ارزیابی ظهور و بروز ویژگی‌های سازمان نوروتیک در سازمان‌ها: مطالعه‌ای در آموزش‌وپرورش با رویکرد نگاشت‌شناختی فازی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشیار، گروه مدیریت، دانشکده اقتصاد، مدیریت و علوم اجتماعی دانشگاه شیراز، شیراز، ایران

2 کارشناس ارشد، گروه مدیریت بازرگانی، دانشکده اقتصاد، مدیریت و علوم اجتماعی، دانشگاه شیراز، شیراز، ایران.

3 استادیار، گروه مدیریت صنعتی، دانشکده مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران.

4 کارشناس ارشد، گروه مدیریت بازرگانی، دانشکده اقتصاد و علوم اجتماعی، دانشگاه شهید چمران اهواز، اهواز، ایران.

چکیده

هدف: هدف از این پژوهش، ارزیابی ظهور و بروز ویژگی‌های سازمان نوروتیک در آموزش‌وپرورش با روش نگاشت‎شناختی فازی است.
روش: برای شناسایی ویژگی‌های رفتار نوروتیک در سازمان مورد مطالعه، از روش نگاشت‌شناختی فازی استفاده ‌شده است. در نخستین گام بعد از مشخص شدن مسئله پژوهش، ابتدا خبرگانی انتخاب شدند که در رابطه با سازمان آموزش‌وپرورش از دانش و آگاهی لازم برخوردار بودند.  بعد از مشخص شدن خبرگان پژوهش، پژوهشگر به استخراج نقشه ذهنی خبرگان اقدام کرده است. به این صورت که با انجام جلسات گروهی فکری از خبرگان خواسته شد تا ویژگی‌های مد نظر را با توجه به بعد مشخص‌شده روی فلیپ چارت نوشته و مکتوب کنند. بعد از رسیدن به اشباع نظری، تسهیلگر گروه، پاسخ‌ها را بر اساس بعد‌های مشخص‌شده، دسته‌بندی کرد، سپس روابط علی بین عناصر هر بعد و روابط با عناصر سایر بعد‌ها بررسی و ترسیم ‌شده است.
یافته‌ها: نگاشت‌شناختی علی رفتارهای نوروتیک در سازمان آموزش‌وپرورش شامل 122 عنصر‌ است. تحلیل نگاشت به‌کمک FCMaper نشان داده که این عناصر شامل 45 عنصر معمولی، 75 عنصر فرستنده و 2 عنصر دریافت‌کننده‌ هستند.
نتیجه‌گیری: نتایج حاصل از نگاشت نشان داده است که عنصر عدم عزت‌نفس، با داشتن بیشترین درجه ورودی، اثرپذیری‌ترین عنصر نگاشت و عنصر رسانه‌ای کردن با داشتن بیشترین درجه خروجی، اثرگذارترین عنصر نگاشت رفتار نوروتیک در سازمان آموزش‌وپرورش هستند. مرکزیت، شاخص دیگری است که نشان‌دهنده شدت اثرگذاری عناصر در رفتار نوروتیک است، تحلیل‌ها نشان می‌دهند که عنصر عدم عزت‌ نفس با داشتن بیشترین مجموع درجه ورودی و خروجی مرکزی‌ترین عنصر نگاشت شناخته ‌شده است. همچنین نتایج حاصل از آزمون اسپیرمن و بررسی سناریوی‌های حدی نشان‎دهنده صحت نتایج به‌دست‌آمده هستند.

کلیدواژه‌ها

عنوان مقاله [English]

Evaluating the Emergence and Incidence of Neurotic Organization Characteristics in Organizations: A Study in Education with Fuzzy Cognitive Mapping Approach

نویسندگان [English]

  • Habib Allah Ranaei Kordshouli 1
  • Amin Nikbakht 2
  • Khadije Mostafaee Dolatabad 3
  • Hatam Khalilipour 4
1 Associate Prof., Department of Management, Faculty of Economic, Management and Social Sciences, Shiraz University, Shiraz, Iran
2 MSc., Department of Business Management, Faculty of Economic, Management and Social Science, Shiraz University, Shiraz, Iran.
3 Assistant Prof., Department of Industrial Management, Faculty of Management and Economics, Tarbiat Modarres University, Tehran, Iran.
4 MSc., Department of Business Management, Faculty of Economic and Social Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
چکیده [English]

