Using Data Mining Techniques to explore Shopping Addiction and Emotion Based Decision Making in Consumers

Compulsive shopping and spending is described as a pattern of chronic, repetitive purchasing that becomes difficult to stop and ultimately results in harmful consequences. It is defined as an impulse control disorder and has features similar to other addictive disorders without involving the use of an intoxicating drug. There has been described as Compulsive buying disorder which occurs when obsessive buying — basically a shopping addiction — leads to negative consequences. The condition affects nearly six percent of the population of the United States. In addition to the distress that arises from the disorder itself, compulsive buying disorder is also strongly indicative of a co morbid condition. Through this paper, shopping addiction is combined with emotion based decision making in order to study emotional empathy and generally consumer behavior of social media users. Emotion-based decision-making, the ability to use emotions when making decisions is a prerequisite for sound judgment in human beings. Emotional empathy is a capacity which allows an appreciation of separateness of human beings and at the same time allows them to connect by attending to and feeling the emotional experiences of others (Hanson, R., (2007). Emotional empathy builds on one’s tendency of emotional awareness. Individuals who make compulsive shopping maybe lack in emotional empathy and the decision making is more emotional rather than rational. The data were collected by completion of the self-report questionnaires "Bergen Shopping Addiction Scale" the "Emotion-Based Decision-Making Scale", "Balanced Emotional Empathy Scale" and used for the application of
data mining methods. Specifically, for the collection of data electronic versions of the above scales were created through Google Forms service and posted through the website “http://www.cicos.gr/iccmi2017/saeb”. 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 results of the present study represent among others, that the emotion based decision making in combination with low levels of emotional empathy can be important predictive factor for the shopping addiction behavior.