THE 10th ISLAMIC BANKING, ACCOUNTING AND FINANCE INTERNATIONAL CONFERENCE 2022
(iBAF 2022)
The Determinants that Influence Mobile Payment Adoption: A Systematic Literature Review
Tuty Kamis
Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia
Tel: +606 798 6304 E-mail: [email protected]
Syadiyah Abdul Shukor
Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia
Tel: + 606 798 6417 E-mail: [email protected]
Norhaziah Nawai
Faculty of Economics and Muamalat, Universiti Sains Islam Malaysia (USIM), Bandar Baru Nilai, 71800 Nilai, Negeri Sembilan Malaysia
Tel: + 606 798 6440 E-mail: [email protected]
Abstract
Mobile payments are a new financial technology-based payment method that allows users to conduct payments via smartphones has become relevant over the past decade in developed and developing countries. Various determinants affect user behaviour toward accepting mobile payments. Hence, identifying the determinants influencing mobile payment adoption remains crucial and needs to be refined and scrutinised to remain relevant to the current situation. Therefore, this study synthesises literature from 2010 to 2021 on mobile payment adoption among users using the PRISMA approach, including identification, screening, and eligibility. Articles are identified through databases such as SCOPUS, Web of Science, Science Direct, Google Scholar, and Mendeley. 953 articles are screened according to the exclusion and inclusion criteria, and duplication matters. Finally, only 67 complete articles were selected for further synthesis and analysis. Applying a thematic analysis using ATLAS ti.8, three sub-themes were coded— personal, environment and barriers, to categorise the determinants.
A study found that innovation is the most frequently examined personal factor, relative advantage and ease of use are the most frequently evaluated environmental factors, and perceived risk has also been the most frequently examined barrier influencing mobile payment adoption a decade ago. This review applied PRISMA is needed to help researchers extend past research to examine further current trends that determine the factors influencing mobile payment adoption. In addition, this review's findings can help stakeholders formulate effective strategies for mobile payment services.
Keywords: Mobile payment; systematic literature review; PRISMA
1. Introduction
Mobile payment is a series of processes for payment through mobile devices that directly links to financial
institutions or through Fintech payment service that connects with financial institutions through IT companies
(Kang, 2018). Generally, mobile payment is a new technology-based payment method enabling users to operate
payments through mobile smartphones (Zhou, 2013) and transfer amounts via mobile phone devices from payer
with or without an intermediary (Mallat, 2007). Mobile payment also is an electronic transaction or exchange of
information under the action of a mobile device and mobile networks (Ramadan and Aita, 2018), leading to the
handover of actual or perceived value in transference for information, services, or goods (Zhou, 2013). Mobile
payment is carried out with a mobile instrument such as a mobile credit card or a mobile wallet (Dahlberg et al.,
2015). Other researcher means mobile payment as a payment that replaced the traditional payment method, which
operated through mobile devices with networks transferred for economic transactions such as purchasing goods,
bills, and services (Choi et al., 2020; Dahlberg et al., 2015; Gong, Cheung, et al., 2020; Gong, Zhang, et al., 2020a;
Gong, Zhang, et al., 2020b; Gong, Zhang, et al., 2020c; Humbani and Wiese, 2017; Iman, 2018; Kang, 2018;
Liébana-Cabanillas et al., 2017; Schierz et al., 2010).
Review articles had arranged to afford a creative standpoint on a topic that configured future research (Alexander, 2020). Also, it contributed substantially to developing knowledge in the discipline (Durach et al., 2017). Review creates a robust basis for knowledge advancement to facilitate theory development, alleviate similarities in an area where much research exists and exposes areas where research needs to be explored (Webster and Watson, 2002). Moreover, a thoroughly conducted review can provide relevant parties with an extensive update on the interest topic or concern (Toronto and Remington, 2020). Snyder (2019) stated that conducting a systematic literature review can identify all empirical evidence of certain research areas that fit the inclusion criteria to answer research questions with minimum bias and reliable findings. A systematic review can justify research rigour that allows for gaps in identification and directions for future research (Shaffril et al., 2020; Shaffril et al., 2018).
