Green Emotion: Incorporating Emotional Perception in Green Marketing to Increase Green Furniture Purchase Intentions

Abstract

The industrialization process has led to environmental deterioration, which has created challenges for sustainable development. However, there is an increasing inclination to purchase green furniture as a sustainable form of furniture. Hence, investigating the determinants of consumers’ intention to purchase green furniture is beneficial for promoting the adoption of sustainable furniture. Previous research has examined the functional aspects of purchasing behavior using the theory of planned behavior (TPB), while giving less consideration to affective elements. This study aimed to investigate the factors that influence the intention of future users to purchase green furniture, explicitly focusing on emotional perception. This study utilized the PAD three-dimensional emotion model. A novel conceptual model was developed, drawing upon the findings of the literature review. This study employed the questionnaire method to collect data, resulting in 412 valid samples. The collected data were then analyzed and processed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS 3.0 software. Additionally, the mediating influence of the variables was examined using the bootstrap method. The results suggested that the perceived pleasure, arousal, and dominance all had a substantial influence on the beneficial effect of green furniture elements on purchase intention. Among these factors, pleasure (PP) had the strongest mediating effect on the relationship between green brand image (GBI) and purchase intention (PI). Arousal (PA) had the strongest mediating effect on the relationship between eco-innovation (EI) and purchase intention (PI). Dominance (PD) had the strongest mediating effect on the relationship between purchase customization (PC) and purchase intention (PI). Furthermore, this paper examined the disparities between the characteristics of green furniture and conventional furniture in terms of their ability to stimulate emotional responses and influence consumers’ intention to purchase. This study revealed that green features (GF) have a greater capacity to evoke emotional responses in consumers, consequently impacting their intention to purchase green furniture. The study’s findings have both theoretical implications and practical relevance. In theory, these findings enhance the theoretical framework of purchase intention for green furniture. In practice, they provide specific ideas and recommendations for green furniture companies to develop emotional marketing strategies.

1. Introduction

Anthropogenic industrial activities release excessive amounts of greenhouse gases, such as carbon dioxide and methane. These emissions significantly alter the physical and chemical qualities of soil, air, and salt water. Furthermore, they contribute to unforeseen climate shifts, including famines, severe thunderstorms, and rising temperatures [1]. Scientists believe that human activities contribute to global warming, which might increase the global temperature by around 10 °C. The rate of anthropogenic global warming is expected to grow by 0.2 °C per decade, with a range of 0.1 to 0.3 °C [2]. As a result, environmental issues are becoming increasingly important and complicated. Ecological sustainability is gaining traction as customers become more environmentally sensitive and industrialization accelerates. The furniture business is seeing the rise of sustainable materials and eco-friendly designs due to increased awareness regarding the environmental problems caused by manufacturing and consumption [3]. As a result, there has been a recent surge in the popularity of green furniture.

Over the last ten years, furniture sales in China have increased significantly. In 2018, the Chinese furniture market was valued at CNY 900 billion. Sustainable furniture, sometimes called ‘green furniture’, is a critical emphasis for the future development of China’s furniture sector [4]. Green furniture requires eco-friendly raw materials, ecologically conscious disassembly design, environmentally friendly clean production practices, and green packing materials, among other things. Simply put, it reduces furniture’s environmental and natural impact at every stage of its life cycle, from raw material selection to design, production, packaging, sales, consumption, disposal, and recycling. Furthermore, it poses no hazards to the safety of either customers or employees [5]. The manufacturing process combines environmental concerns to reduce its negative impact on human health and the environment [6]. Innovative designs, long-lasting construction, and ecological friendliness define green furniture. Green design elements are integrated throughout the product’s life cycle, from design to manufacture, use, and recycling. This integration seeks to improve the quality of furniture design and production, revolutionize the traditional furniture business, meet the growing customer demand for eco-friendly furniture, and promote the harmonious coexistence of humans and nature [7].

Consumers can contribute to a more sustainable and eco-friendly future by buying environmentally conscious products and practicing responsible consumption [8]. The consumer buying process involves a series of stages, from recognizing needs to post-purchase assessment [9]. Van (2013) [10] categorized the buying process into five phases: activation, configuration, browsing, purchase, and decision, excluding post-purchase review. Consumers undergo these stages at varying rates based on individual traits, situational influences, and product types [11]. Consumers engage in a complex cognitive process involving a sequence of emotional impressions while making purchase decisions. Emotional perception entails recognizing emotional states in behavior or surroundings, encompassing emotions, attitudes, emotional intents, and behavioral displays [12], as seen in Figure 1.

Yu et al. (2023) [13] investigated the effects of individual psychological and trait factors on customer purchasing decisions, behaviors, and preferences. This study’s findings showed that psychological aspects influence consumers’ purchasing decisions. Most prior researchers used the Theory of Planned Behaviour, a model biased toward functional rationality, to investigate the intention to purchase green furniture. However, this research has yet to explore its psychological or emotional impact. As a result, this work addresses the research gap. This article divides emotional perception variables into green and traditional aspects. We use the PAD (pleasure, arousal, and dominance) emotional model to examine how emotional perception affects potential users’ intentions to buy green furniture. The goal is to find specific aspects of green furniture that potential customers value, hence increasing the popularity and sales of green furniture. Examining the impact of emotional perception on the intention to buy environmentally friendly furniture can help researchers to better understand consumers’ psychological characteristics during the shopping process. This analysis will help marketers to design a marketing plan for green furniture by examining the critical emotional elements influencing the chance of acquiring such products. The relevant data were analyzed using partial least squares structural equation modeling (PLS-SEM) and SmartPLS 3.0 software. Partial least squares structural equation modeling (PLS-SEM) is a statistical tool for measuring and investigating the relationship between observable and latent variables. This method, like regression analysis, but with greater statistical power, can analyze linear causal relationships between variables. This study investigates the following inquiries.

• How do green furniture’s green and traditional characteristics affect consumers’ emotional perceptions?
• How do consumers’ emotional perceptions, specifically their perceived pleasure, arousal, and dominance, influence their intentions to purchase green furniture?
• Does PAD 3D significantly mediate the relationship between green furniture characteristics and green purchase intentions?
• Is there a notable distinction between green furniture’s green and conventional characteristics in terms of evoking an emotional reaction from consumers and their inclination to make a purchase?
• Do consumers’ demographic variables, such as gender, age, and educational background, have varying emotional effects on their inclinations to purchase green furniture?

