مدل پرتفولیو اعضای هیأت علمی دانشگاه با رویکرد شبکه‌ های عصبی - فازی

نوع مقاله : مدیریت و سازمان(اخلاق و مسئولیت اجتماعی، رهبری و تحول سازمانی، عملکرد سازمانی، ریسک، مدیریت منابع سازمانی، سطوح تحلیل سازمانی، بلوغ سازمانی، آسیب­‌شناسی سازمانی، نظام اداری، . . . )

نویسندگان

1 کارشناس ارشد مدیریت دولتی، گروه مدیریت بازرگانی، دانشکده علوم اقتصادی و اداری، دانشگاه مازندران، بابلسر، ایران

2 دانشیار، گروه مدیریت بازرگانی، دانشگاه مازندران، بابلسر

3 گروه مهندسی برق، دانشکده فنی ومهندسی، دانشگاه مازندران

چکیده

در این پژوهش تشکیل پرتفولیو اعضای هیأت علمی و ارزیابی آنها از دو بعد عملکرد و پتانسیل با استفاده از ماتریس منابع انسانی صورت گرفته است. در بعد عملکرد؛ متغیرهای آموزش و پژوهش و در بعد پتانسیل؛ متغیرهای توانایی فردی، آرزوهای شغلی و تعامل(درگیری)شغلی در نظر گرفته شده است. عملکرد آموزشی و پژوهشی به ترتیب با همکاری دفتر نظارت و ارزیابی، تضمین کیفیت و معاونت پژوهشی دانشگاه جمع آوری شد، همچنین برای ارزیابی پتانسیل اعضای هیأت علمی از فرم های ارزشیابی معتبر و پرسشنامه های استاندارد استفاده شده است. با توجه به روش نمونه گیری هدفمند، 110 نفر از اعضای هیأت علمی مورد ارزیابی و پایش قرار گرفتند. برای مدل سازی و تحلیل داده ها از نرم افزار متلب(R2018b,v9) و روش شبکه ها‌ی عصبی- فازی استفاده شده است. در نهایت اعضای هیأت علمی با دو سناریوی منطق کلاسیک(باینری یا ارسطویی (0و1)) و منطق فازی به چهار بخش ماتریس که عبارتند از؛ ستارگان، کارکنان هسته ای(کلیدی)، افراد مسئله دار و چوب خشکیده نشانه گذاری شدند. با توجه به خروجی های بدست آمده حدود 30% از افراد مورد مطالعه در بخش ستاره، 21 % به عنوان کارکنان هسته ای ،16% به عنوان افراد مسئله دار و 33% در بخش چوب خشکیده قرار گرفتند. در نهایت با مقایسه دو منطق کلاسیک و فازی، مزیت های بکارگیری این روش تشریح شده است. نتایج بدست آمده حاکی از موفقیت روش پیشنهادی در تحلیل کارکرد اعضای هیأت علمی در دانشگاه مورد نظر بوده و می تواند در تصمیمات کلان آن دانشگاه نقش آفرین باشد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A Portfolio Model of Faculty Members using Adaptive Neuro-Fuzzy Inference System

نویسندگان [English]

  • mehdi khosravi 1
  • Abolhassan Hosseini 2
  • Jamal Ghasemi 3
1 Master of Public Administration, Department of Business Management, Faculty of Economics and Administrative Sciences, Mazandaran University, Babolsar, Iran
2 Associate Professor of Business Management, Department of Business Management, Faculty of Economics, University of Mazandaran, Babolsar, Iran
3 ​Faculty of Engineering & Technology, University of Mazandaran,
چکیده [English]

In this research, the portfolio of faculty members has been formed and their evaluation from two dimensions of performance and potential has been done using the human resources matrix. In terms of performance; Education and research variables and in the dimension of potential; The variables of ability, aspirations and engagement are considered. Educational and research performance were collected in collaboration with the Office of Monitoring and Evaluation, Quality Assurance and the Vice Chancellor for Research, respectively, also valid evaluation forms and standard questionnaires have been used to evaluate the potential of faculty members. According to the purposive sampling method, 110 faculty members were evaluated and monitored. MATLAB software (R2018b, v9) and neural-fuzzy network method have been used for modeling and data analysis. Finally, faculty members with two scenarios of classical logic (binary or Aristotelian (0 and 1)) and fuzzy logic into four parts of the matrix, which are; Stars, core employees, question marks and dead woods were marked. According to the obtained outputs, about 30% of the subjects were in the star section, 21% as core employees, 16% as question marks and 33% in the dead woods section. Finally, by comparing the classical and fuzzy logics, the advantages of using this method are described. The obtained results indicate the success of the proposed method in analyzing the function of faculty members in the university in question and can play a role in the major decisions of that university.

کلیدواژه‌ها [English]

  • faculty members
  • performance
  • potential
  • human resource evaluation
  • fuzzy neural network
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