In the rapidly evolving landscape of technology and innovation, Complex Product Systems (CoPS) stand at the forefront of transformative industrial development. CoPS inherently demand multifunctional innovation teams spanning multiple organizations to drive advancement, making them quintessential examples of complicated innovation network organizations. These systems, often seen in cutting-edge sectors such as the Internet of Things (IoT), embody complexity not only through their technical architecture but also through the intricate web of organizational relationships and core competencies required for innovation. Recent research has shed light on the dynamic interplay between various factors that shape the innovation patterns within CoPS, offering new pathways for organizations striving to excel in this challenging arena.
Innovation within CoPS is rarely the outcome of isolated efforts. Instead, it emerges from the synergistic collaboration of diverse firms and knowledge domains. A pivotal question arises: how do different innovation actors select suitable partners and shape unique organizational configurations that best serve their innovative pursuits? Addressing this, a comprehensive study involving 184 firms engaged in the IoT product ecosystem applied the dynamic capability theory—an influential framework that captures an organization’s ability to adapt, integrate, and reconfigure internal and external competences to address rapidly changing environments. This research goes beyond traditional linear analysis, exploring the “joint effect” of five critical factors—Inter-organizational Collaboration Platforms (ICP), Modular Cooperative Platforms (MCP), Inter-organizational Coordination (ICO), External Collaborative Organizations (ECO), and Technological Development Pathways (TDP)—on innovative performance following (IPF).
The findings reveal a nuanced landscape where no single factor suffices or guarantees innovative performance in CoPS; rather, multiple configurations interplay to shape success. The study uncovers three distinct organizational patterns—modular-oriented, integration-oriented, and relationship-oriented—each with unique core and peripheral conditions among the five factors. The modular-oriented pattern emphasizes MCP and ICO as central, with the ICP as a supportive element, highlighting the role of modular design and coordination in fostering innovation. In contrast, the integration-oriented pattern brings ICP and ECO to the core, allowing MCP and ICO to interchange roles based on context, reflecting a system-wide integrative approach. The relationship-oriented pattern centers on ICO and ECO but interestingly positions MCP and TDP as peripheral, underscoring the centrality of coordination and external partnerships in certain innovation environments.
The implications of these configurations for theory are profound. By extending dynamic capability theory into the realm of CoPS innovation, the research advances our understanding of how innovation teams function as complex entities rather than isolated units. Traditionally, innovation studies have concentrated on leaders or teams as monolithic actors, but this study dissects the innovation team into constituent members and their interactions, grouping core competencies and inter-organizational relationships more granularly. This refined division captures the majority of team members and their diverse roles, offering a more accurate reflection of real-world innovation dynamics.
The study further elucidates the interactive relationships among influencing factors, going beyond simple additive effects. For instance, the interaction between ICP and ECO fosters horizontal expansion of resources, ensuring that innovation subjects remain open and diversified. On the other hand, MCP’s collaboration with ICO drives vertical development, promoting constructive accumulation of heterogeneous resources. This reciprocity not only enriches the understanding of dynamic capabilities but also explains how firms manage strategic substitutions—like MCP and ICO swapping roles—to mitigate technical risks through unified planning. Such insights deepen the theoretical framework by integrating a richer, more systemic view of how innovation thrives in complex, networked environments.
Methodologically, the adoption of fuzzy set Qualitative Comparative Analysis (fsQCA) marks a significant advance in capturing the diverse pathways through which innovation subjects in CoPS achieve performance. Unlike traditional variance-based approaches relying on symmetric causality, fsQCA accommodates causal complexity and equifinality—the existence of multiple routes to the same outcome. This approach allows the identification of robust patterns linking combinations of factors to innovation success, thereby offering nuanced and universal explanations suitable for CoPS contexts.