2. Literature Review

Research has demonstrated the feasibility of integrating structural equation modelling with the PAD emotional model in past studies. By conceptually applying the PAD (pleasure, arousal, and dominance) three-dimensional emotional model to analyze the emotional aspects of brand applications, Hsieh et al. (2021) [14] investigated the factors influencing brand application ambience in brand relationships. Using the PAD three-dimensional emotional model, Cho and Lee (2017) [15] examined how interior color choices affect consumer emotions, preferences, and perceptions of luxury products in an upmarket retail environment. Yang and Kim (2020) [16] employed the PAD model to investigate how website attributes impact the emotional strain process of a fashion brand, along with the three emotion dimensions that mediate the influence of fashion brand website behavioral reactions. All of the publications above used a blend of the PAD emotional model and structural equations to investigate factors empirically. Wei et al. (2023) [17] studied how interior colored illumination in rural homes impacts individuals’ moods and visual perceptions. The experimental results were analyzed statistically using the PAD emotional model mapped to eight primary emotions to construct an emotion dimension model. The PAD emotional model analyzes the aspects that impact consumers’ emotional perception.

Prior studies have thoroughly examined the factors influencing people’s desire to make environmentally friendly purchases. Several studies have looked into the impact of social media on adolescents’ intentions to buy ecologically friendly products, taking into account aspects like subjective norms and perceived green values (Xie and Madni 2023 [18]). Another study examined how a green brand image and customer environmental views influence the relationship between green marketing and green purchasing intentions (Majeed et al., 2022 [19]). Another study also investigated the function of customer attention as a mediator between environmental concerns, environmental knowledge, green product eco-innovation, and green purchase intention (Moslehpour et al., 2023 [20]). Using the idea of the planned behavior model as a framework, Xu et al. (2020 [21]) investigated the factors influencing consumers’ propensity to purchase authentic green furniture. Finally, a study evaluated the factors influencing Da Nang residents’ decisions to buy environmentally friendly furniture using the theory of planned behavior and its modifications (Le and Quang, 2023 [3]). Klabi and Binzafrah (2022) [22] conducted the first study of the sequential mediation model, which included environmental concern, self-conformity to a green image, faith in a green brand, and desire to engage in green purchasing. However, past research on green furniture mainly focused on the intention to purchase as a deliberate activity and used utility-oriented models. Only a few studies have looked into the emotional and perceptual components of selecting green furniture.

This investigation offers significant theoretical insights. In their study, Yu et al. (2023) [23] examined the primary determinants of consumer furniture purchases using hierarchical analysis. They found that product indicators were the most significant elements, followed by personal and service factors. This paper also includes individual traits, qualities of the product, and socio-cultural influences. Based on prior research, the elements that influence the intention to purchase green furniture may be categorized into green qualities and traditional characteristics, as illustrated in

Table 1. Factors influencing emotional perception (EP).

Items	Indexes
Green Feature (GF)	Environmental Awareness (EA)
	Eco-Innovation (EI)
	Perceived Green Value (PGV)
	Green Brand Image (GBI)
Traditional Characteristics (TC)	Aesthetic Design (AD)
	Purchase Customisation (PC)
	Perceived Consumer Effectiveness (PCE)
	Subjective Norms (SN)

. This study utilizes the PAD three-dimensional emotional model to examine how specific characteristics influence purchase intention through three-dimensional affective mediation. It also aims to compare the differences in the influencing mechanism between green and traditional characteristics. Additionally, this study conducts a multi-cluster structural equation analysis of consumers’ demographic characteristics. This study aims to enhance consumers’ satisfaction with environmentally friendly furniture and their intention to make more environmentally friendly purchases.

3. Theoretical Framework and Research Hypotheses

3.1. PAD 3D Emotional Model

Mehrabian and Russell (1974) [24] introduced a concept revolving around three emotions: pleasure, arousal, and dominance (PAD). The PAD three-dimensional emotional model classifies human emotions into three fundamental categories. Pleasure (P) represents emotional variability and measures how an individual experiences happiness, joy, or contentment in their surroundings. Arousal (A) refers to emotional arousal, indicating how excited, alert, or active an individual feels. Dominance (D) reflects emotional regulation and the sense of autonomy in a given setting [25], contributing to a three-dimensional model of emotional behavior as depicted in Figure 2. This research examines the aspects of emotional perception, which encompass pleasure (PP), arousal (PA), and dominance (PD). Meanwhile, as summarized by the Institute of Psychology of the Chinese Academy of Sciences [26], the Chinese version of the PAD scale measures pleasantness in this article through the emotions of ‘interested’, ‘friendly’, ‘happy’, and ‘pleased’. Arousal is quantified based on the emotional states of ‘excited’, ‘relaxed’, and ‘awake’. Dominance is quantified based on the emotional states of ‘in control’, ‘in charge’, ‘in control’, and ‘in control’. Dominance is assessed based on the presence of ‘dominant’, ‘dominating’, and ‘affected’ emotions.

3.2. Perceived Pleasure Factor

3.2.1. Perceived Green Value

‘Perceived green value’ is defined by Patterson and Spreng (1997) [27] as ‘the consumer’s overall assessment of the net benefits of a product or service based on the consumer’s environmental desires, sustainability expectations, and green needs’. Research has shown that when consumers are aware of the environmental features and extra value of a product, it triggers positive emotional responses such as satisfaction and happiness, which may enhance their positive affective experience of the product [28]; in addition, perceived green value can also trigger consumers’ self-identity, as they perceive the purchase of green furniture as environmentally responsible behavior, generating a positive affective experience that further enhances the level of perceived pleasure the degree of perceived pleasure [29]. Meanwhile, previous studies have shown that customers’ perceived green value significantly influences green purchase intention and loyalty [30,31].

Hypothesis 1 (H1).

Perceived green value (PGV) and perceived pleasure (PP) are positively correlated.

3.2.2. Green Brand Image

The term ‘green brand image’ refers to a distinct collection of consumer impressions associated with a brand connected to sustainability and environmental concerns [32]. Studies have demonstrated that customers’ positive impressions and trust in environmentally friendly brands can substantially impact their favorable perceptions and emotional attitudes toward the brand, perhaps leading to increased enjoyment [33]. Furthermore, the use of green branding has the potential to evoke emotional resonance in customers, hence intensifying their emotional enjoyment [34]. Moreover, a green brand image has a favorable impact on the selection of eco-friendly brands. This implies that cultivating an ecologically conscious brand identity can significantly influence a company’s standing, while a favorable brand image enhances the probability of consumers selecting environmentally friendly items [35].

Hypothesis 2 (H2).

A green brand image (GBI) and perceived pleasure (PP) are positively correlated.

3.2.3. Aesthetic Design

Aesthetic design refers to the visual appeal and attractiveness of eco-friendly furniture. Several studies have shown that the aesthetic attractiveness of green furniture can increase consumers’ perceived pleasure [36]. The green furniture design is ergonomic, provides comfort, and potentially expands the purchaser’s perceived pleasure during use [37]. Additionally, the design may enhance the purchaser’s perceived pleasure when high-quality materials are selected, offering sensory experiences like tactile sensation and odor [38]. Visual design in website development influences a website’s balance, emotional appeal, and aesthetics using colors, shapes, fonts, and animations, ultimately creating an attractive and enjoyable user experience [39]. Green furniture’s detailed and balanced design affects how consumers perceive its attractiveness and influences their decision to purchase it from a product design perspective. The ambient aesthetics affect consumers’ perceptions of the product [40].

