From Linear Models to Complex Systems: Rethinking Technology Diffusion with Multiplex Network Theory

Classic models like Rogers’ Diffusion of Innovations or the Technology Acceptance Model, referenced in several reviewed works (e.g., Al-shanableh et al., 2024; Bisi, 2024), typically assume a single, homogenous network or a linear chain of adoption. However, real-world diffusion occurs across interwoven networks—think social ties, trade relationships, regulatory connections, and knowledge flows. Drawing inspiration from Zhang et al. (2023) but going much further, this research would use multiplex (multi-layer) network theory to simulate and empirically test how innovations spread when actors are embedded in several networks simultaneously. For example, how does a new technology spread differently when social support is strong but regulatory ties are weak? This approach could reveal “network bottlenecks” invisible to single-layer models, offering a leap forward in both theory and actionable insight for complex innovation ecosystems.

References:

1. Evaluating the Relationship Between Information Technology Adoption and Healthcare Outcomes in Sub-Saharan Africa. Abidemi Bisi (2024). African Journal of Information and Knowledge Management.
2. The adoption of big data analytics in Jordanian SMEs: An extended technology organization environment framework with diffusion of innovation and perceived usefulness. Najah Al-shanableh, M. Alzyoud, Saleh Alomar, Yousef Kilani, Eman Nashnush, S. Al-Hawary, Ala'a M. Al-Momani (2024). International Journal of Data and Network Science.
3. Research on the evolution of disruptive technological innovation cooperation network: a case study of blockchain and automatic driving technology. Jing Zhang, Yazhuang Cao, Neng Shen (2023). Technology Analysis & Strategic Management.