doi: 10.56294/sctconf2024.1180

ORIGINAL

A Study on the Impact of Green Consumption Information Dissemination and Green Concern on Consumers’ Green Purchase Intention on Social Media

Un estudio sobre el impacto de la difusión de información sobre el consumo ecológico y la preocupación por el medio ambiente en la intención de compra ecológica de los consumidores en las redes sociales

Ziyu Zhou¹ *, Fauziah Sheikh Ahmad¹

¹Universiti Teknologi Malaysia Azman Hashim International Business School. Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, 54100, Malaysia.

Cite as: Zhou Z, Ahmad FS. A Study on the Impact of Green Consumption Information Dissemination and Green Concern on Consumers’ Green Purchase Intention on Social Media. Salud, Ciencia y Tecnología - Serie de Conferencias.2024; 3:.1180. https://doi.org/10.56294/sctconf2024.1180

Submitted: 01-03-2024                   Revised: 02-06-2024                   Accepted: 06-10-2024                 Published: 07-10-2024

Editor: Dr. William Castillo-González

Corresponding Author: Ziyu Zhou *

ABSTRACT

Social media platforms impact consumer behavior, particularly regarding environmental sustainability. However, the impact of these platforms on promoting green consumption remains unclear, particularly in China. The gap between the widespread dissemination of green consumption information and actual behavioral change raises concerns about the effectiveness of social media campaigns in promoting genuine green consumption practices. A study aims to investigate the relationship between green consumption information dissemination, consumer green concern, and green purchase intentions in urban China. Preliminary findings show that green information significantly boosts green purchase intentions, particularly among younger and university-educated individuals.

Keywords: Social Media Platforms; Environmental Sustainability; Green Consumption; Consumer Behavior; Machine Learning.

RESUMEN

Las plataformas de redes sociales influyen en el comportamiento de los consumidores, en particular en lo que respecta a la sostenibilidad medioambiental. Sin embargo, el impacto de estas plataformas en la promoción del consumo ecológico sigue siendo poco claro, sobre todo en China. La brecha entre la difusión generalizada de información sobre el consumo ecológico y el cambio de comportamiento real plantea inquietudes sobre la eficacia de las campañas en las redes sociales a la hora de promover prácticas genuinas de consumo ecológico. Un estudio tiene como objetivo investigar la relación entre la difusión de información sobre el consumo ecológico, la preocupación ecológica de los consumidores y las intenciones de compra ecológica en la China urbana. Los resultados preliminares muestran que la información ecológica impulsa significativamente las intenciones de compra ecológica, en particular entre las personas más jóvenes y con estudios universitarios.

Palabras clave: Plataformas de Redes Sociales; Sostenibilidad Medioambiental; Consumo Ecológico; Machine Learning.

INTRODUCTION

Green consumerism means preferring eco-friendly and sustainable goods and services. Consumers worldwide are adopting preference-based consumption.^(1,2) Consumers are becoming increasingly conscious of environmental concerns, including climate change, pollution, and resource depletion; thus, they choose products with little environmental effect.^(3,4) This movement is called green concern and reflects consumers’ environmental knowledge and care.⁽⁵⁾ Green concern generates demand for green goods and affects consumer perception.^(6,7) Social media makes spreading green marketing campaign success easier for prospective customers.⁽⁸⁾ Understanding the link between green consumption and green concern helps businesses modify their tactics to satisfy the demand of environmentally concerned customers, promoting sustainable consumer habits.

Despite the increased interest in sustainable living, consumers’ knowledge and comprehension of green consumption are still low.^(9,10) Many consumers are unaware of the environmental implications of their purchases and the availability and advantages of green goods.^(11,12) Despite their willingness to promote environmental sustainability, lack of awareness and misinformation deter many customers from purchasing green items.⁽¹³⁾ This makes sustainable consumption habits promotion more challenging and may not have the desired effect.^(14,15) To promote eco-friendly purchases, this knowledge gap must be closed. Educational and technical measures are needed to address this knowledge gap and promote green consumption.⁽¹⁶⁾ Governments, NGOs, and corporations should collaborate on educational initiatives using conventional media and digital channels, especially social media, where many consumers participate.⁽¹⁷⁾ Standardising items with unambiguous labelling and environmental certifications helps customers identify green products.⁽¹⁸⁾ These initiatives would make informed decisions easy for customers. The study investigates the influence of green consumption information and green concern on consumers’ green purchase intentions on social media. It uses a path-analytic framework and data from 280 participants in China to determine how social media can enhance consumer awareness and drive sustainable purchasing behaviors. The study analyzes the frequency, quality, and comprehensiveness of online green content, assessing consumers’ levels of green concern and how these factors influence their likelihood of selecting environmentally friendly products. The findings provide insights into the effectiveness of current green marketing strategies and offer a basis for improving consumer engagement in sustainability initiatives.

