استكشاف دور أنظمة دعم القرار (DSS) في تعزيز عمليات اتخاذ القرار عبر وظائف الأعمال المختلفة (التمويل والتسويق وإدارة سلسلة التوريد)

محتوى المقالة الرئيسي

م.م. الحسن علي عبد الكريم

الملخص

تبحث الورقة في نظم دعم القرار (DSS) ) من منظورين نظري وتطبيقي، وتبيّن كيف أن النظم الحديثة وخاصة المعزّزة بالذكاء الاصطناعي وتعلّم الآلة تحسّن بشكل كبير جودة اتخاذ القرار والأداء التشغيلي. وتُظهر دراسات الحالة في شركات كبرى وثلاثة قطاعات رئيسية (التجزئة، الرعاية الصحية، والتصنيع) تحقيق مكاسب في الكفاءة والدقة وتقليل التكاليف. وتخلص الدراسة إلى أن نظم دعم القرار أدوات قوية تعزز القرارات الاستراتيجية والقدرة التنافسية للمنظمات، رغم وجود تحديات تتعلق بجودة البيانات وتبنّي المستخدمين لهذه الأنظمة

تفاصيل المقالة

كيفية الاقتباس
م.م. الحسن علي عبد الكريم م. ا. ع. ع. ا. (2025). استكشاف دور أنظمة دعم القرار (DSS) في تعزيز عمليات اتخاذ القرار عبر وظائف الأعمال المختلفة (التمويل والتسويق وإدارة سلسلة التوريد). مجلة الاقتصادي الخليجي, 41(66), 252–221. استرجع في من https://tge.uobasrah.edu.iq/index.php/tge/article/view/205
القسم
بحوث ومقالات علمية
السيرة الشخصية للمؤلف

م.م. الحسن علي عبد الكريم ، جامعة البصرة / كلية الادارة والاقتصاد

م.م. الحسن علي عبد الكريم

جامعة البصرة / كلية الادارة والاقتصاد

المراجع

Albahri, A. S., Khaleel, Y. L., Habeeb, M. A., Ismael, R. D., Hameed, Q. A., Deveci, M., Homod, R. Z., Albahri, O. S., Alamoodi, A. H., & Alzubaidi, L. (2024). A systematic review of trustworthy artificial intelligence applications in natural disasters. Computers and Electrical Engineering, 118, 109409. https://doi.org/10.1016/j.compeleceng.2024.109409

Alzoubi, S., Amayreh, K. T., Farea, M. M., Baker El-Ebiary, Y. A., Ahmad Saany, S. I., & Bisht, N. (2023). A Review of Effectiveness and Efficiency Methodology of Decision Support System for Selecting Suppliers. 2023 International Conference on Computer Science and Emerging Technologies (CSET), 1–7. https://doi.org/10.1109/CSET58993.2023.10346850

Berkhout, M., Smit, K., & Versendaal, J. (2024). Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process. BMC Medical Informatics and Decision Making, 24(1), 100. https://doi.org/10.1186/s12911-024-02486-3

Berman, A., de Fine Licht, K., & Carlsson, V. (2024). Trustworthy AI in the public sector: An empirical analysis of a Swedish labor market decision-support system. Technology in Society, 76, 102471. https://doi.org/10.1016/j.techsoc.2024.102471

Chen, X., & Geyer, P. (2022). Machine assistance in energy-efficient building design: A predictive framework toward dynamic interaction with human decision-making under uncertainty. Applied Energy, 307, 118240. https://doi.org/10.1016/j.apenergy.2021.118240

Chukuigwe, D. N. (2022). Decision Support Tool and Human Resource Practices in Deposit Money Banks in Rivers State. British Journal of Accounting, Management and Information, 9, 8. https://doi.org/www.bwjournal.org

Crisan, A., Juravle, A., & Bancila, R. (2024). A BIM Enabled Workflow for Rehabilitation of Heritage Steel Bridges. https://doi.org/10.20944/preprints202412.1120.v1

