Fuzzy inference system to study the behavior of the green consumer facing the perception of greenwashing

With increased consumption of green products, organizations have promoted their products and services as green to attract an environmentally growing segment. However, 98% of the products advertised as green have some element characterized as greenwashing, affecting consumer satisfaction. Given the need to classify subjective, ambiguous and imprecise indicators as consumer satisfaction degree of green products, a computational model of measurement is proposed that incorporates fuzzy logic techniques to reduce the incidence of uncertainty in decision analysis processes, facilitating decision-making. The fuzzy rule-based system created allows the efficient handling of uncertainties and vagueness of input data, measuring the relationships between various input variables to analyze consumer behavior and perception of greenwashing. The Mamdani's Inference Method was used to make different combinations of linguistic variables and to evaluate the relationship of these variables to consumer behavior, implementing a quantitative method of decision-making regarding the behavior of the variables. As a result, it is observed that greenwashing confuses and influences the consumer in green product confidence in retail. After the application of the system, it is concluded that the results are feasible and with the use of fuzzy logic, the system can help in the analysis and determination of the consumer satisfaction degree, and can helps companies to make future forecasts about consumer behavior of green products. The proposed approach enriches the information on the attitudes of green consumers when they perceive greenwashing. Besides, the system facilitates the decision-making and actions of both consumers and companies that apply the greenwashing as a marketing strategy. (c) 2019 Elsevier Ltd. All rights reserved.