Evidence map›Paper›PMID 37965665›Full record

ArticleFrontiers in psychology2023

An empirical analysis of the factors driving customers' purchase intention of green smart home products.

Mingyan Guo, Shufeng Simon Xiao

Abstract read
In one paragraph

Article in Frontiers in psychology, 2023. 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
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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

2 authors.

Mingyan GuoCollege of Business, Gachon University, Seongnam, Republic of Korea.
Shufeng Simon XiaoDivision of Business Administration, Sookmyung Women's University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the improvement of consumers' environmental awareness and the popularity of the Internet of Things, green smart home products (GSHPs) are becoming the dominant trend of future home life. This shift not only makes tedious home life easier and more convenient but also helps families save energy and reduce carbon emissions. However, given the impact of the current technological level, the proportion of users who actually purchase GSHPs remains small. Thus, seeking ways to promote the consumption of GSHPs has become an urgent issue. Hence, this study seeks to fill the gap in the existing research on green consumption behavior and obtain a full understanding of the factors influencing the purchase intention of GSHPs. To do so, this work uses task-technology fit theory and considers the actual situation of green smart home consumption to add social-technology fit into the original theoretical basis. In particular, this research focuses on middle- and high-end Chinese consumers who have experience in purchasing GSHPs. Moreover, it aims for an in-depth exploration of the formation mechanism of Chinese consumers' purchase intention for GSHPs through structural equation modeling. Using survey data collected from 331 green smart home product users in China, the study empirically examines the relationships among autonomy, environmental agility, sense of belonging, and self-actualization, and both task-technology fit and social-technology fit, which are expected to shape the purchase intention of GSHP users. The empirical results provide broad support for our hypotheses. The results of this study offer important contributions to the increasing research on GSHPs consumption and shed light on the importance of both technology characteristics and the needs of users in achieving both task-technology fit and social-technology fit and, ultimately enhancing the users' intention to purchase GSHPs.

Indexed as

green smart home productspurchase intentionself-actualizationsense of belongingssocial-technology fittask-technology fit

Identifiers

PMID37965665
PMCPMC10640982

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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.