دانلود مقاله نقش بازاریابی رسانه های اجتماعی در قصد بازخرید محصولات سبز
چکیده
مقدمه
بررسی ادبیات
روش شناسی
نتایج
بحث و نتیجه گیری
مشارکت های نویسنده
تامین مالی
بیانیه هیئت بررسی نهادی
بیانیه رضایت آگاهانه
بیانیه در دسترس بودن داده ها
تضاد منافع
مراجع
Abstract
Introduction
Literature Review
Methodology
Results
Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
Abstract
This study explores the impact of social media marketing activities and ESG green brand involvement on the repurchase intention of green products among members of Taiwan’s green product social media groups. Using the Theory of Reasoned Action, the study employs a quantitative approach, collecting data through an online survey from 438 valid responses. Structural equation modeling (SEM) was applied to analyze the relationships between social media marketing activities (independent variable), green values, environmental concerns, brand image, and brand involvement (mediating variables), and repurchase intention (dependent variable). The findings reveal that social media marketing activities significantly enhance green values, environmental concerns, and brand image, which positively influence brand involvement. Brand involvement significantly mediates the relationship between green values, environmental concerns, brand image, and repurchase intention. This confirms that effective social media marketing can strengthen consumer loyalty and repurchase intentions for green products. The study suggests that companies should integrate green values, environmental concerns, and brand image into their social media marketing strategies to enhance consumer engagement and repurchase intentions. Leveraging social media influencers and interactive content can effectively promote green products and foster a culture of sustainability, creating a win–win situation for companies, consumers, and the environment. This research contributes to the literature by highlighting the mediating roles of green values, environmental concerns, and brand involvement in social media marketing for green products. It provides practical insights for companies aiming to enhance green product repurchase intentions through targeted social media strategies and ESG initiatives, illustrating the strategic use of social media marketing to boost consumer loyalty and sustainable consumption.
Introduction
The effects of global warming include the melting of polar ice, sea level rise inundating low-lying coastal areas, and global climate changes that result in heavy rains, droughts, and even desertification [1,2]. Global warming poses a threat to ecosystems, food chains, water resources, human activities, and public safety [3,4]. The primary cause of global warming is the emission of greenhouse gases, particularly carbon dioxide, which is directly or indirectly emitted by human activities [5]. As the world’s population reaches 8 billion, the climate and environmental quality are suffering a heavy price. Green products have a minimal impact on the environment throughout their life cycle, from production to disposal. They are typically made using sustainable materials and processes, designed to be energy-efficient, and often include features that reduce pollution. Green products aim to conserve resources, reduce the carbon footprint, and promote environmental sustainability [6,7]. To promote the production and sale of green products, reduce corporate carbon emissions, minimize the environmental impact of production lines, and enhance energy efficiency, the United Nations Environment Programme (UNEP) released the report “Who Cares Wins”. The report stresses the importance of business operators and investors balancing profit with their responsibilities. It clearly states that companies should prioritize ESG principles: environmental protection, social responsibility, and corporate governance [8]. Within these principles, environmental protection includes the standards to be considered in the design and manufacture of green products.
The United Nations Environment Programme (UNEP) and various environmental NGOs worldwide have advocated for and promoted the production and marketing of green products [9,10]. Emphasis on ESG (environmental, social, and governance) principles in sustainable corporate development, rising consumer awareness, and governmental environmental regulations are driving companies to shift towards producing green goods. However, the design and manufacturing of green goods often incur higher costs, leading to higher prices and reduced product competitiveness. To prevent companies from hesitating to switch to green products production due to higher costs, a direct solution is needed to enhance consumer purchase behavior regarding green products. This, in turn, boosts companies’ willingness to produce green products, creating a win-win situation for businesses, consumers, and environmental protection.
Results
4. Results
4.1. Descriptive Analysis
The majority of the respondents were male, with 292 people making up 66.7% of the total. Most of the respondents were married, with 347 people representing 79.2%. In terms of education, 317 respondents, or 72.4%, had a graduate degree or higher. Additionally, 304 respondents, or 69.4%, had a monthly income of TWD 70,001 or higher. These details are summarized in Table 1.
4.2. Structural Equation Modeling
4.2.1. Measurement Model Test
1. Convergent Validity
According to Anderson and Gerbing [103], a complete structural equation model (SEM) analysis should be divided into at least two stages. The first stage involves the measurement model, followed by the evaluation of the structural model in the second stage. Confirmatory factor analysis (CFA) is equivalent to measurement model evaluation and is part of SEM analysis. In this study, the evaluation and refinement of CFA measurement models were based on the two-stage approach proposed by Kline [104]. If the measurement model fit is acceptable, the complete SEM model can then be reported. The measurement model was estimated using the maximum likelihood estimation (MLE) method. The estimated parameters included factor loadings, reliability, convergent validity, and discriminant validity. Table 2 provides the standardized factor loadings, composite reliability, and average variance extracted (AVE). According to Fornell and Larcker [105] criteria for convergent validity, the following conditions must be met: first, the standardized factor loading for each variable should be higher than 0.50; second, composite reliability should exceed 0.60; and third, the average variance extracted should be higher than 0.50.