Merge two models - Keras
Generally, I'd say its the same way as finding your "best" feature list, pre-processing methods and algorithm - you'd find most answers starting with "give it a try and compare", "check which combination gives you a better cross-validation?" etc..

More specifically, when there is no farther documentation (and its an open source project) I usually take a look at the code for more intuitions.

In this case concat, dot, average and the like where strait forward implemented as it sounds (concatenating date, averaging, etc..), but it does imply about the amount of processing needed: some of the merging functions adds to the input needed to be processed (concat, add) and some reduces it like an aggregation function (average, min, max)

Beyond that the resulted tensor object will perform a bit different for different datasets. Please give it a try and let us know what merging combination worked best for you, and the dataset type :)