The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Integrating Positivist and Interpretive Approaches to Organizational Research
Abstract
The interpretive approach to organizational research has been gaining increasing attention as a legitimate alternative to the more traditional positivist approach. The organizational literature has already provided thorough descriptions of each approach, and clarified the differences between them. Indeed, it often appears that the two approaches are opposed, with the differences irreconcilable. This paper will go beyond the differences and establish an integrated framework for the two approaches. An actual, published organizational study will be used as an exemplar for the integrated framework (Nardulli 1978, 1979).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Copi, I. M., Cohen, C., & McMahon, K. (2016) · doi:10.4324/9781315510897 · Cited by 497
Cited by
A Set of Principles for Conducting and Evaluating Interpretive Field Studies in Information Systems1
Klein, H. K., & Myers, M. D. (1999) · MIS Quarterly · doi:10.2307/249410 · Cited by 5,263
Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory
DeSanctis, G., & Poole, M. S. (1994) · Organization Science · doi:10.1287/orsc.5.2.121 · Cited by 3,879
Interpretive case studies in IS research: nature and method
Walsham, G. (1995) · European Journal of Information Systems · doi:10.1057/ejis.1995.9 · Cited by 3,834
The Nature of Theory in Information Systems1
Gregor, S. (2006) · MIS Quarterly · doi:10.2307/25148742 · Cited by 3,306
The Technology Acceptance Model: Past, Present, and Future
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003) · Communications of the Association for Information Systems · doi:10.17705/1cais.01250 · Cited by 2,572
Information Privacy: Measuring Individuals’ Concerns About Organizational Practices1
Smith, H. J., Milberg, S. J., & Burke, S. J. (1996) · MIS Quarterly · doi:10.2307/249477 · Cited by 2,266
Combining IS Research Methods: Towards a Pluralist Methodology
Mingers, J. (2001) · Information Systems Research · doi:10.1287/isre.12.3.240.9709 · Cited by 1,380
Dubé, L., & Paré, G. (2003) · MIS Quarterly · doi:10.2307/30036550 · Cited by 976
Pragmatism vs interpretivism in qualitative information systems research
Goldkuhl, G. (2012) · European Journal of Information Systems · doi:10.1057/ejis.2011.54 · Cited by 541
Sarker, S., Sarker, S., Sahaym, A., & Bjørn-Andersen, N. (2012) · MIS Quarterly · doi:10.2307/41410419 · Cited by 367
Using a case study to test the role of three key social enablers in ERP implementation
Sarker, S., & Lee, A. S. (2003) · Information & Management · doi:10.1016/s0378-7206(02)00103-9 · Cited by 344
Self-citationMarkus, M. L. (1994) · ACM Transactions on Information Systems · doi:10.1145/196734.196738 · Cited by 310
A disaster for everyone to see: An interpretive analysis of a failed is project
Myers, M. D. (1994) · Accounting, Management and Information Technologies · doi:10.1016/0959-8022(94)90022-1 · Cited by 203
Burton-Jones, A., McLean, E. R., & Monod, E. (2015) · European Journal of Information Systems · doi:10.1057/ejis.2014.31 · Cited by 167
Q-sorting and MIS Research: A Primer
Thomas, D. M., & Watson, R. T. (2002) · Communications of the Association for Information Systems · doi:10.17705/1cais.00809 · Cited by 144
Doolin, B. (1998) · Journal of Information Technology · doi:10.1057/jit.1998.8 · Cited by 125
The Perils and Promises of Self-Disclosure on Social Media
Richey, M., Gonibeed, A., & Ravishankar, M. N. (2018) · Information Systems Frontiers · doi:10.1007/s10796-017-9806-7 · Cited by 66
Towards Dissolution of the is Research Debate: From Polarization to Polarity
Fitzgerald, B., & Howcroft, D. (1998) · Journal of Information Technology · doi:10.1177/026839629801300409 · Cited by 41
Metadata
- Authors
- Lee, A. S.
- Venue
- Organization Science
- Published
- 1991-11
- Volume
- 2
- Issue
- 4
- Pages
- 342-365
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2124179048
- Cited by
- 1,031
- References
- 1
- FWCI
- 11.10
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.