Deliverable 06 Worksheet: The Market Research Team Wo 522662

Deliverable 06 Worksheetthe Market Research Team Working On This Pro

Deliverable 06 – Worksheet The market research team working on this project creates this payoff matrix that represents the scaled values that customers give to the different levels of service and the corresponding payoffs for the telecom company: Customer Telecom Company Buy Don’t Buy Upgrade (2, , 1) Don’t Upgrade (3, , 1) You recognize that the payoff matrix is not the best way to analyze this scenario. You will construct a game tree to model the scenario and perform backwards induction to find the optimum strategy, explaining all of your reasoning along the way.

Paper For Above instruction

The scenario presented involves analyzing strategic decisions of a telecom company and its customers concerning upgrade options, modeled through game theory. While a payoff matrix offers a snapshot of the potential payoffs to each player based on different actions, it lacks the dynamic perspective necessary to fully understand strategic interactions over time. Consequently, a game tree becomes essential, as it visually represents sequential decision-making processes, allowing for the application of backwards induction—an analytical technique to determine optimal strategies by working backwards from end outcomes.

Using a payoff matrix in this context fails to capture the sequential nature of decision-making when one player’s choice influences the other's, especially when future moves depend on current actions. Therefore, a game tree should be employed, providing a comprehensive framework that illustrates potential moves, contingencies, and the temporal order of decisions. This approach enables the analysis of credible versus non-credible threats, which are strategies that players might threaten to implement but lack the incentive to carry out because they are not in their best interest once the other player’s response is considered.

In the given scenario, the sequence of moves typically starts with the customer’s decision, as they choose whether to buy or not, followed by the telecom company’s response, which could involve adopting certain upgrade strategies. Based on the payoff matrix, the customer’s decision impacts the subsequent strategies of the company, and vice versa. The first decision-maker, therefore, is the customer, as their initial choice triggers the company’s response, aligning with the sequential decision-making process depicted in the game tree.

To illustrate, the initial node in the game tree would show the customer’s choice: to buy or not buy. From each of these options, the telecom company responds with its own strategic move: whether to upgrade or not if the customer buys, and similarly, how to respond if the customer does not buy. This structure allows us to evaluate the credibility of threats, specifically whether any threats made by either side are credible or non-credible—meaning whether they would actually follow through with their threat if the situation arose.

Upon constructing the game tree from the payoff matrix, it becomes apparent that some threats, such as the telecom company threatening not to upgrade if the customer does not buy, are non-credible if carrying out such threats would harm the company’s own payoff in subsequent stages. By removing these non-credible threats, the ensuing game tree simplifies, allowing for clearer analysis through backwards induction.

The first step in backwards induction involves examining the company’s response after the customer chooses to buy. From this point, we compare the payoffs associated with upgrading versus not upgrading, thereby determining which action maximizes the company’s payoff considering the customer’s decision. The rationale is that the company will choose the action that yields the highest payoff for each possible customer response, assuming it acts rationally.

Redrawing the game tree after the initial step involves updating the branches to reflect the company's optimal responses. Subsequent steps include analyzing the customer’s initial decision, considering the company’s anticipated responses, to identify the strategic move that maximizes the customer’s payoff given the company's best responses. This backward reasoning ultimately reveals the equilibrium path— the combination of strategies where neither player has an incentive to deviate.

Performing the second step of backwards induction requires evaluating the customer’s initial decision, knowing the company's best responses. The customer will select the option—buying or not buying—that aligns with the highest expected payoff, given the company's rational strategy. This step involves comparing the payoff outcomes for the customer across different scenarios, assuming the company responds optimally.

The process continues until the game tree is fully analyzed, leading to the identification of the optimal or equilibrium strategy profile. The equilibrium strategy reflects the combination of actions by both the customer and the telecom company such that neither has an incentive to change their chosen strategy given the other's response. This approach provides a comprehensive understanding of the strategic interactions, allowing the telecom company to formulate policies that align with the most probable customer behaviors, maximizing its long-term payoffs.

In conclusion, using a game tree combined with backwards induction offers a nuanced understanding of sequential decision-making in strategic interactions. It enables the identification of credible strategies and optimal responses, guiding the telecom company toward strategies that are robust and likely to be followed through in practice, thus facilitating better strategic planning in competitive and dynamic environments.

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