METHOD

This study proposes a conceptual model that examines the relationships between green consumption information dissemination on social media, consumers’ green concern, and their green purchase intentions.

The key variables of the study are:

· Information Dissemination: refers to the frequency, quality, and comprehensiveness of Green consumption information shared on social media platforms.

· Green Concern: this variable measures the level of concern consumers have regarding environmental issues.

· Green Purchase Intention: this is defined as consumers’ willingness to prefer, seek out, and buy environmentally friendly and sustainable products.

Based on the conceptual model, the following hypotheses are formulated:

· Hypothesis 1 (H1): there is a positive relationship between the dissemination of Green consumption information on social media and consumers’ green purchase intentions.

· Hypothesis 2 (H2): green concern mediates the relationship between Green consumption information dissemination on social media and green purchase intentions.

· Hypothesis 3 (H3): a positive relationship exists between green concern and purchase intentions.

Study Area

The research was conducted in the People’s Republic of China, targeting social media users across various urban regions of China. The sample consisted of 140 individuals aged between 18 and 35 and 140 between 36 and 50. The gender distribution was approximately equal, with 51 % Female and 49 % Male participants. The individuals were active users of platforms such as Weibo, WeChat, and Douyin. The educational background varied, with 25 % holding a high school diploma, 50 % with a bachelor’s degree, and 25 % possessing postgraduate qualifications. The demographic split of the study sample is shown in figure 1.

Figure 1. Participant Characteristics

Data Collection

Participants were fully aware of the study’s goals and procedures before data collection. Each subject gave informed permission, recognising their voluntary involvement and research purpose. We interviewed people from diverse demographics to acquire data. A thorough questionnaire was created based on these first interviews and a study of green marketing and consumer behaviour literature. To test the first questionnaire, 30 people participated in a pilot research. The questions were refined using pilot group feedback. The remaining participants received the revised questionnaire online. Two months were spent surveying. Responses with a completion rate below 70 % were discarded. Of 280 surveys, 187 satisfied the inclusion criteria and were included in the dataset.

Questionnaire

Three 18 questions address distinct elements of green consumption information dissemination on social media and green buying intentions. The 5-point Likert scale, from “Strongly Disagree” to “Strongly Agree,” measures participants’ views and behaviours on all topics.

Section A: Green Information Dissemination on Social Media

· I frequently encounter Green consumption information on social media platforms.

· The green content on social media is informative and easy to understand.

· Social media influences my awareness of environmental issues.

· I trust the Green consumption information shared on social media.

· Green social media efforts inspire me to study about sustainability.

· I will likely follow social media pages or accounts focusing on Green consumption.

· The visual content related to green products on social media grabs my attention.

· Overall, social media is a reliable source of information on Green consumption.

Section B: Green Concern

· I am concerned about environmental issues and their impact on future generations.

· My concern about the environment influences my daily choices and behaviors.

· I actively seek information about sustainable living practices.

· Environmental issues are a significant factor in my purchasing decisions.

· I feel responsible for using products that have a minimal environmental impact.

· Social media discussions regarding sustainability raise my green awareness.

Section C: Green Purchase Intentions

· I prefer products that are advertised as environmentally friendly.

· I prefer products that are advertised as environmentally friendly.

· I am willing to pay a premium for sustainable and eco-friendly products.

· Green items are my preference since I care about the environment.

· Social media recommendations for green items have an impact on my purchases.

