Social Commerce Adoption Predictors: A Review and Weight Analysis

Prianka Sarker; Laurie Hughe; Yogesh K. Dwivedi; Nripendra P. Rana

doi:10.1007/978-3-030-44999-5_15

Social Commerce Adoption Predictors: A Review and Weight Analysis

Prianka Sarker
, Laurie Hughe^*
, Yogesh K. Dwivedi
, Nripendra P. Rana

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Scopus citations

Abstract

Social commerce is a rapidly growing platform of e-commerce that utilises social media and online social interaction to build brand awareness and increase sales. Buying and selling through social media can create a reliable and sustainable platform for buyers and vendors, offering an alternative platform to traditional online approaches. Research on social commerce began to achieve traction in 2006 and has grown since with a significant focus from academics who have offered new insight to many of the key topics. This study seeks to offer an additional contribution to the literature by analysing the predictors of consumer adoption of social commerce from existing studies by employing a weight analysis technique. The analysis considered seven dependent variables (along with their best and worst predictors) that are most frequently examined and are relevant to consumer adoption. The review presented in this study suggests that the intention to purchase is the most frequently examined dependent variable and that trust in the social commerce context is a key factor.

Original language	English
Title of host publication	Responsible 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
Editors	Marié Hattingh, Machdel Matthee, Hanlie Smuts, Ilias Pappas, Yogesh K. Dwivedi, Matti Mäntymäki
Publisher	Springer
Pages	176-191
Number of pages	16
ISBN (Print)	9783030449988
DOIs	https://doi.org/10.1007/978-3-030-44999-5_15
State	Published - 2020
Externally published	Yes
Event	19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020 - Skukuza, South Africa Duration: 6 Apr 2020 → 8 Apr 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12066 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020
Country/Territory	South Africa
City	Skukuza
Period	6/04/20 → 8/04/20

Bibliographical note

Publisher Copyright:
© 2020, IFIP International Federation for Information Processing.

Keywords

Literature review
Social commerce
Weight analysis

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-44999-5_15

Cite this

Sarker, P., Hughe, L., Dwivedi, Y. K., & Rana, N. P. (2020). Social Commerce Adoption Predictors: A Review and Weight Analysis. In M. Hattingh, M. Matthee, H. Smuts, I. Pappas, Y. K. Dwivedi, & M. Mäntymäki (Eds.), Responsible 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 (pp. 176-191). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12066 LNCS). Springer. https://doi.org/10.1007/978-3-030-44999-5_15

Sarker, Prianka ; Hughe, Laurie ; Dwivedi, Yogesh K. et al. / Social Commerce Adoption Predictors : A Review and Weight Analysis. Responsible 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. editor / Marié Hattingh ; Machdel Matthee ; Hanlie Smuts ; Ilias Pappas ; Yogesh K. Dwivedi ; Matti Mäntymäki. Springer, 2020. pp. 176-191 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Social Commerce Adoption Predictors: A Review and Weight Analysis",

abstract = "Social commerce is a rapidly growing platform of e-commerce that utilises social media and online social interaction to build brand awareness and increase sales. Buying and selling through social media can create a reliable and sustainable platform for buyers and vendors, offering an alternative platform to traditional online approaches. Research on social commerce began to achieve traction in 2006 and has grown since with a significant focus from academics who have offered new insight to many of the key topics. This study seeks to offer an additional contribution to the literature by analysing the predictors of consumer adoption of social commerce from existing studies by employing a weight analysis technique. The analysis considered seven dependent variables (along with their best and worst predictors) that are most frequently examined and are relevant to consumer adoption. The review presented in this study suggests that the intention to purchase is the most frequently examined dependent variable and that trust in the social commerce context is a key factor.",

keywords = "Literature review, Social commerce, Weight analysis",

author = "Prianka Sarker and Laurie Hughe and Dwivedi, \{Yogesh K.\} and Rana, \{Nripendra P.\}",

note = "Publisher Copyright: {\textcopyright} 2020, IFIP International Federation for Information Processing.; 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020 ; Conference date: 06-04-2020 Through 08-04-2020",

