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.

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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.

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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.

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Organizational responses to strategic surprises like the credit crunch in 2008 and the pandemic in 2020, are increasingly reliant on scientific insights. As a result, model accuracy has become more critical than ever, and model complexity has increased to help us capture the real-world phenomena we study. 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 accurate for a specific context and are difficult 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 classifying the problems with mismatches between real-world and model complexity. They present a framework of four levels of model complexity and possible oversimplification problems.

The framework can help scholars within the social sciences to detect possible oversimplification from literature reviews and inform choices for either in- or decreases in model complexity.
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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.

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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.

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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.

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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.@en

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.@en

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.@en

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.@en

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.@en

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.@en

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.@en

Corporate Entrepreneurship (CE) programs are formalized efforts to realize entrepreneurial activities in established companies. Despite the growing and evolving landscape of CE programs, effectively managing them remains a challenging endeavor which results in disappointing outcomes and oftentimes leads to the early termination of such programs. We unmask the differences in goal setting of CE programs and highlight that setting appropriate goals is imperative for their desired outcomes. In practice, companies seem to struggle with the goal setting, and scholars have not yet fully solved the puzzle of goals setting in the context of CE programs either. Therefore, we set out to explore the current state of goal setting in the context of CE programs building upon 61 semi-structured interviews with CE program executives from cross-industry companies with different sizes. Our study contributes to a better understanding of goal setting in the context of CE programs by (1) characterizing the goal setting of CE programs based on goal attributes and goal types and (2) identifying differences among the goal setting of CE programs. We provide implications to practice for a more effective management of CE programs and conclude with a discussion for future research on the impact of the different goal settings.@en

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.@en

Four extensive literature reviews on factors for innovation success in terms of market, strategic and social impact for additive manufacturing were performed where the focus lies on three levels of analysis; (inter)organizational, business model, and project.@en

Purpose: This paper addresses the most important factors for the selection of additive manufacturing (AM) technology as a method of production of metal parts. AM creates objects by adding material layer by layer based on 3D models. At present, interest in AM is high as it is hoped that AM contributes to the competitiveness of Western manufacturing industries. Design/methodology/approach: A literature study is conducted to identify the factors that affect the selection of AM technology. Expert interviews and the best–worst method are used to prioritize these factors based on relative factor weights. Findings: Technology, demand, environment and supply-related factors are categorized and further mapped to offer a holistic picture of AM technology selection. According to expert assessments, market demand was ranked highest, although market demand is currently lacking. Research limitations/implications: The composition and size of the expert panel and the framing of some of the factors in light of previous literature cause validity limitations. Further research is encouraged to differentiate the selection factors for different AM implementation projects. Originality/value: The paper presents a more complete framework of factors for innovation selection in general and the selection of AM technology specifically. This framework can serve as a basis for future studies on technology selection in the (additive) manufacturing sector and beyond. In addition to AM-specific factor weights, the paper explains why specific factors are important, reducing uncertainty for managers that have to choose between alternative manufacturing technologies.

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This chapter explores how responsible the innovation process was, in hindsight, in subsequent episodes of wind power development. The episodes are the American farm windmill in 1850–1880 in the USA, the direct current (DC) electricity wind turbine in 1890–1910 in Denmark, and the alternating current (AC) electricity wind turbine in 1940–1990 in the USA. The episodes turn out to be heterogeneous in two aspects: (1) they show different levels of complexity in terms of the number of stakeholders; (2) they vary significantly in terms of responsibility of the innovation process. We conclude that the Danish innovation episode is the most responsible, and the later USA episode is the least responsible. It appears more difficult to innovate responsibly when there is a high level of complexity. However, the Danish episode reveals that responsible innovation processes are also possible in a rather complex case involving many stakeholders. Furthermore, the chapter shows that responsible innovation is not just important prior to the market introduction but remains important throughout the technology life cycle.@en

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book describes responsible innovation in terms of both the innovation process and the innovation outcome, and in doing so it focuses on historical cases of innovation in large societally relevant technological systems. It illustrates how responsible innovation can be defined by discussing how it is applied or can be applied in specific cases of societally relevant large technological systems. The book focuses on large societally relevant, technological systems, most contributions take a systems perspective in which social and technological aspects are explored in combination. It explores how responsible the innovation process was during three episodes of wind power development: the American farm windmill between 1850 and 1880 in the USA, the direct current electricity wind turbine between 1890 and 1910 in Denmark, and the alternating current electricity wind turbine between 1940 and 1990 in the USA.@en