اندازه گیری کارایی هزینه در تحلیل پوششی داده‌های شبکه‌ای
محورهای موضوعی : آمارشهروز فتحی اجیرلو 1 , علیرضا امیرتیموری 2 , سهراب کرد رستمی 3
1 - گروه ریاضی، پردیس علوم و تحقیقات گیلان، دانشگاه آزاد اسلامی، رشت، ایران. گروه ریاضی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران
2 - گروه ریاضی، واحد رشت، دانشگاه آزاد اسلامی، رشت، ایران
3 - گروه ریاضی، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران
کلید واژه: Network System, Data Envelopment Analysis, cost efficiency,
چکیده مقاله :
تحلیل پوششی داده ها یک رویکرد نسبتاً جدید با ماهیت داده ای برای ارزیابی عملکرد مجموعه ای از موجودیت های همتا به نام واحدهای تصمیم گیری (DMUها) است که چندین ورودی را به چندین خروجی تبدیل می کنند. DEA در دوره زمانی نسبتاً محدودی تبدیل به ابزار کمّی و تحلیلی قدرتمندی برای اندازه‌گیری و ارزیابی عملکرد شده است. DEA در انواع مختلفی از کاربردها در فعالیت ها و محیط های مختلف در سرتاسر دنیا با موفقیت به کار گرفته شده است. همچنین مسأله ی اندازه گیری کارایی هزینه در سیستم های تولیدی و اقتصادی یکی از مسائل مهم روز دنیا می باشد. در دنیای واقعی سیستم های اقتصادی و تولیدی وجود دارند که از ترکیب واحدهای مستقل تشکیل شده اند و یکی از روش های اندازه گیری کارایی هزینه برای سیستم های اقتصادی و تولیدی روش DEA می باشد. این مقاله دو مدل DEA شبکه ای را برای اندازه گیری کارایی هزینه از مدل شبکه ای با مولفه های پردازش یکسان با در نظر گرفتن عملکردهای پردازش های فردی در ساختار شبکه را ارائه می کند. در این مقاله به بررسی مدل کارایی هزینه فار و همکاران پرداخته شده و با اعمال تغییراتی در مدل فار و همکاران به ارائه دو مدل جدید تحلیل پوششی داده های شبکه ای و توسعه یافته برای اندازه‌گیری کارایی هزینه در سیستم‌های شبکه‌ای اقتصادی و تولیدی پرداخته شده است.
Data Envelopment Analysis (DEA) is a relatively new data oriented approach for evaluating the performance of a set of peer entities called Decision-Making Units (DMUs) which convert multiple inputs into multiple outputs. In a relatively short period of time DEA has grown into a powerful quantitative, analytical tool for measuring and evaluating performance. DEA has been successfully applied to a host of different types of entities engaged in a wide variety of activities in many contexts worldwide. The issue of measuring the cost efficiency in manufacturing and economic systems is one of the most important issues in the world. In the real world, there are manufacturing and economic systems that are composed of independent units. One of the ways to measure the cost efficiency for economic and production systems is the DEA technique. This paper presents two network DEA models to measure the cost efficiency of a network model with identical processing components taking into account the individual processing functions in the network structure. In this paper, we examine the cost efficieny model of Färe et al., and through modifying the model of Färe et al., a model has been developed to measure the cost efficiency in economic and manufacturing networks.
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