Virtual reality technology and operational performance: The mediating role of contextual awareness in Brimob Polda Ace
Bibliographic record
Abstract
This study aims to examine the impact of the utilization of virtual reality technology on operational performance, with a focus on understanding the mediating role of contextual awareness. The research was conducted in Indonesia, specifically at the Mobile Brigade Corps (Brimob) of the Aceh Regional Police (Polda Aceh). A quantitative approach was used in this study, employing a questionnaire consisting of questions designed based on variable indicators that had been validated and tested for reliability in previous research. Data were collected from a sample of 292 personnel from Brimob Polda Aceh. Structural Equation Modeling (SEM) with Partial Least Squares (PLS) approach was used for data analysis, allowing for the testing of hypothesized relationships between variables. The results of the study show that the utilization of virtual reality technology has a significant positive impact on operational performance, and that contextual awareness acts as a mediating variable influencing the relationship between virtual reality technology utilization and operational performance. Based on these findings, it is concluded that the utilization of virtual reality technology can enhance operational performance through the mediation of contextual awareness among personnel. These findings provide valuable insights for the application of virtual reality technology in improving operational performance in law enforcement agencies and suggest the importance of integrating new technologies to enhance the effectiveness of operational tasks.
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 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 | 0.002 | 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 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".