Reliability and Validity Analysis

Table 1. Measurement of Variables
Variable Type (No. of Questions)	Variable Description	Example Questionnaire Items	Cronbach’s α
Green Information Dissemination (8)	Assesses social media Green consumption information exposure and trust.	"I frequently encounter Green consumption information on social media platforms." "I trust the Green consumption information shared on social media."	0,87
Green Concern (6)	Assesses environmental concerns and how it affects behaviour.	"I am concerned about environmental issues and their impact on future generations." "Environmental issues are a significant factor in my purchasing decisions."	0,85
Green Purchase Intentions (4)	Assesses if environmental concerns and social media use impact green product purchases.	"I prefer products that are advertised as environmentally friendly." "Recommendations on social media about green products influence my purchasing decisions."	0,89

Table 2. Results of Validity Tests
Section of Questionnaire	KMO Value	Bartlett's Test Significance
Green Information Dissemination	0,82	<0,001
Green Concern	0,79	<0,001
Green Purchase Intentions	0,85	<0,001

Each set of variable-related questions was reliability tested using Cronbach’s alpha to determine internal consistency. Table 1 shows that each questionnaire set has internal solid consistency based on Cronbach’s alpha values. The Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s Test of Sphericity were performed for each part of the questionnaire to determine the appropriateness of factor analysis (table 2). Good KMO Values over 0,7 indicate that underlying factors explain a considerable share of variable variation, making factor analysis viable for the data. If Bartlett’s Test Significance level is below 0,05 (or <0,001 for very significant findings), the correlation matrix is not an identity matrix and is acceptable for component analysis.

RESULTS

Metrics Employed

ANOVA

The ANOVA is used to determine if there are statistically significant differences between the means of multiple groups:

Where, MS_between (Mean Square Between Groups) is calculated as:

n_i is the sample size of the i-th group, X‾_i is the mean of the i-th group, and X‾ is the overall mean. MS_within (Mean Square Within Groups) is:

X^ij represents the j-th observation in the i-th group.

Chi-Square Test

This test determines if the observed frequencies in a contingency table differ significantly from the expected frequencies, which are calculated based on the hypothesis of no association.

Welch’s t-Test

Welch’s t-test is applied to compare the means of two groups that may have different variances.

Confidence Intervals (CI): x‾±z×s/√n. This interval estimates the population parameter with a certain degree of confidence (95 %Cl).

Coefficient of Determination (R^∧2) Formula:

This coefficient measures the proportion of variance in the dependent variable that is predictable from the independent variables.

F-test

The F-test is used primarily to test a regression model’s overall significance.

Table 3. Hypothesis Analysis Using ANOVA
Demographic Factor	DF	H1				H2				H3
		Sum of Squares	Mean Square	F-Value	P-Value	Sum of Squares	Mean Square	F-Value	P-Value	Sum of Squares	Mean Square	F-Value	P-Value
Age Group	2	12,34	6,17	5,12	0,007	8,56	4,28	3,95	0,021	14,78	7,39	6,23	0,003
Gender	1	5,47	5,47	4,01	0,045	3,89	3,89	2,88	0,091	6,54	6,54	5,60	0,018
Education Level	3	15,05	5,02	4,76	0,003	9,21	3,07	2,91	0,035	17,32	5,77	5,45	0,001
Error	293	351,12	1,20	-	-	288,45	0,98	-	-	362,58	1,24	-	-
Total	299	384,00	-	-	-	310,10	-	-	-	401,20	-	-	-

Figure 2. F and P values for hypothesis

Figure 3. Sum of Squares Analysis

Figure 4. Mean Square Analysis

Table 3 and figures 2–4 show ANOVA hypothesis analysis. H1 shows significant differences across age groups (F-value=5,12, P-value=0,007), genders (F-value=4,01, P-value=0,045), and education levels (F-value=4,76, P-value=0,003), suggesting that these demographic factors affect how well social media Green consumption information translates into purchase intentions. According to the findings, education level strongly affects customers’ reactions to Green consumption advice. The ANOVA findings for H2 reveal significant F-values and P-values for age groups (F=3,95, P=0,021) and education levels (F=2,91, P=0,035), but not gender (F=2,88, P=0,091). This suggests that green concern mediates this association, although its impact may vary by age and education, not gender. H3 has substantial statistical support across all demographic factors: age groups (F-value=6,23, P-value=0,003), genders (F-value=5,60, P-value=0,018), and education levels (F-value=5,45, P-value=0,001). These data support the premise that environmental concern increases the chance of buying green items across all demographics. The error terms have low mean squares compared to the groups, showing that the models capture the variation in our hypotheses’ data.

