INTRODUCTION
Research background
In recent years, consumer awareness of environmental issues has grown due to the impact of environmental disasters, leading to a heightened focus on environmental protection (Mclntosh, 1991) As a result, environmental concerns have emerged as a significant factor for consumers, prompting companies to seize the opportunity to market green products Sales of eco-friendly products have surged, with consumers increasingly willing to pay a premium for them (Chen, 2008b) Consequently, green marketing has gained importance, particularly for products made with sustainable technology and materials, such as green home appliances (Chen et al., 2006) Companies recognize that by offering environmentally friendly products and services, they can attract and retain customers who prioritize sustainability.
The Vietnamese government is actively promoting the consumption of green products by encouraging green labeling and disseminating information about environmentally friendly options This initiative aims to motivate businesses, such as electronics supermarkets, to distribute green products and adhere to resource-saving practices The study highlights the importance of understanding customer willingness to purchase green products, focusing on key elements of green marketing It identifies four factors influencing customer behavior towards green products: attitude toward green brands, perceived value of green brands, and other relevant aspects.
In Vietnam, the impact of green satisfaction and green trust on consumers' intentions to purchase eco-friendly home appliances is being explored, as suggested by previous research (Kang & Hur, 2011; 2013).
Research on environmental issues has led to a deeper understanding of green marketing dynamics This exploration highlights the connection between consumer attitudes toward green brands and their overall satisfaction with eco-friendly products.
Green brand perceived value, Green trust and Green consumption intention has expected meaningful and practical reasoning in green product management.
Research problems
Environmental pollution in Vietnam is on the rise, posing significant threats to economic and social development The three main types of pollution are soil, water, and air pollution, with air pollution in large cities being the most severe The increasing use of air conditioners contributes to the emission of harmful gases, exacerbating air quality issues and negatively impacting public health To address these environmental challenges, consumers are encouraged to use energy-efficient home appliances and turn off devices when not in use Ultimately, investing in environmentally friendly, energy-saving appliances is essential for sustainable living.
Green products must meet stringent criteria, including compliance with environmental protection laws, high-quality standards, energy efficiency, minimal use of toxic materials in their production, and a commitment to reducing pollution.
Besides, it responsible for ensuring the health of consumers, guide and encourage consumers to use the product in a manner friendly to the environment (Hawari & Hassan, 2008)
Green products offer a variety of models, excellent warranties, and a strong reputation for energy efficiency, ultimately saving consumers money in the long run While the initial cost of these products may be higher than conventional options, they contribute to energy conservation and environmental protection Many consumers, even those with average incomes, are willing to invest in energy-saving home appliances due to their long-term benefits Although the upfront expense can be significant, these products lead to reduced power consumption and lower electricity bills over time, while also being non-toxic and safe for health In contrast, cheaper alternatives often lack energy efficiency, leading to waste and environmental harm For instance, investing in a Daikin air conditioner may involve a higher initial price, but it results in substantial savings on monthly electricity bills due to its energy-saving capabilities.
Daikin and Panasonic air conditioning products utilize clean natural gas, making them ideal for families with children and the elderly (Baocongthuong, 2013) These brands are part of a growing trend towards energy-efficient and environmentally friendly appliances To promote the use of green products, both the government and businesses are encouraging consumers to adopt eco-friendly home appliances.
Research objectives
Because of the problem presented above, this study aims to investigate the factors affecting customer’s green consumption intention: a study of green home appliances products in Viet Nam
In specific, this study aims to: Identify factors effecting customer's green consumption intention toward green home appliances products
Besides, this study determines the different effects of these factors to green consumption intention related customer groups of gender, age, income, education, family status.
Research scope
This study focuses on green home appliances in the Ho Chi Minh market, Vietnam, including Sony televisions, Daikin air conditioners, Samsung refrigerators, and Happy Cook rice cookers, due to their environmental safety and energy efficiency These products are labeled with a green rating system, ranging from 1 to 5 stars, which indicates their quality standards.
The advertising program, along with promotional discounts and price reductions, has effectively introduced green products to consumers We conducted interviews with customers planning to purchase home appliances at electronics supermarkets, as well as those residing in new apartments who are looking to buy appliances for their homes.
Moreover, this study based on these customer groups to focus in asking more that they have intend or they don’t have intend to buy green home appliances products
This study highlights the significance of the Ho Chi Minh market, as Ho Chi Minh City stands as Vietnam's largest and most rapidly developing urban center The market provides a platform for businesses to showcase a variety of eco-friendly products, enabling consumers to purchase safe and environmentally sustainable items while also saving money.
Due to time constraints, selecting the Ho Chi Minh market for this research facilitated a reduction in travel distance, resulting in more accurate survey data and enhanced interview effectiveness.
Research method
This study employs both qualitative and quantitative methods This research process involves pilot study and official research This pilot study is based on the qualitative method
The purpose of pilot study to make questionnaires more perfect before the official research
Official research was carried out using quantitative methods
This study focuses on Vietnamese consumers' intentions to purchase home appliances in electronics supermarkets and new apartments, emphasizing the importance of green consumption It highlights green home appliances, such as televisions, air conditioners, and refrigerators, which are labeled with energy efficiency ratings ranging from 1 to 5 stars Higher star ratings indicate better energy savings, although these products typically come at a higher price.
This study aimed to assess customer acceptance of green home appliances after providing explanations about their benefits The research involved a pilot study and official data collection through face-to-face interviews conducted in electronics supermarkets and new apartment complexes.
In a pilot study, a draft of questionnaires was distributed to 20 customers interested in purchasing green home appliances at electronics supermarkets After gathering feedback from these customers, the questionnaires were revised and enhanced to better align with the objectives of the official research Subsequently, the finalized questionnaires were distributed for the main study.
300 customers who have intended to buy home appliance productsand checked in total 300 customers, how many customers have green consumption intention
This study employs a two-step approach to test hypotheses derived from existing behavioral consumption theories, initially utilizing quantitative methods followed by qualitative analysis for deeper insights To ensure the reliability of the measurement scales, Cronbach’s Alpha is calculated using SPSS software on standardized items Subsequently, the validity of the measurement scales is assessed through exploratory factor analysis (EFA).
(Exploratory Factor Analysis) Finally, the paper applies regression for testing assumptions and hypothesis.
Significance of research
Green consumer products offer significant advantages for businesses, consumers, and the environment They enable companies to enhance their credibility regarding product origin, quality, and brand reputation, reducing the need for extensive explanations by salespeople Consumers can feel confident in the high quality and stability of these products, which often lead to lower energy consumption and improved health By choosing green consumer products, individuals not only gain economic benefits but also contribute to alleviating pressure on national electrical systems and supporting environmental protection and climate change adaptation.
Structure of the study
Chapter 1 is mention two parts The first part relates to the overview of environmental awareness and green consumption trend in the present The second part involves the problem statement and gives the reasons to select the topic
Chapter 2 of the paper identifies four key customer factors influencing green consumption intention: attitude toward green brands, green satisfaction, perceived value of green brands, and green trust It also presents hypotheses and outlines the conceptual framework for the research.
