ArticlePloS one2024
An analysis of the impact of digital technology adoption on the income of high quality farmers in production and operating.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital technology is shaping our traditional agriculture in unprecedented ways. As a new engine to empower farmers and promote common prosperity in rural areas, the development of the digital economy can help revitalize rural industries, providing strong support for increasing industrial value-added income and farmers' income levels. Based on 676 pooled cross-section data of high-quality farmers in China Guangdong Province from 2020-2021, the article empirically examines the impact of digital technology adoption on the production and business income of high-quality farmers and explores its mechanism of action, based on theoretical analysis and using the ERM model. It is found that the use of digital technology helps to increase the income of high quality farmers in production and business, but effects vary for different income levels and different types of high quality farmers. In addition, tests of the mechanism of action suggest that the introduction of digital technologies can mitigate the negative impact of market distance on the income of high quality farmers in production and business. After applying variable substitution, model replacement, and propensity score matching (PSM) for robustness checks, the research findings still hold true. Therefore, efforts should be made to speed up the upgrading of rural digital technology and other infrastructure, increase training for high quality farmers to improve their digital literacy through multiple channels, for the better marketing of agricultural products.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.