The Impact of Social Media on the Purchase Intention of Organic Products

Abstract

The main objective of this study was to assess whether social media directly influences purchase intention and how it indirectly influences key psychological determinants, such as environmental attitude, subjective norms, and perceived behavioral control, based on the Theory of Planned Behavior. A quantitative, cross-sectional, and correlational approach was adopted, with data collected through surveys of 430 people in Guayaquil, Ecuador, using a 5-point Likert scale. Reliability was tested using Cronbach’s alpha, while data analysis employed confirmatory factor analysis and structural equation modeling using SPSS 24 and AMOS 24. The results indicate that social media does not directly affect purchase intention but significantly influences environmental attitudes, subjective norms, and perceived behavioral control; consequently, these factors positively affect purchase intention. This study contributes to the literature by highlighting the indirect role of social media in shaping green purchasing behavior, suggesting that marketing strategies should focus on improving consumer attitudes, social support, and accessibility to organic products.

1. Introduction

Social media (SM) has emerged as one of the most influential communication tools in the digital age [1]. Since the launch of platforms such as Facebook in 2004, its exponential growth has facilitated new forms of interaction and information consumption [2]. In consumer behavior research, SM contact has transformed how individuals discover, evaluate, and purchase products [3]. The ability to share opinions, reviews, and experiences has created a digital environment in which brands can connect directly with their audiences [4]. This constant interaction has positioned SM as a key channel in shaping Purchase Intentions (PIs), particularly for products with associated values, such as organic products [5]. However, although SM increasingly influences purchasing decisions, its impact on ecological consumption remains to be investigated. Xie et al. [6] highlighted how these platforms have transformed the ecological market and consumer perceptions. Therefore, they suggested that future studies should analyze the impact of SM on ecological PIs. Additionally, Hu et al. [3] stated that the research gap lies in understanding how marketing strategies disseminated through SM contact can influence environmental concerns and, consequently, the intention to purchase products associated with environmental protection.

Simultaneously, environmental degradation has caused concerns regarding the negative effects of conventional consumption [7]. Pollution from industrial agriculture, the excessive use of agrochemicals, and deforestation have prompted the search for more sustainable alternatives [8]. Organic products have emerged in response, and are characterized by environmentally responsible practices and a reduced ecological footprint [9,10]. Their adoption stems from both environmental and health benefits. However, the transition to sustainable consumption relies heavily on consumer perception and PIs, which are areas where SM contact can play a crucial role by raising awareness and educating consumers on organic product advantages [11,12].

Theory of Planned Behavior (TPB) is one of the most widely applied theoretical frameworks [13]. This theory posits that an individual’s intention to perform a behavior is determined by three key factors: Attitude, Subjective Norms (SNs), and Perceived Behavioral Control (PBC) [14]. In this context, Environmental Attitude (EA) refers to an individual’s positive or negative evaluation of a specific behavior [10]. SNs reflect perceived social pressure to perform the behavior [7], whereas PBC refers to the perceived ease or difficulty of performing the behavior [8]. Together, these elements shape PI, allowing a structured analysis of the role that the SM plays in the formation of such intentions [15].

SM has become integral to consumer preferences as it shapes purchase decisions, brand perceptions, and interactions between companies and consumers. According to the Digital 2022 Global Overview Report [16], Ecuador’s population reached 18.28 million in 2024, with 17.56 million active mobile connections, representing 96% of the population. Furthermore, 12.66 million Ecuadorians use SM, equivalent to 69.2% of the population. TikTok users total 14.2 million, Instagram 6.8 million, Facebook 13.6 million, LinkedIn 4.5 million, and X (Twitter) 3.5 million [17]. These scenarios illustrate the pervasive impact of digital platforms on Ecuadorians’ daily lives, underscoring the need for future research on the influence of SM on organic product consumption [18].

Given this context, this study aimed to determine the influence of SM on the PI of organic products. The main research question was the following: what is the impact of SM on the PIs of organic products in Ecuador? Additionally, to contribute empirical evidence from a country where research on organic product PIs is scarce, this study seeks to answer the following sub-questions: (a) What is the impact of EA, SN, and PBC on the PIs of organic products? (b) What is the impact of SM on the PIs of organic products? (c) What is the impact of SM on EA, SN, and PBC on consumers?

