One of the reasons I developed my own bike friendly city ranking system was to provide a better measurement when comparing cities. Since the League of American Bicyclists (LAB) uses a nominal ranking (Platinum, Silver, Gold, Bronze), the difference in bike friendliness between cities of the same rank may be small or great. A numerical scoring system on a predictable and familiar scale will better highlight the distance of one city to another on achieve that city’s level of bike friendliness.
I created a method that would compare my ranking to LAB’s ranking and that was to find the variance (which isn’t the same as range) in scores in my ranking for each nominal level in LAB’s ranking. Platinum cities had a very high variance and Bronze cities had the lowest variance. Gold and Silver had swapped positions: Gold cities had a lower variance than Silver cities.
The beauty with creating your own bike friendly measurement system is that you can make the outcome order whatever you want.
In the days since, I’ve developed another bike friendliness measurement system, one that’s easier to understand, whose rankings are still relative to other cities, and that can be weighted. (I’m emphasizing the bike commute mode share.) It uses percentile scoring so all scores are positive but still based on the distribution of values. I’ve listed the scores for Method 1 (which uses a normalizing function based on mean and standard deviation) and Method 2 below.[table “5” not found /]