Demystifying beliefs about the natural sciences in information system

Siponen, Mikko T.; Klaavuniemi, Tuula

doi:10.1177/0268396220901535

Cited by 15 publications

(22 citation statements)

References 63 publications

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“…The dual nature of science in terms of its processes (verb) and its outcomes (noun) provides complementary but separable lens for viewing the quality of scientific research in IS. While Siponen and Klaavuniemi (2020) critique IS research projects on their appropriation and use of scientific methods (process view), this brief commentary argues for assessing the quality of IS research projects on their innovative research contributions (outcome view) to descriptive and prescriptive knowledge bases. This knowledge-based outcome view emphasizes a philosophy of pragmatism, which is expressed in DSR as the requirement to solve real-world problems with practical solutions (Hevner et al, 2004).…”

Section: Resultsmentioning

confidence: 99%

“…The interesting and insightful paper by Siponen and Klaavuniemi (2020) calls out instances of misunderstandings and misapplications of natural science methods in IS research. While these examples provide largely valid critiques, I observe that the focus of the essay is on the use of scientific methods (verb).…”

Section: Introductionmentioning

confidence: 99%

“…I suggest in this commentary that the dual lens of scientific knowledge (noun) offers a more precise and, perhaps, a more useful way of evaluating scientific advances in IS research. I begin by briefly responding to several points in the Siponen and Klaavuniemi (2020) paper that reference quotations from the Hevner et al’s (2004) paper on design science research (DSR). The remainder of the commentary applies the lens of advancing scientific knowledge to IS research.…”

Section: Introductionmentioning

confidence: 99%

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The duality of science: Knowledge in information systems research

Hevner

2020

Journal of Information Technology

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Rigorous research in Information Systems requires an understanding of how scientific foundations drive both the process and outcome. This science duality addresses the effective application of the scientific method (process) as well as the advance of knowledge (outcome) from the research project. This commentary responds to Siponen and Klaavuniemi’s paper with a focus on the uses of knowledge in Information Systems research.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The duality of science: Knowledge in information systems research

Hevner

2020

Journal of Information Technology

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“…ethics of AI), however, may introduce non-human intentionality in IS. We proposed that we can also learn from NS despite the differences (Siponen and Klaavuniemi, this issue): “Many differences exist between IS and the natural sciences, and thus IS should not blindly follow the natural sciences. However, there is much that IS research could learn and adopt from natural science research.”…”

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confidence: 99%

“…Mingers (this issue) criticizes that we did not put forward “an alternative approach,” or a model. We in Siponen and Klaavuniemi (this issue) did not introduce a specific model or approach. However, Siponen and Klaavuniemi (this issue) recommended several issues for future consideration.…”

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confidence: 99%

On natural science beliefs in IS: Short comments to commentators

Siponen

Klaavuniemi

2020

Journal of Information Technology

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McBride (in this issue) rightfully stresses some differences between IS and natural sciences (NS). For him, for example, the IS phenomenon is more complex than cancer biology. This is questionable. 1 The complexity, however, may be different. Another difference noted by McBride (this issue) is human intentionality, which NS phenomena lack. AI research issues (e.g. ethics of AI), however, may introduce non-human intentionality in IS. We proposed that we can also learn from NS despite the differences (Siponen and Klaavuniemi, this issue): "Many differences exist between IS and the natural sciences, and thus IS should not blindly follow the natural sciences. However, there is much that IS research could learn and adopt from natural science research." Hevner (this issue) clarifies that the goal of scientific research is truth-not absolute truth. This clarification is important. However, it remains to be seen how idealizations common in sciences are compatible with this view. In addition, many candidates for "laws" in IS, including design science, seems more rightly probabilistic statements rather than genuine laws (Siponen and Klaavuniemi, 2020). According to Mingers (this issue), most of Siponen and Klaavuniemi's (this issue) criticism has been covered by critical realism (CR). Although CR advocates in IS often posit CR against, and superior to, positivism and interpretivism, we missed a systematic critique of NS beliefs in IS by CR advocates. Mingers (this issue) criticizes that we did not put forward "an alternative approach," or a model. We in Siponen and Klaavuniemi (this issue) did not introduce a specific model or approach. However, Siponen and Klaavuniemi (this issue) recommended several issues for future consideration. These recommendations were given without restriction to a specific approach, or a philosopher. This is a strength. It allows IS scholars to update their views based on recent developments in the philosophy of science, without imposing any restrictions by a specific philosopher or approach. Mingers (this issue) highlights the promise of mechanismbased explanations (MBEs), as they are often deemed alternative to laws. MBEs are promising, especially given that we hardly have genuine laws or deductive-nomological (D-N)

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The Primary Scientific Contribution is Hardly a Theory in Design Science Research

Siponen

Klaavuniemi

2021

The Next Wave of Sociotechnical Design

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Generally, to publish a paper in a top IS journal, making a new theory contribution is, so we are told, required. Such a requirement also exists in Design Science Research (DSR) literature. We review a number of claims about the necessity of theory as it applies to DSR. We find these claims wanting. For example, medical research and engineering are both called "design science" in Simon's (1996) Sciences of the Artificial. However, most articles in the top medical, computer engineering, and network engineering journals do not develop new theories. Unless the proponents of theories, as the primary vehicle of scientific DSR knowledge, can offer a satisfactory argument for why theories are the primary scientific contribution, we do not have to regard 'theory' as the primary outcome of good scientific research in DSR. If we are correct, then theory is not valuable in its own right in (applied) science, as theory serves higher purposes.

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Demystifying beliefs about the natural sciences in information system

Cited by 15 publications

References 63 publications

The duality of science: Knowledge in information systems research

The duality of science: Knowledge in information systems research

On natural science beliefs in IS: Short comments to commentators

The Primary Scientific Contribution is Hardly a Theory in Design Science Research

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