Responding—or Not—to IT Project Risks: Conceptualizing Risk Response as Planned Behavior
Bibliographic record
Abstract
Prior research suggests that IT project managers’ risk response behavior sometimes differs from the prescriptions in the literature. Conceptualizing performing a risk response as planned behavior, this study draws upon the theory of planned behavior (TPB) and develops a model to enrich the understanding of the relationship between perceiving risk and enacting—or not—a risk response. The model includes the TPB constructs—behavioral attitude, perceived pressure and perceived control. It also leverages the notion of ‘background factors’ in TPB that allows the inclusion of antecedents of behavioral attitude, in the present study, perceived risk of project without the risk response and perceived risk of enacting the risk response. The research design comprises three studies. Study 1 selected three specific risk responses. Study 2 elicited IT project managers’ beliefs about each risk response. Study 3 (in progress), tests the proposed model—enriched with the elicited beliefs—for each risk response.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".