An Empirical Study on the Adoption of RFID Technology for Logistics Service Providers in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of this paper is to study the influences of technological, organizational and environmental factors on the adoption of RFID technology for logistics service providers in China. While the growth of China’s economy hinges to a large extent on the ability of the logistics industry to operate more efficiently and effectively in the global supply chain system, China’s logistics companies should pay attention to adopt more efficient logistics technologies to provide better services for their customers. The data to study the factors affecting the adoption of RFID technology came from a questionnaire survey of logistics service providers in China, and 574 logistics companies were analyzed. According to the survey results, about fifty percents of logistics companies are interested in RFID technology, but less than ten percents have the experiences of using RFID technology. Explicitness and accumulation of technology, organizational encouragement for innovation, quality of human resources, and governmental support exhibit significant influences on the willingness to adopt RFID technology.
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.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it