Generic filters
Exact matches only
Filter by content type

Marius Schmid

Wissenschaftlicher Mitarbeiter
Büro 52-6150
Müller-Friedberg-Strasse 8
9000 St Gallen
+41 71 224 3800


Firms struggle to meet dynamically changing customers’ needs. One challenge is to navigate a complex search space to find resources needed for innovations that meet customers’ needs. Another challenge is to acquire the resources at lower costs than revenue opportunities to yield profitability. Digital platforms promise to address these challenges better than the market by providing search matching capabilities and modular, reusable resources. We examine whether platforms improve innovation performance and profitability of firms better than the market, as assumed. Using agent-based modeling and simulation, we find that firms perform better in the market when environmental complexity is low. As environmental complexity increases, firms start to perform better on the platform than in the market, specifically when the platform owner remarkably invests in search matching and modularity capabilities. The study advances our understanding of the environmental conditions under which platforms could be superior or inferior to the market.

In the context of digital platforms, platform owners strive to maximize both their platform’s stability and generativity. This is complicated by the paradoxical relationship of generativity and stability, as well as associated tensions. To aid B2B platform owners in their design decisions, we aim to derive specific design principles that address the inherent tensions such that generativity and stability are maximized simultaneously. This requires a better understanding of when and to which extent a platform’s generativity and stability are paradoxical, and under which circumstances they can be maximized simultaneously. Thus, we first develop an agent-based simulation model to analyze the effects of an exemplary design decision regarding a tension (i.e. control vs. openness) on a platform’s generativity and stability. The developed simulation model enables predictive analyses of varying degrees of control and openness and their effect on generativity and stability. The simulation model must be further refined and applied to other tensions to thoroughly understand the impact of design decisions on a platform’s generativity and stability, and ultimately derive design principles.