Remote People Management - Resolving Organizational Issues at Call Centers : Case Study of the Bank of Nova Scotia
Bibliographic record
Abstract
Transformation of management coincided with rise of IT and re-orientation towards the demand driven economy. IT facilitated the development of remote communication and data accessibility, while re-profiling the management methods, in meanwhile, customer focus has led to organization of customer-oriented establishments such as call centers. However, aside from benefits, including accessibility, convenience, and long term cost reductions, implementation of innovations in information technologies has yielded issues. Complete assimilation of technology proved to be difficult due to factors emerging from technological, organizational and environmental contexts. Namely, factors that are most applicable in the call center context are technology readiness and managerial obstacles. Another issue that had risen as a consequence of wide spread use of IT in the call center context is employee turnover. Although not directly linked to turnover per se, IT assisted in transformation of management methods, which, uncompensated, exert pressure onto employees, while often remaining unseen. Since pressure in addition to contributing factors is linked to stress, one suggests that stress is the leading cause of turnover at call centers. Accordingly, pressure to perform, along with applied control methods will be examined in this thesis. Thesis proceeds to investigate background information on these issues, followed by review of the relevant academic work, concluding with the case study in the banking sector aiming to look at specific issues in order to find practical solutions. Finally, a summary will indicate the proposed direction for issue resolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".