Globalization of performance appraisals: theory and applications
Bibliographic record
Abstract
Purpose The purpose of this article is to provide a more complete perspective regarding the “best practices” for performance appraisals of “distant” employees in global organizations. Design/methodology/approach A range of published works (1998‐2009) on multinational corporations and performance appraisals was reviewed. The literature was used to determine human resource challenges associated with globalization as well as the types of performance appraisals, common pitfalls and elements for improvement of appraisal systems. Concepts were then combined to determine the “best practices” for performance appraisal in a global setting. Finally, a small questionnaire consisting of six questions was constructed and sent to managers in two companies in the health care industry meeting the criteria of having “distant” employees. The questions were open‐ended in order to allow for a variety of responses enabling the researchers to view trends and make comparisons with the literature. Findings Adequate training must be provided to both the appraiser and the appraisee in order to avoid the many rating errors that are common in performance appraisal. Training should include cultural, legal and customer differences by country providing managers with the tools to improve on the process. Managers must also be given the opportunity to build the required relationship with these employees. Research limitations/implications A questionnaire was sent to several key managers in two complex pharmaceutical firms meeting the criteria with responses received. Further empirical research on the best practices of performance appraisal for distant employees in global organizations should be pursued. Practical implications This article provides a source of information on what practices are followed in order to support the performance appraisal of “distant” employees in different parts of the world. Originality/value There is limited literature dealing with “distant” employee performance appraisal in global organizations and this article attempts to fill this gap.
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 | 0.054 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".