Multi-Attribute Decision Making
Saba Amiri; Saeed Setayeshi
Abstract
Purpose: Neuromarketing is an interdisciplinary and emerging field which can be used in order to relate consumer behavior to neuroscience. So, in recent decades, the importance and interest in buying sustainable products for protecting the environment has been increased. Thus, the present study was done ...
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Purpose: Neuromarketing is an interdisciplinary and emerging field which can be used in order to relate consumer behavior to neuroscience. So, in recent decades, the importance and interest in buying sustainable products for protecting the environment has been increased. Thus, the present study was done with the aim of fuzzy analytic hierarchy process of neuromarketing evaluation criteria for sustainable products.Methodology: The research was performed with a quantitative approach and by using multiple-criteria decision analysis. For this purpose, in order to gain a deep understanding of the subject and collecting useful data, after carefully reviewing the related studies, the views of 16 experts were collected using a fuzzy hierarchical researcher-made questionnaire, which the inconsistency rate of the questionnaires confirmed reliability of them. Also, sensitivity analysis was used to ensure.Findings: The results showed that the criteria for evaluating neuromarketing are in seven categories, which based on FAHP are: accuracy, biasness, exploration of memory and emotion, information quality, usefulness, time saving, cost, respectively. Also, the alternatives of marketing for sustainable products affected by neuromarketing in order of priority are: advertising, product design and development, branding, consumer decision, pricing and distribution. Sensitivity analysis also showed that the research findings are confirmed, but in the case of two criteria of biasness and exploration of memory and emotions, there is a possibility of displacement.Originality/Value: Neuromarketing, due to the provision of high-precision and high-quality information and the reduction of bias in the analysis of results, provides the possibility of predicting consumer buying behavior and affects the marketing mix of sustainable products.