A2 Text Assignment 2 Case Problem Real Estate Development Se

A2 Textassignment 2 Case Problem Real Estate Development Select A N

A real estate company is considering the development of one of the following three possible projects: (1) an apartment building; (2) an office building; (3) a warehouse. The payoff (profit) depends on economic conditions categorized as optimistic, realistic, and pessimistic, with estimated payoffs and probabilities provided for each scenario. Additionally, if the company hires a business analyst, there will be an upfront survey fee, and the survey results can be positive or negative, each with their own probabilities. The decision to hire the analyst affects the potential payoffs depending on the survey outcome, which in turn influences the expected monetary value (EMV) calculations.

The assignment requires preparing a managerial report that addresses two main questions: which project should the company develop, and whether it should hire the business analyst based on the estimates. The report should include the construction of payoff tables, decision trees, EMV calculations, sensitivity analysis, and use of decision analysis software such as TreePlan in Excel. This involves analyzing the payoffs and probabilities, calculating expected values, assessing the impact of the survey results, and making a data-supported recommendation. The report must follow the APA format and be approximately three pages in length, excluding additional supplementary materials like screenshots, charts, and appendices.

Paper For Above instruction

Introduction

Choosing the optimal investment project in real estate development is a complex decision-making process that involves analyzing potential payoffs under uncertain economic conditions. In addition, incorporating the option to conduct a detailed survey through a business analyst introduces further strategic considerations. This paper aims to evaluate three project options—apartment, office, and warehouse—and determine whether hiring a business analyst enhances decision quality based on expected monetary value analysis. The analysis further considers the influence of survey results, associated probabilities, and sensitivity of the decision to changes in these probabilities.

Development of Payoff Tables and Decision Tree

Initially, payoff tables for each project under the three economic conditions—optimistic, realistic, and pessimistic—are created without incorporating probabilities. These tables display the potential profits for each project under different states of nature. Next, a decision tree is constructed to visualize the sequential decision process: choosing whether to hire the analyst, the possible survey outcomes (positive or negative), and subsequent payoffs under each economic condition. The decision tree reveals the structure of the problem, illustrating all possible pathways and outcomes, and serves as a foundation for calculating expected values.

Calculation of EMVs and Investment Decision

The core of the analysis involves calculating the expected monetary value (EMV) for each decision option. When the company does not hire the analyst, the EMV is computed by multiplying each payoff with its probability under the respective economic condition. When the company hires the analyst, additional steps include calculating EMV for both positive and negative survey result scenarios, considering the survey’s cost, and updating payoffs accordingly. The probabilities of the survey results being positive or negative (i and k) are integrated into the analysis. The EMVs are then compared between hiring and not hiring to determine the most financially advantageous option. The results indicate whether the expected benefits of obtaining further information outweigh the costs involved.

Sensitivity Analysis and Probabilistic Impact

To understand the robustness of the decision, sensitivity analysis is performed on the probabilities associated with survey results. By varying the probability of positive survey outcomes within a plausible range, the analysis identifies the threshold at which the decision to hire or forego hiring the analyst changes. This is represented graphically via a sensitivity chart, which helps managers understand how uncertain elements influence the optimal choice. The critical probability at the crossover point informs strategic considerations, especially in evaluating whether investing in the survey is justified under certainty conditions.

Use of Decision Analysis Software and Final Recommendations

The application of decision analysis tools such as TreePlan facilitates a visual and computational approach to identifying the optimal decision. The software constructs a detailed decision tree incorporating payoffs, probabilities, and EMV calculations. The output confirms the quantitative analysis, supporting or challenging the initial findings. Based on the aggregated results, the report concludes with actionable recommendations: selecting the project with the highest EMV and assessing the value of hiring the analyst. Generally, if the EMV for hiring the analyst exceeds that without hiring, and sensitivity analysis shows stability across probability ranges, the company should proceed with engaging the analyst. Conversely, if the analysis indicates minimal benefit, the company should proceed without the survey.

Conclusion

Effective decision-making in real estate development under uncertain economic conditions requires a systematic approach to evaluating payoffs, incorporating additional information through surveys, and analyzing the probabilistic impacts on expected profits. The combination of payoff tables, decision trees, EMV calculations, sensitivity analysis, and decision support software provides a comprehensive framework for making informed strategic choices. The final recommendation hinges on whether the benefits of further information justify the costs, considering the probabilities of survey outcomes and their impact on project profitability.

References

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