AbstractThis thesis uses cluster analysis, mixed effect regressions and generalised structural equation modelling to develop and apply comprehensive statistical approaches in order to reasonably categorise highly diverse electricity generating/supplying companies and study any existing average productivity trends and dependences on other performance variables characterising the production process and size of the involved companies. Specific recommendations for the regulating authorities and company management were proposed. These included the need for different managerial approaches in different company groups/categories, different recommended company sizes, managerial approaches to overcome the general negative productivity trends on the power generation market, and the need for government support to ensure the successful transition to renewable energy sources.
|Date of Award||11 Feb 2017|
|Supervisor||Michael Regan (Supervisor)|
The Impact of Supply Chains on Productivity and Financial Performance of Power Producers in Australia.
Aburadi, N. (Author). 11 Feb 2017
Student thesis: Doctoral Thesis