Enabling Lean Construction 4.0 through human-centric digital transformation: organisational leadership insights
Why this work is in the frame
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Bibliographic record
Abstract
Purpose This study investigates the challenges construction organisation leaders face when implementing human-centric digital transformation to enable Lean Construction 4.0. It aims to provide insights into how organisations can effectively manage the human aspects of digital transformation while addressing industry-specific barriers to lean implementation. Design/methodology/approach The research employed a qualitative approach through semi-structured interviews with senior organisation leaders from construction organisations across New Zealand, Australia, the UK and Denmark. Data analysis followed a systematic thematic analysis approach to identify key challenges and patterns. Findings The study revealed ten key challenge areas in implementing human-centric digital transformation for Lean Construction 4.0: strategic vision communication, organisational competencies assessment, training development, resource allocation, employee involvement, value integration, technological adoption, performance monitoring, well-being support and cultural reinforcement. Critical barriers include the industry’s traditionally low-profit margins limiting investment capacity, high staff turnover rates complicating training initiatives and resistance from long-tenured employees transitioning from memorised to documented processes. The findings highlight how the construction industry’s unique characteristics create distinct challenges in terms of implementing Lean Construction 4.0 that extend beyond general digital transformation barriers. Originality/value This study is among the first to specifically examine human-centric digital transformation challenges in implementing Lean Construction 4.0 in construction organisations from a leadership perspective. It contributes to both theory and practice by providing a comprehensive understanding of the barriers that leaders face when implementing digital transformation while maintaining a human-centric focus. The findings bridge the gap between theoretical understanding and practical implementation of Lean Construction 4.0, offering insights for construction organisations seeking to balance technological advancement with human factors.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it