Public Perception of Green Supply Chains and Its Impact on Customer Behavior: An Empirical Analysis

Abstract

The public is increasingly becoming aware of environmental challenges and adjusting its purchasing behavior in pursuit of sustainable products and services. To compete in the global scene, firms need to transform their supply chains to adhere to eco-friendly practices. This study focuses on the electronics market, which is distinctively interesting due to its small product life cycles, high-end capabilities, and fierce competition. A novel research model comprising nine hypotheses that attempt to investigate and assess the factors influencing customers’ perceptions and purchasing preferences in relation to green supply chains in the electronics industry was developed. We conducted field research to test the model empirically using survey data from 147 individuals with different backgrounds. The dataset was verified and validated by means of explanatory factor analysis. Structural equation modeling analysis was performed that revealed the linkage between demographics (age), willingness to pay, purchasing intention, and green consumerism. Other research findings included the intricate interconnections between environmental concern, knowledge, attitude, customers’ perceptions/effectiveness, and behavior. This research gives insights into green consumerism in the electronics sector, and its managerial implications can guide sustainable supply chain practices and customer-centric marketing approaches.

1. Introduction

In a globally competitive business market, firms can benefit from lean and green thinking in supply chain management (SCM) to reduce costs, improve quality, and reduce risk (Wiese et al. [1]; Paksoy et al. [2]; Paraschos et al. [3]; Koulinas et al. [4]). Green supply chain (GSC) practices, e.g., lean and green principles, increase environmental efficiency and improve a company’s reputation. They also reduce environmental pollution and product production costs (Katsios et al. [5]), and accelerate economic growth. Green supply chains also create a competitive advantage by improving customer satisfaction, generating a positive image, and exporting opportunities to environmentally friendly countries (Paksoy et al. [2]). The main target of GSCs is to reduce air, water, as well as waste pollution while also improving business performance through product reuse and recycling, reducing manufacturing costs, and increasing resource efficiency and customer satisfaction (Khan and Dong, [6]; Khan, [7]).

1.1. Related Work

1.1.1. Green Supply Chain Management and Practices

Green supply chain management (GSCM) involves applying environmental management practices to all activities throughout the customer order cycle and integrating environmental concerns into sustainable supply chain management practices, including reverse logistics (Ahi and Searcy, [8]; Sarkis et al. [9]). Despite its broad definition, common terms include “environmental supply chain management”, “green purchasing and procurement”, “green logistics and environmental logistics”, and “sustainable supply network management” (Ming-Lang et al. [10]).

This research highlights five dimensions of green supply chain management (GSCM) that companies could use to plan their supply chains. These are green markets, internal environmental management practices, eco-design, customer cooperation on environmental issues, and end-of-life management of products (Zhu et al. [11]). More specifically, green markets integrate environmental concerns into material selection and supplier management, while internal environmental management efforts drive GSC practices [11]. Eco-design aims to eliminate environmental burdens during production (Xanthopoulos et al. [12]), while customer cooperation on environmental issues is crucial for integrating environmental issues into the supply chain (Lewis and Gretsakis, [13]; Ginsberg and Bloom, [14]).

1.1.2. Green Products and Customer Purchasing Behavior

Green purchasing behavior is a sophisticated ethical decision-making process that aims to achieve social change by using purchasing power to achieve environmental protection and social awareness (Jaiswal and Kant, [15]). Green products such as organic products, energy-efficient light bulbs, plant-based products, and eco-friendly washing machines are environmentally superior and have low environmental impact (Joshi and Rahman, [16]). The theory of planned behavior (TPB) attempts to explain customer intention but is often interpreted as a good indicator of behavior (Ajzen, [17]; Liobikienė et al. [18]). Customer attitude is another factor that influences purchasing behavior toward green products. Environmental knowledge is often considered the main motivator of customers’ green behavior, as customers who are more aware of environmental problems and the benefits of using green products may have more positive attitudes toward green products (Peattie, [19]; Zhao et al. [20]). Social pressure inspires customers to buy green products, but subjective norms and social values do not significantly impact purchase intention (Biswas and Roy, [21]; Ritter et al. [22]; Kumar, [23]). Green products are usually sold at higher prices due to the additional costs of better raw materials and labeling certification (Ling, [24]; Zhao and Zhong, [25]). However, customers are willing to pay a higher price for “green” products when they perceive that their quality is higher than that of conventional products. As customers become more aware of the environmental impact of their consumption habits, they try to modify their attitudes and behaviors in order to benefit future generations (Paul et al. [26]; Paco et al. [27]).

Previous research explored the relationship between customers’ attitudes toward environmentally friendly products and their actual purchasing behavior (Wheale and Hinton, [28]; Joshi and Rahman, [16]). However, most studies found a weak association between customers’ positive attitudes and their actual purchasing behavior, known as the attitude–behavior gap (Vermeir and Verbeke, [29]; Wheale and Hinton, [28]). The capacity to forecast attitudes remains debatable in the context of environmental consumerism [16]. The theory of planned behavior was not considered an appropriate model for explaining ethical behavior as it does not consider the emotional component of customers or their ‘habitual’ purchasing behavior (Padel and Foster, [30]). Additionally, the TPB approach does not consider the effect of situational factors like economic constraints on the relationship between environmental attitudes and behavior (Carrington et al. [31]). Some studies suggested modifications to the TPB to overcome its limitations so that it could explain the observed inconsistencies in green markets (Joshi and Rahman, [16]).

