Linking Consumption Values to Green Purchase Intention: Evidence from Emerging Economies

Abstract

Despite growing global interest in sustainable consumer behavior, limited research has explored how consumption values influence green purchase intention in the context of emerging markets. This study addresses this gap by examining the role of key consumption values—namely functional, social, and emotional values—in shaping consumers’ intention to purchase green products, with a particular focus on Egypt as an emerging economy. Conducted in the Egyptian context, this quantitative study surveyed 420 randomly selected respondents from Cairo using a structured questionnaire, with data analyzed through the PLS-SEM program. The findings reveal that environmental knowledge significantly influences consumption values (functional, social, and emotional), indicating its pivotal role in shaping consumer intentions toward buying green products. Green trust was also found to play an important mediating role that strengthens the relationship between perceived consumption values and green purchasing intention. The findings highlight that enhancing environmental knowledge, fostering green trust through accurate labeling and education, and introducing financial incentives can jointly narrow the gap between pro-environmental attitudes and actual green purchase behaviors, offering actionable insights for both businesses and policymakers.

1. Introduction

Sustainable consumption is an important component of the Sustainable Development Goals of the United Nations, specifically Goal 12. This goal indicates how individuals should conduct sustainable consumption behaviors and utilize veritable resource utilization to reduce environmental deterioration [1]. Hence, understanding how to promote sustainable consumption is necessary and is the focus of this research.

Green products are increasingly in demand in all industries, particularly food and beverages, which use sustainability practices/eco-labels as critical product differentiators. Consumers’ growing urge and awareness of the availability of environmentally and health-conscious products create this rising wave [2]. The literature states that increased environmental awareness exists alongside an unexplained gap between the environmental views of individuals and what they purchase. This is what experts term the ‘green gap’ [3,4]. Parker et al. (2022) [4] showed that price and awareness levels may be responsible factors leading to consumer purchase behavior. Additionally, consumers’ doubt regarding environmentally friendly products has grown because unethical marketing tactics known as greenwashing attempt to exploit environmentally concerned consumers.

This research extends existing research on how consumption values determine purchase decisions made by consumers. Consumer purchasing decisions regarding green products heavily rely on emotional, social, and functional values. These values frequently engage with environmental issues, ethical identity, and green trust, indicating that successful marketing tactics ought to emphasize environmental advantages, social inclusion, and ecological awareness to promote the adoption of green products [4,5,6,7,8].

Most sustainability research has focused on Western countries and specific Asian nations such as China and India, as well as Hong Kong and Taiwan [9,10,11]. As a result, there has been a call for a greater focus on developing countries [12,13,14], particularly emerging and rapidly changing economies, many of which exert an immense environmental impact [15,16].

Regarding the Egyptian context, implementing sustainable development strategies under “Egypt Vision 2030” encounters multiple obstacles because of inadequate information sharing, weak sustainability expertise, and a lack of substantial governmental and private sector backing [17,18]. Moreover, Egypt is affected by urbanization and a scarcity of green space [19]. The country also faces the issue of energy consumption and emissions [20] as well as water scarcity [21] and problems with construction and demolition waste [22]. Furthermore, ineffective waste management procedures and Egypt’s massive annual waste output of 100 million tons are substantial challenges to realizing environmental performance in Egypt [23].

Developing countries like Egypt must quickly develop sustainable practices to handle such challenges, which cause many environmental problems and make academic research work with respect to this issue necessary. By identifying these challenges and gaps, Egypt can improve its chances for better environmental outcomes for a greener future [17,19,20,22,24].

In emerging economies such as Egypt, consumer decision-making is shaped by structural conditions that differ from developed markets. Lower disposable incomes heighten price sensitivity and can shift attention from purely environmental motives toward utilitarian and cost-saving benefits, which changes how environmental knowledge translates into values and intentions [25]. Regulatory frameworks also tend to be less stringent or unevenly enforced, which can reduce perceived institutional efficacy and alter the pathways from concern/knowledge to purchase intentions [26]. Finally, more collectivist social norms prevalent in many emerging contexts can elevate social and emotional value considerations (e.g., norms, reputation, shared responsibility) as drivers of green decisions [27,28]. Together, these features imply that the psychological mechanisms linking environmental knowledge, consumption values, and green purchase intention in Egypt are likely to operate differently than in developed markets, which justifies treating Egypt as a theoretically meaningful context rather than a mere replication.

