Market Orientation and Corporate Performance of Insurance Firms in Nigeria
Bibliographic record
Abstract
The study examined the effect of market orientation on corporate performance of insurance firms in Nigeria. Thespecific objectives of the study include determining how the various indices of market orientation like customerorientation, competitor orientation and inter functional coordination have influenced the corporate performanceof these insurance firms. This study adopted a survey research methodology to examine the market orientationstrategies of insurance firms in an attempt to attain their desired performance potential. The hypotheses in thestudy were tested using Spearman’s Rank correlation coefficient (r), multiple regression and partial correlationanalyses to determine the strength of relationships and effects of dependent/independent and moderatingvariables respectively. Fifty two respondents of the insurance firms indicated that there was a positiverelationship between market orientation and corporate performance in the insurance industry. The result alsorevealed that age of the firm and market information system has weakly moderate the relationship. The researchfindings show that the insurance firms that engage in market orientation recorded progress while those that havenot applied this strategy experience low performance. We conclude that only the combination of customer focus,competitor focus and inter functional coordination can drive performance. This study, therefore, is of the viewthat insurance firms operating in Nigeria should emphasize market orientation if their objectives are to enhancetheir corporate performance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".