Nonusable Enterprise Systems and Productivity and Well-Being of Canadian Automobile Dealership Accountants
Bibliographic record
Abstract
Enterprise system software is adapted by organizations to automate business processes. However, adaptation failures ranging from 50% to 90% make an enterprise system nonusable, costing millions of dollars to companies. The problem was the systemic barrier hindering productivity, which impels a phenomenological study to explore on what are the lived experiences of Canadian automotive dealership accountants related to their productivity and well-being when the enterprise system is nonusable. The research question asked, what are the lived experiences of Canadian automotive dealership accountants related to their productivity and well-being when the ES is nonusable. The conceptual framework for this research was a synthesis of the philosophy of utilitarian accounts of Griffin, the job demand-resource theory of Bakker and Demerouti, and change management applied to enterprise system adaptation. Data were collected via interviews and analyzed via a modified Stevick–Colaizzi–Keen data analysis technique. Findings indicated that enterprise system nonusability affects the productivity and well-being of automotive dealership accountants in carrying out their tasks to fulfill their deliverables. Six major themes were identified: enterprise system support, job demands for accountants, the importance of training, limited features/providers slow to improve, setup and configuration, and a proactive approach. Implications for positive social change include adding more emphasis on the human aspects of enterprise system adaptation for productivity and promotion of health and well-being among users to benefit employers, employees, customers, and the community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".