VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live

Arturas Kaklauskas, Domnica Dzitac, Jurate Sliogeriene, Natalija Lepkova, Ingrida Vetloviene

Abstract


The best and worst places to live have been analysed in the world for many years and multiple criteria analysis has been used for that purpose. The quality of housing and its environment, pollution, green places, public spaces, physical movement and health, crime rates and individual safety, the wellbeing of youngsters, unemployment, job value, economic scarcity, governance, circadian rhythm, weekly rhythm and other factors are the focus of such analyses that aim to determine levels of positive emotions and happiness in built environment. Questionnaires are the most common tool for such analyses, where inhabitants are asked to rank their happiness experience as a whole in built environment. Many studies demonstrate that happy people are effective in multiple areas of their life including job efficiency, salary, health, human relations, etc. The innovative aspect of this research stems from the fact that biometric technologies (affective attitudes, emotional and physiological states) and the VINERS method developed by the authors are used to determine the best places to live and to serve neuro ads of homes for sale. To do this, rational segments of homebuyers are determined according to their demographic profiles (age, gender, education, marital status, families with children, main source of income), consumer psychographics and behaviour (happy, sad and angry along with valence and heart rate) and then select a rational video ad for such rational segment. The aim of our research is to develop the VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live (VINERS method) by combining the Somatic Marker Hypothesis, biometrics, neuromarketing and COPRAS method. This article presents a case study to demonstrate the VINERS method put to practice.

Keywords


COPRAS and VINERS Methods, Neuromarketing, Multiple criteria analysis, Best Places to Live.

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References


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DOI: https://doi.org/10.15837/ijccc.2019.5.3674



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