The foundation of this research is deeply rooted in and expands upon the insights gleaned from the scholarly publications listed below. This study is guided by and seeks to build upon the findings and contributions put forth in these academic works, aiming to extend and contribute to the existing body of knowledge in the respective field.

A mutual deterministic theory was presented by Phipps et al. [32] to explain sustainable consumption behavior. The significance of “past” behavior, which claims that it is a predictor of “future” sustainable behavior, was emphasized in this approach. This model suggests that personal characteristics like attitude, as well as earlier sustainable behaviors and sociocultural settings, have an impact on future sustainable behavior.

Hojnik et al. [33] investigated Slovenia’s economy, which is fueled by environmental sustainability concerns, to learn more about the “ancestors” of green customerism. The researchers discovered that customer dedication to the environment, perceptions of green products, and perceptions of impediments to going green all have a favorable impact on customers’ intentions to buy green items. According to the findings, customers’ dedication to the environment and their perception of green products were the main factors influencing whether they planned to make green purchases.

Along the same line, Naz et al. [34] attempted to pinpoint the variables that affect customers’ decisions to purchase environmentally friendly goods. The findings indicated that the primary variables impacting green purchasing behavior are willingness to pay and intention to make green purchases. The study’s findings, in light of the fact that younger students have a sufficient understanding of environmental issues and are eager to pay a premium for environmentally friendly goods, demonstrate that there is no prejudice in behavior among students of different ages, genders, or educational backgrounds.

Similarly, Jaiswal and Kant [15] used structural equation models (SEM) to analyze data from 351 Indian customers and investigated a model based on “attitude, intention, and behavior”. The results showed that the customer’s perceived efficacy, environmental concern, and attitude to green products were major and direct drivers of green purchase intention. Attitude to green products also served as a mediating factor. However, it was discovered that environmental awareness had no bearing on customers’ attitudes toward green products or their intentions to make green purchases.

Finally, Chaudhary and Bisai [35] tried to expand the theory of planned behavior (TPB) by introducing two new factors: environmental concern and willingness to pay more for a green product. Their data were gathered from 202 students from different departments at an Indian higher education institution. Structural equation models were used to test the suggested model; the TPB framework was supported, with the exception of the linkage between subjective norm and purchase intention.

This research addresses significant gaps in existing studies:

• by focusing on green electronic products, a domain largely overlooked in previous research.
• by adopting a more comprehensive approach encompassing alternative regions and diverse demographics, unlike prior works that often concentrated on specific geographical locations or demographic groups such as students or millennials.
• by rectifying the oversight of disregarded factors and interdependencies in previous research, aiming to provide a more nuanced and interconnected model of electronic products’ green consumerism.

In essence, this research contributes by filling crucial gaps in the literature, advancing our understanding of environmentally sustainable electronics across various contexts.

1.2. Research Motivation, Goals, and Contribution

The objective of this research was to empirically investigate and assess the impact of the factors that affect Greek customers’ perceptions and purchasing preferences in relation to green supply chains in the electronics industry. It also explored customers’ awareness and sensitization to environmental issues.

A new conceptual framework is developed and nine hypotheses are explored. It incorporates two groups of independent factors. The first group includes six factors (customers’ perceptions, their environmental commitment, environmental concerns, attitude toward green products, perceived environmental knowledge, and perceived effectiveness in terms of their contribution to environmental protection), while the second one includes two factors (customer purchase intention for green electronics and willingness to pay). The model also includes one more dependent factor (green consumerism and green purchasing behavior).

The motivation behind this research can be summarized as follows:

• To find out whether the residents of Greece are aware and informed about environmental issues and to find out their perception of these issues in general. The more environmentally informed and aware customers are, the greater the demand for green products will be, which means that more companies will be driven to implement green practices and procedures in their supply chains.
• To determine the perceived effectiveness of customers in terms of their ability to help and contribute to environmental issues. One way for customers to contribute is to have green purchasing behavior, i.e., to support companies that have implemented green supply chains. This combined with the criticality of the times due to climate change makes it even more imperative that a shift to green supply chains is implemented by the majority of companies producing electronic products.
• To identify the attitudes of Greek residents toward green electronic products, whether they have the intention to buy or the willingness to pay, and finally, identify those who have green buying behaviors for electronic products.

One of the most important gaps in this research field, which was discovered from the extended literature review, is that no recent similar studies examining the specific research factors in Greece were found. For this reason, it was considered very interesting to conduct this research in order to determine the perception, awareness, and ultimately the outcome of the purchasing behavior/decision of Greek residents towards electronic products coming from green supply chains. Thus, examining the influence of cultural variations on these views might facilitate the development of customized solutions for various locations or demographic groups. Additionally, from the behavioral economics perspective, further exploration of the behavioral economics component has the potential to enhance comprehension of the impact of cognitive biases, social norms, and decision-making processes on the correlation between public perception of green supply chains and customer behavior. By addressing these gaps, researchers can enhance their understanding of the relationship between public perception of green supply chains and consumer behavior. This can lead to valuable insights for firms seeking to embrace sustainable practices and influence customer decisions.

