The effects of motivation and work climate on employee acceptance and usage of two new information systems : a study at five partner hospitals in Canada
Bibliographic record
Abstract
Despite tremendous financial investments in information technology (IT), many technological interventions that are initiated in organizational work environments ultimately fail as employees do not fully accept and use the available IT. In an effort to understand the specific conditions that lead to the acceptance of new IT and related work outcomes, this research examined the relationships between work climate, motivation, and the acceptance and usage of new IT, using the motivational framework of Self-Determination Theory. Two studies were conducted. In Study One, 336 clerical and administrative staff, nurses, technicians, and professionals completed questionnaires following the implementation of a patient scheduling and appointment management information system. In Study Two, 64 pharmacists, pharmacy assistants, and managers completed web-surveys following the implementation of a pharmacy information system. Results indicated that perceived organizational support and distributive justice were positively related to employee acceptance of an organizational IT change and employee enjoyment and interest in using IT. In some cases, perceived organizational support and distributive justice were also negatively related to the pressure and tension experienced. Supervisor contingent-reward behaviour and supervisor contingent-punishment behaviour were also related to employee attitudes toward IT. Situational autonomous motivation to use new IT was shown to mediate several of the above-mentioned relationships. Recommendations for health-care organizations are discussed, as are contributions to theory and general organizational practice.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".