Rethinking the Concept of Organizational Readiness: What Can IS Researchers Learn from the Change Management Field?
Bibliographic record
Abstract
The organizational readiness construct has been investigated in information systems (IS) research for more than two decades and has yielded tremendous insights on topics such as IS organizational adoption, IS organizational use and institutionalization, IS project success, and knowledge acquisition and sharing. Notwithstanding the strong implications of this construct for our discipline, a critical and comprehensive assessment of the conceptualization of organizational readiness in IS research has not yet been conducted. Thus, this review article proposes to fill this gap and reflects on the conceptualization of organizational readiness in prior IS literature. Building upon the recommendations made by change management theorists, it proposes a new, yet multi-dimensional conceptualization of organizational readiness, including two overarching dimensions and nine sub-dimensions. We discuss how the proposed conceptualization is likely to offer a richer understanding of this construct in the IS discipline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.004 | 0.048 |
| Scholarly communication | 0.020 | 0.048 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".