Fuentes-Peñailillo, F., Gutter, K., Vega, R., & Silva, G. C. (2024). Transformative Technologies in Digital Agriculture: Leveraging Internet of Things, Remote Sensing, and Artificial Intelligence for Smart Crop Management. Journal of Sensor and Actuator Networks, 13(4). https://doi.org/10.3390/jsan13040039

Giannakopoulos, N. T., Terzi, M. C., Sakas, D. P., Kanellos, N., Toudas, K. S., & Migkos, S. P. (2024). Agroeconomic Indexes and Big Data: Digital Marketing Analytics Implications for Enhanced Decision Making with Artificial Intelligence-Based Modeling. Information, 15(2), 67. https://doi.org/10.3390/info15020067

Gil, Y., Garijo, D., Khider, D., Knoblock, C. A., Ratnakar, V., Osorio, M., Vargas, H., Pham, M., Pujara, J., Shbita, B., Vu, B., Chiang, Y.-Y., Feldman, D., Lin, Y., Song, H., Kumar, V., Khandelwal, A., Steinbach, M., Tayal, K., … Shu, L. (2021). Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making. ACM Trans. Interact. Intell. Syst., 11(2), 11:1–11:49. https://doi.org/10.1145/3453172

Hamrouni, B., Bourouis, A., Korichi, A., & Brahmi, M. (2021). Explainable Ontology-Based Intelligent Decision Support System for Business Model Design and Sustainability. Sustainability, 13(17), 9819. https://doi.org/10.3390/su13179819

Hossain, M. A., Tiwari, A., Saha, S., Ghimire, A., Imran, M. A. U., & Khatoon, R. (2024). Applying the Technology Acceptance Model (TAM) in Information Technology System to Evaluate the Adoption of Decision Support System. Journal of Computer and Communications, 12(8). https://doi.org/10.4236/jcc.2024.128015

Maaitah, T. (2023). The Role of Business Intelligence Tools in the Decision Making Process and Performance. Journal of Intelligence Studies in Business, 13(1). https://doi.org/10.37380/jisib.v13i1.990

Pillai, A. S. (2023). AI-enabled Hospital Management Systems for Modern Healthcare: An Analysis of System Components and Interdependencies. Journal of Advanced Analytics in Healthcare Management, 7(1).

Psarommatis, F., & Kiritsis, D. (2022). A hybrid Decision Support System for automating decision making in the event of defects in the era of Zero Defect Manufacturing. Journal of Industrial Information Integration, 26, 100263. https://doi.org/10.1016/j.jii.2021.100263

Qiu, K., Chen, J., Ashraf, S., & Shahid, T. (2024). Strategic Decision Support System with Probabilistic Linguistic Term Sets: Extended CRADIS Approach for Supply Chain Risk Management in Sports Industry. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3416391

Ruiz, M., Orta, E., & Sánchez, J. (2024). A simulation-based approach for decision-support in healthcare processes. Simulation Modelling Practice and Theory, 136, 102983. https://doi.org/10.1016/j.simpat.2024.102983

Sadeghi, R. K., Ojha, D., Kaur, P., Mahto, R. V., & Dhir, A. (2024). Explainable artificial intelligence and agile decision-making in supply chain cyber resilience. Decision Support Systems, 180, 114194. https://doi.org/10.1016/j.dss.2024.114194

Sarker, I. H. (2021). Data Science and Analytics: An Overview from Data-Driven Smart Computing, Decision-Making and Applications Perspective. SN Computer Science, 2(5), 377. https://doi.org/10.1007/s42979-021-00765-8

Shahcheraghian, A., Ilinca, A., & Sommerfeldt, N. (2025). K-means and agglomerative clustering for source-load mapping in distributed district heating planning. Energy Conversion and Management: X, 25, 100860. https://doi.org/10.1016/j.ecmx.2024.100860

Shim, J. P., Warkentin, M., Courtney, J. F., Power, D. J., Sharda, R., & Carlsson, C. (2002). Past, present, and future of decision support technology. Decision Support Systems, 33(2), 111–126. https://doi.org/10.1016/S0167-9236(01)00139-7

Spoladore, D., Tosi, M., & Lorenzini, E. C. (2024). Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review. Artificial Intelligence in Medicine, 151, 102859. https://doi.org/10.1016/j.artmed.2024.102859