مقایسه ساختار رسمی و غیررسمی در سازمان‌ها با استفاده از روش تحلیل شبکه اجتماعی

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه مهندسی صنایع، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران

2 استاد، گروه مدیریت سیستم و بهره‌وری، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران

10.22059/imj.2023.355111.1008026

چکیده

هدف: ساختار با توجه به اهداف استراتژیک سازمان و فرایندهای شناسایی و تعریف‌شده طراحی می‌شود و مبنای طراحی فعالیت‌ها و ارتباطات کارکنان قرار می‌گیرد. فرایندها و فعالیت‌های سازمان‌ها و شرکت‌ها نیز، از طریق نقش‌ها و سمت‌های سازمانی‌ای اجرا می‌شود که بر اساس ساختار و با توجه به دستیابی به اهداف سازمانی، به کارکنان واگذار می‌شود. اما سؤال مهم این است که ساختار رسمی تا چه اندازه می‌تواند پاسخ‏گوی نیازهای ارتباطی مردم و اجرای فعالیت‌های تفویض‌شده باشد. این در حالی است که در بسیاری از سازمان‌ها، به موازات ساختار رسمی، ساختاری غیررسمی نیز شکل می‌گیرد و بسیاری از فعالیت‌ها، بر اساس روابط شکل‌گرفته در ساختار غیررسمی انجام می‌شود؛ زیرا به‌دلایل مختلف، کارکنان بعضی سازمان‌ها مجبورند که از طریق ارتباطات غیررسمی و در قالب تیم‌های کاری موقت، بخشی از فرایندهای سازمانی را انجام دهند. در واقع، وجود ساختار غیررسمی در بسیاری از سازمان‌ها اجتناب‌ناپذیر است. حال که از وجود ساختارهای غیررسمی در سازمان‌ها گریزی نیست، بهتر است سازمان‌ها با علم به این موضوع و با دیدی روشن، این ساختارها را مدیریت کنند. موضوع اصلی، نظارت بر ساختار غیررسمی و مدیریت صحیح این ساختار و روابط ناشی از آن است. سنجش میزان تشابه و تفاوت ساختارهای رسمی و غیررسمی سازمان، از اهداف این پژوهش است.
روش: ساختار رسمی، از نمودار سازمانی استخراج شده است. ساختار غیررسمی، مبتنی بر ثبت اطلاعات و اطلاعات موجود در منابع و پایگاه‌های مختلف است. گزارش‌هایی از رویدادهای ناشی از تعاملات کاری افراد، در فرایند انتخاب تأمین‌کننده از یک شرکت پروژه‌محور، در یکی از پروژه‌های ساختمانی پیچیده جمع‌آوری شد و به‌کمک روش تحلیل شبکه‌های اجتماعی، از این داده‌ها به‌عنوان یک شبکه غیررسمی استفاده شد. میزان تشابه و تفاوت ساختار رسمی و غیررسمی شرکت، از طریق معیارهای شبکه اجتماعی و شاخص رند سنجیده شد.
یافته‌ها: بر اساس اطلاعات به‌دست‌آمده در فرایند یادشده، کارگروه‌ها یا جوامع غیررسمی ناشی از تعاملات واقعی افراد شناسایی و تجزیه‌وتحلیل شد. این جوامع بر اساس ساختار سلسله‌مراتبی سازمان با اداره‌ها و واحدهای رسمی مقایسه شدند. با استفاده از شاخص رند، شباهت این دو ساختار 76/0 درصد برآورد شد. این روش می‌تواند مبنایی برای مقایسه ساختار رسمی و ساختار واقعی شرکت‌ها باشد. درجه شباهت یا تفاوت ایدئال بین این دو ساختار، بسته به ماهیت، فرهنگ و مأموریت هر شرکت، متفاوت است.
 
نتیجه‌گیری: استفاده از این روش و شناسایی و تحلیل علل تفاوت‌های این دو گروه از ساختارهای ارتباطی، می‌تواند به سازمان‌ها کمک کند تا ساختارهای خود را بهبود بخشند، آن‌ها را چابک‌تر کنند و برخی کاستی‌های ساختاری را جبران کنند. با استفاده از این روش تحلیل و مقایسه نتایج در این دو گروه، می‌توان ساختار سازمانی را بررسی کرد، کارگروه‌ها و تیم‌های مؤثر را تقویت کرد، از ارتباطات مؤثر حمایت کرد و حتی، از ضعف ارتباطات پیشگیری کرد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Comparison of Formal and Informal Structures in Organizations Using the Social Network Analysis

نویسندگان [English]