This paper is organized into eight sections. Section 1 introduces the study and contextualizes the research problem, questions, and objectives. Section 2 reviews the literature, focusing on prior studies of the influence of SM contact on consumer behavior and the application of TPB to green consumption. Section 3 outlines the research methodology, detailing the research design, data collection, and the analytical approach. Section 4 presents the results, followed by Section 5, which discusses the findings in relation to theory and prior studies. Section 6 summarizes the main conclusions and addresses the theoretical, practical, and social implications of the study. Finally, it discusses the limitations and future research directions. This comprehensive approach provides valuable insights into the impact of SM contact on green PIs and contributes knowledge to academics, businesses, and policymakers.

2. Literature Review

2.1. Theory of Planned Behavior

The Theory of Planned Behavior (TPB) has been extensively applied in green consumption studies because of its capacity to predict PIs based on psychological and social factors [19]. This theory has been employed in numerous studies to construct hypothetical models that explain consumer behavior regarding organic product purchases [7,8]. Prior research has demonstrated that EA, influenced by the perception of environmental and health benefits, is a key determinant of PIs [13,20,21]. Likewise, SNs, such as the influence of family and friends, reinforce consumers’ predisposition toward organic products [19,22]. Additionally, studies have shown that PBC, which refers to the ease with which consumers can access organic products, plays a crucial role in the realization of purchases [23]. These dimensions have been validated across various cultural and economic contexts, providing empirical evidence supporting the applicability of the TPB in the study of sustainable consumption [24,25]. This demonstrates that the TPB is the most appropriate theoretical framework to support the hypothetical model proposed in this study.

2.2. Environmental Attitude and Purchase Intention

EA is a psychological construct that reflects an individual’s overall evaluation of an object, person, or situation. According to Ajzen [14], EA is defined as a psychological tendency expressed by evaluating a particular entity with some degree of favorability or unfavorability. In the context of organic product consumption, an individual’s EA towards these products can significantly influence their purchasing behavior [10]. For example, individuals who positively value the health and environmental benefits associated with organic products are more likely to purchase them [26,27].

Assessing EA is essential in studies seeking to understand organic product purchase behavior, as this variable acts as a significant predictor of PI. Research has shown that a positive attitude toward organic products is associated with a higher intention to purchase. For instance, Palomino and Barcellos [10] found that favorable attitudes toward organic foods directly influence consumers’ PI [5,8]. Understanding consumer attitudes enables businesses and marketing professionals to design more effective strategies to promote these products by addressing misconceptions and highlighting benefits, such as in health and environmental sustainability.

Several studies have found that consumers with strong environmental awareness and positive attitudes toward sustainability exhibit a greater PI for organic products [13,21]. For example, within the Ecuadorian context, several studies have found that a positive EA is significantly associated with PI for organic products [7,8,21,28,29]. This is because consumers perceive that choosing organic products contributes to environmental conservation and personal well-being [26]. Given that fostering positive EA among consumers can be an effective strategy to increase the demand for organic products, this study proposes the following hypothesis:

H1. 

Environmental attitudes influence the purchase intention of organic products.

2.3. Subjective Norms and Purchase Intention

The SN is a fundamental concept for understanding consumer behavior, particularly within the TPB framework [10]. Ajzen [14] defined SN as the perceived social pressure to perform a specific behavior. This includes an individual’s perception of whether important referents, such as family, friends, or society in general, expect them to engage in a particular action [30]. Similarly, Islam et al. [31] described a SN as the perception that most people who are important to an individual believe they should or should not perform the behavior in question. These definitions underscore the influence of social expectations on personal decision-making processes [20,23].

Analyzing SN is crucial in studies aimed at identifying organic product purchase behavior [10]. Several investigations have indicated that SNs significantly influence the PI for organic foods [7,8,12,20,21]. For example, Islam and Khan [31] found a positive correlation between SNs and PI in organic foods. This suggests that, when individuals perceive that their loved ones value and expect the consumption of organic products, they are more likely to develop a stronger intention to purchase such items [32].

