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This study aims to examine the mediating effects of corporate governance mechanisms like the board of directors on the association between disruptive technology adoption by audit clients and the risk of material misstatements, including inherent risk and control risk. In particular, the authors study the mediating effects of board characteristics such as board size, independence and gender diversity.

Based on a sample of 100 audit clients listed on the FTSE 100 from 2015 to 2021, this study uses structural equation modelling to test the research objectives.

The findings indicate a significant and negative association between disruptive technology adoption by audit clients and inherent risk. However, there is no significant evidence observed for control risk. The utilisation of disruptive technology by the audit client has a significant impact on the board characteristics, resulting in an increase in board size, greater independence and gender diversity. The authors also find strong evidence that board independence mediates the association between disruptive technology usage and both inherent risk and control risk. In addition, board size and gender exhibit distinct and differential mediating effects on the association and across the two types of risks.

The study reveals that the significant role of using disruptive technology by audit clients in reducing the risk of material misstatements is closely associated with the board of directors, which makes audit clients place greater emphasis on the construction of effective corporate governance.

This study offers essential primary evidence that can assist policymakers and standard setters in formulating guidance and recommendations for board size, independence and gender quotas, ensuring the enhancement of effective governance and supporting the future of audit within the next generation of digital services.

With respect to relevant stakeholders, it is imperative for audit clients to recognise that corporate governance represents a fundamental means of addressing the ramifications of applying disruptive technology, particularly as they pertain to inherent and control risks within the audit client.

This study contributes to the existing literature by investigating the joint impact of corporate governance and the utilisation of disruptive technology by audit clients on inherent risk and control risk, which has not been investigated by previous research.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.