Determinants of Financial Performance in Advertising and Marketing Companies: Evidence from Central and Eastern European Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The issue of key determinants affecting the financial performance of advertising and marketing companies in Central and Eastern Europe remains understudied, despite the industry’s rapid growth and regional specifics. This study investigates financial performance determinants of advertising and marketing companies in four CEE countries (the Czech Republic, Poland, the Slovak Republic, and Ukraine) during 2021–2023, employing the least absolute deviations method. The study examines three financial performance measures (Return on Assets, Return on Equity, and Operating Profit Margin) using three independent variables (Current Ratio, Debt to Equity, and Total Asset Turnover) and control variables such as Company Size, Leverage, and Company Type. The results show that Total Asset Turnover consistently has a significant positive impact on ROA and ROE across all studied countries. The study also identified significant regional variations in liquidity and capital structure impacts, particularly in the Polish market, and uncovered distinct patterns in how financial leverage affects various performance metrics across the studied countries. Specifically, while leverage shows a predominantly negative relationship with ROE in most countries, it positively influences OPM for Polish, Slovak, and Ukrainian companies, suggesting that the role of financial leverage in company performance is highly context-dependent. The novelty of the study lies in a comprehensive investigation of specific determinants of financial performance in the CEE advertising and marketing sector, revealing the crucial role of efficient asset and equity management in the region.
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.
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 | 0.001 |
| 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