraction technique. This chelating agent allowed the extraction of copper and iron from the soil, forming soluble complexes that were then measured by spectrometry.

3.3. Data Analysis

The responses obtained through the survey were processed with SPSS statistical software (version 26.0.0.0), allowing the tabulation of data and the calculation of performance points corresponding to each indicator and category for the different interest groups. This analysis focused on evaluating how information and communication technologies (ICTs) influence producers’ marketing and fertilization, using multiple linear regression analysis. For this purpose, we used the weighted averages of each dimension (information sources, information evaluation, informational, social and economic dimensions) according to the province of origin. In the multiple linear regression analysis, the economic and social dimensions are considered as dependent variables, while the remaining dimensions act as independent variables. This technique has as its method the construction of an equation, generating a first-order mathematical model, expressed by the following equation:
Y = β 0 + β 1 X + ϵ ,
where:
β 0   and β 1   are unknown parameters and ϵ is the random error [64].
In addition, the results of the soil analyses were subjected to an analysis of variance (ANOVA) to detect significant differences between groups, establishing a significance level of p < 0.05. As a complement, the Duncan multiple comparisons test was applied under the same significance level, with the objective of specifying the differences between the means of the groups analyzed. All statistical processing was performed using SPSS software (SPSS version 26.0.0.0.0).

4. Results and Discussion

4.1. Profile of Smallholder Cocoa Farmers

The profile of the small cocoa farmers who participated in this research included farmers from the provinces of Guayas and Los Rios, in Ecuador. In total, 150 randomly selected individuals were surveyed, whose characteristics are detailed in Table 2.
According to the data collected, 70.67% of producers were men, while 29.33% were women. These figures are consistent with INEC records [18] in 2023, which indicate a distribution of 71.4% men and 28.6% women engaged in agriculture.
In terms of age groups, the most represented were producers between 46 and 55 years old, followed by those between 26 and 35 years old. Regarding educational level, 30.67% of the respondents completed secondary education, while 21.33% reached a higher educational level. Regarding agricultural experience, 22.67% have between 16 and 20 years of experience working in the sector, and 24.67% of the respondents have been living in that locality for more than 20 years. Regarding the cultivated area, 24% of the respondents managed between 0.5 and 3 hectares of cultivation, and 36.67% of them focused on the cultivation of domestic cocoa, this being the predominant type in the region.
The analysis of socio-demographic information is of utmost importance for a social analysis. The educational level of cocoa farmers seems to be directly related to information behavior in rural areas. Previous studies have found that farmers with secondary or higher education have easier access to online information sources, which allows them to optimize fertilization and improve their marketing. In contrast, those without formal education face significant barriers in the incorporation of digital tools, which undoubtedly affects their competitiveness in the market.
On the other hand, the demographic stability of producers also influences technology adoption. Those who have lived in the province for more than 20 years tend to develop trust networks in which traditional means of information predominate, while the younger ones show a greater openness to the use of digital platforms, highlighting the importance of differentiated training programs to ensure the digital inclusion of all producers.

