Electronic Commerce

Purpose: With the expansion of technology and its impact on the various aspects of human life, particularly in the field of commerce and exchanges, and with the expansion of competition in the field of international trade, the study of various aspects of electronic commerce as one of the most important effects of this type of business, is inevitable. The present research seeks to answer the main question: "what is the judicial citation of electronic evidence in electronic commerce cases, and what legal and social effects will it have?". Methodology: The present study is a descriptive-analytic (qualitative) one and uses inferential methodology using the researcher's ability to understand the legal scans related to the judicial citation of electronic evidence in electronic commerce cases and also to rely on evidence and facts are used. Findings: Using electronic communications as a means of conducting various types of interaction, such as deals, poses an important topic for e-commerce that due to the features of cyberspace, the clarification of the legal system in electronic commerce cases has a particular importance to the other issues of IT rights in the line with judicial justice. Conclusion: If the process of discovery and access to electronic evidence is carried out in accordance with the legal principles, it can be the basis for issuing the sentence and the rules governing the evidence (law) are also the same for the electronic commerce cases.

As electronic commerce has gained widespread popularity, payments made for users' transactions through credit cards also gained an equal amount of reputation. Whenever shopping through the web is made, the chance for the occurrence of fraudulent activities are escalating. In this paper, we have proposed a three-phase scheme to detect fraudulent activities. A profile for the card users based on their behavior is created by employing a machine learning technique in the second phase extraction of a precise communicative pattern for the card users depending upon the accumulated transactions and the user's earlier transactions. A collection of classifiers are then trained based on all behavioral pattern. The trained collection of classifiers are then used to detect the fraudulent online activities that occurred. If an emerging transaction is fraudulent, feedback is taken, which resolves the drift's difficulty in the notion. Experiments performed indicated that the proposed scheme works better than other schemes.

The purpose of this study was to identify barriers to the development of the electronic-marketing in the sports industry. The present study is a correlational and applied one. The statistical population consisted of 203 individuals including university faculty members, experts, managers of sport federations, members of sport federations board, and experts in e-marketing. The available non-random sampling method is also used in this research. Moreover, data collection tool was a researcher-made questionnaire that was extracted from two external articles. Besides, ten experts in sport management confirmed the validity of the questionnaire. The reliability of the questionnaire was likewise calculated using Cronbach alphas test. Confirmatory factor analysis and structural equation modeling were used to analyze the questionnaire data. The results showed that sports marketing barriers were cultural and social, technical, legal and organizational, high cost, limitation of government support, lack of information, low skills of staff and finally security threats. It is suggested that the policy makers of the country's sports industry consider these barriers before developing strategies for developing e-marketing capabilities.