Business Systems in Context

Business systems encompass the integrated frameworks through which organisations collect, process and distribute information to support decision-making, operations and strategic initiatives. Core components include transactional platforms—such as enterprise resource planning (ERP) for finance, manufacturing and supply chain; business intelligence (BI) systems for reporting and analytics; and specialised modules for customer relationship, human resources and digital content. Effective deployment demands not only technical alignment—through data governance, system interoperability and service-oriented architectures—but also organisational integration, ensuring processes, culture and leadership reinforce one another. In an era of digital transformation, firms must balance operational efficiency with agility: they need stable back-office solutions that sustain everyday performance while remaining flexible enough to accommodate rapid shifts in market demands, regulatory requirements and emerging technologies. Increasingly, business systems extend beyond single enterprises to orchestrate value-added services across networks of partners, suppliers and customers, giving rise to distributed ecosystems in which strategic partnerships and process collaboration underpin competitive advantage.

Research from Nature Portfolio

Empirical studies in large manufacturing organisations demonstrate that user satisfaction with ERP implementations depends critically on system quality, service quality and ease of use rather than on perceived usefulness alone. In one investigation of a shipbuilding company, active user participation, stable system performance and responsive support services were shown to drive satisfaction and acceptance, underscoring the need for inclusive design and reliable IT operations to sustain ERP engagement.

In the small and medium-sized enterprise sector, research integrating information-systems success, technology acceptance and expectation-confirmation models has identified system quality, information quality, perceived usefulness, perceived ease of use and confirmation of expectations as key determinants of SMEs’ intention to continue using digital accounting platforms. This combined model outperformed traditional frameworks in explaining ongoing adoption, emphasising that alignment between system capabilities and user expectations is vital for the long-term viability of enterprise systems in resource-constrained environments.

Research from all publishers

In the domain of management accounting, extended information-systems success models reveal that system quality, data quality, information quality and service quality each drive both routine and advanced use of BI systems. Notably, advanced BI use yields greater performance gains, with self-efficacy playing a larger role when tasks are complex. These findings highlight the importance of high-quality data and supportive services to elevate BI from a reporting tool to a strategic decision-support platform.

Healthcare settings offer illustrative evidence of how technical and organisational factors interact to shape system adoption. A study of hospital information systems for infection prevention and control found that system quality, information quality and service quality significantly influence clinician satisfaction, intention to use and perceived benefits. Furthermore, organisational culture emerged as a critical moderator, indicating that even well-designed systems require supportive norms and training to realise their full potential.

Business Systems in Context publication trend

The graph below shows the total number of articles in business systems in context across all publications each year (not limited to Nature Index journals).

Technical terms

Enterprise resource planning (ERP): An integrated suite of applications that manage core business processes—such as finance, manufacturing, supply chain and human resources—using a shared data model to provide real-time transactional information.

Business intelligence (BI): Tools and applications that analyse organisational data—drawing on system, data and service quality—to deliver descriptive, predictive and prescriptive insights for strategic and operational decision-making.

System quality: The performance attributes of an information system, including reliability, usability and response time, that underpin user satisfaction.

Information quality: The accuracy, relevance and timeliness of data produced and disseminated by a system, essential for trustworthy analytics and reporting.

Service quality: The degree of support provided to users—encompassing training, help-desk response and customisation—that facilitates acceptance and effective system use.

Continuance intention: A user’s resolved commitment to keep using an information system over time, reflecting confirmation of expectations and ongoing perceived value.

References

1. Mechanisms for successful management of enterprise resource planning from user information processing and system quality perspective. Scientific Reports (2023).
2. What determines digital accounting systems’ continuance intention? An empirical investigation in SMEs. Humanities and Social Sciences Communications (2023).
3. Determinants and consequences of routine and advanced use of business intelligence (BI) systems by management accountants. Information & Management (2024).
4. Factors Influencing Clinicians’ Use of Hospital Information Systems for Infection Prevention and Control: Cross-Sectional Study Based on the Extended DeLone and McLean Model. Journal of Medical Internet Research (2023).