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الگوی حکمرانی دادهمحور: تابآوری سازمانهای دولتی در مواجهه با بحران | ||
| مدیریت راهبردی دانش سازمانی | ||
| مقاله 2، دوره 9، شماره 2 - شماره پیاپی 33، تیر 1405، صفحه 46-70 اصل مقاله (1.16 M) | ||
| نوع مقاله: مقاله پژوهشی با اصالت | ||
| شناسه دیجیتال (DOI): 10.47176/SMOK.2026.1990 | ||
| نویسندگان | ||
| عبداله ساعدی* 1؛ محمد توسلی2 | ||
| 1استادیار گروه مدیریت ، دانشکده اقتصاد و مدیریت، دانشگاه لرستان، خرم آباد، ایران، Saedi.a@lu.ac.ir | ||
| 2استادیار گروه مدیریت ، دانشکده اقتصاد و مدیریت، دانشگاه لرستان، خرم آباد، ایران، Tavassoli.m@lu.ac.ir | ||
| تاریخ دریافت: 07 دی 1404، تاریخ بازنگری: 21 فروردین 1405، تاریخ پذیرش: 31 اردیبهشت 1405 | ||
| چکیده | ||
| هدف: پژوهش حاضر با هدف تدوین الگوی حکمرانی دادهمحور برای تابآوری سازمانهای دولتی در مواجهه با بحران انجام گرفت. روش پژوهش: جامعه آماری پژوهش را اساتید و مدیران سازمانهای دولتی تشکیل میدهند که با استفاده از روش نمونهگیری هدفمند 16 نفر به عنوان مشارکتکننده انتخاب شدند. ابزار گردآوری دادهها در این پژوهش مصاحبه نیمهساختاریافته است که برای روایی ابزار از روشهای بازبینی توسط خبرگان و اجرای پایلوت مصاحبهها استفاده شد. همچنین جهت پایایی دادهها نیز از روش کدگذاری مستقل توسط دو پژوهشگر و مقایسه نتایج بهره گرفته شد. در تحلیل دادهها، مصاحبهها ضبط و کدگذاری شدند. تحلیل مضمون با استفاده از نرمافزار MAXQDA انجام گرفت و در نهایت الگوی حکمرانی دادهمحور تدوین گردید. یافتهها: یافتههای پژوهش نشان میدهد حکمرانی دادهمحور، متأثر از مجموعهای از عوامل مؤثر همچون زیرساختهای دادهای، حمایت مدیریت و ... است که از طریق راهبردهایی نظیر یکپارچهسازی دادهها، بهرهگیری از هوش مصنوعی و ... عملیاتی میشود. تحقق این الگو منجر به پیامدهایی همچون افزایش تابآوری سازمانی، بهبود سرعت و کیفیت تصمیمگیری و ... میگردد. بحث: سازمانهای دولتی با نهادینهسازی حکمرانی دادهمحور و سرمایهگذاری هدفمند در زیرساختها و توانمندیهای دادهای، میتوانند از آن بهعنوان یک رویکرد راهبردی در مدیریت بحران و افزایش تابآوری سازمانی بهره گیرند. نتیجهگیری: حکمرانی دادهمحور، با نهادینهسازی عقلانیت دادهبنیان در سطوح تصمیمسازی و سیاستگذاری، امکان مدیریت فعال عدمقطعیت، کاهش شکنندگی ساختارهای دولتی و افزایش ظرفیت انطباقپذیری در شرایط بحرانی را فراهم میسازد و میتواند مبنایی راهبردی برای بازطراحی نظام حکمرانی عمومی در عصر بحرانهای پیچیده و دادهمحور تلقی شود. | ||
تازه های تحقیق | ||
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| کلیدواژهها | ||
| حکمرانی داده محور؛ تاب آوری سازمانی؛ فرهنگ سازمانی داده محور؛ نوآوری داده محور؛ بحران | ||
| عنوان مقاله [English] | ||
| Data-driven governance model: resilience of government organizations in the face of crisis | ||
| نویسندگان [English] | ||
| Abdullah Saedi1؛ Mohammad Tavassoli2 | ||
| 1Assistant Professor, Department of Management, Faculty of Management and Economics, Lorestan University, Khorramabad, Iran, Saedi.a@lu.ac.ir | ||
| 2Assistant Professor, Department of Management, Faculty of Management and Economics, Lorestan University, Khorramabad, Iran, Tavassoli.m@lu.ac.ir | ||
| چکیده [English] | ||
| Purpose: This study aimed to develop a comprehensive data-driven governance model to enhance the resilience of public organizations in responding crises and managing uncertainty. Methodology: A qualitative research design based on thematic analysis was employed. The study population consisted of academic experts and senior managers from public organizations. Using purposive sampling, 16 participants were selected. Data were collected through semi-structured interviews, transcribed verbatim, and analyzed using MAXQDA software. Instrument validity was established through expert review and pilot interviews, while reliability was ensured through independent coding by two researchers and comparison of coding results. Results: The findings revealed that effective data-driven governance is supported by several enabling factors, including robust data infrastructure, top management support, organizational capabilities, and data-oriented culture. The proposed model is operationalized through strategies such as data integration, artificial intelligence adoption, advanced data analytics, and digital governance practices. Implementing