Abstract:One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome.

Social shopping behavior of fashion embraces various activities, direct/indirect complex and dynamic interpersonal happening during the process of buying fashion and causes customers' pleasure and satisfaction from purchasing intention, which in long-term helps sales improvement. This study has taken place in city of Tehran, Iran in order to assess the social purchase behavior of consumers and drivers in the field of fashion garments. Data analysis was performed using partial least squares. Research findings indicate a significant positive relationship between obsessed with fashion garments and the five dimensions of social shopping behavior. On the other hand, there is a positive and meaningful relationship between materialism and the need for uniqueness by consumers' involvement toward fashion apparel.