Hypothesis 3 (H3).

Aesthetic design (AD) and perceived pleasure (PP) are positively correlated.

3.3. Perceived Arousal Factors

3.3.1. Environmental Awareness

In China, consumers now prioritize “environmental performance” over the “price factor” when buying furniture [41]. Environmental awareness refers to individuals’ consciousness of environmental challenges and their readiness to address them [42]. Pagiaslis and Krontalis (2014) [43] emphasize that consumers’ understanding of the environment has a favorable impact on their likelihood of purchasing eco-friendly items. Environmental awareness can indirectly impact pro-environmental intentions and behaviors through attitudes, subjective standards, and perceived behavioral control [44,45]. Extremely environmentally conscious consumers are more likely to be concerned about ecological issues and, hence, are more likely to recognize the presence of eco-friendly furniture. This awareness increases the probability that they will prefer products with eco-friendly attributes [46].

Hypothesis 4 (H4).

Environmental awareness (EA) and perceptual arousal (PA) are positively correlated.

3.3.2. Eco-Innovation

Eco-innovation plays a crucial role in achieving both environmental and economic advantages. Studies have demonstrated that the adoption and execution of eco-innovations can improve consumers’ favorable opinions of the company, amplify their positive emotions and trust towards the company, and subsequently raise their awareness and interest in environmental matters [47]. Furthermore, adopting eco-innovations can elicit favorable emotions in consumers, such as surprise and excitement, thereby enhancing their consciousness of environmental concerns [48]. Conversely, Sharma et al. (2022) [49] examined the correlation between green purchasing behavior and eco-innovations and the influence of emotion generation and loyalty. Eco-innovation aims to minimize the environmental impact by lowering the ecological footprint. It achieves this by preventing waste and promoting the reuse of trash at the early stages of the production process.

Hypothesis 5 (H5).

Eco-innovation (EI) and perceived arousal (PA) are positively correlated.

3.3.3. Perceived Consumer Effectiveness

Perceived consumer effectiveness, as described by Ellen et al. (1991) [50], refers to how much consumers that believe their actions, such as environmentally friendly shopping, help to address societal issues like pollution. Roberts (1996) [51] defines individuals’ perspectives on environmental matters as “perceived consumer effectiveness (PCE)” to refer to individuals’ perceptions of ecological concerns. Various studies indicate that consumers who believe that they are effective tend to adopt eco-friendly behaviors because they believe that their actions positively affect the environment. This confidence might boost their enthusiasm for eco-friendly products like green furniture [52]. Consumers with a deep trust in their ability to impact change are more inclined to select eco-friendly products, considering this a meaningful environmental action. Increased confidence can boost the inclination to purchase environmentally friendly furniture [53].

Hypothesis 6 (H6).

Perceived consumer effectiveness (PCE) and perceived arousal (PA) are positively correlated.

3.4. Perceived Dominance Factors

3.4.1. Green Brand Image

According to research, a positive sense of trust in a green brand increases a consumer’s identification. This leads to users making their own purchasing decisions, growing a sense of autonomy over brand choices [54]. Furthermore, establishing a green brand image can increase consumers’ emotional connection and sense of belonging to the company. This leads to a perceived sense of control when consumers see supporting a green brand as a statement of their commitment to environmental protection [55]. As a result, a green brand image may directly impact customers’ perceived dominance of the brand by influencing their cognitive and emotional responses.

Hypothesis 7 (H7).

A green brand image (GBI) and perceived domination (PD) are positively correlated.

3.4.2. Purchase Customization

Customizing a green furniture purchase allows users to tailor its material, appearance, and color to their preferences and requirements, ensuring that their demands are met. Laminated wood, an eco-friendly material, can be tailored for customized furniture in China. Chen and Sun (2023) [56] used hierarchical analysis and QFD to build a future strategy for wood laminate panels in customized furniture, explicitly focusing on customized kitchen cabinets to suit target users’ desires.

Multiple studies have demonstrated that personalized items provide increased options and authority for consumers to customize eco-friendly furniture to their preferences, perhaps boosting their sense of control during the buying process. Consumers’ perception of increased control can increase confidence in purchase decisions [57]. Furthermore, consumers can enhance their connection with the product by engaging in the customization process. Through hands-on involvement, consumers may feel more dominant over green furniture, believing that their choices and actions impact the ultimate product outcome [58]. Ha and Janda (2014) [59] and Kim and Lee (2020) [60] showed that online customization information could decrease information overload, streamline decision-making, and have a favorable impact on users’ online buying choices. Streamlining the decision-making process can increase consumers’ feeling of control over buying decisions and make them more inclined to purchase.

Hypothesis 8 (H8).

Purchase customization (PC) and perceived dominance (PD) are positively correlated.

3.4.3. Subjective Norms

Subjective norms are the perceived societal influences affecting an individual’s behavior [61]. Higher subjective norms suggest a greater likelihood of engaging in that behavior [62]. Research has shown that individuals can be affected by others’ conduct and societal standards while making purchasing choices, leading to a rise in dominance. Consumers are more inclined to purchase eco-friendly furniture when they perceive societal approval, which boosts their intention to comply with this norm [63].

Hypothesis 9 (H9).

Subjective norms (SN) and perceived dominance (PD) are positively correlated.

3.5. Perceived Pleasure, Arousal, and Dominance Outcomes

A green purchase intention is a deliberate and thoughtful decision describing why a consumer buys a specific product or brand [64]. It also impacts eco-friendly purchasing habits. When individuals experience a PAD emotional state, they are inclined to exhibit proximity behavior in their surroundings. Donovan and Rossiter (1994) [65] found that pleasure impacted the consumer’s likelihood to purchase. Arousal led to a positive tendency to interact with the retail setting and raised the possibility of the consumer repeating the same activity or visiting the same place. Studies indicate that the feeling of control resulting from perceived dominance influences behaviors like purchase intention [66]. Studies have shown a correlation between affective states of pleasure and arousal and the intention to purchase in physical and virtual retail environments [67]. Pleasure and arousal linked to website elements can boost approach behaviors, including purchase intentions, attitudes, and satisfaction [68,69]. The present study indicates that the emotional condition of individuals experiencing PAD emotions when buying green furniture will likely boost their intention to purchase.

Hypothesis 10 (H10).

Perceived pleasure (PP), arousal (PA), dominance (PD) and green Furniture purchase intention (PI) are positively correlated.

3.6. Theoretical Framework

Figure 3 illustrates the theoretical structure of the final study, which examines the influence of emotional perception on the consumer’s inclination to purchase environmentally friendly furniture based on the literature review analysis.

