ارائه مدلی بمنظور پیش‌بینی کارایی شعب بانک تحت شرایط عدم قطعیت مبتنی بر رویکرد SDEA-PCA و شبیه‌سازی مونت‌کارلو

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی پسادکتری، دانشکده علوم اجتماعی، دانشگاه بین المللی امام خمینی (ره)، قزوین، ایران

2 دانشیار، گروه مدیریت صنعتی، دانشکده علوم اجتماعی، دانشگاه بین المللی امام خمینی (ره)، قزوین، ایران

چکیده

امروزه نیاز به استفاده از سیستم‌های اندازه‌گیری کارایی در صنعت بانکداری نوین به طور فزاینده‌ای آشکار شده است. بنابراین لازم است کارایی بانک‌ها پیش‌بینی شود تا بتوان در تصمیم‌گیری های آتی، رشد اقتصادی آنها را رصد کرد. بدین جهت، این مقاله مدل یکپارچه جدیدی جهت پیش‌بینی کارایی شعب در صنعت بانکداری نوین براساس تحلیل پوششی داده‌های تصادفی (SDEA) و روش تحلیل مولفه‌های اصلی (PCA) در فضای پویا با لحاظ بازدهی نسبت به مقیاس متغیر برای شعب طراحی می‌نماید. همچنین به جهت مواجهه با عدم قطعیت در پیش‌بینی کارایی، ورودی‌ها و خروجی‌های شعب در مدل ارائه شده بصورت متغیرهای تصادفی فازی مثلثی با توزیع نرمال طراحی شده‌اند. در این مطالعه برای حل مدل پیشنهادی، از شبیه‌سازی مونت‌کارلو و الگوریتم‌های فراابتکاری استفاده شده است. در نهایت بمنظور ارزیابی عملکرد و دقت مدل یکپارچه پیشنهادی، یک مطالعه موردی مبتنی بر شاخص‌های بانکداری نوین جهت پیش‌بینی کارایی دوره مالی آتی شعب ارائه و نتایج تجزیه و تحلیل شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Proposing a Model to Forecast the Efficiency of Bank Branches under Uncertainty Conditions based on SDEA-PCA Approach and Monte Carlo Simulation

نویسندگان [English]

  • Ali Yaghoubi 1
  • Safar Fazli 2
1 Postdoctoral Research student, Faculty of Social Sciences, Imam Khomeini International University (IKIU), Qazvin, Iran
2 Associate Professor, Department of Industrial Management, Faculty of Social Sciences, Imam Khomeini International University (IKIU), Qazvin,
چکیده [English]

Today, the need to use efficiency measurement systems in the modern banking industry has become increasingly apparent. Therefore, the efficiency of banks needs to be forecasted so that future economic growth can be monitored in future decisions. This paper designs a new integrated model based on the Stochastic Data Envelopment Analysis (SDEA) model and the Principal Component Analysis (PCA) method in a dynamic environment to forecast the efficiency of branches in the modern banking industry by considering variable returns to scale for them. In order to deal with the uncertainty in efficiency forecasting, the inputs and outputs of the branches are designed as triangular fuzzy stochastic variables with normal distribution. In this study, Monte Carlo (MC) simulation and meta-heuristic algorithms have been used to solve the proposed model. Finally, in order to evaluate the performance and accuracy of the proposed integrated model, a case study based on modern banking indicators has been presented to forecast the efficiency of the future financial period of the branches and the results have been analyzed.

کلیدواژه‌ها [English]

  • Efficiency
  • Stochastic Data Envelopment Analysis
  • Principal Component Analysis
  • Fuzzy- Dynamic Programming
  • Monte Carlo Simulation
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