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Robotic System Adoption and Business Model Innovation: A Cross-level Study with the Serially Moderated–Mediated Model

Adil Riaz et al.

FIIB Business Review2026https://doi.org/10.1177/23197145261416250article
AJG 1ABDC B
Weight
0.50

Abstract

This study examines how the adoption of robotic systems (RSA) promotes business model innovation (BMI) in manufacturing firms, with a particular focus on the dual and serial mediation roles of innovation capabilities and organizational agility. Grounded in the dynamic capabilities theory and the technology acceptance model, this research also examines whether trust in human–robot interaction moderates the influence of RSA on innovation capabilities and BMI. Due to the multilevel nature of the constructs, the study adopts a cross-level design, collecting data from managers and employees of Chinese manufacturing firms. Using partial least squares structural equation modelling (PLS-SEM), we find that RSA is positively associated with BMI, innovation capabilities and organizational agility. Furthermore, both innovation capabilities and organizational agility mediate the relationship between RSA and BMI, with evidence supporting a serial mediation pathway. Additionally, human–robot interaction trust strengthens the impact of RSA on both innovation capabilities and BMI. These findings underscore the strategic importance of adopting robotic systems and cultivating trust in human–robot collaboration to enhance innovation potential and drive business model transformation in manufacturing firms.

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https://doi.org/https://doi.org/10.1177/23197145261416250

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@article{adil2026,
  title        = {{Robotic System Adoption and Business Model Innovation: A Cross-level Study with the Serially Moderated–Mediated Model}},
  author       = {Adil Riaz et al.},
  journal      = {FIIB Business Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/23197145261416250},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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