Consumer Mobile Shopping Acceptance Predictors and Linkages: A Systematic Review and Weight Analysis

Kuttimani Tamilmani*, Nripendra P. Rana, Yogesh K. Dwivedi, Hatice Kizgin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Mobile phones have become an integral part of human lives with majority of people using them to access product and services for their day-to-day needs. However, mobile shopping adoption across the globe is not wide or fast as expected. In addition, the research is very scant in understanding various predictors of consumer adoption towards mobile shopping. The objective of this study is to identify most significant and non-significant predictors of consumer mobile shopping acceptance. Systematic review and weight analysis on 34 mobile shopping studies revealed researchers mostly employed TAM and UTAUT model as theoretical lens. This study found an interesting revelation that extrinsic motivation variables such as social influence and perceived usefulness determine consumer mobile shopping behavioral intention during early stages. However, in later stages intrinsic motivation variables such as satisfaction and trust play crucial role to emerge as best and promising predictor of consumer continuous intention respectively.

Original languageEnglish
Title of host publicationResponsible Design, Implementation and Use of Information and Communication Technology - 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020, Proceedings
EditorsMarié Hattingh, Machdel Matthee, Hanlie Smuts, Ilias Pappas, Yogesh K. Dwivedi, Matti Mäntymäki
PublisherSpringer
Pages161-175
Number of pages15
ISBN (Print)9783030449988
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020 - Skukuza, South Africa
Duration: 6 Apr 20208 Apr 2020
Conference number: 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12066 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020
Abbreviated titleI3E 2020
CountrySouth Africa
CitySkukuza
Period6/04/208/04/20

Keywords

  • Continuous intention
  • Mobile shopping
  • Weight analysis

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