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Sarker, P, Hughe, L, Dwivedi, YK & Rana, NP 2020, Social Commerce Adoption Predictors: A Review and Weight Analysis. in M Hattingh, M Matthee, H Smuts, I Pappas, YK Dwivedi & M Mäntymäki (eds), Responsible 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. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12066 LNCS, Springer, pp. 176-191, 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020, Skukuza, South Africa, 6/04/20. https://doi.org/10.1007/978-3-030-44999-5_15

Social Commerce Adoption Predictors: A Review and Weight Analysis. / Sarker, Prianka; Hughe, Laurie; Dwivedi, Yogesh K. et al.
Responsible 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. ed. / Marié Hattingh; Machdel Matthee; Hanlie Smuts; Ilias Pappas; Yogesh K. Dwivedi; Matti Mäntymäki. Springer, 2020. p. 176-191 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12066 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Social Commerce Adoption Predictors

T2 - 19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020

AU - Sarker, Prianka

AU - Hughe, Laurie

AU - Dwivedi, Yogesh K.

AU - Rana, Nripendra P.

PY - 2020

Y1 - 2020

N2 - Social commerce is a rapidly growing platform of e-commerce that utilises social media and online social interaction to build brand awareness and increase sales. Buying and selling through social media can create a reliable and sustainable platform for buyers and vendors, offering an alternative platform to traditional online approaches. Research on social commerce began to achieve traction in 2006 and has grown since with a significant focus from academics who have offered new insight to many of the key topics. This study seeks to offer an additional contribution to the literature by analysing the predictors of consumer adoption of social commerce from existing studies by employing a weight analysis technique. The analysis considered seven dependent variables (along with their best and worst predictors) that are most frequently examined and are relevant to consumer adoption. The review presented in this study suggests that the intention to purchase is the most frequently examined dependent variable and that trust in the social commerce context is a key factor.

AB - Social commerce is a rapidly growing platform of e-commerce that utilises social media and online social interaction to build brand awareness and increase sales. Buying and selling through social media can create a reliable and sustainable platform for buyers and vendors, offering an alternative platform to traditional online approaches. Research on social commerce began to achieve traction in 2006 and has grown since with a significant focus from academics who have offered new insight to many of the key topics. This study seeks to offer an additional contribution to the literature by analysing the predictors of consumer adoption of social commerce from existing studies by employing a weight analysis technique. The analysis considered seven dependent variables (along with their best and worst predictors) that are most frequently examined and are relevant to consumer adoption. The review presented in this study suggests that the intention to purchase is the most frequently examined dependent variable and that trust in the social commerce context is a key factor.

KW - Literature review

KW - Social commerce

KW - Weight analysis

UR - https://www.scopus.com/pages/publications/85084916893

U2 - 10.1007/978-3-030-44999-5_15

DO - 10.1007/978-3-030-44999-5_15

M3 - Conference contribution

AN - SCOPUS:85084916893

SN - 9783030449988

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 176

EP - 191

BT - Responsible 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

A2 - Hattingh, Marié

A2 - Matthee, Machdel

A2 - Smuts, Hanlie

A2 - Pappas, Ilias

A2 - Dwivedi, Yogesh K.

A2 - Mäntymäki, Matti

PB - Springer

Y2 - 6 April 2020 through 8 April 2020

ER -

Sarker P, Hughe L, Dwivedi YK, Rana NP. Social Commerce Adoption Predictors: A Review and Weight Analysis. In Hattingh M, Matthee M, Smuts H, Pappas I, Dwivedi YK, Mäntymäki M, editors, Responsible 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. Springer. 2020. p. 176-191. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-44999-5_15

Social Commerce Adoption Predictors: A Review and Weight Analysis

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this