The link between management accounting information systems and firm competitiveness: The mediating role of innovation capabilities
Bibliographic record
Abstract
This paper aims to examine the strategic role of management accounting information system (MAIS) usage in driving innovation capabilities and firm competitiveness for Jordanian SMEs, besides assessing if innovation capabilities mediate the accounting-competitiveness relationship. Survey data was gathered from over 500 managers of Jordanian SMEs spanning multiple sectors and hypotheses were tested using partial least squares structural equation modelling. Results demonstrate management accounting information system usage has a significant positive direct effect on both innovation capabilities and firm competitiveness. The findings also confirm a positive link between innovation capabilities and SME competitiveness. Most critically, innovation capabilities were found to significantly mediate the relationship between management accounting information system usage and competitiveness. The paper contributes by providing novel empirical evidence on the direct and indirect strategic impacts of management accounting adoption on vital performance outcomes like innovation and competitiveness specifically for the underexplored context of SMEs in developing Arab economies. The firm-level findings encourage Jordanian SME managers and policymakers to prioritize building accounting and innovation capacities in tandem rather than solo to amplify competitiveness and long-run sustainability of this vital economic sector. The cross-sectional survey design limits determining causality. Additionally, subjective biases may arise from single respondents. Generalizability beyond Jordan requires further cultural and economic boundary testing.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".