A game theory-based analysis of merchants’ mobile payment adoption using hybrid SEM-neural network approach

Babak Naysary

doi:10.1108/CR-04-2023-0074

A game theory-based analysis of merchants’ mobile payment adoption using hybrid SEM-neural network approach

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	Competitiveness Review
DOIs	https://doi.org/10.1108/CR-04-2023-0074
Publication status	Published (VoR) - 15 Aug 2023

Keywords

Malaysia
Merchants’ perspective
Mobile payment
Opportunism
Trust

Access to Document

10.1108/CR-04-2023-0074

Cite this

@article{6462f6c6f42c4c88acface30c4882877,

title = "A game theory-based analysis of merchants{\textquoteright} mobile payment adoption using hybrid SEM-neural network approach",

keywords = "Malaysia, Merchants{\textquoteright} perspective, Mobile payment, Opportunism, Trust",

author = "Babak Naysary",

note = "Publisher Copyright: {\textcopyright} 2023, Emerald Publishing Limited.",

year = "2023",

month = aug,

day = "15",

doi = "10.1108/CR-04-2023-0074",

language = "English",

journal = "Competitiveness Review",

issn = "1059-5422",

publisher = "Emerald",

}

TY - JOUR

T1 - A game theory-based analysis of merchants’ mobile payment adoption using hybrid SEM-neural network approach

AU - Naysary, Babak

PY - 2023/8/15

Y1 - 2023/8/15

KW - Malaysia

KW - Merchants’ perspective

KW - Mobile payment

KW - Opportunism

KW - Trust

UR - http://www.scopus.com/inward/record.url?scp=85167408207&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85167408207&partnerID=8YFLogxK

UR - https://www.open-access.bcu.ac.uk/15154/

U2 - 10.1108/CR-04-2023-0074

DO - 10.1108/CR-04-2023-0074

M3 - Article

AN - SCOPUS:85167408207

SN - 1059-5422

JO - Competitiveness Review

JF - Competitiveness Review

ER -

A game theory-based analysis of merchants’ mobile payment adoption using hybrid SEM-neural network approach

Keywords

Access to Document

Other files and links

Fingerprint

Cite this