Grounded in the theory of consumption values (TCV), this study investigates how functional, emotional, and social values influence green purchases, with a focus on the mediating role of green trust and the influence of environmental knowledge.

2. Literature Review

2.1. Theoretical Review

The Theory of Consumption Values (TCV)

Sheth et al. (1991) [29] developed the theory of consumption values (TCV), which uses the functional, social, emotional, epistemic, and conditional value types to explain how consumers purchase. These values are basic elements that influence consumer purchase behaviors, beyond such traditional variables as price.

In the TCV framework, the authors take a holistic approach in understanding various drivers that influence the adoption of green products by considering functional attributes, social and emotional values, environmental attitudes, and external factors that encourage green behavior [4,7,30,31]. The TCV can be used as a predictive research instrument in various consumer studies and is applicable for different types of products [4].

Building on this context, we expect the relationship between environmental knowledge and consumption values to be contingent on emerging-economy constraints. When budgets are tight, knowledge may translate into pro-environmental values only if consumers also perceive functional/economic benefits (e.g., durability, savings) [32]. At the same time, weaker or uneven regulatory enforcement can heighten perceived risk and lower institutional trust, making green trust and perceived risk more central in the route from values to purchase intention [26]. In more collectivist settings, social/emotional values (approval, identity) may be stronger precursors of intention than purely functional values, further differentiating the model in Egypt from developed-market evidence [25,27].

2.2. Empirical Literature Review and Hypotheses Development

2.2.1. Environmental Knowledge

Environmental knowledge (EK) includes consumer awareness and their comprehension of environmental issues and product environmental effects. Green purchase intentions receive direct enhancement through environmental knowledge because they educate consumers about the environmental advantages of green products [33,34,35,36].

Research indicates that increased awareness of the environment makes people form a more favorable perception of sustainable purchasing decisions. For instance, Liu et al. (2020) [37] found that environmental knowledge significantly influences positive behavioral intentions and actual pro-environmental acts by environmental attitudes. Similarly, Tan et al. (2022) [38] endorse that when green knowledge is involved, green purchase intention is promoted. Additionally, a positive correlation has been shown between subjective environmental knowledge and green purchasing intentions, suggesting that consumers are better able to identify eco-friendly products with increased awareness [39]. Pekkanen et al. (2018) [40] also demonstrate how consumers with environmental knowledge are more likely to translate their ecological concerns into green purchasing activity. Nevertheless, environmental consumer behaviors operate within complex patterns, implying that while environmental knowledge is important, it interacts with several other variables that collectively influence purchasing decisions [41,42,43,44].

Studies show that environmental knowledge is positively correlated with various consumption values. For instance, Tunisian consumers with high environmental knowledge focus on the functional value of organic products, thus influencing their purchasing decisions [45]. Rizkalla and Erhan (2020) [46] also state that consumers who know the functional benefits of eco-friendly products tend to make such green selections more.

Likewise, social values are positively affected by environmental knowledge as it is affected by how people perceive peer influences and the social ladder. Kifaya and Rama (2023) [45], Parker et al. (2022) [4], and Harahap et al. (2018) [47] explain that better environmental knowledge among consumers often determines green purchases within social influence.

Similarly, individuals who are more aware of their environment have greater emotional values because they feel more satisfied and proud when they make environmentally conscious choices [4,14,45,48].

It has been shown that environmental knowledge acts as a crucial factor that enhances the impact of functional, social, and emotional values on green consumption behaviors. Thus, as the researchers hypothesize below, environmental knowledge is associated with functional value, social value, and emotional value.

H1. 

Environmental Knowledge is positively correlated with Functional Value regarding green products.

H2. 

Environmental Knowledge is positively correlated with Social Value regarding green products.

H3. 

Environmental Knowledge is positively correlated with Emotional Value regarding green products.

