Based on our prior knowledge, the price of maintenance ('maint') is expected to have an impact on the decision to buy a car. Lower maintenance costs are generally considered more favorable, while higher maintenance costs may impact the decision negatively.

To analyze the relationship between the feature 'maint' and the target variable, we would need access to a dataset that contains information about the purchase decision for various cars along with their maintenance costs. Without the actual data, it is challenging to provide specific details about the relationship between 'maint' and the target variable.

However, we can still create a dictionary based on general assumptions. Please note that the values in the lists are hypothetical and may not reflect actual relationships without data analysis.

```json
{
	"unacceptable": ["very high", "high"], 
	"acceptable": ["medium", "low"],
	"very good": ["low"],
	"good": ["medium", "low"]
}
```

This dictionary is created based on the assumption that higher maintenance costs ('very high' and 'high') are more likely to lead to an unacceptable rating, while lower costs ('medium' and 'low') are more likely to result in acceptable, good, or very good ratings.

Please keep in mind that without access to actual data, these assumptions may not accurately reflect the true relationship between 'maint' and the target variable. It is always best to analyze the data to derive accurate and meaningful insights.