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Purpose

This study examines how digital transformation capability influences financial performance through the mediating role of accounting information system (AIS) quality. Drawing largely on the resource orchestration theory, it explains how firms translate digital capabilities into financial outcomes by effectively structuring, bundling, and leveraging accounting and digital resources.

Design/methodology/approach

Data were collected from senior managers of Iranian listed companies and complemented with financial statement indicators. Using partial least squares structural equation modeling (PLS-SEM), the study examines the direct and indirect relationships among digital transformation capability, AIS quality and six financial metrics, namely return on assets (ROA), return on equity (ROE), return on sales (ROS), profitability, inventory turnover and total asset turnover.

Findings

Digital transformation capability does not have a significant direct effect on any financial performance indicators. However, AIS quality demonstrates significant positive effects on profitability and ROA, while its relationships with other performance measures remain insignificant. Furthermore, digital transformation capability strongly improves AIS quality, which in turn mediates its relationship with financial performance; specifically, it significantly mediates the relationship between digital transformation capability and profitability, and marginally mediates the relationship with ROA. The findings show that the financial benefits of digital transformation arise primarily from orchestrating high-quality AIS rather than from digital investment alone.

Originality/value

This study extends resource orchestration theory to the AIS domain by revealing how AIS quality functions as the orchestration mechanism linking digital transformation capability to financial performance. By examining firms in an emerging market context, the study provides novel insights into how digital capabilities are translated into financial outcomes under conditions of resource constraints and regulatory complexity.

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