  The aim of this paper is to propose a new method to identify main paths in a
technological domain using patent citations. Previous approaches for using main
path analysis have greatly improved our understanding of actual technological
trajectories but nonetheless have some limitations. They have high potential to
miss some dominant patents from the identified main paths; nonetheless, the
high network complexity of their main paths makes qualitative tracing of
trajectories problematic. The proposed method searches backward and forward
paths from the high-persistence patents which are identified based on a
standard genetic knowledge persistence algorithm. We tested the new method by
applying it to the desalination and the solar photovoltaic domains and compared
the results to output from the same domains using a prior method. The empirical
results show that the proposed method overcomes the aforementioned drawbacks
defining main paths that are almost 10x less complex while containing more of
the relevant important knowledge than the main path networks defined by the
existing method.
