Our results summarize the correlation analysis as well as describe the process for presenting and analyzing the model and hypothesis testing. To begin, the Pearson Coefficients in Table 13 show statistically significant high correlations between measures of the same variable, consistent with convergent validity (Bhattacherjee (2012). For example, the two measures (CPAR and Profit Margin) of the dependent variable, Project Performance, have a statistically significant Pearson Coefficient of 0.35. Likewise, the two measures (Observations and Certifications) of the independent variable, Culture of Safety, and our two measures of the independent variable, Safety Plan, have a statistically significant Pearson Coefficients of 0.65 and 0.42, …show more content…
Specifically, we build up regression models by incrementally adding variables to the previous model (Kim, 2016), as described and displayed in Tables 14 (model summary) and 15 (coefficients summary). We start with a baseline model (#1), which includes the constant and controls. We add each independent variable to the previous models, creating Models #2 and #3. Thereafter, we add the moderating variable, generating Model #4, which represents our conceptual model. Next, we include the best-fit model (#5) from “Backward” method. Model #5 is the best-fit model from a statistical significance and explanation of variance (R squared) aspect. Consequently, we analyze, but do not show other models produced from the “Backward” method, because they also overlap with Models #1 through #4. We repeat this systematic process for the financial measure (Profit Margin) of the dependent variable, Project Performance, creating Tables 15 (model summary) and 16 (coefficients summary). Finally, we illustrate a revised conceptual model, supported by the regression model and coefficient data, for both the operational (CPAR) and the financial measure (Profit Margin) of the Project Performance (see Figures 10 and 11). We now describe the regression model results, starting with the operational and followed by the financial measure of Project Performance. Project Performance
1.1. Review principles of estimating project cash flows. Suggested reading: Ch. 9 “Capital Budgeting and Cash Flow Analysis” in “Contemporary Financial Management”, 11th ed. by Moyer, McGuigan, and Kretlow.
Estimate the project’s operating cash flows for each year of the project’s economic life. (Hint: Use Table 2 as a guide)
Finally, in order to complete a more accurate comparison between the two projects, we utilized the EANPV as the deciding factor. Under current accepted financial practice, NPV is generally considered the most accurate method of predicting the performance of a potential project. The duration of the projects is different, one lasts four years and one lasts six years. To account for the variation in time frames for the projects and to further refine our selection we calculated the EANPV to compare performance on a yearly basis.
Moreover, Robert Gates’ estimation of the price increase (2.0%) differs from the information provided in the case (1.7%). This overestimates revenue and thereby FCF. To make better projections for the firms’ FCF, Robert Gates would also have to consider the opportunity cost of alternative investments, the risk exposure throughout the project and operational risks after three years.
Evaluating the risks, calculating the probability of success, and factoring in the projected profit from sales will provide a clearer NPV to be compared with other projects in the
At the new WACC of 19%, the home appliance and agricultural machinery projects are valued based on their inherent levels of risk. The beta of the industry average home appliance project is 0.95, whereas the beta for the industry average agricultural machine project is calculated as 0.88. CAPM was then employed to find the cost of capital of each project. The cost of capital for the home appliance and agricultural machinery projects were found to be 10.4% and 9.92%, respectively (Appendix B). This analysis allows Star Company to allocate funds to projects that create returns greater than the industry cost of capital for each specific project.
592 Week 1 DQ 1 WBS Construction PROJ 592 Week 1 DQ 2 Project Cost Estimates and Assumptions PROJ 592 Week 2 DQ 1 Cost Components PROJ 592 Week 2 DQ 2 Estimating Processes PROJ 592 Week 3 DQ 1 Project Schedules PROJ 592 Week 3 DQ 2 Sensitivity Analysis PROJ 592 Week 4 DQ 1 Resource Allocation and Leveling PROJ 592 Week 4 DQ 2 Advanced Schedule Techniques PROJ 592 Week 5 DQ 1 Earned Value Calculation PROJ 592 Week 5 DQ 2 Project Monitoring and Control & EV PROJ 592 Week 6 DQ 1 Forecasting Project Completion Cost PROJ 592 Week 6 DQ 2 Project Control PROJ 592
When implementing project 1, you face technical and market risk. How would you assess the risks embedded in Project 1?
Since the maximum value of the predictor variable (calls) is used to formulate the given regression model is 201.00, which is less than 300, we cannot use the given regression model to accurately estimate the weekly sales for weekly call of 300. So we can’t say anything about the weekly sales when weekly calls are 300.
Furthermore, a sensitivity analysis of factors such as the cost of raw materials, selling price per unit and capacity utilization demonstrates that a small change in any one of these variables could have a major impact on the project’s bottom line. In Appendix B, I examine a scenario in which the selling price per unit decreases by 1% and the cost of raw materials per unit increases by 1% at the outset of the project. In this scenario, the resulting NPV changes from a positive $5.4 million to a loss of $666,000, and the IRR falls below the discount rate to 9.15%. This, to me, reveals that the potential upside of this project is not large enough to account for discrepancies due to imprecise projections, flawed assumptions, or unforeseen risks.
The Modified Internal Rate of Return is an underused measure for selection of projects that a company can choose because it is more effective at dealing effectively with periodic free cash flows that develop from the time that an asset is purchased through its life to the point where it is sold, ranking projects and variable rates of return through the project life. The Internal Rate of Return is an inefficient model to make decisions with because it lack the ability to account for the periodic free cash flows, proper ranking and variable returns from certain projects.
The analysis of the financial projection in this report is based on the assumptions and the information which you (client) provided. These assumptions and information can be change with the passage of time. The
This case study analyzed five different projects Target Corporation had to decide on capital spent for which project created the most value and the most growth for the company and its shareholders. By analyzing the financial statements and exhibits of each project, I was able to determine the positives and negatives of each of these alternatives. The alternatives were Gopher Place, Whalen Court, The Barn, Goldie’s Square, or Stadium Remodel.
The use of an accounting rate of return also underscores a project 's true future profitability because returns are calculated from accounting statements that list items at book or historical values and are, thus, backward-looking. According to the ARR, cash flows are positive due to the way the return has been tabulated with regard to returns on funds employed. The Payback Period technique also reflects that the project is positive and that initial expenses will be retrieved in approximately 7 years. However, the Payback method treats all cash flows as if they are received in the same period, i.e. cash flows in period 2 are treated the same as cash flows received in period 8. Clearly, it ignores the time value of money and is not the best method employed. Conversely, the IRR and NPV methods reflect that The Super Project is unattractive. IRR calculated is less then the 10% cost of capital (tax tabulated was 48%). NPV calculations were also negative. We accept the NPV method as the optimal capital budgeting technique and use its outcome to provide the overall evidence for our final decision on The Super Project. In this case IRR provided the same rejection result; therefore, it too proved its usefulness. Despite that, IRR is not the most favorable method because it can provide false results in the case where multiple negative
The following paper analyzes a project from financial perspectives using the capital budgeting techniques like Net Present Value (NPV) and Internal Rate of Return (IRR).