The use of big data and the internet of things leadership and organizational culture: The innovative capacity of the Amman Stock Exchange
Bibliographic record
Abstract
The aim of this study is to investigate the relationship between big data adoption and Internet of Things adoption and entrepreneurial behavior at Amman Stock Exchange The study focuses on how the ability to innovate mainly mediates this link. The study method uses a quantitative approach that includes conducting a professional survey, conducting a statistical analysis, and testing mediation Key results show that the use of big data improves the ability to innovate largely, and affects employees’ practical leadership capabilities The interaction between Internet adoption and leadership capabilities is influenced by product capabilities, which emphasizes the important role of innovation as a mediator in shaping employee behavior emphasizing Practical results of this study show that Amman Stock Exchange companies strategically use big data and IoT technologies to promote innovation. Shortcomings of the study include the specificity of digital work, the reliance on self-reported data, and the use of static analysis. Subsequent research should expand participants and use more comprehensive methods. Recommendation: Embrace technology with an emphasis on innovation, provide leadership training, and increase knowledge about technology, innovation and human behavior.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".