Digital product innovation within four classes of innovation networks

Abstract

The increased digitization of organizational processes and products poses new challenges for understanding product innovation. It also opens new horizons for information systems research. We analyse how ongoing pervasive digitization of product innovation reshapes knowledge creation and sharing in innovation networks. We argue that advances in digital technologies (1) increase innovation network connectivity by reducing communication costs and increasing its reach and scope and (2) increase the speed and scope of digital convergence, which increases network knowledge heterogeneity and need for integration. These developments, in turn, stretch existing innovation networks by redistributing control and increasing the demand for knowledge coordination across time and space presenting novel challenges for knowledge creation, assimilation and integration. Based on this foundation, we distinguish four types of emerging innovation networks supported by digitalization: (1) project innovation networks; (2) clan innovation networks; (3) federated innovation networks; and (4) anarchic innovation networks. Each network involves different cognitive and social translationsor ways of identifying, sharing and assimilating knowledge. We describe the role of five novel properties of digital infrastructures in supporting each type of innovation network: representational flexibility, semantic coherence, temporal and spatial traceability, knowledge brokering and linguistic calibration. We identify several implications for future innovation research. In particular, we focus on the emergence of anarchic network forms that follow full-fledged digital convergence founded on richer innovation ontologies and epistemologies calling to critically re-examine the nature and impact of modularization for innovation.

Digital Innovation Management: Reinventing Innovation Management Research in a Digital World

“…More recently, there has been an expansion to identifying and articulating unique aspects of digitization in industries, specific organizational domains, or product families (e.g., Agrawal et al 2013;Anderson and Agarwal 2011;Greenstein et al 2013;Xue et al 2013). They have especially highlighted the paradoxes and dilemmas that digitization creates for organizations developing, deploying, and managing digital innovation (e.g., Breshnahan and Greenstein 2014; Kallinikos et al 2013;Lyytinen et al 2016;Nambisan 2013;Tilson et al 2010;Tiwana et al 2010;Yoo et al 2010). IS scholars have also been increasingly focused on the materiality of digitization within innovation processes and outcomes (e.g., Boland et al 2007; Lee and Berente 2012;).…”

Emergent Ecosystem for Radical Innovation: Entrepreneurial Probing at Formula E

“…Recently, Lyytinen Yoo, and Boland [17] proposed a new organizing form for radical digital innovation, created by the distributed, fluid, editable, and configurable nature of digital technologies. The new form is an anarchic innovation network.…”

“…One key aspect of anarchic networks described by Lyytinen et al [17] is that they are not designed ex ante because the knowledge resources needed for innovation are not known a priori. Rather, anarchic networks emerge through interactions among various heterogeneous partnerships and collaboration opportunities.…”

“…Rather, anarchic networks emerge through interactions among various heterogeneous partnerships and collaboration opportunities. But neither Lyytinen et al [17] nor Majchrzak et al [19] address the challenges of an entrepreneurial firm in emerging a radical innovation network. How to formulate a rich landscape of opportunities so that a search for heterogeneous needsolution pairs can take place?…”

“…Initiatives serving as probes can expand the landscape by generating new cognitive and social translations [17]. Cognitive dynamics "form a generative dance of knowledge identification, sourcing, creation, dissemination and validation" [17, p. 56].…”