Culture and organizational culture in the construction industry : a literature review
Bibliographic record
Abstract
The effectiveness and competitive advantage of an organization/project can be enhanced when its members possess an understanding, respect, acceptance, and capacity to manage cross-cultural differences. Ignoring or failing to manage such differences may lead to many problems in the project (e.g., project delays and productivity decrease). In fact, international/transnational projects involving participants from diverse political, legal, economic, and cultural backgrounds are on the rise. Hence, firms should be cross-culturally competent and capable of managing in contrasting cultural factors. However, a recent study conducted in 2013 by the Construction Industry Institute (CII) reported that one of the major concerns of construction professionals is a widespread lack of understanding of foreign cultures, ethnicities, and languages. The aim of this paper is to present a comprehensive review of the literature on cultural aspects in the construction industry so as to identify the knowledge gaps and to suggest recommendations for future research. To do so, the authors have identified and compared major studies on cultural factors. From the comparison, the authors have identified the categories that are considered the most central to understanding cultural differences; they are, “group attachment and relations,” “authority and status,” “uncertainty and rules,” “gender roles and assertiveness,” and “time and future orientation.” The authors also summarize the current research topics in culture in construction and recommend ideas for future research into culture as it pertains to a construction context.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".