Chapter 3 outlines the research methodology, detailing the research process, questionnaire design, sample selection, and data collection and analysis techniques It clearly defines the measurement scales used for the research factors, ensuring their appropriateness Additionally, this chapter explains the methods for data collection and analysis to evaluate the research hypotheses established in Chapter 2.
Chapter 4 presents an analysis of the survey data and discusses the findings in relation to the research model This section details the empirical aspects of the study, outlining the data collection methods employed to test the hypothesis Additionally, it evaluates the reliability of the data and conducts a multiple regression analysis.
Chapter 5, this chapter concludes research findings, managerial implications, research limitations and directions for future research.The final of this chapter is further research
References and appendixes are included in the end of thesis.
LITERATURE REVIEW
Some previous studies related to this research
Previous studies indicate that awareness of green marketing positively influences green consumption intentions Balderjahn (1988) found that consumers with a favorable attitude towards environmental protection are more likely to purchase and use green products Furthermore, as consumers increasingly recognize and evaluate health-related environmental issues, they become more willing to buy green products (Loudon & Bitta, 1988).
Numerous studies indicate that government initiatives play a crucial role in fostering green consumption intentions and protecting the environment To enhance public awareness of environmental safety, governments should actively promote policies that encourage environmental sustainability and provide incentives for marketers to introduce green products Pavan (2010) emphasized the importance of implementing campaigns to raise public awareness about environmental issues, which significantly influences consumers' purchasing behavior towards green products (Wahid, Rahbar & Tan, 2011).
(2006) the role of the government was an important element in establishing green product purchasing behavior
Research shows that environmental knowledge is positively associated with the intention to consume green products This knowledge influences all stages of the implementation process Studies indicate that a consumer's level of knowledge and experience significantly impacts their ability to assess and evaluate products, ultimately shaping their consumption intentions (Alba & Hutchinson).
Research has shown that knowledge about the environment significantly influences environmentally friendly behavior Consumers utilize their environmental awareness to guide their purchasing decisions regarding green products.
China (Chan & Lau, 2000) In addition, each of the results also shows that China with knowledge of the environment, would have a stronger intentions to buy green products
Following Wahid, Rahbar and Tan (2011) demonstrated that knowledge of the environment would have a significant effect on the buying behavior of green products
Previous studies have identified factors such as awareness of green marketing, government initiatives, and environmental knowledge that influence green consumption intentions However, the current study introduces additional factors affecting these intentions, supported by a comprehensive review of relevant literature Specifically, this research is grounded in three key papers that form the theoretical framework and proposed research model, with the first paper focusing on the antecedents of green brand equity in a sustainable context.
Development Perspective (Kang & Hur, 2011) The second paper is Effects of green brand on green purchase intention (Huang, Yang & Wang, 2013) And third paper is Antecedents of
Green Brand Equity: An Integrated Approach (Butt, Ng, Khong & Ong, 2013)
Kang and Hur (2011) identified four key factors influencing green brand equity: green trust, green satisfaction, green effect, and green loyalty Their research model demonstrates the interrelationships among these factors.
Figure 2: Kang and Hur (2011)’s research model
However, the Green Brand Equity variables may be not appropriated in the condition about environmental context in Viet Nam So, based on first paper, this study changed Green
The study explores the relationship between brand equity and green consumption intention, utilizing green satisfaction and green trust as foundational variables Additionally, it incorporates the attitude toward green brands, as discussed in Huang's second paper, to further understand its impact on green consumption intention.
Yang and Wang (2013) and green brand perceived value variable in third paper of Butt, Ng,
Khong and Ong (2013) are also used to do the theoretical basis for factors effecting green consumption intention in this study.
Definitions of the concepts
The definitions of the concepts in this study are following:
Attitude toward the behavior is the individual preference for one object (Ajzen, 1985)
Brand attitude is a reflection of a consumer’s preference for and overall evaluation of a brand
(Teng, as cited in Huang, Yang & Wang, 2013) In summary, according to Ajzen (1985) and
Teng (as cited in Huang, Yang & Wang, 2013) posits that a consumer's attitude toward a green brand reflects their preferences and overall assessment of the brand This attitude conveys essential information about the product's distinctive attributes and benefits, particularly its role in minimizing environmental impact and showcasing eco-friendly characteristics.
Green satisfaction encompasses various definitions and has been the subject of extensive debate It is generally understood as the sense of pleasure or gratification that consumers feel when a product or service meets their expectations, desires, and needs (Mai & Ness, as cited in Kang & Hur, 2011).
According to Chen (2009) green satisfaction is defined as “a pleasurable level of consumption-related fulfillment to satisfy a customer’s environmental desires, sustainable expectations, and green need”
Customer satisfaction with green products is a psychological response linked to the environment, occurring when their needs are fully met This satisfaction arises from a comparison between the perceived benefits and their expectations Customer expectations are shaped by shopping experiences, recommendations from friends and colleagues, and information from sellers and competitors When the actual benefits align with these expectations, customer satisfaction is achieved.
Green brand perceived value refers to a consumer's overall assessment of the net benefits derived from a product or service, weighing what is received against what is given This evaluation is influenced by the consumer's environmental aspirations, sustainable expectations, and green requirements.
Consumer perception of green brand value encompasses how a brand's marketing efforts convey its commitment to environmentally friendly practices This includes promoting products or services that positively impact the environment and minimize negative effects, as highlighted by Cherian & Jacob (2012).
According to Chen and Chang (2012a) and Cherian and Jacob (2012), the perceived value of green brands reflects consumers' overall awareness of environmentally friendly products Companies that produce green products cater to consumers' environmental desires and needs, resulting in a positive impact on the environment.
Green trust can be identified as the tendency of a customer to believe that a brand keeps its promise regarding green performance (Chaudhuri & Holbrook, as cited in Kang & Hur,
2011) In addition, Ganesan (as cited in Kang & Hur, 2011) argued that trust is a willingness to depend on another partner based on recognition of customer about ability, reliability, and benevolence
Trust is a level of the confidence that another partner would behave as expected (Hart &
Saunders, 1997) According to Rousseau et al (1998) asserted that trust is the intention to accept damages based on positive expectations of the behaviors or intentions of another
Besides, previous studies argued that trust includes three beliefs: integrity, benevolence, and ability (Blau, 1964)
This study, referencing Blau (1964) and Ganesan (as cited in Kang & Hur, 2011), defines green trust as the tendency to depend on a product, service, or brand, which is influenced by perceptions of its credibility, benevolence, and environmental performance.
Green consumption intention is defined as a consumer’s desire to purchase the product after they are aware it is a green product or green brand (Chen & Chang, 2012a; Zeithaml,
1988) Green consumption intention is a consumer’s intention or actual purchase of an environmentally friendly product or brand which they are aware of its green attributes (Oliver
& Lee, as cited in Huang, Yang & Wang, 2013)
Green consumption intention serves as a key predictor of purchase behavior, reflecting consumers' emotional responses based on their overall evaluation of a product This intention not only signifies a favorable assessment but also suggests a strong likelihood that consumers are inclined to make a purchase.
