طراحی الگوی پذیرش هوش مصنوعی در حکمرانی هوشمند با استفاده از رویکرد فراترکیب

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مدیریت دولتی، دانشکدۀ مدیریت و اقتصاد، دانشگاه سیستان و بلوچستان، زاهدان، ایران.

2 استاد، گروه مدیریت دولتی، دانشکدۀ مدیریت و اقتصاد، دانشگاه سیستان و بلوچستان، زاهدان، ایران.

3 دانشیار، گروه مدیریت دولتی، دانشکدۀ مدیریت و اقتصاد، دانشگاه سیستان و بلوچستان، زاهدان، ایران.

4 استاد، گروه خط‌‌مشی‌گذاری عمومی، دانشکده علوم اداری و سازمانی، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.

10.22059/jipa.2025.398124.3737

چکیده

هدف: یکی از مفاهیمی که در سال‌های اخیر در راستای تحول دولت‌ها و حرکت به‌سوی دولت هوشمند مطرح شده است، مفهوم پذیرش هوش مصنوعی در قالب حکمرانی هوشمند است. شناسایی عوامل مؤثر بر پذیرش هوش مصنوعی در حکمرانی و دولت‌های هوشمند، می‌تواند نقشه‌راهی برای طراحی و اجرای خط‌مشی‌های مؤثر باشد. یکی از اهداف حکمرانی هوشمند، ایجاد رضایت در میان همۀ ذی‌نفعان جامعه است؛ به ویژه، در مواجهه با چالش‌هایی نظیر رشد جمعیت، بحران‌های متعدد و پیچیدگی‌های مدیریتی، نقش محوری ایفا می‌کند. این پژوهش تلاش دارد تا با استفاده از رویکرد فراترکیب، چارچوبی جامع برای پذیرش هوش مصنوعی در حکمرانی هوشمند طراحی کند. این چارچوب با هدف شناسایی، تحلیل و طبقه‌بندی مؤلفه‌ها و عوامل مرتبط با پذیرش فناوری‌های نوین، به حکمرانی کمک می‌کند تا از ظرفیت‌های هوش مصنوعی در همۀ ابعاد طراحی، مدیریتی و اجرایی بهره‌مند شود. همچنین، این مطالعه، در پی آن است که از طریق مرور پژوهش‌های پیشین، راه‌حل‌هایی جامع برای بهره‌برداری بهینه از اطلاعات و داده‌ها ارائه دهد و زمینه را برای پژوهش‌های آتی فراهم کند.
روش: رویکرد پژوهش حاضر کیفی است و برای دستیابی به اهداف پژوهش از روش فراترکیب استفاده شده است. این روش، بر پایه مدل پیاز پژوهش ساندرز و همکاران شکل گرفته که یکی از روش‌های رایج و معتبر در پژوهش‌های کیفی، برای ترکیب سامان‌مند یافته‌های پیشین است. در این پژوهش، به‌منظور بررسی عوامل مرتبط با پذیرش هوش مصنوعی در حکومت، منابع علمی معتبری شامل ۱۱۲۳ مقاله و کتاب از پایگاه‌های دادۀ خارجی، بررسی شده است. منابع بر اساس معیارهای ورود و خروج مشخص و با تمرکز بر اطلاعات و داده‌های مرتبط با حکمرانی هوشمند و عوامل ضروری پذیرش فناوری انتخاب شدند. داده‌های این پژوهش از منابعی استخراج شدند که بین سال‌های ۲۰۱۵ تا ۲۰۲۵ میلادی، در معتبرترین پایگاه‌های علمی منتشر شدند. نتایج حاصل از این تحلیل سامان‌مند، به ارائۀ یک مدل جامع برای پذیرش هوش مصنوعی، بر پایۀ ترکیب یافته‌های کیفی و شناسایی مؤلفه‌های محوری منجر شد.
یافته‌ها: یافته‌ها نشان می‌دهد که چارچوب جامع و یکپارچۀ پذیرش موفق هوش مصنوعی در حکمرانی هوشمند، چهار لایۀ اصلی را دربرمی‌گیرد: ۱. لایۀ اطلاعاتی: زمینۀ فناوری؛ ۲. لایۀ نهادی: زمینۀ سازمانی؛ ۳. لایۀ ارزشی: زمینۀ محیطی؛ ۴. لایۀ کنشی: ظرفیت جذب. مهم‌ترین مؤلفه‌های شناسایی‌شده در این پژوهش عبارت‌اند از: زیرساخت‌های دیجیتال، حکمرانی و امنیت داده و شفافیت الگوریتمی در لایۀ اطلاعاتی؛ فرهنگ سازمانی نوآورانه، رهبری تحول‌گرا و آموزش و توانمندسازی کارکنان در لایۀ نهادی؛ چارچوب‌های قانونی، فشارهای رقابتی و خواسته‌های شهروندان در لایۀ ارزشی و در نهایت، قابلیت‌های پویا و سازوکارهای اشتراک دانش در لایۀ کنشی.
نتیجه‌گیری: پژوهش حاضر با هدف طراحی الگوی پذیرش هوش مصنوعی در حکمرانی هوشمند انجام شد و نتایج آن نشان می‌دهد که پذیرش موفق این فناوری، مستلزم فراهم‌سازی زیرساخت‌های دیجیتالی، تدوین خط‌مشی‌های حمایتی، توسعۀ فرهنگ دیجیتال، تقویت مهارت‌های انسانی و نظارت بر فرایندهای هوش مصنوعی است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The Design of an Artificial Intelligence Adoption Model in Smart Governance Using a Meta-Synthesis Approach

