A Study of Value Addition by Information Systems to a Service Providing Business at the Meteorological Services Department in Zimbabwe
Bibliographic record
Abstract
Many companies are using only a portion of what is needed in terms of Information Technologies (IT) and this has caused the researcher to study how best MSD can effectively utilize Management Information Systems (MIS). The objective that directed the study was to investigate value addition by information systems to a service providing business with specific reference to the weather station in Zimbabwe (Meteorological Services Department). Knowing the value added by MIS to one’s business and working environment is key to cope with the ever increasing challenges such as the volume of information resources, nature and quality of information, user needs and expectations, information and communication technology competencies and infrastructure, inflated cost of information resources and staffing needs. The researcher studied how information systems add value to the daily business of Meteorological Services Department (MSD) in the following areas of the organisation processes: products, quality, management, problem solving and decision of the organisation. The study on value addition by management information systems will assist in the improvement of the MSD in Zimbabwe. The study used a multistage sampling process for drawing sample from the target population. Secondary and primary data collection methods were used for data collection purposes. The source for primary data was questionnaire. Five different types of Management Information Systems that add value to the MSD were identified; Management Information Systems, Office Automation Systems, Executive Support Systems, Expert Systems, Decision Support System and Transaction Processing System. From the findings it was concluded that management information systems add value by allowing valid decisions which provide accurate and up-to-date information and performing analytic functions. This study demonstrated the importance of information systems in an organisation and outlined the fundamental roles of Information Systems (IS) which are to support business processes and operation, support decision making by employees and managers and support strategies for competitive advantage.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".