Integrating the Last Planner System and Immersive Virtual Reality: Exploring the Social Mechanisms Produced by Using LPS in Projects
Bibliographic record
Abstract
Over the last 30 years, the last planner system (LPS), as a Lean-driven production planning and control tool, has consistently demonstrated its capability to improve planning reliability and overall performance in construction projects. Recent research provides evidence suggesting that the LPS ability to do good to projects has not reached its full potential yet. In fact, it has been observed that by identifying the missing social mechanisms in its implementation process and managing more effectively the complex socio-technical nature of the LPS, its implementation effectiveness is improved. However, commonly used research approaches, such as the case study method, have been criticized for lacking scientific control, replicability, and external validity. Alternatively, immersive virtual reality (IVR)-based simulation games have the methodological capability to enable the study of the social mechanisms that the LPS engenders when implemented in projects, by providing a highly controlled, reproducible, and ecologically valid experimental environment. However, how to leverage effectively IVR-based gaming technology to study the social mechanisms that the LPS engenders in construction organizations is not well understood. In order to bridge this gap, this paper established the conceptual and technical foundations to set IVR-based experimental environments and developed an IVR prototype encompassing nonlean and LPS-based rounds. The evaluation of the IVR prototype involved both quantitative and qualitative research approaches, focusing on its functionality, user-perceived presence and usability, task performance, and lean expert feedback. The results demonstrated the prototype’s capability to create a controlled experimental environment while offering participants a user-friendly, immersive, and realistic LPS simulation experience. The contributions of this study are twofold: (1) the addition of a new method to the research methodology toolbox in construction engineering and management; and (2) the generation of design insights to develop IVR prototypes for research in construction engineering and management, and preliminary evidence for its ecological validity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".