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.

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.

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.

This article explores Maritime Autonomous Surface Ships (MASS) through the Technological Innovation Systems (TIS) framework to identify strategies for creating a market for this emerging technology. It examines the current state of TIS components for MASS and the factors shaping their development. Through a literature review and expert interviews, the article highlights key barriers, particularly the cost-benefit ratio, and suggests niche strategies to address barriers. Proposed strategies include the top niche strategy, lead user strategy, and hybridization niche strategy, aimed at overcoming challenges and facilitating broader market adoption of MASS in the future.

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.

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.

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.

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.

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.

Recent theoretical advances hold that platforms comprise a second strategic dimension next to size, called identity, which describes the platform's technological and market scope. Letting go of platform size as the main criterion for platform value opens the possibility for platforms to pursue differentiation strategies with a distinct market positioning. The concept of optimal distinctiveness (OD) implies that differentiation can be optimized so that it maximizes performance. In this paper, we draw on recent OD research in and outside of the field of platforms and elaborate on the role of platform size within the distinctiveness framework. We discuss platform size and identity in the context of OD and suggest propositions for future research. The paper contributes to the management of platforms and OD in platform markets by showing how a platform's distinctiveness strategy may depend on its size. We contribute to platform management across various platform sizes and to research on OD in platform markets.

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.

We analyze organizational configurations of digital platforms for manufacturing according to two dimensions: platform functions and platform types. Platform functions refer to the organizational functions of platforms: manufacturing, data sharing, market making, and innovation. Platform types refer to a typology of how platforms are organized: as internal, supply chain, or industry type. We combine those dimensions into a framework and use that to analyze seven cases of digital platforms from the manufacturing sector. Our research answers calls for conceptual clarity and scoping of the digital platform concept and mends relative lack of attention toward digital platforms for the manufacturing sector. We find that digital platforms for manufacturing come in different, partly unexpected, configurations: (1) not all functions are necessarily organizationally part of the platform, (2) not all functions are necessarily organized according to the same platform type, but (3) also not all random configurations of platform types and functions seem to be possible. This complexity highlights the importance of the innovation function for exploring effective configurations of digital platforms for manufacturing.

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.

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.

Corporate Entrepreneurship (CE) has now evolved into an imperative innovation practice of established companies. Despite organizational design models for CE activities and companies' frequent initiation of new activities, effectively managing them remains a challenging endeavor which results in disappointment about the outcomes of CE and its early termination. We assume specific types of goals for CE as one element of this unresolved management issue. While both practice and literature address goals in different contexts, no uniform picture has emerged so far. Although goals are commonly used to categorize CE activities, they seldomly seem to be the core subject of investigation. Based on this preliminary analysis and consolidation, we put the goals of CE in focus. In a systematic literature review, we reveal aspects of goals to unmask the different types of goals and their underlying dimensions and characteristics. Our review contributes to a better understanding of goals by (1) organizing relevant literature on goals of CE in a specific classification process, (2) describing dimensions and attributes for a systematic classification of CE goals; and (3) providing a framework showing differences of goals for the CE context. We conclude with a discussion and hints for future research paths.

Pioneering companies of radically new technological innovations often suffer from a slow uptake of their innovations and struggle to find the right introduction strategy. This paper aims to conceptualize a Technological Innovation System framework that can be applied to formulate and study niche introduction strategies from a company perspective. It combines insights from two literatures: the socio-technical systems literature and the innovation & strategic management literature. This results in a framework consisting of seven Technological Innovation System building blocks and seven influencing conditions that can influence the building blocks. The Technological Innovation System building blocks in the framework are: product performance and quality; product price; production system; complementary products and services; network formation and coordination; customers; and innovation-specific institutions. The influencing conditions in the framework are: knowledge and awareness of technology; knowledge and awareness of application and market; natural, human and financial resources; competition; macro-economic and strategic aspects; socio-cultural aspects; and accidents and events. The framework can help explore the context around an innovation during the early stages of Technological Innovation System formation and specify the scope, timing and type of niche introduction strategies that fit this context. This is illustrated with two cases: dual-clutch transmission technology and photovoltaic cells.

Nowadays established companies use Corporate Entrepreneurship (CE) as a means to create discontinuous innovations. Many companies thereby even implement multiple CE units that typically involve several entrepreneurial activities. This explorative study aimed to identify the reasons why established companies implement multiple CE units concurrently. In conducting a comparative case study with eight companies from different industries, valuable insights for science and practice were gained. We provide an overview of different 11 reasons for implementing multiple CE units. This shows that the combination of CE units used by companies differs depending on the reason. It further allowed to derive general approaches of established companies to the implementation of CE units. Last, we identify the concept of co-specialization to be a central driver explaining the creation of the need to set up multiple units. We conclude by indicating implications and subjects for future research.

Despite their importance little is known about how innovation ecosystems come into existence. We address this gap through an historical case study Herceptin, a revolutionary drug developed for the treatment of ovarian and breast cancer, and the innovation ecosystem that emerged around this drug between 1978 and 1998. Through qualitative content analysis of a broad scope of archival documents (2474 in total), we define a cast of roles and determine their timing of entry onto the stage of ecosystem emergence, and in turn describe the interaction of these roles that govern emergence. We find that the locus of ecosystem emergence shifts gradually from discovery, resource provision and commitment, to the formation of connections and trust, and finally to complementarity and value creation. These activities are facilitated by specific roles that gain significance at various points in time. We additionally witness shifts in interaction dynamics, from individual level interactions early on, to interactions across levels, and finally to interactions at the organisational level. We synthesize these findings to propose a framework of a processual understanding of how innovation ecosystems come into existence.

It is important for companies to be able to make their business models dynamic. This enables them to adapt to changing circumstances and remain viable. The aim of this paper is to combine insights from the literature on business models and business model dynamics into a comprehensive dynamic business model framework. The framework that is developed in this paper takes into account various origins of changes in business models (internal or external to the company) and various types of changes in business models (primary or secondary changes and forced changes or strategic choices) and also includes the issue of business model consistency. In order to combine different origins and different types of business model change into one dynamic business model framework, some simplifications of reality were needed. The framework is described in text and shown in a comprehensive picture. The application of the framework to two cases of renewable energy companies in Indonesia shows that the framework is able to capture business model dynamics in a simplified and comprehensive way and that it allows for case study comparison. In a thorough discussion, it is shown how the framework can be adapted to make it better able to represent more complex dynamics.

The research into the perception of early signals, the so-called weak signals, started in the field of strategic planning in the 1970s. Soon, research dispersed into new, specialized fields, such as foresight, sense-making, and entrepreneurial alertness. Each field used different terms for weak signals and framed the research in its own theoretical and methodological basis, which led to many different descriptions of weak signals. To put a stop to the growing number of definitions, this paper presents a contrarian approach. The usual simple combinations are likely to omit relevant meaning when underlying definitions only partially overlap. Therefore, his paper used a three-step approach including cluster analysis to unify 68 reviewed definitions into one. Cluster analysis includes more meaning by summarizing data. The analysis resulted in the defining of weakness in terms of distance to a perceiver's frame of reference. Distance explains the difficulty of perceiving weak signals more clearly than keywords like novel, ambiguous, or ill-defined. Distance also helps to quantify the amount of weakness in signals. Our approach may help others to find clarity and retain meaning when constructs are fuzzy. Defining weakness in distance opens up comparative studies between signals of various levels of weakness.