Information technology management practices: A descriptive analysis of the challenges facing information technology managers
Bibliographic record
Abstract
The paper intended to study managerial impediments which may hinder effective managerial practices by IT managers and their co-workers. The managerial drivers included: rules, initiatives, emotions, immediate action and integrity. This paper described the drivers of managerial practices by managers in information technology departments. The findings on Perception of IT managers and administrators towards the drivers of managerial practices by IT managers put a lot of emphasis on immediate action with regards to emergencies and driver of rules ( lack of commitment) to explain the impediments faced by IT managers. Purpose: This research sought to find out if IT managers were facing challenges resulting from administration and management practices. This research was carried out to investigate on the impediments facing IT managers. The study involved effective drivers of management adopted from Sabourin (2009) experiential leadership model, with managerial drivers of; rules, initiatives, integrity, immediate action and emotions to better identify key obstacles that face information technology managers and their management practices. Methodology: A mixed method of qualitative (focus group discussion) and quantitative (a survey with a questionnaire) approaches was applied to this study. These involved group discussion of IT technicians and administrators in the selected organizations in a Canadian province. The total number of surveyed managers was 149. Findings: With regards to the drivers of management practices, it was established that the driver of immediate action holds the highest consideration towards managerial practices by IT managers. This driver had, a frequency recorded 131, mean of 3.1897, median of 3.200 and standard deviation of 0.75874. The driver of rules was after analysis found to have a frequency of 132, a mean of 2.5773, median of 2.500 and standard deviation of 0.72983. The driver of emotions had a frequency of 131, mean of 2.5530, median of 2.400 and standard deviation of 0.71773. The driver of integrity had a frequency of 130, mean of 2.6969, median of 2.600 and standard deviation of 0.70603. The driver of initiatives had a frequency of 130; mean score of 2.8923, median of 2.800 and standard deviation of 0.80602. The summary of the report has been presents in table 2. Conclusion: This study focused on the challenges experienced by IT managers and co-workers as they execute their management practices. Taken as a whole, our findings suggest that, there are some impediments associated with drivers of Emotions, immediate action, Rules and initiatives as well as integrity. Even if these obstacles are in multiple levels to develop and promote IT management practices, it is imperative to study with more depth obstacles faced by IT managers in order to better understand how the obstacles they face represent an impediment to the development of their competencies and effective performance in IT. Keywords: Managerial drivers, managerial practices, Information technology (IT), Information management
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".