Product platforms are assets shared by multiple products. Their primary purpose is to offer product variety while keeping time-to-market and operational costs down. As new products are developed over time, the question arises when to replace a platform. The repetitive use of the same platform for multiple product generations keeps platform development time and costs low. As the platform gets obsolete, however, the time and efforts to adapt the platform to the newest product will go up. With these dynamics in mind, we develop a simulation model to gain insight into the desired platform replacement planning. We examine how platform replacements are impacted by a firm's performance objectives, the speed of innovation, and the competitive landscape.

Companies increasingly face the need for transformation in today’s rapidly changing business environment, characterized by major shifts in technology, regulation, and customer behavior. A lack of strategic risk insight and foresight leaves many incumbents insufficiently prepared in the face of such deep uncertainty. We argue that traditional risk management falls short because it predominantly focuses on strategy execution while leaving strategy formulation largely untouched. Moreover, an administrative-heavy risk management process can create strategic inertia and a misleading sense of control. In today’s dynamic business context, companies must not only increase the speed and impact of their strategy execution but also continuously explore the development of new strategies in response to disruptive events or emerging opportunities. Our research shows how leading companies develop a strategic risk management (SRM) capability to increase their resilience and agility in response to deep uncertainty. SRM takes a strategic, forward-looking perspective and focuses on strengthening processes, people, and practices for purposefully integrating risk into the strategy formulation process. This article offers a framework with three proven configurations of content and timing integration, risk management roles, and leading practices that enable effective SRM.

There is no single right answer as to which model might be most appropriate for assessing the impact of Maker initiatives. Instead, we discuss the different parameters that are relevant for choosing the appropriate SIA model and provide a matrix of 69 SIA models with their respective approaches and parameters in this dataset and in deliverable D6.2. See also: http://make-it.io/open-data-api/

The interplay between innovation and the stock market has been extensively studied by scholars across all business disciplines. However, one phenomenon remains understudied: the association between innovation and stock market bubbles. Bubbles—defined as rapid increases and subsequent declines in stock prices—have been primarily examined by economists who generally do not focus on individual characteristics of innovations or on the consequences of bubbles for their parent firms. We set out to fill this gap in our paper. Using a sample of 51 major innovations introduced between 1825 and 2000, we test for bubbles in the stock prices of parent firms subsequent to the commercialization of these innovations. We identify bubbles in 73% of the cases. The magnitude of these bubbles increases with the radicalness of innovations, with their potential to generate indirect network effects, and with their public visibility at the time of commercialization. Moreover, we find that parent firms typically raise new equity capital during bubble periods and that the amount of equity raised is proportional to the magnitude of the bubble. Finally, we show that the buy-and-hold abnormal returns of parent firms are significantly positive between the beginning and the end of the bubble, suggesting that these innovations add value to their firm and to the economy, in spite of the bubble. Our findings have important implications for managers interested in commercializing innovations and for policy makers concerned with the stability of the financial system. Data and the online appendix are available at https://doi.org/10.1287/mksc.2018.1095 .

Maker technologies, including collaborative digital fabrication tools like 3-D printers, enable entrepreneurial opportunities and new business models. To date, relatively few highly successful maker startups have emerged, possibly due to the dominant mindset of the makers being one of cooperation and sharing. However, makers also strive for financial stability and many have profit motives. We use a multiple case study approach to explore makers’ experiences regarding the tension between sharing and commercialization and their ways of dealing with it. We conducted interviews with maker initiatives across Europe including Fab Labs, a maker R&D center, and other networks of makers. We unpack and contextualize the concepts of sharing and commercialization. Our cross-case analysis leads to a new framework for understanding these entrepreneurs’ position with respect to common-good versus commercial offerings. Using the framework, we describe archetypal trajectories that maker initiatives go through in the dynamic transition from makers to social enterprises and social entrepreneurs.