Evidence map›Paper›PMID 36249586›Full record

ArticleBusiness strategy and the environment2022

Achieving sustainability: Determinants of conscious green purchasing behavior during the COVID-19 pandemic.

Xianchuan Yang, Jiayun Jiang, Shih-Chih Chen

Abstract read
In one paragraph

Article in Business strategy and the environment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Xianchuan YangSchool of Economics and Management Wuxi Vocational Institute of Commerce Wuxi Jiangsu China Mainland.ORCID https://orcid.org/0000-0002-4534-2878
Jiayun JiangSchool of Digital Commerce Wuxi Vocational Institute of Commerce Wuxi Jiangsu China Mainland.
Shih-Chih ChenDepartment of Information Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has spread worldwide, resulting in crises in public health and sustainable development. Aimed at understanding the determinants of conscious green purchasing behavior (GPB), this paper developed a comprehensive framework linking the moderating effect of negative environmental affective reactions (NEAR) to COVID-19 based on the S-O-R paradigm. Using randomly selected urban residents from China's Yangtze River Delta and Bohai Rim regions, the empirical study was conducted using 559 valid responses. The results show that media and peers are the major social forces activating altruistic and egoistic motivations, while family influence was not significant. Dual motivations significantly mediated the relationships of unconditional and conditional GPB with media exposure and peer influence. Contrary to expectations, NEAR negatively moderated the formation process of conscious GPB. The findings indicate that the influence of peers on conscious GPB through dual motivations is stronger compared to media. Negative affective reactions to COVID-19 were also found to inhibit the impact of peer influence on altruistic and egoistic motivations, as well as the path of altruistic motivation on unconditional GPB. The results of this study have important theoretical and practical implications for enterprise marketing and environmental campaigns, and narrowing the green attitude-behavior gap.

Indexed as

conditional green purchasing behaviorCOVID‐19 emergencydual motivationsS–O–R modelunconditional green purchasing behavior

Identifiers

PMID36249586
PMCPMC9538399

What OpenQuestion holds

Textmetadata
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.