Modularity and incremental innovation: the roles of design rules and organizational communication

Abstract

As little attention has been paid to the relationship between modularity and near decomposability, extant studies have not unveiled the impact of modularity on incremental innovation completely. We argue that the modular structure is a special case of nearly decomposable structure, in which the interdependencies between modules are specified by design rules, and the degree of modularity is defined by the level of near decomposability and the extent to which intermodule dependencies are specified. The results of our simulation experiments show that in the term of near decomposability, the increase of modularity leads to higher innovation advantage in the short term, but effective communication between modules can help systems with moderate and low modularity gain more innovation benefits in the long term; in the aspect of design rules, modularization may restrict the search space of the incremental innovation within each module, but under some conditions the option value of modularity may offset or even exceed the restriction effect of design rules.

Usage of Agent-Based Modeling and Simulation in Marketing

“…This search resulted in 141 publications, by taking into consideration their abstracts 89 of them found as irrelevant. [7], [8], [9], [10] Consumer Behavior 7 [11], [12], [13], [14], [15], [16], [17] Delivery 9 [15], [18], [19], [20], [21], [22], [23], [24], [25] Digital Rights Management 2 [26], [27] E-Commerce 3 [24], [27], [28] Innovation 16 [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [ [34], [58] In fact, all articles were carefully screened to meet two criteria:…”

“…Also we can group innovations as radical and incremental innovations. Reference [36] examined radical innovation their paper while Reference [37] examined modularity and incremental innovation. Reference [38], [39], and [40] modeled innovation diffusion.…”

Parametric interdependence, learning-by-doing, and industrial structure

“…Therefore, researchers frequently identify classes of relevant landscapes and use stochastic simulation techniques to generate thousands of landscapes within each class (see Auerswald 2010;Auerswald et al 2000;Frenken 2006;Kauffman et al 2000;Lobo and Macready 1999;Zhang and Gao 2010).…”

“…1 The proposition that NK landscapes can represent a technology landscape, a strategy landscape, or the contours of the "firm's problem" is widely applied in the literature (cf. Almirall and Casadesus-Masanell 2010;Auerswald et al 2000;Fang et al 2010;Frenken 2006;Frenken and Nuvolari 2004;Gavetti et al 2005;Ganco and Hoetker 2009;Kauffman et al 2000;Kollman et al 2000;Lenox et al 2007;Levinthal 1997;Lobo and Macready 1999;Lobo et al 2004;Marengo et al 2000;Rivkin 2000;Rivkin andSiggelkow 2002, 2005;Zhang and Gao 2010). NK landscapes are also frequently used as a model of team interaction (cf.…”

“…There has been prior work considering the impact of parametric interdependencies on learning-by-doing (cf. Auerswald 2010; Auerswald et al 2000) and incremental innovation (Zhang and Gao 2010). However, prior work in this area has not addressed the socially optimal industrial structure, nor has it addressed the optimal level of spillovers.…”