4.2. The Influence of Information Competencies in the Marketing Field

The mean scores obtained for the main study variables ranged between 3.07 and 3.04 on a five-point Likert scale, corresponding to the interest groups of Guayas and Los Ríos, respectively. To assess the content validity of the instrument used, Cronbach’s alpha coefficient was calculated, yielding a value of 0.98. This result demonstrates a high internal consistency, ensuring the reliability of the measurements. According to Nunnally and Bernstein [65], a coefficient above 0.90 is considered excellent, which supports the robustness of the instrument used in this research.
The results shown in Table 3 reveal significant differences in the performance of the participants, particularly in Los Ríos, where a decrease in the score associated with the use of information sources and their impact on social and economic factors was detected. This suggests an evaluation between the dimensions studied. A noteworthy finding is that most farmers do not implement advanced techniques to search for agricultural information, which could be explained by a lack of knowledge, limited resources to acquire electronic devices or time constraints.
Regarding the reliability and quality of the sources consulted, farmers in Guayas show a greater inclination toward the use of printed publications and price optimization in agricultural marketing. On the other hand, while both groups exhibit common strengths, key differences are identified: Guayas farmers have an advantage in market diversification and in the use of printed publications, while Los Ríos excels in promoting investments in agricultural activities. These differences could be associated with factors such as the availability of resources, digital literacy and marketing experience.
In line with these findings, Gumbi et al. [66] conducted a systematic review of digital solutions for the agricultural sector, concluding that many smallholders are left out of reach of these tools. The digital agriculture ecosystem comprises essential elements such as digital platforms, business model innovation, digital literacy and skills, accessibility, and the advances of the Fourth Industrial Revolution (4RI). Despite efforts to optimize production and access to agricultural information through digital tools, barriers such as high service costs and limited digital literacy persist, significantly affecting smallholder farmers. This reinforces the need to implement inclusive strategies that reduce these technological gaps.
Regarding the social dimension, which is related to the impact of communication on commercialization, respondents from the Guayas province showed a higher rate of perception of how the media contributes to improving interaction and the exchange of agricultural information, also strengthening their empowerment.
The study by Zhu and Wang [67] addresses, from a socioecological perspective, how agricultural cooperatives empowered collective action. Their results highlighted that these cooperatives, through joint decision-making and internal monitoring mechanisms, are able to empower farmers by integrating resources and promoting an equitable distribution of risks and benefits.
In addition, the perception of small cocoa farmers on the impact of the economic and social dimensions of information on the marketing of their product was assessed. The results obtained from the multiple linear regression analysis, presented in the form of a scatter plot (see Figure 8), show a strong explanatory capacity of the dimensions evaluated in the model. In particular, the economic dimension reached an adjusted R2 of 0.865, indicating that 86.5% of the variability in this dimension is explained by the independent variables considered. On the other hand, the social dimension presented an adjusted R2 of 0.89, demonstrating an even greater predictive capacity since 89% of the variability is attributed to the factors analyzed.
The results showed that, in the economic dimension, both information sources and information evaluation were found to have a significant influence. The information sources variable stood out with an unstandardized coefficient of 0.433. Information evaluation, although with a smaller impact, had a coefficient of 0.298, which implies that a one-unit increase in these variables raises the economic dimension on average. The standardized coefficients (Beta) confirm that information sources (0.567) have a greater influence than information evaluation (0.382) on this dimension. This highlights the importance of fostering access to quality information to boost farmers’ economic capabilities.
In the social dimension, the same variables (information sources and information evaluation) also showed a significant effect, with significance values lower than 0.05. The information sources variable presented an unstandardized coefficient of 0.560, indicating that greater use of these sources is associated with a considerable increase in social performance. In turn, the evaluation of information contributed a coefficient of 0.445, highlighting its relevance in the improvement of this dimension. The standardized coefficients show that information sources (0.543) have a stronger impact than information evaluation (0.422) on this dimension. This suggests that access to and use of information resources are essential for social capacity building among producers.
The results obtained in the present analysis partially support the findings of Zanello and Srinivasan [68], who emphasized the relevance of radio and mobile telephony in the transmission of commercial information. In this case, it was observed that “Information Sources” have a significant impact on the social and economic dimension of cocoa farmers. However, as in the aforementioned study, the reliability of the sources is a determining factor for this information to have a positive effect on decision-making. The data obtained reinforce the idea that extensionists, not only the media, are key to providing reliable information. In this sense, farmers who employ advanced strategies to evaluate information are able to maximize their impact, especially in marketing and fertilization.