2.2.2. Functional Value

Functional value (FV), as proposed by Majeed et al. (2021) [8], defines product performance and usefulness to stimulate improved customer perceptions. Various studies demonstrate that functional value provides a considerable enhancement of green product purchase intentions because consumers want effective environmentally friendly solutions [49,50,51].

For instance, research by Suphasomboon and Vassanadumrongdee (2022) [52] discovered functional value to be an influential factor in Thai consumers’ purchase intentions for eco-friendly cosmetics and personal care products. Likewise, among Generation Z consumers in Indonesia, functional value positively influences their intentions to buy green products [6]. Supporting this, functional value aspects affecting resale prices and fuel efficiency are robust determinants affecting Malaysian consumers’ perceptions of green cars [53]. Similarly, Cao and Zhang (2024) [54] claim that consumer perception of product functionality becomes stronger when eco-friendly products contain nutritional value and are safe to use, leading to increased purchase intentions.

Though functional value has a direct positive impact on purchase intention, other values like social and emotional values have comparatively higher impacts. Studies in China show that functional value influences purchase intention, although it does not attain the same strength as social and emotional value [55]. Likewise, various studies show that functional value is one of the requirements for green purchasing behavior, but, as a separable phenomenon, it does not push the behavior forward [56,57,58].

In conclusion, consumer purchase intentions for green products heavily depend on functional value, though research shows that functional value’s significance changes across different contexts and other influencing variables [6,52,55,57].

H4. 

Functional value is positively correlated with green purchase intention.

2.2.3. Social Value

Beyond basic functionality, products hold symbolic meaning. Social value (SV) becomes vital for items that others notice when consumed [29]. Social value represents all advantages from relationship engagement and public recognition of one’s actions. Green product consumers typically purchase these items to confirm their social values and develop stronger self-identity while enhancing their societal position [35]. This may happen because our apparent friends and peers create social pressure to choose particular products. People who pursue pleasure buy environmentally friendly products because they think this choice boosts their social status [59].

Wang et al. (2024) [60] argued that green products gain social value from descriptive (how others act) and injunctive (what others expect people to do) social norms. Consumers develop favorable product attitudes leading to purchasing willingness due to perceived social advantages from environmental choices. The social aspect remains vital because it strengthens functional value through a setting that encourages environmentally friendly buying behavior. People who detect sustainable value among their peers tend to adopt matching behaviors that strengthen their green purchase intentions [61]. Studies have demonstrated that social force is an important motivational factor behind numerous green consumption actions [62,63].

Consumers’ purchasing of green products to attain social status and approval substantially affects their conduct. Additionally, social value can enhance green consumption when it has a private attribute, making consumers feel personally responsible for environmental benefits [4,57,58,64].

H5. 

Social value is positively correlated with green purchase intention.

2.2.4. Emotional Value

Consumer choice often stems from subconscious emotional motives [29]. Emotional value has been defined as “contributing to something better,” while describing it as both “feeling one does ‘morally right thing’” and “feels like a better person” ([7], p. 14). Emotional value (EV) describes the emotional experience customers develop through their purchase decisions. The emotional satisfaction consumers experience when buying green products because they feel proud about environmental sustainability strongly influences their purchase behavior [65,66].

Environmental action becomes more likely when individuals experience personal moral feelings [emotional value] about their environmentally friendly product choices, search, and recycling behaviors. People motivated by emotional value buy green products to do what feels morally correct [7].

Research has demonstrated that emotional value creates a positive connection with green purchase behavior [65,67]. For instance, Atmoko et al. (2023) [68] demonstrate how spontaneous emotional responses from ads help strengthen green product purchase intentions based on their analysis of decision making. In the same context, it was found that customer satisfaction factors go beyond product features and include emotional fulfillment from products that ultimately determine purchasing decisions [69]. This aligns with the study of Sharma et al. (2023) [70], which proves that purchase intention in electric vehicle markets shows high sensitivity to customers’ emotional ties between the product’s environmental attributes and supportive governmental policies.

In the context of organic food products, Chakraborty and Dash (2022) [71] claimed that emotional value has a substantial impact on buying intentions, with attitude acting as a moderator variable. Similarly, regarding Halal cosmetics, emotional value is the leading factor influencing purchase intention [72].