From a managerial perspective, the findings translate into actionable strategies for innovation practitioners. Entities with strong ICP capabilities should leverage information technology strategically, establishing innovation platforms and data retrieval tools to optimize resource allocation and consolidate competitive advantages. For these actors, fostering coordination with government bodies, clients, and research institutions is crucial—policy alignment, understanding client needs, and collaborative R&D initiatives can expand technical knowledge boundaries and enrich product solutions. Meanwhile, innovation subjects excelling in MCP should prioritize long-term cooperative relationships built on strategic convergence and shared interests to enhance trust and industry influence, ultimately strengthening the modular ecosystem of CoPS.
Organizations maintaining a balance between ICP and MCP have a distinctive yet potent opportunity. These actors can spearhead knowledge-sharing platforms, information exchanges, and innovation service initiatives—platforms essential for integrating independent and open innovation modes. By combining hard technological power with soft support mechanisms, these firms can strategically widen their reach across supply chains and broaden industrial impact vertically and horizontally. This dual orientation fosters resilience and adaptability, enabling firms to thrive amid complex innovation demands.
Recognizing the crucial role of government as both policymaker and a primary client of CoPS, the study underscores the importance of policy frameworks that actively nurture technological advancement, iterative development, and stable innovation ecosystems. Governments must implement conducive policies across market regulation, financial incentives, technological standards, and environmental management, thereby orchestrating fertile ground for sustained innovation performance.
Despite these comprehensive insights, the research acknowledges several limitations while laying fertile ground for future explorations. For one, the dynamic capability framework employed, while robust, does not account for all potential influencing elements. Attributes such as design transparency and interdependence among innovation subjects remain unexplored yet hold significant promise for advancing innovation efficiency and output expansion. Future research might delve into these areas, enriching the explanatory power of innovation theories in CoPS.
Furthermore, the study is constrained by cross-sectional data based on respondents’ recollections of the entire innovation process. Since CoPS innovation unfolds over project lifecycles encompassing bidding, design, and development phases—with differing actors and tasks—the dynamic processual complexities remain underexplored. Pursuing longitudinal, stage-specific analyses could unravel the temporal evolution of organizational patterns and innovation drivers, yielding more dynamic and actionable insights.
Another critical boundary to the study derives from its Chinese IoT industry focus. Although IoT exemplifies the new generation of information technology, findings may not fully generalize to other industries or geographic regions with disparate economic or cultural characteristics. Future inquiries might extend this analytical lens to CoPS innovation subjects in various global domains, thereby constructing a more globally comprehensive understanding of organizational choices in innovation.
In a field where the convergence of technology development and organizational strategy defines competitive advantage, this research bridges crucial gaps between theory and practice. By systematic dissection and innovative methodological application, it charts the terrain within which innovation actors navigate the complex interplay of capabilities and relationships to carve out distinct organizational patterns. These insights not only enrich academic discourse but also empower enterprises to strategically configure themselves for long-term innovation success in the ever-more interconnected and technologically sophisticated world of Complex Product Systems.
As the innovation ecosystem continues to evolve, the need for adaptable, resilient, and diversified organizational configurations becomes paramount. This work thus resonates as a clarion call for innovation subjects to continuously reassess and realign their core competencies and network relationships, moving beyond one-size-fits-all solutions towards bespoke strategies that reflect their unique contexts and strengths. The dynamic capability lens, illustrated through the intricate world of CoPS, provides both a compass and a roadmap to navigate this complex but promising journey toward sustainable innovation leadership.
Subject of Research: Organizational patterns and innovation dynamics within Complex Product Systems (CoPS) in the Internet of Things (IoT) industry, approached through dynamic capability theory and fsQCA method.
Article Title: How to choose an organization pattern in the innovation of the complex product systems: findings from fsQCA.
Article References:
Hou, J., Zhang, M., Li, K. et al. How to choose an organization pattern in the innovation of the complex product systems: findings from fsQCA.
Humanit Soc Sci Commun 12, 938 (2025). https://doi.org/10.1057/s41599-025-05251-7
Image Credits: AI Generated