Objective:The purpose of this study was to evaluate the Emergence and incidence of neurotic organization characteristics in education by fuzzy cognitive mapping.
Methods: Fuzzy cognitive mapping is used to identify the characteristics of neurotic behavior in the organization under study. In the first step after identifying the research problem, the experts with the necessary knowledge and knowledge were selected by the education organization. After identifying the research experts, the researcher has extracted the mental map of the experts by asking the experts for brainstorming. Write and write the flip charts according to the specified dimension, and after reaching the theoretical saturation, the facilitator has grouped the responses according to the specified dimensions, and then causal relations between the elements of each dimension and relationships with other elements. It is later examined and plotted.
Results: Cognitive mapping of neurotic behaviors in an education organization contains 122 elements. FCMaper mapping analysis has shown that these elements consist of 45 ordinary elements, 75 transmitter elements and 2 receiving elements.
Conclusion: The results of mapping showed that self-esteem element with the highest input degree is the most effective mapping element and media with the highest output degree is the most effective element of neurotic behavior mapping in the educational organization. Centrality is another indicator that shows the effect of the elements on the neurotic behavior. Analyzes show that the element of self-esteem is the most central mapping element identified with the highest degree of input and output. Also, the results of the Spearman test and limit scenarios show the validity of the results.

کلیدواژه‌ها [English]

  • Neurotic behavior
  • Dramatic
  • Obsessive
  • Depressive
  • Schizoid
  • Pessimistic
  • Fuzzy cognitive mapping

