Inductive Empiricism, Theory Specialization and Scientific Idealization in IS Theory Building
Juhani Iivari
Abstract
Open-access reader
Juhani Iivari
Abstract
Open-access reader
This paper distinguishes and discusses three strategies for theory building in Information Systems (IS) - inductive empiricism, theory specialization, and scientific idealization - and contrasts them in terms of three desiderata of theories - realism, generality, and precision - and the tradeoffs between them. Inductive empiricism, emphasizing realism and generality, represents the received view with the classic Grounded Theory Methodology as a prime example. This paper argues for openness to theory specialization in practical disciplines such as IS. Theory specialization implies sacrificing a generality of theories for their realism and precision. The distinctive attention of the paper lies in scientific idealization, sacrificing the realism of theories for their precision and generality. It has almost been completely omitted in the literature on IS theory building. The special focus of this paper lies in IT applications as a category of IT artifacts and in design-oriented theories that provide knowledge of how to design “better” IT applications. This paper illustrates its points using TAM/UTAUT research.
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This paper distinguishes and discusses three strategies for theory building in Information Systems (IS) - inductive empiricism, theory specialization, and scientific idealization - and contrasts them in terms of three desiderata of theories - realism, generality, and precision - and the tradeoffs between them. Inductive empiricism, emphasizing realism and generality, represents the received view with the classic Grounded Theory Methodology as a prime example. This paper argues for openness to theory specialization in practical disciplines such as IS. Theory specialization implies sacrificing a generality of theories for their realism and precision. The distinctive attention of the paper lies in scientific idealization, sacrificing the realism of theories for their precision and generality. It has almost been completely omitted in the literature on IS theory building. The special focus of this paper lies in IT applications as a category of IT artifacts and in design-oriented theories that provide knowledge of how to design “better” IT applications. This paper illustrates its points using TAM/UTAUT research.
Key concepts: Idealization, Generality, Empiricism, Epistemology, Scientific theory, Realism, Scientific realism, Philosophy of science