شناسایی پیامدهای پنهان‌سازی دانش منابع انسانی : رویکرد ترکیبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه مدیریت، دانشکده مدیریت و علوم مالی، دانشگاه خاتم، تهران، ایران.

2 گروه مدیریت، دانشکده مدیریت و علوم مالی، دانشگاه خاتم، تهران، ایران

3 کارشناس ارشد مدیریت بازرگانی گرایش بازاریابی، دانشکده مدیریت و علوم مالی، دانشگاه خاتم، تهران، ایران.

10.22080/shrm.2024.4831

چکیده

هدف پژوهش حاضر، شناسایی پیامدهای پنهان‌سازی دانش منابع انسانی و توسعه مدل ساختاری و روابط علی بین آن‌ها با رویکرد ترکیبی است. روش‌شناسی پژوهش از نظر فلسفه پژوهش؛ پارادایم عمل‌گرا، و از نظر رویکرد ترکیبی؛ در فاز اول کیفی و در فاز دوم کمی می‌باشد و از نظر استراتژی پژوهش؛ پیمایشی است. جامعه آماری بخش کیفی شامل 34 مقاله از 45 مقاله مربوط به بازه زمانی 2000 تا 2023 و مرتبط با پیامدهای پنهان‌سازی دانش منابع انسانی است. در بخشی کمی پژوهش نیز جامعه آماری شامل 10 نفر از خبرگان حوزه مدیریت دانش بوده است. در فاز اول که فاز کیفی پژوهش است، داده‌هایی از تحلیل محتوای مقالات مرتبط با پنهان‌سازی دانش به‌دست آمد که در آن 16 پیامد پنهان‌سازی دانش شناسایی گردیده است. در مرحله دوم، دلفی فازی به‌منظور انتخاب مهم‌ترین آن‌ها اتخاذ شده است و در نهایت 8 عامل شناسایی گردیده است. در مرحله بعد، مدل ساختاری این عوامل با روش مدل‌سازی ساختاری تفسیری تدوین شده است. سپس با استفاده از تحلیل میک‌مک، عوامل براساس قدرت نفوذ و وابستگی طبقه‌بندی شده‌اند. در پایان، مدل دیمتل فازی به‌منظور تحلیل روابط علی بین عوامل اتخاذ شده است. نتایج نشان داد که عدم توانمندسازی، مهم‌ترین پیامد پنهان‌سازی دانش منابع انسانی است و عدم خلاقیت و نوآوری، کیفیت پایین تصمیم‌گیری، عدم تعهد سازمانی، نارضایتی شغلی، عدم توسعه سازمانی، ضعف عملکرد و تمایل به جابجایی و ترک خدمت، از دیگر پیامدهای پنهان‌سازی دانش منابع انسانی می‌باشند. در پایان، مدل پیشنهادی نویسندگان در زمینه پنهان‌سازی دانش منابع انسانی براساس نتایج ارائه شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Identifying the Consequences of Human Resources Knowledge Hiding with a Mixed Approach

نویسندگان [English]

  • Fatemeh Karimi Jafari 1
  • Maryam Daneshvar 2
  • Fatemeh Saberi 3
1 Assistant Professor, Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran.
2 Management Department, Faculty of management and finance, Khatam University, Tehran, Iran
3 MSc., Department of Management, Faculty of Management and Finance, Khatam University, Tehran, Iran.
چکیده [English]

This research aims to identify the consequences of knowledge hiding and develop a structural model and the causal relationships between them using a mixed method. Research methodology is pragmatic paradigm in terms of research philosophy with integrated approach, the first phase is qualitative and the second phase is quantitative, it is also survey in terms of research strategy. The statistical population of the qualitative section includes 34 articles out of 45 related to the period 2000 to 2023 and related to the consequences of knowledge hiding. In the quantitative part of the research, the statistical population included 10 experts in the field of knowledge management. In the first phase, data was obtained from the content analysis of articles related to knowledge hiding, in which 16 consequences of knowledge hiding were identified. In the second step, fuzzy Delphi was adopted in order to select the most important ones and finally 8 factors were identified. In the next step, the structural model of these factors was developed using the interpretive structural modeling method. By using Micmac analysis, the factors were classified based on driving and dependence power. At the end, the fuzzy DEMATEL method was adopted in order to analyze the causal relationships between the factors. The results showed that lack of empowerment is the most important consequence of knowledge hiding, and lack of creativity and innovation, low quality of decision-making, lack of organizational commitment, job dissatisfaction, lack of organizational development, poor performance and turnover intentions are other consequences of knowledge hiding.

کلیدواژه‌ها [English]

  • Human Resources Knowledge Hiding
  • Consequences
  • Content analysis
  • Interpretive Structural Modeling
  • Fuzzy Delphi and DEMATEL
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