4. Experiments

4.1. Research Methods and Materials

This study investigates the potential users of green furniture purchasing. It places the population for this questionnaire distribution in the Post-1990s, Post-1980s, and Post-1970s groups, as these stages of the population consists of young people who have just begun their careers, those in the early stages of starting new families, and working people who are more environmentally conscious. Data were collected using the questionnaire approach, with a two-part questionnaire serving as this study’s primary data-gathering tool. The first section focused on respondents’ traits, while the second section included questions aimed at measuring the emotional and perceptual aspects influencing green furniture buying intentions. The data were acquired using random sampling, and the questionnaire was completed online. The questionnaires were delivered randomly to 420 persons, and after removing invalid questionnaires, the responses of 412 people were experimentally examined. Thus, the effective questionnaire recovery rate was approximately 98.10 percent.

The questions were set on a five-point Likert scale, and all responses were given on a Likert scale of 1 (strongly disagree) to 5 (strongly agree). The detailed questionnaire is shown in

Table A1. Constructions and their measurements.

Components		Items	Sources
Green Feature (GF)	Environmental Awareness (EA)	(EA-01) I am very concerned about the current environmental situation in my country	[45,70]
		(EA-02) I believe that individuals have a responsibility to protect the environment.
		(EA-03) I am willing to control my consumption to protect the environment
	Eco-Innovation (EI)	(EI-01) I think green furniture is easier to recycle than traditional furniture	[71]
		(EI-02) I think green furniture reduces the damage caused by waste compared to traditional furniture.
		(EI-03) I think green furniture uses less material than traditional furniture.
	Perceived Green Value (PGV)	(PGV-01) I think green furniture is more valuable to the environment than traditional furniture.	[72]
		(PGV-02) I think green furniture is more valuable compared to paid currency.
		(PGV-03) I hope that green furniture will improve environmental performance.
	Green Brand Image (GBI)	(GBI-01) I think to implement green practices, green furniture is successful.	[32]
		(GBI-02) I think that by implementing green practices, green furniture will have a good reputation.
		(GBI-03) I think green furniture is in the limelight to implement environmental protection measures.
		(GBI-04) Green furniture with good green brand trust appeals to me.
Traditional Characteristics (TC)	Aesthetic Design (AD)	(AAD-01) I would love visually appealing green furniture.	[22,24]
		(AAD-02) I like green furniture that has a sense of design and has been professionally designed.
		(AAD-03) Furniture with innovative green materials appeals to me!
	Purchase Customisation (PC)	(PC-01) I like to personalize when buying furniture	[58]
		(PC-02) I want to buy green furniture with CMF (Colour, Material, Workmanship) at my disposal.
		(PC-03) I would buy green furniture that can be customized.
	Perceived Consumer Effectiveness (PCE)	(PCE-01) I think it’s worth it for individual consumers to try to protect and improve the environment.	[73]
		(PCE-02) By purchasing green furniture, I believe I can positively impact the environment and society.
		(PCE-03) I believe that by greening my consumption, I will influence my living environment.
	Subjective norms (SN)	(SN-01) People who are important to me think I should buy green furniture.	[45,62]
		(SN-02) People who influence my behavior think I should buy green furniture.
		(SN-03) People whose opinions I value prefer me to use green furniture.
Emotional perception (EP)	Perceived Pleasure (PP)	(PP-01) Buying furniture with more green values would make me feel very friendly	[16]
		(PP-02) Buying green furniture with good aesthetic design will make me happy!
		(PP-03) I am very interested in green furniture with a good green brand image.
	Perceptual Arousal (PA)	(PA-01) I’m very conscious of the need to protect the environment by controlling consumption.
		(PA-02) Eco-innovation through the purchase of green furniture would excite me!
		(PA-03) The efficacy of the positive impact of buying green furniture makes me feel relaxed
	Perceptual Domination (PD)	(PD-01) Green brand image will have a dominant influence on whether I buy green furniture or not.
		(PD-02) I want to buy green furniture that I can customize at my discretion.
		(PD-03) Whether or not I buy green furniture can be influenced by others.
Purchase Intention (PI)		(PI-01) I’m willing to buy green furniture that gives me pleasure.	[11]
		(PI-02) I’m willing to buy green furniture that excites me.
		(PI-03) I am willing to buy green furniture at my disposal

. Items measuring environmental awareness were adapted from Chen and Tung (2014) [45] and Paul et al. (2016) [70]; items measuring eco-innovation were adapted from Yurdakul and Kazan (2020) [71]; items measuring perceived green value were adapted from Chen et al. (2012) [72]; items measuring green brand image were adapted from Bashir et al. (2020) [32]; and items measuring aesthetic design were adapted from Hekkert and Snelders (2003) [22] and Hsieh et al. (2021) [24]. Items for measuring purchase modification were derived from Schreier (2006) [58]. Items evaluating perceived consumer effectiveness were derived from Cho et al. (2013) [73], while those measuring subjective norms were developed by Kim and Han (2010) [62] and Chen and Tung (2014) [45]. Items assessing perceived pleasure, arousal, and dominance were derived from Yang and Kim (2020) [16]. Items assessing green furniture purchase intention were modified by Xu et al. (2020) [21].

4.2. Analytical Method

Validation factor analysis and multiple regression analysis were performed using SmartPLS 3.0 software to determine the validity of the hypotheses. The data were analyzed using partial least squares structural equation modeling (PLS-SEM), which has grown in popularity in recent years due to its ability to handle non-normal data, small sample sizes, and the use of formative indicators. Bootstrap approaches were used to explore the PAD effect’s mediating influence, including measurement and structural models. The measuring model was evaluated using standardized item loadings, internal consistency reliability, convergent validity, and discriminant validity [74]. The PLS-SEM statistical model can be used to investigate the associations between latent and explicit (observed) variables [75].

5. Results

5.1. Demographics

Out of all the participants, 50.49 percent were women, while 49.51 percent were men. Most of the population was born after the 1980s, totaling 161 individuals. Regarding educational background, most had university degrees, accounting for 34.7 percent, while 17.23 percent had postgraduate degrees or above. Figure 4 displays the sample characteristics of this investigation. The demographic data elucidate the study’s findings and enhance comprehension of the audience’s characteristics.

5.2. Data Validity Testing

The Kaiser–Meyer–Olkin (KMO) sample adequacy measure and Bartlett’s test of sphericity were used to assess the validity of the factor data analysis. Bartlett’s test assesses whether the total correlation matrix is unitary. The KMO test assesses the extent variables share variance [76]. Following the validity analysis, the questionnaire’s Kaiser–Meyer–Olkin (KMO) value was 0.987, indicating high validity, as it exceeded 0.7. The p-value was less than 0.001, confirming the questionnaire’s strong validity for the following analysis, as shown in

Table 2. KMO and Bartlett’s test.