4.3. Analysis of Soil Nutritional Quality in Small-Scale Cocoa Farms

The results of the chemical analysis of the soils of the provinces studied, presented in Table 4, showed similar and favorable characteristics for the crop. In terms of pH, the soils of Guayas were slightly less acidic (6.39 ± 0.74) compared to Los Ríos (6.08 ± 0.93), both within a range close to neutral. The levels of organic matter, calcium and available phosphorus were moderate between both provinces, indicating conditions conducive to nutrient retention and improvement of soil structure. On the other hand, total nitrogen and potassium showed low levels in both localities (Guayas: 0.33 ± 0.10 and 0.33 ± 0.11; Los Ríos: 0.32 ± 0.10 and 0.34 ± 0.11, respectively), suggesting the need for fertilization to optimize plant growth.
As for metals, the levels of cadmium and exchangeable aluminum were low in both provinces, which is positive for complying with international export standards. Copper values were slightly higher in Guayas (2.16 ± 1.35) than in Los Ríos (2.02 ± 1.38), while iron levels were moderately high and similar (Guayas: 5.25 ± 0.67; Los Ríos: 4.94 ± 1.72), both of which are adequate for plant metabolism.
Cocoa farms in the Guayas province presented a greater alignment with optimal fertilization ranges, which could be attributed to their high capacity for agricultural adaptation and access to diverse sources of information. These findings coincide with the results published by Dr. Loli [46], who identified that farmers in Peru with access to modern technologies demonstrated a greater willingness to integrate new sources of information into their agricultural practices.
On the other hand, several researchers have pointed out that small farmers face difficulties in increasing their production levels and improving marketing efficiency due to scarcity of resources, lack of adequate technologies and limited economic capital. These constraints represent a significant barrier to the adoption of new technologies. In this context, farmers would be willing to incorporate innovations, such as digital media, only if these techniques previously guarantee a proven economic return in nearby or similar areas.
The identification of disparities in the access to and use of information by the rural community shows the need to design differentiated policies that optimize the transfer of knowledge according to the socioeconomic and productive characteristics of each group. The implementation of training strategies adapted to local realities would improve farmers’ capacity to obtain and use relevant technical data in decision-making, which would facilitate the modernization of their agricultural practices. To this end, it is recommended that structured training programs be established that integrate innovative methodologies in the search for and analysis of agricultural information, promoting the use of digital platforms specialized in crop and market management. At the same time, the creation of technical assistance centers in rural areas would favor continuous access to specialized advice and agricultural monitoring technologies, thus contributing to the sustainability of the cocoa sector.

5. Conclusions

The results of this study showed that the information behavior of cocoa farmers in Guayas and Los Ríos significantly influences the effectiveness of their marketing and fertilization strategies. The survey identified that farmers in Guayas have a more developed information behavior, standing out in the use of printed publications, digital platforms and advanced information search techniques. In contrast, farmers in Los Ríos showed lower access to and use of information sources, which favors a more dynamic social interaction and facilitates the marketing of their products.
In relation to the research questions, it was confirmed that information behavior, structured in five dimensions (information sources, information evaluation, informative, social and economic), has a direct impact on the optimization of agricultural strategies. In particular, the economic dimension presented a significant correlation with the diversity and reliability of the sources consulted, suggesting that access to quality information improves commercial opportunities. In addition, the social dimension showed that interaction with other actors in the sector favors strategic decision-making in cocoa marketing.
The soil analysis, complemented by grower perceptions, revealed that current fertilization practices are not fully aligned with efficient standards, given that despite favorable soil conditions, low nitrogen and potassium concentrations can affect yields.
Finally, this study supports the hypothesis that access to technical agricultural information positively influences the productivity of smallholder cocoa farmers. However, structural challenges remain, such as resistance to technological change and limited training in digital tools.

5.1. Limitations of the Study

  • Since data were collected from 50 plantations, generalization of the results could be limited because only two provinces were included (Guayas and Los Rios). This excludes other cocoa-growing regions of Ecuador that might have different agroclimatic conditions and agricultural practices.
  • This study focused on the chemical characteristics of the soil and the informational capabilities of the farmers, leaving aside biological and physical aspects of the soil that can also influence cocoa yields.
  • Although social and economic factors are analyzed, the complexity of these variables may require further research to fully understand their impact on productivity and marketing.
  • The analysis was based on period-specific data, which limits the possibility of capturing seasonal variations or long-term changes in farming practices and soil conditions.

5.2. Recommendations for Future Studies

  • Implement training programs aimed at cocoa producers, especially in the province of Los Ríos, to improve access to and use of digital platforms, technical publications and agricultural information networks.
  • Promote producer associations and cooperatives that facilitate the exchange of information and successful experiences in the marketing and management of the crop.
  • Promote the use of periodic soil analysis and technical advice to adjust fertilization practices according to the specific needs of the crop.
  • Develop awareness and practical training strategies that facilitate the progressive adoption of new technologies in cocoa production. This includes access to technical advice in the field and the integration of accessible digital solutions for small producers.

