A Socio-Technical Theory of Blockchain Alignment Under Institutional Fragmentation

Blockchain technologies are frequently associated with decentralization, disintermediation, and systemic disruption. Yet adoption outcomes across sectors and jurisdictions remain highly uneven. Existing scholarship explains these outcomes primarily through technological capability, innovation diffusion, or market incentives, but lacks an integrated framework capable of explaining how blockchain infrastructures evolve within fragmented institutional environments.
This paper develops the Blockchain System Alignment Framework (BSAF) as a socio-technical theory of blockchain alignment under conditions of institutional fragmentation. The framework argues that blockchain adoption and infrastructural scaling depend on conjunctural alignment across three interdependent dimensions: technical viability, institutional compatibility, and economic incentive coherence. Rather than conceptualizing blockchain as an inherently disruptive technology, the paper argues that blockchain systems become system-reconfiguring only when governance structures, interoperability conditions, and stakeholder coordination mechanisms evolve in mutually reinforcing ways.
Drawing on comparative institutional analysis across stablecoins and central bank digital currencies (CBDCs), tokenized asset markets, and blockchain-enabled supply chains, the paper demonstrates how fragmented governance regimes, standards competition, and asymmetrical incentive structures shape adoption trajectories across domains. The analysis further shows that blockchain infrastructures not only operate within fragmented institutional environments but may also generate new forms of fragmentation through competing standards, governance architectures, and coordination asymmetries.
The paper contributes to socio-technical transition theory, institutional political economy, and digital infrastructure studies by reframing blockchain as a conditional coordination infrastructure embedded within evolving governance systems rather than as a universally transformative technology. More broadly, the findings suggest that the future trajectory of blockchain infrastructures will depend less on technological performance alone than on the capacity of institutions, governance regimes, and stakeholders to coordinate under conditions of geopolitical and institutional fragmentation.

Blockchain; Socio-Technical Alignment; Institutional Fragmentation; Digital Infrastructure; Political Economy; System Reconfiguration; Institutional Compatibility; Tokenization; CBDCs

1. Abbott, K. W., & Snidal, D. (2001). International ‘standards’ and international governance. Journal of European Public Policy, 8(3), 345–370. https://doi.org/10.1080/13501760110056013 [Google Scholar] [Crossref]

2. Ahmed, M. F., Rahman, M. M., & Akter, S. (2025). Reducing supply chain disruptions, costs, and waste using AI and blockchain to strengthen U.S. economic resilience. Journal of Tianjin University Science and Technology, 58(7). https://doi.org/10.5281/zenodo.16028865 [Google Scholar] [Crossref]

3. Alstyne, M. W. Van, Parker, G. G., & Choudary, S. P. (2016). Pipelines, platforms, and the new rules of strategy. Harvard Business Review, 94(4), 54–62. [Google Scholar] [Crossref]

4. Atzori, M. (2015). Blockchain technology and decentralized governance: Is the state still necessary? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2709713 [Google Scholar] [Crossref]

5. Benkler, Y. (2006). The wealth of networks. Yale University Press. [Google Scholar] [Crossref]

6. Bryman, A., & Bell, E. (2015). Business research methods (4th ed.). Oxford University Press. [Google Scholar] [Crossref]

7. Catalini, C., & Gans, J. S. (2017). Some simple economics of the blockchain. Rotman School of Management Working Paper No. 2874598; MIT Sloan Research Paper No. 5191-16. https://doi.org/10.2139/ssrn.2874598 [Google Scholar] [Crossref]

8. Celestin, M., Vasuki, M., Dinesh Kumar, A., & Alghazali, T. A. H. (2025). The synergy between blockchain technology and fintech in reinventing global financial systems. International Journal of Engineering Research and Modern Education, 10(2), 97–109. https://doi.org/10.5281/zenodo.17328416 [Google Scholar] [Crossref]

9. Christensen, C. M. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Harvard Business School Press. [Google Scholar] [Crossref]

10. Coase, R. H. (1937). The nature of the firm. Economica, 4(16), 386–405. [Google Scholar] [Crossref]

11. Edwards, P. N. (2010). A vast machine: Computer models, climate data, and the politics of global warming. MIT Press. [Google Scholar] [Crossref]

12. Eisenhardt, K. M., & Graebner, M. E. (2007). Theory building from cases: Opportunities and challenges. Academy of Management Journal, 50(1), 25–32. [Google Scholar] [Crossref]

