Receiving and Action Oriented Attitude of the Youth Towards Mobile Marketing: A Transitional Economy Perspective
Bibliographic record
Abstract
The advancement in technology is influencing the ways in which organizations conduct business and marketing activities. Mobile Marketing has become one of the most widespread media to communicate with potential and existing customers mainly in the form of text advertisements through the internet. This study is aimed at finding out the receiving and action-oriented attitudes of the youth towards mobile marketing, particularly the rate at which the youth use mobile marketing to determine the propensity to be influenced in their actions. The study also investigated the factors affecting consumer attitudes and their relationship with mobile marketing. The study employed descriptive and exploratory research methodology design and the data were collected using a structured questionnaire. Four hundred (400) questionnaires were administered to young people between the ages of 18 and 35 years in Accra and Three hundred and fifty 350 were used. We found a high rate of youth’s preference for mobile marketing messages and a relationship between youth attitude and mobile marketing messages and/or the youth’s attitude being influenced by mobile marketing messages. Finally, it revealed that there is a relationship between the youth’s receiving and action-oriented attitude and consumer factors that influence the use of mobile marketing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".