Author Contributions

Conceptualization, I.S.B.V. and J.F.G.V.; formal analysis, L.E.S.G.; investigation, J.D.V.C.; methodology, I.S.B.V., J.F.G.V., J.D.V.C. and L.E.S.G.; writing—original draft, I.S.B.V., J.F.G.V., J.D.V.C. and L.E.S.G.; writing—review and editing, I.S.B.V. and J.F.G.V. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by an Universidad Estatal de Milagro (UNEMI) scholarship.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors are grateful to Universidad Estatal de Milagro (UNEMI).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Characterization of cocoa production 2023. Data source: Ministerio de agricultura y ganaderia [17].
Figure 1. Characterization of cocoa production 2023. Data source: Ministerio de agricultura y ganaderia [17].
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Figure 2. Fertilization of cocoa areas in Ecuador. Data source: [17].
Figure 2. Fertilization of cocoa areas in Ecuador. Data source: [17].
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Figure 3. Conceptual framework on digital marketing influence. Source: adapted from [31].
Figure 3. Conceptual framework on digital marketing influence. Source: adapted from [31].
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Figure 4. Research model.
Figure 4. Research model.
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Figure 5. Study area.
Figure 5. Study area.
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Figure 6. Representative scheme of the non-probabilistic sampling procedure. SSH: smallholder farmers.
Figure 6. Representative scheme of the non-probabilistic sampling procedure. SSH: smallholder farmers.
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Figure 7. Structure of the schematization of the dimensions used in this research.
Figure 7. Structure of the schematization of the dimensions used in this research.
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Figure 8. Relationship between information dimensions and economic and social indicators. Note: (A) Relationship of information dimensions and information evaluation with the economic dimension. (B) Relationship of information dimensions and information evaluation with the social dimension.
Figure 8. Relationship between information dimensions and economic and social indicators. Note: (A) Relationship of information dimensions and information evaluation with the economic dimension. (B) Relationship of information dimensions and information evaluation with the social dimension.
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Table 1. Conceptualization factors for indicators of smallholder information behavior.
Table 1. Conceptualization factors for indicators of smallholder information behavior.
DimensionIndicatorNomenclatureDescription
Sources of
information
Print publicationsSI1Use of printed media as a source of agricultural information.
Digital and electronic platformsSI2Use of electronic tools to obtain information
Use of advanced information search techniquesSI3Ability to use specialized methods for locating specific information
Evaluation
of information
Reliability and quality of sources consultedEI1Criteria for selecting reliable high-quality sources
Constant updating of the data obtainedEI2Frequency with which information is renewed and updated
Identification of prominent authors in the sectorEI3Recognizing and following experts or opinion leaders
InformativeDetection and recognition of specific information needsDI1Type of information needed according to the demand of the production environment.
Ability to locate and access relevant informationDI2Effectiveness in the search for information
Participation in various marketsDI3Diversification of markets
SocialPrice optimization in commercializationDS1Maximization of economic benefit according to market conditions.
Strengthening of entrepreneurial and social capacitiesDS2Development of entrepreneurial and social interaction skills
Effective interaction and communication with other stakeholdersDS3Exchange of information with stakeholders such as buyers, suppliers and other producers.
EconomicIncreased autonomy in agricultural trade strategiesDE1Independent decision-making in marketing processes
Establishment of commercial infrastructureDE2Use of facilities or structures to strengthen business activities
