Anticipating the emergence of radically new technologies poses significant methodological challenges due to high uncertainty surrounding their development and diffusion. Conventional forecasting approaches, which rely on stable relationships and historical data extrapolation, are often ill-suited to such conditions. This editorial examines how different anticipatory methods address uncertainty and what this implies for method selection in technology foresight. Drawing on four case studies—quantum technologies in healthcare, fusion energy, defense technologies, and the emergence of technology clusters—the special issue compares horizon scanning, scenario planning, Delphi-based expert elicitation, and computational weak-signal analysis. Using an emerging-technology framework that treats uncertainty as a defining and evolving attribute rather than a temporary knowledge gap, the editorial shows that method suitability depends on the nature and degree of uncertainty; the time horizon becomes meaningful only under specific uncertainty conditions. Foresight methods that structure exploration across multiple plausible futures remain applicable across uncertainty contexts, whereas forecasting is conditionally applicable and depends on predominantly epistemic uncertainty. The comparison further demonstrates that each method has structural limitations, underscoring the need for strategic combinations under higher uncertainty. By positioning uncertainty as the central organizing principle for methodological choice, this editorial contributes to futures and foresight research and offers guidance for designing anticipatory approaches that remain robust under radical uncertainty.

This study examines what technology-based startups treat as external triggers for initiating sustainable business model innovation (SBMI) through an interview-centered, comparative qualitative study of 31 sustainability-oriented startups in the Netherlands. The 46 semi-structured interviews conducted during 2023–2025 were complemented by archival material to develop a multilevel framework of external triggers. The analysis identifies seven trigger domains across two distinct levels. At the value network level, startups report customer and user adoption expectations for greener solutions, ecosystem gatekeeper and competitive pressures, impact-oriented finance and public funding conditions, and digital trust, traceability, and transparency requirements in procurement and inter-organizational exchange. At the institutional level, startups report clean-tech trajectories and socio-technical infrastructures, rules, standards, and compliance regimes, and societal climate and circularity norms shaping legitimacy climates and solution spaces. The findings show that SBMI initiation is not prompted by an undifferentiated set of generic environmental factors, but by structured multilevel triggers that impact startups through distinct ecosystem channels and prompt reconsideration of value creation, value delivery, and value capture.

Corporate Entrepreneurship units (CE units) are instrumental in driving innovation and change within established companies. However, these units are recurrently being subjected to downsizing or closure with minimal understanding of the underlying reasons. This conceptual study addresses this gap by drawing on three theoretical perspectives and three cases of closed German CE units to identify key reasons. These reasons and perspectives are then further integrated into a framework. In addition, overarching categories of reasons are derived using analytical concepts. These findings provide a basis for future research efforts that seek to investigate and explain CE unit closure, as well as novel insights into previously neglected managerial concepts for CE. Practitioners can utilize these findings to identify stumbling blocks that may prevent CE units from being closed.

The ability of innovation ecosystems to deliver desired economic output, particularly under conditions of uncertainty shaped by market shifts, competitive change, and regulatory pressure, concerns all ecosystem stakeholders. Understanding innovation ecosystem performance, therefore, emerges as an important topic for scholars, managers, and policymakers. The objective of this article is to propose a conceptual framework of ecosystem performance that builds on the inherent connection between system-level outcomes and the performance of all components that constitute the ecosystem. To this end, we apply a socio-technical lens to identify performance-deficient social or technical components known as “reverse salient” that influence the performance of the ecosystem as a whole. Our case study of a regional Australian food innovation ecosystem identifies numerous reverse salients that inhibit ecosystem performance as the system transitions from its current focus on high-quality produce to a future state characterized by increased output capacity and value-added offerings. We categorize these reverse salients as those associated with “actors” in the ecosystem, “connections” between actors, and “resources” flowing among them. While these categories align with the ecosystem-as-structure perspective, our findings additionally underscore the moderating role of ecosystem “leadership” and “rules of engagement” that can themselves act as reverse salients when misaligned. We present a conceptual model that integrates these insights and offer a set of propositions to guide future empirical research.

Organizational and political responses to strategic surprises such as the credit crunch in 2008 and the pandemic in 2020 are increasingly reliant on scientific insights. As a result, the accuracy of scientific models has become more critical, and models have become more complex to capture the real-world phenomena as best as they can. So much, so that appeals for simplification are beginning to surface. But unfortunately, simplification has its issues. Too simple models are so generic that they no longer accurately describe or predict real-world cause-effect relationships. On the other hand, too complex models are hard to generalize. Somewhere on the continuum between too simple and too complex lies the optimal model. In this article, the authors contribute to the ongoing discussion on model complexity by presenting a logical and systematic framework of simplification issues that may occur during the conceptualization and operationalization of variables, relationships, and model contexts. The framework was developed with the help of two cases, one from foresight, a relatively young discipline, and the other from the established discipline of innovation diffusion. Both disciplines have a widely accepted foundational predictive model that could use another look. The shared errors informed the simplification framework. The framework can help social scientists to detect possible oversimplification issues in literature reviews and inform their choices for either in- or decreases in model complexity.