This study holds significance because it explores green consumerism and supply chains, a subject of considerable contemporary interest. Furthermore, its importance is underscored by its explicit focus on the dynamic electronics market. Additionally, the research assumes significance by the proposed model, which is firmly grounded on empirical data and rigorous statistical analyses. This model provides a robust decision-making tool with significant potential for benefits to firms arising from the heightened public sensitivity to ecological concerns.

The remainder of this article is organized as follows: In Section 2, the conceptual framework along with the proposed hypotheses are discussed. Section 2 also presents the research methodology followed to collect the appropriate and necessary primary data needed to empirically test the proposed hypotheses. Then, in Section 3, the results of the data analysis are presented, while their interpretation is discussed in Section 4. Finally, Section 5 provides a summary and presents the main conclusions drawn from this research as well as its limitations.

2. Materials and Methods

2.1. Development of Conceptual Framework

The proposed conceptual framework aims to empirically examine the factors that relate to Greek customers’ perceptions of green supply chains in the electronics industry (and therefore their perception of green electronic products) and explores whether green supply chains influence customers’ purchasing behavior.

The factors incorporated in this framework were first identified through an extensive literature review; these were then discussed with five experts in the field (SCM executives) using an electronic focus group method. The final nine factors selected are:

• Customers’ perceptions of electronic products from green supply chains (customers’ perceptions).
• Environmental commitment of customers (environmental commitment).
• Environmental concerns (environmental concern).
• Attitude towards green electronic products.
• Perceived environmental knowledge.
• Perceived customer effectiveness.
• Purchase intention.
• Willingness to pay.
• Green consumerism and green purchasing behavior.

In the following section, an attempt will be made to conceptualize the aforementioned research factors by referencing various articles in the international literature.

Customer perception of green electronics refers to how individuals perceive and interpret various aspects of such a product based on their sensory experiences, beliefs, social background, and past experiences. According to Roberts [36], the most reliable indicator of environmentally responsible behavior (i.e., purchasing green products) was found to be consumers’ belief and confidence in their ability to address environmental challenges. This factor is influenced, indicatively, by the quality, price, brand reputation, and design of green electronic products (Ajzen, [17]).

The environmental commitment of customers reflects their willingness to make choices and take actions that align with environmentally friendly values, including eco-friendly purchases, recycling, conserving energy and resources, and so forth (Hojnik et al. [33]). Additionally, according to Sohn et al. [37]), customer commitment constitutes an integral aspect of cohesion and sequential obligations among pertinent stakeholders. Its primary objective is maintained through the relationship linked to a specific service or product, which establishes the pivotal factors that influence the intention to maintain or terminate an economic relationship.

The environmental concern of a customer refers to the level of awareness and worry that an individual has about environmental issues. It reflects a person’s interest in environmental issues such as global warming, pollution, and habitat destruction (Prakash and Pathak, [38]). Pro-environmental consumer behaviors are significantly influenced by their important role; specifically, it is widely acknowledged as a significant determinant of consumers’ motivation to embrace a sustainable way of life (De Canio et al. [39]. Further, Hartmann and Apaolaza-Ibanez [40] confirmed the influence of environmental concerns on consumers’ intentions to purchase green energy brands. Thus, environmental concern is typically considered the key element in green marketing research that studies the eco-behavior of customers (Naz et al. [34]).

Naz et al. [34] state that, as per Ajzen [17], “a customer’s attitude is described as an unfavorable or favorable evaluation of a person of a particular behavior”. In other words, the term “attitude toward a behavior” pertains to an individual’s assessment, either favorable or negative, of a certain conduct. It encompasses an individual’s prominent views concerning the anticipated outcomes associated with engaging in that behavior. Numerous parameters play a role in shaping one’s attitude.

Environmental knowledge refers to a person’s understanding of various aspects of the natural environment, including ecosystems, biodiversity, and natural resources, and the interrelationships between human activities and the environment. It encompasses a wide range of information and principles pertinent to the natural world and the ways in which human actions affect it (Naz et al. [34]; Tan, [41]). In this framework, Brosdahl and Carpenter [42] found that these individuals exhibit a willingness to engage in the purchase of products that are designed to minimize their negative impact on the environment. Additionally, according to some researchers (Levine and Strube, [43]; Ogbeide et al. [44]), there exists a considerable relationship between general ecological knowledge and pro-environmental actions, and individuals who possess a greater understanding of long-term environmental issues are more inclined to allocate a larger portion of their financial resources to the acquisition of ecologically sustainable items.

Customer-perceived efficacy commonly refers to an individual’s belief that he/she can contribute to resolving environmental issues and mitigating his/her adversarial effects on ecosystems (Naz et al. [34]; Tan, [41]). The self-efficacy belief of customers has a significant influence on their cognitive responses to purchasing product or service decision-making. In other words, this statement suggests that an individual’s sense of self-efficacy has a role in shaping their sense of responsibility and their willingness to engage in environmentally responsible behaviors.

