This paper is an extension and elaboration of previous research on the simulation of three competing technologies that interact. A modified version of the three-technology system is investigated, and some initial system dynamics results are reported illustrating the progression from asymptotic to cyclic behaviour. Technology is considered in this research as a result of innovation, a rate-dependent process that may include several non-linearities due to interaction with the environment and social context. Using bibliometrics as a research data source is an interesting way to trace technology growth patterns very effectively. In this research, the existence of cyclic behaviour in two real life technologies is illustrated using bibliometrics. In this paper, a technology system consisting of three interacting technologies is treated and modelled in a coupled manner where the interacting dynamics is described by the Lotka-Volterra system of differential equations. The effect of interaction between the technologies and the period of cyclic behaviour is illustrated parametrically. Furthermore, the possible uncertain diffusion as well as interaction effect for two of the technologies is also addressed in this research using a Monte Carlo multivariate simulation technique and a system dynamics approach. The research method is exploratory and case based.
A systems approach to creating a system is discussed. The system engineering process, and specifically the system architecture process, is formulated and applied to a typical (physical) system, enterprise, and project. These lead to the concepts of system architecture (SA), enterprise architecture (EA), and project architecture (PA) respectively. Similarities and interrelationships among these architectures and related methodologies are investigated, seeking better interaction among them. 'Work' is proposed as an important conceptual building-block of these architectures, properly defined as activity with associated inputs, outputs, governances, and mechanisms. Techniques such as functional analysis, process modelling, and task analysis are used to demonstrate the interrelationships among these apparently unrelated organisational perspectives of product, process, and project.
This research emanates from a systems-oriented process of investigation into the educational approach of masters in engineering management programmes in order to find ways to improve student through-put rate and the quality of learning. The document describes the educational process, with specific emphasis on student preparedness, including the value and impact of a pivotal preparation test. This process is guided by constructive alignment; learning cycles through interactive blended teaching; and a focus on student learning. A longitudinal descriptive case study of the programmes was undertaken, focusing on a systems engineering module, which is integral to all masters programmes. The case is described with regard to its context; the educational process and teaching approach; and an educational and statistical analysis of the preparation test.The main contribution of the paper is the resulting structured, holistic, and integrated education process, designed to address the challenges, including a specific focus on student preparation and the pivotal preparation test. A clear link was established between student preparedness and the subsequent levels of teaching and learning. The preparation test was found to be on the relevant cognitive level; a predictor of course success; influencing positively the motivation of students; as well as impacting on the adaptation of the educational process. The use of the adapted Bloom's taxonomy to evaluate cognitive levels of an intervention; the application of learning cycles and constructive alignment; as well as the impact of a preparation test, can significantly enhance the quality of the education process and consequently, student through-put rates. C⃝ 2014 Wiley Periodicals, Inc. Syst Eng 00: [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15] 2014
Central to project management is risk management-and the need to develop better and more specific tools to manage risk. This is driven by the desire to reduce uncertainty and risk on projects. Quantitative tools such as Monte Carlo simulation are sometimes used to analyse risk, but it is not clear how widespread, accepted, or useful such tools are for practising project personnel. This research was undertaken to gain feedback from practising project and risk management personnel about the use of risk management tools. Special attention was given to the levels of use of quantitative risk management tools and the benefits gained from their use. A conceptual framework was created linking the factors that affect tool use to the actual tool use levels, and ultimately to project performance. Research questions reported on in this paper addressed levels of tool use, factors that affect tool usage, and the benefit aspect of tool use on project performance. Data were gathered via an on-line questionnaire that was statistically analysed, and a number of hypotheses were tested. The results of this study show that the levels of use of both qualitative and quantitative risk management tools are low compared with general project management tools. Correlations were found between a number of factors that affect tool use.
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