Researching ecosystems in innovation contexts

Purpose – The rapid adoption of the ecosystem concept in innovation contexts has led to a proliferation of differing uses. Scholars need to be crystal clear which concept of the ecosystem they are using to facilitate communication between scholars and allow for cumulativeness and creativity. This paper aims to introduce some clarity into the conceptual mist that surrounds the notion of “ecosystems” in innovation contexts. Design/methodology/approach – A review of the extant literature on ecosystems in innovation contexts to derive an integrated approach to understanding the variety of constructs in use. Findings – This paper introduces clarity into the conceptual mist that surrounds the term “innovation ecosystem”, showing there are three basic types of ecosystems, all of which have a common focus on the collective production of a coherent system-level output. Originality/value – Contributes through a comprehensive overview of the differing ecosystem types in innovation contexts and with a heuristic to disambiguate types of innovation ecosys tems

Digital innovation: transforming research and practice

There is no doubt that digital technologies are spawning ongoing innovation across most if not all sectors of the economy and society. In this essay, we take stock of the characteristics of digital technologies that give rise to this new reality and introduce the papers in this special issue. In addition, we also highlight the unprecedent opportunities that digital innovation provides to study innovation processes more generally. Overall, we conclude that the speed, observability, and relative ease in investigating relationships between multiple analytical levels, mean that digital innovation is both a ‘model of’ that also provides a ‘model for’ the study of innovation processes more broadly in non-digital and hybrid contexts

Distinguishing digitization and digitalization: A systematic review and conceptual framework

With increasing interest in how digital technology impacts innovation, the constructs "digitization" and "digitalization" have become popular. However, different conceptualizations have emerged resulting in conceptual overlap and little definitional consensus. To understand how these two constructs have been used within innovation management, we systematically review both constructs and identify 26 different definitions used for both, underscoring the need for greater precision. Building from our systematic review, we synthesize and integrate these findings to derive clear and parsimonious definitions of digitization and digitalization and propose a conceptual framework that systematically links both constructs with existing innovation scholarship. We then discuss the implications of our framework on theories of the process of innovation and digital transformation. We recommend future research into digital design principles, digital product life cycle, knowledge accumulation, generativity, and the feedback dynamics within our framework. We also provide practitioner implications and limitations.ISSN:0737-6782ISSN:1540-588

Small is big in ICT: The impact of R&D on productivity

We examine the contribution of R&D to firm productivity in a large panel of European firms and study its variation with the age, size, and sub-sector of firms. We find that R&D capital in ICT firms has a larger effect on revenue when compared to non-ICT firms. At the firm level, our results suggest that, surprisingly, smaller and older ICT firms benefit the most from R&D. Small but mature ICT firms are likely to dominate market niches, and small size may enable them to be flexible and adaptable which helps them respond to technological opportunities to develop innovative products and services. This has important implications for public policy based upon firm age

Distinguishing digitization and digitalization: A systematic review and conceptual framework

With increasing interest in how digital technology impacts innovation, the constructs “digitization” and “digitalization” have become popular. However, different conceptualizations have emerged resulting in conceptual overlap and little definitional consensus. To understand how these two constructs have been used within innovation management, we systematically review both constructs and identify 26 different definitions used for both, underscoring the need for greater precision. Building from our systematic review, we synthesize and integrate these findings to derive clear and parsimonious definitions of digitization and digitalization and propose a conceptual framework that systematically links both constructs with existing innovation scholarship. We then discuss the implications of our framework on theories of the process of innovation and digital transformation. We recommend future research into digital design principles, digital product life cycle, knowledge accumulation, generativity, and the feedback dynamics within our framework. We also provide practitioner implications and limitations

Markets for data

Although datasets are abundant and assumed to be immensely valuable, they are not being shared or traded openly and transparently on a large scale. We investigate the nature of data trading with a conceptual market design approach and demonstrate the importance of provenance to overcome appropriability and quality concerns. We consider the requirements for efficient data exchange, comparing existing trading arrangements against efficient market models and show that it is possible to achieve either large markets with little control or small markets with greater control. We describe some future research directions

Platform Externalities: Beyond the N In Network Effects

Network effects have been theorized as the defining growth mechanism in platform markets. The increase in the number of platform participants (N) fuels a virtuous cycle of growth, a network effect. However, beyond the N, what are the distinct qualitative attributes that drive the increasing value for a particular side of a platform as the number (quantity) of participants increases? To answer to this question, we develop a theory of platform externalities to provide three novel contributions to the understanding of platform markets. First, we clarify the role of network externalities and network effects in causing the self-reinforcing growth of value in platform markets. Second, to move beyond the N, we identify four specific externalities in platform markets - quantity, variety, utility, and accumulation - which we call platform externalities. We also clarify the role of complementarity in case of variety and accumulation externalities. Third, we highlight the negative counterparts for each of the four platform externalities. Our explicit theorization calls for delineating platform strategy theories that rely on network effects to recognize distinct platform externalities and their negative counterpart

Digital innovation: transforming research and practice

There is no doubt that digital technologies are spawning ongoing innovation across most if not all sectors of the economy and society. In this essay, we take stock of the characteristics of digital technologies that give rise to this new reality and introduce the papers in this special issue. In addition, we also highlight the unprecedent opportunities that digital innovation provides to study innovation processes more generally. Overall, we conclude that the speed, observability, and relative ease in investigating relationships between multiple analytical levels, mean that digital innovation is both a ‘model of’ that also provides a ‘model for’ the study of innovation processes more broadly in non-digital and hybrid contexts