The Impact of Change Management on the Efficiency of Organizations: An Applied Study on the DAL Dairy Factory - Sudan 2019 - 2020
Bibliographic record
Abstract
Objectives: This study aims to know the effect of change in culture and technology on efficiency in Dairy Factory - Sudan, 2019-2020 and to know the views of managers on the impact of change management on efficiency, to identify the positive aspects that help in improving this efficiency as well as to identify the negatives Which limit the company's efficiency in this field, by answering the following research questions: - Is there an impact of changing culture and technology on increasing the efficiency of institutions? To answer these questions on which the problem is centered around, the following scientific hypotheses were put forward: - There is a statistically significant relationship between changing the organization's culture and increasing the efficiency of organizations, as well as the existence of a statistically significant relationship between changing technology in the organization and increasing the efficiency of organizations. Methods: The descriptive and analytical approach was used to describe the phenomenon under study, and the questionnaire was used to collect various data. The questionnaire was distributed to the sample members who numbered (55) employees to conduct the statistical analysis for this study, through the program used for the statistical analysis of social sciences, the hypotheses were tested by Median and chi-square. Finding: inflating the culture of the departments and divisions of the company, the stagnation and inflexibility of the society's culture, and the inadequacy of that culture to the requirements of work within the community, which led to an overlap in the powers and responsibilities? The most important recommendations: The necessity of changing the organizational structure to comply with the requirements of work, after carefully studying the internal and external environment, and for the change to take place based on the recommendations of specialists in administrative sciences. So that it is not random and does not lead to an inflation of the organizational structure without success. Value: The importance of the study stems from the fact that it addresses an important topic in business administration, which is managing change in organizations, which is the only way for these organizations to develop and continue to exist. It also studies the reality of change management in the DAL Dairy Factory - Sudan.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".