طراحی مدل ترکیبی DEA–ANN برای پیش‌بینی و بهینه‌سازی مدیریت ریسک در زنجیره تأمین دیجیتال صنعت فولاد

نویسندگان

    نادیا شاه محمدی گروه مدیریت صنعتی، واحد تهران مرکزی، دانشگاه آزاد اسلامي، تهران، ايران
    حسین معین زاد * گروه مدیریت صنعتی، واحد تهران مرکزی، دانشگاه آزاد اسلامي، تهران، ايران moinzad@iauctb.ac.ir
    صفیه مهری نژاد گروه مدیریت مالی ، واحد تهران مرکزی، دانشگاه آزاد اسلامي، تهران، ايران
    محمدعلی کرامتی گروه مدیریت صنعتی، واحد تهران مرکزی، دانشگاه آزاد اسلامي، تهران، ايران

کلمات کلیدی:

تحول دیجیتال, زنجیره تامین دیجیتال, مدیریت ریسک, شبکه عصبی مصنوعی

چکیده

هدف این پژوهش طراحی و اعتبارسنجی یک مدل هوشمند ترکیبی مبتنی بر تحلیل پوششی داده‌ها و شبکه عصبی مصنوعی به‌منظور پیش‌بینی و بهینه‌سازی ریسک در زنجیره تأمین دیجیتال صنعت فولاد است.  پژوهش از نوع کاربردی و با رویکرد آمیخته انجام شد؛ بدین‌صورت که ابتدا با مرور نظام‌مند ادبیات و مصاحبه با خبرگان، 160 ریسک شناسایی گردید و سپس با استفاده از پرسشنامه، شاخص‌های احتمال وقوع، شدت اثر و قابلیت کشف کمی‌سازی شدند. عدد اولویت ریسک محاسبه و به‌منظور بهینه‌سازی و استخراج کارایی متقاطع، مدل DEA به‌کار گرفته شد. در نهایت، خروجی DEA به‌عنوان داده آموزشی برای مدل شبکه عصبی مصنوعی استفاده شد. نتایج نشان داد مدل DEA–ANN با ساختار دو لایه پنهان و تنظیمات بهینه، قدرت تبیین بالایی داشته و قادر است تغییرات سطح ریسک و کارایی متقاطع را با دقت مناسب پیش‌بینی کند؛ به‌گونه‌ای که شاخص‌های خطا کاهش معنادار و ضریب تعیین در سطح مطلوبی قرار گرفت. مدل پیشنهادی ابزاری کارآمد برای پیش‌بینی ریسک و پشتیبانی از تصمیم‌گیری هوشمند در زنجیره تأمین دیجیتال فولاد فراهم می‌کند و می‌تواند جایگزینی مؤثر برای روش‌های سنتی ارزیابی ریسک باشد.

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شاه محمدی ن. .، معین زاد ح.، مهری نژاد ص.، و کرامتی م. (1405). طراحی مدل ترکیبی DEA–ANN برای پیش‌بینی و بهینه‌سازی مدیریت ریسک در زنجیره تأمین دیجیتال صنعت فولاد. یادگیری هوشمند و تحول مدیریت، 1-25. https://jilmt.com/index.php/jilmt/article/view/113

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