Table 4. Hypothesis Analysis Using Chi-square
Demographic Factor	DF	H1		H2		H3
		Chi-Square Value	P-Value	Chi-Square Value	P-Value	Chi-Square Value	P-Value
Age Group	2	5,34	0,069	10,21	0,006	3,88	0,144
Gender	1	2,47	0,116	1,93	0,165	4,56	0,033
Education Level	3	9,85	0,020	8,04	0,045	11,22	0,011

Figure 5. Chi-square analysis

Chi-square findings for H1 in table 4 and figure 5 demonstrate that this association varies by demographic group, albeit not all are statistically significant. While age and gender do not reveal significant relationships (P-values of 0,069 and 0,116, respectively), education level does (Chi-square value of 9,85, P-value of 0,020). The quantity of exposure and sensitivity to Green consumption information may explain why educational background greatly influences buying intentions. H2 shows significant associations across age groups (Chi-square value of 10,21, P-value of 0,006) and education levels (Chi-square value of 8,04, P-value of 0,045), suggesting that these demographic factors significantly influence how green concern mediates information dissemination on purchase intentions. Despite gender variations, this mediating impact of green concern was not significantly affected (P-value of 0,165). The Chi-square test for H3 demonstrates substantial demographic relationships for gender (4,56, P-value 0,033) and education level (11,22, P-value 0,011). The age group exhibits no significant correlation (P-value 0,144), showing that green concern may not affect purchasing intentions differently across age groups.

Table 5. Categorical Comparison for Hypothesis 1
Comparison	Welch's t-test P value	t value	df	Mean of Group A	Mean of Group B	95 % CI of Difference	R²	F-test to compare variances F value	DFn	Dfd	F-test P value
Age Group: 18-35 vs 36-50	0,032	2,15	198	3,45	3,02	(0,10, 0,76)	0,04	1,22	1	198	0,273
Gender: Male vs Female	0,045	1,98	210	3,20	3,50	(-0,58, -0,02)	0,03	0,95	1	210	0,500
Education Level: High School vs University	0,007	2,89	165	2,90	3,40	(-0,75, -0,25)	0,07	1,15	1	165	0,284

Figure 6. Categorical analysis for Hypothesis 1

In table 5 and figure 6, the categorical analysis for hypothesis H1 demonstrates that younger and older age groups respond differently to green consumption information (P-value=0,032). Younger people (mean=3,45) had stronger purchase intentions than older people (mean=3,02), with a confidence range of 0,10 to 0,76. Due to increasing digital participation, younger consumers may be more impacted by social media Green consumption information. Male and female responses to green consumption information vary significantly (P-value=0,045). Strangely, females (mean=3,50) had more excellent green purchase intentions than men (mean=3,20), with a confidence interval of -0,58 to -0,02. This suggests that women may be more responsive to or impacted by green marketing on social media owing to their environmental concerns or sustainability awareness.

University-educated people (mean=3,40) had more excellent green-buying intentions than high school graduates (mean=2,90) (P-value=0,007). According to the confidence range of -0,75 to -0,25, education strongly affects receptivity to Green consumption information, showing that higher education may increase sustainable practice comprehension and valuing. Higher t-values imply more significant group differences. Demographic variations explain a tiny but significant amount of buying intentions, as shown by low R² values. The F-tests for variances demonstrate no significant differences between groups (P-values>0,05), validating the t-test comparisons.

Table 6. Categorical Comparison for Hypothesis 2
Comparison	Welch's t-test P value	t value	df	Mean of Group A	Mean of Group B	95 % CI of Difference	R²	F-test to compare variances F value	DFn	Dfd	F-test P value
Age Group: 18-35 vs 36-50	0,018	2,40	198	4,10	3,68	(0,15, 0,69)	0,05	1,08	1	198	0,342
Gender: Male vs Female	0,038	2,08	210	3,75	4,05	(-0,55, -0,05)	0,04	1,03	1	210	0,584
Education Level: High School vs University	0,015	2,47	165	3,25	3,75	(-0,70, -0,30)	0,06	1,20	1	165	0,270

Figure 7. Categorical analysis for Hypothesis 1

Table 6 and figure 7 show the categorical analysis for hypothesis H2. Younger people (mean=4,10) report more substantial green concerns than older people (mean=3,68) (P-value = 0,018). The difference in confidence interval (0,15 to 0,69) implies that younger age groups are more responsive to green consumption information, which may lead to green purchases. Although tiny, the R² value 0,05 suggests that age somewhat explains the variation in green concern and purchasing intentions. Males had a lesser green concern (mean=3,75) than females (mean=4,05) (P-value=0,038). Females may incorporate green concerns more into social media-influenced purchases, according to the confidence range of (-0,55 to -0,05). The study shows that gender impacts environmental concerns and shopping behaviour.