The management of technology is increasingly fuelled by societal challenges and user problems. For effective technology development and implementation, it is important that both are relevant not only in the present, but also in the future. Technological development and implementation take time which means that a technology originally meant to address a particular societal challenge, may be no longer relevant at the time it is implemented because the challenge or problem may no longer exist. We call this ‘future technology myopia’. This myopia implies that while analysing the possible future development of a technology, sufficient vigilance should be given to the persistence of i). the technical challenge and ii). the development of the societal problem, and of alternative ways to deal with both. In view of the increasing interdependence between technology and society, broadening the technology management and analysis is therefore relevant for the effective development of technology to address future societal and user problems and for developing relevant strategic technology policies. In this paper we develop a Technology Management Ailment Matrix that identifies imbalances that might arise during the technology development process. It enables firms to identify and compare different technology management ailments collectively; it also identifies a further new ailment: future technology myopia.

Corporate Entrepreneurship (CE) has become an established tool to create discontinuous innovations for many established companies. Thus, they have started to implement multiple CE units in parallel. However, despite different positive effects potentially arising from the parallel use and purposeful coordination of CE units, managers and scholars alike have so far widely ignored such holistic perspectives. This study therefore wants to shed light on the effects the parallel use and coordination have on established companies' innovation performance. Following an explorative approach, it investigates quantitatively the relationships between the number of CE units as well as their heterogeneity (in terms of their forms) used by a company and companies' innovativeness. Further, it employs qualitative interview data to gain deeper insights into the effects. Interestingly, the results show that the mere number of CE units does not have a significant effect on the innovativeness, but that more heterogeneous sets of CE units do. This provides an argument for the strategic coordination and co-specialization of CE units in order to make use of positive effects associated with multiple CE units. The study thereby contributes both to Asset Orchestration theory and the CE literature and provides multiple managerial implications as well as different avenues for future research.

Technological innovations are becoming increasingly systemic in the complex and interconnected world. The initiation and evolution of systemic innovations take time and include numerous challenges, and the mechanisms through which systemic innovations emerge in the interaction between different technologies represent a research gap. This paper explores the emergence of ceramic additive manufacturing as an example of a systemic manufacturing technology innovation. We implemented an event history analysis of four ceramic-material additive manufacturing technologies. We traced the initiation and evolution paths of each of the four technologies over time and showed a pattern of activities within and across the technologies. The study contributes by revealing that systemic innovations emerge as a result of parallel and sequential development paths of within-technology system components as well as the interaction between multiple technologies. The timing of the coalescing development paths of the system components and technologies appears crucial but serendipitous instead of coordinated. The findings open new pathways for speeding up the emergence of systemic innovations and forthcoming research to support the evolution of additive manufacturing.

While Corporate Entrepreneurship (CE) units have become essential tools for creating new kinds of innovation within established companies, their performance measurement remains underexplored. With CE units, companies intend to contribute to new business and organizational transformation. Thereby, CE units are used to create outputs that are new for the core organization. Until now, scholars have neglected to investigate assessing CE unit performance, leading to a lack of understanding of appropriate metrics for CE units. Companies often use traditional metrics designed for relatively static contexts, but these metrics do not fit for CE units. This study explores the metrics used in CE units, analyzing 12 interviews with 11 German companies. The analysis reveals a list of different metrics, categories, and underlying dimensions for CE unit performance measurement. Finally, we suggest scientific and managerial implications and topics for future research.

This article analyses current developments in Autonomous Shipping (MASS) by adopting a socio-technical system perspective to explain why the technology is (still) only applied in small-scale niche applications and still not applied on a large scale. Using literature study and an exploratory research approach to obtain in-depth information from naval practitioners and experts in the (autonomous) shipping industry we identify which factors currently stimulate or hamper the diffusion of autonomous shipping.An analysis of the Technological Innovation System (TIS) of the maritime industry shows that the 'standard' building blocks framework requires adjustment with regard to the market building block to make it applicable to analyze and understand developments in and motives and drivers of Autonomous Shipping. A subsequent analysis of the current status of the maritime-specific market building blocks showed these were to a large extent complete, with the exception of cost-benefit aspects. This result shows that large-scale diffusion is primarily hampered by this issue and cannot easily be resolved in the foreseeable future.

Corporate Entrepreneurship (CE) units have become an increasingly important part of established companies' development activities enabling them to also create more discontinuous innovations. As a result, companies have developed and implemented different forms of CE units, such as corporate accelerators, incubators, startup supplier programs, and corporate venture capital. Driven by the need to innovate, companies have even begun to use multiple CE units simultaneously. However, this has not been empirically investigated yet. Thus, with this study, we aim to shed some light on this by investigating the parallel use of multiple CE units in the German business landscape. We conducted an extensive desk research, combining, coding, and analyzing different sources. We found that 55 out of 165 large established companies have multiple CE units, which allowed us to characterize the parallel use and identify differences and similarities, e.g., in terms of industry, company size, and CE forms implemented. We conclude by presenting different implications for both practice and research and by pointing out directions for future research.

Research credits corporate entrepreneurship (CE) with enabling established companies to create new types of innovation. Scholars have focused on the organizational design of CE activities, proposing specific organizational units. These semi-autonomous units create a tense management situation between the core organization and its CE activities. Management and organization research considers control as a key managerial function for help. However, control has received limited research attention regarding CE units, leaving design issues for appropriate control of CE units unanswered. In this study, we link management control and CE to illustrate how control is understood in the context of CE. For this, we scanned the CE literature to identify underlying attributes and characteristics that allow specifying control for CE. We identified 11 attributes to describe control for CE activities in a first round and to derive future research paths.