Where Do Games of Innovation Come From? Explaining the Persistence of Dynamic Innovation Patterns

Floricel, Serghei; Dougherty, Deborah

doi:10.1142/s136391960700162x

Cited by 13 publications

(7 citation statements)

References 69 publications

(78 reference statements)

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“…Velocity refers to the perceived intensity of directional change in meso‐level systems, such as advances in the frontier of functionality, performance and cost brought about by technological innovation (Moore, 1965; Eisenhardt, 1989). This type of change is reproduced in the long term by resource feedback processes occurring inside meso‐level systems (Floricel and Dougherty, 2007). Strategic actors ‘read’ the resulting dynamics and adopt strategies that contribute to its reproduction (Bogner and Barr, 2000).…”

Section: Understanding Dynamic Riskmentioning

confidence: 99%

Using R&D portfolio management to deal with dynamic risk

Floricel¹,

Ibanescu²

2008

R & D Management

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We develop a theoretical framework for understanding why firms adopt specific approaches for the management of innovation project portfolios. Our theory focuses on a key contingency factor for innovation, namely the dynamics of competitive environments. We use four dimensions to characterize the patterns of environmental dynamics: velocity, turbulence, growth and instability. The paper then proposes the concept of dynamic risk as a determinant of portfolio management processes. Dynamic risk results from second‐order learning by a firm confronted with a specific dynamic pattern in its environment. This learning concerns the likely nature of threats and the required updating of cognitive frameworks in such environments. Attempts to deal with dynamic risk enable various actors inside the firm to understand what kind of dynamic capabilities are needed in their innovation portfolio management processes. As a result of this diffuse learning, firms tend to favor certain common characteristics in their concrete portfolio management activities. To advance the theorizing of these characteristics, the paper also proposes four dimensions of portfolio management: structure, commitment, emergence and integration. Based on arguments inspired by the dynamic capability and related literatures, we advance a series of hypotheses, that relate environmental dynamics dimensions and portfolio management dimensions. These hypotheses are tested based on a survey of 795 firms in a variety of sectors and on four continents, using original scales and structural equation modeling methods. The results show, among other findings, that high‐velocity environments favor structured as well as integrated portfolio management approaches, while high‐growth environments favor approaches that are structured but commit significant resources to each project as well. Turbulent environments favor approaches that are emergent, but also, contrary to our expectations, have high resource commitment levels. Finally, firms in unstable environments have a marginal preference for emergent approaches. Results could help advance the dynamic contingency theoretical perspective on dynamic capabilities, as well as improve the practice of innovation portfolio management.

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Section: Understanding Dynamic Riskmentioning

confidence: 99%

Using R&D portfolio management to deal with dynamic risk

Floricel¹,

Ibanescu²

2008

R & D Management

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“…In turn, organization scholars study mechanisms such as structuring from repeated interactions between actors [73,74] or lifecycles in which stabilization follows turbulent periods [75][76][77]. Others pay attention to processes that maintain highly dynamic patterns, such as high velocity and exponential growth [78][79][80].…”

Section: Theoretical Contextmentioning

confidence: 99%

Strategies for Managing the Structural and Dynamic Consequences of Project Complexity

2018

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We propose a theoretical framework that highlights the most important consequences of complexity for the form and evolution of projects and use it to develop a typology of project complexity. This framework also enables us to deepen the understanding of how knowledge production and flexibility strategies enable project participants to address complexity. Based on this understanding, we advance a number of propositions regarding the strategies that can be most effective for different categories of complexity. These results contribute to the integration of various strands in the research on project complexity and provide a roadmap for further research on the strategies for addressing it.

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“…These existing systems provide models for different kinds of governing structures that enable collective, long term co-evolution of sciences and technologies for innovation. These systems include open innovation (Chesbrough 2003), regional clusters (Gilbert 2012), network innovations (Iansiti and Levien 2004), industry platform systems (Gawer and Cusumano 2002), and the more general ideas about technology trajectories that build on the efforts of many different organizations and innovators (Dosi 1982;Floricel and Dougherty 2007).…”

Section: Institutional Innovating To Generate Collaborative Commonsmentioning

confidence: 99%

Taking advantage of emergence for complex innovation eco-systems

Dougherty

2017

Journal of Open Innovation: Technology, Market, and Complexity

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Our most pressing societal problems such as enhancing health care, developing alternate energy, revitalizing cities, and advancing the economy are complex innovation eco-systems. Complex innovation eco-systems are the next frontier in technology and innovation management, and require a transformation in strategic and institutional management so that managers can muster the staying power to persist and learn far into the future. I develop a framework to explain how participants can strategize across an entire eco-system, deal with the profound ambiguity from complexity, and handle the very long cycle times of complex innovations. Transformed strategic and institutional management combines abductive learning routines with clock-time and event-time pacing to map a portfolio of value creating opportunities far into the future. Eco-system participants use learning events, which represent available knowledge, to hypothesize new value creating opportunities and new kinds of governance structures for specific collaborations, evaluate these opportunities and governance structures by trying them out to explore assumptions and surface new possibilities, and reframe them over time.Many of society's most pressing problems are complex innovation eco-systems. Pharmaceuticals, health care more generally, alternate energy systems, climate control, education, and myriad social problems rely on ongoing innovation to continually generate new projects, products, programs, processes, capabilities, and value creation opportunities that address these critical challenges. These "grand challenges" (Ferraro et al. 2015) represent the next frontier in technology and innovation management, because they require new theory for managing multiple organizations, agents, and agencies, and new theory for collaborative learning about the co-evolution of sciences and technologies among vast, globally dispersed networks of knowledge workers.Taking advantage of emergence (Dougherty 2016) is a central capability around which new theories for complex innovation eco-systems will build. Innovators in complex eco-systems must take advantage of the emergence of knowledge about sciences, technologies, user needs, delivery systems and so on for their new products and programs, because knowledge for innovation does not already exist. Taking advantage of emergence refers to grabbing the inherently fragmented and noisy information that abounds in complex eco-systems, configuring information bits into potential solutions

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Where Do Games of Innovation Come From? Explaining the Persistence of Dynamic Innovation Patterns

Cited by 13 publications

References 69 publications

Using R&D portfolio management to deal with dynamic risk

Using R&D portfolio management to deal with dynamic risk

Strategies for Managing the Structural and Dynamic Consequences of Project Complexity

Taking advantage of emergence for complex innovation eco-systems

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