Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis

Kuttimani Tamilmani; Nripendra P. Rana; Yogesh K. Dwivedi

doi:10.1007/978-3-030-02131-3_1

Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis

Kuttimani Tamilmani^*, Nripendra P. Rana, Yogesh K. Dwivedi

^*Corresponding author for this work

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

20 Scopus citations

Abstract

Mobile phone subscriptions are the largest form of consumer technology adopted across the world. Despite their potential, the research is very scant in understanding various predictors of consumer adoption towards mobiles technologies in particular mobile applications. This study intend to fulfil this purpose through weight analysis on mobile application adoption based studies that utilized UTAUT2 model. Studies needed for weight analysis were located through cited reference search method in Scopus and Web of Science bibliographic databases. The results of weight analysis revealed performance expectancy/perceived usefulness, trust and habit as best predictors of consumer behavioural intention to mobile applications adoption whereas behavioural intention was the best predictor of use behaviour. There were also two promising predictors with perfect weight of one such as perceived risk on behavioural intention and habit on use behaviour. Further steps of this research involves meta-analysis to develop comprehensive conceptual model concurrent with weight analysis results for empirical evaluation on various mobile applications.

Original language	English
Title of host publication	Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings
Editors	Matti Mäntymäki, Salah A. Al-Sharhan, Antonis C. Simintiras, Luay Tahat, Issam Moughrabi, Taher M. Ali, Marijn Janssen, Yogesh K. Dwivedi, Nripendra P. Rana
Publisher	Springer Verlag
Pages	1-12
Number of pages	12
ISBN (Print)	9783030021306
DOIs	https://doi.org/10.1007/978-3-030-02131-3_1
State	Published - 2018
Externally published	Yes
Event	17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018 - Kuwait City, Kuwait Duration: 30 Oct 2018 → 1 Nov 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11195 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018
Country/Territory	Kuwait
City	Kuwait City
Period	30/10/18 → 1/11/18

Bibliographical note

Publisher Copyright:
© IFIP International Federation for Information Processing 2018.

Keywords

Systematic review
UTAUT2
Weight analysis

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-02131-3_1

Cite this

Tamilmani, K., Rana, N. P., & Dwivedi, Y. K. (2018). Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis. In M. Mäntymäki, S. A. Al-Sharhan, A. C. Simintiras, L. Tahat, I. Moughrabi, T. M. Ali, M. Janssen, Y. K. Dwivedi, & N. P. Rana (Eds.), Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings (pp. 1-12). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11195 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-02131-3_1

Tamilmani, Kuttimani ; Rana, Nripendra P. ; Dwivedi, Yogesh K. / Mobile application adoption predictors : Systematic review of UTAUT2 studies using weight analysis. Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings. editor / Matti Mäntymäki ; Salah A. Al-Sharhan ; Antonis C. Simintiras ; Luay Tahat ; Issam Moughrabi ; Taher M. Ali ; Marijn Janssen ; Yogesh K. Dwivedi ; Nripendra P. Rana. Springer Verlag, 2018. pp. 1-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{32aad84a660d4db8acfb950d30f4c226,

title = "Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis",

abstract = "Mobile phone subscriptions are the largest form of consumer technology adopted across the world. Despite their potential, the research is very scant in understanding various predictors of consumer adoption towards mobiles technologies in particular mobile applications. This study intend to fulfil this purpose through weight analysis on mobile application adoption based studies that utilized UTAUT2 model. Studies needed for weight analysis were located through cited reference search method in Scopus and Web of Science bibliographic databases. The results of weight analysis revealed performance expectancy/perceived usefulness, trust and habit as best predictors of consumer behavioural intention to mobile applications adoption whereas behavioural intention was the best predictor of use behaviour. There were also two promising predictors with perfect weight of one such as perceived risk on behavioural intention and habit on use behaviour. Further steps of this research involves meta-analysis to develop comprehensive conceptual model concurrent with weight analysis results for empirical evaluation on various mobile applications.",

keywords = "Systematic review, UTAUT2, Weight analysis",

author = "Kuttimani Tamilmani and Rana, \{Nripendra P.\} and Dwivedi, \{Yogesh K.\}",

note = "Publisher Copyright: {\textcopyright} IFIP International Federation for Information Processing 2018.; 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018 ; Conference date: 30-10-2018 Through 01-11-2018",

