Abstract
Among the defining characteristics of a healthy research discipline is the ability to correct its knowledge if more recent evidence creates grounds for this. Studies that reveal errors in earlier theories demonstrate, in line with Karl Popper’s thinking, an approach called falsificationism. They complement approaches aimed at developing and expanding knowledge by generalising empirical observations or postulating new contributions and testing them. The paper presents an analysis that applies this categorisation to abstracts of research papers (N = 5,202) in the eight leading IS journals. Machine-learning-based classification determined that only 7.0% of the papers manifested any clear form of knowledge-contestation, such as falsification, in the approach or findings presented. In light of this, we call on IS researchers to increase the falsification and knowledge-contestation in their research, to nurture more valid theories, methods, and practices, thereby achieving greater societal impact. We present two suitable IS research designs accordingly: knowledge-contesting comparisons and knowledge-contesting replications. We also discuss how these designs, exemplifying opportunities to increase the number of knowledge-contesting studies in the field, can be applied in both positivist and interpretivist research epistemology.
Original language | English |
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Pages (from-to) | 65-83 |
Number of pages | 19 |
Journal | European Journal of Information Systems |
Volume | 29 |
Issue number | 1 |
Early online date | 24 Nov 2019 |
DOIs | |
Publication status | Published - 2 Jan 2020 |
MoE publication type | A1 Journal article-refereed |
Keywords
- epistemology
- falsification
- machine learning
- Methodology
- philosophy of science
- Prof. Frantz Rowe
- scientometric research