Working Capital Management and Profitability Relationship-Evidences from Emerging Markets of UAE
Bibliographic record
Abstract
The real estate & construction sector of UAE has seen tremendous expansion during 2004-2007 and a deep decline in the recent past due to global crisis. In spite of showing some signs of recovery in 2011, these sectors are still struggling with the excess of supply over demand, sluggish growth, so it becomes imperative to explore the relationship between the working capital management and the profitability.In the current study all real estate and construction companies listed on Abu Dhabi stock exchange have been studied for a period of 4 years from 2007-2010. The study is based on the secondary data obtained from the annual reports of the respective companies. The Return on Assets has been taken as dependent variable and cash conversion cycle and its components have been taken as independent variables. Size, leverage and liquidity are taken as control variables. The study uses correlations and multiple regression analysis to draw interpretations.The key findings of this study are that there exists a significant negative relationship between the profitability and the length of the firm’s cash conversion cycle. Longer the cash conversion cycle, lesser will be the profitability. The payables and inventories period are also found to be significant factors.This paper is first attempt to study the working capital management and profitability relationship in UAE’s Real Estate and Construction companies, (as per author’s knowledge) as no previous research has been undertaken in this context.The practical implication of this research is to guide the actions of UAE’s Real Estate and construction company’s policy makers. The results of this study can be used for giving the strategic focus on reduction of cash conversion cycle in order to enhance profitability. The effective management of Inventory and payables can ensure a sound bottom-line for the real estate and construction companies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".