Globally, it was reported that in 2019, 89% of consumers were aware of the existence of in-store mobile payment platforms, and 82% were aware of peer-to-peer payment systems and non-bank money transfers (Ernst and Young, 2019). This shows customer acceptance of mobile payments and service providers have a competitive advantage in the industry. However, some factors influence customer acceptance of mobile payments. Some countries have very high internet penetration among consumers, but the penetration rate of mobile payment usage is still low. For example, in developing countries like Malaysia, it was reported in 2018 that internet penetration was 85.7%, online banking penetration reached 85.1%, and application mobile penetration was only 40% (Fong, 2018). While the data reveals a low transaction value for Fintech mobile apps, it is seen that mobile apps are the preferred alternative for payments. It can be concluded that customers accept mobile payments but still lack confidence in using them. Therefore, this literature review is needed for the researcher to extend the previous study to study the trend of factors influencing consumer adoption of mobile payment services.
This review aims to synthesise literature from 2010 to the first half of 2021 on the variance of mobile payment adoption and to discuss the scope of the studies on which the researcher focus based on the main research question – what are the determinants that influence mobile payments adoption among users? This study is about the consumer perspective as this group is the end-users who accept this new digital payment platform, thus leading to financial inclusion (Rana et al., 2019; Zhang et al., 2022) that is important to socio-economic development (Pal et al., 2020).
This review study contributes to three major areas. This study focused on mobile payment across the area of study and highlighted the determinants that influenced consumers' adoption of mobile payments by the previous researcher. Secondly, this paper addressed the future direction of mobile payment concerns. Finally, this study applied the approach of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and utilised a systematic literature review with a systematic searching strategy (Shaffril et al., 2020). This in-depth review study systematically plans to validate the research questions. Thus, it is useful for scholars to guide their future studies to extend previous studies by examining current trends in determining the factors that influence mobile payments adoption and suggesting future research directions. This first section describes the study's purpose, while the second section details the methodology. The third section systematically reviews and synthesises the scientific literature to identify, select and evaluate selected articles. And the last section identifies future research paths.
2. Methodology
Review can be of many types, and the most basic review is a narrative review that summarises selected literature without any systematic method on a selected study that only supports the reviewer's opinions or assumptions (Toronto and Remington, 2020). The integrative review contains theoretical and methodological literature as the aim of the review which all selected studies went through the process of identifying, analysing, appraising and synthesising excluded statistical synthesis methods (Toronto and Remington, 2020). And the most complex is a systematic review, which collects, analyses, appraises and synthesises the randomised control studies that address a formulated question (Higgins et al., 2021; Page, Moher, et al., 2021; Page, McKenzie, et al., 2021).
Fisch and Block (2018) indicate that the review process should be crystal clear and reproducible by clearly outlining the search strategy in identifying relevant literature systematically with as much transparency as possible. And through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) as a basis for a systematic review that allows the evaluation of random trials, it was reporting other systematic reviews and appropriate for critical appraisal of published systematic reviews (Moher et al., 2009).
Hence, this study utilises PRISMA as a basis for the review. PRISMA determines how to search the literature
and applies screened and eligibility criteria. In the end, a smaller number of articles will remain (Moher et al.,
2009). This study uses systematic searching strategies applied by Shaffril et al. (2020) in synthesising the searched
article to capture the knowledge gap. And the data were synthesised through thematic analysis using ATLAS. ti
8 to evaluate trends and patterns (Zairul, 2020) of determinants that influence mobile payment adoptions in the various published articles a decade ago.
2.1 Resources
The literature searching of this study relies on the Web of Science Core Collection (WoS) and Scopus as a leading databases. Gusenbauer and Haddaway (2020) point out that if the reviewer's goal is to reach beyond the limitations of a specialised search system, it might prove beneficial to use citation information from a comprehensive, multidisciplinary search system and quality article controls to broaden the search scope and these features found in WoS dan Scopus. Furthermore, this leading database has used the search function with the most frequent Boolean operator, truncation, and wild cards in particular phrase searching (Gusenbauer and Haddaway, 2020).
Moreover, Shaffril et al. (2020) revealed WoS maintained by Clarivate Analytics is a scientific citation indexing service that is only accessed through institutional subscription-based services with a comprehensive citation search function in multiple databases referenced across disciplinary research. While Scopus is one of the largest abstracts and citation databases of peer-reviewed literature that consists of diverse subject areas and document types such as scientific journals, books, and conference proceedings in multifield of research with smart tools component that able to track, analyse, and visualise research easily (Shaffril et al., 2020). In total, the leading databases used in the searching process were two, and further searching continued with the additional database.