In summary, follow Chen and Chang (2012a), Oliver and Lee (as cited in Huang, Yang
According to Wang (2013) and Grewal et al (1998), green consumption intention refers to consumers' desire and ability to purchase environmentally friendly products once they become aware of their beneficial properties.
Hypothesis developing and proposed research model
Recent research indicates that positive attitudes towards green brands significantly influence consumers' intentions to engage in green consumption According to Zeithaml (1988), purchasing intention is assessed through consumer attitudes, which encompass the desire to buy, the thought of buying, and the perceived ability to purchase green products.
Research indicates that consumer attitudes significantly influence their preferences and purchasing intentions, particularly regarding green products and environmentally friendly brands (Blackwell et al., as cited in Huang, Yang & Wang, 2013).
Research in social psychology has demonstrated that consumer attitudes towards green brands can effectively predict purchasing behavior and intentions (Mostafa, 2007) Additionally, studies indicate that positive attitudes fostered by green marketing significantly influence the intention to purchase green products (Smith et al., as cited in Huang, Yang & Wang, 2013).
According to Kalafatiset et al (as cited in Huang, Yang & Wang, 2013), consumer motivation to buy green products stems from their environmentally friendly purchasing behaviors.
Some research suggests the emotional elements of a positive attitude affects the intention to buy environmentally friendly products (Smith et al., as cited in Huang, Yang & Wang,
2013) Mostafa (2007) showed that consumers’ attitude towards green brand can influence their Green consumption intention and directly affects their actual green purchase behavior
Teng (as cited in Huang, Yang & Wang, 2013) found that consumers have a positive attitude towards a specific green brand increased the green product purchase intention of consumers
To encourage customers to purchase green products, manufacturers must improve consumer attitudes by emphasizing the value of these products in terms of safety, quality, service style, and customer care A positive attitude towards green products significantly influences consumers' intention to buy them Consequently, this study suggests that favorable attitudes towards green brands positively impact green consumption intentions, supporting the first hypothesis.
H1: Attitude toward green brandis positively associated with Green consumption intention
Current research indicates that green satisfaction positively influences green consumption intentions Customer satisfaction is a widely discussed topic in marketing (Oliver, 1996) Previous studies have shown that green satisfaction significantly impacts customers' intentions to purchase green products (Mai & Ness, as cited in Kang & Hur).
2011) Besides, Chang and Tu (2005) agreed that the green satisfaction will repeat for behavioral intention
Oliver (1996) emphasized that a satisfactory shopping experience enhances consumer satisfaction and positively influences future purchase intentions Conversely, an unsatisfactory experience diminishes customer satisfaction and reduces the likelihood of future purchases He confirmed that satisfaction is a crucial component of consumer attitude, which in turn positively affects purchase intentions, establishing a strong relationship between satisfaction and intention Additionally, Oliver noted that satisfaction plays a vital role in facilitating the execution of purchase intentions.
The continue studies have also demonstrated a positive relationship between satisfaction and behavioral intention (LaBarbera & Mazursky, 1983)
Kotler (2009) highlighted that customer satisfaction significantly influences the willingness to purchase a product Despite the presence of competing brands, consumers often remain loyal to companies that offer green products, demonstrating that satisfaction with environmentally friendly options positively affects their purchasing intentions.
When considering Electrolux refrigerators and washing machines, consumers often associate the brand with high quality, smooth operation, long-term reliability, and energy efficiency These attributes not only fulfill customer needs but also enhance satisfaction, leading to a greater inclination towards purchasing eco-friendly products.
Therefore, this study made the following second hypothesis:
H2: Green satisfaction is positively associated with Green consumption intention
Recent studies indicate that the perceived value of green brands significantly influences consumers' intentions to engage in green consumption Enhancing customers' positive perceptions of green products is crucial, as it can lead to increased customer value efficiency.
According to Malik (as cited in Butt, Ng, Khong & Ong, 2013), consumer intention to purchase green products or services can be significantly improved by fostering a positive perception of their value (Chen & Chang, 2012a, b).
Green home appliances, known for their environmentally friendly features, significantly enhance brand perceived value compared to conventional appliances This aspect is crucial for companies, as they must effectively introduce and distribute green home appliances to foster a meaningful intention towards green consumption (Ottman et al., as cited in Butt, Ng, Khong & Ong, 2013).
The perceived value of green brands, characterized by their environmentally friendly features, significantly influences consumer preferences and intentions to purchase green products (Hartmann & Apaolaza-Ibanez, as cited in Butt, Ng, Khong & Ong, 2013).
According to Fornell, Johnson, Anderson, Cha and Bryant (1996) has shown that consumers was affected by perceived value when they buy products
Zeithaml (1988) identified three key indicators for assessing green consumption intention: the likelihood of consumers purchasing a product, their consideration of buying it, and their willingness to recommend it to friends and family.
Research indicates that measuring green consumption intention involves factors such as purchase possibility, purchase price, and purchase intention (Grewal et al., 1998) Consequently, the intention to engage in green consumption is influenced by the perceived value of green brands associated with a product, demonstrating a positive relationship between perceived value and consumer intentions.
Kaufman (1998) suggested that perceived value can be used to detect wishes, needs and values of customer through exchange for goods or services when making purchase intention
Perceived value is subjective perception of consumers; it is related to reactions, emotions, experience and influence to consumer behavior (Dumana & Mattilab, 2005)
Research model
This study explores the impact of consumer attitudes towards green brands on their intention to engage in green consumption It emphasizes the positive relationships between green consumption intention and four key independent variables: attitude towards green brands, green satisfaction, perceived value of green brands, and green trust The researchers argue that these four factors significantly influence consumers' intentions to adopt green consumption practices.
Researchers have discovered that consumer demographics—including income, education, age, gender, and family status—significantly impact the relationship between attitudes toward green brands, green satisfaction, perceived value of green brands, green trust, and intentions for green consumption Consequently, a research model has been proposed to illustrate these connections.
Figure 3 is recommended for a detailed description of each variable So, all hypotheses in the proposed research model are stated as follow:
H1: There is a positive relationship between Attitude toward green brand and Green consumption intention
H2: There is a positive relationship between Green Satisfaction and Green consumption intention
H3: There is a positive relationship between Green Brand Perceived Value and Green consumption intention
H4: There is a positive relationship between Green Trust and Green consumption intention
H5: Effects of Moderating Variable on relationship between Attitude toward green brand, Green satisfaction, Green Brand Perceived Value, Green trust and Green consumption intention
Income, Education, Age, Gender and Family Status
Summary
This study builds on previous research by examining key behavioral factors influencing green consumption intention, including Attitude toward green brand, Green satisfaction, Green brand perceived value, and Green trust, as identified in the works of Kang and Hur (2011), Huang, Yang, and Wang (2013), and Butt, Ng, Khong, and Ong (2013) Additionally, it explores how demographic groups impact the relationship between Attitude toward green brand and green consumption intention.
Green satisfaction, Green Brand Perceived Value, Green trust and Green consumption intention.
