The Impact of Mobile Telephony on Developing Country Enterprises: A Palestinian Case Study
Bibliographic record
Abstract
Abstract This paper aims to explore the use and impact of mobile telephony on the performance of companies in developing countries, through a nationwide survey comprised of thousands of enterprises representing a true sample of the business sector in Palestine. This paper complements studies that make the linkage between mobile communications and economic activities at micro or enterprise level. It analyses the adoption patterns and rational behind these patterns as revealed by the business owners and managers of Palestinian enterprises. Porter's value chain is used as a framework to assess the impact of mobile telephony in work processes. The survey covered thousands of enterprises of all sizes and economic activities, selected to embody a representative sample of the Palestinian business sector. It further explores the views of the owners and managers of these enterprises regarding the use of ICTs. The study reveals that mobile phones have meaningfully enhanced internal processes and the overall value chain. Most notably, mobile phones were effective in bridging the information and connectivity gap businesses in developing countries ordinarily suffer. The study has also found that small and micro enterprises gain from the use of mobiles the same as what large enterprises do, especially in mainstream operations like marketing and sales, information flow, and provision of customer services. This is happening at the time when there is a huge difference in resources between the two categories of enterprises. The study came to conclude that mobile benefits are not favoring one business sector from the other, in the sense that all business sectors are capable of tailoring mobile phone services to suit their needs.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".