SNs can interact with other factors such as EA and PBC to shape PI [29]. For instance, individuals with positive attitudes toward organic products and who perceive strong social support for their consumption are more likely to have PI for these products [33]. However, some studies contradict this finding, finding that a SN does not always exert pressure on the PI [34,35]. Considering the contradictions in the literature, this study emphasizes the importance of analyzing SNs alongside other determinants in comprehensive consumer behavior models and proposes the following hypothesis:

H2. 

Subjective norms influence the intention to purchase organic products.

2.4. Perceived Behavioral Control and Purchase Intention

PBC posits that human action is guided by three types of consideration: behavioral beliefs, normative beliefs, and control beliefs [6,36]. PBC refers to an individual’s perception of the ease or difficulty of performing a particular behavior, reflecting both past experiences and anticipated obstacles [30]. Ajzen [14] defined PBC as “the perceived ease or difficulty of performing the behavior” and suggested that it is determined by the total set of accessible control beliefs. These control beliefs refer to the presence of factors that may facilitate or impede behavioral performance [33].

Analyzing PBC is crucial for understanding purchase behavior in the context of organic product consumption. Research indicates that PBC significantly influences the PI of organic products [37,38]. For example, Hoyos et al. [23] reported a positive correlation between PBC and PI in organic foods. This suggests that when individuals perceive greater control over purchasing organic products (owing to factors such as availability, affordability, or sufficient knowledge), they are more likely to form a strong PI [13,14,24,29]. Therefore, evaluating PBC can provide valuable insights into the barriers and facilitators that consumers face, allowing the development of strategies to improve organic product consumption [23].

By identifying factors that enhance consumers’ sense of control, marketers and policymakers can design initiatives to strengthen consumer PBC [30]. This, in turn, can lead to increased PI and actual buying behavior related to organic products [7,23]. Thus, PBC serves as a critical lever for promoting sustainable consumption choices [39]. Based on this, this study proposes the following hypothesis:

H3. 

Perceived behavioral control influences purchase intention for organic products.

2.5. Social Media and Its Influence on Purchase Intention, Environmental Attitude, Subjective Norms, and Perceived Behavioral Control

SM has become an integral part of modern communication, influencing various aspects of daily life, including consumer behavior [40]. Hu et al. [3] defined SM as “a network of individuals (such as friends, acquaintances, and colleagues) connected through interpersonal relationships.” In the digital context, Li et al. [4] describe SM as “websites and applications that enable users and organizations to connect, communicate, share information, and form relationships”. These platforms facilitate the exchange of information, ideas, and interests among users, shaping perceptions and behaviors [41].

Analyzing the role of SM is crucial in studies aimed at understanding the purchase behavior of organic products [5]. SM platforms serve as important channels through which consumers gather information, form perceptions, and make purchase decisions regarding organic products [42]. Li et al. [4] found that SM discussions have led consumers to shift toward organic products, especially following health concerns during the pandemic. This underscores the importance of SM in shaping consumer preferences and highlights the need for researchers to consider these platforms when examining the factors that influence organic product consumption [43].

SM influences consumers’ PI for organic products by affecting key psychological determinants such as EA, SN, and PBC [44]. Participation in SM directly affects consumer awareness, perceptions, and attitudes toward organic products [40]. Positive information and recommendations shared within these networks can enhance favorable attitudes toward organic consumption [45]. Moreover, the prevalence of organic product discussions and recommendations on SM can establish norms, making individuals feel that purchasing organic products is a socially accepted and expected behavior [46]. SM can also increase PBC by providing consumers with information on where and how to buy organic products, reducing perceived barriers, and facilitating the purchasing process [4]. Considering the above, this study seeks to test the following hypotheses:

H4. 

Social Media influences the purchase intention of organic products.

H5. 

Social Media influence consumers’ environmental attitudes.

H6. 

Social Media influences consumers’ subjective norms.