RESEARCH METHODOLOGY
Research design
This study used two research methods The first phase, qualitative research identified the models, factors, suitable measurement variables for research in Ho Chi Minh market
The questionnaire was developed based on previous research and underwent a pilot test to assess the clarity and effectiveness of the questions This pilot survey aimed to refine the relevant items and create a comprehensive questionnaire The second phase involved a quantitative survey, which served as the primary method for this study, focusing on identifying the factors influencing green consumption intentions The research process is detailed in Figure 4.
Define reseach problem Literature review Research model
The draft of questionnaire Pilot survey
Assessment of measurement (Cronbach alpha EFA)
Testing of hypotheses (Standard multiple regression) Discussion recommendation and conclusion
The research methodology includes both a pilot study and official research, with the pilot study employing a qualitative approach Its primary aim is to refine the questionnaires, ensuring they are more effective prior to the official research phase.
A comprehensive study utilized quantitative methods, employing questionnaires to gauge the preferences of 233 customers from an electronics supermarket and 67 customers from a new apartment complex interested in purchasing home appliances The research also assessed the green consumption intentions of a total of 300 customers regarding eco-friendly home appliance products.
Previous research scales were conducted across various cultures, economic development levels, and respondent selections, highlighting the need for a pilot study This study aimed to gather information and adjust the variables in these scales Additionally, the scales were translated into Vietnamese to ensure that respondents could easily understand the questions without confusion The pilot survey was conducted in Ho.
Chi Minh City and draft questionnaires which be translated to Vietnamese language were sent
In a pilot survey conducted with 20 customers at electronics supermarkets, feedback was collected after three days To enhance understanding, the questionnaire was modified to include Vietnamese language adjustments, specifically using italics for the revised items listed in Table 1 Additionally, a new variable for green consumption intention, labeled as GCI 25, was incorporated as question number 25 to improve the accuracy of the survey results during analysis The measurement scales for the constructs, including original, revised, and added items, are detailed in Table 1 of the pilot study.
Construct Code of variables Original Items Current revised Items
I think the funtion of the brand is more reliable than other product
I think the funtion of the brand X is more reliable than other product ATGB
I think the brand can represent my socioeconomic status
I think the brand X can represent my socioeconomic status
I think the funtion of the brand can fit my needs
I think the funtion of the brand X can fit my needs ATGB
I think the price of the brand is satisfaction for me
I'm satisfactied for price of brand X
I like the brand’s outlook I like the outlook of brand X
My friend would have a positive opinion when they discovered I Purchased this brand
My friend would have supported me when they discovered I purchased this brand X
The function of the brand is trustworthy
The function of the brand X is trustworthy
Driving car makes me feel relaxed and happy
Using brand X makes me feel relaxed and happy
You are happy about the decision to choose this brand because of its environmental commitments
I'm happy about the decision to choose this brand X because of its environmental commitments
You believe that it is a right thing to purchase this brand because of its environmental performance
I believe that it is a right thing to purchase this brand X because of its environmental performance
GS 11 Overall, you are glad to buy this brand because it is environmental friendly
I'm happy to buy this brand X because it is environmental friendly
Overall, you are satisfied with this brand because of its environmental concern
I’m satisfied with this brand X because of its environmental concern
Green brand perceived value (Chen
This brand’s environmental functions provide very good value for me
This brand X’s environmental functions provide very good value for me GBPV
This brand’s environmental performance meets my expectations
This brand X’s environmental performance meets my expectations GBPV
I purchase this brand because it is environmental friendly
I purchase this brand X because it is environmental friendly
I purchase this brand because it has more environmental benefit than other products
I purchase this brand X because it has more environmental benefit than other products
You feel that this brand’s environmental commitments are generally reliable
I feel that this brand X’s environmental commitments are generally reliable
You feel that this brand’s environmental performance is generally dependable
I feel that this brand X’s environmental performance is generally dependable
You feel that this brand’s environmental argument is generally trustworthy
I feel that this brand X’s environmental argument is generally trustworthy
GT 20 This brand’s environmental concern meets your expectations
This brand X’s environmental concern meets my expectations
This brand keeps promises and commitments for environmental protection
This brand X keeps promises and commitments for environmental protection
I would definitely intend to buy those products that are environmental friendly
I would definitely intend to buy those products of brand X that are environmental friendly
I would absolutely consider buying those products that are environmental friendly
I would absolutely consider buying those products of brand X that are environmental friendly GCI 24
I would absolutely plan to buy those products that are environmental friendly
I would absolutely plan to buy those products X that are environmental friendly
I have just only choice to buy the products that are environmental friendly
I am committed to purchasing environmentally friendly products, specifically product X A survey involving 300 customers from electronics supermarkets and new apartments was conducted, and after excluding 33 customers without a green consumption intention, the study assessed the reliability and validity of measurement scales using exploratory factor analysis (EFA) with a sample size of N=7 Ultimately, SPSS software was employed for regression analysis to test the hypotheses.
To empirically test five hypotheses, a survey with the question be made and distributed to consumers wishing and has intention to purchase green home appliances products in the
Electronics Supermarket or in the new apartment areas where consumers has intention to purchase green home appliances devices for their home
Four Electronics supermarkets and One New Apartment selected are the Nguyen Kim (NK), Thien Hoa (TH), Cho Lon (CL), Dien May Thu Duc (DMTD) and SunView Town
A total of 300 individuals were selected for interviews, comprising 233 participants from four areas in Electronics Supermarket and 67 from New Apartment The screening questions confirmed that these potential respondents are likely to purchase green home appliances in the future.
The researchers employed a five-point Likert scale for nearly all questions in their study Initially, a pilot study was conducted with a sample of 20 respondents to assess their comprehension, leading to modifications in the questionnaire for clarity A total of 300 samples were targeted, with questionnaires distributed to 233 private customers in electronics supermarkets and 67 customers in new apartments After excluding 33 samples lacking green consumption intention, the final dataset consisted of 267 valid responses for analysis.
This study presents various values from the conceptual model tested using the questionnaire provided in Appendix 1 It includes a summary of the dependent variable and the relevant independent variables As a descriptive and applied research, this study aims to propose solutions for enhancing green consumption intentions.
This quantitative study employs a large sample size to test hypotheses, utilizing a cross-sectional design Data were collected through a structured questionnaire aimed at assessing the factors influencing consumer perspectives on green home appliances.
The researchers conducted a survey to collect data using a structured questionnaire, most of the questions in the questionnaire have been passed from Patrick et al (2005), Oliver
Research by Chen (1996, 2009), Chen and Chang (2012a, b), and Chan (2001) highlights the need to address additional variables and adjust questions to align with the study's objectives and the goals of respondents This study focuses on green home appliance products, including televisions.
Sony, Daikin air-conditioning, electric cooker Happy cook,
Hatcher (1994) suggests that the minimum sample size for exploratory factor analysis (EFA) should be at least five times the number of variables, recommending a sample size of 125 for a study with 25 questions (N = 5 x 25) Furthermore, Tabachnick and Fidell (2007) outline that for regression analysis, the sample size should be calculated as NP + 15*k, where k represents the number of independent variables In this study, with four independent variables, the required sample size is 110 (NP + 15*4).
