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From its earliest days, information systems (IS) research has been pulled between two competing impulses: the desire to treat information systems as technical artifacts that can be engineered for efficiency, and the recognition that these systems are embedded in complex social, organizational, and political contexts. This tension has driven a series of paradigm shifts, each emerging as a response to the limitations of its predecessors, and has left the field today with a pluralistic landscape of coexisting and competing frameworks.
The first systematic research framework in IS, the Technical-Rational Paradigm (roughly 1968–1980), approached information systems as purely technical problems. Drawing on management science and computer engineering, it assumed that organizational goals were clear and that better data processing would automatically improve decision-making. Research under this paradigm focused on building models, optimizing algorithms, and measuring system performance. The landmark 1973 paper "A Program for Research on Management Information Systems" by Mason and Mitroff exemplified this view, calling for a science of MIS that would match system designs to decision-maker types. Yet by the late 1970s, a growing number of system failures and user rejections made it clear that technical optimization alone could not explain why systems succeeded or failed in practice.
Sociotechnical Systems Theory (1977–present) emerged as a direct reaction against the Technical-Rational Paradigm. Drawing on the Tavistock tradition from organizational psychology, it argued that any information system must be understood as the joint product of its technical components and the social system of people, work practices, and power relations. Early IS applications, such as Bostrom and Heinen's two-part 1977 MIS Quarterly article "MIS Problems and Failures: A Socio-Technical Perspective," showed that treating technical and social design as interdependent could reduce implementation failures. Sociotechnical Systems Theory did not replace the Technical-Rational Paradigm so much as absorb its technical concerns into a broader framework; it remains active today, especially in participatory design and work-system analysis.
Shortly afterward, the Organizational and Managerial Paradigm (1980–1995) superseded the Technical-Rational Paradigm by reframing IT as a strategic resource rather than a mere tool. Researchers in this tradition, influenced by strategic management and organizational behavior, studied how IT could reshape competitive advantage, alter industry structures, and enable new forms of organizing. The paradigm broadened the unit of analysis from the individual system to the firm and its environment. It retained the positivist, quantitative methods of the Technical-Rational Paradigm but shifted the research questions from technical efficiency to organizational impact and managerial decision-making.
Within the Organizational and Managerial Paradigm, a highly influential but narrower model emerged: the Technology Acceptance Model (TAM) (1989–present). Developed by Fred Davis in his 1989 paper "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology," TAM offered a parsimonious, theory-driven explanation of why individuals adopt or reject new systems. It posited that perceived usefulness and perceived ease of use were the two primary determinants of user acceptance. TAM did not challenge the broader paradigm; rather, it narrowed the focus to individual-level adoption and provided a reliable measurement instrument that became the most widely used model in IS research for decades. TAM remains active today, though it has been extended and critiqued for ignoring social and organizational factors.
By the early 1990s, dissatisfaction with the positivist assumptions underlying both the Technical-Rational and Organizational and Managerial Paradigms gave rise to two distinct but related reactions. The Interpretive Paradigm (1991–present) reacted against the Organizational and Managerial Paradigm by arguing that information systems cannot be understood through objective measurement alone. Drawing on sociology of knowledge and hermeneutics, interpretive researchers such as Walsham (1993) and Orlikowski and Baroudi (1991) insisted that meaning is socially constructed and that researchers must understand the subjective interpretations of users and stakeholders. Their methods—case studies, ethnography, discourse analysis—aimed to produce rich contextual understanding rather than generalizable laws. The Interpretive Paradigm did not reject the importance of organizations or management, but it fundamentally disagreed with the positivist epistemology of its predecessor.
At roughly the same time, Critical Research in Information Systems (1990–present) emerged as a competitor to the Interpretive Paradigm. While both rejected positivism, critical researchers went further by arguing that IS research should expose power imbalances, ideological biases, and structures of domination embedded in information systems. Drawing on critical theory (Habermas, Foucault), scholars such as Hirschheim and Klein (1994) called for research that not only interprets but also emancipates. Critical Research competes with the Interpretive Paradigm over the purpose of research: interpretation versus critique. Both paradigms remain active, with critical research often focusing on issues like surveillance, digital labor, and algorithmic bias.
While interpretive and critical approaches were gaining ground, a very different reaction was taking shape. Design Science Research (DSR) (1995–present) emerged as a direct competitor to the Interpretive Paradigm, arguing that the primary goal of IS research should be the creation of useful artifacts—software, methods, models, and constructs—rather than the understanding of existing systems. Drawing on Herbert Simon's "sciences of the artificial," DSR was formalized in key works by March and Smith (1995) and Hevner et al. (2004). DSR competes with the Interpretive Paradigm over the fundamental purpose of the field: utility versus understanding. While interpretive researchers seek to describe and explain, design scientists aim to build and evaluate. DSR has become a major force in IS, especially in technical subfields like systems analysis and design and enterprise architecture.
Today, five frameworks remain active: Sociotechnical Systems Theory, TAM, Critical Research, the Interpretive Paradigm, and Design Science Research. They coexist in a state of productive tension, each with its own strengths and blind spots. Sociotechnical Systems Theory provides a balanced lens for analyzing work-system redesign. TAM remains the go-to model for quick, quantitative adoption studies. The Interpretive Paradigm excels at uncovering the nuanced meanings that users attach to technology. Critical Research pushes the field to confront ethical and political dimensions. Design Science Research drives innovation in artifact creation.
What these leading frameworks agree on is that context matters: no information system can be understood or designed in isolation from its social, organizational, and historical setting. They also agree that research must be rigorous, though they differ sharply on what rigor means—statistical validity, interpretive depth, critical reflexivity, or practical utility. The deepest disagreement is over the ultimate goal of IS research: whether it should aim to predict and control (TAM, parts of Sociotechnical), to understand and interpret (Interpretive), to critique and emancipate (Critical), or to create and evaluate (DSR). This pluralism is not a sign of fragmentation but of a mature field that has learned to accommodate multiple ways of knowing. The history of IS research is thus a story of successive frameworks that have expanded the field's vision, each building on, reacting against, or competing with its predecessors, and together forming a rich intellectual tapestry.