Application of Analytic Hierarchy Process to Determine Consumers’ Perceptions of Corporate Social Responsibility Strategy for Organizations in the Nigerian Global System for Mobile Telecommunication Industry
Bibliographic record
Abstract
In recent years, research has revealed the importance of Corporate Social Responsibility (CSR) and its significant impact on organizational performance. Also, scholars have recognized that consumers’ attitudes and behaviors towards products and organizations are greatly influenced by organizational CSR programs and strategies. Consumers are generally recognized as one of the primary stakeholders of organizations in the marketing exchange process hence their perceptions of CSR are important since stakeholders’ perceptions influence organizations' CSR practices. Given the vibrant nature of service industry in general and its telecommunication sector in particular, this study applied the Analytic Hierarchy Process (AHP) Model to determine consumers’ perceptions of the CSR activities and strategy for organizations in the Nigerian Global System for Mobile (GSM) telecommunication industry. To achieve these aims, a sample of 600 consumers of the four major operators in the Nigerian GSM telecommunication industry (MTN/AIRTEL/GLO/ETISALAT) were drawn from tertiary institutions using the convenience sampling technique. The data obtained was analyzed using descriptive statistics and the Expert Choice software. Findings show that the CSR activities consumers feel organizations in the Nigerian GSM telecommunications industry should place high priority on are: Organizing or participating in public welfare activities, Encouraging employee’s voluntary welfare programs, Improving employee welfare (facilities and benefits), Active contribution of tax to government and Contribution to cultural and literacy programs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".