The study required a sample size of over 125 participants, which was successfully achieved with a total of 267 participants This result confirms that the study meets the necessary criteria.
Questionnaire design
3.2.1 Measurements scales of the constructs
The questionnaire utilized a five-point Likert scale ranging from 1 to 5, where 1 represents "strongly disagree" and 5 indicates "strongly agree." This study introduces five key constructs: attitude toward green brands, green satisfaction, perceived value of green brands, green trust, and intention to consume green products.
This study measures attitudes toward green brands using eight items adapted from Patrick et al (2005) Green satisfaction is assessed with four items based on the work of Oliver (1996) and Chen (2009) The perceived value of green brands is evaluated through four items adapted from Chen and Chang (2012a, b) Additionally, green trust is measured with five items from Chen (2009), while green consumption intention is assessed using three items adapted from Chan (2001) These constructs aim to analyze consumer purchasing intentions regarding green home appliances, with detailed measurement scales presented in Table 1.
A five-point Likert scale questionnaire was utilized to gather data on the research model's factors, ensuring content validity by adapting items from previous studies The measurement of constructs such as attitude toward green brands, green satisfaction, perceived value, trust, and consumption intention was based on established research methodologies, as detailed in section 3.2.1.
The questionnaires consist of two main parts:
Part 1: Collect general information to get information about the respondents who have intention to buy green home appliances This information helps select the target respondent to study
Part 2: The main information includes statements (questions) are based on a scale of measurement was proposed for the research The items were measured on the Likert 5 - point scale from 1 to 5 (1 = “strongly disagree”, 2 = “disagree”, 3 = “neutral”, 4 = “agree”, 5 “strongly agree”)
The researcher translated the survey questions from English to Vietnamese, with additional editing by others After revising and enhancing the draft questionnaire, a comprehensive set of questions was developed for interviewing 300 customers in the official research The finalized questionnaires in both English and Vietnamese are detailed in Appendix 1 and Appendix 2.
Measurement scales testing
3.3.1 Test of scales measurement reliability
Cronbach’s Alpha Test is utilized to assess the reliability of measurement scales using 5-point Likert scales, reflecting the consistency of participant responses across various items This test aids in predicting the reliability of respondents' answers, making it a valuable tool in behavioral research as an indicator of reliability (Helms, Henze, Sass & Mifsud, 2006, p.633; Liu, Wu &).
The Cronbach’s alpha is highly appropriate for this research due to the use of 5-point Likert scale measurements and its focus on consumer behavior This study utilizes Cronbach’s alpha to assess the reliability of measurement scales, which are derived from factor analysis According to Nunnally (1978), this method is essential for ensuring the consistency of the factors identified.
Cronbach’s alpha should be at least 0.7 to make sure that the measurements are reliabled
Many statisticians consider a Cronbach’s alpha value above 0.6 to be acceptable (Shelby, 2011, p.143) Additionally, it is crucial to evaluate the corrected item-total correlations when utilizing the Cronbach’s alpha index, with a recommended threshold of 0.3 or higher for these correlations (Shelby, 2011, p.143).
This research establishes that an acceptable Cronbach’s alpha range is between 0.7 and 0.8, with a corrected item-total correlation index of 0.3 or higher These criteria are applied to assess the measurements of green consumption intention behaviors among new customers in the Ho Chi Minh market.
Moreover, the accepted significant level of the F-test in Cronbach’s alpha technique is not more than 0.05 The Cronbach’s alpha test is finished by SPSS software
This study employs Exploratory Factor Analysis (EFA) to identify the underlying factors influencing green consumption intentions, as measured by questions 22 to 25 of the questionnaire EFA is utilized to streamline the questionnaire by eliminating items that do not satisfy the analysis criteria.
(O’brien, 2007, p.142) In this case, EFA is utilized to test the hypotheses shown in the research model of Chapter 2
In this research, the following criteria of the exploratory factor analysis are applied
Factor loadings represent the correlations between each item and its corresponding factor, with values exceeding 0.5 indicating practical significance in exploratory factor analysis (EFA) when the sample size is 100 (Hair et al., 1998) Additionally, the Kaiser-Meyer-Olkin (KMO) measure, total variance explained, and eigenvalues are crucial metrics in assessing the adequacy and effectiveness of the factor analysis.
The Kaiser-Meyer Olkin Measure of Sampling Adequacy (KMO) presents the level of suitability of using EFA for the collected data The KMO should be between 0.5 and 1.0
(significant level less than 0.005) to make sure that factor analysis is suitable for the data (Ali,
According to Zairi & Mahat (2006), the total variance explained is crucial for determining the number of factors to retain in a study Factors should be retained until the last one accounts for a minimal portion of the explained variance, with a recommendation that the total variance explained exceeds 50% (Hair et al.).
1998, p.111) Eigen-value is an attribute of factors, being defined as the amount of variance in all items (variables) explained by a given factor Eigen-value should be greater than 1 because
Eigen value is less than 1 means that information explained by the factor is less than by a single item (Leech, Barrett & Morgan, 2005, p.82) The EFA is done by SPSS software.
Hypothesis testing
This research utilized a comprehensive set of variables, necessitating separate exploratory factor analyses (EFA) for independent and dependent variables To confirm the correlation between the dependent variable and each independent variable, it was essential to test these relationships The results of the separated EFA were deemed acceptable and meaningful According to Pallant (2011), Pearson correlation coefficients (r) range from -1 to +1 and should ideally be less than 0.7.
Regression analysis, as described by Leech, Barrett, and Morgan (2005), serves as a statistical tool to assess the relationships between variables and their consumption intentions The author gathered data on various variables and utilized regression to estimate the impact of independent variables on dependent variables Researchers employed adjusted R², which is typically lower than unadjusted R², to indicate the percentage of variance that can be predicted from the independent variable, with adjustments influenced by sample size and magnitude Additionally, the author applied the F-test to evaluate the significance of the model, presenting hypotheses H0 and H1 accordingly.
H0: ò1 = ò2 = … = òk = 0 (no linear relationship) H1: at least one òi ≠ 0 (at least one independent variable affects Y)
If p-value 0.5, alongside assessments of convergent and discriminant validity Convergent validity is confirmed when items exhibit high loadings (loading > 0.5) on their respective factors Additionally, the KMO (Kaiser-Meyer-Olkin) test and Bartlett's test were employed to evaluate the compatibility of the sample.
Exploratory factor analysis (EFA) was employed to examine the behavioral variables influencing consumption intention, aiming to identify the factors affecting these variables The prerequisites for conducting factor analysis were outlined in Chapter.
After several rounds of eliminating unsuitable items, the analysis revealed that the remaining items could be categorized into five variables, consisting of four independent variables and one dependent variable.
