ارائه یک مدل ریاضی برای تحلیل ریسک‌های تعاملی سیستم زنجیره تأمین دارو با استفاده از شبکه‌های باور بیزی

نوع مقاله : پژوهشی اصیل

نویسندگان
1 دانشیار دانشگاه سمنان
2 دانشجوی دکترای مدیریت سیستم ها دانشگاه سمنان
3 استاد دانشگاه تربیت مدرس تهران
4 استادیار دانشگاه سمنان
چکیده
وجود ریسک و نیز ایجاد شکست در زنجیره تامین می­تواند اثر معنی داری بر عملکرد کوتاه مدت و نیز اثر منفی بلند مدت بر عملکرد شرکت کنندگان در زنجیره داشته باشد. لذا این پژوهش با نگاهی نوآورانه به دنبال ارائه یک مدل ریاضی برای تحلیل ریسک­های تعاملی سیستم زنجیره تامین با استفاده از شبکه های باور بیزی است. پژوهش حاضر به لحاظ هدف کاربردی و به لحاظ ماهیت توصیفی است. جامعه خبرگان پژوهش در دو دسته خبرگان آکادمیک و خبرگان صنعت طبقه­بندی شده­اند. در این پژوهش اطلاعات لازم از زنجیره تامین دارویی بیمارستان امام رضا (ع) مشهد بدست آمده و با استفاده از فرایند مدلسازی شبکه های باور بیزی تجزیه و تحلیل شده است. یافته­های این پژوهش نشان می­دهد شبکه­های باور بیزی نسبت به روش­های سنتی تحلیل ریسک بسیار بهتر عمل می­کند چرا که می تواند تحلیل ریسک پایه­ای از جمله رتبه بندی ریسک­ها و تحلیل سناریو و دیگر ملزومات تحلیل ریسک را بخوبی انجام دهد. همچنین BBN می تواند انواع عدم قطعیت­های متفاوت را به زبان احتمالات با شکل بصری مناسب نمایش داده و دید بهتر و جامع­تری نسبت به شرایط زنجیره و ریسک­های آن فراهم آورد
کلیدواژه‌ها

موضوعات


عنوان مقاله English

A Mathematical Model for Analyzing Medicine Supply Chains’ System Interactive Risks Using Bayesian Belief Networks

نویسندگان English

azim allah zareie 1
Mahdi Shakeri 2
Adel Azar 3
morteza maleki 4
1 Associate professor of semnan university
2 Phd student of system management, Semnan university
3 Professor of Tarbiat Modares university of Tehran
4 Assistant professor of Semnan university
چکیده English

Risk and failure in the supply chain can have a significant and negative effect on the short-term and long-term performance of the participants in the chain. Therefore, this research has an innovative look for a mathematical model for analyzing the interactive risks of the supply chain system using Bayesian belief networks. The study is descriptive in terms of purpose and has descriptive nature. The research community is classified into the two categories of academic experts and operational experts. In this research, information on the drug supply chain of the Imam Reza Hospital of Mashhad was obtained and analyzed using the bayesian belief network modeling process. The findings of this study show that Bayesian belief networks are much better than traditional risk analysis methods, because it can analyze basic risk analysis, including risk ranking and scenario analysis, and other essentials. BBN can also display different uncertainties in the language of probabilities with an appropriate visual form and provide more comprehensive view of the supply chain conditions and its risks

کلیدواژه‌ها English

Interactive Risks of Supply Chain System
mathematical modeling
Bayesian Belief Networks
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