Colour Choice as a Strategic Instrument in Neuromarketing
Social relationships have been and are the basis for achieving objectives of all kinds, whether altruistic or lucrative. Among the aspects that make up non-verbal communication are physical appearance in general, clothing, and, in particular, colour combinations. In this article, we analyse whether...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/25142 |
| Acceso en línea: | http://hdl.handle.net/10256/25142 |
| Access Level: | acceso abierto |
| Palabra clave: | Lògica difusa Fuzzy logic Neuromàrqueting Neuromarketing Comunicació no verbal Nonverbal communication Lògica polivalent Many-valued logic |
| Sumario: | Social relationships have been and are the basis for achieving objectives of all kinds, whether altruistic or lucrative. Among the aspects that make up non-verbal communication are physical appearance in general, clothing, and, in particular, colour combinations. In this article, we analyse whether colour combinations can be established in individuals’ clothing that maximise their chances of success for a specifically established social objective. To measure this objective, we use multivalent logics, which are characterised by their great flexibility and adaptability. Within the framework of fuzzy logic, we extract evaluations for various colours based on the judgements of experts, provided by recognised authors in the literature, and compare these with the results obtained in a survey conducted by the authors. For the purposes of contrast, we employ two instruments with accredited validity: Similarity by Direct Computation (SDC) and the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS multicriteria method) |
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