As mentioned in chapter 3, The KMO should be greater than 0.5 and the Bartlett test should be significant (significant level less than 0.05) Factor loading is greater than or equal
0.5 So, if items that had factor loadings were less than 0.5, they were deleted The total variance explained was suggested to be more than 50% (Hair et al., 1998, p.111) Absolute values of different between loadings are equal or greater than 0.3 Eigen-value should be greater than 1 because Eigen-value is less than 1 means that information explained by the factor is less than by a single item (Leech, Barrett & Morgan, 2005, p.82)
The results of the Exploratory Factor Analysis (EFA) indicated a KMO value of 0.748, exceeding the threshold of 0.5, and a total variance explained of 72.817%, which is greater than 50% This suggests that the factor loading is appropriate for the survey data Additionally, the Bartlett's test showed a significance level of 0.000, which is less than 0.05, confirming that the items are sufficiently correlated to justify the use of factor analysis.
The factor analysis results indicate that the green satisfaction variable and the green brand perceived value variable are not distinct and should be merged To align with the rotation matrix, certain items in the Pattern Matrix, specifically ATGB 01, ATGB 06, ATGB 08, GS 11, GS 12, and GBPV 15, need to be removed.
The items GBPV 16, GT 20, GCI 22, and ATGB02 should be deleted based on the analysis of Cronbach's alpha in the main study Additionally, the details of the KMO, Bartlett's Test, and Pattern Matrix from the factor analysis conducted at time 1 are provided in Appendix 3.3.
4.2.3 Factor analysis (EFA) round time 2
After deleting items including ATGB 01, ATGB 02, ATGB 06, ATGB 08, GS11, GS
12, GBPV 15, GBPV 16, GT 20, GCI 22, results presented that KMO = 0.727>0.5, Bartlett
Significant level was 0.000 (< 0.05) Factor loadings were ≥ 0.5, all items were greater than
0.5 Therefore factor loading was suitable for data of survey After running factor analysis, the result of Pattern Matrix in table 4 was presented as below:
Table 4: Pattern Matrix in Factor analysis (EFA) round time 2
The results presented in Table 4 of the Pattern Matrix indicate that all items exhibited loadings greater than 0.3, leading to their acceptance Furthermore, all items related to green satisfaction (GS) and green brand perceived value (GBPV) were found to be interconnected.
The ATGB05 item, which measures attitudes toward green brands, shares similar content with all GS and GBPV items, indicating a strong integration among these variables Detailed results, including KMO, Bartlett's Test (time 2), and the Pattern matrix, can be found in Appendix 3.4.
Following the completion of the exploratory factor analysis (EFA) at time 2, this study has derived new variables The independent variables have been renamed to reflect their new designations: the green satisfaction variable (GS) and the green brand perceived variable (GBPV), which have been integrated into a cohesive framework.
Gsatistion2 Second, new name for independent variable of GT items (green trust variable) is
The study introduces new terminology for its variables, renaming the independent variable related to attitude toward green brands as GAtitude2 and the dependent variable concerning green consumption intention as Gconsump2 Following a thorough factor analysis, these components were utilized for regression analysis Additionally, the research model has been updated to reflect the integration of green satisfaction and green brand perceived value variables, as illustrated in Figure 5.
Green Satisfaction and Green brand perceived value
Moderating Variable: Income, Education, Age, Gender and Family Status
The revised research model in Figure 5are stated as follow:
H1: There is a positive relationship between Attitude toward green brand and Green consumption intention
H2: There are a positive relationship between Green Satisfaction, green brand perceived value and Green consumption intention
H3: There is a positive relationship between Green Trust and Green consumption intention
H4: Effects of Moderating Variable on relationship between Attitude toward green brand, Green satisfaction, Green Brand Perceived Value, Green trust and Green consumption intention
*** Correlation is significant at the 0.01 level (2-tailed)
According to Pallant (2011), Pearson correlation coefficients (r) range from -1 to +1 and should be less than 0.7 In this study, with a sample size of 267 cases, the positive correlation values indicate that as one variable changes, the others tend to change in the same direction The Pearson correlation coefficients between the dependent variable (Gconsump2) and independent variables (Gsatisfaction2, Gtrust2, GAttitude2) were all below 0.7, demonstrating significant correlations while remaining distinct enough to avoid merging Consequently, the separate exploratory factor analysis (EFA) results for dependent and independent variables were deemed acceptable The validity and reliability of the measurement scales in the research model were confirmed through EFA and Cronbach’s Alpha Reliability Analysis, with detailed correlations of the new variables provided in Appendix 3.5.
Hypotheses testing using multiple regressions
4.3.1 Checking assumption of Multiple Regression
Multiple regression analysis is an advanced form of correlation that predicts a dependent variable based on multiple independent variables Its primary purpose is to test models and hypotheses, providing insights into the overall model and the relative significance of each contributing factor Two crucial statistical measures in this analysis are the squared multiple correlation coefficient (R) and the standardized coefficient weight (beta weight).
The R value indicates the proportion of variance in the dependent variable, specifically green consumption intention, that is explained by the predictor variables in the model In contrast, the beta value reflects the significance of each independent variable in predicting the dependent variable Both R and beta values range from 0 to 1.0, with values closer to 1.0 indicating better predictive power A summary of the multiple regression analysis is presented in Table 7.
Model R R Square Adjusted R Square Std Error of the Estimate
Table 6 presents the R Square and Adjusted R Square values, which indicate the extent to which the model accounts for the variance in the dependent variable, green consumption intention A high R value signifies a successful model with a significant level of variance explained.
R square value have a propensity to somewhat overrate the success of the model when applied to the real world scenario
The Adjusted R Square value provides a more correct estimate measure of the success of the model In case, the R square value 119 and the Adjusted R Square was 109 There was
11.9 percent of the variance in the green consumption intention of dependent variable explained by the model To better depict a true estimate the Adjusted R Square indicated that the model explains 10.9% of the variance in the dependent variable
From the Anova Table 07, the significance of the result was 000, this means p < 05, so the significance of the model was available
The tolerance indicators ranged from 749 to 895, exceeding the required threshold of 10, while the VIF values, which are the inverse of tolerance, remained below the acceptable limit of 2 This indicates that multicollinearity among the independent variables is not a concern.
Model Sum of Squares df Mean Square F Sig
Total 266.000 266 a Predictors: (Constant), GAttitude2, Gtrust2, GSatistion2 b b Dependent Variable: GConsump2
Table 08 displays the significance coefficient and the standardized beta coefficient, indicating the unique contribution of each independent variable to the model while controlling for other predictors A higher value suggests that the corresponding variable significantly impacts the model.
The primary factor influencing Gconsump2 is GAttitude2, which has the highest Beta value of 284, indicating a strong predictive relationship Additionally, Gtrust2 also contributes to explaining the Gconsump2 dependent variable, with a Beta value of 128.
