تبیین اثر عوامل روان‌شناختی مصرف‌کنندگان بر انواع رفتار خرید سبز: نقش تعدیل‌گر ویژگی‌های جمعیت شناختی

Aim and Introduction:
 As consumer awareness and concern about environmental issues grow, and the demand for eco-friendly products intensifies, companies are increasingly adopting green marketing strategies to capitalize on emerging market opportunities. Green marketing, aimed at minimizing or eliminating adverse environmental impacts, involves understanding the factors that influence consumers' intentions and behaviors related to eco-friendly shopping, as well as empowering them to make informed decisions. Recently, numerous studies have sought to explain the purchasing behavior of consumers of green products. Despite the valuable insights gained from these studies, some evidence indicates that a more profound understanding of this consumer behavior is still necessary. For instance, although consumers' awareness of environmental issues and the detrimental effects of environmental degradation often leads to green purchasing behavior, some studies have found no significant relationship between these factors. However, analyzing the types of green purchases made by consumers may offer a more nuanced understanding of the factors that influence their purchasing intentions and behaviors. Building on the theory of planned behavior, this study examines how demographic and psychological characteristics influence consumers' green shopping behaviors, differentiating among various types of green shopping behaviors, including unconditional shopping, conditional shopping, and accidental shopping. By contributing to the development of the Theory of Planned Behavior, this research aims to provide companies with actionable insights for creating more targeted green marketing strategies and enhancing the effectiveness of these initiatives.
Methodology: This applied research utilizes a descriptive survey approach. A conceptual model, consisting of four hypotheses, was developed based on a thorough review of the literature. To collect data, a 7-point Likert scale electronic questionnaire consisting of 25 items was administered to Iranian consumers who had previously participated in green purchasing.
The statistical population for this study comprised all Iranian consumers with experience in green purchasing, from which a random sample was drawn during the winter of 2023. Data collected from 380 consumers of green products were analyzed using variance-based structural equation modeling (SEM), a technique selected for its robustness to sample size and data distribution, high predictive power, and suitability for theory development. Structural Equation Modeling (SEM) was identified as an appropriate method for testing the research hypotheses and analyzing the relationships between demographic information and consumer opinions.
Findings: The comprehensive evaluations confirmed the acceptable quality of both the measurement and structural models for the three types of green shopping behaviors: unconditional, conditional, and accidental. With the research data considered reliable, the study proceeded to test the research hypotheses. The results indicate that perceived consumer effectiveness, willingness to adopt environmentally friendly practices, and perceived behavioral control significantly influence unconditional green purchasing behavior. Additionally, the willingness to be environmentally friendly has a significant, albeit weak, effect on both conditional and incidental purchase behaviors. Notably, demographic variables such as age, gender, and education do not have a significant moderating effect on the relationships between the independent variables—perceived consumer effectiveness, willingness to be environmentally friendly, and perceived behavioral control—and the various types of green purchasing behaviors (unconditional, conditional, and accidental).
Discussion and Conclusion: The results of the study suggest that, despite environmental concerns, consumers may not prioritize green purchases if they perceive that green products do not match their non-green traditional counterparts in terms of features such as price, ease of use, durability, and efficiency. Therefore, to encourage the consumption of green products, it is crucial to emphasize their features in conjunction with their environmental benefits. By highlighting these aspects, we can address the concerns of environmentally conscious consumers. Offering price discounts on eco-friendly products can also help address some of the concerns of consumers. Notably, if green and traditional products are perceived as similar, consumers are more likely to engage in impulsive shopping behavior. Furthermore, the study recommends utilizing psychological factors, rather than demographic characteristics, for the market segmentation of green products. However, due to certain methodological limitations, caution should be exercised when applying the recommendations of this study. First, this study employed available probabilistic sampling. Second, the tool used to measure the psychological characteristics of individuals was primarily developed in Western cultures. Third, despite the emphasis on the confidentiality of responses, some individuals may exhibit bias in their answers due to social desirability. This study examined the factors influencing unconditional, conditional, and random green buying behavior in general. Future research could investigate these behaviors separately for different product categories. For instance, findings may vary across a range of health-related purchasing behaviors. In addition, geographical and cultural characteristics can significantly influence various buying behaviors, underscoring the necessity for cross-cultural studies to gain a deeper understanding of these differences. It is also advisable to develop culturally sensitive tools for measuring psychological traits and purchasing intentions. Finally, according to the research literature, incorporating additional modifier variables into the conceptual framework—such as recycling intention and environmental awareness—could enhance the model's explanatory power.