KMO and Bartlett’s Test
Kaiser–Meyer–Olkin metric for sampling adequacy.		0.987
Bartlett’s test of sphericity	approximate chi-square (math.)	12,726.578
	df	820
	Sig.	0.000

.

5.3. Measurement Models

A validation factor analysis is conducted to assess the accuracy of the proposed conceptual model. This analysis helps to determine the extent to which the measured variables demonstrate a pattern or can be utilized to evaluate the theory of measurement [77]. Researchers employ a measurement model to articulate latent constructs using indicator variables to formulate causal hypotheses [78]. The internal model is a structural equation modeling (SEM) study component and elucidates the interrelation between the latent variables that constitute the model. The external model elucidates the correlation between the underlying variables and their respective dimensions. The internal model elucidates the relationship between the factors and provides the loading values of the factors, whereas the variables are shown in the external model. Figure 5 illustrates the impact of eight attributes of green furniture on consumers’ inclination to buy green furniture. It also examines how the perception of pleasure, arousal, and dominance affects this readiness to purchase. The picture also displays the factor loadings for each item, which define their respective latent variables. The factor loadings for each variable were uniform, with factor loading values exceeding 0.7, and the questions assessing the underlying characteristics were in line with the theoretical foundations and factor arrangement. The suitability of the measurement model implies that the items are dependable indicators of the proposed structure, allowing for the examination of structural linkages [79].

5.3.1. Reliability Test

Four techniques were employed to assess reliability: composite reliability (CR), rho_A, average variance extraction (AVE), and Cronbach’s α. Hair et al. (2014) [80] state that the dependability value is deemed adequate at 0.7. All components in

Table 3. Reliability analysis.

Component	Cronbach’s Alpha	rho_A	Composite Reliability	Average Extraction Variance (AVE)
AD	0.807	0.807	0.886	0.721
EA	0.875	0.876	0.923	0.800
EI	0.883	0.884	0.928	0.811
GBI	0.870	0.870	0.911	0.719
PA	0.811	0.812	0.888	0.726
PC	0.811	0.811	0.888	0.725
PCE	0.805	0.807	0.885	0.720
PD	0.839	0.839	0.903	0.756
PI	0.850	0.850	0.909	0.769
PP	0.835	0.836	0.901	0.752
PGV	0.890	0.890	0.931	0.819
SN	0.807	0.807	0.886	0.721

have values above the 0.7 criterion, suggesting strong structural reliability for all variables. Yap et al. (2012) [81] asserted that the mean variance recovered is evidence of convergent validity. Hair et al. (2014) [80] state that an AVE value of 0.5 is acceptable. Higher AVE values indicate the strong credibility of this technique. The average variance extracted (AVE) suggests that the factors in this analysis are over 0.5, demonstrating strong convergent validity.

5.3.2. Distinctive Validity

Discriminant validity was assessed by examining the correlation coefficients between the average variance extracted (AVE) of the latent variable and the other latent variables.

Table 4. Distinctive validity ¹.

AD

EA

EI

GBI

PA

PC

PCE

PD

PI

PP

PGV

SN

AD

0.849

EA

0.831 ***

0.894

EI

0.802 ***

0.852 ***

0.900

GBI

0.802 ***

0.814 ***

0.817 ***

0.848

PA

0.757 ***

0.794 ***

0.817 ***

0.767 ***

0.852

PC

0.785 ***

0.800 ***

0.802 ***

0.794 ***

0.776 ***

0.852

PCE

0.765 ***

0.809 ***

0.804 ***

0.795 ***

0.770 ***

0.753 ***

0.848

PD

0.774 ***

0.788 ***

0.786 ***

0.764 ***

0.762 ***

0.758 ***

0.755 ***

0.870

PI

0.780 ***

0.816 ***

0.802 ***

0.798 ***

0.784 ***

0.768 ***

0.776 ***

0.765 ***

0.877

PP

0.776 ***

0.792 ***

0.796 ***

0.785 ***

0.777 ***

0.764 ***

0.746 ***

0.767 ***

0.755 ***

0.867

PGV

0.810 ***

0.831 ***

0.840 ***

0.812 ***

0.806 ***

0.812 ***

0.805 ***

0.788 ***

0.820 ***

0.786 ***

0.905

SN

0.791 ***

0.800 ***

0.794 ***

0.780 ***

0.758 ***

0.754 ***

0.764 ***

0.753 ***

0.750 ***

0.751 ***

0.787 ***

0.849

¹ *** denotes p < 0.001.

demonstrates that the AVE root mean squares exceed the correlation coefficients between the latent variables, indicating a robust discriminant validity for the scale. Furthermore, it is evident that there exists a strong link among the variables, and all of them exhibit statistical significance at a 99% confidence level. Figure 6 displays a heat map illustrating the correlation between variables, focusing on the Person correlation. Thus, we can perform a structural equation modeling analysis.

5.3.3. Covariance Test

The variance inflation factor (VIF) values for the formative measures in the model were all below 5, ranging from 1.631 to 2.636 [82]. Thus, multiple covariances are not a concern, as demonstrated in

Table 5. Covariance test.

	VIF		VIF
AD_Row1	1.840	PC_Row1	1.753
AD_Row2	1.668	PC_Row2	1.762
AD_Row3	1.767	PC_Row3	1.798
EA_Row1	2.397	PD_Row1	2.086
EA_Row2	2.527	PD_Row2	1.869
EA_Row3	2.216	PD_Row3	1.993
EI_Row1	2.300	PI_Row1	2.152
EI_Row2	2.603	PI_Row2	2.233
EI_Row3	2.628	PI_Row3	1.903
GBI_Row1	2.169	PP_Row1	1.949
GBI_Row2	2.044	PP_Row2	1.966
GBI_Row3	2.049	PP_Row3	1.914
GBI_Row4	2.126	PGV_Row1	2.636
PA_Row1	1.828	PGV_Row2	2.622
PA_Row2	1.806	PGV_Row3	2.529
PA_Row3	1.702	SN_Row1	1.805
PCE_Row1	1.674	SN_Row2	1.631
PCE_Row2	1.792	SN_Row3	1.871
PCE_Row3	1.771

.

5.4. Structural Models

5.4.1. Model Fit

The normative fit index (NFI) ranges between 0 and 1. A number nearing 1 signifies a more accurate model match. In

Table 6. Model fit.

	Saturated Model	Estimated Model
SRMR	0.034	0.053
d_ULS	0.837	1.957
d_G	0.776	0.888
chi-square value	1835.288	1968.952
NFI	0.859	0.849

, the NFI value exceeds 0.7, which is acceptable. The standardized root mean square residual (SRMR) evaluates the average discrepancy between observed and expected correlation matrices. It is part of the ultimate goodness-of-fit index. According to Hu and Bentler (1988) [83], an SRMR value below 0.05 is considered very good, while a value below 0.1 is acceptable. This study’s SRMR index was less than 0.05, indicating a very high absolute goodness of fit.

