Olga Kokshagina

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.

Gambling versus Designing: Organizing for the Design of the Probability Space in the Energy Sector

The objective of this paper is to elucidate an organizational process for the design of generic technologies (GTs). While recognizing the success of GTs, the literature on innovation management generally describes their design according to evolutionary strategies featuring multiple and uncertain trials, resulting in the discovery of common features among multiple applications. This random walk depends on multiple market and technological uncertainties that are considered exogenous: as smart as he can be, the ‘gambler’ must play in a given probability space. However, what happens when the innovator is not a gambler but a designer, i.e., when the actor is able to establish new links between previously independent emerging markets and technologies? Formally speaking, the actor designs a new probability space. Building on a case study of two technological development programmes at the French Center for Atomic Energy, we present cases of GTs that correspond to this logic of designing the probability space, i.e. the logic of intentionally designing common features that bridge the gap between a priori heterogeneous applications and technologies. This study provides another example showing that the usual trial-and-learning strategy is not the only strategy to design GTs and that these technologies can be designed by intentionally building new interdependences between markets and technologies. Our main result is that building these interdependences requires organizational patterns that correspond to a ‘design of exploration’ phase in which multiple technology suppliers and application providers are involved in designing both the probability space itself and the instruments to explore and benefit from this new space.

A New Perspective for Risk Management: A Study of the Design of Generic Technology with a Matroid Model in C-K Theory

Risk management today has its main roots in decision theory paradigm (Friedman and Savage, J Polit Econ 56:279–304, 1948). It consists in making the optimal choice between given possible decisions and probable states of nature. In this paper we extend this model to include a design capacity to deal with risk situations.