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In today’s fast-paced digital economy, no company can innovate in isolation. The most groundbreaking ideas often emerge at the intersections of different fields, organizations, and perspectives. But how do companies effectively share knowledge across organizational boundaries when they’re separated by different systems, cultures, and competitive concerns?
Cheng, Peng, Dai, & Zhang (2025) offer a clear answer: through digital innovation that transforms knowledge into shareable digital assets. Think of it this way—just as the internet transformed how we share information globally, digital innovation is transforming how organizations share knowledge professionally.
The study identifies two powerful approaches to digital innovation:
Distributed digital innovation represents the logic of open-source software development. It is inherently decentralized and collaborative, relying on loosely coupled actors who contribute knowledge beyond formal organizational boundaries. For example, globally distributed engineers from different firms may collaborate on platforms such as GitHub to collectively improve a shared software framework. In this setting, innovation emerges through continuous interaction and voluntary contribution, enabling knowledge to circulate freely across organizational lines and giving rise to networks of shared expertise rather than hierarchical control.
Combined digital innovation, by contrast, is closer to a strategic alliance in which organizations deliberately integrate complementary knowledge bases. Here, innovation results from purposeful coordination rather than spontaneous collaboration. An illustrative example is an automotive manufacturer partnering with a technology startup and a materials science laboratory to develop an electric vehicle. Each actor contributes specialized expertise—software, hardware, and advanced materials—which is recombined through structured collaboration into novel solutions. In this mode, digital platforms function as integrative mechanisms that facilitate coordination, knowledge recombination, and joint value creation across organizational boundaries.
Unlocking Interorganizational Knowledge Sharing Through Digital Innovation
How distributed and combined digital innovation facilitate knowledge sharing across organizations, mediated by knowledge digitization processes.
This empirical study examines how two types of digital innovation—distributed and combined—facilitate knowledge sharing across organizational boundaries, with knowledge digitization (codability, convergence, and generativity) playing a key mediating role. Based on survey data from 304 digital group members in China, the research provides evidence-based insights for organizations navigating digital transformation.
How to read this analysis: The sections below move from the core findings to the methodological approach, results, theoretical and practical implications, and future research directions. The structure supports both quick insights and deeper engagement with the research.
Summary
Digital innovation is fundamentally reshaping how organizations create, share, and utilize knowledge. This study introduces a novel classification of digital innovation into two types: distributed digital innovation (decentralized innovation across networks) and combined digital innovation (integration of diverse knowledge sources through recombination).
The research demonstrates that both types of digital innovation significantly enhance interorganizational knowledge sharing. More importantly, this relationship is mediated by knowledge digitization—specifically through three key characteristics: codability (ability to encode knowledge digitally), convergence (integration across domains), and generativity (dynamic updating and expansion).
These findings suggest that digital innovation alone is insufficient for effective knowledge sharing across organizations. Instead, organizations must strategically invest in knowledge digitization processes that transform innovation outcomes into accessible, shareable digital assets. This transformation reduces sharing costs, improves transparency, and enables continuous knowledge evolution through collaborative networks.
Methodology
The study employs a rigorous quantitative approach:
- Sample: 304 members from digital groups in China participating in interorganizational collaboration activities
- Data Collection: Online questionnaire distributed via a platform similar to Amazon Mechanical Turk (January-March 2024)
- Analysis Method: Partial Least Squares Structural Equation Modeling (PLS-SEM) using R (lavaan and seminr packages)
- Measurement: Variables measured with validated scales from existing literature using 7-point Likert scales
- Variables: Distributed digital innovation (6 items), combined digital innovation (5 items), knowledge digitization characteristics (3 items each for codability, convergence, generativity), and interorganizational knowledge sharing (5 items)
Results
- Both distributed digital innovation (β = 0.142, p < 0.01) and combined digital innovation (β = 0.267, p < 0.001) have significant positive effects on interorganizational knowledge sharing
- All three knowledge digitization characteristics positively influence knowledge sharing: codability (β = 0.139), convergence (β = 0.292), and generativity (β = 0.170), all with p < 0.01
- Distributed digital innovation strongly affects all digitization characteristics: codability (β = 0.583), convergence (β = 0.476), generativity (β = 0.409)
- Combined digital innovation also significantly influences digitization characteristics: codability (β = 0.198), convergence (β = 0.273), generativity (β = 0.410)
- Knowledge digitization fully mediates the relationship between both types of digital innovation and interorganizational knowledge sharing
- Statistical power analysis confirmed 97% power with the sample size of 304, well above the minimum requirement of 267
Implications
Theoretical Contributions:
- Introduces new classification of digital innovation (distributed vs. combined)
- Extends Knowledge-Based View to digital contexts and interorganizational settings
- Expands understanding of knowledge digitization beyond intraorganizational applications
- Provides empirical evidence for the mediating role of knowledge digitization characteristics
Practical Implications:
- For Managers: Position knowledge digitization as a core strategy, invest in interoperable digital platforms, cultivate digital proficiency and sharing culture
- For Policymakers: Integrate knowledge digitization into digital economy priorities, invest in public digital knowledge infrastructure, establish standards for knowledge exchange
- For Organizations: Build collaborative networks through digital platforms, optimize digital knowledge flow mechanisms, leverage both distributed and combined innovation approaches
Future Directions
- Sampling Improvements: Future studies should use stratified sampling to better represent different organizational subgroups and digital maturity levels
- Cross-Cultural Validation: Research should extend to other countries and regions to account for cultural, policy, and technological development differences
- Longitudinal Approaches: Future research could employ longitudinal designs to capture the evolution of knowledge digitization processes over time
- Industry-Specific Studies: Investigation of how these dynamics vary across different industries and organizational types
- Technology-Specific Effects: Research on how different digital technologies (blockchain, AI, IoT) differentially affect knowledge digitization characteristics
References
Cheng, Q., Peng, C., Dai, Y., & Zhang, S. (2025). Unlocking interorganizational knowledge sharing: the mediating role of knowledge digitization in the age of digital innovation. Journal of Knowledge Management. DOI: 10.1108/JKM-06-2024-0687
Additional References from the Study: Nambisan et al. (2020), Yoo et al. (2010, 2012), Cheng et al. (2023), Han et al. (2024), Bereznoy et al. (2021)
