Similar to Kuhnian notions of scientific progress (Kuhn, 1970), technological development is known to take a staged trajectory. A new technology, by definition, implies a radical departure from past practice (Abernathy and Clark, 1985). Therefore, in its early stages of development, the economic prospects and utility of a new technology are not fully revealed to the industry players. Before a dominant design appears,
investment in the manufacturing process is suppressed because of uncertainty and risk in commercialization, and firms compete for design and industry standards. Once a
dominant design emerges, the field of technology is populated with a myriad of
incremental innovations that address small technical problems. In this stage, competition shifts from design to manufacturing efficiency. This picture is repeatedly supported by the advocates of technology evolution (Abernathy and Clark, 1985; Dosi, 1982;
Henderson and Clark, 1990; Tushman and Anderson, 1986; Utterback, 1994). A common prediction from this lineage of theoretical explanations is that, as a dominant design appears in a technology field, technological uncertainty decreases, the field is populated with many incremental innovations, utility and demands for the technology are widely recognized among firms, and manufacturing processes and facilities are standardized.
We argue that the overall characteristics of technologies in their post-dominant design era constitute a selection environment in which the odds of commercializing a particular technology are higher. Nelson and Winter (1982) proposed four elements that affect the selection environment of technological advancement: 1) the nature of the benefits and costs that are weighed by the organizations that will decide to adopt or not to adopt a new innovation; 2) consumer preferences and institutional environments that affect
profitability from innovation; 3) prospects of profit growth; and 4) the difficulty of imitation and learning effects. These elements should vary, more or less, by industry sectors and individual firm characteristics. However, apart from sectoral heterogeneity, increased levels of familiarity with technology and well-established demands and supplies of complementary technologies, which are a defining characteristic of the post- dominant design stage of technology evolution, would constitute a favorable selection environment for a member technology. This argument is particularly related to the first and the last element of Nelson and Winter’s selection environment. First, if there is a well-populated group of users or developers for a technology, an innovator in that
technology area benefits from monitoring others about which innovations perform well or poorly (Nelson and Winter, 1982). The learning effects occur both at technological (Wade, 1995) and organizational dimensions (Abrahamson, 1991; Hannan and Freeman, 1977). Second, a large population of components in a technology will reduce the costs of implementing a similar technology. If adoption of a technology goes beyond a certain point, complementary factors required for adopting it will be readily available to the innovator. The complementary factors include organizational routines, skills,
complementary technologies, manufacturing processes, and others. Third, the well- populated technology area will have positive impacts on the innovators’ aspirations for the benefits. Albeit too simplistic, we argue that at least an established level of demands will favor adopting a technology.12 In his recent reflection on the original 1986 article, “Profiting from technological innovation,” Teece (2006) provides a refined view of the relationship of the emergence of dominant design with the profitability and
commercialization of innovation. Teece’s remedy for profiting from innovation in
technologies where a dominant design has not emerged is to wait until a dominant design emerges, unless the innovator has the capability to promote one. Our argument elaborates on Teece’s framework.
Besides the macroevolutionary aspects of technological development, emergence of a dominant design (or mature technology) influences the propensity to commercialize in a more nuanced way. According to transaction cost economics (Williamson, 1981), market transaction of technology will be suppressed when it involves more technological
uncertainty (Arrow, 1969; Oxley, 1997). When market transactions are either risky or costly, the innovator will face two options available for his existing patented inventions: 1) to integrate them into his own commercial applications or 2) if the first option is not appropriate, then to seek another option which includes just putting them on the shelf or using them for strategic purposes such as bargaining chips in cross-licensing negotiations or blocking competitors (Grindley and Teece, 1997; Hall and Ziedonis, 2001). The first option is a choice between two different modes of commercialization (or “within-
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However, this argument is incomplete unless the following aspects regarding firm-specific and invention- specific factors are not considered together: competitive environment, the amount of the benefits from innovation, and the uncertainty/risk involved in realizing the benefits.
effects”), which, resultantly, would not affect the overall propensity to commercialize. The second option is a choice between commercialization and non-commercialization (or “between-effects”). In a regime where technological uncertainty is high, the propensity to commercialize will decrease because of the between-effects. The between-effects are composed of, among others, plain nonuse (or “sleeping”) patents and strategic nonuse patents. All else equal, we postulate that otherwise commercializable (or licensable) patents are strategically exploited rather than put on the shelf. This is consistent with Merges’ views (1994) that technological uncertainty induces bargaining failure and results in blocking patents. The arguments developed here are first explored in this part and further examined with particular focus on strategic nonuse in Part III.
Some technology-based products are built on complex integration of technology components, while some other products are built on a relatively simple composition of technologies. Semiconductor or electronics goods typically integrate several hundreds to several thousands of technological components, many of which are complementary and cumulative. On the other hand, pharmaceuticals or agricultural goods are built on a relatively small number of technological components (Cohen, Nelson, and Walsh, 2000). In complex industry, utility and commercialization of a new technological component is determined in the relationship with other technological components and fitness with the final system. Introduction of a new technology cannot be instantly integrated into a commercial product because developing and optimizing with interfacing and complementary technologies will require a certain level of familiarity with that
technology. Therefore, familiarity with a technological component among the system builders will be more influential on commercialization in complex industry.