Social Network Analysis-Opportunities in PPPM
Construction productivity have been a classic concern with negative growth in the period 1964-2012 [1], the most likely reasons behind this situation may be the highly fragmented project workflows, procurement systems based on competitive rather than collaborative teams, paper-based project delivery systems (PDS) with a low use of technology in their processes affecting the flow of data and information between the stakeholders creating conflicts and lowering the quality of the projects along all their life cycle.
With the introduction of CPM/PERT in 1958’, the use of technology has been gradually extended in the Project Management discipline [2], but is not until the past decade when their use is being more extensive, the evolution of the technology applied in projects is transforming the Building Industry moving from a paper-based towards a BIM-based type of projects shifting to a lean collaborative processes [3] [4].
Since 2000’s it has been observed a continuous growth of complexity in projects[5][6]caused by the increasingly use of technology, project size/scale, construction methods, stakeholders diversity and overlapping processes in the life cycle of a project, as a result Project Managers have been facing an increase of challenges at strategic, organizational and human resources level[7].
Projects are team-based developed, currently, as a result of the technological advancements projects are producing an immense amount of data, sorting useful data to transform in coordinate and productive information that flows through all the processes along the life cycle of a project is crucial in their success.
Social Network Analysis (SNA) appears as recently technique that explore, maps and measure data & information flows and relationship between organizations, groups, people or other entities.
The aim of this article is to explore different opportunities in the combined use of Data Analysis and SNA for project managers.
Contents |
Social Network Analysis(SNA)-Historical evolution
Organizations are composed by individuals and, based in their ranks, assembled in different groups organized in a hierarchical structure. Work activities and tasks constitutes the main interaction type between these individuals establishing a formal network.
However, within the same organization, interaction between individuals could be based in their work-space proximity, nationality, sport preference, etc. in this case creating different groups and establishing an informal network.
Individuals and organizations are the main actors from either formal or informal structures and as a result of their interaction within a network or with other networks, different behaviour patterns and influential actors could be identified, the analysis of these network dynamics constitutes the object of study of Social Network Analysis (SNA).
According Freeman the historical evolution of SNA comprises the following periods [8][7]:
1. Everything before 1929, focused on the interaction and relationship between actors
2. From 1929 to 1939, focused in a systematic collection of data between this actors
3. From 1940 to 1969, with the introduction of graph theories
4. From 1970 until now, the modern era based on the use of mathematical/computational tools to analyse these interactions
In the past years with the birth of internet and the technological advancements, SNA gained relevance; research studies have been reformulated and reconsider their approach, being the use of network studies an important part, not only, of sociological studies but also incorporated as a strategy used by different disciplines [9][8] (Figure 1).
SNA-Stakeholders perspective
Open systems [10], as organizations, could be influenced by internal or external changes in the environment and at the same time the interconnection between systems could be altered as a result of the above mentioned changes. The propagation of changes would be affected by the network type, cohesive or bridging[11].
References
- ↑ P. Teicholz, “Labor productivity declines in the construction industry: causes and remedies (another look),” AECbytes Viewp., 2013.
- ↑ M. Kozak-Holland, “The History of Project Management,” Lessons from Hist., vol. 18, no. 4, p. 640, 2011.
- ↑ R. Soares, “Reengineering Management of Construction Projects,” Int. J. Bus. Soc. Sci., vol. 4, 2013.
- ↑ P. Teicholz, “Labor productivity declines in the construction industry: causes and remedies (another look),” AECbytes Viewp., 2013.
- ↑ V. R. Santos, António Lucas Soares, and J. Á. Carvalho, “Knowledge Sharing Barriers in Complex Research and Development Projects: an Exploratory Study on the Perceptions of Project Managers,” Knowl. Process Manag., vol. 19, no. 1, pp. 27–38, 2012.
- ↑ B. Xia and A. P. C. Chan, “Measuring complexity for building projects: a Delphi study,” Eng. Constr. Archit. Manag., vol. 19, no. 1, pp. 7–24, 2012.
- ↑ G. R. Jones and J. M. George, “Essentials of Contemporary Management,” Essentials of Contemporary Management, Fifth Edition, 2012.
- ↑ B. H.Rusell, “Linton C. Freeman, The Development of Social Network Analysis: A Study in the Sociology of Science-Review,” vol. 27, pp. 377–384, 2005.
- ↑ R. Rousseau and E. Otte, “Social network analysis: a powerful strategy, also for the information sciences,” J. Inf. Sci., vol. 28, no. 6, pp. 441–453, 2002.
- ↑ J. Hayes, The Theory and Practice of Change Management. Palgrave Macmillan, 2014.
- ↑ J. Battilana and T. Casciaro, “The network secrets of great change agents,” Harvard Business Review, pp. 62–68, 2013.
Appendix 1
In this section are listed all the documents used in the tables and figures.
On September the 17th “DTU Findit” database has been used for search documents that lately are used in the conformation of tables and figures.
A first search with the phrase “Social Network” was used with a total of 113043 entries.
A second search with the phrase “Social Network Analysis (SNA)” was used with a total of 1890 entries.
The prefix “ab: abstract” and the operator “AND” were selected for a third search on the formula “ab: (SNA) AND Stakeholder” with a total 63 entries, 3 entries corresponded to repeated papers, finally a total of 60 documents were retrieved.
