Evidence map›Paper›PMID 36878938›Full record

ArticleScientific reports2023

Exploring consumers' environmental ethical preferences in the context of unmanned aerial vehicle utilization for plant protection.

Baoshu Wu, Jinlian Lu, Bo Zhou, Zhenjiang Song

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Baoshu WuSchool of Business Administration, Jiangxi University of Finance and Economics, Nanchang, 330032, China.
Jinlian LuCollege of Economics and Management, Jiangxi Agricultural University, Nanchang, 330045, China.
Bo Zhou *College of Economics and Management, Jiangxi Agricultural University, Nanchang, 330045, China. 7836zhoubo@163.com.
Zhenjiang Song *College of Economics and Management, Jiangxi Agricultural University, Nanchang, 330045, China. tgsongzhenjiang@126.com.
Jiangxi Agricultural University · CNJiangxi University of Finance and Economics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of unmanned aerial vehicles (UAVs) has increased agricultural productivity, achieved food security, and eased the pressure associated with environmental degradation and population growth. However, consumer sentiment remains unclear. The results show that pressures regarding food safety, production safety, and ecological safety have different degrees of positive impact on perceived benefits but no significant impact on perceived barriers. They strongly influence both perceived benefits to the adoption of UAV plant protection agricultural products. Perceived benefits demonstrated a mediating role between the three safety pressures and the adoption of UAVs. Lay beliefs showed a positive moderating effect on perceived benefits and obstacles to the adoption of UAV-based plant protection products. Based on these findings, this paper concludes that consumers are developing new consumer ethics that integrate concepts of food safety, safe production, and regional environmental protection with their acceptance of new technology, which is directly dependent on the combined effect of environmental and consumer ethics. To promote sustainable development, policies must be further optimized on this original basis.

Indexed as

MagnoliopsidaUnmanned Aerial DevicesAgricultureFood SafetyPolicy

Identifiers

PMID36878938
PMCPMC9987396
OpenAlexW4323313485

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.