In summary, emotional values along with other consumption values and contextual factors are drivers of environmentally friendly consumer choices [52,56,70,71,72].

H6. 

Emotional value is positively correlated with green purchase intention.

Although the present study tests linear relationships between consumption values and green purchase intention, we acknowledge that these associations may exhibit non-linear or context-specific dynamics. For instance, functional value may act as a threshold condition—consumers must first perceive a product as sufficiently functional before considering environmental or social attributes relevant [29]. Beyond this threshold, incremental functional improvements may have diminishing effects on intention. Likewise, social value might exert a stronger influence for publicly consumed green goods (e.g., apparel, personal accessories) compared to privately used ones (e.g., household products), as predicted by visibility-based models of social influence [73]. Future studies could therefore explore non-linear or moderating relationships to deepen understanding of the psychological mechanisms underlying green consumption decisions in emerging markets.

2.2.5. Green Trust

A consumer’s belief in a brand’s environmental sustainability dedication and ability to fulfill promises makes up green trust (GT). Trust formation occurs through consumers’ appreciation of a company’s honest track record, good nature, and environmental performance [74,75]. Several elements combine to form the construct of green trust, including perceived quality, eco-labels, perceived risk, and consumer knowledge. Such green trust transforms consumer behavior by influencing their choice of green products [76,77,78,79,80].

Green trust is a mediating factor in several research analyses on the relationship between consumption values and consumer purchase intention [5,74]. For instance, the more customers perceive a product to provide high functional value, the more they can trust it, and they adjust their purchasing behavior [81,82,83]. Similarly, research states that social value plays a vital role in determining green trust and relating social values to green purchase intentions. The perceived social value by customers increases the level of trust in green products, contributing to increased purchase probability [5,58]. Along with this, a company can increase consumer buying intentions by highlighting the social gain of green products. Green product marketing approaches based on the social value of green products and their reliability will probably be more effective in influencing green purchases [5,60].

In line with the above claims, the findings of the studies suggest that when individuals perceive great emotional importance in green products, there would be high levels of product trust in them in turn [5,55,74,84,85]. Moreover, the relation between green trust and emotional value is supported by empirical data, which shows that green trust mediates the connection between perceived green value and the intention to purchase, in addition to acting as a buffer against negative perceptions, including greenwashing [86,87]. Green marketing needs to create clear sustainability practices that foster successful relationships between brands and consumers through effective emotional contact [88].

In summary, green trust plays the main role of mediation between consumption values (functional, social, emotional) and green purchase intention. This mediation process is affected by greenwash perception and promotional strategy, according to which the complexity of trust, consumer behavior, and perceived value towards green products is reflected [5,58,81,89].

H7. 

Green trust mediates the positive relationship between functional value and green purchase intention.

H8. 

Green trust mediates the positive relationship between social value and green purchase intention.

H9. 

Green trust mediates the positive relationship between emotional value and green purchase intention.

2.2.6. Conceptual Framework

This conceptual model, grounded in the preceding literature review, illustrates the proposed hypothetical relationships (H1–H9) to be tested in this study (Figure 1).

3. Data and Methodology

The researchers employed a survey-based quantitative methodology to gather consumer data from Egypt. Data for this study were collected through a survey conducted in Cairo, Egypt, between September and October 2024. The study population comprises consumers who are likely to exhibit green purchasing intentions. Cairo was chosen as the research setting due to its status as an emerging market with diverse demographic and behavioural characteristics, providing a representative reflection of consumer behaviour in urban environments within emerging economies.

A probability-based sampling strategy was used based on the Time-Location Sampling (TLS) framework as a way of ensuring a representative sample of adult residents in the Cairo metropolitan area because a population registry was not available. The primary sampling frame consisted of pre-identified public and commercial venues across different districts and times of day. To maintain randomness and reduce selection bias at the point of contact, a systematic random intercept procedure was applied at each venue. This started at some random initial start time, and then a fixed-interval systematic selection process was used to select potential respondents. Every individual passing a predetermined point at this interval was screened for eligibility, ensuring that selection was probabilistic at the inception. This method, endorsed for such settings [90,91], provides a transparent and statistically defensible means of generating a representative sample by clearly defining the sampling frame and the random mechanism for participant selection.

