سید محمد زرگر

Intelligence is an essential factor in supply chain. It prepares the ground for effective and timely communication and facilitates information sharing among supply chain components in both production and service sectors. Hence, the present study seeks to identify the components of services intelligent supply chain and categorize them as a comprehensive model by using the meta-synthesis approach. In this research, total of 437 articles in the field of services intelligent supply chain was identified and examined at first step. Articles were in the period of 1980 to 2022. Finally, after evaluation of articles, 53 articles remained. Then, based on the process of the meta-synthesis and the use of coding method, four main fields and a number of sub-fields were found for the services intelligent supply chain variable. Initial codes introduced in the software for conceptualization and categorization. The main fields of services intelligent supply chain included intelligence dimensions, intelligence conditions, intelligence strategies and intelligence consequences. Each of these main fields has a number of sub-fields. The result of the study shows that in order to implement the services intelligent supply chain, several dimensions and components are considered, concepts such as real-time online information flow, intelligent fund flow, intelligent services flow, process management and technology infrastructure play an important role. Suggestions are presented in accordance with the comprehensive model identified. Also, the conceptual model designed can be useful as a basis for future research in the direction of practical manual in the effective use of the services intelligent supply chain.

Introduction: User trust is one of the main ethical principles that affect the success or failure of a social network platform. The multiplicity and interaction of users in social networks leads to the risks of data breach or disclosure of users' information. Therefore, the importance of correct decision-making by the managers of this social network and the prediction of events is of great importance. Therefore, the main goal of this research is to identify the main factors affecting users' trust and solutions to compensate the lost trust among the users of this social network. Material and Methods: The current research was applied and among post-event researches. The statistical population of this research was media and communication experts who were selected using a random sample of 52 people. The questionnaire tool was made by the researcher. Data analysis was done with Kolmogorov-Smirnov test, Friedman test and dynamic systems analysis, and SPSS and Vensim simulation software were used. Results: In this research, 34 factors affecting trust in social networks were investigated. The most important of which were internet fraud, the release of malicious software, the disclosure of personal information, the type of social networks and adherence to ethical principles, etc., and things such as cooperation and coordination between people, responsibility and commitment, benevolence, excessive use of social media in priority. There is an end. The validity of this model was proved by evaluating the appropriateness of the model boundary based on the purpose of the model and ensuring the realistic behavior of the model under limit conditions. Conclusion: It is possible to increase the trust of users as well as the solutions for breaching data and privacy of users through the construction of cause and effect loops and finding the root of their main causes. Also, the effective factors and its solutions in the form of three balance circles were investigated and rooted.