Consumer Acceptance of More-Than-Voice (MTV) Services: Evidence from the Bottom of Pyramid in Bangladesh
Bibliographic record
Abstract
More-than-voice (MTV) services are becoming widespread in the developing countries among individuals who represent the bottom-of-pyramid (BoP). The BoP comprises individuals whose income is less than $2 per day. Despite the widespread use of MTV services among the consumers at the BoP, there is no study on what affects their adoption of these services. Therefore, this study investigates the factors that influence consumer acceptance of MTV services at the BoP. The research model proposes that perceived usefulness, perceived ease of use, perceived social influence, perceived acumen to use, perceived value and perceived facilitating conditions are the principal factors influencing the consumer acceptance of MTV services at the BoP. Secondary data collected by Teleuse@BOP4 from Bangladesh were used to validate the proposed model. Multiple regression analysis was conducted to test the hypotheses. The results indicate that the acceptance of MTV services at the BoP is positively influenced by perceived usefulness, perceived ease of use, perceived acumen to use, perceived facilitating conditions and perceived value. The results also indicate that perceived social influence has no significant influence on the acceptance of MTV services by consumers in the BoP.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".