مراجع

باقرزاده، رویا (1391). ویژگی‌های سازمان‌های نوروتیک و رابطه‌ آن با ابعاد عدالت و تعهد سازمانی در شهرداری شیراز. پایان‎نامه کارشناسی ارشد، دانشکده علوم تربیتی و روان‎شناسی، دانشگاه آزاد اسلامی واحد مرودشت.
سوادکوهی، علیرضا؛ کامکار، منوچهر و سماواتیان، حسین (1390). رابطه ابعاد نوروتیک سازمان از دیدگاه کارکنان با سلامت روانی آنها.فصلنامه روان شناختی تحلیلی شناختی، 2(6)، 53-63.
شکروی، شیرین؛ حسینیان، سیمین؛ سماواتیان، حسین؛ صمصام شریعت، سید محمد رضا (1389). بررسی رابطه بین سازمان‎های بیمار (نوروتیک) با سبک رهبری و جو سازمانی.‎ اندیشه‌های نوین تربیتی، 6(3)، 95- 114.
کامکار، منوچهر؛آتشپور، سیدحمید (1386).روان‎شناسیسازمان‌هایبیمار(نوروتیک).اصفهان:نشرمحبان.
مصطفائی دولت آباد، خدیجه؛ آذر، عادل؛ مقبل باعرض، عباس (1397). شناساییوتحلیلریسک‌های عملیاتیبااستفادهازنگاشت‌شناختیفازی، مدیریت دارایی و تأمین مالی، 4(23)، 1- 18.
منافی شرف‎آباد، کاظم؛ زمانی، الهام (1391). نقش نظام آموزش‌وپرورش در توسعه فرهنگی جامعه. فصلنامه مهندسی فرهنگی، 73، 134-152.
یاسینی، علی؛ شیری، اردشیر؛ مرادی کیا، فریبا (1397). مطالعه مقایسه‌ای نقش جنبه‌های منفی رفتار سازمانی در بروز رفتارهای ناکارآمد شغلی کارکنان. مطالعات مدیریت (بهبود و تحول)، 27(90)، 65-88.
References
Aguilar, J. (2001, June). A fuzzy cognitive map based on the random neural model. In International conference on industrial, Engineering and other applications of applied intelligent systems (pp. 333-338). Springer, Berlin, Heidelberg.
Ahmadi, S., Yeh, C. H., Martin, R., & Papageorgiou, E. (2015). Optimizing ERP readiness improvements under budgetary constraints. International Journal of Production Economics, 161, 105-115.
Al-Hila, A. A., Alshaerb, I. M. A., Al Shobaki, M. J., & Abu Naser, S. S. (2017). The Impact of the Governance of Private Universities in Building Partnership with NGOs Operating in Gaza Strip. International Journal of Engineering and Information Systems, 1(9), 11-30.
Alipour, M., Hafezi, R., Amer, M., & Akhavan, A. N. (2017). A new hybrid fuzzy cognitive map-based scenario planning approach for Iran's oil production pathways in the post–sanction period. Energy, 135, 851-864.
Amer, M., Jetter, A. J., & Daim, T. U. (2013, July). Scenario planning for the national wind energy sector through Fuzzy Cognitive Maps. In 2013 Proceedings of PICMET'13: Technology Management in the IT-Driven Services (PICMET) (pp. 2153-2162). IEEE.
Auten, D., & Fritz, C. (2019). Mental health at work: How mindfulness aids in more ways than one. Organizational Dynamics, 48(3), 98-104.
Azar, A., & Dolatabad, K. M. (2019). A method for modelling operational risk with fuzzy cognitive maps and Bayesian belief networks. Expert Systems with Applications, 115, 607-617.
Bağdatlı, M. E. C., Akbıyıklı, R., & Papageorgiou, E. I. (2017). A fuzzy cognitive map approach applied in cost–benefit analysis for highway projects. International Journal of Fuzzy Systems, 19(5), 1512-1527.
Bagherzadeh, R. (2012). Characteristics of Neurotic Organizations and Their Relationship with the Dimensions of Organizational Justice and Organizational Commitment in Shiraz Municipality. M.Sc., Faculty of Educational Sciences and Psychology, Islamic Azad University, Marvdasht Branch. (in Persian)
Bakhtavar, E., & Shirvand, Y. (2019). Designing a fuzzy cognitive map to evaluate drilling and blasting problems of the tunneling projects in Iran. Engineering with Computers, 35(1), 35-45.
Balafoutis, A. T., Papageorgiou, E., Dikopoulou, Z., Fountas, S., & Papadakis, G. (2014). Sunflower oil fuel for diesel engines: an experimental investigation and optimum engine setting evaluation using a multi-criteria decision making approach. International journal of green energy, 11(6), 642-673.
Bendiab, K., Shiaeles, S., Boucherkha, S., & Ghita, B. (2019). FCMDT: A novel fuzzy cognitive maps dynamic trust model for cloud federated identity management. computers & Security, 86, 270-290.
Brandes, C. M., & Tackett, J. L. (2019). Contextualizing neuroticism in the Hierarchical Taxonomy of Psychopathology. Journal of Research in Personality, 81, 238-245.
Bueno, S., & Salmeron, J. L. (2009). Benchmarking main activation functions in fuzzy Cognitive maps. Expert Systems with Applications, 36(3), 5221–5229.
Chandola, R. (2016). Personality Difference between Psychotics & Neurotics: A Clinical Analysis. International Journal of Indian Psychology, 3(3), 107-115.
Chunying, Z., Lu, L., Dong, O., & Ruitao, L. (2011, April). Research of rough cognitive map model. In International Conference on Electronic Commerce, Web Application, and Communication (pp. 224-229). Springer, Berlin, Heidelberg.
