Investigating the effects of stakeholder collaboration strategies on risk prevention performance in a digital innovation ecosystem

Abstract

Purpose The risks associated with digital innovation increasingly challenge value co-creation among stakeholders within the innovation ecosystem. Stakeholder collaboration is helpful in preventing risk occurrence. This study intends to explore the effects of different stakeholder collaboration strategies on risk prevention performance in a digital innovation ecosystem context. Design/methodology/approach A systematic literature analysis was first conducted to identify risk factors of digital innovation based on the technology–organization–environment (TOE) framework. Then, a bidimensional network model was constructed to visualize the collaborative relationships among stakeholders and the identified risks by focusing on a digital innovation case. The social network analysis method was applied to design stakeholder collaboration strategies from the ego and global network perspectives, and a simulation approach was conducted to evaluate the effects of the strategies on risk prevention performance. Findings The results validate the positive effect of stakeholder collaboration on risk prevention performance and reveal the important role of network reachability in formulating collaboration strategies. The strategy of strong–strong collaboration strategy can best enhance risk prevention performance like a “Matthew effect” in the digital innovation ecosystem. Originality/value First, risk identification based on the TOE framework provides a systematic list of risk factors for future digital innovation risk management research. Second, this study designs stakeholder collaboration strategies from a network perspective to enhance the understanding of the network status of each stakeholder and the network structure of the digital innovation ecosystem. Third, the simulation results reveal the effects of different collaboration strategies on risk prevention performance.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 52 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.