The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Profiles of Strategic Information Systems Planning
Abstract
Improving strategic planning within the realm of information technology management is consistently identified by top corporate executives as a critical competitive issue. While relevant literature in the area is replete with descriptions of planning tools and methodologies, investigations that examine this activity from the perspective of process-based characteristics, or “profiles,” are still in the formative stages. Through multivariate analysis of data gathered from 253 organizations, the findings of this study suggest that five distinct profiles of strategic planning can be identified based on dimensions of comprehensiveness (extent of solution search), formalization (existence of rules and procedures), focus (extent of innovation versus integration), flow (top-down, bottom-up), participation (number and variety of planners), and consistency (frequency of planning). While each profile exhibits strength across particular measures of planning effectiveness, the profile associated with all measures of planning effectiveness seems to incorporate elements of rationality (high comprehensiveness, high formalization, control focus, top-down flow) and adaptation (high participation, high consistency). Postsurvey field study of selected firms suggests that the five approaches may represent distinct “schools” of thought that are reflective of deep-seated beliefs and attitudes about strategic planning. These schools (design, planning, positioning, learning, and political) are founded on very different assumptions and provide substantive interpretation for the empirical findings.
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Cites
A Paradigm for Developing Better Measures of Marketing Constructs
Churchill, G. A. (1979) · Journal of Marketing Research · doi:10.1177/002224377901600110 · Cited by 16,549
Information Systems Success: The Quest for the Dependent Variable
DeLone, W. H., & McLean, E. R. (1992) · Information Systems Research · doi:10.1287/isre.3.1.60 · Cited by 10,697
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Representing and Testing Organizational Theories: A Holistic Construal
Bagozzi, R. P., & Phillips, L. W. (1982) · Administrative Science Quarterly · doi:10.2307/2392322 · Cited by 2,064
Cited by
How to improve firm performance using big data analytics capability and business strategy alignment?
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.08.018 · Cited by 1,624
Kearns, G. S., & Sabherwal, R. (2006) · Journal of Management Information Systems · doi:10.2753/mis0742-1222230306 · Cited by 573
Metadata
- Authors
- Segars, A. H., & Grover, V.
- Venue
- Information Systems Research
- Published
- 1999-09
- Volume
- 10
- Issue
- 3
- Pages
- 199-232
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2160804203
- Cited by
- 267
- References
- 4
- FWCI
- 7.15
- Type
- journal article
- Language
- en
- Open access
- closed
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