Corporate financial strategies and performance: Insights from China’s Shanghai Stock Exchange
Bibliographic record
Abstract
This study investigated the impact of corporate financial strategies-(CFSs) on the performance of companies listed on the Shanghai Stock Exchange-(SSE) from 2010-2023, analyzing data from 2,269 firms, yielding 31,766 balanced firm-year observations. Utilizing a mixed-methods approach with a quasi-experimental design grounded in pragmatism, the inquiry employed two-step System-GMM technique to address endogeneity, simultaneity, heteroscedasticity, reverse causality and Nickell bias. Fixed effects-(FE) and random effects-(RE) models were applied to handle unobserved heterogeneity, omitted variable bias and guarantee robustness. The results revealed that, total-debt-to-assets-ratio-(TDTAR) and dividend yield-(DY) significantly and negatively impacted firm performance-(FP), measured by return on assets-(ROA) and Tobin’s Q-(TQ). Contrary, cash conversion cycle-(CCC), current ratio-(CR), total-assets-turnover-(TAT), tangibility-(TANG), total-equity-to-total-assets ratio-(TETAR), dividend payout ratio-(DPR), firm size-(SIZE), and firm age-(AGE) had a significantly positive effect on FP-(ROA and TQ). The study emphasizes the importance of effective CFSs in improving FP and offers insights for policymakers, investors, and managers, highlighting the need for corporate deleveraging, capital structure optimization and efficient asset and working capital management. Although focused on China, the study’s framework is applicable to other emerging markets, providing valuable theoretical, conceptual, and methodological insights as it integrates CFS metrics into the resource-based view theory-(RBVT), extending the theory’s scope making it more robust and generalizable.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.000 | 0.001 |
| 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".