H7. 

Social Media influences consumers’ perceived behavioral control.

Although previous studies have attempted to determine the influence of SM on green PIs through mediating factors [5,47], there is a lack of research examining whether the three mediating constructs of the TPB mediate the relationship between SM and the intention to purchase organic products. In this regard, a literature review identified only one study indicating that SN and PBC mediate the relationship between SM and PI [40]. Given the limited research on SM’s influence on organic product consumers in Ecuador, understanding these dynamics is vital for researchers and marketers aiming to effectively promote organic consumption. Therefore, this study proposes the following hypotheses:

H8. 

Environmental Attitude mediates the relationship between social media and purchase intention for organic products.

H9. 

Subjective norms mediates the relationship between social media and purchase intention for organic products.

H10. 

Perceived behavioral control mediates the relationship between social media and purchase intention for organic products.

2.6. Research Model

In order to facilitate the understanding of the hypothesis formulation described above, Figure 1 is presented below, showing the research model tested in the present study.

3. Method

3.1. Instrument Design and Data Collection

This study adopted a quantitative correlational methodology with a cross-sectional design. Data collection was carried out through a self-administered paper survey administered in person to undergraduate and master’s degree university students in Guayaquil, Ecuador. The survey consisted of 20 questions measured using a 5-point Likert scale. The items were developed based on bibliographic references from academic articles on sustainable consumption (Appendix A).

To ensure the validity and reliability of the measurement instrument, the survey was reviewed by a panel of experts comprising marketing and research specialists that validated the proposed items. A pilot test was conducted with 25 participants to evaluate the clarity and relevance of the questions. A probabilistic sampling approach was employed, resulting in the voluntary participation of 430 participants.

3.2. Internal Consistency of the Instrument

Following the survey administration, the internal consistency of the instrument was assessed using statistical procedures based on recent studies of green consumption [6,8,10,48]. First, the instrument’s reliability was evaluated using Cronbach’s alpha test. The initial results indicated the need to remove four items because of their low factor loadings, which weakened the predictive power of the constructs (EA4, SN1, PBC1, and SM2). Consequently, the questionnaire was reduced to 16 items for statistical analysis. Cronbach’s alpha was then recalculated, yielding a value of 0.824, which confirmed the instrument’s adequate internal consistency.

3.3. Data Analysis

To validate the data obtained in this study, a Confirmatory Factor Analysis (CFA) was initially performed to assess the convergent and discriminant validity of the hypothesized model. Regarding convergent validity, the factor loadings of the indicator variables were calculated, followed by the Composite Reliability (CR) and Average Variance Extracted (AVE) for the model constructs. For discriminant validity, the square root of the AVE (SRAVE) was compared with the correlation values among the constructs. Excel and SPSS 24 were used for these calculations.

The acceptance or rejection of the hypotheses was determined through the implementation of structural equation modeling (SEM) using AMOS 24 software. Multiple fit indices were employed to ensure the model’s adequacy, including the chi-square value relative to the degrees of freedom (χ²/df), Goodness-of-Fit Index (GFI), Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), and Normed Fit Index (NFI). The Mean Squared Residual (MSR) and Root Mean Square Error of Approximation (RMSEA) were subsequently calculated, and AMOS 24 software was used for all statistical analyses.

4. Results

4.1. Demographic Analysis

Demographic data reflect the composition of a sample drawn from the Guayaquil population: 64% were undergraduate students and 36% were master’s students. Of the respondents, 35% were between the ages of 23 and 28, followed by 30% in the 29–34 age range. This indicates that the majority belonged to the young adult stage, a demographic segment characterized by high engagement with SM contact, particularly on platforms such as Instagram, TikTok, and Twitter. Additionally, 14% of the sample fell within the 35–44 age range, a group that also participated actively in SM but with a greater presence on platforms such as Facebook and LinkedIn. Further, 10% of respondents were aged between 44 and 55 years, while 3% were over 55 years old. These older segments tend to use SM less frequently and demonstrate a preference for more traditional platforms, such as Facebook and WhatsApp. Moreover, 8% of the sample consisted of individuals under 23 years of age, a segment characterized by high digital consumption and a marked preference for video content on platforms such as TikTok and YouTube.

