Deliverable 06 Worksheet: The Market Research Team Wo 695704

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. Slide 1 · Explain why a game tree must be used in this scenario instead of a payoff matrix. · Identify who will go first in the game Slide 2 · Draw the game tree that represents the scenario using the payoff matrix given above. · Identify and explain any non-credible threats. Slide 3 · Redraw the game tree with any non-credible threats removed. · Identify and explain where the first step of backwards induction will occur. Slide 4 · Using the game tree from slide 3, perform the first step of backwards induction. · Explain your reasoning behind the step you took. Slide 5 · Redraw the game tree after the first step of backwards induction. · Identify where the next step of backwards induction occurs. Slide 6 · Using the game tree from slide 5, perform the next step of backwards induction. · Explain your reasoning behind the step you took. Slide 7 · Redraw the game tree after the step you took in slide 6. · Identify the optimum strategy of the game.

Paper For Above instruction

In strategic decision-making scenarios involving interdependent choices between a customer and a telecom company, the use of a game tree provides a more comprehensive analysis than a simple payoff matrix. This is because payoff matrices depict the potential outcomes for each player simultaneously but do not account for the sequential nature of decisions or the credibility of threats. A game tree, on the other hand, visualizes the sequence of moves and allows for the application of backward induction to identify optimal strategies based on credible threats and rational decision-making.

The primary reason a game tree must be used here is that it models the sequential decisions of the players, which is essential for understanding the strategic interactions accurately. The payoff matrix provided suggests that the customer has two options—Buy or Don’t Buy—and the telecom company can choose to Upgrade or Not. However, the sequence in which these decisions are made can significantly influence the outcome. For example, if the telecom company moves first by choosing to upgrade, the customer then responds by deciding whether to buy or not, based on the perceived value of the upgrade.

In this scenario, the first player to move is typically assumed to be the telecom company, as they decide whether to upgrade initially. This is because the company's decision to upgrade or not influences the customer's subsequent choice, making the firm the first mover in the strategic interaction.

To illustrate this scenario, the game tree begins with the telecom company's decision node, where it chooses either to upgrade or not. If the company upgrades, the customer then chooses between buying or not, with payoffs depending on these combined decisions. Conversely, if the company chooses not to upgrade, the customer’s options might be limited or less advantageous, reflected in the payoffs.

When drawing the game tree from the payoff matrix, it is essential to identify any non-credible threats. For instance, if the telecom company threatens to upgrade only if the customer does not buy, but upon discovering that such a threat would not maximize their payoff, that threat is non-credible and should be eliminated from the analysis. Ensuring only credible threats remain is crucial for accurate backward induction.

Removing non-credible threats simplifies the game tree, making it easier to perform backward induction. The first step of backward induction occurs at the customer’s decision node, where they evaluate the payoff from buying or not, given the company's move. The customer will choose the option with the higher payoff, provided it is credible.

Applying backward induction, the customer’s decision is analyzed first. Suppose the customer prefers to buy if the upgrade occurs only when it yields a higher payoff, such as 3, compared to not buying or the other strategies. The telecom company, anticipating this, will select the strategy that leads to the most favorable outcome based on the customer's response.

After performing the first backward induction step, the game tree is redrawn to reflect the customer’s optimal response. The next step involves the telecom company choosing its initial move (whether to upgrade or not), considering the customer’s best response. This process continues until the game tree reflects the optimal strategies for both players.

The process of backward induction ultimately reveals the equilibrium strategies: the options that rational players would choose, considering the other's best responses. The telecom company's optimal strategy, in this case, might be to upgrade if the anticipated payoff from customer purchase outweighs the cost or risk involved, or to refrain from upgrading if the response does not justify the expense.

In conclusion, using a game tree coupled with backward induction provides a structured approach for analyzing sequential decision-making scenarios. It ensures that strategies account for credible threats and best responses, leading to rational choices for both the telecom company and the customer. This method offers a clearer understanding of strategic interactions than the more static payoff matrix alone, allowing firms to optimize outcomes based on rational decision-making processes.

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