A multi‐level, multi‐theory perspective of information technology implementation
Bibliographic record
Abstract
Abstract. Much of information technology (IT) implementation research has focused on individuals' acceptance of IT by examining their behaviour when faced with new IT and the antecedents of these behaviours. As they are frequently undertaken within a project framework, IT implementations also entail the application of project management practices in order to be successful. Based on the premise that antecedents of lower level theories are frequently determined by the outcomes of a higher level theory, the present paper illustrates how organizational‐level decisions, examined from the perspective of economics theories, can help explain the antecedents of project risk management at the project and individual levels. To do so, the paper describes an IT implementation effort which went through three phases; the first two of which were abandoned versions of the same project. An organizational‐level analysis of the case from an economics perspective and its project‐level analysis from a risk management perspective show how organizational‐level decisions influenced the antecedents at the project and individual levels, providing a more complete understanding of the IT implementation in question, an understanding which neither a theory approach nor a level perspective could provide on its own.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".