Detecting Sticky Costs in Iraqi Industrial Companies an Empirical Study of a Sample of Iraqi Companies Registered on Iraq Stock Exchange
Bibliographic record
Abstract
Purpose: This research aims to reveal the sticky costs in Iraqi joint stock companies. Theoretical framework: Sticky costs refer to the costs that increase with the increase in revenues by a greater amount than their decrease in exchange for a similar decrease in revenues. To manage cost, it is important to understand and know the behavior of cost. Design/methodology/approach: This research uses inductive and descriptive analytical methods that is commonly used in applied and field studies on accounting and management issues, as well as in literature and empirical studies to verify research proposals. This study adopted multiple logarithmic linear regression analysis estimated by ordinary least squares (OLS) to examine asymmetrical behavior of selling costs, general and administrative costs, and costs of goods sold individually and collectively (total costs) for a sample (101) of published lists of Iraqi joint stock companies registered in Iraqi Stock Exchange for the period 2010-2019. Findings: The results showed that sticky behavior of selling and general and administrative costs and their components is a common phenomenon in cost behavior of Iraqi joint stock companies during the study period, while costs of goods sold, and total costs are not. The latter may have been showing anti-sticky behavior. Research, Practical & Social implications: Our work contrasts the conventional model of cost behaviour, in which costs move proportionately with changes in activity, with an alternative model, in which sticky costs emerge. This is because managers consciously shift the resources devoted to activities. Originality/value: The sticky cost research that has been done in relation to the initial sticky cost research, particularly in industrialised nations like the UAS, Uk, and Canada, is the main emphasis of this study. Future research will take into account how sticky research is developing in any other nations, which could expand our understanding of sticky cost research as a whole.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".