5.4.2. R²

The R² value represents the correlation between an endogenous variable and its anticipated latent variable. The coefficient of determination (R²) should exceed 0.3 [80]. The R² values for PA, PD, PI, and PP in this investigation were all above 0.3, indicating the superior fit of the model, as shown in

Table 7. R².

	R2	Adjusted R2
PA	0.718	0.716
PD	0.676	0.673
PI	0.700	0.697
PP	0.702	0.699

.

5.4.3. Q² and F²

The Stone–Geisser Q² criteria have also been employed to assess the predictive capacity of the model [84]. We discovered that the Q² values of PA, PD, PP, and PI for the proposed theoretical framework are 0.516, 0.506, 0.523, and 0.533, respectively, which are greater than 0 and more significant than 0.35, indicating that the model has high predictive relevance. The F² effect size is a numerical scale that assesses the strength of the association between two variables. Cohen’s F² is calculated using methods such as analysis of variance (ANOVA) and multiple regression to evaluate effect size, as shown in

Table 8. F².

	F2
PA→PI	0.149
EI→PA	0.145
PD→PI	0.104
GBI→PP	0.094
SN→PD	0.094

. According to this indicator, perceived arousal (PD) and purchase intention (PI) (0.149 = medium effect), eco-innovation (EI) and perceived arousal (PA) (0.145 = medium effect), perceived dominance (PD) and purchase intention (PI) (0.104 = weak effect), green brand image (GBI) and perceived pleasure (PP) (0.094 = weak effect), and subjective norms (SN) and perceived dominance (PD) (0.094 = weak effect) had the most significant impact on emotional perceptions of green furniture purchase.

5.5. Hypothesis Testing Results

Table 9. Hypothesis testing results.

Path	Path Factor (β)	T-Statistic (|O/STDEV|)	p-Value	95%CI		Results
				LLCI	ULCI
AD→PP	0.272	5.218	<0.001	0.166	0.373	Accept
EA→PA	0.252	4.294	<0.001	0.148	0.381	Accept
EI→PA	0.416	7.557	<0.001	0.305	0.518	Accept
GBI→PD	0.293	6.424	<0.001	0.203	0.373	Accept
GBI→PP	0.316	6.610	<0.001	0.209	0.404	Accept
PA→PI	0.369	8.054	<0.001	0.276	0.454	Accept
PC→PD	0.300	6.245	<0.001	0.202	0.386	Accept
PCE→PA	0.231	4.389	<0.001	0.125	0.327	Accept
PD→PI	0.303	6.874	<0.001	0.209	0.382	Accept
PP→PI	0.236	5.398	<0.001	0.147	0.316	Accept
PGV→PP	0.308	6.827	<0.001	0.216	0.392	Accept
SN→PD	0.298	6.781	<0.001	0.213	0.385	Accept
EA→PA→PI	0.093	3.632	<0.001	0.049	0.149	Accept
EI→PA→PI	0.154	5.836	<0.001	0.102	0.208	Accept
PCE→PA→PI	0.085	3.706	<0.001	0.045	0.132	Accept
GBI→PD→PI	0.089	4.433	<0.001	0.052	0.131	Accept
PC→PD→PI	0.091	4.596	<0.001	0.056	0.131	Accept
SN→PD→PI	0.090	4.850	<0.001	0.060	0.127	Accept
AD→PP→PI	0.064	3.870	<0.001	0.037	0.103	Accept
GBI→PP→PI	0.075	4.119	<0.001	0.042	0.112	Accept
PGV→PP→PI	0.073	4.056	<0.001	0.041	0.111	Accept

displays the hypothesis testing findings, including the path coefficient (β), p-value, and confidence interval. The path coefficient indicates the strength of the association between the explanatory and interpreted variables. According to the table, this article confirms the correctness of the hypothesized model. The perceived green value (PGV) (β = 0.308, p < 0.001), a green brand image (GBI) (β = 0.316, p < 0.001), and an attractive design (β = 0.272, p < 0.001) all positively impact perceived enjoyment, supporting hypotheses H1, H2, and H3. Environmental awareness (EA) (β = 0.252, p < 0.001), eco-innovation (EI) (β = 0.416, p < 0.001), and perceived consumer effectiveness (PCE) (β = 0.231, p < 0.001) all had a positive effect on perceived arousal, supporting hypotheses H4, H5, and H6. A green brand image (GBI) (β = 0.293, p < 0.001), purchase customization (PC) (β = 0.300, p < 0.001), and subjective norms (SN) (β = 0.298, p < 0.001) all have a positive influence on perceived domination, supporting Hypotheses H7, H8, and H9. Hypothesis H10 is supported by the positive effects of perceived pleasure (β = 0.236, p < 0.001), arousal (β = 0.369, p < 0.001), and dominance (β = 0.303, p < 0.001) on purchase intention for green furniture. Data with 95% confidence intervals support all hypotheses; hence, they are acceptable. This indicates that green furniture and traditional features positively affect consumers’ emotional perceptions. A green brand image (GBI) has the most significant positive effect on perceived pleasure (PP), eco-innovation (EI) has the most significant positive impact on perceived arousal (PA), purchase customization (PC) has the greatest positive effect on perceived dominance (PD), and perceived arousal (PA) has the greatest positive effect on green furniture purchases. Intention (PI) exerts the biggest beneficial influence.

Nine additional indirect effects are also present. Table 9 reveals that the path coefficient for the relationship between EA→PA→PI is 0.093, the coefficient for EI→PA→PI is 0.154, the coefficient for PCE→PA→PI is 0.085, the coefficient for GBI→PD→PI is 0.089, the coefficient for PC→PD→PI is 0.091, the coefficient for SN→PD→PI is 0.090, the coefficient for AD→PP→PI is 0.064, the coefficient for GBI→PP→PI is 0.075, and the coefficient for PGV→PP→PI is 0.073. The PAD three-dimensional emotions significantly mediate the positive effect between the characteristics of green furniture and the intention to purchase green products. Furthermore, EI→PA→PI has the largest mediating effect.

5.6. Comparative Analysis of Green and Traditional Features

To assess the variability of the impact of the green and traditional characteristics of green furniture on the emotional perception of intention to purchase green furniture, the variables EA, EI, GBI, PGV, AD, PC, PCE, SN, PA, PD, and PP were standardized and then analyzed using structural equation modeling. The results indicate that the adjusted R² values for EP and PI were 0.861 and 0.697, respectively. The variance inflation factor (VIF) values ranged from 1.903 to 4.936. The model fit indices, specifically SRMR (0.031) and NFI (0.933), demonstrated good model fit as they were below the threshold of 0.05 and above the standard value of 0.9, respectively. These findings suggest that the model fit was satisfactory, and there were no issues with covariance. The measurement model, path coefficient β, significance p-value, and confidence intervals are displayed in Figure 7 and

Table 10. Multi-cluster structural equation modelling analysis.