Green purchase intention, also known as eco-purchase intention, refers to a customer’s expressed willingness to buy products that are environmentally friendly and have a lower negative impact in comparison to conventional ones (Lai and Cheng, [45]; Jaiswal and Kant, [15]). According to Zhuang et al. [46], “Purchasing intention is usually defined as a prerequisite for stimulating and pushing consumers to actually purchase products and services… and green purchase intention is the possibility of consumers wishing to purchase environmentally friendly products”.

The willingness to pay provides a vital link in transforming green-minded intentions into tangible actions that promote sustainable consumption. Finally, the green customerism factor broadly refers to green customer behavior, that is, the purchasing of eco-friendly products or services.

2.2. Formulation of Research Hypotheses

This section presents the research hypotheses that emerged from the research factors mentioned above, as well as the rationale by which they were formulated. The resulting, and novel, research model comprises nine hypotheses that form a two-level hierarchical structure.

Six factors are assumed by the model to positively and significantly impact the green purchase intention of electronics customers. The latter, together with the willingness to pay and the demographic variables, determine the green purchasing behavior of consumers of electronic products. The complete research model is displayed graphically in Figure 1. In the following section, we discuss the empirical support for the nine research hypotheses that comprise the model.

Based on the findings reported earlier (Hojnik et al. [33]), it is assumed that customer perception of electronic products from green supply chains will have a significant positive impact on green purchasing intentions. Chen and Chang [47] and Yu and Lee [48] confirmed that customer perceptions of green values have a significantly positive effect on purchase intention. Oluwajana et al. [49] suggested that customers’ environmental commitment has a positive and significant effect on purchasing continuity toward an eco-friendly product.

Overall, previous research (Al Mamun et al. [50]; Cerri et al. [51]) established the linkage between customers’ environmental commitment and the intention to procure eco-friendly products, which led to the formulation of research hypothesis 2.

Scholars have documented that a person’s level of environmental awareness has a clear and substantial effect on their attitude to green products, and this, in turn, affects their inclination to buy such items (Yadav and Pathak, [52]; Paul et al. [26]). Moreover, Michaelidou et al. [53] and Fauzan and Azhar [54] argue that environmental concern is one of the most significant factors that directly affect green purchase intentions. In line with the previous argument, Majeed et al. [55] found that customers’ environmental concerns have an impact on their purchase intentions. In the same framework, it has also been reported that the high environmental interest of customers is directly associated with a substantial level of intention to purchase these products (Jaiswal and Kant, [15]; Naz et al. [34]).

The existing body of research suggests that buyers who hold more positive views about green products tend to be more engaged in the process of deciding to purchase these products (Lee, [56]; Joshi and Rahman, [16]). Furthermore, Liao et al. [57] found that there is a statistically significant and positive impact of customer attitudes on green purchase intention. Consequently, this research aims to study the connections between attitudes toward green products and the intention to purchase them (Jaiswal and Kant, [15]).

The perceived environmental knowledge factor can be defined as an individual’s cognitive capacity to comprehend issues concerning the environment or sustainability, particularly in areas like air, water, and soil pollution, energy usage, waste generation, and their impact on both society and the natural world (Tan, [41]; Yadav and Pathak, [52]). This subjective measure of perceived environmental knowledge was examined by Jaiswal and Kant [15] to explore the role of attitude towards green products and green purchase intention. The recent research by Elbarky et al. [58] found that there is no significant correlation between perceived environmental knowledge and green purchase intention; however, they stated that further research incorporating other moderators and mediating factors has to be undertaken.

Within the realm of research on eco-conscious customer behavior, many scholars have extensively examined customers’ sense of effectiveness (Tan, [41]; Kim, [59]; Dagher and Itani, [60]). According to Majeed et al. [61], “Given the limited studies on the direct impact of customer’s self-efficacy belief on personal norms, and drawing on the above, it is clear that customers’ self-efficacy belief influences customer personal norms in protecting the natural environment” (i.e., purchasing green services and products). Additionally, some academic studies have indicated that the perceived effectiveness of such efforts is closely linked to, and impacts, their decisions to purchase these products (Tan, [41]; Kang et al. [62]).

The inclination of an individual to buy environmentally friendly products is referred to as their green purchase intention. Levine and Strube [43] conducted research aimed at understanding how green purchase intention affects the eco-conscious buying behavior of undergraduate students and the study’s findings revealed a strong and significant correlation between intentions and the purchasing behavior of the subjects; consequently, customers tended to exhibit more extensive eco-friendly buying behaviors (Naz et al. [34]).

According to Le Gall-Ely [63] “Willingness to pay or reservation price, defined as the maximum price a given consumer accepts to pay for a product or service, is of particular interest as it is richer in individual information”. Additionally, willingness to pay represents the highest amount a customer is prepared to spend in order to acquire a specific environmentally friendly product (Li and Meshkova, [64]). Numerous research studies have investigated customers’ readiness to incur extra expenses to acquire products with a minimal impact on the environment. Scholars have documented that customers are open to paying an additional cost if they are assured that this contributes to environmental protection (Moser, [65]; Hinnen et al. [66]; Naz et al. [34]).

