Pathology
Pantea Ghaffari; Seyyed Mehdi Alvani; Amirhesam Arabi
Abstract
In the contemporary era of digital transformation and escalating complexity of social, economic, and environmental challenges, the integration of artificial intelligence into public policymaking has evolved into a strategic imperative. This research is designed with the objective of conducting a critical ...
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In the contemporary era of digital transformation and escalating complexity of social, economic, and environmental challenges, the integration of artificial intelligence into public policymaking has evolved into a strategic imperative. This research is designed with the objective of conducting a critical analysis of artificial intelligence's role in the era of digital transformations and increasing complexity of social, economic, and environmental issues, utilizing artificial intelligence in public policymaking has become a strategic necessity. This research aims to critically analyze the role of artificial intelligence in the policymaking process and provide an indigenous framework for using AI in Iran's decision-making system. The research methodology has been developed through a systematic review using PRISMA standards and comparative analysis of leading countries' experiences such as Canada, Estonia, and Singapore. In this study, 632 articles were identified in the initial search, and after applying inclusion and exclusion criteria, 28 credible scientific articles were subjected to in-depth analysis. The research findings indicate that artificial intelligence plays a key role in all stages of policymaking, including problem identification, policy analysis, solution design, effective implementation, and continuous improvement evaluation. The most important AI functions include big data processing, identifying hidden patterns, predicting outcomes, and social network analysis. However, challenges such as algorithmic bias, lack of model transparency, and privacy threats still persist. Based on the findings, this article proposes a three-layered indigenous framework appropriate to Iran's requirements that, while strengthening transparency, accountability, and efficiency, provides the foundation for developing data-driven and intelligent governance.
Modeling
Abdollah Saedi; Nazanin Asadi
Abstract
Big data in the organization can create insight that leads to better decision-making and discovering strategic paths. The purpose of this research is to analyze and evaluate the consequences of big data in human resource management in government organizations. This research is practical in terms of its ...
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Big data in the organization can create insight that leads to better decision-making and discovering strategic paths. The purpose of this research is to analyze and evaluate the consequences of big data in human resource management in government organizations. This research is practical in terms of its purpose, and in terms of the method of collecting descriptive information, it is of the survey type, and in terms of typology, it is among mixed research. The statistical population of the research includes university professors in the field of management and human resource managers in government organizations, 17 of whom were selected using the purposeful sampling method and based on the principle of theoretical adequacy. In the qualitative part of the data collection tool, there is a semi-structured interview, the validity and reliability of the tools were confirmed using content validity and intra-coder and interrater reliability methods, respectively. The tool for collecting data in the quantitative part is a questionnaire, which was confirmed using content validity and retest reliability. In the qualitative part of this research, the data obtained from the interview were identified using the Max-QDA-E software and the analysis coding method and the consequences of big data in human resource management. In the quantitative part of the research, the prioritization of factors and their causal relationships were determined using the fuzzy cognitive mapping method. The results show that intelligent recruiting and hiring, identifying skill gaps, foresight, talent management, eliminating discrimination and retention, employee retention and performance management are respectively the most important consequences of big data in human resource management. The governance of big data in government organizations enables human resource managers to act more intelligently in the fields of human resources such as recruitment and employment, recruitment, salary system, etc.
Jafar Ahanghran; Yazdan Shirmohammadi; Mahmoud Karimi
Abstract
The purpose of this study is to investigate the application of big data and IoT analysis strategies to gain a sustainable competitive advantage in public organizations by considering the capabilities of big data analysis. This study evaluates data quality as a strategy for gaining a competitive advantage ...
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The purpose of this study is to investigate the application of big data and IoT analysis strategies to gain a sustainable competitive advantage in public organizations by considering the capabilities of big data analysis. This study evaluates data quality as a strategy for gaining a competitive advantage as interdisciplinary research while introducing the capabilities of big data analysis and the Internet of Things. In terms of philosophical foundations of research, this research is based on the paradigm of positivism, in terms of research approach, is quantitative, and in terms of research strategy, is part of survey research. Library and field resources were used in data collection. The statistical population of the research is unlimited and the statistical sample of this research includes 384 managers and specialists using random and convenience sampling methods from the statistical population of the research applying the Morgan table. To collect data in this study, a questionnaire was used, the validity of which was confirmed by experts as content validity using SPSS software, and its reliability was confirmed using Cronbach's alpha coefficient. Also, fit indices and path analysis were evaluated using AMOS software. Research findings show that data quality should become part of the strategy to create value for government organizations. The ability to analyze big data also positively mediates the relationship between data quality and competitive advantage. On the other hand, strategic performance and financial management have a positive and significant effect on competitive advantage.