  • Seyedeh Motahareh Hosseini 1
  • Mohammad Aghdasi 2
1 Candidate, Department of Industrial Engineering, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
2 Prof., Department of System Management and Productivity, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran
چکیده [English]

Objective
Organizational structures are purposefully crafted around the strategic objectives of companies, incorporating well-defined processes that serve as the foundation for employee activities and communication. The processes and activities of organizations and companies are implemented through organizational roles and positions that are assigned to employees based on the structure and goals. However, the crucial question lies in how effectively official structures can address people's communication needs and facilitate the implementation of activities. Within numerous organizations, an informal structure emerges in parallel to the official hierarchy, leading to the execution of various activities based on the relationships established within this informal framework. Because of various reasons, employees in some organizations are forced to carry out organizational processes through informal communication and in temporary work teams. The presence of an informal structure in numerous organizations is an unavoidable phenomenon. However, the primary concern lies in effectively monitoring and appropriately managing this structure and the relationships that arise from it. This study mainly seeks to measure the degree of similarity and difference between the formal and informal structures of the organization.
 
Methods
In the present study, the official structures were extracted based on the organizational chart. The informal structures were based on data logs and information from different sources and bases. Reports of events taking place via the work interactions of people in the process of supplier selection in a project-oriented company were collected in one of the complex construction projects. The gathered data was used as an informal network using the social network analysis method. The degree of similarity and difference between the formal and informal structure of the company was measured through social network criteria and the Rand index.
 
Results
Based on the information obtained, the informal working groups or communities resulting from the real interactions of people were identified and analyzed. Also, these communities were compared with departments and formal units based on the hierarchical structure of the organization. In addition, by using the Rand index, the similarity of these two structures was estimated to stand at 0.76%. This method can be a basis for comparing the official structure and the real structure of companies. The ideal degree of similarity or difference between the two structures varies depending on the nature, culture, and mission of each company.
 
Conclusion
Using this method and identifying and analyzing the causes of the differences between these two groups of communication structures can help organizations improve their structures, make them more agile, and compensate for some structural deficiencies. By using this way of analyzing and comparing the results in these two groups, it is possible to examine the organizational structure, strengthen effective working groups and teams, support effective communication, and even prevent weak communication.

کلیدواژه‌ها [English]

  • Construction project
  • Organizational structure
  • Social network communities
  • Social Network Analysis (SNA)

