Determining mobile payment adoption: A systematic literature search and bibliometric analysis

Figures & data

Figure 1. Design of the study

Source:-Prepared by researcher

Table 1. Inclusion and Exclusion Criteria

Inclusion Criteria
Article Published in peer Reviewed Journal
English language
Only Empirical papers
Exclusion Criteria
Book Chapters
Review
Conference papers
Conference Review
Articles outside the scope of m-payment
Articles not available as full text

Source: Prepared by Researcher

Table 2. Descriptive Information about Scientific papers retrieved

Description	Results
Documents	56
Sources (Journals, Books, etc.)	44
Keywords Plus (ID)	167
Author’s Keywords (DE)	193
Period	2005–2020
Average citations per documents	46.66
Authors	140
Author Appearances	166
Authors of single-authored documents	4
Authors of multi-authored documents	136
Single-authored documents	4
Documents per Author	0.4
Authors per Document	2.5
Co-Authors per Documents	2.96
Collaboration Index	2.62
Document types
ARTICLE	56

Source:-Prepared by Researcher

Figure 2. Article Publication per year

Source:-Prepared by Researcher

Figure 3. Country wise Scientific Production

Source: Prepared by Researcher

Table 3. Most productive Authors in the field of m-payment(2005–2020)

Author Name	Article	Institute	Country	h index
Liébana-Cabanillas, F.	5	Universidad de Granada	Spain	20
Muñoz-Leiva, F.	4	Universidad de Granada	Spain	22
Sánchez-Fernández, J.	4	Universidad de Granada	Spain	16
Phonthanukitithaworn, C.	3	Kasetsart University	Thailand	6
Sellitto, C.	3	Victoria University Melbourne	Australia	12
Bailey, A.A.	2	The College of Business and Innovation, Toledo	US	12
Ben Mimoun, M.S.	2	Qatar University,	Qatar	6
Fong, M.W.L.	2	Victoria University Melbourne	Australia	6
Lara-Rubio, J.	2	Universidad de Granada	Spain	6
Mao, E.	2	Nicholls State University	U.S	9
Mishra, A.S.	2	Indian Institute of Management Ranchi	India	6
Pentina, I.	2	The College of Business and Innovation, Toledo	U.S	15
Singh, N.	2	Jaipuria Institute of Management	India	3
Sinha, N.	2	Guru Gobind Singh Indraprastha University	India	7
Upadhyay, P.	2	Institute of Management Technology	India	7

Source: Prepared by researcher

Table 4. Highly cited research papers on m-payment

S.No	Authors	Title	Source title	Cited by	C/Y
1	Schierz et al. (2010)	Understanding consumer acceptance of mobile payment services: An empirical analysis	Electronic Commerce Research and Applications	454	41.27
2	Kim et al. (2010)	An empirical examination of factors influencing the intention to use mobile payment	Computers in Human Behavior	420	38.18
3	Shin (2009)	Towards an understanding of the consumer acceptance of mobile wallet	Computers in Human Behavior	254	21.16
4	Leong et al. (2013).	Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach	Expert Systems with Applications	171	21.375
5	Liébana-Cabanillas et al. (2014)	Antecedents of the adoption of the new mobile payment systems: The moderating effect of age	Computers in Human Behavior	150	21.42
6	Liébana-Cabanillas et al.(2014)	The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN)	International Journal of Information Management	105	15
7	Mao et al. (2005)	A research model for mobile phone service behaviors: Empirical validation in the U.S. and Turkey	Journal of Global Information Technology Management	90	5.625
8	José Liébana-Cabanillas et al. (2014)	Role of gender on acceptance of mobile payment	Industrial Management and Data Systems	77	11
9	Koenig et al (2015)	Enjoyment and social influence: predicting mobile payment adoption	Service Industries Journal	69	11.5
10	Arvidsson (2014)	Consumer attitudes on mobile payment services—results from a proof of concept test	International Journal of Bank Marketing	68	9.71
11	Thakur & Srivastava, (2013)	Customer usage intention of mobile commerce in India: An empirical study	Journal of Indian Business Research	60	7.5
12	Johnson et al. (2018)	Limitations to the rapid adoption of M-payment services: Understanding the impact of privacy risk on M-Payment services	Computers in Human Behavior	53	17.67
13	Di Pietro et al. (2015)	The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical application to public transport	Transportation Research Part C: Emerging Technologies	51	8.5
14	Zhou(2011)	The effect of initial trust on user adoption of mobile payment	Information Development	51	5.1