Regarding gender distribution, 57% of the respondents were women, while 43% were men, indicating a slight predominance of female participants in the sample. Overall, the data revealed a concentration of individuals within the youth and young adult segments, suggesting a high level of SM interaction. This demographic profile represents a key opportunity for developing targeted digital marketing strategies.

Table 1. Demographic characteristics.

Characteristics.	Category	n	%
City	Guayaquil	430	100%
Education Level	Undergraduate	275	64%
	Master’s degree	155	36%
Age	Under 23 years old	35	8%
	Between 23 and 28 years old	150	35%
	Between 29 and 34 years old	130	30%
	Between 35 and 44 years old	59	14%
	Between 45 and 55 years old	41	10%
	Over 55 years old	15	3%
Gender	Female	247	57%
	Male	183	43%

presents the demographic characteristics of the participants.

4.2. Measurement Model Estimation

The measurement model, comprising five constructs (EA, SN, PBC, SM, and PI), was assessed through confirmatory factor analysis (CFA). To determine the reliability of the instrument and convergent validity of the model, the following minimum thresholds were applied: Cronbach’s alpha (CA) ≥ 0.7, Composite Reliability (CR) ≥ 0.7, and Average Variance Extracted (AVE) ≥ 0.5 [49,50,51]. Both the CA and CR values exceeded the 0.70 threshold, while the AVE for each construct was greater than 0.50 and lower than its respective CR, in accordance with the recommendations in the literature [52,53]. See

Table 2. Convergent validity.

Variable	Item	Loading Factor	CA	CR	AVE
EA	EA1	0.955	0.943	0.948	0.860
	EA 2	0.916
	EA 3	0.911
SN	SN 2	0.945	0.932	0.938	0.835
	SN 3	0.871
	SN 4	0.924
PBC	PBC2	0.906	0.881	0.938	0.835
	PBC 3	0.783
	PBC 4	0.884
SM	RS1	0.866	0.825	0.864	0.680
	RS3	0.862
	RS4	0.739
PI	PI1	0.696	0.857	0.889	0.670
	PI2	0.911
	PI3	0.730
	PI4	0.913
Total CA	0.824

.

To assess the discriminant validity of the model, bivariate correlation values between the constructs of the hypothesized model were initially calculated, followed by the calculation of the Square Root of each AVE value (SR AVE). The discriminant validity of the model was confirmed when the SR AVE values were greater than the correlation values between each pair of constructs [49,50,51,53]. For further details, see

Table 3. Discriminant validity.

	EA	SN	PBC	SM	PI	SR AVE
EA	0.860					0.927
SN	0.135 **	0.835				0.913
PBC	0.238 **	0.173 **	0.670			0.818
SM	0.220 **	0.193 **	0.291 **	0.739		0.859
PI	0.105 *	0.224 **	0.137 **	0.483	0.680	0.824

**. The correlation is significant at the 0.01 level (two-tailed) *. The correlation is significant at the 0.05 level (two-tailed).

.

4.3. Structural Equation Modeling

After assessing the convergent and discriminant validity of the research model, a Structural Equation Model (SEM) was constructed to validate the study hypotheses. The results obtained through the maximum-likelihood estimation in AMOS 24 reflected satisfactory fit indices: χ² (df) = 132.704 (96), χ²/df = 1.382, NFI = 0.978, TLI = 0.992, CFI = 0.994, RMSEA = 0.030; * p < 0.05; *** p < 0.001. When examining the relationships between the five variables of the hypothesized model and considering the significance levels (p < 0.05), six hypotheses were accepted, and one was rejected.

The findings of this study indicated that EA (β = 0.112; p < 0.05), SN (β = 0.124; p < 0.05), and PBC (β = 0.154; p < 0.05) significantly influenced PI. While SM (β = 0.154; p > 0.05) did not directly influence PI, it did influence EA (β = 0.406; p < 0.05), SN (β = 0.277; p < 0.05), and PBC (β = 0.245; p < 0.05).

