This paper discusses the issue of modularity from a problem-solving perspective. Modularity is in fact a decomposition heuristic, through which a complex problem is decomposed into independent or quasi-independent sub-problems. By means of a model of problem decomposition, this paper studies the trade-offs of modularity: on the one hand finer modules increase the speed of search, but on the other hand they usually determine lock-in into sub-optimal solutions. How effectively to balance this trade-off depends upon the problem environment and its complexity and volatility: we show that in stationary and complex environments there exists an evolutionary advantage to over-modularization, while in highly volatile – though “simple” – en- vironments, contrary to usual wisdom, modular search is inefficient. The empirical relevance of our findings is discussed, especially with reference to the literature on system integration.
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Paper provided by University of Sussex, SPRU - Science and Technology Policy Research in its series SPRU Electronic Working Paper Series with number
123.
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