Several studies have been conducted to assess green purchasing behavior in relation to social and demographic variables (Prakash and Pathak, [38]; Chekima et al. [67]). It has been reported that parameters such as age, gender, and educational level are paramount to understanding customers’ green purchasing behavior (Naz et al. [34]). As a result of this analysis, we derived the following nine hypotheses:

Hypothesis 1. 

Customers’ perceptions of green electronic products have a positive and significant impact on their intention to purchase electronics from green supply chains.

Hypothesis 2. 

The environmental commitment of customers has a positive and significant impact on the intention to buy green electronic products.

Hypothesis 3. 

The stronger the environmental concern, the stronger the intention of customers to purchase green electronic products.

Hypothesis 4. 

Attitudes towards green electronic products have a positive and significant impact on the intention to purchase such products.

Hypothesis 5. 

Perceived environmental knowledge has a positive and significant impact on the intention to purchase green electronic products.

Hypothesis 6. 

The stronger the perceived efficiency of customers, the stronger the purchase intention of electronic products that originate from green supply chains.

Hypothesis 7. 

The stronger the green purchase intention, the stronger the customers’ green purchasing behavior toward electronic products.

Hypothesis 8. 

The stronger the willingness to pay, the stronger the customers’ green purchasing behavior toward electronic products.

Hypothesis 9. 

Demographic variables positively and significantly impact the customers’ green purchasing behavior toward electronic products.

2.3. Research Methodology

The population targeted by this survey comprises residents of Greece, regardless of gender, age, or educational level. In short, the only limitation for participation in this research was that the participants had to be exclusively resident in Greece, otherwise, it was not possible to proceed to the next step.

Due to the fact that the survey questionnaire was distributed exclusively electronically via Google Forms, it is reasonable to conclude that it was targeted at Internet users only. The questionnaire was distributed in various ways, all of them electronic. This was primarily conducted via email, LinkedIn, Facebook, and Messenger, and posted as a link on some websites. It is clear, therefore, that the sampling approach adopted is the “convenience” and the “snowball” approach since researchers could not control those who viewed and filled in the questionnaire. Each of the nine factors was measured using multiple questions. These variables were derived from relevant international studies and were measured using a five-point Likert scale (i.e., from 1—strongly disagree to 5—strongly agree).

The questionnaire consists of four main sections. In the first section, participants are asked about their demographic characteristics, i.e., age, gender, level of education, and place of residency. In the second section are questions about six factors that influence customers’ perceptions and purchasing preferences. The third section includes questions related to the two factors of intention to buy green products and the willingness to pay for such products. Finally, the fourth section includes questions about the dependent factor, green purchasing behavior.

The scales used to measure the factors incorporated in the proposed research model were adopted from various sources, including Jaiswal and Kant [15], Chaudhary and Bisai [35], Prakash and Pathak [38], Tan [41], Hojnik et al. [33], and Naz et al. [34]. A total of 45 closed-ended questions were used to measure all the research factors. Since these scales were in English, they were initially translated into Greek and then back-translated (by a different person) into English to ensure that there was no problem with the translated scales.

Before the full-scale distribution of the questionnaire used in the present survey, the necessary validity check was carried out to ensure that its content and purpose would be easily and fully understood by the majority of the participants.

A pilot application of the questionnaire was conducted in a group of 10 people to identify any ambiguities in its content or general problems of understanding or formulation of the terms used. In addition to this, in-depth discussions were held with students and professionals on the content of the questionnaire to check whether the content of the questionnaire, as a whole, was understandable.

Closed-ended questions with answers on a five-point Likert scale were chosen to simplify the way in which the participant was asked to complete the questionnaire and to make the analysis of the data easier. The total number of questions was 45.

The sample initially included 152 people (n = 152); however, 5 of these people were excluded because they declared themselves to be foreign residents and thus did not proceed to the subsequent stages of the questionnaire. Therefore, the final sample consisted of 147 people, i.e., n = 147. After the above procedures, the necessary corrections were made to the structure of the questionnaire, as well as to its wording and content, so that it could be easily understood by the participants.

All this was absolutely necessary because the factors and their variables were derived from a large number of articles found in the international literature and for this reason, it was necessary to ensure full understanding by the Greek population and successful adaptation to the Greek realities.

Of the individuals who constituted the sample, 48.7% and 51.3% were male and female, respectively. Regarding the ages of the participants, 27.6% were between 26 and 30 years old, 24.3% belonged to the 31–35-year-old age group, and 15.1% were between 21 and 25 years old. All other age groups in the sample constituted substantially lower percentages. Finally, 36.2%, 31.6%, 9.9%, and 9.9% of the survey participants held postgraduate, university, technological institution, and high school degrees, respectively.

Explanatory factor analysis (EFA) was used to unveil underlying patterns in the set of observed variables. Before diving into EFA, preliminary tests like Bartlett’s test of sphericity and the Kaiser–Mayer–Olkin measure were used to assess whether the data were suitable. Bartlett’s test checked whether there were patterns, and KMO assessed sampling adequacy. Eigenvalues revealed how much variance each factor explained, with values above one indicating significance. Factor loadings showed the strength of the relationship between variables and factors. Total variance explained (TVE) gave the cumulative proportion of explained variance. Cronbach’s alpha measured internal consistency reliability. Together, these tests and indices help us understand the underlying structure and reliability of factors identified through EFA.

