An Empirical Examination of Competitive Capability’s Contribution toward Firm Performance: Moderating Role of Perceived Environmental Uncertainty
Bibliographic record
Abstract
In the world of competition, manufacturing and service companies are trying to enhance their competitive capabilities in order to be able to give more value to their customers and gain prominent positions in competition with other companies. Every company tries to concentrate on its one or more capabilities in competition in order to turn them into a clear competitive advantage that improves the firm performance. In fact, it is necessary for the firms being active in market and being consistent with competitive requirements to gain and maintain a competitive advantage. This study investigates the effect of competitive capability on firm performance under environmental uncertainty conditions. The findings show that competitive capability has direct positive effect on customer satisfaction, financial performance, and market performance. In other words, enhancing these capabilities leads to improving customer satisfaction and increases market and financial performance. Investigation of the effects of different aspects of competitive capabilities on different performance aspects show that the capability of cost leadership positively affects financial performance and market performance but, has no effect on customer satisfaction. Also, the capability of differentiation has direct positive effect on customer satisfaction but affects financial performance and market performance negatively. Additionally, the examination of the moderating effect of perceived environmental uncertainty on the relationship between competitive capability and firm performance shows that in different environmental conditions, the effects of cost leadership capability on customer satisfaction, differentiation capability on financial performance, and differentiation capability on market performance are moderated. On the other word, managerial decisions in these areas are affected by environmental conditions involved in processes of material supply, production, and market demand.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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".