University graduates had a more significant green concern (mean=3,75) than high school graduates (mean=3,25), with a P-value of 0,015 and a t-value of 2,47. The confidence range (-0,70 to -0,30) strongly suggests that higher education levels increase green information responsiveness, influencing purchase intentions. The R² value of 0,06 indicates that education significantly affects how green concern affects information and buying intentions. All demographic F-tests show non-significant findings (P-values>0,05), showing that the variances are close enough for valid t-tests. This validates the results’ cross-group dependability.

Table 7. Categorical Comparison for Hypothesis 3
Comparison	Welch's t-test P value	t value	df	Mean of Group A	Mean of Group B	95 % CI of Difference	R²	F-test to compare variances F value	DFn	Dfd	F-test P value
Age Group: 18-35 vs 36-50	0,021	2,30	192	3,85	3,40	(0,10, 0,80)	0,04	1,10	1	192	0,310
Gender: Male vs Female	0,029	2,12	205	3,65	3,95	(-0,50, -0,10)	0,03	1,05	1	205	0,552
Education Level: High School vs University	0,012	2,56	158	3,10	3,60	(-0,65, -0,35)	0,06	1,15	1	158	0,290

Figure 8. Categorical analysis for Hypothesis 1

Table 7 and figure 8 show the categorical analysis for hypothesis H3, showing that younger people (mean=3,85) have higher green purchase intentions than older people (mean=3,40) (P-value=0,021). The confidence range for the difference (0,10 to 0,80) implies that younger people are more inclined to buy green. The R² value of 0,04 suggests that age moderates the impact of environmental concern on buying intentions. Gender differences (P-value = 0,029) show that ladies (mean=3,95) have more excellent green purchasing intentions than men (mean=3,65). The negative confidence interval (-0,50 to -0,10) reiterates that females are more likely to buy environmentally conscious products. This shows that gender matters in green market customer behaviour.

DISCUSSION

Educational background substantially impacts (P-value=0,012) how green concerns translate into purchase intentions. Individuals with a university education (mean=3,60) exhibit higher green purchase intentions than those with only a high school education (mean=3,10). The confidence interval (-0,65 to -0,35) robustly supports that higher education correlates with a greater propensity to engage in environmentally responsible purchasing behaviors. The R² value of 0,06 suggests that education significantly influences this relationship. The F-tests across all comparisons indicate no significant differences in the variances between the groups (P-values>0,05), which validates the assumptions required for conducting Welch’s t-tests.

CONCLUSIONS

The study highlights the significant role of social media in shaping consumer behaviors towards green consumption. It shows that disseminating green consumption information on social media platforms significantly enhances green purchase intentions, especially among younger and university-educated consumers in urban China. The effect is mediated by the level of green concern, emphasizing the importance of presenting green information and fostering environmental concern among consumers to translate it into actionable behavior. Effectively targeted social media campaigns can close the gap between awareness and actual green purchasing.

Future research should continue to explore this dynamic, considering varying cultural contexts and demographic specifics to refine the approach of using SMP for environmental advocacy.

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FINANCING

Currently, there are no available financing sources designated for this project. This absence of financial support underscores the need for strategic planning to identify potential funding avenues that could facilitate the successful implementation and advancement of the initiative.

CONFLICT OF INTEREST

The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

AUTHORSHIP CONTRIBUTION

Conceptualization: Ziyu Zhou, Fauziah Sheikh Ahmad.

Investigation: Ziyu Zhou, Fauziah Sheikh Ahmad.

Methodology: Ziyu Zhou, Fauziah Sheikh Ahmad.

Writing - original draft: Ziyu Zhou, Fauziah Sheikh Ahmad.

Writing - review and editing: Ziyu Zhou, Fauziah Sheikh Ahmad.