Patrick Cogez

Platform Emergence in Double Unknown (Technology, Markets): Common Unknown Strategy

The proposed chapter deals with platform emergence in double unknown situations when technology and markets are highly uncertain. The interest in technological platform development to enable creation of products and processes that support present and future development of multiple options is widely recognized by practitioners and academics. The existing literature considers that platforms already invented and the development is mostly based on exploiting this common platform core to build future markets and technological derivatives. However, when we are in double unknown situations, markets and technologies are highly uncertain and neither market options, nor platform cores are known. Thus, how to start an exploration? How can one ensure platform emergence in double unknown? What are the market and technology conditions that lead to different strategies of platform emergence? To answer these questions, we formally describe identified strategies and fabricate simple economical model to compare them. We illustrate the insights of the model through a case study of innovative technology development in semiconductor industry. Our results allow for better understanding market and technological conditions that allow for minimization of risks and exploration costs in double unknown and exploration costs in double unknown. Following the principle of value creation across various applications, this work extends the comprehension of generic technology design in double unknown.

Industry-wide technology roadmapping in double unknown — The case of the semiconductor industry

Many companies face today a dilemma of “double unknown” when deciding where to put their research dollars: ignorance of which one among many possible technologies is most likely to emerge and similar ignorance of which one among many possible applications will most likely be a driver for the technology. Generic technologies are widely recognized to be beneficial for various market applications ([Bresnahan, Trajtenberg, 1995]; [Maine, Garsney, 2006]) and recent research results show that double unknown can lead companies to organize design activity to develop generic technologies suitable for several emerging markets application [Kokshagina, et al. 2012a]. However, the investigations so far focused on the level of the individual firm, while a “double unknown” situation is typically characterizing an industrial sector as a whole. This is in particular the case of the semiconductor industry: While the International Technology Roadmap for Semiconductors (ITRS) primary focus has been and still is the continuation of Moores law, it introduced recently the “More than Moore” concept, to account for technologies which do not necessarily follow the CMOS miniaturization trends, and represent a growing part of the total silicon-based semiconductor market. The sheer diversity of both those technologies and their potential applications renders a roadmapping exercise very challenging. Nevertheless, given the benefits that roadmapping has brought to the semiconductor industry, the International Roadmap Committee (IRC) of the ITRS has decided to extend its activities to this new field. Which strategies do the ITRS experts implement to select which technologies to roadmap and which applications to target in double unknown? In this paper, we show that to design roadmaps for More than Moore technologies, the ITRS experts apply a strategy of “common unknown” [Kokshagina, et al. 2012a], along with additional community building activities specific to the situation of inter-firm collaboration.

Absorptive capacity for radical innovation: A case study in the semiconductor industry

Absorptive capacity is one of the most important constructs to emerge in organizational research in recent decades for gaining insight into the link between knowledge and innovation. In 1989, Cohen and Levinthal analyzed the role of R&D in this context and distinguished “information generation” and the “ability to assimilate and exploit existing information” for innovation purposes [5]. They proposed a model of this second, less recognized capacity. They define Absorptive Capacity (AC) as the organizational capability to organize value and assimilate external knowledge in order to increase firm innovativeness. They assume that AC is a dynamic capability that depends on prior related knowledge in the form and combines value recognition of the missing knowledge, its assimilation and application.