3. Results

3.1. Factor Analysis

Factor unidimensionality was examined by performing explanatory factor analysis (EFA). More specifically, the following measures were examined: Bartlett’s test of Sphericity and Kaiser–Mayer–Olkin (KMO) (accepted scores > 0.600), Eigenvalue, factor loadings (accepted scores > 0.600), and total variance explained (TVE) (accepted scores > 60.000). Furthermore, Cronbach’s alpha was used to estimate the reliability of the factors (accepted scores > 0.600) (Shrestha, [68]). The results (

Table 1. Factor analysis.

	Items	KMO	TVE	Factor Loadings	Cronbach’s α	Mean	Std. Dev.
Customers’ perceptions	4/4	0.636	51.094	0.651–0.799	0.679	3.96	0.573
Environmental commitment	4/4	0.833	75.098	0.854–0.885	0.876	4.43	0.649
Environmental concern	7/8	0.845	53.604	0.629–0.822	0.849	4.05	0.644
Attitude	2/2	0.500	90.160	0.950–0.950	0.891	4.42	0.665
Environmental knowledge	5/5	0.798	60.591	0.731–0.842	0.837	3.49	0.721
Customer effectiveness	3/3	0.684	68.562	0.809–0.864	0.766	4.01	0.631
Purchase intention	6/6	0.860	65.931	0.750–0.842	0.892	4.03	0.703
Willingness to pay	3/3	0.682	79.025	0.812–0.928	0.865	3.58	0.915
Green purchasing behavior	9/10	0.904	59.929	0.639–0.922	0.913	3.47	0.782

) are satisfactory and support the claim that the factors are both valid and reliable. It should be highlighted that of the 45 items originally used, only 2 were discarded.

The means, in the second to last column of Table 1, can be interpreted as follows: Customer perception of green electronic products is positive, and the majority of customers feel quite strongly about environmental commitment. Customers are quite concerned about the environment and have quite positive attitudes towards the idea of buying green electronic products; nonetheless, they believe they have moderate environmental knowledge. Customers believe that they can help and act effectively to protect the environment and agree that they intend to buy green electronic products; however, they seem to be a little reluctant to pay more for such products compared with conventional ones. Customers seem more reluctant to buy green electronic products when it comes time for the final purchase decision.

The results of analysis of variance (ANOVA) clearly show that the scores of only three factors are differentiated when the gender of the respondents is taken into consideration, while only four factor scores significantly differ when the age of the participant is considered (

Table 2. Analysis of variance.

	Gender	Age	Education
Customers’ perceptions		0.035
Environmental commitment	0.003
Environmental concern	0.004	0.006
Attitude	0.039
Environmental knowledge
Customer effectiveness
Purchase intention		0.021
Willingness to pay
Green purchasing behaviour		0.008

). On the other hand, it seems that the education level of the participant does not differentiate the score of any factor. This result suggests that gender and age should be included in the proposed research model along with the other nine factors.

3.2. Structural Equation Modelling

The first conclusion that can be drawn is that, based on the model fit indices used (

Table 3. Model-fit indices.

	Cmin/DF	CFI	GFI	NFI	RMR	RMSEA
Accepted Scores	<5	>0.900	>0.900	>0.900	<0.100	<0.100
Actual Scores	3.015	0.921	0.928	0.890	0.081	0.097

), the model is valid since the actual scores for these indices are within accepted ranges. The second one is that the prediction power of the model is satisfactory since it can explain 63% of the variation in the value of the main dependent factor (green purchasing behavior). Interestingly, it can also explain 56% of the variation in the value of the second dependent factor (purchase intention). Third, “willingness to pay” is the factor with the highest direct impact on both “green purchasing behavior” (0.40) and “purchase intention” (0.38). Fourth, it seems that “customers’ perception” and “environmental commitment” do not significantly affect any of the other factors in the model, thus they are discarded from the final model. Finally, age is the most important demographic characteristic since it affects not only the dependent factor, but also three others (purchase intention, environmental concern, and knowledge).

Figure 2 shows the resulting structural equation model and

Table 4. Standardized, direct, indirect, and total effects.

		Gender	Age	Environmental Concern	Attitude	Customer Effectiveness	Willingness to Pay	Purchase Intention	Environmental Knowledge
Environmental concern	D	0.274	0.204
	I	0.000	0.000
	T	0.274	0.204
Willingness to pay	D	0.000	0.000	0.547
	I	0.150	0.111	0.000
	T	0.150	0.111	0.547
Purchase intention	D	0.000	0.165	0.291	0.208	0.164	0.378
	I	0.136	0.101	0.207	0.000	0.000	0.000
	T	0.136	0.266	0.498	0.208	0.164	0.378
Environmental Knowledge	D		0.192
	I		0.000
	T		0.192
Green purchasing behaviour	D	0.000	0.148	0.000	0.000	0.000	0.405	0.207	0.381
	I	0.089	0.173	0.324	0.043	0.034	0.078	0.000	0.000
	T	0.089	0.322	0.324	0.043	0.034	0.483	0.207	0.381

presents the standardized direct, indirect, and total effects. As far as the examination of the proposed hypotheses is concerned, only eight of the initially proposed hypotheses are accepted, while two (H1 and H2) are rejected (

Table 5. Hypothesis testing.

