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This paper studies two fundamentally distinct approaches to opening a technology platform and their different impacts on innovation. One approach is to grant access to a platform and thereby open up markets for complementary components around the platform. Another approach is to give up control over the platform itself. Using data on 21 handheld computing systems (1990-2004), I find that granting greater levels of access to independent hardware developer firms produces up to a fivefold acceleration in the rate of new handheld device development, depending on the precise degree of access and how this policy was implemented. Where operating system platform owners went further to give up control (beyond just granting access to their platforms) the incremental effect on new device development was still positive but an order of magnitude smaller. The evidence from the industry and theoretical arguments both suggest that distinct economic mechanisms were set in motion by these two approaches to opening.

PurposeAs an important driving factor of digital innovation, distributed innovation has received extensive attention from academia and business circles in recent years. However, extant works lack a discussion on the influence of distributed innovation on digital innovation performance. Drawing on the opportunity perspective, the study constructs a moderated mediating model to address how distributed innovation directly affects enterprises' digital innovation performance. Particularly, it investigates the moderating and mediating effects of IT-enabled capabilities and digital entrepreneurial opportunities on the above correlation.Design/methodology/approachWith a survey data set of 399 Chinese science and technology enterprises, the study conducts hierarchical linear modeling (HLM) and bootstrap to test the study’s hypotheses.FindingsResults demonstrate that (1) distributed innovation positively enhances enterprises' digital innovation performance; (2) digital entrepreneurial opportunities partially mediate the positive relationship between distributed innovation and digital innovation performance; (3) IT-enabled capabilities positively moderate the relationship between distributed innovation and digital entrepreneurial opportunities; (4) IT-enabled capabilities positively moderate the mediating role of digital entrepreneurial opportunities in the relationship between distributed innovation and digital innovation performance.Originality/valueThis is an empirical study on the impact mechanism of IT-enabled capabilities and digital entrepreneurial opportunities on the relationship between distributed innovation and digital innovation performance in China. It advances theories related to distributed innovation, digital innovation and digital entrepreneurial opportunities, and provides decision-making references for the enhancement of digital innovation capabilities of science and technology enterprises.

Purpose Despite the support of digital technology, there is a high degree of ambiguity and fluidity in the boundaries of digital products. This is because the addition of distributed innovation entities has an impact on the scope and scale of digital product innovation. Building upon the knowledge orchestration perspective, this study aims to construct a theoretical model, comprising distributed innovation, knowledge reorchestration and digital product innovation performance, and discuss the moderating roles of intellectual property protection and knowledge exchange activities. Design/methodology/approach Using a sample of 362 Chinese science and technology enterprises, the scholarship’s framework and hypotheses were tested using regression and bootstrap analysis. Findings The results confirm that distributed innovation positively enhances enterprises’ digital product innovation performance; knowledge reorchestration plays a partial mediating role in the linkage amongst distributed innovation and digital product innovation performance; and intellectual property protection and knowledge exchange activities negatively and positively moderate the mediating role of knowledge reorchestration amongst distributed innovation and digital product innovation performance, respectively. Originality/value This empirical scholarship explores the effect mechanism of intellectual property protection, knowledge exchange activities and knowledge reorchestration on the linkage amongst distributed innovation and digital product innovation performance. This paper expands the theoretical application of distributed innovation, knowledge orchestration and other related theories in the context of the digital economy and further provides a policymaking reference for the improvement of enterprises’ digital product innovations.

Smart city initiatives are being promoted across the world to address major urban challenges, and they all share a common belief in the transformative power of digital technologies. However, the pace of innovation in smart cities seems to be much slower than the rapid and profoundly disruptive transformations brought about by digital innovation in many other domains. To develop new insights about the main causes behind this relatively modest success, this study provides a Systematic Literature Review (SLR) on the connection between major smart city challenges and the essential properties of digital innovation. The review involved the qualitative analysis of 44 research papers reporting on smart city innovation practices and outcomes. The results characterize five major challenge categories for smart city innovation: Strategic vision; Organizational Capabilities and Agility; Technology Domestication; Ecosystem Development; and Transboundary Innovation. This study also explores the connections between these challenges and concrete digital innovation practices in smart city initiatives. The main conclusion is that current innovation practices in smart cities are not properly aligned with what the research literature commonly describes as core properties of digital innovation and that this might be a major cause behind the limited progress in smart city initiatives.

A step-by-step approach to applying high-impact innovation principles in any organization Innovation is an important force in creating and sustaining organizational growth. Effective innovation can mean the difference between leading with a particular product, process, or service--and simply following the pack. Innovation transforms mediocre companies into world leaders and ordinary organizations into stimulating environments for employees. Applying Innovation combines the key ingredients from areas including innovation management, strategic planning, performance measurement, creativity, project portfolio management, performance appraisal, knowledge management, and teams to offer an easily applied recipe for enterprise growth. Authors David O′Sullivan and Lawrence Dooley map out the main concepts of the innovation process into a clear, understandable framework--the innovation funnel. Unlike other texts for this course, Applying Innovation goes beyond methodologies and checklists to offer an invaluable step-by-step approach to actually applying high-impact innovation in any organization using a knowledge management systems, whether for a boutique firm or one comprised of thousands of individuals. Key Features: Adopts a practical approach to overseeing innovation that focuses on useful tools and techniques rather than on theory and methodologies Offers student activities within the text for immediate application of key concepts, reinforcing retention and comprehension Teaches students to build and apply effective innovation management systems for any organization successfully, regardless of the firm′s size or structure Intended Audience: Applying Innovation is designed for undergraduate and graduate courses such as Innovation Management, Project Management, Strategic Planning, and Performance Management in fields of business, science, and engineering. This book appeals to instructors who want to reduce the \"chalk and talk\" and increase the hands-on practicality of their courses in innovation management.

