Supply chains unchained: how blockchain sparks a self-organized structure

Blockchain technologies are perceived as groundbreaking solutions that effectively support a wide array of organizational domains. One such domain that remains profoundly unexplored is the ability of supply chains to self-organize. This paper aims to explore the role of blockchain in enhancing the capability of supply chains to self-organize. Using the tenets of Complex Adaptive Systems (CAS) theory, we describe how the main features of blockchain, smart contracts, and consensus mechanisms can affect the way supply chains self-organize. The study employs a narrative literature review approach, focusing particularly on integrating the constructs of blockchain and self-organization within the supply chain framework. To do that, we followed the IMRaD approach (Introduction, Methods, Results, and Discussion). The results indicate that blockchain technologies have the potential to enable supply chains to self-organize. Although the application of blockchain in the supply chain context is still in its infancy, the study shows that there are numerous opportunities to improve internal processes, enabling the supply chain to become self-organized. The potential areas of application include heterogeneous agents and interactions, which can be supported by a distributed ledger, decentralization, and autonomy, enhanced by blockchain decentralization and control by influence. Moreover, the study advances CAS theory from abstract organizational concepts into concrete operational reality. Rather than merely digitizing traditional centralized structures, blockchain introduces “control by influence”, an algorithmically mediated coordination model operating in the middle ground between rigid top-down hierarchy and complete, unguided autonomy. By redistributing custody, ownership, and data access rights across network nodes, blockchain fundamentally alters governance logic. Another key theoretical and managerial finding of this study lies in how spontaneity functions across different agent compositions. While strict consensus rules maximize deterministic efficiency for fully digital agents, they also strip away contextual adaptability. Conversely, consensus mechanisms enhance spontaneity when human-inclusive agents remain in the loop. Managers need therefore to strategically delineate where full automation creates value and where human involvement is necessary to maintain strategic flexibility and relationship management.