			Direct Effect	Total Effect
H1	Customers’ perceptions	Purchase intention	Reject	Reject
H2	Environmental commitment	Purchase intention	Reject	Reject
H3	Environmental concern	Purchase intention	Accept	Accept
H4	Attitude	Purchase intention	Accept	Accept
H5	Knowledge	Purchase intention	Reject	Reject
H6	Customer effectiveness	Purchase intention	Accept	Accept
H7	Purchase intention	Green purchasing behaviour	Accept	Accept
H8	Willingness to pay	Green purchasing behaviour	Accept	Accept
H9a	Gender	Green purchasing behaviour	Reject	Reject
H9b	Age	Green purchasing behaviour	Accept	Accept
H9c	Education	Green purchasing behaviour	Reject	Reject

). Hypothesis H9 was mixed since it referred to the effect of the demographic characteristics (gender, age, and education) on the dependent factor (green purchasing behavior). The results suggest that H9 is accepted only when the age of the participant is considered.

Furthermore, some new relationships also emerged (

Table 6. New relationships emerging from structural equation modeling.

		Direct Effect	Total Effect
Knowledge	Green purchasing behaviour	Accept	Accept
Environmental concern	Green purchasing behaviour	Reject	Accept
Age	Environmental concern	Accept	Accept
Age	Knowledge	Accept	Accept
Age	Willingness to pay	Reject	Accept
Age	Purchase intention	Accept	Accept

). Considering these new relationships, the significance of age emerged as it seemed to affect four of the factors incorporated in the proposed research model. Finally, the strong direct effect of “environmental knowledge” and the strong indirect effect of “environmental commitment” on the dependent factor (green purchasing behavior) should also be highlighted.

Overall, it is observed that when only the direct impacts are considered, four factors affect green purchasing behavior (willingness to pay, knowledge, purchase intention, and age), with the strongest being the willingness to pay (0.405). However, when indirect effects are also considered, environmental concern is also associated with green purchasing behavior (in fact, this factor has the third strongest total impact on green purchasing behavior).

4. Discussion

As shown in the previous analysis, hypothesis H1 was not confirmed, thus suggesting that customers’ perceptions of green electronic products do not affect their intention to buy green products. In short, although someone may have a positive opinion of green electronic products, it does not necessarily mean that they will have the intention to buy them. In the same framework, hypothesis H2 was also not confirmed, probably underlying the fact that feeling obligated and committed to protecting the environment does not strengthen one’s intention to buy green electronic products.

As far as hypothesis H3 is concerned, the results are in line with the findings of previous research (Jaiswal and Kant, [15]; Naz et al. [34]). Specifically, a customer’s environmental concern has a statistically significant impact on purchase intention, indicating that customers with increased environmental concerns are also more intent on buying green electronic products. Thus, customer awareness of environmental issues plays an important role in whether they will eventually show an intention to purchase such products. Additionally, it was found that environmental concern has a significant indirect impact on green purchasing behavior, something that probably indicates that customers who have high levels of concern about the planet’s environmental “wellbeing” are willing to pay more for green products and, eventually, purchase green and eco-friendly products.

Further, the impact of customers’ attitudes on purchase intention (H4) indicates that when customers have and exhibit positive attitudes towards green electronic products, they have a very high likelihood of proceeding to buy them. Lee [56] and Joshi and Rahman [16] found similar results.

As far as the impact of customers’ knowledge on purchase is concerned (H5), it emerged that although environmental knowledge does not affect customers’ intention to buy green electronic products (something that is in line with the findings by Elbarky et al. [58], interestingly, it has a rather strong direct effect on green purchasing behavior. This can probably be explained by the fact that those who actually buy green electronic products ultimately have increased environmental knowledge, which is not the case with those who simply intend to buy such products.

Regarding customer effectiveness (H6), the results are in line with the findings of Tan [41] and Kang et al. [62] and suggest that if customers believe that their actions can help change the environment and, generally, help protect the environment, then eventually they will want to buy green electronic products.

Focusing on customers’ purchase intention (H7), the results suggest, as expected (confirming the findings by Naz et al. [34]), a significant impact on green buying behavior, indicating those who would consider switching to eco-friendly brands depending on whether they prefer green electronic products to non-green electronic products. Thus, customers who show an intention of buying green products are also more likely to engage in green buying behavior and, therefore, to buy such products. Similar to the prior hypothesis, customers who are willing to pay more for green electronic products are more likely to purchase such products (H8), as previous research indicates (Moser, [65]; Hinnen et al. [66]; Naz et al. [34]).