However, GSatistion2 (include Green satisfaction and Green brand perceived value) has the smallest Beta 020, so it is not supported to predict Gconsump2 dependent
The t and Sig (p) values indicate the statistical significance of each independent variable in predicting the dependent variable A large absolute t value and a small p value (p ≤
.05) points out that a predictor variable is significant in predicting the dependent variable
From the result of the analysis (Table 08), GSatistion2 (t = 295 and p = 768), Gtrust2 (t 1.964 and p =.051) and GAttitude2 (t = 4.639 and p = 000) are significant factors in predicting Green consumption intention
As a result, significant level of GSatistion2 (0.768) was greater than 0.05, hence it had no significance in the research It meant that the findings did not support the hypotheses
H2(Green Satisfaction & Green Brand Perceived value has melding together) In contrast, significant level of Gtrust2 was signed as 0.051, this significant level could be accepted
B Std Error Beta Tolerance VIF
The analysis revealed a significant positive relationship between green trust and green consumption intention, supporting hypothesis H3 The findings indicated that the significance level was well below 0.05, confirming the impact of green trust on consumers' intentions to engage in environmentally friendly consumption.
GAttitude2 was 0.000 ( p ≤ 0.05) was satisfied requirement and had significance in the study
As a result, the findings supported the hypothesis H1 that Attitude toward green brand influenced on Green consumption intention The detail of regression presented in appendix
The study examined the accuracy of predictions by testing a linear relationship between independent variables, such as Gsatisfaction2, Gtrust2, and GAttitude2, and the dependent variable Gconsump2.
Almost of them have linear relationship together via straight line
Second, assumption was no multicollinearity that was mentioned above In the regression analysis, all of variables including Gsatisfaction2, Gtrust2 and GAttitude2 and
The analysis revealed no multicollinearity in Gconsump2 Both Gtrust2 and GAttitude2 were accepted due to their significant levels being below 0.05 In contrast, Gsatisfaction2 was not accepted as its significant level exceeded 0.05 Further details can be found in Appendix 3.6.
The normality test indicates that if the p-value is less than or equal to 0.05, the null hypothesis (H0) is rejected; conversely, if the p-value is greater than 0.05, H0 is accepted Consequently, the findings related to the three hypotheses outlined in Chapter 4 are summarized in Table 09 below.
Table 9: Results of hypothesis test
H1 Attitude toward green brand is positively associated with Green consumption intention Supported
H2 Green satisfaction and Green brand perceive value are positively associated with Green consumption intention Do not support
H3 Green trust is positively associated with Green consumption intention Supported
Test the effect of moderating variables
This study examines the impact of moderating variables, including gender, age, education, income, and family status, on the relationship between independent and dependent variables in hypothesis 4, as illustrated in Figure 5 of the revised research model.
4.4.1 Test the moderating of gender:
Table 10: Comparison of coefficients related gender: Female
Unstandardized Coefficients Standardized Coefficients t Sig
B Std Error Beta Tolerance VIF
The analysis reveals that GSatistion2 (t = -0.331, p = 0.741) does not significantly influence green consumption intention, as its p-value exceeds 0.05, indicating that female gender does not impact the relationship between green satisfaction, perceived value, and consumption intention Conversely, Gtrust2 (t = 1.942, p = 0.054) and GAttitude2 (t = 3.142, p = 0.002) are significant predictors, with Gtrust2 being slightly above the threshold at 0.054, while GAttitude2 is significantly lower at 0.002 This suggests that female gender positively affects the relationship between green trust, attitude toward green brands, and green consumption intention.
Table 11: Comparison of coefficients related gender: Male
B Std Error Beta Tolerance VIF
The analysis reveals that GSatistion2 (t = 674, p = 501) and Gtrust2 (t = 823, p = 412) are not significant predictors of green consumption intention, as their p-values exceed 0.05 This indicates that male gender does not influence the relationship between green satisfaction, green brand perceived value, and green trust with green consumption intention Conversely, GAttitude2 (t = 3.467, p = 001) is a significant factor, with a p-value below 0.05, suggesting that male gender positively affects the relationship between attitude toward green brands and green consumption intention.
The findings indicate that females exhibit a stronger intention for green consumption compared to males Specifically, females demonstrate a positive relationship between their attitude toward green brands, green trust, and green consumption intention, while males only show a positive relationship between their attitude toward green brands and green consumption intention Detailed results for gender groups can be found in Appendix 3.7.
4.4.2 Test the moderating of Age
Table 12: Comparison of coefficients related Age: 35
B Std Error Beta Tolerance VIF
The analysis results indicate that GSatistion2 (t = 793, p = 429) and Gtrust2 (t = 1.832, p = 0.69) are not significant predictors of green consumption intention, as their p-values exceed 0.05 This suggests that customers over 35 years old do not influence the relationship between green satisfaction, green brand perceived value, and green trust with green consumption intention In contrast, GAttitude2 (t = 2.680, p = 008) is a significant factor, with a p-value below 0.05, indicating that customers older than 35 have a positive effect on the relationship between their attitude toward green brands and green consumption intention.
The analysis reveals a positive relationship between attitudes toward green brands and green consumption intentions for both age groups: those aged 35 and younger, and those older than 35 Detailed results for these age groups can be found in Appendix 3.8.
4.4.3 Test the moderating of Family status
Table 14: Comparison of coefficients related family status: Single
B Std Error Beta Tolerance VIF
The analysis results indicate that GSatistion2 (t = 5.168, p = 000) and GAttitude2 (t = 4.404, p = 000) are significant predictors of green consumption intention, while Gtrust2 (t = 1.108, p = 270) is not significant The significant levels of GSatistion2 and GAttitude2 are both below 0.05, highlighting their importance in influencing the relationship between green satisfaction, perceived value of green brands, and attitudes toward green brands.
Green consumption intention However, significant level of Gtrust2 (.270) was higher than
0.05 So, the group of single don’t effect relationship between green trust and Green consumption intention
Table 15: Comparison of coefficients related family status: Married
B Std Error Beta Tolerance VIF
The analysis results indicate that GSatistion2 (t = 0.232, p = 0.817) and Gtrust2 (t = 0.341, p = 0.734) are not significant predictors of green consumption intention, as their p-values exceed the 0.05 threshold In contrast, GAttitude2 (t = 2.093, p = 0.038) is a significant factor Consequently, the marital status of individuals does not influence the relationship between green satisfaction, green brand perceived value, and green trust.
Green consumption intention However, significant level of Gattitude2 (.038) was lower than
0.05 So, the group of married has positively effect relationship between attitude toward green brand and Green consumption intention
Singles exhibit a stronger intention for green consumption compared to married individuals This is evidenced by the positive relationships between their attitudes toward green brands, green satisfaction, perceived value of green brands, and their overall intention to engage in green consumption.
Married has only positively effect relationship between attitude toward green brand and Green consumption intention.The detail results of family status groups have shown in appendix 3.9
4.4.4 Test the moderating of Education
The statistical analysis revealed that the sample sizes for the bachelor group (125 samples) and the combined bachelor and master group (142 samples) are not equivalent, making regression analysis unsuitable for comparing the effects of these groups on the relationship between customer behavior and green consumption intention Consequently, the study calculated the average of three variables—GCI 23, GCI 24, and GCI 2—to create a new variable related to education The mean coefficient of this new variable was then analyzed to assess its influence on green consumption intention, with the results summarized in Table 17.
