The effects of digital transformation, digital leadership, and entrepreneurial motivation on business decision making and business process performance: Evidence from greater Amman municipality
Bibliographic record
Abstract
The purpose of this research was to examine the effects of digital transformation, digital leadership, and entrepreneurial motivation on business decision making and business process performance in the Greater Amman Municipality. The study's hypotheses were put to the test and proven through a variety of quantitative analysis and data processing techniques. The research hypotheses were evaluated using a Structural Equation Model. Participants in this research are managers from the middle and high echelons of the Greater Amman Municipality, who were responsible for making decisions in their respective divisions. One hundred and eighty middle and upper-level managers with at least eight years' experience in public service were recruited for this study from the Greater Amman Municipality. Distributed questionnaires and the deliberate sampling technique were used to compile this data. Decision making had a positive effect on the business process performance, and the results of hypothesis testing data processing using Structural Equation Model indicated that digital transformation, digital leadership, and the motivation of the business environment all had positive and significant effects on business decision making and business process performance in the Greater Amman Municipality. To conduct their research, the authors opted to focus on digital transformation, which includes four primary components: process transformation, business model change, domain transformation, and cultural transformation. The following dimensions commander, communicator, collaborator, and co-creator were all indicative of digital leadership. Entrepreneurial motivation could be seen in the word’s communication, hassle-free work environment, mastering the art of constructive criticism, and trust among others. The novel aspect of this study is the model developed to explain the interplay between digital transformation, digital leadership, and entrepreneurial motivation, and how these factors influence business decision making and business process performance at Greater Amman Municipality.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".