Abstract
Online dispute resolution (ODR) mode is an effective mechanism to resolve mobile e-commerce disputes. However, there are some obstacles in the development of ODR, such as low public acceptance, difficult technology realization and lack of uniform management standards. At present, the problem that needs to be studied urgently in the field of ODR is to analyze the characteristics of the case according to the ODR mediation case, to study which characteristics have an impact on the mediation results, and then to improve the efficiency of mediation. Based on the collection of mobile e-commerce transaction dispute mediation applications, this paper carries on the text mining, observes and summarizes the original text, extract variables from the text that can describe the case attribute information. The variables found to be able to distinguish the type of case are: X4 (whether the platform was involved), X9 (type of dispute), Y (case status), X8 (number of claims), X10 (type of product), X5 (number of respondent), X3 (number of applicant), X6 (amount of claim), X7 (difference ratio). The difference variables feature distribution can better describe the characteristics of the cases. According to the characteristics of case attributes, the second-order clustering method is used to cross-classification. In this paper, the ODR cases are divided into four categories. The paper find that the cases of mediation failure are mostly type I and type II, while the cases of mediation success are mostly type III and type IV. This kind of classification is advantageous to the mediator to the dispute case classification processing, enhances the mediation success rate.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.