Table 4. Hypothesis test result.

Hypothesis	Relationship	β	p-Values	Hypothesis
H1	EA-PI	0.112	***	Accepted
H2	SN-PI	0.124	0.039	Accepted
H3	PBC-PI	0.154	***	Accepted
H4	SM-PI	0.128	0.19	Rejected
H5	SM-EA	0.406	0.01	Accepted
H6	SM-SN	0.277	***	Accepted
H7	SM-PBC	0.245	***	Accepted
H8	SM-EA-PI	0.259	***	Accepted
H9	SM-SN-PI	0.201	***	Accepted
H10	SM-PBC-PI	0.199	***	Accepted

Note(s): Goodness-of-fit indices: χ² (gl) = 132,704 (96), χ²/g = 1382, NFI = 0.978, TLI = 0.992, CFI = 0.994, RMSEA = 0.030; *** p < 0.001.

presents the values of these relationships.

5. Discussion

To facilitate a comprehensive understanding of the study’s findings, the discussion is structured around addressing the following research sub-questions: (a) What is the impact of EA, SNs, and PBC on the PI of organic products? (b) What is the impact of SM on the PI of organic products? (c) What is the impact of SM on EA, SNs, and PBC?

5.1. Impact of EA, SN, and PBC on the PI of Organic Products

The results confirmed that EA significantly influenced the PI for organic products, leading to the acceptance of H1. This finding reinforces prior empirical evidence that EA is a key determinant of consumers’ purchasing decisions [10,26,27]. This aligns with the existing literature, which consistently highlights that consumers with strong environmental awareness prefer sustainable products, viewing their purchases as an effective means of reducing environmental impact and contributing to planetary conservation [5,8]. Moreover, environmental protection remains a pivotal criterion in product selection, as ecologically conscious consumers aim to minimize environmental pollution through their consumption habits [7,21,29]. Thus, the preference for organic products reflects not only a market trend but also a consumer commitment to sustainability [26,28].

Additionally, the study confirmed that SN significantly influences the PI for organic products, supporting H2. This finding aligns with empirical evidence that SN is a critical factor in sustainable PI [10,30,33]. The results support the existing literature, indicating that the influence of colleagues, friends, family, and social pressure plays a fundamental role in consumers’ decisions, as perceived social approval can reinforce their inclination toward organic products [20,23,31]. Among consumers with a strong environmental identity, recommendations from their social circle can be decisive as they seek to prevent environmental degradation and align their consumption patterns with ecological values [7,8,9,21]. However, this finding contrasts with those of some studies suggesting that SNs do not always exert direct pressure on PI, implying that organic product purchase decisions may be more closely tied to other personal factors [34,35]. This divergence in the literature highlights that SNs’ influence may vary depending on cultural and social contexts, underscoring the need for further research to better understand their impact across different markets and consumer segments.

Furthermore, the study confirmed that PBC significantly influences the PI of organic products, leading to the acceptance of H3. This result corroborates prior empirical evidence indicating that an individual’s perception of the ease or difficulty of performing a behavior directly affects their intention to undertake it [36,39]. In the context of organic product consumption, product availability and affordability can either facilitate PI or become barriers limiting it [7]. Supporting previous studies, this research shows that when consumers perceive organic products as readily available and competitively priced, their PI increases significantly [8,23,37,38], emphasizing that accessibility is crucial for fostering responsible and sustainable consumption habits [33]. Additionally, consumers with a strong environmental orientation perceive purchasing organic products as a tangible way to contribute to environmental protection and to reduce their ecological footprint [13,14,24,29]. However, when the perceived difficulty of acquiring such products is high, PI decreases, highlighting the need for strategies to improve access and availability [30].

5.2. Impact of SM on PI of Organic Products

The statistical results revealed that SM contact does not directly influence the PI for organic products, leading to the rejection of H4. This finding suggests that despite the growing presence of brands on social platforms, the data show that SM interactions do not directly affect consumers’ purchasing decisions. This result contradicts previous research indicating that SM influences PI [5,44,54,55], and that interactions on these platforms encourage consumers to increase their PI [56,57].

