جستجوی مقالات مرتبط با کلیدواژه "حکمرانی داده محور" در نشریات گروه "علوم اجتماعی"

The importance of data and data-driven analytics in governance is undeniable. Data-driven governance is one of the prerequisites for achieving good governance and citizen satisfaction with governance. To promote and expand this concept and to familiarize with the obstacles and challenges of its implementation in public and sectoral governance in Iran, a call for papers titled “Data-Driven Governance” was issued by the Journal of Strategic Policy Studies in Public Policy in the winter of 2023. Out of more than 40 abstracts received, six research articles were finally accepted in three main areas: the concept of data-driven governance and its prerequisites, the obstacles and challenges of data-driven governance, and the ethical and policy considerations of data-driven governance. These articles are presented in this special issue for readers and enthusiasts of data-driven governance. This special issue is an initial effort to value the application of data in governance, and it is hoped that it will promote this important matter in other scientific journals in the country and, more importantly, in the field of governance practice

The public sector is facing diverse and complex challenges in the current era. Solving these challenges, which are often related to the development of communication and data, will not be possible except by benefiting from the capacities created by these technologies and realizing data-driven governance. Artificial intelligence technology is one of the revolutionary technologies in the current era that can be used to improve the quality of governance. In order to apply this technology, it is necessary to first consider possible obstacles and challenges in a conscious way. Therefore, in the current research, after a systematic review of the literature, 16 obstacles and challenges of using artificial intelligence in the public sector have been identified and prioritized using the fuzzy simple weighting method(FSAW). According to the findings, "access to data and its quality" have been identified as the most important obstacle, and "ignoring public and social considerations" as the most important challenge. Finally, the identified cases are placed in 6 economic, social, political, managerial, technological and ethical categories, and policy recommendations are proposed according to each category and relevant stakeholders.

Data-driven governance advocates for the use of data in policymaking to effectively guide societal affairs. Policy research is a method that emphasizes the use of real data and multilateral analysis at various stages of policymaking, . The aim of this study is to identify the main components of the policy research system to enhance the feasibility of its effective implementation. To this end, in addition to utilizing archival documents, semi-structured interviews were conducted with 16 academic and executive experts, and the main components of the policy research system were identified using thematic analysis. According to the research findings, the main components of the policy research system include inputs, processes, outputs, feedback, and actors. Inputs refer to human resources, financial resources, a clearly defined issue, and the policymaker, all of which must be timely integrated into the system for the policy research system to be established. The process of the policy research system pertains to the various evaluations carried out by policy research centers, which include pre-evaluation, evaluation during implementation, and post-evaluation. The outputs of the policy research system may comprise proposed policies resulting from pre-evaluation, recommendations to overcome implementation barriers, decisions regarding the continuation or amendment of executed policies, as well as lessons learned. The feedback from this system also refers to revisions in evaluation methods, data collection, indicators gathered, and required human resources that feed back into the inputs or processes. Three actors:supporters, implementers, and overseers—are introduced as the sustaining and driving agents of this system at different stages

Big data is considered a valuable asset and provides significant opportunities for policy makers. Data-driven governance is a new approach in public administration and seeks to use these opportunities with the systematic use of data. Data-driven governance needs to comply with special ethical and policy considerations, and in the absence of them, it faces malfunctions such as discrimination, power concentration, social harms, reduction of public trust, and human rights violations. The current research approach is inductive and based on interpretivism philosophy. In this qualitative-exploratory research, data was collected using 15 in-depth and unstructured interviews with experts in the field of data-driven governance. The snowball sampling method was used to select the experts of this research. Finally, after analyzing the interviews with thematic analysis method, ethical and policy considerations of data-driven governance were identified. Based on the findings of this research, the ethical considerations of data-driven governance include data and its management transparency, legal access, considering people's authority and consent, preserving people's privacy, and collecting high quality data. Additionally, its policy considerations encompass data-driven dynamics, training and culture development, the creation of a monitoring and correction mechanism, cooperation and partnership with the private and international sectors, and ensuring data security.

As a key mechanism in governance, the intersection of data-driven governance and regulatory frameworks can play a crucial role in addressing the numerous challenges of Data-centric governance. This issue is particularly pertinent given the advancements in data-based technologies, such as artificial intelligence, alongside the evolving needs of society. This paper employs the meta-synthesis method to examine regulatory approaches in managing these challenges. The primary objective of this research is to identify and analyze the policy and ethical challenges associated with data-driven governance and to propose effective regulatory solutions for managing these issues. The study's findings indicate that formulating comprehensive and clear regulations, establishing independent regulatory bodies, developing technical standards and guidelines, public education and awareness, and international cooperation are among the most important regulatory aspects of data-driven governance. This research, with a focus on the country's needs and based on a regulatory approach, offers practical and policy solutions that could improve the oversight and enforcement of laws related to data-driven governance. This paper employs the meta-synthesis method to examine regulatory approaches in managing these challenges. The present study is qualitative, with its philosophical foundations and paradigm being interpretive. The research orientation is applied, aimed at developing practical knowledge in a specific field.