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The Impact of Technology Perception and Government Support on E-Commerce Sales Behavior of Farmer Cooperatives

Evidence From Liaoning Province, China

Bibliographic Data

ID3538930
AuthorsYanan Huang (0000-0003-0354-9608, Shenyang Agricultural University), Xu Li (0000-0003-3888-3235, Shenyang Agricultural University, corresponding author), Guangsheng Zhang (0000-0002-9776-0529, Liaoning University, corresponding author)
Year2021
Volume11
Issue2
Publication date2021-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSAGE Open (JOURNAL)
Journal identifiersISSN: 2158-2440 • E-ISSN: 2158-2440
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/21582440211015672
OpenAlexW3170641356
LanguageEN
Citations received4
References cited15

The sales-related difficulties faced by cooperatives can be solved by expanding their sales channels through e-commerce. However, extant studies have only examined cooperatives' e-commerce sales behavior from either a technology perception or government support perspective. To fill this gap, based on survey data of 215 farmer cooperatives in Liaoning province, China, this study employs a probit model to analyze the impact of both technology perception and government support on these cooperatives' e-commerce sales behavior, as well as their marginal and accelerating effects. Both factors were shown to have a significant positive impact. Technology perception has a greater impact on e-commerce sales behavior than government support, while perceived effectiveness has the most significant impact. This study also found that government support has an accelerating effect on the relationship between technology perception and farmer cooperatives' e-commerce sales behavior. Therefore, governments should improve cooperative members' technology perception to aid them in expanding sales

Business · China · E-commerce · Economics · Extant taxon · Ordered probit · Perception · Probit model · Survey data collection · Digital Marketing and Social Media · Psychology · Marketing

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Unique citing works4
Citations per year2
Citation span2024 - 2025 (2)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 4

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