ارائۀ یک مدل برای ارزیابی عملکرد زنجیرۀ تأمین پایدار با استفاده از تحلیل پوششی داده های شبکه ای و شبیه سازی بوت استرپ

محورهای موضوعی : مدیریت بازرگانی- بازرگانی

مسعود واسعی ¹ (دانشجوی دکتری گروه مهندسی صنایع، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران)
مریم دانشمندمهر ² (استادیار گروه مهندسی صنایع، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران(نویسندۀ مسئول))
مرتضی بذرافشان ³ (استادیار گروه مهندسی صنایع، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران)
آرمین قانع کنفی ⁴ (استادیار گروه ریاضی، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران)

تاریخ دریافت : 1401/11/10 تاریخ پذیرش : 1402/02/25 تاریخ انتشار : 1402/03/01

کلید واژه: شبکه, تحلیل پوششی داده­ ها, بوت ­استرپ,

چکیده مقاله :

زمینۀ تحلیل پوششی داده‌ها در حوزۀ علوم داده و تجزیه وتحلیل آن ها قرار می‌گیرد. هدف اصلی این تحلیل، بررسی و تحلیل جوانب مختلف و متنوع داده‌ها در یک مجموعه داده است. تحلیل پوششی برای شناخت بهتر داده‌ها، شفافیت بیشتر و فهم عمیق‌تر از الگوها، روابط و خصوصیات داده‌ها به کار می‌رود. هدف اصلی تحلیل پوششی داده‌ها، کشف اطلاعات پنهان و ناشناخته در داده‌ها و استخراج دانش از آن ها است. با استفاده از روش‌های تحلیل پوششی، می‌توان مشاهده و شناخت الگوها، روابط، اختلاف‌ها و تغییرات در داده‌ها را انجام داد و به ارائۀ دیدگاه‌های جدید و بالقوۀ مفید در مورد داده‌ها و فرآیندهای مربوط به آن ها پرداخت. از این رو، در این مقاله با استفاده از فرآیند شبیه سازی بوت استرپ برای بالا بردن دقت کارایی برآورده شده استفاده شده است. برای این منظور امتیاز کارایی کلی و مرحله ای به طور جداگانه برای هر یک از واحدها از طریق مقادیر شبیه سازی شده برای ورودی ها و خروجی ها تعیین می شوند؛ لذا، مهم‌ترین نوآوری این تحقیق ارائۀ چارچوبی برای تعیین امتیاز کارایی واحدهایی که به طور شبکه ای در ارتباط هستند با استفاده از تحلیل پوششی داده های بوت استرپ شده است. برای نشان دادن روش پیشنهادی، یک مورد مطالعاتی واقعی در شبکۀ زنجیرۀ تأمین رب گوجه فرنگی در نظر گرفته شده است. بر طبق نتایج، دقت روش بکار گرفته شده نشان داده شده است.

چکیده انگلیسی:

The field of data envelopment analysis in the realm of data science and analytics focuses on examining and analyzing various aspects of data within a dataset. The main objective of this analysis is to investigate and analyze different and diverse dimensions of the data. Data envelopment analysis is employed to gain a better understanding of the data, enhance transparency, and achieve a deeper comprehension of patterns, relationships, and characteristics within the data. The primary goal of data envelopment analysis is to discover hidden and unknown information within the data and extract knowledge from it. By utilizing data envelopment analysis methods, one can observe and comprehend patterns, relationships, differences, and variations in the data, leading to the provision of new and potentially valuable insights regarding the data and its associated processes. Therefore, in this article, the bootstrap simulation process has been utilized to improve the accuracy of achieved performance. The main objective of this article is to present a framework for measuring the performance of evaluated units under the bootstrap scenario. To accomplish this, overall and stage-wise performance scores are separately determined for each unit through simulated values for inputs and outputs. Thus, the most significant innovation of this research is the presentation of a framework for determining the performance scores of interconnected units using bootstrap-data envelopment analysis. To demonstrate the proposed method, a real case study in the tomato supply chain network has been considered. According to the results, the accuracy of the employed method has been demonstrated.

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