The threshold correction factor value is usually advised to tune last , after you test all the different combination of threshold strategy and method .
Global > Otsu > Two classes
Global > Otsu > Three classes (middle class assigned to Foreground/Background)
Adaptive > Otsu > etc. etc…
Only whence you really need to perfect the object segmentation, you would need to change the correction factor. Leaving it at 1 would most often be more robustly applicable to different sets of images (i.e. not to “overfit” to just one image)