نوع مقاله : مقاله پژوهشی - کاربردی

نویسندگان

گروه مهندسی صنایع، واحد علوم و تحقیقات دانشگاه آزاداسلامی، تهران، ایران.

چکیده

هدف: استراتژی اصلی‌ترین منبع رشد بلندمدت سازمان‌ها می‌باشد و در صورت عدم اجرای موفق استراتژی، حتی اگر استراتژی‌های مناسبی اتخاذشده باشد این فرآیند بیهوده است. هدف این مقاله پیشنهاد یک مدل جامع ترکیبی را برای پیش‌بینی شاخص‏های عملکردی سازمانی است.
روش‌شناسی پژوهش: به منظور رسیدن به هدف پژوهش، ابتدا از کارت امتیازی متوازن به‌عنوان ابزاری برای طراحی شاخص‌های ارزیابی عملکرد و از تحلیل پوششی داده‌های شبکه‌ای به‌عنوان ابزاری برای ارزیابی عملکرد استفاده شده است. سپس با استفاده از تطبیق شاخص بهره‌وری مالمکوئیست با مدل ترکیبی مذکور، به ارائه مدل پیشرفت و پسرفت سازمان‌ها طی دو دوره متوالی پرداخته می‌شود. سرانجام با ترکیب مدل‏های پیشنهادی و شبکه‏های عصبی مصنوعی راهکاری را برای ارزیابی عملکرد 500 شعبه بانک و نیز تشخیص پیشرفت و پسرفت آن‌ها ارائه می‏گردد.
یافته‌ها: نتایج به‌دست‌آمده نشان‌دهنده دقت مناسب و زمان محاسباتی کمتر مدل‏های ترکیبی پیشنهادی است.




اصالت/دانش‌افزایی علمی: پژوهش حاضر با ارائه یک مدل ترکیبی با استفاده از تحلیل پوششی داده‌های شبکه‌ای و کارت امتیازی متوازن می‌تواند به دانش موجود در خصوص ارزیابی عملکرد بنگاه‌های اقتصادی بیافزاید و روش‌های پیشنهادی می‌توانند ابزارهای نوید‌بخشی برای ارزیابی عملکرد سازمان‌ها، به‌خصوص داده‏های بزرگ باشند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

A comprehensive hybrid Ndea- Bsc model and a new neural network for predicting organizational performance indicators

نویسندگان [English]

  • Seyyed Esmaeil Najafi
  • Mohammad Jaberi
  • Farhad Hoseinzadeh Lotfi
  • Mohammad Haji molana

Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.

چکیده [English]

Purpose: Strategy is the main source of long-term growth of organizations and if the strategy is not successfully implemented, even if the appropriate strategies are adopted, this process is useless. The purpose of this paper is to propose a comprehensive hybrid model for predicting organizational performance indicators.
Methodology: In order to achieve the research goal, first, a balanced scorecard as a tool for designing performance evaluation indicators and network data envelopment analysis as a tool for performance evaluation has been used. Then, by matching the Malmquist productivity index with the mentioned hybrid model, the model of progress and regression of organizations in two consecutive periods is presented. Finally, by combining the proposed models and artificial neural networks, a solution is presented to evaluate the performance of 500 bank branches and also to identify their progress and regression.
Finding: The obtained results show good accuracy and less computational time of the proposed hybrid models.</p
Originality/Value: The present study can add to the existing knowledge on performance appraisal of enterprises by providing a hybrid model using network data envelopment analysis and balanced scorecard; And the proposed methods can be promising tools for evaluating the performance of organizations, especially big data.

کلیدواژه‌ها [English]

  • "network data envelopment analysis (NDEA)"
  • " balanced score cards (BSC)"
  • "strategy goals"
  • "Malmquist productivity index
  • artificial neural system"
  • "multilayered perceptron
  • efficiency"
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