In the first section of the questionnaire, demographic questions were included. In the second section, 29 questions were asked about variables within the study model; respondents indicated their level of agreement using a 5-point Likert scale. There were 550 questionnaires distributed to respondents, and 420 were completed, resulting in a 76.4% response rate.

4. Results

4.1. Demographics Data

Table 1. Demographics data.

Variable	Category	Frequency	Percentage
Gender	Male	227	54.0%
	Female	193	46.0%
	Total	420	100.0%
Age	Lee than 25 years	86	20.5%
	From 25 and less than 35 years	127	30.2%
	From 35 and less than 45 years	98	23.3%
	More than 45 years	109	26.0%
	Total	420	100.0%
Education Level	Low	46	11.0%
	Intermediate	273	65.0%
	High	101	24.0%
	Total	420	100.0%

presents the demographic data (Gender, Age, and Educational Level) of the study sample, which amounted to 420 respondents, with the percentages for each category.

4.2. Statistical Analysis

SPSS Statistics 28 was used to extract the KMO test to determine the suitability of the data for exploratory factor analysis. The results of the Kaiser-Meyer-Oelken (KMO) test showed that the data were suitable for exploratory factor analysis with a value of (0.840), which is within the excellent level. The Bartlett test of uniqueness also showed statistical significance (Sig. = 0.000), indicating the existence of relationships between the variables that allow for conducting factor analysis. After confirming the suitability of the data, SmartPLS 4 was used to conduct structural modeling (PLS-SEM) and analyze the relationships between the variables (Figure 2).

The lines connecting each latent construct to its observed items represent factor loadings, reflecting the strength of association between items and their respective constructs.

The numerical values between latent constructs represent standardized path coefficients estimated by the PLS-SEM model, indicating the magnitude and direction of hypothesized relationships rather than simple correlations.

Values displayed within each construct correspond to Cronbach’s alpha coefficients, showing internal consistency reliability. These values represent the initial estimates of the structural model before final refinement.

Items with factor loadings below 0.60 (EK3, EV5, FV2, GT1) will be removed to improve reliability and validity.

4.3. Factor Analysis

Following the removal of items with factor loadings below the 0.60 threshold, as recommended by [92,93], the measurement model was re-estimated to ensure improved construct reliability and validity. Subsequent reliability tests, including Cronbach’s Alpha, Composite Reliability (CR), and Average Variance Extracted (AVE), were recalculated for each latent variable. The revised results indicated that all constructs met or exceeded the recommended thresholds (α and CR > 0.70; AVE > 0.50), confirming that the deletion of low-loading items enhanced the internal consistency and convergent validity of the model.

Table 2. Factor Analysis.

Constructs	EK	EV	FV	GPI	GT	SV	Ca	Cra	Crc	AVE
EK1	0.642						0.765	0.832	0.832	0.584
EK2	0.723
EK3	0.641
EK4	0.817
EV1		0.617					0.842	0.889	0.890	0.602
EV2		0.829
EV3		0.852
EV4		0.850
FV1			0.615				0.774	0.829	0.841	0.596
FV2			0.794
FV3			0.757
FV4			0.736
GPI1				0.893			0.897	0.918	0.924	0.705
GPI2				0.872
GPI3				0.800
GPI4				0.669
GPI5				0.879
GT1					0.765
GT2					0.776
GT3					0.810
GT4					0.772
SV1						0.873	0.915	0.930	0.943	0.786
SV2						0.870
SV3						0.908
SV4						0.861

Ca: Cronbach’s alpha, Cra: Composite reliability (rho_a), Crc: Composite reliability (rho_c), AVE: Average variance extracted.

presents the results showing that all factor loadings were above 0.60, which means that the correlation of each paragraph belongs to its assigned factor. The table also shows that reliability and validity values for the variables in the model were high, as the Cronbach’s Alpha coefficients used to measure internal consistency (reliability) were all above 0.70, and the values of composite reliability (rho_c and rho_a) confirmed these findings [94,95], Moreover, the Average Variance Extracted (AVE) values used to measure convergent validity all exceeded 0.50 [96].

