CORPORATE STRUCTURE ANALYSIS OF ORGANIZATIONS FROM NETWORK PERSPECTIVE

Yıl 2018, Cilt: 5 Sayı: 3, 231 - 237, 30.09.2018

Cigdem Baskici Yavuz Ercil

Öz

Purpose- The aim of our study is to reveal the corporate structure of
organizations from network perspective. It is aimed to establish decision
criteria for the efficiency and priority of actions in line with analysis
results.

Methodology- We use the document relationships between all units of a professional
organization with public institution status in 2016. The relations between
these units are evaluated by network analysis. Six indicators such as
integration, driving, driven, stability, criticality and precarious are used to
describe the dynamic character of the organizational structure.

Findings- According to the analysis results, two units are defined as integrative,
two are as driving and three of them as driven, two are critical and two of
them are precarious. Overall system stability is %56. This means that the
system in focus is not under the threat of neither disorganization nor inertia.

Conclusion- With study findings, it is possible to follow the dynamic reflection of
any topic on the system and apply the targets of the units in the most
appropriate way to the institutional structure.

Anahtar Kelimeler

Network analysis, corporate structure, dynamic structure, strategic decision, strategic management

Kaynakça

• Bar-Yam, Y. (1997). Dynamics of complex systems. Reading, MA: Addison-Wesley.
• Baxter, G., Sommerville, I. (2011). Socio-technical systems: from design methods to systems engineering. Interacting with Computers, 23(1), 4-17.
• Borgatti, S. P., Halgin, D. S. (2011). On network theory. Organization Science, 22(5), 1168-1181.
• Burt, S. R. (1995). Structural holes: the social structure of competition. USA: Harvard University Press.
• Burt, S. R. (2011). Neighbor networks: competitive advantage local and personal. USA: Oxford University Press.
• Egghe, L. (2009). Mathematical derivation of the impact factor distribution. Journal of Informetrics, 3(4), 290–295.
• Ercil, Y. (2014). Örgütsel tasarım ve değişim. (Ed) Ü. Sığrı, & S. Gürbüz, Örgütsel davranış (ss. 634-659). İstanbul: Beta.
• Geels, F. W. (2004). From sectoral systems of innovation to socio-technical systems: insights about dynamics and change from sociology and institutional theory. Research Policy, 33(6-7), 897-920.
• Hanneman, R. A., Riddle, M. (2005). Introduction to social network. CA: University of California. http://faculty.ucr.edu/hanneman/nettex
• Hanseth, O., Lyytinen, K. (2016). Design theory for dynamic complexity in information infrastructures: the case of building internet. (Ed) L. P. Willcocks, C. Sauer, & M. C. Lacity, Enacting research methods in information systems (ss. 104-142). Cham: Palgrave Macmillan.
• Haythornthwaite, C. (1996). Social network analysis: an approach and technique for the study of information exchange. Library and Information Science Research, 18(4), 323-342.
• James, L. R., Jones, A. P. (1976). Organizational structure: a review of structural dimensions and their relationships with individual attitudes and behavior. Organizational Behavior and Human Performance, 16, 74-113.
• Jo, H., Park, Y., Kim, S. E., Lee, H. (2016). Exploring the intellectual structure of nanoscience and nanotechnology: journal citation network analysis. Journal of Nanoparticle Research, 18, 167.
• Lei, D., Slocum, J.W. (2005). Strategic and organizational requirements for competitive advantage. The Academy of Management Executive, 19(1), 31-45.
• Linss V., Fried, A. (2010). The ADVIAN® classification — a new classification approach for the rating of impact factors. Technological Forecasting & Social Change, 77, 110–119.
• Maoz, Z. (2011). Network of nations. The evolution, structure, and impact of international network, 1861-2001. USA: Cambridge University Press.
• Marin, A., Wellman, B. (2014). Social network analysis: an introduction. (Ed) J. Scott, and P. J. Carrington, The SAGE handbook of social network analysis (ss. 11-25). Great Britain: SAGE.
• McKelvey, B. (1999). Complexity theory in organization science: seizing the promise or becoming a fad?. Emergence, 1(1), 5-32.
• Nelson, R. E. (2011). The strength of strong ties: social networks and intergroup conflict in organizations. (Ed) M. Kilduff and A. V. Shipilov, Organizational network volume II (ss. 3-26). London: SAGE.
• Pryke, S. (2012). Social network analysis in construction. Chichester: John Wiley and Sons.
• Read, G. J., Salmon, P. M., Lenné, M. G., Stanton, N. A. (2015). Designing sociotechnical systems with cognitive work analysis: putting theory back into practice. Ergonomics, 58(5), 822-851.
• Rosenthal, C. (2013). Big data in the age of the telegraph. McKinsey Quarterly, 1.
• Rousseau, D. M. (1977). Technological differences in job characteristics, employee satisfaction, and motivation: a synthesis of job design research and sociotechnical systems theory, Organizational Behavior and Human Performance, 19(1), 18-42.
• Stacey, R. D. (1995). The science of complexity: an alternative perspective for strategic change processes. Strategic Management Journal, 16(6), 477-495.
• Trist, E. (1981). The evolution of socio-technical systems. Occasional Paper, No.2.
• Von Tunzelmann, N. (2004). Network alignment in the catching-up economies of Europe. (Ed) McGowan F., Slavo R., & von Tunzelmann N., The emerging industrial structure of the wider Europe (ss. 24-40). Routledge.
• Wasserman, S., Faust, K. (1994). Social network analysis: method and applications. Cambridge: Cambridge University Press.
• Wheatley, M. (2006). Leadership and the new science. Berrett-Koehler Pub., 27-32.