ابوذر عرب سرخی

This study investigates the potential of blockchain technology to support compliance with the General Data Protection Regulation (GDPR). By integrating blockchain's core features, such as transparency, immutability, and data encryption, with GDPR principles like data minimization and accuracy, the research develops a comprehensive applicability model. This model serves as a Reference Framework for evaluating blockchain systems' alignment with GDPR requirements. The study employs a meta-synthesis method and qualitative content analysis of 67 articles, culminating in a detailed examination of 31 selected articles. The findings reveal that blockchain technology can significantly enhance GDPR compliance, particularly in securing personal data and ensuring transparency. Importantly, the research introduces a novel model validated by a panel of 13 experts, which identifies and prioritizes key areas where blockchain can effectively support GDPR requirements. This model provides valuable insights for policymakers, industry leaders, and technology developers, emphasizing blockchain's strategic role in enhancing data protection under GDPR.

Blockchain is one of the trending emerging technologies that enables immutable data storage over distributed ledgers. The fundamental features of blockchain technology, such as record and identity traceability and immutability makes it an attractive alternative for the state-of-the-art information systems. Thus, blockchain has found its way into various fields. In Iran, blockchain technology has been employed in different areas including: commercial mining platforms, secure exchange platforms, and innovative trustless projects. One of the main applications of blockchain is secure management of sensitive information, which makes it a suitable infrastructure for providing advanced control over data in police task forces. The motivation behind this research is to provide a conceptual framework for employing blockchain in law enforcement organizations by analysis and comparison of best practices in other countries and academic case-studies. We provide a systematic overview of case-studies by qualitative content analysis. Moreover, the reliability of our statistics is evaluated by Cohen's kappa coefficient roughly 0.64. Finally, the prioritized applications were evaluated by a 14 member experts panel through fuzzy Delphi method with a Kendall’s Coefficient of Concordance of W=0.711, indicating high rates of agreement among members. To this end, “trustless authentication systems”, “distributed data/resource/information management”, and “inter-department integrated information systems” were selected as most valuable applications of blockchain for police task forces and law enforcement agencies in Iran.

Despite the vital role of information in relational-oriented firms, there are limited studies on the impact of information quality on relationship marketing. To address this gap, this study develops a conceptual model to examine the impact of information quality on the successful implementation of relationship marketing by assessing the mediating role of salespeople's relational competency. The proposed model is tested using structural equation modeling (SEM) technique with data collected from 140 employee-customer pair sample of Shatel Group (Tehran, Iran). Stratified sampling is our applied research methodology, we also employed questionnaire for data collection. The results indicate that while there is no meaningful relationship between information quality and salespeople's relational competency, there is a significant relationship between salespeople's relational competency and relationship marketing. Accordingly, it could be concluded that salespeople's relational competency cannot act as a mediating variable and thus information quality cannot affect relationship marketing indirectly.