EPEIM

Decision Making with Machine Learning Techniques in Consumer Performance: Empathy, Personality, Emotional Intelligence as Mediators

Evgenia Gkintoni1, Niovi Christina Papavasileiou2, Hera Antonopoulou2, Constantinos Halkiopoulos,2, Giorgos Stamoulis2

 

[Abstract]

Despite the importance of emotion in decision making (e.g., ohm and Clore 2002; Luce 1998; Pham 1998; Ruth 2001), research has yet to fully understand how consumers’ use emotional information to make effective decisions. A growing body of research continues to focus on the emotions present in consumption situations, however a better understanding of emotional processing abilities can have important effects on consumer performance outcomes. The current research focuses on the impact of emotional intelligence onconsumer decision making and evaluates the consumer emotional ability in a sample of social network users. Additionally, through the present project, empathy, personality and emotional intelligence are being measured as intrusive variables that mediate and determine the consumer decision making.

The innovative element of the current project was the application of data mining methods in psychometrics. Specifically, in order to clarify the consumer emotional decision making, were administered to the participants’ five scales that have been created through Google Forms* service and posted through the website “https://www.cicos.gr/iccmi2017/epeim”. Then the collected data were selected for analysis, with relevant transformations in order to have a suitable form for the implementation of the respective machine learning algorithms included in the software package R. The administered scales were: a) Consumer Emotional Ability Scale-Revised by the present authors in order to define how emotional intelligence affected performance among consumer relationships, b) Empathy Quotient a new self-report questionnaire, for use with adults of normal intelligence, c) Balanced Emotion Empathy Scale in order to assess the emotive component of empathy, d) Eysenck Personality Questionnaire, measuring personality traits, e) Emotional Intelligence Questionnaire, defining four aspects of emotionally thinking.

Findings of the present research indicated that emotional ability predicts consumer performance beyond the effects of cognitive ability, supporting the importance of the emotional ability construct in consumer behavior.

Keywords: Consumer Ability, Emotional Intelligence, empathy, decision making, R, Machine Learning

 

References:

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  2. Eysenck H.J, (1950), Criterion analysis – an application of the hypothetico – deductive method in factor analysis, Psychol. Rev. 1950, 57, p. 38 – 53.
  3. Gkintoni, E., Halkiopoulos, C., Antonopoulou, H., Togias, P., Mitropoulos, A., “Emotional Intelligence in Social Network Consumers”, International Conference on Contemporary Marketing Issues, 22-24 June 2016, Heraklion, Greece
  4. James G., Witten D., Hastie T., Tibshirani R. An Introduction to Statistical Learning with Applications in R. Springer; 2013.
  5. Cohen H., Lefebvre C. editors. Handbook of Categorization in Cognitive Science. Elsevier; 2005.
  6. Baron-Cohen, S. and Wheelwright, S. (2004) The Empathy Quotient: An Investigation of Adults with Asperger Syndrome or High Functioning Autism, and Normal Sex Differences. Journal of Autism and Developmental Disorders, 34, 163-175. http://dx.doi.org/10.1023/B:JADD.0000022607.19833.00
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1Dept. of Psychology, University of Crete, Greece

2Dept. of Business Administration, Technological Educational Institute of Western Greece, Greece

[Conference Program: ICCMI 2017]

© The Author(s) 2017. Published by 5th International Conference Proceedings on behalf of C.I.CO.S Research Team and the Entrepreneurship & Digital Innovation LAB of the Business Administration Department (Technological and Educational Institute of Western Greek) and Department of Psychology (University of Crete).

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

*Research Questionnaire: Decision Making with Machine Learning Techniques in Consumer Performance: Empathy, Personality, Emotional Intelligence as Mediators

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