Market Structure Analysis of Revenue of International Construction Professional Service (I-CPS): A Country-Level Analysis
Bibliographic record
Abstract
International construction professional service (I-CPS) refers to a knowledge-intensive professional service (KIPS), such as architecture, engineering, and consultancy, which uses technology/human capital as its major input and is better positioned to create new market opportunities and profitability. While the I-CPS market has recently stagnated owing to political, economic, and social uncertainties, the continuous growth and survival of I-CPS firms are becoming an issue, and a country’s competitiveness in supporting these firms is becoming increasingly important. The market structure of an industry results from the competition between countries or firms, which helps identify future market opportunities and establish a timely competitive strategy. The objective of this study is to quantitatively analyze the I-CPS market structure based on top international design firms (TIDFs). This study analyzes the revenue structures of TIDFs by nationality to identify country-specific factors in the I-CPS industry. The Engineering News-Record’s (ENR) Top 225/200 International Design Firms List for the past decade (2011–2021) was used to analyze international revenue in the major 15 countries. This study analyzed the I-CPS industry’s concentration for static analysis, and for dynamic analysis, the rank distribution of TIDFs, their mobility, and instability by firm nationality were analyzed sequentially. The results confirmed that market forces shifted from Europe and USA to Canada and China and that the market position was unstable in many countries. Additionally, this study divides the 15 countries into four static and dynamic combinations: high-static and high-dynamic, high-static and low-dynamic, low-static and high-dynamic, and low-static and low-dynamic. The findings of this study help understand country-level competition in the I-CPS market from a macro perspective, and provide directions for follow-up studies related to the I-CPS market structure.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".