Information technology investment and working capital management efficiency: evidence from India survey data
Why this work is in the frame
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Bibliographic record
Abstract
Purpose This study aims to test the relationship between information technology investment (IT_INVEST) and working capital management (WCM) efficiency. Design/methodology/approach This study utilized a survey research design to collect data from micro, small and medium enterprises (MSMEs) owners in India. Findings Empirical results show that perceived IT_INVEST plays a role in improving WCM efficiency by decreasing the inventory holding period and reducing the cash conversion cycle (CCC) in India. A three-stage least square model (3SLS) shows that IT_INVEST decreases CCC directly and indirectly through the inventory holding period, accounts receivable period and accounts payable period. The empirical analysis also shows that IT_INVEST decreases the inventory holding period and CCC by 16.80% and 26.40%, respectively, for the examined firms. Research limitations/implications If MSMEs' owners perceive a higher level of IT_INVEST, then the owners perceive a higher WCM efficiency and vice versa. Originality/value This study contributes to the literature on the relationship between IT_INVEST and WCM efficiency. This study may encourage further studies of IT investment and WCM efficiency using data from other industries and countries. MSME owners may find empirical results beneficial to improve WCM efficiency. Moreover, financial management consultants may find results helpful to provide consulting services.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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 it