نویسندگان [English]

  • Amirreza Momeni 1
  • Nour Mohammad Yaghoubi 2
  • Seyed Aligholi Roshan 3
  • Ali Asghar Pourezzat 4
1 PhD Candidate, Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchistan, Zahedan, Iran.
2 Prof., Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchistan, Zahedan, Iran.
3 Associate Prof., Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchistan, Zahedan, Iran.
4 Department of Public Policy, Faculty of Public Administration and Organization Science, College of Management, University of Tehran, Tehran, Iran.
چکیده [English]

Objective
In recent years, a key concept in the transformation toward smart governance has been the adoption of artificial intelligence (AI). Identifying the factors that influence AI acceptance in governance can provide a roadmap for designing and implementing effective policies. Smart governance seeks to foster satisfaction among all societal stakeholders and plays a central role in addressing challenges such as population growth, recurring crises, and managerial complexity. Consequently, this study seeks to develop a comprehensive framework for AI adoption in smart governance using a meta-synthesis approach. The proposed framework aims to identify, analyze, and classify the components and factors associated with the acceptance of emerging technologies, enabling governance systems to fully leverage AI capabilities across design, managerial, and operational dimensions. Furthermore, through a systematic review of prior research, this study endeavors to provide integrated solutions for the optimal utilization of data and information, paving the way for future scholarly investigations.
Methods
This study employed a qualitative approach, utilizing the meta-synthesis method to achieve its research objectives. The process was structured according to Saunders et al.’s “research onion” model, a widely recognized and reliable framework for systematically integrating qualitative findings. To examine the factors related to AI adoption in governance, a comprehensive review of 1,123 scholarly articles and books from international academic databases was conducted. Source selection was based on well-defined inclusion and exclusion criteria, with a particular focus on literature related to smart governance and the critical factors influencing technology adoption. The analyzed works were published between 2015 and 2025 in leading scientific databases. The findings from this systematic analysis were synthesized to develop a comprehensive model for AI adoption, structured through the integration of qualitative results and the identification of key components.
Results
The findings reveal that the successful adoption of artificial intelligence in smart governance requires a comprehensive framework incorporating four fundamental layers. First, the informational layer (technological context) encompasses digital infrastructure, data governance and security, and algorithmic transparency. Second, the institutional layer (organizational context) includes an innovative organizational culture, transformational leadership, and employee training and empowerment. Third, the value layer (environmental context) consists of legal and regulatory frameworks, competitive pressures, and citizens’ demands. Finally, the action layer (absorptive capacity) comprises dynamic capabilities and mechanisms for knowledge sharing. Collectively, these four layers and their associated components establish a holistic foundation through which governments can effectively integrate artificial intelligence into the design, management, and execution of smart governance.
Conclusion
This study aimed to design a model for the adoption of artificial intelligence in smart governance. The findings demonstrate that successful technological integration requires robust digital infrastructure, supportive policies, a mature digital culture, enhanced human skills, and continuous oversight of AI-driven processes. The proposed multi-layered framework offers a strategic roadmap for policymakers and administrators, emphasizing that AI adoption is not merely a technical upgrade but a systemic transformation involving technological, institutional, environmental, and capability-based dimensions. Future research should empirically validate and refine this framework across different governmental contexts.

کلیدواژه‌ها [English]

  • Artificial intelligence
  • Smart government
  • Smart governance
  • Future of government

مراجع

پورعزت، علی اصغر؛ عباسی، طیبه؛ مقصودی کناری، شهریار و نامدار جویباری، محمد مهدی (1403). بررسی نقش مؤلفه‌‌های اساسی حکمرانی هوشمند در تحقق شهر هوشمند با روش ISM (مطالعه موردی: شهر تهران). مدیریت دولتی، 16(3)، 535-561. 
روشن، سید علیقلی؛ یعقوبی، نورمحمد و مومنی، امیررضا (1400). کاربست هوش مصنوعی در بخش دولتی (مطالعه‌ای فراترکیب). فصلنامه انجمن علوم مدیریت ایران، 16(61)، 117-145.
 
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مدیریت دولتی
دوره 18، شماره 1
1405
صفحه 263-295

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