Abstract
Customer to customer (C2C) e-commerce has gained a remarkable importance in recent years. Individuals can reach what they desire to obtain as a buyer in an easy way, and also can sell their properties by using mobile applications and websites as e-commerce platforms rapidly. However, high human involvement and internet infrastructure establishes risky situations in e-shopping. In this paper, the risks encountered in e-commerce between individuals were identified, and inter-relations of these risks were discussed with real C2C buyers by using a fuzzy scale. Next, a Fuzzy Interpretive Structural Modeling (FISM) result was extracted. Interdependencies of the C2C e-commerce risks were examined with buyers’ perspectives in order to reach the root causes of these C2C e-commerce risks.
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Karadayi-Usta, S. (2020). C2C E-Commerce Fuzzy Risk Analysis with Buyer Perspective. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_54
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DOI: https://doi.org/10.1007/978-3-030-23756-1_54
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