This is a more conceptual than practical question and is about exploratory cluster identification. While there are very specific meanings in the geography canon as to what they are, in economics they seem to be somewhat loosely defined, often following Porter's lead:
Clusters are geographic concentrations of interconnected companies and institutions in a particular field. Clusters encompass an array of linked industries and other entities important to competition. Porter, M. E. (1998). Clusters and the New Economics of Competition. Harvard Business Review, (November-December 1998), 77–90.
However, I am interested in specifics and formal definitions. I work in city plannning, and there is plenty of talk about cluster x or cluster y being in existence at place z, but I would like to pin it down more and have a data-driven, rather than policy-driven inventory of any and all clusters.
Specifically, assuming a point data set representing business establishments, weighted by their employment, and I am interested in exploring, rather than confirming pre-conceived ideas of which clusters may or may not exist, which GIS approach is best suited for identifying which industries might exhibit clustering at a given scale? Is this a Ripley's K case where each industry grouping would be passed separately, or is there a more appropriate approach in the exploration stage when it is not 'known' which industry levels might cluster (depending on how one aggregates the classes, there could be several hundred distinct industries).