This study takes initial steps to understand why 47% of companies creating Radically New Technological Innovations fail before reaching large scale diffusion and how to prevent such failures. This was achieved by integrating Ortt’s (2010) evolution model—which states that an innovation passes through a development and adaptation phase before reaching large-scale diffusion—with the Technological Innovation System framework, which emphasizes that an innovation encompasses more than just its technical features. These combined theories were then analyzed using the System Dynamics Modelling approach. The main question in this process was: “How can we develop a System Dynamics Model that accurately portrays the interactions among elements within the Technical Innovation System, shedding
light on the system’s behavior across different phases and identifying factors hindering the progression of the adaptation into the diffusion phase?"

To answer this question, we developed a method, a model depicting the interactions between the TIS-factors, a theory on transitions between phases, and a simulation model demonstrating the influence of certain factors on these transitions. The developed method is based on synthesis, in which theories on the factors within the TIS, namely customers, price, performance, production, networks, institutions, and complementary products and services, are combined into one coherent framework. This framework acts as a hypothesis, outlining the variables that make up the factors and defining their interrelations. From this hypothesis, a conceptual and a simulation model can be built which can be validated using expert interviews and experimentation. Using this method, we built a conceptual model that maps the variables and their relationships, while also clearly stating its assumptions. Through evaluating this model, we identified customers, production, networks, and complementary products and services as potential drivers in the system.

Additionally, we found that growth in legitimacy and R&D can have both positive and negative influences on the system, depending on how other factors develop. To understand how the TIS is first adapted and then reaches large scale diffusion, a theory on market transitions was designed. Here we hypothesized that the adaptation and diffusion phases are really a series of heterogeneous markets that are characterized by different demand preferences. Initially, during the adaptation phase, these are niche markets, while in the diffusion phase, the innovation can enter larger and more demanding main markets. Additionally, we proposed three pathways for an innovation to transition from one market to another: first, by evolving its TIS to align with the market’s demand preferences, which is often essential in main markets; second, when demand preferences shift to match with the TIS, typically seen in smaller niche markets; and third, when both demand and the TIS evolve to better align.

Lastly, our goal was to begin to identify which elements are crucial in market transitions. To achieve this, we constructed a simulation model that illustrated the interaction between standardization and potential shifts in demand preferences. The variable Standardization is grounded in the assumption derived from the conceptual model that, given enough time, all TISs will produce a standardized product. Our findings indicate that when entering a market, having a high level of standardization is essential to achieve high-level diffusion, particularly in markets focused on a developed TIS. Conversely, to prevent low diffusion levels, it is important to enter the market only when the product is favored by consumers, especially in markets determined by external demand preferences; additionally, low standardization should also be avoided.

In conclusion, the synthesis method created here can be used to indicate what elements are essential in enabling or hindering the progression from the adaptation to the diffusion phase. Initial conclusions indicate that there are several drivers and potential hindrances within the system and that both standardization and shifting demand preferences can greatly impact possible transitions, depending on the specific characteristics of the market.
As these are the first steps in a long line of research, there is so much more to be done. For this it might seem obvious to only look to the future and aim to design more specialized conceptual models, or a simulation model that encompasses all elements. However, I also want to invite you to look to the past and see how this study can be used to clarify the theories and methods that form its foundation.