As the study results demonstrated that SM does not have a direct influence on the intention to purchase organic products, statistical analyses revealed that this relationship is fully mediated by EA, SN, and PBC. Accordingly, hypotheses H8, H9, and H10 are supported, indicating that exposure to SM content alone does not directly drive ecological PI, but rather does so through how consumers perceive and process information. Specifically, EA plays a crucial role in shaping positive perceptions of organic products [5,8,10], SNs reinforce social influence and normative pressure to adopt more sustainable consumption behaviors [29,31,36], and PBC enhances self-efficacy and the perceived feasibility of making such purchases [6,30,36].

These findings highlight the importance of SM marketing strategies that not only inform but also strengthen consumer beliefs, values, and perceptions of control to drive behavioral change. In this regard, the selection of EA, SN, and PBC as mediating variables is grounded in the well-established framework of the TPB [23,24,25,33,39,48], demonstrating that PI is not formed in isolation but is shaped by key psychological determinants. Prior research has shown that SM interactions influence consumer behavior through cognitive and social mechanisms rather than exerting a direct impact on PI [47]. However, by integrating mediating variables into the hypothesized model, this study extends the theoretical understanding of how digital engagement contributes to sustainable consumer behavior. It demonstrates that EA captures the cognitive–affective dimension of consumer perceptions, shaping how individuals evaluate organic products in light of sustainability concerns [7,13,21,28,29]. Meanwhile, SN reflects the influence of social endorsement and peer expectations, which are amplified in digital environments where social validation plays a fundamental role [12,20,21,23,31,32]. Finally, PBC accounts for the practical considerations and perceived feasibility of purchasing organic products, an aspect heavily influenced by the accessibility of information [6,30,33,37,38].

5.3. Impact of SM on EA, SN, and PBC

This study confirms the acceptance of H5, indicating that SM contact plays a significant role in shaping EA. Exposure to informational content, shared experiences, and persuasive messages about sustainability fosters a more positive perception of environmentally friendly practices among users [58,59]. Although this influence does not directly translate into PI, it strengthens EA and creates a favorable predisposition toward responsible consumption, which may generate indirect effects on future purchasing decisions [60,61].

Similarly, this study supported H6, demonstrating that SM contact influences the perception of SNs regarding sustainable consumption. In digital environments, the opinions and behaviors of friends, family, and communities act as key references for shaping social expectations of responsible consumption [48]. This effect reinforces perceived social pressure to adopt environmentally conscious behaviors [40,59,61], although it does not necessarily lead to immediate PI for organic products [34,35]. While SM contact does not directly impact PI, this study shows that SNs can strengthen the perception of social approval for these practices, creating a normative framework that may influence medium- to long-term purchasing decisions [46,54].

Finally, the study confirmed H7, demonstrating that SM affects PBC in the context of organic product consumption. By disseminating information on the availability of organic products, responsible consumption strategies, and other consumer experiences, SM users develop a greater sense of capability and autonomy to adopt such practices [40,44,54]. Although this increased perception of control does not directly translate into PI, it reduces perceived barriers [48] and facilitates an environment in which adopting sustainable behaviors becomes more feasible and accessible over time [4].

6. Conclusions

The results from the study reveal that although SM contact does not directly influence the PI of organic products, it plays a fundamental role in shaping the psychological factors that determine it. In this regard, this research demonstrates that SM significantly impacts all three factors (EA, SN, and PBC), strengthening consumers’ favorable predisposition toward organic product consumption.

The influence of SM on EA is evident because exposure to informational content and shared experiences allows users to develop a more positive perception of sustainability and responsible consumption. Similarly, SNs are reinforced in digital environments where social validation and peer pressure can consolidate a favorable predisposition toward organic product purchases. In addition, SM enhances PBC by providing key information on product availability and benefits. Nonetheless, the absence of a direct connection to PI suggests that these influences are necessary but not sufficient to drive immediate purchasing decisions.

