پژوهش‌های مدیریت منابع سازمانی

پژوهش‌های مدیریت منابع سازمانی

ارائه چارچوبی برای طراحی مدل شایستگی مدیران با رویکرد یادگیری ماشین

نوع مقاله : پژوهشی اصیل

نویسندگان
1 دانشجوی دکتری، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.
2 دانشیار، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.
3 دانشیار، گروه رهبری و سرمایه انسانی، دانشکده مدیریت دولتی و علوم سازمانی، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.
4 استاد، گروه مدیریت فناوری اطلاعات، دانشکده مدیریت صنعتی و فناوری، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران.
چکیده
در چشم‌انداز در حال تحول مدیریت منابع انسانی، مدل‌ شایستگی به‌عنوان ابزاری کلیدی برای هم‌راستاکردن توسعه منابع انسانی با اهداف راهبردی سازمان به‌ویژه در نقش‌های مدیریتی عمل می‌کند. هر چند مدل‌های شایستگی مدیریت از سال 1990 گسترش پیدا کرده‌اند، اما رویکردهای مرسوم در طراحی مدل‌های شایستگی و ارزیابی مبتنی بر این مدل‌ها، با چالش‌هایی از نقطه نظر چیستی شایستگی، ارتباط شایستگی‌ها با عملکرد برتر و روش ایجاد مدل که اغلب مبتنی بر قضاوت خبرگان و ارزیابی‌های کیفی و در نتیجه تجربیات و داوری‌های ذهنی است، مواجه بوده‌اند. در راستای پاسخ به این چالش‌ها، پژوهش حاضر چارچوبی مبتنی بر داده‌کاوی برای طراحی مدل شایستگی برای مدیران ارائه می‌دهد. این چارچوب بر‌پایه تحلیل محتوای کیفی قیاسی بر ۲۵ مقاله منتخب که از راه مرور نظام‌مند ادبیات شناسایی شدند و بر‌مبنای فرایند استاندارد برای داده‌کاوی CRISP-DM توسعه یافته است. بر‌این‌اساس از 25 پژوهش که از روش‌های داده‌کاوی در مراحل مختلف طراحی مدل شایستگی برای مدیران استفاده کرده‌اند، الگوهای مشترک استخراج و تلفیق شده‌اند. در‌نتیجه تحلیل محتوای کیفی 16 مقوله به‌دست‌آمده که 12 مقوله از‌جمله خوشه‌بندی شایستگی‌ها، خوشه‌بندی افراد بر‌اساس عملکرد، تفسیر خوشه‌های عملکرد و شناسایی خوشه عملکرد برتر، الگوریتم‌های دسته‌بندی برای ایجاد رابطه میان شایستگی و عملکرد، تفسیر مدل و مشخص‌ کردن محدوده شایستگی‌ها در قالب چارچوب طراحی مدل شایستگی ارائه شده است و 4 مقوله نیز به تکمیل چارچوب و استفاده از آن کمک می‌کند. بر‌این‌اساس، این چارچوب امکان طراحی مدل‌های عینی‌تر و مبتنی بر داده را فراهم می‌سازد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Providing a framework for designing a manager competency model with a machine learning approach

نویسندگان English

Fatemeh Mozaffari 1
Saeed Rouhani 2
Hamid Reza Yazdani 3
Marjan Fayyazi 3
babak sohrabi 4
1 PhD Candidate, Group of Information Technology Management, Faculty of Technology and Industrial Management, College of Management, University of Tehran, Tehran, Iran.
2 Associate Professor, Group of Information Technology Management, Faculty of Technology and Industrial Management, College of Management, University of Tehran, Tehran, Iran.
3 Associate Professor, Group of Leadership and Human Capital, Faculty of Public Administration and Organization Science, College of Management, University of Tehran, Tehran, Iran.
4 Professor, Group of Information Technology Management, Faculty of Technology and Industrial Management, College of Management, University of Tehran, Tehran, Iran.
چکیده English

In the evolving landscape of human resource management, competency models serve as a crucial tool for aligning human resource development with an organization's strategic goals, particularly in managerial roles. Although management competency models have been developed since 1990, conventional approaches to designing competency models and assessments based on these models have faced challenges in terms of what constitutes competency, the relationship between competencies and superior performance, and the method of model development, which is often based on expert judgment and qualitative assessments, and therefore are subjective experiences and judgments. To address these challenges, this study proposes a data mining-based framework for developing competency models for managers.
This framework has been developed through deductive qualitative content analysis of 25 studies identified through a systematic literature review, based on the standard process for data mining, CRISP-DM. 25 studies that employed data mining techniques at various stages of competency model design for managers used to identify and integrate common patterns. As a result of qualitative content analysis, 16 categories were obtained, of which 12 categories, including competency clustering, clustering individuals based on performance, interpretation of performance clusters and identification of superior performance cluster, classification algorithms for establishing a relationship between competency and performance, interpretation of the model, and specifying the rules related to competencies, are presented in the form of a framework for designing competency model, and 4 categories also help to complete the framework and use it. Accordingly, this framework enables the design of more objective and data-driven models.

کلیدواژه‌ها English

Competency
Competency Model for Managers
Machine Learning
Talent Management
Superior Performance
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