Abstract
Theorizing about the definition, nature, and importance of theory and theorizing absorbs too much energy and attention in the IS discipline. Achieving the discipline’s goals calls for viewing theory differently and focusing on rigorous generalizations meant as scientific or practical IS knowledge, i.e., abstractions that express valuable and logically and/or empirically justifiable ideas concerning IS-related entities, practices, and phenomena about which knowledge matters. There is no reason to think that theories are inherently superior to other types of generalizations such as statements, axioms, principles, guidelines, models, ontologies, or methods. Criteria for evaluating rigorous generalizations include 1) conceptual clarity, 2) domain clarity, 3) appropriate parsimony, 4) relevant exemplars, 5) omissions, 6) likely lifespan, 7) convincing justification, 8) value relative to understanding, comparison, explanation, prediction, design, or other uses of knowledge. Focusing on rigorous generalizations instead of theory and theorizing could increase the production of useful IS-related knowledge.
Recommended Citation
Alter, Steven, "Vanquishing “Theory As King” By Focusing Instead On Rigorous Generalizations" (2024). ECIS 2024 Proceedings. 2.
https://aisel.aisnet.org/ecis2024/debates/debates/2
Vanquishing “Theory As King” By Focusing Instead On Rigorous Generalizations
Theorizing about the definition, nature, and importance of theory and theorizing absorbs too much energy and attention in the IS discipline. Achieving the discipline’s goals calls for viewing theory differently and focusing on rigorous generalizations meant as scientific or practical IS knowledge, i.e., abstractions that express valuable and logically and/or empirically justifiable ideas concerning IS-related entities, practices, and phenomena about which knowledge matters. There is no reason to think that theories are inherently superior to other types of generalizations such as statements, axioms, principles, guidelines, models, ontologies, or methods. Criteria for evaluating rigorous generalizations include 1) conceptual clarity, 2) domain clarity, 3) appropriate parsimony, 4) relevant exemplars, 5) omissions, 6) likely lifespan, 7) convincing justification, 8) value relative to understanding, comparison, explanation, prediction, design, or other uses of knowledge. Focusing on rigorous generalizations instead of theory and theorizing could increase the production of useful IS-related knowledge.
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