Balancing the power of global network and the power of local/asset knowledge

Publication Type:

Conference Paper


Gerpisa colloquium, Paris (2019)


The purpose of this exploratory research is to see how business firms seek for balances between the power of global network effect and that of specific local/asset knowledge in the era of “paradigm-shift.”  It argues that, while the logic of global cumulative network effects help platform-leading firmsincrease demand-supply matching efficiencies and asset utilization ratios when the system in question is weight-free and architecturally open-modular, specific asset/local knowledge that the firms possess may becomemore important when the network deals with artifacts or local systems that are complex, physical, architecturally closed/integral, and thus difficult to control. This logic may lead to the following practical implication: When a global firm excessively dependsupon the power of the aforementioned network effect, deemphasizing the specific asset/local knowledge, itmay face strategic difficulty vis-à-vis its local or physical-manufacturing competitors when it enters into a new businesses or regions that are occupied by such complex artifacts or systems.  
Methodology and Concepts
As this is an exploratory research on dynamic industrial phenomena, the authors use comparative case studies for hypothesis generation. We use such concept as open/closed architectures, cumulative network effects (network externality), asset/local knowledge, complexity of artifacts/systems, weight-free or weighty artifacts, etc., as well as an analogical model of high-sky, low-sky and ground, for analyzing the abovementioned theme.  
The paper applies these concepts and logic to such cases as GE and Siemens in digital manufacturing, Uber and Asian local competitors (Grab, etc.), as well as Google/Apple and the major automakers in the area of infotainment and autonomous driving, where ourframework of balancing the network power and asset/local knowledge may be applied reasonably effectively.  In the field of digital manufacturing, for example Siemens carefully acquired asset-specific knowledge in such areas as PLM, CAD and MES, and has been growing and profitable particularly in Chinese market, while GE might have overemphasized the power of generic network effects at the initial stage of its entrance into the platform business. The same logic may be applied to Uber, with global networking power, versus its Asians rivals with local knowledge on low cost MaaS operations. 
Business firms in the era of digitization and paradigm shifts to platform competition should still consider the power of specific local/asset knowledge when they build their business models for complex artifacts or systems. A naïve assumption that the “winners-take-all” effect always happens in the era of platform competition may mislead the firms’ competitive behaviors, particularly where the products in question are physically complex goods or services that deal with complex human interactions.    

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