Evidence map›Paper›PMID 36090232›Full record

ArticleHeliyon2022

Do smallholder farmers belong to the same adopter category? An assessment of smallholder farmers innovation adopter categories in Ghana.

Daniel Nyarko Ayisi, József Kozári, Tóth Krisztina

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

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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

3 authors.

Daniel Nyarko AyisiSchool of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Hungary.
József KozáriInstitute of Regional Economics and Rural Development, Hungarian University of Agriculture and Life Sciences, Hungary.
Tóth KrisztinaInstitute of Regional Economics and Rural Development, Hungarian University of Agriculture and Life Sciences, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

More often than not, good innovations introduced to farmers failed to be adopted or diffused among them, simply because the complexities and the variations in farmers' innovation adoption are not well explore. This study aims to analyse the innovation adopter categories that smallholder farmers belong to in Ghana and how their socioeconomic attributes influence their innovativeness. A survey was employed to gather information from smallholder farmers in Ghana. The data obtained from the survey were analysed using the SPSS version 22 and the Individual Innovativeness (II) scales. The hypotheses were tested using the Logistic regression model. The results indicated a large number (36.6%) of the smallholder farmers belong to the late majority of the innovation adopter category. Also, more than three-quarters of the farmers were classified as low innovators. Factors such as farmer education and gender were found to be insignificant to their innovativeness, while other prominent factors were significant to farmers' innovativeness. The study also made a novel revelation on Roger's innovation adopter categorisation values. The study concluded that smallholder farmers in the study area do not belong to a homogenous innovation adopter category. Also, educated farmers without income are less innovative. It was therefore recommended that stakeholders introducing new technologies to smallholder farmers should develop attractive marketing packages combined with videos and pictures to educate farmers on the new products, to speed up adoption.

Indexed as

AdoptionAfricaAgricultureGhanaInnovationLogitSmallholder farmerTechnology

Identifiers

PMID36090232
PMCPMC9449744

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.