Finally, regarding hypothesis H9, the results partially confirm the findings of previous studies [34]. The results suggest that age affects green purchasing behavior, in contrast to gender and education. It seems that older people, over the age of 40 in particular, show a higher intention to buy and eventually buy green electronic products. It is worth noting that the education criterion did not have any impact on green purchasing behavior. This probably means that more teaching units focusing on customers’ green purchasing behavior should be added throughout the various educational levels. This practice will possibly strengthen the value and impact of education on green purchasing behavior. The results also showed that age directly affects environmental concern, knowledge, and purchase intention. This observation suggests that as an individual’s age increases, their awareness and understanding of environmental concerns, such as recycling, also tend to increase. Consequently, this heightened knowledge contributes to the development of a more environmentally conscious shopping approach.

5. Conclusions

The application value of this research can be summarized as follows: First, a novel conceptual model pertaining to green consumerism in the electronics market is introduced. This model is tested in a selected geographical area and other scholars can apply and assess it in other environments/regions or “build” on it to expand it. Second, this research provides insight into customers’ green purchasing mindsets and supports the R&D of new or revamped products in the electronics industry. Additional details are provided in the remainder of this section.

The purpose of this study was to understand how customers view green electronic products and supply chains and to draw conclusions about whether or not green supply chains have an effect on customer intent and purchasing behavior. Additionally, the study aimed to ascertain whether the implementation of green supply chains has any impact on customer intent and purchasing behavior. Specifically, it highlighted the significant importance of parameters such as “age”, “environmental concern”, “knowledge”, and “willingness to pay”. Initially, it appeared that “age” may serve as a plausible determinant of an individual’s receptiveness to environmental concerns and, therefore, their inclination to partake in environmentally conscious consumer behavior as they advance in age. The environmental concerns of customers appeared to exert a significant impact on their purchase intentions. Specifically, those who demonstrate a higher level of environmental consciousness are more inclined to acquire green electronic devices, even when these products are seen to be more costly. Furthermore, the acquisition of “knowledge” has a substantial role in shaping customers’ adoption of environmentally conscious purchasing practices. Ensuring that consumers get a full understanding of the environmental consequences associated with a product is crucial in order to foster a greater and more conscious embrace of sustainable consumption behaviors.

As far as the managerial implications of this research are concerned, it can be suggested that there are important implications for companies producing, as well as for companies selling, electronic products and specific electronic products originating from green supply chains. This is because there are key implications for both types of business. The growing desire for goods that not only satisfy the immediate demands of customers but also have advantages for the environment in the long run. Nevertheless, it is essential for businesses, and particularly marketing managers, to acknowledge that the criteria customers use to evaluate products and services are susceptible to ongoing shifts and modifications. Customers who are interested in making a purchase are thinking carefully about not just the benefits but also the environmental effects of the products they are considering buying. This suggests that a product demonstrating harmful effects on the environment can see a fall in sales, similar to a product that fails to comply with specified needs and client expectations, despite the fact that the product is environmentally conscientious in nature. According to Hojnik et al. [33], buyers consider not only the person but also the environmental aspects associated with a product before announcing whether or not they intend to make a purchase based on their evaluation. Based on the above, someone may draw the conclusion that having the desire to buy environmentally friendly electronic devices almost always results in actually making environmentally friendly purchases, at least in the case of people living in Greece.

Customers are driven to buy green electronic products when they have the intention to buy green and the willingness to pay extra. On the other hand, the intention to buy green is driven by customers’ environmental concerns, attitudes toward green electronic products, and perceived customer effectiveness. In addition, increased awareness of society and states on environmental issues changed customers’ behaviors and led them to purchase green products. The product strategies of businesses that produce or sell environmentally friendly goods will need to be rethought, particularly with regard to value proposition, communication tactics, and eco-labeling. In particular, it is suggested that businesses devote a greater portion of their resources to the development of environmentally friendly marketing strategies and participation in activities associated with corporate social responsibility. This approach aims to enhance customer awareness, knowledge, and environmental responsibility, ultimately leading to a beneficial impact on green market intents and the promotion of green customerism. Corporate social responsibility serves as a means for organizations to integrate entrepreneurship with ethics, thus extending their emphasis beyond mere financial gains [33].

Limitations and Directions for Future Research

The first limitation is the relatively small sample size, especially when the number of factors examined is considered. The current research should, therefore, be considered as a pilot study; it is recommended that other relevant studies should include larger samples. Future similar research should be undertaken in countries with different economic and cultural bases. This will contribute to a more comprehensive understanding of the many environmental factors that impact green consumer behavior. Furthermore, it is recommended that future studies incorporate perceived environmental performance and corporate social responsibility factors as key determinants of green market intent. This suggestion is based on the findings of previous research, which indicate that customers exhibit a greater inclination to purchase products from companies that are perceived to have a strong environmental performance. Moreover, organizations that engage in corporate social responsibility are inclined to create enduring relationships with their customers more effortlessly.

Finally, research on green electronic products will further contribute to a better understanding of the key drivers of green market intent and green purchasing behavior. Promoting green customer purchasing behavior is an effective and perhaps the only way of reducing negative impacts on the environment. Equally important, however, is that customers should stop looking exclusively at their own self-interest, but also operate on the basis of environmental commitment and general thinking about environmental protection by adopting green purchasing behaviors. Companies should also make efforts to gain customer trust and loyalty in electronic products coming from green supply chains, leading more customers to green customerism and shopping behaviors.