13. Farrell, H., & Newman, A. L. (2019). Weaponized interdependence: How global economic networks shape state coercion. International Security, 44(1), 42–79. https://doi.org/10.1162/isec_a_00351 [Google Scholar] [Crossref]

14. García Sáez, M. I. (2020). Blockchain-enabled platforms: Challenges and recommendations. SSRN Electronic Journal. [Google Scholar] [Crossref]

15. Geels, F. W. (2002). Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study. Research Policy, 31(8–9), 1257–1274. https://doi.org/10.1016/S0048-7333(02)00062-8 [Google Scholar] [Crossref]

16. Geels, F. W., & Schot, J. (2007). Typology of sociotechnical transition pathways. Research Policy, 36(3), 399–417. https://doi.org/10.1016/j.respol.2007.01.003 [Google Scholar] [Crossref]

17. Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard Business Review, 95(1), 118–127. [Google Scholar] [Crossref]

18. International Monetary Fund (IMF). (2023). Fintech and financial inclusion database 2023 update. https://doi.org/10.5089/9781513592038.082 [Google Scholar] [Crossref]

19. Jasanoff, S. (2004). States of knowledge: The co-production of science and social order. Routledge. [Google Scholar] [Crossref]

20. Jeyaraj, A., Rottman, J. W., & Lacity, M. C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21(1), 1–23. [Google Scholar] [Crossref]

21. Kashem, M. A., Shamsuddoha, M., Nasir, T., & Chowdhury, A. A. (2023). Supply chain disruption versus optimization: A review on artificial intelligence and blockchain. Knowledge, 3(1), 80–96. [Google Scholar] [Crossref]

22. Keskin, M. (2026). Sustainable financing architecture for digitalised international trade: The transformation of the banking sector. In I. Akben (Ed.), Digitalization and sustainability in international trade (pp. 71–97). Özgür Publications. https://doi.org/10.58830/ozgur.pub1231 [Google Scholar] [Crossref]

23. Mazzucato, M. (2013). The entrepreneurial state: Debunking public vs. private sector myths. Anthem Press. [Google Scholar] [Crossref]

24. North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge University Press. [Google Scholar] [Crossref]

25. OECD. (2024). OECD Digital Finance Report 2024. Organisation for Economic Co-Operation and Development. https://doi.org/10.1787/dfin-2024-en [Google Scholar] [Crossref]

26. Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge University Press. [Google Scholar] [Crossref]

27. Öztürk, O. (2026). The role of digital product passport in sustainable international trade. In I. Akben (Ed.), Digitalization and sustainability in international trade (pp. 21–32). Özgür Publications. https://doi.org/10.58830/ozgur.pub1231 [Google Scholar] [Crossref]

28. Perez, C. (2002). Technological revolutions and financial capital: The dynamics of bubbles and golden ages. Edward Elgar. [Google Scholar] [Crossref]

29. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. [Google Scholar] [Crossref]

30. Srnicek, N. (2017). Platform capitalism. Polity Press. [Google Scholar] [Crossref]

31. Star, S. L. (1999). The ethnography of infrastructure. American Behavioral Scientist, 43(3), 377–391. https://doi.org/10.1177/00027649921955326 [Google Scholar] [Crossref]

32. Swan, M. (2015). Blockchain: Blueprint for a new economy. O’Reilly Media. [Google Scholar] [Crossref]

33. Tapscott, D., & Tapscott, A. (2016). Blockchain revolution: How the technology behind Bitcoin is changing money, business, and the world. Portfolio. [Google Scholar] [Crossref]

34. Williamson, O. E. (1985). The economic institutions of capitalism. Free Press. [Google Scholar] [Crossref]

35. Winner, L. (1980). Do artifacts have politics? Daedalus, 109(1), 121–136. [Google Scholar] [Crossref]

36. Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). Sage. [Google Scholar] [Crossref]

37. Zysman, J., & Kenney, M. (2020). The next phase in the digital revolution: Intelligent tools, platforms, growth, employment. Communications of the ACM, 63(2), 54–63. https://doi.org/10.1145/3358902 [Google Scholar] [Crossref]

• Impact of Leadership Styles on Employee Adaptability During Digital Transformation: Change Management Practices and Organizational Support as Moderators
• Impact of Artificial Intelligence on Assessment, Engagement and Motivation among Secondary School Students in Kaduna State, Nigeria
• “Mumbai City – The Wizard of Fashion: A Perspective Analysis on India’s Emerging Digital Marketing in the Fashion Industry.”