Expanded access to alternative marketsDE3Diversification of markets into new sectors
Encouraging investment in agricultural activitiesDE4Reinvestment of producers in their activities
Table 2. Characteristics of small cocoa farmers.
Table 2. Characteristics of small cocoa farmers.
CategoryFactorFrequencyProportion (%)
GenderMale10670.67
Female4429.33
Age18–252818.67
26–353120.67
36–452718.00
46–553825.33
>562617.33
Education levelNo education2214.67
Primary2114.00
Secondary4630.67
Third level3221.33
Technologist2919.33
Experience in agriculture (years)1–53120.67
6–102919.33
11–152416.00
16–203422.67
>203221.33
Residence in the province (years)1–51812.00
6–102617.33
11–153322.00
16–203624.00
>203724.67
Planted area (ha)0.5–33624.00
4–62315.33
6–83020.00
8.5–103322.00
>102818.67
Planted cocoa varietyNational5536.67
CCN-514932.67
Both4630.67
Table 3. Performance points of information capabilities and their relevance to business strategies.
Table 3. Performance points of information capabilities and their relevance to business strategies.
IndicatorsStakeholder Group
PPGPPLR
Print publications3.282.72
Digital and electronic platforms3.112.95
Use of advanced information search techniques2.612.97
Reliability and quality of sources consulted3.032.89
Constant updating of the data obtained2.893.04
Identification of prominent authors in the sector2.922.99
Detection and recognition of specific information needs3.252.91
Ability to locate and access relevant information3.053.01
Participation in various markets3.053.03
Price optimization in commercialization3.172.85
Strengthening of entrepreneurial and social capacities3.042.80
Effective interaction and communication with other stakeholders3.032.81
Increased autonomy in agricultural trade strategies3.002.96
Establishment of commercial infrastructure3.163.00
Expanded access to alternative markets3.122.89
Encouraging investment in agricultural activities3.374.84
Note: PPG: small farmers in the province of Guayas; PPLR: small farmers in the province of Los Ríos.
Table 4. Results of chemical analysis of soils carried out in different cocoa plantations at the microscale level.
Table 4. Results of chemical analysis of soils carried out in different cocoa plantations at the microscale level.
ParameterSoil Fertility
Guayas Los Ríos
pH6.39 ± 0.746.08 ± 0.93
Organic Matter (MO)4.53 ± 1.304.50 ± 1.14
Total Nitrogen (N) 0.33 ± 0.100.32 ± 0.10
Exchangeable Potassium 0.33 ± 0.110.34 ± 0.11
Calcium (Ca) [cmol(+)/L]17.79 ± 0.7417.77 ± 0.68
Magnesium (Mg) [cmol(+)/L]3.03 ± 1.022.98 ± 1.13
Available Phosphorus (P) (mg/L)118.20 ± 1.15118.09 ± 1.01
Cadmium (Cd) (mg/kg)0.06 ± 0.020.06 ± 0.03
Exchangeable Aluminum (Al) [cmol(+)/L]0.34 ± 0.120.68 ± 0.46
Copper (Cu) (mg/L)2.16 ± 1.352.02 ± 1.38
Iron (Fe) (mg/L)5.25 ± 0.674.94 ± 1.72
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Burgos Villamar, I.S.; Solís Granda, L.E.; Guevara Viejó, J.F.; Valenzuela Cobos, J.D. Analysis of the Impact of Information Behavior on the Marketing and Fertilization Strategies of Small Cocoa Producers in the Provinces of Guayas and Los Ríos in Ecuador. Agriculture 2025, 15, 858. https://doi.org/10.3390/agriculture15080858

AMA Style

Burgos Villamar IS, Solís Granda LE, Guevara Viejó JF, Valenzuela Cobos JD. Analysis of the Impact of Information Behavior on the Marketing and Fertilization Strategies of Small Cocoa Producers in the Provinces of Guayas and Los Ríos in Ecuador. Agriculture. 2025; 15(8):858. https://doi.org/10.3390/agriculture15080858

Chicago/Turabian Style

Burgos Villamar, Ivonne Soraya, Luis Eduardo Solís Granda, Jorge Fabricio Guevara Viejó, and Juan Diego Valenzuela Cobos. 2025. "Analysis of the Impact of Information Behavior on the Marketing and Fertilization Strategies of Small Cocoa Producers in the Provinces of Guayas and Los Ríos in Ecuador" Agriculture 15, no. 8: 858. https://doi.org/10.3390/agriculture15080858

APA Style

Burgos Villamar, I. S., Solís Granda, L. E., Guevara Viejó, J. F., & Valenzuela Cobos, J. D. (2025). Analysis of the Impact of Information Behavior on the Marketing and Fertilization Strategies of Small Cocoa Producers in the Provinces of Guayas and Los Ríos in Ecuador. Agriculture, 15(8), 858. https://doi.org/10.3390/agriculture15080858

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