Towards the improved treatment of generalization of knowledge claims in IS research : drawing general conclusions from samples Seddon, Peter B. and Scheepers, Rens 2012, Towards the improved treatment of generalization of knowledge claims in IS research : drawing general conclusions from samples, European journal of information systems, vol. 21, pp. 6-21, doi: 10.1057/ejis.2011.9. Attached Files Name Description MIMEType Size Downloads Title Towards the improved treatment of generalization of knowledge claims in IS research : drawing general conclusions from samples Author(s) Seddon, Peter B. Scheepers, Rens orcid.org/0000-0003-2791-6513 Journal name European journal of information systems Volume number 21 Start page 6 End page 21 Total pages 16 Publisher Palgrave Macmillan Ltd. Place of publication Basingstoke, England Publication date 2012 ISSN 0960-085X 1476-9344 Keyword(s) research methodology other-settings generalization external validity sample P-value Bayesian statistics Summary This paper presents a framework for justifying generalization in information systems (IS) research. First, using evidence from an analysis of two leading IS journals, we show that the treatment of generalization in many empirical papers in leading IS research journals is unsatisfactory. Many quantitative studies need clearer definition of populations and more discussion of the extent to which ‘significant’ statistics and use of non-probability sampling affect support for their knowledge claims. Many qualitative studies need more discussion of boundary conditions for their sample-based general knowledge claims. Second, the proposed new framework is presented. It defines eight alternative logical pathways for justifying generalizations in IS research. Three key concepts underpinning the framework are the need for researcher judgment when making any claim about the likely truth of sample-based knowledge claims in other settings; the importance of sample representativeness and its assessment in terms of the knowledge claim of interest; and the desirability of integrating a study’s general knowledge claims with those from prior research. Finally, we show how the framework may be applied by researchers and reviewers. Observing the pathways in the framework has potential to improve both research rigour and practical relevance for IS research. Language eng DOI 10.1057/ejis.2011.9 Field of Research 080699 Information Systems not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2011, Operational Research Society Ltd. All rights reserved Persistent URL http://hdl.handle.net/10536/DRO/DU:30036689 Document type: Journal Article Collections: Faculty of Business and Law School of Information and Business Analytics 2018 ERA Submission Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 16 Aug 2011, 15:40:10 EST Wed, 17 Aug 2011, 16:45:34 EST Wed, 17 Aug 2011, 16:46:23 EST Wed, 17 Aug 2011, 16:47:19 EST Fri, 27 Jan 2012, 11:15:12 EST Fri, 27 Jan 2012, 11:15:43 EST Fri, 27 Jan 2012, 11:17:32 EST Tue, 14 Feb 2012, 10:16:48 EST Tue, 14 Feb 2012, 10:18:55 EST Tue, 14 Feb 2012, 13:39:07 EST Tue, 30 Apr 2013, 10:27:30 EST Wed, 01 May 2013, 08:38:39 EST Wed, 01 May 2013, 08:53:38 EST Tue, 04 Jun 2013, 14:10:50 EST Mon, 16 Jun 2014, 18:44:49 EST Tue, 03 Feb 2015, 12:51:11 EST Filtered Full Citation counts:   Cited 73 times in TR Web of Science Cited 83 times in Scopus Search Google Scholar Access Statistics: 830 Abstract Views, 13 File Downloads  -  Detailed Statistics Created: Tue, 16 Aug 2011, 15:39:57 EST by Katrina Fleming