Path	Path Factor (β)	T-Statistic (|O/STDEV|)	p-Value	95%CI		Results
				LLCI	ULCI
EP→PI	0.835	62.059	<0.001	0.805	0.859	Accept
GF→EP	0.551	9.869	<0.001	0.447	0.673	Accept
TC→EP	0.390	6.966	<0.001	0.270	0.497	Accept
GF→EP→PI	0.460	9.634	<0.001	0.374	0.563	Accept
TC→EP→PI	0.326	6.938	<0.001	0.225	0.415	Accept

. There is a noticeable disparity in how consumers emotionally respond and intend to purchase green furniture compared to standard furniture due to the presence of green characteristics. The impact of green features (GF) on emotional perception (EP) is more pronounced (β = 0.511, p < 0.001) compared to the effect of traditional features (TC) on emotional perception (EP) (β = 0.390, p < 0.001).

Additionally, the mediating effect of GF→EP→PI (β = 0.460, p < 0.001) is stronger than the mediating effect of TC→EP→PI (β = 0.326, p < 0.001). This effect (β = 0.326, p < 0.001) is more pronounced, meaning that the green qualities of green furniture are more likely to evoke emotional responses from customers, subsequently influencing their intention to purchase green furniture. This implies that customers are more inclined to consider green features a significant element in their purchasing choice. Secondly, consumers’ emotional reactions to green features have a more immediate influence on their intention to acquire green furniture, as opposed to traditional characteristics.

5.7. Multi-Cluster Structural Equation Modelling Analysis

This article utilized a multi-cluster structural equation modeling approach, specifically PLS-MGA analysis, to examine variations in the influence of user demographic factors (gender, age, educational background) on the path of the primary effects model. The data were analyzed using SmartPLS 3.0 , and the results for the standardized path coefficients and significance differences are presented in

Table 11. Multi-cluster structural equation modelling analysis ².

Demographics		GBI→PP	PGV→PP	EP→PI
Gender	Male	0.329	0.381	0.807 *
	Female	0.299	0.230	0.861 *
Age group by birth	1990s	0.197 *	0.407 **	0.822
	1980s	0.277	0.387 **	0.859
	1970s	0.509 *	0.064 **	0.823
Educational background	Low	0.263	0.282	0.844
	High	0.379	0.310	0.826

² * denotes p < 0.05, ** denotes p < 0.01; low education attainment is defined as less than specialized, and high education attainment is defined as specialized and above.

. Specific demographic parameters have varying impacts on the model. Among the factors considered, the educational background does not impact the model. However, a green brand image (GBI) significantly influences consumers born after the 1970s, compared to those born after the 1990s, who prioritize pleasure. On the other hand, the perceived green value (PGV) has a more substantial impact on consumers born after the 1990s, who experience higher levels of pleasure and are more likely to be influenced in their purchase intention of green furniture. Additionally, females are more susceptible to the features of green furniture and tend to have stronger emotional perceptions than males. Furthermore, females are more likely to be influenced by the features of green furniture than males. Green furniture exhibits certain features, and females are more influenced by the emotional impression of green furniture than males. Potential causes for these phenomena include the following:

• Individuals born after the 1970s may have a greater inclination to place trust in established brands and regard environmentally friendly furniture brands with greater importance;
• Furthermore, individuals born after the 1970s may already have a deeply rooted sense of environmental consciousness. Consequently, individuals are more inclined to experience enjoyment and opt for environmentally friendly brands;
• Individuals born after the 1990s may exhibit a greater emphasis on sustainable principles;
• Individuals born after the 1990s are more inclined to utilize social media platforms and are susceptible to the impact of environmental issues discussed on these platforms. Exposure to green ideals on social media can significantly impact individuals, increasing their susceptibility to influence and fostering greater interest and satisfaction with green furniture;
• Women are typically more emotional and focused on emotional experiences, and green furniture may inspire emotional resonance in women through features such as its sustainable philosophy and the aesthetics and style of home décor, making them more likely to desire to buy.

6. Discussion

Furthermore, other scholars have studied the impact of correlated variables on the intention to make environmentally friendly purchases. Klabi and Binzafrah (2022) [22] confirmed a positive relationship between environmental concern and green purchasing intention and between green brand trust and green buying intention. This study confirms that ecological awareness (EA) has a positive impact on the intention to purchase green furniture by increasing arousal level (β = 0.093, p < 0.001). It also confirms that a green brand image (GBI) positively impacts the intention to purchase green furniture by increasing the levels of pleasure and dominance. Le and Quang (2023) [3] argued that subjective norms (SN) do not directly affect the intention to purchase green furniture. Still, this paper verifies that subjective norms (SN) can indirectly influence the intention to purchase green furniture by increasing consumers’ dominance level (β = 0.090, p < 0.001). Additionally, Le and Quang (2023) [3] concluded that perceived consumer effectiveness positively influences attitudes, which in turn affects the intention to purchase green furniture. This paper establishes that perceived consumer effectiveness (PCE) has a positive impact on the intention to purchase green furniture by increasing arousal level (β = 0.085, p < 0.001). Zhang et al. (2023) [85] confirmed that the aesthetic design layout of the product detail page influences consumers’ purchase intentions. This study also confirmed that aesthetic design (AD) increases consumers’ desire to purchase by positively impacting the level of perceived enjoyment (β = 0.064, p < 0.001). Consumers’ purchasing of green products is influenced by their perceived functional value of the product [86]. This study confirms that perceived green value (PGV) indirectly affects green furniture purchase intention by increasing consumers’ pleasure levels (β = 0.073, p < 0.001). Moslehpour et al. (2023) [20] also found that eco-innovation positively influences green purchase intention. It was further confirmed that eco-innovation (EI) positively affects the level of perceived arousal, thereby enhancing purchase intention (β = 0.154, p < 0.001). Additionally, this study demonstrates that purchase customization (PC) positively affects the level of perceived dominance, leading to an increase in the purchase intention of green furniture (β = 0.091, p < 0.001).