Cohen, W., & Cohen, N. (2003). The paranoid organization & 8 other ways your company can be crazy. AMACOM: New York.
De Colle, S., & Freeman, R. E. (2020). Unethical, neurotic, or both? A psychoanalytic account of ethical failures within organizations. Business Ethics: A European Review, 29(1), 167-179.
Ficher, T. F, (2004). Five types of organizational dysfunction, Ministry of health LL cus. A.
Froelich, W., & Pedrycz, W. (2017). Fuzzy cognitive maps in the modeling of granular time series. Knowledge-Based Systems, 115, 110-122.
Furfaro, R., Kargel, J. S., Lunine, J. I., Fink, W., & Bishop, M. P. (2010). Identification of cryovolcanism on Titan using fuzzy cognitive maps. Planetary and Space Science, 58(5), 761-779.
Groumpos, P. P. (2010). Fuzzy cognitive maps: Basic theories and their application to complex systems. In Fuzzy cognitive maps (pp. 1-22). Springer, Berlin, Heidelberg.
Harder, H. (2003). Early intervention in disability management: Factors that influence successful return to work. International Journal of Disability, Community and Rehabilitation, 2(2), 1-8.
Hoboken. (1991). Depressed organizations: Identifying the symptoms and overcome. Employment Relations Today, 18, 443-452.
Kamkar, M., & Atashpour, S. H. (2007).Psychology of Patient Organizations (neurotic). Esfahan: Moheban. (in Persian)
Kersten, A. (2005). Crisis as usual: organizational dysfunction and public relations. Public relations review. Vol (31). pp 544-549.
Kets de Vries, M. (2004). Dysfunctional leadership. Encyclopedia of leadership. Great Barrington, MA: Berkshire. Sage. Retrieved, 4(12), 2004.
Kets de Vries, M. F., & Miller, D. (1984). Neurotic style and organizational pathology. Strategic management journal, 5(1), 35-55.
Kets de Vries, M. F., & Rook, C. (2018). Coaching challenging executives. Mastering Executive Coaching (2018), Jonathan Passmore and Bryan Underhill,(Eds.) Routledge.
Kontogianni, A., Tourkolias, C., & Papageorgiou, E. I. (2013). Revealing market adaptation to a low carbon transport economy: Tales of hydrogen futures as perceived by fuzzy cognitive mapping. International journal of hydrogen energy, 38(2), 709-722.
Kosko, B. (1986). Fuzzy cognitive maps. International journal of man-machine studies, 24(1), 65-75.
Kosko, B. (2010). Fuzzy cognitive maps: advances in theory, methodologies, tools and applications (studies in fuzziness and soft computing).
Kyriakarakos, G., Dounis, A. I., Arvanitis, K. G., & Papadakis, G. (2017). Design of a Fuzzy Cognitive Maps variable-load energy management system for autonomous PV-reverse osmosis desalination systems: A simulation survey. Applied Energy, 187, 575-584.
Lahey, B. B. (2009). Public health significance of neuroticism. American Psychologist, 64(4), 241.
Mago, V. K., Bakker, L., Papageorgiou, E. I., Alimadad, A., Borwein, P., & Dabbaghian, V. (2012). Fuzzy cognitive maps and cellular automata: An evolutionary approach for social systems modelling. Applied Soft Computing, 12(12), 3771-3784.
Manafi Sharafabad, K., & Zamani, E. (2012). The role of education system in cultural development of society. Journal of Cultural Engineering. 73, 134-152. (in Persian)
Mostafaee, K., Azar, A., Moghbel, A. (2018). Identification and Analysis of Operational Risks: A Fuzzy Cognitive Map Approach. Asset Management and Financing, 6(4), 1-18. (in Persian)
Motamedi, K. (2006). Seven neurotic styles of management. Graziadio Business Review, 9(4).
Ormel, J., Bastiaansen, A., Riese, H., Bos, E. H., Servaas, M., Ellenbogen, M., ... & Aleman, A. (2013). The biological and psychological basis of neuroticism: current status and future directions. Neuroscience & Biobehavioral Reviews, 37(1), 59-72.
Papageorgiou, E. I., & Stylios, C. D. (2008). Fuzzy cognitive maps. Handbook of Granular computing, 123, 755-775.
Papageorgiou, E. I., Hatwágner, M. F., Buruzs, A., & Kóczy, L. T. (2017). A concept reduction approach for fuzzy cognitive map models in decision making and management. Neurocomputing, 232, 16-33.
Papageorgiou, E. I., Poczęta, K., Yastrebov, A., & Laspidou, C. (2017, June). Fuzzy cognitive maps and multi-step gradient methods for prediction: applications to electricity consumption and stock exchange returns. In International Conference on Intelligent Decision Technologies (pp. 501-511). Springer, Cham.
