FACTORS INFLUENCING CASH HOLDING IN THE NON-CYCLICAL CONSUMER INDUSTRY AFTER THE COVID-19 PANDEMIC
Bibliographic record
Abstract
The COVID-19 pandemic resulted in all sectors recording negative performance in the first quarter of 2020, including the consumer goods sector. In economic uncertainty due to the COVID-19 pandemic and intense competition between companies, many company experienced a significant decline and even decided to go on insolvency because they were unable to finance their operational activities. Therefore, the availability of cash or cash holding is essential to support the company’s operational activities, and error in calculating cash holding can result in the company experiencing financial difficulties. This study aims to analize the effect of cash conversion cycle, cash flow, and leverage on cash holding in consumer non-cyclicals companies listed on the Indonesia Stock Exchange (BEI) for the 2020-2022. The data used in this study were collected from IDX website. Analyzed data by using Eviews version 13. Sampling method used is Purposive sampling techniques. There were 47 companies met the criteria as the sample.
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.
How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".