BQOM 2521- Decision Making in a Complex Environment Joseph M. Katz Graduate School of Business
March 27, 2018
Table of Contents
4Final Results and Saaty Compatibility Index (4)
In order select an industry to evaluate the market share, it was important to choose something that I have personal knowledge of and therefore will not need to look up large amounts of data to make decisions. I decided to use the SuperDecisions to estimate the makeup of the energy source industry in the United States. There are obviously many different energy sources utilized in the United States, but they are often broken down into three main categories: •Fossil Fuels
I chose this topic, because I have an undergrad in mining engineering and I worked for three years in the coal industry and one year in the nuclear industry prior to attending Katz. This gives me a reasonable amount of knowledge to properly estimate the makeup of these energy sources in the US using the software
The complete network completed in the SuperDecisions software is displayed in the following screen shot:
The network mostly speaks for itself, but as a summary I chose three different clusters that I thought properly represented what determines what energy is utilized in the US. There is one additional connection I made, in that consumer price is correlated to capital and operating costs.
Since there are an excessive amount of judgements to be made, the only screenshot that will be shown is the comparison of clusters with respect to alternatives since these have a massive impact on the weighting of the clusters. Price and Availability have the largest impact on the energy makeup of the United States, whereas the role of perception is growing larger, it still does not have the effect that the economies of scale have to bring price down and the availability of resources throughout the country can.
Further judgements can be seen in the model itself and through the discussion in the conclusion regarding the results.