The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Abductive reasoning in logistics research
Abstract
Purpose: To construct a framework for exploring and discussing the use of different research approaches – deductive, inductive and abductive – in logistics. Design/methodology/approach: A review of research articles in three major logistics journals (International Journal of Logistics Management, International Journal of Physical Distribution & Logistics Management and Journal of Business Logistics) from 1998 to 2002. Findings: Recognizes the dominance of deductive research in logistics, and the need for more inductive and, in particular, abductive research for theory development. Discusses the use of the abductive research approach in logistics. Research limitations/implications: Keywords searches led to a small sample size; more thorough content analysis is needed to apply the findings from the constructed framework. Practical implications: Useful source of information on the three different research approaches, their possibilities and implications for research. Originality/value: The abductive research approach has not yet been discussed in logistics.
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Cites
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The Logic of Scientific Discovery
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Systematic combining: an abductive approach to case research
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Tolkning och reflektion: Vetenskapsfilosofi och kvalitativ metod
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The complexity of logic-based abduction
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Metadata
- Authors
- Kovács, G., & Spens, K. M.
- Venue
- International Journal of Physical Distribution & Logistics Management
- Publisher
- Emerald
- Published
- 2005-02-01
- Volume
- 35
- Issue
- 2
- Pages
- 132-144
- ISSN
- 0960-0035 (ISSN-L)
- OpenAlex
- W1976075852
- Cited by
- 688
- References
- 21
- FWCI
- 7.32
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.