year = "2018",

doi = "10.1007/978-3-030-02131-3\_1",

language = "English",

isbn = "9783030021306",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

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editor = "Matti M{\"a}ntym{\"a}ki and Al-Sharhan, \{Salah A.\} and Simintiras, \{Antonis C.\} and Luay Tahat and Issam Moughrabi and Ali, \{Taher M.\} and Marijn Janssen and Dwivedi, \{Yogesh K.\} and Rana, \{Nripendra P.\}",

booktitle = "Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings",

address = "Germany",

}

Tamilmani, K, Rana, NP & Dwivedi, YK 2018, Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis. in M Mäntymäki, SA Al-Sharhan, AC Simintiras, L Tahat, I Moughrabi, TM Ali, M Janssen, YK Dwivedi & NP Rana (eds), Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11195 LNCS, Springer Verlag, pp. 1-12, 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Kuwait City, Kuwait, 30/10/18. https://doi.org/10.1007/978-3-030-02131-3_1

Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis. / Tamilmani, Kuttimani; Rana, Nripendra P.; Dwivedi, Yogesh K.
Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings. ed. / Matti Mäntymäki; Salah A. Al-Sharhan; Antonis C. Simintiras; Luay Tahat; Issam Moughrabi; Taher M. Ali; Marijn Janssen; Yogesh K. Dwivedi; Nripendra P. Rana. Springer Verlag, 2018. p. 1-12 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11195 LNCS).

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

TY - GEN

T1 - Mobile application adoption predictors

T2 - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018

AU - Tamilmani, Kuttimani

AU - Rana, Nripendra P.

AU - Dwivedi, Yogesh K.

N1 - Publisher Copyright: © IFIP International Federation for Information Processing 2018.

PY - 2018

Y1 - 2018

N2 - Mobile phone subscriptions are the largest form of consumer technology adopted across the world. Despite their potential, the research is very scant in understanding various predictors of consumer adoption towards mobiles technologies in particular mobile applications. This study intend to fulfil this purpose through weight analysis on mobile application adoption based studies that utilized UTAUT2 model. Studies needed for weight analysis were located through cited reference search method in Scopus and Web of Science bibliographic databases. The results of weight analysis revealed performance expectancy/perceived usefulness, trust and habit as best predictors of consumer behavioural intention to mobile applications adoption whereas behavioural intention was the best predictor of use behaviour. There were also two promising predictors with perfect weight of one such as perceived risk on behavioural intention and habit on use behaviour. Further steps of this research involves meta-analysis to develop comprehensive conceptual model concurrent with weight analysis results for empirical evaluation on various mobile applications.

AB - Mobile phone subscriptions are the largest form of consumer technology adopted across the world. Despite their potential, the research is very scant in understanding various predictors of consumer adoption towards mobiles technologies in particular mobile applications. This study intend to fulfil this purpose through weight analysis on mobile application adoption based studies that utilized UTAUT2 model. Studies needed for weight analysis were located through cited reference search method in Scopus and Web of Science bibliographic databases. The results of weight analysis revealed performance expectancy/perceived usefulness, trust and habit as best predictors of consumer behavioural intention to mobile applications adoption whereas behavioural intention was the best predictor of use behaviour. There were also two promising predictors with perfect weight of one such as perceived risk on behavioural intention and habit on use behaviour. Further steps of this research involves meta-analysis to develop comprehensive conceptual model concurrent with weight analysis results for empirical evaluation on various mobile applications.

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KW - UTAUT2

KW - Weight analysis

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DO - 10.1007/978-3-030-02131-3_1

M3 - Conference contribution

AN - SCOPUS:85055769808

SN - 9783030021306

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

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A2 - Mäntymäki, Matti

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A2 - Simintiras, Antonis C.

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A2 - Ali, Taher M.

A2 - Janssen, Marijn

A2 - Dwivedi, Yogesh K.

A2 - Rana, Nripendra P.

PB - Springer Verlag

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Tamilmani K, Rana NP, Dwivedi YK. Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis. In Mäntymäki M, Al-Sharhan SA, Simintiras AC, Tahat L, Moughrabi I, Ali TM, Janssen M, Dwivedi YK, Rana NP, editors, Challenges and Opportunities in the Digital Era - 17th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2018, Proceedings. Springer Verlag. 2018. p. 1-12. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-02131-3_1

Mobile application adoption predictors: Systematic review of UTAUT2 studies using weight analysis

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this