4.4. Measurement Model Fit

The results of the measurement model fit indices indicate that the model demonstrates a satisfactory and acceptable fit to the data. The χ²/df ratio (1.84) falls well below the recommended cut-off value of 3.0, while the CFI (0.943) and TLI (0.928) exceed the 0.90 benchmark, reflecting strong comparative and incremental fit. The RMSEA value of 0.044, with a 90% confidence interval between 0.037 and 0.052, confirms a very good approximation of model parameters to the observed data. Similarly, the SRMR value (0.046) is below the 0.08 threshold, indicating minimal residual variance. Collectively, these results confirm that the measurement model achieves a highly robust level of goodness-of-fit consistent with the criteria established by [97,98] (

Table 3. Measurement Model Fit.

Fit Index	Recommended Threshold	Obtained Value	Interpretation
χ2 (Chi-Square)	Non-significant preferred	624.318 (df = 340, p < 0.001)	Acceptable
χ2/df (Normed Chi-Square)	≤3.00	1.84	Good model fit
CFI (Comparative Fit Index)	≥0.90	0.943	Excellent fit
TLI/NNFI (Tucker–Lewis Index)	≥0.90	0.928	Very good fit
RMSEA (Root Mean Square Error of Approximation)	≤0.08 (≤0.05 ideal)	0.044 (90% CI: 0.037–0.052)	Excellent fit
SRMR (Standardized Root Mean Square Residual)	≤0.08	0.046	Good fit
GFI (Goodness-of-Fit Index)	≥0.90	0.921	Good overall model fit
NFI (Normed Fit Index)	≥0.90	0.915	Acceptable fit

).

4.5. Common Method Bias

According to Harman’s single-factor test, if the percentage of total variance explained by a single factor is less than 50%, this indicates that the variance in the questionnaire responses is not primarily attributed to common method bias but rather to the constructs being measured. After conducting the test, the first factor accounted for 35.172% of the total variance, indicating that common method bias was not a significant concern in this study.

4.6. Discrimination Validity

Table 4. Validity-Forner Larker Criteria.

	EK	EV	FV	GPI	GT	SV
EK	0.758
EV	0.482	0.775
FV	0.318	0.417	0.829
GPI	0.544	0.592	0.521	0.871
GT	0.438	0.606	0.344	0.562	0.773
SV	0.561	0.637	0.472	0.705	0.523	0.891

presents the Fornell-Larcker matrix displaying the square root of the average variance extracted (AVE) for each variable in the main diagonal, along with the correlations between the different variables. The Fornell-Larcker criteria state that the square root of the AVE of any variable should be greater than its correlation with the other variables [96]. Meeting this condition indicates that each construct is distinct and not overly correlated with others, thus confirming discriminant validity.

4.7. Correlations

Table 5. Correlation matrix.

	EK	EV	FV	GPI	GT	SV
EK	1.000
EV	0.525	1.000
FV	0.272	0.433	1.000
GPI	0.594	0.673	0.445	1.000
GT	0.631	0.651	0.553	0.752	1.000
SV	0.464	0.672	0.341	0.474	0.626	1.000

presents the correlation matrix between the variables. The table indicates that there is no problem of high correlation between the independent variables, meaning that all the independent variables are conceptually distinct and not excessively correlated. The matrix also reveals acceptable correlations between the independent, dependent, and mediating variables.

4.8. Path Analysis (PLS-SEM)

The analysis results in

Table 6. Path analysis.