This research examines how artificial intelligence is reshaping business and labor structures through a sustainability lens. Drawing on survey data from 127 organizations and 14 case studies, we quantify workforce impacts while exposing methodological limitations in current projections. Our analysis reveals implementation variations of 37% across industries and 41% higher user adoption rates for hybrid governance approaches versus centralized models. The evidence supports a three-dimensional strategic framework for sustainable organizational development: comprehensive upskilling fostering behavioral change (2.7× higher implementation success), distributed innovation enabling cross-functional ideation (3.1× more identified use cases), and strategic integration aligning systems across departments (explaining 31% of implementation success variance). Organizations deploying all three dimensions achieved a 74% AI initiative success rate versus 12% for those using none. Implementation barriers include regulatory uncertainty, organizational resistance, and ethical considerations, with data infrastructure maturity (β = 0.32), executive sponsorship (β = 0.29), and change readiness (β = 0.26) explaining 58% of implementation success variance. Our findings indicate that sustainable adaptation capacity—not merely technological investment—determines which organizations successfully navigate this transformation while maintaining long-term organizational viability, workforce resilience, and contribution to broader sustainable development goals.

The effectiveness and creativity of Linux, Wikipedia, and a plethora of other distributed innovation systems have attracted the attention of scholars, practitioners, and policy makers. The hallmark of these distributed innovation systems is that value creation transcends the boundaries of hierarchically organized firms. To date, only relatively few studies have focused on the organization design of distributed innovation systems. This conceptual article addresses this lacuna by asking, how does organization design structure relationships in distributed innovation systems, including interactions between the “visible hand” of the manager and the “crowd” of distributed innovation? The purpose of this article is to shift the unit of analysis of organization design from the individual firm to networks of actors providing a framework to study how design organizes distributed innovation systems. In order to do so, three design mechanisms (interface design, the design of participatory architectures, and the design of evaluative infrastructures) are proposed through which firms and other network actors organize their encounter in “the open” and through which they manage communication, coordination of tasks, and control in distributed innovation systems.

How does a firm’s value chain digitalization contribute to its innovation in value chains? This study investigates innovation activities in value chains from a combination of distributed innovation perspective and technology affordance theory. We posit that a digital value chain (DVC) plays a pivotal role in driving distributed innovation in value chains. Our focus is specifically directed toward exploring the interconnected dynamics of the DVC, global value chain (GVC), and diversification strategy, elucidating the influence of their interactions on a firm’s distributed innovation in value chains. Leveraging the data of 862 manufacturing firms from the World Bank Enterprise Survey (WBES) in China, our empirical analysis reveals several key findings: (1) value chain digitalization positively influences distributed innovation in value chains and GVC embeddedness, (2) GVC embeddedness enhances distributed innovation in value chains, and (3) product diversification serves as a positive moderator, strengthening the effects of both value chain digitalization and GVC embeddedness on distributed innovation in value chains. In summary, this paper deepens our understanding of the relationships between DVC, GVC, diversification strategy, and distributed innovation in value chains. Our research provides theoretical and policy implications for digitalization and innovation strategies which are significant sources of sustainable development for firms and GVCs.

In this paper, I study the effect of adding large numbers of producers of application software programs (“apps”) to leading handheld computer platforms, from 1999 to 2004. To isolate causal effects, I exploit changes in the software labor market. Consistent with past theory, I find a tight link between the number of producers on platform and the number of software varieties that were generated. The patterns indicate the link is closely related to the diversity and distinct specializations of producers. Also highlighting the role of heterogeneity and nonrandom entry and sorting, later cohorts generated less compelling software than earlier cohorts. Adding producers to a platform also shaped investment incentives in ways that were consistent with a tension between network effects and competitive crowding, alternately increasing or decreasing innovation incentives depending on whether apps were differentiated or close substitutes. The crowding of similar apps dominated in this case; the average effect of adding producers on innovation incentives was negative. Overall, adding large numbers of producers led innovation to become more dependent on population-level diversity, variation, and experimentation—while drawing less on the heroic efforts of any one individual innovator.

Synthetic biology is in the process of inventing itself and its ownership regimes. There are currently two dominant approaches to ownership and sharing in the field. The work of the J. Craig Venter Institute is grounded in molecular biology and in gene patenting. Parts-based approaches to synthetic biology, in contrast, are inspired by engineering, open source software and distributed innovation, and they are building new communities to help further this agenda. Despite these differences, the two approaches make very similar use of informational and computational metaphors. They both also have a place in a vision for the future of synthetic biology as a ‘diverse ecology’ of the open and the proprietary. It remains to be seen whether such a diverse ecology will be sustainable, whether synthetic biology will go down the patenting route taken by previous biotechnologies or whether different forms of ownership and sharing will emerge. Which path is taken will depend on the success of synthetic biology in achieving both its technical objectives and its social innovations.