Which of the following forecasting methods relies on expert opinions?

The subjective model is characterized by its reliance on expert opinions and judgment rather than purely quantitative methods. This approach is often employed when there is limited historical data available or when the situation is unique and requires insights that cannot be captured by statistical methods alone. Experts may use their knowledge and experience to provide forecasts based on current trends, possible future events, or industry-specific dynamics.

In contrast, the moving average and exponential smoothing methods are both statistical techniques rooted in historical data analysis. The moving average smooths fluctuations by averaging past data points over a specific time period. Exponential smoothing also uses historical data but gives more weight to recent observations, making it responsive to changes over time.

Similarly, the causal model analyzes the relationship between variables using data, relying on established causative factors to predict outcomes. While this method uses historical data to establish connections, it does not depend on personal judgments or insights from experts, distinguishing it from the subjective model.

Thus, the subjective model accurately reflects the use of expert opinions as its foundational approach to forecasting.