Table 16: Mean related Education of 267 samples
N Minimum Maximum Mean Std Deviation
The results in table 16 shows that mean coefficient of total 267 samples with GCI 23 is 3.78, GCI 24 is 4.01, GCI 25 is 4.01, Intention is 0.0712
This study calculated the mean coefficient for various education groups, specifically those with less than a bachelor's degree and those with a bachelor's to master's degree The findings are detailed in Tables 17 and 18 below.
Table 17: Mean related education: under Bachelor groups with 125 samples
N Minimum Maximum Mean Std Deviation
The results in Table 17 shows the groups of under Bachelor education with GCI23 is 3.61, GCI 24 is 3.79, GCI 25is 3.81, Intention is 0.008
Table 18: Mean related education: Bachelor and Master groups with 142 samples
The results of Table 18 shows the groups of bachelor and master education with GCI 23 is 3.93, GCI 24 is 4.20, GCI 25 is 4.18, Intention is 0.1268
A comparison of the mean coefficients reveals that individuals with bachelor's and master's degrees exhibit a higher intention for green consumption than the overall average for all education groups Conversely, those with education levels below a bachelor's degree show lower mean coefficients than the total education group Detailed results for each education group can be found in Appendix 3.10.
4.4.5 Test the moderating of Income
N Minimum Maximum Mean Std Deviation
Similarly educated groups, income groups have also no equivalent Such as Incomce ≤
12 million is 79 customers, Income >12 million is 188 customers So, the study was also calculated the average total of 3 variables GCI 23, GCI 24, GCI 25 to create a new variable is
Intention2 relating to Income, then using the mean coefficient to analyze their influence to green consumption intention The mean coefficient results of total income groups as table 19
Table 19: Mean related Income of 267 samples
The results in table 19 shows that mean coefficient of total 267 samples with GCI 23 is 3.78, GCI 24 is 4.01, GCI 25 is 4.01, Intention2 is 0.0974
Besides, this study has also calculated mean coefficient for every income groups with low income groups and high income groups The results were presented in tables 20 and 21 as below:
Table 20: Mean related low income groups: ≤ 12 million with 79 samples
N Minimum Maximum Mean Std Deviation
The results of Table 20 shows that mean coefficient of low income groups with GCI 23 is 3.52, GCI 24 is 3.58, GCI 25 is 3.59, Intention2 is 0.0127
Table 21: Mean related high income groups: >12 million with 188 samples
N Minimum Maximum Mean Std Deviation
The results of Table 21 shows that mean coefficient of high income groups with GCI 23 is 3.89, GCI 24 is 4.19, GCI 25 is 4.18, Intention2 is 0.1330
A comparison of the mean coefficients reveals that high-income groups exhibit higher mean coefficients than the overall total income groups, while low-income groups show lower mean coefficients This indicates that individuals with higher incomes demonstrate a greater intention for green consumption compared to those with lower incomes Detailed results can be found in Appendix 3.11.
Normality, linearity, homoscedasticity and outliers
The shape of Histogram in figure 6 in Appendix 3.12 showed a reasonable normal distribution of all variables with mean was approximately 0 and the standard deviation
(Std.Dev.) was about 0.994 Hence the assumption about normality was not violated
Additionally, in the Normal Probability Plot (P-P) of the Regression Standardized Residual, most of scores concentrated in the center and along the 0 point (see Figure 7 in Appendix 3.12)
The Scatterplot in Figure 8 (Appendix 3.13) indicates that outliers predominantly fall within the range of -3 to +3, suggesting a lack of homoscedasticity The standardized residuals exceeded ±0.3 standard deviations, yet the analysis revealed no significant outliers or influential points, thereby satisfying the assumptions of the study.
The graphs illustrating the normality test of the residuals can be found in Appendix 3.12 The final assumption confirmed the normality of the residuals, indicating that multiple linear regression is suitable for the sample data, as all assumptions for this analysis were met.
N Minimum Maximum Mean Std Deviation
Valid N (listwise) 188 regressions were met, the regression results were analyzed further to test the hypotheses of this research.
Discussions
The study concludes by addressing all research questions outlined in Chapter 3, confirming that the research objectives have been met and the hypotheses, along with the moderating variable, have been tested The subsequent section presents the conclusions drawn from the study's results.
The hypothesis test results from the revised research model indicate that two hypotheses, H1 and H3, are supported, while H2 is not Specifically, H1, which examines the relationship between attitude toward green brands, shows a beta of 0.284 with t = 4.639 and significance (sig) = 0.000 H3, related to green trust, has a beta of 0.128, t = 1.964, and sig = 0.051 Both H1 and H3 are significant at the p ≤ 0.05 level, with H1 demonstrating a stronger support due to its higher t-value and lower significance level compared to H3 Additionally, previous studies corroborate these findings, as both the attitude toward green brands and green trust variables were also significant at p ≤ 0.05, meeting the required standards Thus, the current study's results align with prior research, reinforcing the support for hypotheses H1 and H3.
Research indicates that the hypothesis linking Green satisfaction and Green Brand Perceived Value to Green consumption intention is not supported in Vietnam, where green home appliances are still developing Although these eco-friendly products promote energy savings and environmental safety, their higher prices compared to conventional products pose a challenge Analysis shows that customers with higher incomes are more inclined to purchase green home appliances than those with lower incomes.
Bachelor and master education are more intention to buy green home appliances products than
Customers with low income and those with less than a bachelor's education tend to resist green consumption due to high prices and a lack of awareness regarding the value of green products Consequently, these groups do not support hypothesis 2.
The samples of low-income and high-income groups, as well as those with under Bachelor education compared to Bachelor and Master education groups, differ significantly To assess the impact of these groups on green consumption intention, mean analysis is employed to compare the intention to purchase green home appliances across various education and income levels However, this method falls short in examining the intricate relationships between green satisfaction, perceived value of green brands, trust, attitude towards green brands, and green consumption intention, which can be better analyzed using regression analysis that considers factors such as gender, age, and family status.
Summary
The analysis of results highlights how customer factors influence green consumption intentions This study examines the impact of demographic groups, including gender, age, education, income, and family status, on the relationship between independent and dependent variables.
The reliability of the analytical results was assessed using Cronbach's Alpha coefficients for the factors in the research model To enhance reliability, the item ATGB 02 was removed, along with several other items, to align with the EFA matrix.
The study analyzed various variables, including ATGB 06, ATGB 08, GS11, GS 12, GBPV 15, GBPV 16, GT 20, and GCI 22 Factor analysis was conducted, resulting in new variables named Gsatisfaction2, Gtrust2, and Gconsump2 for regression analysis Additionally, the impact of education and income groups on green consumption intention was assessed by calculating the average of three items—GCI 23, GCI 24, and GCI 25—leading to the creation of new variables related to these groups, termed Intention.
This study employs regression analysis to examine the relationship between independent and dependent factors, specifically focusing on the effects of gender, age, family status, education, and income groups on green consumption intention Hypothesis 4, illustrated in figure 5, is tested through both regression and mean analysis to assess how these demographic variables influence sustainable consumer behavior.