these strategies enhances organizational resilience by improving the speed and quality decision-making, strengthening crisis preparedness and response, increasing operational flexibility, and promoting more effective organizational performance under uncertain conditions. Discussion: The findings indicate that institutionalizing data-driven governance and making strategic investments in data infrastructure, digital technologies, and analytical capabilities enable public organizations to respond more proactively and effectively to complex and rapidly evolving crises. Conclusion: Data-driven governance institutionalizes evidence-based decision-making across organizational and policy processes, enabling public organizations to anticipate uncertainty, reduce structural vulnerability, strengthen adaptive capacity, and improve crisis management. Accordingly, it provides strategic foundation for redesigning public governance systems in an increasingly complex, dynamic, and data-intensive environment. | ||
| کلیدواژهها [English] | ||
| Data-driven Governance, Organizational Resilience, Data-driven Organizational Culture, Data-driven Innovation, Crisis | ||
| مراجع | ||
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Abdullahi, U., Mohamed, A & Senasi, V (2023) Exploring Global Trends of Research on Organizational Resilience and Sustainability: A Bibliometric Review. Journal of International Studies (JIS), 19 (2), 27-66. https://repo.uum.edu.my/id/eprint/30154/ Alarsaheb, I & Waza, A (2025). Smart Cities and Political Accountability: Challenges of Data-Driven Governance, International Journal of Advance Social Sciences and Education (IJASSE), 3(3), 78-91. https://doi.org/10.59890/ijasse.v3i3.74 Attard, J., Orlandi, F & Auer, S (2016). Data Driven Governments: Creating Value Through Open Government Data, Lecture Notes in Computer Science, 84-110. https://doi.org/10.1007/978-3-662-53416-8_6 Banihashemi, S. A., & Ghermezi, N. (2022). Modeling the effect of knowledge management and social capital on organizational resilience with the mediating role of organizational agility (case study: Employees of Asaluyeh Petrochemical Company). Strategic Management of Organizational Knowledge, 5(4), 173-203. https://doi.org/10.47176/smok.2022.1551 Biagi, V & Russo, A (2022). Data Model Design to Support Data-Driven IT Governance Implementation, Technologies, 10(106), 1-19. https://doi.org/10.3390/technologies10050106 Bui, M (2024). Toward a community-driven approach to urban data-driven governance, Anti-Oppressive Arts-Based Research Methodologies, 87(1), 289-301. https://doi.org/10.1177/17480485241261572 Chandler, D (2020). The Rise of Data-Driven Governance, Current History, 119(813), 3-8. https://www.jstor.org/stable/48614495 Chen, Y., Sun, Y & Lindtner, S (2023). Maintainers of Stability: The Labor of China’s Data-Driven Governance and Dynamic Zero-COVID, Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1-16. https://doi.org/10.1145/3544548.3581299 Cong, W (2021). From Pandemic Control to Data-Driven Governance: The Case of China’s Health Code. A section of the journal Frontiers in Political Science, 3(1), 1-14. https://doi.org/10.3389/fpos.2021.627959 Curran, D & Smart, A (2020). Data-driven governance, smart urbanism and risk-class inequalities: Security and social credit in China, Sage Journals, 58(3), 76-91. https://doi.org/10.1177/0042098020927855 Dencik, Lina; Redden, Joanna; Hintz, Arne; Warne, Harry (2019) .The 'golden view': data-driven governance in the scoring society, Internet Policy Review, 8(2), 1-24, https://doi.org/10.14763/2019.2.1413 Dickson, R (2025). Organizational Resilience as the Springboard for Organizational Success in a Turbulent Business Environment, European Journal of Management Economics and Business 2(2), 3-24. https://doi.org/10.59324/ejmeb.2025.2(2).01 Elugbaju, W., Ijeoma Okeke, N & Anne Alabi, O (2024). Conceptual framework for enhancing decision-making in higher education through data-driven governance, Global Journal of Advanced Research and Reviews, 2(2), 