Evidence map›Paper›PMID 32992905›Full record

ArticleInternational journal of environmental research and public health2020

University Students' Purchase Intention and Willingness to Pay for Carbon-Labeled Food Products: A Purchase Decision-Making Experiment.

Rui Zhao, Meng Yang, Jianxiao Liu, Linchuan Yang, Zhikang Bao, Xinyun Ren

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

6 authors.

Rui ZhaoSouthwest Jiaotong University, Chengdu 611756, China.
Meng YangSouthwest Jiaotong University, Chengdu 611756, China.
Jianxiao LiuDepartment of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, China.
Linchuan YangSouthwest Jiaotong University, Chengdu 611756, China.ORCID 0000-0001-6070-9044
Zhikang BaoDepartment of Real Estate and Construction, University of Hong Kong, Hong Kong, China.
Xinyun RenSouthwest Jiaotong University, Chengdu 611756, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon labeling describes carbon dioxide emissions across food lifecycles, contributing to enhancing consumers' low-carbon awareness and promoting low-carbon consumption behaviors. In a departure from the existing literature on carbon labeling that heavily relies on interviews or questionnaire surveys, this study forms a hybrid of an auction experiment and a consumption experiment to observe university students' purchase intention and willingness to pay for a carbon-labeled food product. In this study, students from a university in a city (Chengdu) of China, the largest carbon emitter, are taken as the experimental group, and cow's milk is selected as the experimental food product. The main findings of this study are summarized as follows: (1) the purchase of carbon-labeled milk products is primarily influenced by price; (2) the willingness to pay for carbon-labeled milk products primarily depends on the premium; and (3) the students are willing to accept a maximum price premium of 3.2%. This study further offers suggestions to promote the formation of China's carbon product-labeling system and the marketization of carbon-labeled products and consequently facilitate low-carbon consumption in China.

Indexed as

Consumer BehaviorFood LabelingStudentsAnimalsCattleChinaFemaleHumansIntentionUniversitiesauction experimentcarbon-labeled foodconsumer behaviorconsumption experimentmilkprice premiumpurchase intentionuniversity studentwillingness to pay

Identifiers

PMID32992905
PMCPMC7579656

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Registered trials

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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.