Business Information Systems Overview

Principles

Definition

Business information systems is an academic field concerned with the integrated study of information technology, data, processes, and organizational context to design, implement, and manage systems that support business operations, management, and strategic decision-making. This field investigates how these systems can be effectively leveraged to enhance organizational efficiency, performance, and competitiveness.

Ontological type

Core Concepts

Business Applications

Theoretical Foundations

Key developments

Key Figures

Strategic IS Alignment era

Ephraim R. McLean [1] was a prominent scholar in the Strategic IS Alignment era, with affiliations at Georgia State University [3] and The University of Texas at El Paso [4]. His key contribution, Information Systems Success: The Quest for the Dependent Variable [7], reframed IS success as a measurable outcome and laid the groundwork for governance, measurement, and impact assessment in this era. Peter B. Seddon [2] was also a central figure during this period, with ties to The University of Melbourne [5] and Temple University [6]. His influential paper A Respecification and Extension of the DeLone and McLean Model of IS Success [8] extended the IS success construct to better capture value realization and contingency effects, reinforcing the measurement and alignment agenda for strategic information systems in this era.

Artifact-Centric Contextualization era

Thomas H. Davenport [1] emerges as a leading figure in artifact-centric business information systems of this era, with notable ties to the University of Florida [3] and Babson College [4]. His 2004 papers, Enterprise systems and ongoing process change [7] and Enterprise systems and the supply chain [8], articulate how enterprise systems drive process reengineering and supply-chain integration, a cornerstone for context-sensitive deployment and user-centered evaluation in artifact-centric design. Gurpreet Dhillon [2], associated with the University of California, San Francisco [5] and Baylor College of Medicine [6] in this era, contributes a framework for context-specific theorizing in information systems. Dhillon's 2013 work, A Framework and Guidelines for Context-Specific Theorizing in Information Systems Research [9], provides structured guidelines for tailoring IS theories to organizational context, a vital advancement for contextualized, artifact-centered research in enterprise settings.

Analytics-Driven Transformation era

Samuel Fosso Wamba [1] is a scholar whose work in this analytics-driven transformation era is associated with Georgia Institute of Technology [3] and Université Fédérale de Toulouse Midi-Pyrénées [4]. In 2020, Samuel Fosso Wamba [1] analyzes in the paper 'Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects' [7] how AI-powered transformation can generate business value and improve firm performance, illustrating why AI adoption is central to analytics-enabled decision making. Varun Grover [2] is a scholar whose work at Michigan State University [5] and University of South Carolina [6] reflects the analytics-driven strategy emphasis of this era. Varun Grover [2] advances the field with the 2018 paper 'Creating Strategic Business Value from Big Data Analytics: A Research Framework' [8], which provides a framework for extracting strategic value from big data analytics and highlights governance, measurement, and organizational capabilities as core mechanisms for value capture in analytics-enabled transformation.