Source: Prepared by Researcher

Figure 4. Co-Authorship Network of Authors

Source:-Prepared by researcher

Figure 5. Co-Authorship Network of Author Affiliated Countries

Source:-Prepared by researcher

Figure 6. Co-Occurrence of Author’s Specific Keyword

Source: Prepared by researcher

Figure 7. Bibliographic coupling of Documents

Source: Prepared by researcher

Figure 8. Co-citation pattern of the cited sources

Source:-Prepared by researcher

Figure 9. Co-citation of the cited authors

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Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216. doi:https://doi.org/10.1016/j.elerap.2009.07.005.

 Google Scholar

Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. doi:https://doi.org/10.1016/j.chb.2009.10.013.

 Google Scholar

Shin, D.-H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343–1354. doi:https://doi.org/10.1016/j.chb.2009.06.001.

 Google Scholar

Leong, L.-Y., Hew, T.-S., Tan, G. W.-H., & Ooi, K.-B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604–5620. doi:https://doi.org/10.1016/j.eswa.2013.04.018.

 Google Scholar

José Liébana-Cabanillas, F., Sánchez-Fernández, J., & Muñoz-Leiva, F. (2014). Role of gender on acceptance of mobile payment. Industrial Management & Data Systems, 114(2), 220–240. https://doi.org/https://doi.org/10.1108/imds-03-2013-0137

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Mao, E., Srite, M., Thatcher, J. B., & Yaprak, O. (2005). A research model for mobile phone service behaviors: empirical validation in the U.S. and Turkey. Journal of Global Information Technology Management, 8(4), 7–28. doi:https://doi.org/10.1080/1097198X.2005.10856406.

 Google Scholar

Koenig-Lewis, N., Marquet, M., Palmer, A., & Zhao, A. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537–554. https://doi.org/https://doi.org/10.1080/02642069.2015.1043278

 Google Scholar

Arvidsson, N. (2014). Consumer attitudes on mobile payment services - results from a proof of concept test. International Journal of Bank Marketing, 32(2), 150–170. doi:https://doi.org/10.1108/IJBM-05-2013-0048.

 Google Scholar

Thakur, R., & Srivastava, M. (2013). Customer usage intention of mobile commerce in India: an empirical study. Journal Of Indian Business Research, 5(1), 52–72. https://doi.org/https://doi.org/10.1108/17554191311303385

 Google Scholar

Johnson, V. L., Kiser, A., Washington, R., & Torres, R. (2018). Limitations to the rapid adoption of M-payment services: understanding the impact of privacy risk on M-Payment services. Computers in Human Behavior, 79, 111–122. doi:https://doi.org/10.1016/j.chb.2017.10.035.

 Google Scholar

Di Pietro, L., Guglielmetti Mugion, R., Mattia, G., Renzi, M., & Toni, M. (2015). The Integrated Model on Mobile Payment Acceptance (IMMPA): An empirical application to public transport. Transportation Research Part C: Emerging Technologies, 56, 463–479. https://doi.org/https://doi.org/10.1016/j.trc.2015.05.001

 Google Scholar

Zhou, T. (2011). The effect of initial trust on user adoption of mobile payment. Information Development, 27(4), 290–300. https://doi.org/https://doi.org/10.1177/0266666911424075

 Google Scholar