Cash Conversion Cycle and Profitability: Evidence from Greek Service Firms
Bibliographic record
Abstract
The present study examines the relationship between the cash conversion cycle (CCC) and profitability in major service sectors in Greece, including hotels, education, healthcare, transfer—rentals, and information technology. Using financial data from 343 public limited companies for the year 2023, the research applies descriptive statistics, Pearson correlation analysis, and ANOVA to evaluate how CCC components affect profitability, measured through return on assets (ROA). The results indicate that firms across all sectors maintain a negative CCC, suggesting efficient liquidity management, with the education sector exhibiting the most negative CCC due to upfront tuition payments. Additionally, the study finds a significant positive correlation between CCC and ROA, implying that firms with longer negative CCC values tend to achieve higher profitability. However, firm size, measured by total assets and sales, does not appear to influence CCC efficiency or profitability. These findings underscore the importance of industry-specific financial strategies and highlight the role of CCC optimization in enhancing financial performance. The study contributes to the literature on working capital management and provides practical implications for improving liquidity and profitability in service-oriented firms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".