The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Making Sense of Technology Trends in the Information Technology Landscape: A Design Science Approach1
Abstract
A major problem for firms making information technology investment decisions is predicting and understanding the effects of future technological developments on the value of present technologies. Failure to adequately address this problem can result in wasted organization resources in acquiring, developing, managing, and training employees in the use of technologies that are short-lived and fail to produce adequate return on investment. The sheer number of available technologies and the complex set of relationships among them make IT landscape analysis extremely challenging. Most IT-consuming firms rely on third parties and suppliers for strategic recommendations on IT investments, which can lead to biased and generic advice. We address this problem by defining a new set of constructs and methodologies upon which we develop an IT ecosystem model. The objective of these artifacts is to provide a formal problem representation structure for the analysis of information technology development trends and to reduce the complexity of the IT landscape for practitioners making IT investment decisions. We adopt a process theory perspective and use a combination of visual mapping and quantification strategies to develop our artifacts and a state diagram-based technique to represent evolutionary transitions over time. We illustrate our approach using two exemplars: digital music technologies and wireless networking technologies. We evaluate the utility of our approach by conducting in-depth interviews with IT industry experts and demonstrate the contribution of our approach relative to existing techniques for technology forecasting.
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
Building Theories from Case Study Research
Eisenhardt, K. M. (1989) · The Academy of Management Review · doi:10.2307/258557 · Cited by 17,455
Design Science in Information Systems Research1
Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004) · MIS Quarterly · doi:10.2307/25148625 · Cited by 10,707 · cited 5×
“We follow guidelines in Hevner et al. (2004) and use an analysis of real data to demonstrate our methodology.”
MethodInfluentialDesign science in information systems research
(2004) · Journal of the Association for Information Systems · doi:10.5555/2017212.2017217 · Cited by 8,254
Strategies for Theorizing from Process Data
Langley, A. (1999) · The Academy of Management Review · doi:10.5465/amr.1999.2553248 · Cited by 7,008
Technological paradigms and technological trajectories
Dosi, G. (1982) · Research Policy · doi:10.1016/0048-7333(82)90016-6 · Cited by 6,685
The Nature of Theory in Information Systems1
Gregor, S. (2006) · MIS Quarterly · doi:10.2307/25148742 · Cited by 3,306 · cited 1×
“In this section, we discuss our use of theory to support the design of artifacts (Gregor 2006) and define constructs that provide foundations for a new visual representation and empirical approach for modeling technology evolution patterns over time.”
Steps toward an ecology of infrastructure: Design and access for large information spaces
Star, S. L., & Ruhleder, K. (1996) · Information Systems Research · doi:10.1287/isre.7.1.111 · Cited by 3,238
Information Technology and Organizational Change: Causal Structure in Theory and Research
Markus, M. L., & Robey, D. (1988) · Management Science · doi:10.1287/mnsc.34.5.583 · Cited by 2,108
Longitudinal Field Research Methods for Studying Processes of Organizational Change
van de Ven, A. H., & Huber, G. P. (1990) · Organization Science · doi:10.1287/orsc.1.3.213 · Cited by 832
Cited by
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010) · Information Systems Research · doi:10.1287/isre.1100.0322 · Cited by 2,964
Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018) · Journal of Management Information Systems · doi:10.1080/07421222.2018.1440766 · Cited by 2,109
Self-citationService Innovation: A Service-Dominant Logic Perspective1
Lusch, R. F., & Nambisan, S. (2015) · MIS Quarterly · doi:10.25300/misq/2015/39.1.07 · Cited by 1,949
Introduction—Platforms and Infrastructures in the Digital Age
Constantinides, P., Henfridsson, O., & Parker, G. G. (2018) · Information Systems Research · doi:10.1287/isre.2018.0794 · Cited by 943
Cocreation of Value in a Platform Ecosystem: The Case of Enterprise Software1
Ceccagnoli, M., Forman, C., Huang, P., & Wu, D. J. (2012) · MIS Quarterly · doi:10.2307/41410417 · Cited by 794
Metadata
- Authors
- Adomavicius, G., Bockstedt, J. C., Gupta, A., & Kauffman, R. J.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 2008-12-01
- Volume
- 32
- Issue
- 4
- Pages
- 779-809
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1545576888
- Cited by
- 236
- References
- 9
- FWCI
- 13.84
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Making Sense of Technology Trends in the Information Technology Landscape: A Design Science Approach1. https://app.cochat.ai/papers/10.2307/25148872
- The paper
- Adomavicius, G., Bockstedt, J. C., Gupta, A., & Kauffman, R. J. (2008). Making Sense of Technology Trends in the Information Technology Landscape: A Design Science Approach1. MIS Quarterly. https://doi.org/10.2307/25148872
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.