Enterprise Resource Planning–enabled Data Integration and Decision Support Performance in Smart Manufacturing

Enterprise resource planning systems have become fundamental components of smart manufacturing environments, enabling real-time information sharing, process integration, and data-driven decision-making across increasingly digitalized production networks. The rapid adoption of Internet of Things technologies, cyber-physical systems, cloud computing platforms, and manufacturing execution systems has significantly increased the volume, variety, and complexity of manufacturing data, making effective data integration a critical requirement for organizational competitiveness and operational excellence. This study investigates the relationship between enterprise resource planning-enabled data integration and decision support performance within smart manufacturing environments. Primary data were collected from 250 professionals, including production managers, information technology managers, operations managers, quality managers, and supply chain managers, representing five manufacturing sectors i.e., automotive, electronics, food and beverage, pharmaceuticals, and machinery. The findings confirm that enterprise resource planning-enabled data integration significantly enhances decision support performance, highlighting the strategic importance of integrated information architectures in facilitating timely, accurate, and effective managerial decisions. Furthermore, cybersecurity governance, cross-platform interoperability, and workforce digital readiness strengthen this relationship, indicating that technological integration generates greater value when supported by robust security practices, seamless system compatibility, and digitally competent employees. Additional analyses reveal that organizational characteristics, including firm size and industry type, influence decision support outcomes, explaining that the effectiveness of data integration initiatives may vary across manufacturing contexts. The findings offer practical implications for manufacturing managers, Enterprise Resource Planning developers, and Industry 4.0 policymakers seeking to design secure, interoperable, and workforce-oriented digital infrastructures that enhance decision quality and organizational performance in increasingly complex manufacturing environments.