Papageorgiou, E. I., Stylios, C., & Groumpos, P. P. (2006). Unsupervised learning techniques for fine-tuning fuzzy cognitive map causal links. International Journal of Human-Computer Studies, 64(8), 727-743.
Papageorgiou, E. I., Subramanian, J., Karmegam, A., & Papandrianos, N. (2015). A risk management model for familial breast cancer: A new application using Fuzzy Cognitive Map method. Computer methods and programs in biomedicine, 122(2), 123-135.
Papakostas, G. A., & Koulouriotis, D. E. (2010). Classifying patterns using fuzzy cognitive maps. In Fuzzy cognitive maps (pp. 291-306). Springer, Berlin, Heidelberg.
Papakostas, G. A., Boutalis, Y. S., Koulouriotis, D. E., & Mertzios, B. G. (2008). Fuzzy cognitive maps for pattern recognition applications. International Journal of Pattern Recognition and Artificial Intelligence, 22(08), 1461-1486.
Poczęta, K., & Yastrebov, A. (2015, March). Monitoring and prediction of time series based on fuzzy cognitive maps with multi-step gradient methods. In International Conference on Automation (pp. 197-206). Springer, Cham.
Poczeta, K., Kubus, L., & Yastrebov, A. (2019). Analysis of an evolutionary algorithm for complex fuzzy cognitive map learning based on graph theory metrics and output concepts. BioSystems, 179, 39-47.
Puerto, E., Aguilar, J., López, C., & Chávez, D. (2019). Using multilayer fuzzy cognitive maps to diagnose autism spectrum disorder. Applied Soft Computing, 75, 58-71.
Rezaee, M. J., Yousefi, S., & Hayati, J. (2018). A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level. Neural Computing and Applications, 29(3), 761-777.
Salmeron, J. L., & Froelich, W. (2016). Dynamic optimization of fuzzy cognitive maps for time series forecasting. Knowledge-Based Systems, 105, 29-37.
Salmeron, J. L., & Papageorgiou, E. I. (2012). A fuzzy grey cognitive maps-based decision support system for radiotherapy treatment planning. Knowledge-Based Systems, 30, 151-160.
Salmeron, J. L., Mansouri, T., Moghadam, M. R. S., & Mardani, A. (2019). Learning fuzzy cognitive maps with modified asexual reproduction optimisation algorithm. Knowledge-Based Systems, 163, 723-735.
Salmeron, J. L., Rahimi, S. A., Navali, A. M., & Sadeghpour, A. (2017). Medical diagnosis of Rheumatoid Arthritis using data driven PSO–FCM with scarce datasets. Neurocomputing, 232, 104-112.
Salmeron, J. L., Ruiz-Celma, A., & Mena, A. (2017). Learning FCMs with multi-local and balanced memetic algorithms for forecasting industrial drying processes. Neurocomputing, 232, 52-57.
Savadkouhi, A.R., Kamkar, M., & Samavatian, H. (2011). Relationship between Dimensions of Organizational Neuroticism and Mental Health from the Viewpoint of Employees, Journal of Modern Industrial/Organization Psychology, 2(6), 53-63. (in Persian)
Schwarz, J. O. (2007). Assessing future disorders in organizations: implications for diagnosing and treating schizophrenic, depressed or paranoid organizations. Foresight. 9(2), 15-26.
Shokravee, S., Hosseyneeyaan, S., Samaavaateeyaan, H., Samsaamshareeat, M. (2010). Leadership style and organizational atmosphere in Neurotic organizations. The Journal of New Thoughts on Education, 6(3), 95-114. (in Persian)
Skład, A. (2019). Assessing the impact of processes on the Occupational Safety and Health Management System’s effectiveness using the fuzzy cognitive maps approach. Safety science, 117, 71-80.
Spector, P. E. (2006). Industrial and organizational psychology: Research and practice. John Wiley & Sons Inc.
Stylios, C. D., & Groumpos, P. P. (2004). Modeling complex systems using fuzzy cognitive maps. IEEE Transactizons on Systems, Man, and Cybernetics-Part A: Systems and Humans, 34(1), 155-162.
Tsadiras, A. K. (2008). Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps. Information Sciences, 178(20), 3880-3894.
Vergini, E. S., & Groumpos, P. P. (2016). A new conception on the fuzzy cognitive maps method. IFAC-PapersOnLine, 49(29), 300-304.
Wang, L., Liu, Q., Dong, S., & Soares, C. G. (2019). Effectiveness assessment of ship navigation safety countermeasures using fuzzy cognitive maps. Safety science, 117, 352-364.
Yasini, A., Shiri, A., Moradi Kia, F. (2018). A Comparative Study on the Role of Negative Behaviors of Organizational Behavior in inefficient Occupational Behaviors of Employees. Management Studies in Development and Evolution, 27(90), 65-88. (in Persian)
مدیریت دولتی
دوره 12، شماره 3
1399
صفحه 461-493

فایل ها

هم رسانی

ارجاع به این مقاله

آمار