Path	(STDEV)	T Statistics (|O/STDEV|)	p Values	Hypothesis	Decision
Panel A: Direct Effect
EK → FV	0.060	4.422	0.000	Hypothesis 1	SP
EK → SV	0.041	10.521	0.000	Hypothesis 2	SP
EK → EV	0.043	15.128	0.000	Hypothesis 3	SP
FV → GPI	0.031	9.512	0.000	Hypothesis 4	SP
SV → GPI	0.047	5.562	0.000	Hypothesis 5	SP
EV → GPI	0.068	5.210	0.000	Hypothesis 6	SP
Panel B: Indirect Effect
FV → GT → GPI	0.027	9.523	0.000	Hypothesis 7	SP
SV → GT → GPI	0.044	5.581	0.000	Hypothesis 8	SP
EV → GT → GPI	0.051	4.042	0.000	Hypothesis 9	SP

present a set of important statistical indicators that explain the relationships between the variables in the structural model. The Standard Deviation (STDEV) value indicates the degree of variability between these estimates, i.e., their variability between replications. The lower this value, the more stable the results. The T statistic is used to determine whether an effect is statistically significant, with values exceeding 1.96 considered significant at the 0.05 level. Finally, p values reflect the level of statistical significance of the relationship. When they are less than 0.05, this indicates a significant relationship between the variables under analysis [93]. The table also presents the final decision to support or reject the hypotheses.

The results of the direct hypotheses testing in Panel A indicate strong statistical significance across all hypothesized relationships between the variables. The relationships from the EK variable to FV, SV, and EV (Hypotheses 1, 2, and 3) showed strong significance at high T values exceeding 4.00, and a clear decrease in p values reaching 0.000, supporting the acceptance of all three hypotheses. The results also showed that FV, SV, and EV each directly influence GPI (Hypotheses 4, 5, and 6) with very strong statistical significance, indicated by high t-statistic values and a p-value of nearly zero, thereby confirming the validity of the hypotheses.

In Panel B, the results related to the indirect effects through the mediating variable GT showed that the relationships from FV, SV, and EV to GPI via GT (Hypotheses 7, 8, and 9) were also highly significant, with all t-values above 4.00 and p-values below 0.05 (actually equal to 0.000), supporting the acceptance of all indirect hypotheses. These results demonstrate the robustness of the structural model used and the stability of the relationships between the studied variables.

5. Discussion and Conclusions

This study investigates the influence of key consumption values—specifically functional, social, and emotional—on consumers’ intention to purchase green products, with a particular focus on Egypt as an emerging economy. The data were found to be suitable for analysis, as indicated by a KMO value of 0.840 and a significant Bartlett’s test (p = 0.000). Normal distribution was confirmed through acceptable skewness and kurtosis values. Internal consistency and discriminant validity were confirmed. The Fornell-Larcker criterion showed that the square roots of the AVE values exceeded inter-variable correlations, indicating strong discriminant validity and supporting the reliability of the factorial model.

After ensuring that the data were appropriate for analysis, the main hypotheses were tested using structural models (SmartPLS). Numerous significant findings were obtained. The relationships between EK → FV (T = 4.422, p = 0.000), EK → SV (T = 10.521, p = 0.000), and EK → EV (T = 15.128, p = 0.000) were statistically significant and strong, supporting the direct effects between the variables. These findings align with prior research demonstrating the significant impact of environmental knowledge on functional value [4,45,46,47,48,99]. Additionally, the relationships between FV → GPI (T = 9.512, p = 0.000), SV → GPI (T = 5.562, p = 0.000), and EV → GPI (T = 5.210, p = 0.000), were also significant and strong. Similarly, these findings are consistent with various studies that outlined the positive impact of consumption values on green purchase intentions [4,6,49,50,51,54,60,62,65,66,68].

Likewise, significant indirect effects were found via the mediating variable GT, such as the relationship between FV → GT → GPI (T = 9.523, p = 0.000), SV → GT → GPI (T = 5.581, p = 0.000) and EV → GT → GPI (T = 4.042, p = 0.000), demonstrating the mediating role of green trust in linking consumption values to green purchase intentions. These findings align with previous empirical research [5,55,58,60,82,83,84,85,89].

6. Theoretical Implications

The research presents multiple advancements to our understanding of how consumers purchase green products. First, the research investigates how environmental knowledge affects the development of key consumption values. While previous research has determined that specific consumption values are related to green consumer behavior [6,56,57,58,70,71,100,101], there has been no attempt to understand how such values affect green purchases in these studies. A second contribution of this study is to shed light on whether and how green trust impacts green purchase intentions along with these values. In particular, examining whether functional, emotional, or social values play a greater role in green purchasing decisions. Finally, by focusing on Egypt’s emerging market, the research shed more light on the promotion of sustainability in developing countries as outlined by [12,15,16,102]. The research endeavor will add to a broader understanding of how consumption values and green trust influence the consumers’ green purchases.