The findings of this study must be interpreted within the cultural and economic context of Ecuador, an emerging economy where consumers’ purchasing decisions are influenced by distinct regional factors. Ecuador’s organic market is still in a developmental phase, with accessibility, habits, pricing, and consumer awareness playing crucial roles in shaping PI. Unlike studies conducted in developed economies, where organic consumption is often driven by deeply embedded environmental values and regulatory incentives, Ecuadorian consumers may face structural barriers such as limited availability, higher costs, and lower exposure to sustainability campaigns. Additionally, the strong influence of SNs found in this study may be a reflection of Latin American collectivist cultures, where social validation and peer influence significantly shape consumer behavior. These regional dynamics align with findings from studies in other emerging economies, such as India and Indonesia [9,13,20], where social endorsement and perceived feasibility of purchasing organic products also mediate PI. However, they contrast with research in Western contexts, where individual EA tends to have a stronger direct effect on green purchasing behavior [18,33]. Given these contextual differences, the generalization of the findings should consider how economic and cultural structures influence the role of SM and psychological determinants in sustainable consumption.

In conclusion, although SM contact does not directly determine the PI of organic products in Ecuador, it plays an essential role in creating the conditions that facilitate it. Its impact on EA, SNs, and PBC suggests that these platforms can serve as strategic tools for strengthening consumer education and environmental awareness. However, it is crucial to complement SM strategies with more direct marketing approaches such as economic incentives, improved product availability, and persuasive campaigns that reduce perceived barriers.

6.1. Theoretical, Practical, and Social Implications

From a theoretical perspective, this study contributes to the field of consumer behavior and digital marketing by demonstrating that SM engagement does not directly influence the PI of organic products. Unlike previous studies that have explored the direct impact of SM on PI through the TPB, this research offers a distinctive perspective by showing that this influence is not direct but fully mediated by the psychological variables of the TPB. In this regard, the study’s findings indicate that exposure to SM content does not directly foster PI for organic products; rather, this relationship only materializes when SM alters consumers’ underlying perceptions and beliefs. This theoretical distinction is crucial, as it not only reinforces the validity of the TPB in the context of organic product consumption but also redefines the role of SM as an indirect persuasion channel, where behavioral change does not occur immediately but through the progressive transformation of EA, SNs, and PBC.

From a practical point of view, the results suggest that SM strategies should focus on enhancing positive attitudes toward organic products, creating favorable social norms, and improving perceptions of accessibility. Rather than solely emphasizing direct promotion, brands can leverage consumer testimonials and educational content to reinforce their environmental awareness and social validation. Additionally, businesses should pair these digital strategies with practical measures such as expanding distribution channels, improving product availability in physical and online stores, and offering competitive prices or purchasing incentives.

Finally, from a social perspective, the findings highlight the potential of SM as a tool to promote sustainable consumption, although it has limitations in converting intention into action. This implies that environmental awareness campaigns must extend beyond SM and should be complemented by environmental education in schools, government incentives, and regulations that promote the production and accessibility of organic products. Moreover, this study reinforces the importance of social influence in purchasing decisions, indicating that community initiatives, responsible consumption networks, and loyalty programs can support the transition to more sustainable consumption patterns in Ecuador.

6.2. Limitations and Recommendations for Future Research

This study has several limitations. First, the sample focused exclusively on consumers from Guayaquil, restricting the generalizability of the findings to the national level or other sociocultural contexts within Ecuador. Additionally, the research design was cross-sectional, preventing analysis of how perceptions and PI evolve over time. Finally, as the study relied on self-administered surveys, the results may have been subject to self-reporting and social desirability biases, potentially affecting response accuracy.

To address these limitations, future research should expand the sample to the national level and conduct comparative studies across different regions in Ecuador. Longitudinal studies are also suggested to observe changes in PI over time and assess the cumulative impact of SM. Combining quantitative and qualitative methodologies, such as interviews or focus groups, can offer deeper insights into the factors influencing purchasing decisions. Finally, future research should explore the type of SM content (educational, promotional, and influencer recommendations) that has the greatest impact on consumer perception and behavior.