مدیریت پایدار داده‌های سازمانی در شبکه‌های اجتماعی: چهارچوب مفهومی با رویکرد فراترکیب

Purpose: The main objective of this study is to identify the key components of sustainable management of organizational data in social networks. Organizational members use social networks to receive information and news about the organization, as well as to exchange information among themselves, and organizational audiences can communicate with the organization, receiving answers to their questions and the services they need. Managers also more easily monitor the outcomes of organizational activities and improve their performance by receiving feedback. . By generating organizational data and sharing them on social networks, organizations create a type of formal communication, and this data becomes part of organizational memory. On the other hand, it seems that social networks do not support data retention, and organizational data shared on social networks is often unstable and may not be available for the long term. Therefore, it can be acknowledged that sustainable management of social networks data poses a challenge for organizations, and identifying and implementing the components of sustainable data management, as well as providing a coherent conceptual framework of these components, can be considered as a solution in this regard.
Methods: To conduct the present study, a systematic review method with a meta-synthesis approach was employed. For meta-synthesis, the present study used the Sandelowski and Barroso (2006) method. In this method, the steps included specifying the research question, systematically reviewing previous research, evaluating and selecting appropriate articles, extracting information, analyzing and synthesizing qualitative findings, quality control, and presenting the findings. All relevant research sources were identified and analyzed using keywords in scientific databases. In total, after screening the sources in the meta-synthesis stages, 48 sources were identified and extracted published between 2006 and 2024 and 101 codes were identified and extracted. Then, based on the processes introduced by Zahid et al. (2023) for the secure management of government organization data presented in the long term, the main and secondary components were identified and categorized.
Findings: Based on the findings of the present study, 16 main components and 76 sub-components were identified, including collection tools and methods (data extraction, data discovery, data creation, data collection tools, collaborative collection approach), collection criteria (preservation, data evaluation, data selection, completeness of data collection, data transparency, data source information, collection objectives, optimizing the selective collection process, determining the population (users), specifying the scope of collection, data collection frequency, requirements), preparation (data preprocessing, data cleansing, quality assessment, data mapping, data indexing), data analysis (machine learning, data interpretation, data classification, data integrity, data aggregation, data cross-linking), security and privacy (data anonymization, data traceability, protection, bit-level protection, risk management), storage infrastructure (database, long-term data preservation platform, data repository mission determination, storage space, recording and maintenance, infrastructure security), organization (data update, persistent identifier assignment, metadata, file format, data appearance, process automation), access and exploitation (retrieval, searchability, accessibility, interactivity, data literacy), user interface and interaction (user interface, search interface, message interface, use of programming language, use of personas), ethical and legal issues (fairness, terms of use, publication of a code of conduct, user agreement, intellectual property, copyright, restrictions), trust and security (trust building, security standards, use of blockchain, increasing immutability), sharing ethics (ethical and legal sharing, balance between privacy and public information rights, censorship, rules and obligations), standards (use of international standards), structure and process (creation of a common terminology, policy, development, assignment of responsibilities), ethical issues (licenses) and guidelines (deletion guidelines).
Conclusions: This study is a pioneering effort in the field of comprehensively examining the components of sustainable organizational data management in social networks. These components can serve as a basis for decision-making by organizational managers in the field of social network data management. Furthermore, it seems that the proposed components can be used to develop a roadmap and guide for sustainable organizational data management in social networks.