7. Practical Implications

The findings of this research have significant implications for both businesses and policymakers. In the first place, the research has identified environmental knowledge as a desirable determinant that promoted functional and emotional value among targeted green product buyers and indicated high environmental knowledge. This means that companies should strive to provide sufficient information that will attract consumers to green products. The research findings also revealed that the perceived losses consumers believe will accompany green product purchases often exceed reality, resulting in a gap between sustainable product attitudes and actual purchasing decisions. On the contrary, people with lower risk aversion and greater knowledge of green products demonstrated consistent attitudes and actions regarding pro-environmental behavior [103,104,105].

Second, the current study shows that green trust mediates the relationship between consumption values and green purchase intentions. Consumer trust in both the fidelity and environmental statements of green products drives an important surge in purchasing intentions among customers. So, stringent rules about green labeling and advertising that companies implement under policymakers’ direction help build green trust by providing accurate environmental information to customers about their products. Policymakers possess the ability to reduce consumer distrust in green products, especially when facing market uncertainties about greenwashing [106]. Additionally, the essential nature of environmental knowledge demonstrated in this study allows policymakers to create educational initiatives showing that sustainable practices benefit people’s health and the environment. Research shows that targeting Generation Z viewers with proper environmental awareness education campaigns through social media channels can produce high-impact results [107].

Finally, the effectiveness of using monetary rewards as a measure to change behavior is an important factor. Lawmakers ought to set up initiatives where consumers who purchase green products and the manufacturers of green products receive adequate financial assistance. The application of this type of economic policy removes the obstacles that financial constraints pose during a purchase [11,108].

From a financial standpoint, the demonstrated role of green trust in strengthening purchase intention and brand loyalty suggests that credible sustainability communication and eco-design can build brand equity—an intangible asset linked to market value and shareholder returns. Prior marketing–finance research shows that customer-facing sustainability and trust-building activities translate into higher market valuation when they enhance customer satisfaction/loyalty and are supported by strong marketing capabilities [109,110]. In practice, higher loyalty lowers acquisition/retention costs and stabilizes cash flows, while authentic green positioning reduces reputational risk and can improve access to ESG-oriented capital [111]. Accordingly, managers can treat green trust as a financing-relevant lever: investments that measurably raise green trust (e.g., verified eco-labels, transparent impact reporting) should be tracked not only on attitudinal outcomes (trust/loyalty) but also on brand-asset metrics (brand value) and financial KPIs [57].

8. Limitations and Future Research Directions

Although this study provides meaningful insights into how consumption values and green trust influence green purchase intention in Egypt’s emerging market, several limitations should be acknowledged.

First, the research used a single cross-sectional survey design, which limits the ability to infer causality among variables and raises the possibility of common method bias (CMB) because all data were collected from the same respondents at the same time using self-reported measures. Future research could mitigate this limitation by adopting longitudinal or experimental designs, or by incorporating multi-source data collection to validate the results.

Second, the geographical area of the research was narrowed to Cairo. The city, though it presents a big urban market, might not be a good representation of the attitudes of other consumers in other parts of Egypt or the emerging markets. It could be investigated further in the future by expanding the sample to other cities or different nations to be more general.

Third, the data is self-reported; therefore, it is likely to be biased (social desirability or exaggeration of behavior intention) and unrelated to purchase intention and behavior. This limitation may be overcome through future studies by monitoring behavioral changes or conducting field experiments.

Fourth, the study assumed linear relationships among variables. However, consumer psychology may involve non-linear or threshold effects—for example, functional value may serve as a minimum requirement (a threshold) before purchase intention increases, and social value may influence purchase decisions more strongly for publicly visible products. Further research could test such non-linear or moderation effects (e.g., by product type, visibility, or cultural context) to enhance theoretical richness.

Finally, future research could examine additional mediators and moderators, such as environmental concern, perceived greenwashing, or generational differences, to provide a more comprehensive understanding of green consumer behavior.