2020
DOI: 10.1016/j.jclepro.2019.03.060
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Fuzzy inference system to study the behavior of the green consumer facing the perception of greenwashing

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Cited by 101 publications
(70 citation statements)
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“…However, the research based on the theory of planned behavior has not taken into account the interference of external situational factors, consequently, it is difficult to interpret the complex process of green consumption. Third, the decision-making process of consumers' green consumption behavior is discussed on the basis of decision-making theory to explore the logic of the decision of buying environmentally friendly products [39][40][41][42][43]. Among them, rationalism, behaviorism and empiricism respectively describe an effective way for consumers to make purchasing decisions and explain the decision rule for consumers to buy green products [39,40].…”
Section: Green Consumptionmentioning
confidence: 99%
See 1 more Smart Citation
“…However, the research based on the theory of planned behavior has not taken into account the interference of external situational factors, consequently, it is difficult to interpret the complex process of green consumption. Third, the decision-making process of consumers' green consumption behavior is discussed on the basis of decision-making theory to explore the logic of the decision of buying environmentally friendly products [39][40][41][42][43]. Among them, rationalism, behaviorism and empiricism respectively describe an effective way for consumers to make purchasing decisions and explain the decision rule for consumers to buy green products [39,40].…”
Section: Green Consumptionmentioning
confidence: 99%
“…Among them, rationalism, behaviorism and empiricism respectively describe an effective way for consumers to make purchasing decisions and explain the decision rule for consumers to buy green products [39,40]. The rationalism viewpoint believes that consumers will collect as much information as possible when considering green purchasing to make reasonable decisions [41,44]. However, consumers may not carry out this complex and elaborate process of collecting information every time and may not make rigorous logical purchases in reality.…”
Section: Green Consumptionmentioning
confidence: 99%
“…The American Marketing Association (AMA) in 1975 stated that "marketing of products that are assumed to be environmentally safe and friendly is called green marketing". In general, there is no universal definition of green marketing (also similarly termed as environmental marketing, eco-marketing, social marketing, organic marketing, and sustainability marketing), but ecological awareness is a common component of the definitions [2,36] where business organizations are committed to promoting, designing, distributing, and pricing products that do not negatively impact the environment [37]. In the recent past, many authors defined green marketing [3,9,[38][39][40][41][42][43][44].…”
Section: Why Green Marketing?mentioning
confidence: 99%
“…Green marketing recommends using eco-friendly products, e.g., refillable, ozone friendly, healthy food, phosphate-free and recyclable products. Moreover, green marketing can be applied in environmentally friendly ways to satisfy the customers' needs, wants, and demands by protecting the environment and society [1,2].…”
Section: Introductionmentioning
confidence: 99%
“…Research, Society and Development, v. 9, n. 9, e887997772, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i9.7772 Research, Society and Development, v. 9, n. 9, e887997772, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i9.7772 Research, Society and Development, v. 9, n. 9, e887997772, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i9.7772 A presente análise com redes neurais faz parte de uma série de aplicações sem sistemas inteligentes artificiais , tal como ilustrado em Gabriel Filho et al (2011, 2015, 2016, Putti et al (2014Putti et al ( , 2017, Viais Neto et al (2019a, 2019b e Martínez (2020). Mais especificamente, na área de redes neurais, destacam-se os trabalhos de Bonini Neto et al (2017, Chitero et al (2020) e Souza et al (2019).…”
Section: Metodologiaunclassified