THE EFFECTS OF ADVERTISING ON CONSUMER BUYING BEHAVIOUR IN THE MOBILE TELECOMMUNICATION INDUSTRY
Bibliographic record
Abstract
Marketing as a business concept has been largely accepted all over the world, and Ghana is no exception. This recognition has increased competition among businesses in Ghana. Companies are resulting to various strategies and tactics in order to be on top of the markets in which they operate. Over the years, the prominent tool that businesses have relied on to compete basically has been the marketing communication tools, of which advertising stands tall. Advertising is probably the first option that comes to mind when businesses need to communicate to the market. Advertising is so pervasive in our business environment that, one begins to wonder whether businesses that use it are achieving their objectives. In Ghana today, the highest advertising spenders are the Mobile Telecommunication Companies. It is reported that in 2009, mobile telecommunication advertising spend recorded 43.5 billion Ghana Cedis out of a total of 184.9 billion Ghana Cedis. That is about 23.5% or close to a quarter of the entire national advertising budget. (www.myjoyonline.com/businessreport, 23rd June 2010.)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".