Dominant design, Innovation, Expectations, Prototyping, Hydrogen, and Automotive industry

The notion of dominant designs refers to dominance in the market, hence the literature on dominant designs ignores the selection process that already takes place in pre-market R&D stages of technological innovation. In this paper we address the question to what extent pre-market selection takes place within an industry and how this may lead to dominance of one design over others before the market comes into play. Furthermore we study what selection criteria apply in the absence of actual market criteria. We do so through a historical analysis of design paths for hydrogen passenger cars.

Consumer innovation, Personality, Diffusion, Product solution, and User innovation

Via a study of innovating and non-innovating German consumers, we explore links between the “Big Five” personality traits and successful accomplishment of three basic innovation process stages by consumer-innovators: (1) generating an idea for a new product or product improvement, (2) developing a prototype that implements that idea, and (3) diffusing the innovation to others. We find that personality traits are significantly associated with success differ at each stage. First, those who score higher on openness to experience are significantly more likely to have new product ideas. Second, being introverted and conscientious is significantly associated with successful prototyping. Third, those who possess high levels of conscientiousness are more likely to successfully commercially diffuse their innovations, whereas, in contrast, conscientiousness lowers the likelihood of successful peer-to-peer diffusion.

Specialists of different domains have to collaborate whenever technically demanding product innovations are developed. Their respective knowledge contributions need to be integrated into a functioning whole. Two approaches provide insight into how this is achieved: the dominating cross-learning approach assumes that the specialists of different knowledge domains have to intensively learn from each other in order to be able to jointly develop the new product. This cross-learning implies that groups of specialists transfer their specific knowledge, which encompasses different concepts (theories), methods and world views, among each other. However, some researchers argue that intensive cross-learning between specialists is a considerable expense in time and effort and, therefore, inefficient. They insist that integration of specialists' knowledge is achieved through structural mechanisms that significantly reduce the need for cross-learning. This article is based on one of the latter approaches. We argue that the mechanisms of transactive memory, modularization and prototyping in combination can considerably reduce knowledge transfers. This assumption has found empirical support for incremental innovations. On the basis of a comparison between incremental and radical innovation projects in an electrotechnical company, we analyze whether the assumption that, on the basis of structural mechanisms, specialists can integrate their knowledge without having to intensively learn from each other, also holds for radical innovations.

Specialists of different domains have to collaborate whenever technically demanding product innovations are developed. Their respective knowledge contributions need to be integrated into a functioning whole. Two approaches provide insight into how this is achieved: the dominating cross-learning approach assumes that the specialists of different knowledge domains have to intensively learn from each other in order to be able to jointly develop the new product. This cross-learning implies that groups of specialists transfer their specific knowledge, which encompasses different concepts (theories), methods and world views, among each other. However, some researchers argue that intensive cross-learning between specialists is a considerable expense in time and effort and, therefore, inefficient. They insist that integration of specialists' knowledge is achieved through structural mechanisms that significantly reduce the need for cross-learning. This article is based on one of the latter approaches. We argue that the mechanisms of transactive memory, modularization and prototyping in combination can considerably reduce knowledge transfers. This assumption has found empirical support for incremental innovations. On the basis of a comparison between incremental and radical innovation projects in an electrotechnical company, we analyze whether the assumption that, on the basis of structural mechanisms, specialists can integrate their knowledge without having to intensively learn from each other, also holds for radical innovations.