مراجع

 
References
Abbsaian-Hosseini, A., Liu, M. & Hsiang, S.M. (2019). Social network analysis for construction crews. International Journal of Construction Management, 19(2), 1-15.
Ahmady, Gh.A., Mehrpour, M. & Nikooravesh, A. (2016). Organizational structure. Procedia-Social and Behavioral Sciences, 230, 455-62.
Akgül, B.K., Ozorhon, B., Dikmen, I. & Birgonul, M.T. (2017). Social network analysis of construction companies operating in international markets: case of Turkish contractors. Journal of Civil Engineering and Management, 23(3), 1-11.
Alinezhad, E., Teimourpour, B., Sepehri, M.M. & Kargari, M. (2020). Community detection in attributed networks considering both structural and attribute similarities: two mathematical programming approaches. Neural Computing and Applications, 32, 3203-20.
Amit, R. & Zott, C. (2012). Creating value through business model innovation. MIT Sloan Management Review, 53(3), 41-49.
Appice, A. (2018). Towards mining the organizational structure of a dynamic event scenario. Journal of Intelligent Information Systems, 50,165-193.
Bastian, M., Heymann, S. & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. In Third international AAAI conference on weblogs and social media.
Berahmand, K., Bouyer, A. & Vasighi, M. (2018). Community detection in complex networks by detecting and expanding core nodes through extended local similarity of nodes. IEEE Transactions on Computational Social Systems, 5, 1021-33.
Biffl, D.W. (2010). Process Analysis and Organizational Mining in Production Automation Systems Engineering. Vienna University of Technology, Austria.
Bonanomi, M. M., Hall, D.M., Staub-French, S., Tucker, A. & Talamo, C.M.L. (2019). The impact of digital transformation on formal and informal organizational structures of large architecture and engineering firms. Engineering, Construction and Architectural Management, 27(4), 872-892.
Bouyer, A. & Roghani, H. (2020). LSMD: A fast and robust local community detection starting from low degree nodes in social networks', Future Generation Computer Systems, 113, 41-57.
Chen, N., Liu, Y., Chen, H. & Cheng, J. (2017). Detecting communities in social networks using label propagation with information entropy. Physica A: Statistical Mechanics and its Applications, 471, 788-98.
Chinowsky, P., Diekmann, J. & Galotti, V. (2008). Social network model of construction. Journal of construction engineering and management, 134, 804-12.
Cisterna, D., Von Hey, J., Alarcón, D.M., Herrera, R.F. & Alarcón, L.F. (2018). Application of social network analysis in lean and infrastructure projects. In 26th Annual Conference of the International Group for Lean Construction: Evolving Lean Construction Towards Mature Production Management Across Cultures and Frontiers, 412-21.
Cross, R.L., Cross, R.L. & Parker, A. (2004). The hidden power of social networks: Understanding how work really gets done in organizations. Harvard Business Press.
Elezaj, E., Morina, D. & Kuqi, B. (2020). How organizational matrix structure can impact in project management success. International Multidisciplinary Scientific GeoConference: SGEM, 20, 131-38.
Fani, H. & Bagheri, E. (2018). Community detection in social networks. in, Semantic Computing (World Scientific).
Ferreira, D.R. & Vasilyev, E. (2015). Using logical decision trees to discover the cause of process delays from event logs. Computers in Industry, 70, 194-207.
Fonseca, L. (2022). The EFQM 2020 model. A theoretical and critical review. Total Quality Management & Business Excellence, 33, 1011-1138.
Fortunato, S. (2010). Community detection in graphs. Physics reports, 486, 75-174.
Guimera, R., Danon, L., Diaz-Guilera, A., Giralt, F. & Arenas, A. (2006). The real communication network behind the formal chart: Community structure in organizations. Journal of Economic Behavior & Organization, 61(4), 653-667.
Hitt, M.A., Ireland, R.D. & Hoskisson, R.H. (2019). Strategic management: Concepts and cases: Competitiveness and globalization. Cengage Learning.
Kereri, J.O. & Harper, C.M. (2018). Trends in social network research in construction teams: A literature review. In Construction Research Congress 2018, 115-25.
Kim, Y., Choi, T.Y., Yan, T. & Dooley, K. (2011). Structural investigation of supply networks: A social network analysis approach. Journal of Operations Management, 29, 194-211.
Malisiovas, A. & Song, X. (2014). Social network analysis (SNA) for construction projects' team communication structure optimization. In Construction research congress 2014: Construction in a global network, 2032-2042.
McEvily, B., Soda, G. & Tortoriello, M. (2014). More formally: Rediscovering the missing link between formal organization and informal social structure. Academy of Management Annals, 8, 299-345.
Meese, N. & McMahon, C. (2012). Analysing sustainable development social structures in an international civil engineering consultancy. Journal of Cleaner Production, 23, 175-185.
Monavarian, A., Asgari, N. & Ashena, M. (2007). Structural and content dimensions of knowledge-based organizations. In The first national conference of knowledge management, 10-20.
Murata, T. (2010). Detecting communities in social networks. Handbook of social network technologies and applications (Springer).
Nedioui, M.A., Moussaoui, A., Saoud, B. & Babahenini, M.Ch. (2020). Detecting communities in social networks based on cliques. Physica A: Statistical Mechanics and its Applications, 551, 124100.
Nickerson, J.A. & Zenger, T.R. (2002). Being efficiently fickle: A dynamic theory of organizational choice. Organization Science, 13, 547-566.
Orman, G.K., Labatut, V. & Cherifi, H. (2012). Comparative evaluation of community detection algorithms: a topological approach. Journal of Statistical Mechanics: Theory and Experiment, 2012: P08001.
Rand, W.M. (1971). Objective criteria for the evaluation of clustering methods. Journal of the American Statistical association, 66, 846-50.
Shabani, S. & Nik-Bakht, M. (2021). Social network analysis of project procurement in Iranian construction mega projects. Asian Journal of Civil Engineering, 22(2).
Soda, G. & Zaheer, A. (2012). A network perspective on organizational architecture: Performance effects of the interplay of formal and informal organization. Strategic Management Journal, 33, 751-771.
Van Der Aalst, Wil., Reijers, H.A. & Song, M. (2005). Discovering social networks from event logs. Computer Supported Cooperative Work (CSCW), 14, 549-93.
Van Der Aalst, Wil., Reijers, H.A. & Song, M. (2004). Mining social networks: Uncovering interaction patterns in business processes. In International conference on business process management, 244-60. Springer.
Wang, H., Lu, W., Söderlund, J. & Chen, K. (2018). The interplay between formal and informal institutions in projects: A social network analysis. Project management journal, 49, 20-35.
Wenger, E. C. & Snyder, W.M. (2000). Communities of practice: The organizational frontier. Harvard business review, 78, 139-46.
You, X., Ma, Y. & Liu, Z. (2020). A three-stage algorithm on community detection in social networks. Knowledge-Based Systems, 187, 104822.
مدیریت صنعتی
دوره 15، شماره 3
1402
صفحه 365-385

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