Towards a social networks model for understanding factors for variances in cost and schedule in project implementation and project completion times
According to several theorists, effective communication is one of the key factors in determining the success of failure of a project. However, communication is a complex and challenging management function underpinned by dynamic social processes that are difficult to capture. Over the last century, human communication has been studied widely in the fields of business, anthropology, sociology, and psychology, yet few tools have been developed that allow managers to analyse how their teams communicate. Recently, research on social network analysis (SNA) studies to understand team communication, advice-seeking, and information sharing patterns and its implication on performance is fairly prevalent. For instance, Chung and Hossain (2009) report on using SNA as a methodology to describe the professional advice-seeking networks of rural doctors in NSW, Australia for understanding delivery of quality care. The use of a social networks perspective to model the relationship between project communication structure and project completion is therefore quite novel. In this research, the following motivating questions are asked: (i) what forms of network structure, ties and position are conducive to successful project completion in terms of positive cost and schedule variances? (ii) does strength of tie play an important role in shortening project lead times (iii) is there an inherent relationship between the properties of project communication networks and successful project outcomes irrespective of project domain?
This research will deploy the use of qualitative in-depth interviews to develop a conceptual model for the study, which is to be validated empirically. It is anticipated that the findings will be useful to the project management community as a whole, project managers especially, and to scholars in the area of information science, and the domain level experts within which the data is to be collected from (e.g. construction/engineering industry).
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The opportunity ID for this research opportunity is: 1381
Other opportunities with Dr Kenneth Chung
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