16-30. https://doi.org/10.58175/gjarr.2024.2.2.0055 Farhang,S . (2025). Designing a Crisis Management Improvement Model with Emphasis on the Role of Social Media. Emergency Management, 14(1), 37-52. http://www.joem.ir/article_721106.html?lang=en (In Persian) Feng, R., Zhang, L & Xu, H (2025). Data-driven governance: Developing evaluation indices for China's intelligent political and legal systems, Sustainable Futures, 10(2), 22-36. https://doi.org/10.1016/j.sftr.2025.101207 Firouzi, A, & Rahimipour, M (2025). Multi-criteria analyses of synergy between data sovereignty and data-driven governance: A comparative framework for designing intelligent organizations, Transcendental Governance, 6(21), 103-141. https://dor.isc.ac/dor/20.1001.1.28212614.1404.6.1.5.4 (In Persian) Ghosh, R (2024). Data-driven governance and performances of accountability: critical reflections from US agri-environmental policy, Science as Culture, 33(1), 70-96. https://doi.org/10.1080/09505431.2023.2175654 Guang, W., Yuan, Y., Huang, S., Zhang, F & Hu, F (2025). Application of Large AI Models in Safety and Emergency Management of the Power Industry in China, Processes, 13(8), 1-13. https://doi.org/10.3390/pr13082569 Han, Q (2025). Data-Driven Smart Governance for National Fitness Public Services, Economics & Management Information, 4(5), 1-6. https://doi.org/10.62836/emi.v4i5.517 Hossin, M., Du, J., Mu, L & Asante, I (2023). Big Data-Driven Public Policy Decisions: Transformation Toward Smart Governance, Sage Journals, 13(4), 1-10. https://doi.org/10.1177/21582440231215123 Karami-Tire Shabankareh, M, Turkfar, A, & Mirhosseini, S. M. A (2021). Presenting a model for developing data-driven governance in Iranian sports, 13(3), 1-22. https://doi.org/10.22059/jsm.2021.325293.2740 (In Persian) Keller, S., Lancaster, V & Shipp, S (2017). Building Capacity for Data-Driven Governance: Creating a New Foundation for Democracy, Statistics and Public Policy, 4(1), 1-11. https://doi.org/10.1080/2330443X.2017.1374897 Lin, X (2025). A Model of Big Data-Based Governance: China’s National Government Big Data Platform and an Analysis of Its Governance Competence, Chinese Political Science Review, 10(5), 25-37. https://doi.org/10.1007/s41111-025-00279-1 Novák, A., Sedlackova, A., Vochozka, M & Popescu, G (2022). Big Data-driven Governance of Smart Sustainable Intelligent Transportation Systems: Autonomous Driving Behaviors, Predictive Modeling Techniques, and Sensing and Computing Technologies, Contemporary Readings in Law and Social Justice, 14(2), 100-117. https://doi.org/10.22381/CRLSJ14220226 O’Rourke, D & Lollo, N (2021). Incentivizing Environmental Improvements in Supply Chains through Data-Driven Governance, California Management Review, 64(1), 27-39. https://doi.org/10.1177/00081256211049827 Qin, T., Wu, K & Xiu, D (2019). Data driven governing equations approximation using deep neural networks, Journal of Computational Physics, 395(7), 620-635. https://doi.org/10.1016/j.jcp.2019.06.042 Shaya, N., Abukhait, R., Madani, R & Khattak, M (2022). Organizational Resilience of Higher Education Institutions: An Empirical Study during Covid‑19 Pandemic, Higher Education Policy. 36(1), 529-555. https://doi.org/10.1057/s41307-022-00272-2 Sprenkamp, K., Zavolokina, L., Angst, M & Dolata, M (2023). Data-Driven Governance in Crises: Topic Modelling for the Identification of Refugee Needs, Proceedings of the 24th Annual International Conference on Digital Government Research, 1-11. https://doi.org/10.1145/3598469.3598470 Zahedi, A.E (2025). Combining knowledge management and artificial intelligence to improve human resource performance (Case study: executive agencies of Markazi province). Strategic Management of Organizational Knowledge, 8(3), 36-61. https://doi.org/10.47176/SMOK.2025.1913 (In Persian) Zhang, J., Li, H & Zhao, H (2025). The Impact of Digital Transformation on Organizational Resilience: The Role of Innovation Capability and Agile Response, Systems, 13(2), 75-91. https://doi.org/10.3390/systems13020075 | ||
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