I'm not an evangelist for JSON, I'm someone who ran tests and came to conclusions with the help of multiple others. These weren't a generic benchmark for random or general academic purposes. These were representative samples of datasets we're actively going to be or actually are already using.
Even in my other interests I'm using JSON for configuration and data transfer. It shines there quite nicely. XML was generally suitable but its verbosity didn't provide any real advantage and the library support tried to drag in too many dependencies. TSV files weren't suitable even though they were simpler and we had control of the data sources.
You mention Java / Javascript but neither is what we're using. There's probably some irony in not using javascript for JSON i/o but it is what it is. (The purists will agree there's no requirement and so do we). You also didn't mention in passing any of the other interchange / file and document formats we actively compared. JSON / XML etc were just some of the candidates.
Thank you for letting me know that the teams I work with demonstrate "lack of experience". I've forgotten which logical fallacy that is but I'll leave that to someone else to know or look up. I'm just glad I've kept beginner's mind: its a key aspect of neuro-plastic mindset. Its a requirement for keeping an open mind.
We won't be ignoring our testing on real data subsets. The results are clear enough.
(The samples we tested with were around 5MB, 50Mb, 1GB, 10GB and 50GB in size as various combinations of lists and trees etc.)