Optimised Modular Design Study For Complex Systems By Considering Coordination Costs

Over the last decade, the concept of modularity has caught the attention of engineers, management researchers and firm decision-makers in a number of industries. Modularity is generally used as a design strategy by companies developing such complex systems as computers and software systems. Using standardized and specified components to support mass customization and rapid development may increase the cost of coordination. Although there has been a considerable set of contributions to modularity over the last decade, few has devoted to the issues that the optimal level of modularity poses in considering coordination costs.In this paper, we formulate a quantitative modularity profit model based on real options and coordination theory to analyze the optimal modular design policy that simultaneously decides the optimal number of modules, and the optimal number of substitutions per module. In addition, we develop an effective search procedure with polynomial complexity to solve the model.Three key findings are that: (1) In an expensive test and integration environment, it's optimal for an organization to divide a system into fewer modules and run fewer experiments on each, and further reduce the number of independent parallel design when unit coordination cost is high; (2) In a sophisticated test and integration environment, the optimal splitting policy depends on coordination factors such as ex-ante coordination effectiveness and bug-fixing cost, but the optimal substitution policy only depends on unit design cost; (3) Finally, when the cost per standard test and the cost per integration are both between the low value and the high value, splitting decision depends on a subset of the factors listed in the second situation. Furthermore, substitution decision depends on the design cost per design decision and a factor among the coefficient of variable design cost and the fixing cost coefficient.