In addition, several researchers have looked into the mediating impacts of PAD 3D emotions. Hsieh et al. (2021) [14] demonstrated a positive correlation between design aesthetics and entertainment with enjoyment. The implementation of gamification has a positive impact on arousal, dominance, pleasure, and brand loyalty. In their study, Yang and Kim (2020) [16] found that interactive services significantly positively affect the dominance state, further confirming the influence of the pleasure state on the intention to revisit brand websites. Zhou et al. (2022) [87] conducted a study to examine the impact of various page layouts and colors in smart homes for older individuals on perceived usability, specifically in terms of pleasure (P), activation (A), and dominance (D). This paper also performs a mediation analysis. The aesthetic design (AD) of green furniture positively impacts consumers’ intention to purchase by increasing their enjoyment. The visual appeal of green furniture aligns with consumers’ aesthetic preferences, and the design promotes a sense of comfort that leads to both physical and mental pleasure. The perceived green value (PGV) is directly linked to perceived pleasure (PP), enhancing the purchase intention for green furniture through heightened enjoyment. Furthermore, the perceived pleasure also plays a significant role in this regard. Perceived pleasure is not the only factor at play here. The green brand image (GBI) also acts as a mediator. Consumers’ positive perception and trust in green brands significantly enhances their goodwill and pleasure towards the brand. This, in turn, increases their willingness to make a purchase. The mediating factors that contribute to this effect are perceived arousal (PA), which is influenced by environmental awareness (EA), and perceived consumer effectiveness (PCE). Additionally, eco-innovation (EI) plays a role in this process. A higher environmental awareness indicates more vital values toward ecological protection, stimulating the desire to buy green furniture. Therefore, increasing consumers’ perceived efficacy enhances their understanding of environmentally friendly products like green furniture. Additionally, implementing eco-innovation leads to improved emotional resonance and triggers positive emotions in consumers. These factors indirectly contribute to an increased willingness to purchase green furniture. Perceived dominance (PD) is influenced by purchase customization (PC), a green brand image (GBI), and subjective norms (SN). When consumers feel they have more control over the purchasing process, they are more likely to be willing to purchase green furniture. Green brand trust can enhance consumers’ perceived dominance of the product. Additionally, individuals can be influenced by the behaviors of others and social expectations, which can shape their perception of dominance. The behavior of others and social expectations can influence people’s purchasing decisions. These influences are further influenced by the perceived dominance, which indirectly and favorably affects the propensity to acquire green furniture.

Finally, this article investigates the differences between green and traditional features in triggering emotional reactions and influencing purchasing intentions. The findings demonstrate that green furniture’s green features are more capable of eliciting an emotional response from consumers, which influences their intention to acquire green furniture. In furniture design, it is critical to emphasize green design, focus on eco-innovation, develop a green brand link, and form green ideals to elicit consumers’ emotional responses and induce buy intentions.

7. Conclusions

This article examines the disparities in eliciting emotional responses and impacting buying intentions between green and conventional characteristics. The results indicate that the environmentally friendly characteristics of green furniture have a more remarkable ability to evoke an emotional reaction from consumers, which in turn affects their desire to have green furniture. In furniture design, it is crucial to prioritize green design, concentrate on eco-innovation, establish a strong connection with a green brand, and foster green values. This will evoke consumers’ emotional responses and encourage them to make purchase decisions.

(1)

Perceived arousal (PD) and purchase intention (PI) (0.149 = medium effect), eco-innovation (EI) and perceived arousal (PA) (0.145 = medium effect), perceived dominance (PD) and purchase intention (PI) (0.104 = weak effect), a green brand image (GBI) and perceived pleasure (PP) (0.094 = weak effect), through F² values, and subjective norms (SN) and perceived domination (PD) (0.094 = weak effect), had the greatest impact on the emotional perception of green furniture purchase intent.

(2)

All explanatory variables are significantly related to the explanatory variable (green furniture purchasing intention). Furthermore, all PAD three-dimensional emotions significantly moderated the association between green furniture attributes and purchasing intent.

(3)

Additional examination using multi-group structural equation modeling indicates that the impact of a green brand image (GBI) on the intention to purchase green furniture is more substantial for consumers born after the 1970s than those born after the 1990s. Conversely, the influence of perceived green value (PGV) on the intention to purchase green furniture is more significant for consumers born after the 1990s due to their higher level of pleasure. Furthermore, females are more likely than males to be influenced by the features of green furniture, which elicit emotional perception and generate purchase intention. Simultaneously, women are more prone to being swayed by the attributes of green furniture, which affects their emotional perception and intention to make a purchase.

(4)

This study examined the impact of green features and traditional features of green furniture on consumers’ emotional perception and purchase intention. The findings revealed that green features had a more substantial influence on emotional perception (β = 0.511, p < 0.001) compared to traditional features (β = 0.390, p < 0.001). They exhibited greater strength.

The findings of this study are categorized into theoretical and practical findings. Firstly, it enhances the existing theoretical framework of green furniture purchase intention. Secondly, it demonstrates that eco-innovation (EI), a green brand image (GBI), and purchase customization (PC) have the most significant positive impact on perceived pleasure (PP), arousal (PA), and dominance (PD), respectively. Additionally, green features (GFs) have the greatest influence on emotional perception (EP). All of these factors have a positive and significant influence on purchase intention, which is a distinct focus of previous research. Therefore, this study contributes to the advancement of theoretical knowledge in this field. The practical ramifications of this paper are as follows:

(1)

Enhance the emotional marketing plan: Considering the significant influence of emotional perception on the intention to purchase, green furniture companies should improve their emotional marketing strategy. By utilizing emotional advertising, brand narrative, education, and publicity, we may heighten consumers’ environmental consciousness and self-assurance, reinforcing their emotional attachment and intention to purchase.

(2)

Emphasis on green features and eco-innovation: Research results show that in green furniture marketing, it is crucial to emphasize the product’s green features, followed by eco-innovation, which has the most significant impact on consumers’ perceived pleasure. Therefore, companies should continuously launch products that meet environmental needs and highlight the green features of furniture, such as environmental protection and sustainability, to attract consumers and enhance their pleasure.

(3)

Improving green brand image: The findings indicate that a green brand image has the greatest impact on consumers’ perceived pleasure. As a result, businesses should commit to developing a positive green brand image through brand marketing activities and brand image to improve consumer satisfaction. They should also use branding and marketing methods to encourage consumers to favorably appraise and recognize green furniture while keeping in mind the influence of subjective norms.

(4)

Customized services and distinct experiences: The findings indicate that purchase customization has the biggest impact on perceived dominance. As a result, businesses can match consumer demand for individualized products by offering customized services. In addition, because different gender and age groups have different levels of willingness to buy, in the case of fierce market competition, green furniture enterprises should focus on specific groups of users to achieve differentiated product services.

This study has the following limitations and research deficiencies that can be improved through future research:

• Due to the use of the questionnaire approach, the data acquired for this study were limited to a cross-sectional perspective. To address this constraint, future analyses should investigate using a longitudinal experimental design;
• An analysis can be conducted to examine the emotional influence of intentions to make environmentally friendly purchases in various locations;
• This paper only investigated the impact of green furniture features on consumers’ emotional responses, and the mechanisms explored in the future could be the dual-mediated impacts of the functional and emotional dimensions.