The Role of Information Technology in Customers’ Service Delivery and Firm Performance: Evidence from Nigeria’s Insurance Industry
Bibliographic record
Abstract
Information technology is crucial for a communication based process. Therefore, this study presents aninvestigation of the significant role of information technology in customer service delivery and firm performancein selected insurance companies in Nigeria. Specifically, three hypotheses were tested. They are to determinewhether: (i) customers are not aware of the availability of IT facilities in their dealings with the Nigerian insurancecompanies; (ii) the use of IT does not enhance the performance efficiency of insurance organizations in Nigeria;and (iii) providing quality customer service delivery will not enhance organizational performance of insurancecompanies. The survey research design for the study was a cross examination. The study sample consisted of 112participants made up of IT managers, marketing managers, and underwriting managers drawn from 25 insurancecompanies which were randomly selected from the directory of member companies. One-sample T-test and simplefrequency percentage tables were used for data analysis. The study revealed that most customers hardly use onlineservices in their engagement with the Nigerian insurance companies even with the level of awareness createdwhich depicts a low level business relationship. Thus, many of the insurance organizations indicated that theyexperienced high performance efficiency in their investment in and adoption of information technology. This studyrecommends that insurance administrators and regulators at all levels should gather relevant information as regardsfactors that may assist in contributing meaningfully to the usefulness of IT in effective service delivery. Theyshould also undertake optimal investment in IT, provide quality service delivery to customers and regularlyevaluate IT usage in every department of insurance organizations in Nigeria in order to take appropriate strategicdecisions capable of enhancing firm performance.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".