We begin by distinguishing between the natural sciences and the social sciences, particularly in how knowledge is produced, validated, and applied in each domain. In the natural sciences, such as physics, chemistry, and biology, knowledge is grounded in stable and immutable natural laws. These laws exist independently of human interpretation and allow researchers to deduce hypotheses with a high degree of precision. Because the underlying phenomena are relatively invariant across time and context, natural science research often achieves strong predictability, replicability, and generalizability. If conditions are held constant, outcomes are expected to be the same.
The social sciences, however, operate under fundamentally different conditions. Rather than studying fixed natural laws, social scientists study human behavior, social structures, institutions, technologies, and interactions, all of which are historically situated, context-dependent, and reflexive. Humans learn, adapt, resist, reinterpret, and change their behavior in response to new information, incentives, and environments. As a result, the level of precision and predictability characteristic of the natural sciences is neither achievable nor desirable in the social sciences.
Because social phenomena are shaped by culture, power, norms, incentives, and technology, attempts to formulate universal, law-like explanations often fail or oversimplify reality. In fields such as Information Systems, where people interact with digital artifacts, organizations, and environments, the goal is not to discover timeless laws but to develop theoretical explanations that help us understand patterns, mechanisms, and conditions under which certain outcomes are more or less likely to occur. Social science theories thus aim for analytical generalization rather than mechanical prediction.
One important advantage of Information Systems research, in particular, is the pliability of knowledge. Unlike natural laws, which are fixed and non-negotiable, social science knowledge is inherently interpretive and evolving. Theories are not final truths but lenses, or ways of seeing and explaining phenomena. This flexibility allows IS researchers to reinterpret existing theories, combine perspectives, shift levels of analysis, and apply established ideas to new technological contexts.
Importantly, this manipulation of knowledge should not be understood as deception. Rather, it reflects the scholarly responsibility to position contributions strategically, framing research in a way that highlights novelty, relevance, and theoretical value. IS scholars routinely adapt established theories such as institutional theory, sociotechnical systems, or the resource-based view to emerging contexts like artificial intelligence, platforms, or digital ecosystems. This adaptability is not a weakness of the field; it is one of its greatest strengths.
At the same time, academic institutions and peer reviewers tend to be inherently conservative. Reviewers evaluate new work using the cognitive and theoretical tools they already possess. As a result, research that deviates too far from the existing knowledge base may be perceived as unclear, underdeveloped, or insufficiently grounded, regardless of its potential value. This conservatism serves an important function. It maintains standards, ensures cumulative knowledge, and prevents intellectual fragmentation. However, it also creates barriers for highly novel or unconventional ideas.
For PhD students and early-career scholars, this reality has important implications. Early in one’s career, researchers often adopt more conservative theoretical and methodological choices, building directly on established theories, accepted methods, and familiar scholarly conversations. This is not intellectual timidity but strategic learning. By first demonstrating competence within existing paradigms, scholars earn credibility and legitimacy within the field.
As researchers progress in their careers, building reputations, networks, and publication records, they gradually acquire greater intellectual license. Senior scholars are better positioned to take theoretical risks, challenge dominant assumptions, and introduce paradigm-shifting ideas because they are already recognized as legitimate contributors. Even then, successful boundary-pushing is rarely reckless. It is typically anchored in deep familiarity with the existing literature and framed in ways that allow the academic community to make sense of what is new.
In sum, the difference between natural and social sciences is not one of rigor but of epistemological orientation. Information Systems research thrives precisely because it embraces the complexity, uncertainty, and malleability of social reality. The central challenge of IS scholarship is to balance innovation with intelligibility, pushing knowledge forward while remaining connected to the intellectual foundations that make progress possible.
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