According to (Gusenbauer and Haddaway 2020), supplementary search methods can improve search outcomes. An additional database is needed to enrich data sources such as non-indexing journals and search variations for missing articles from the leading databases (Shaffril et al., 2018). Moreover, Xiao and Watson (2019) stated that searches should be taken from various databases due to the unavailability of a database that includes a complete set of published material. Thus, the literature searching of this study continues with other four supporting databases, namely EBSCO, ProQuest, Mendeley, Google Scholar, and University/ Institution Library (printed document).
This study selects Google Scholar as a supporting database in expanding the scope of literature search due to the different policy of Google Scholar than indexing databases that can produce tremendous results and found as an important resource that is freely available (Loan and Sheikh, 2018). Also, Loan and Sheikh (2018) found that Google Scholar is very helpful in finding resources, which often leads users to the availability of the sources such as institution libraries or open access sources. Furthermore, more than a hundred million journal articles are available on Google Scholar (Gusenbauer and Haddaway, 2020; Orduña-Malea et al., 2017; Haddaway et al., 2015). Google Scholar contains a large amount of grey literature and specialised and well-known studies, but most of the literature identified duplicates similar search results used in the Web of Science, with some important literature found missing in the search. Thus, Google Scholar is used only as a supporting searching method and cannot be used alone for systematic literature searches (Haddaway et al., 2015). Halevi et al. (2017) found that most studies focused on coverage issues found in the major publisher coverage content, which indicate quality and transparent indexing policies, originality and advanced search options that are full of quality control indexing capabilities, and all of these are not available on Google Scholar. Also, the quality control over its indexing capabilities is debated (Halevi et al., 2017), and the inability to export results in bulk as a citation also limits the use of Google Scholar in scholarly searches. Therefore, this literature study combines this database with a controlled database and not as a leading source.
Electronic searching is not enough, and search can be supplemented by manual searching through printed journals (Okoli, 2015). Therefore, this study searched for the related printed journals/documents, and the university/agency library was visited face to face or via email. Application for selected articles is available through inter-library loan services offered by University / institutional libraries.
2.2 Inclusion and exclusion criteria
This study determined the selection criteria applied to find suitable articles in the systematic review process to ensure that only relevant articles needed to be read and reviewed—the criteria as summarised in Table 1.
Table 1. Inclusion and exclusion criteria.
Criteria Inclusion Exclusion
Timeline publication 2010 to June 2021 none
Publication type Article journal Journal (systematic review), conference proceeding, newspaper, review paper, book
Language English Other than English
2.3 Process of systematic review
Shaffril et al. (2019) and Shaffril et al. (2018) stated that the systematic searching strategies involved several processes: 1) Identification, the process of identifying and enriching keywords using advanced and manual searching techniques, 2) Screening, an article screened based on selection criteria done automatically from a selected database or excluded manually, and 3) Eligibility, the process to ensure that the selected article meets the specified criteria as highlighted by Moher (2009). And a four-phase flow diagram (Moher. 2009) has been practised and adapted (Shaffril et al., 2020) in this study, as depicted in Figure 1, which summarises the systematic review process of this study.
Figure 1. The flow diagram of the study (adapted from Moher et al., 2009; Samsuddin et al., 2019; Shaffril et al., 2019)
2.3.1 Identification
Identification starts with keyword identification for information searching purposes. This process searches for any synonym, related terms, and variation for the main keywords (Shaffril et al., 2020; Shaffril et al., 2019;
Shaffril et al., 2018) based on study purposes and questions (Durach et al., 2017) namely mobile payments, user and adoption. Ultimately, these keywords will be used to build a search string, which is applied to an electronic academic database (Pilbeam et al., 2012) and provide more options for a selected database to search for more related literature to review (Shaffril et al., 2020). Within the scope of the study, keywords were determined and enriched from several relevant information sources such as Thesaurus (https://www.thesaurus.com and https://www.lexico.com/english-thesaurus), encyclopaedia (https://www.encyclopedia.com), Google synonyms, Word thesaurus, and keywords suggested by experts as well as raw searching (handpicking and snowballing) were also practised, and the result as shown in Table 2.
Table 2. Keyword identification.
Section Main keywords Enriched keywords
RQ. What are the determinants that influence mobile payments adoption among users?
1) Mobile payments 2) Adoption 3) User 4) Determinants
1) Mobile payment = mobile payment system, electronic wallet, electronic money, mobile contactless payment excluding bitcoin and crypto 2) Adoption = acceptance, favourable,
favour to use, usage, continuance usage, actual use, intention
3) User = consumer 4) Determinant = factor
Accordingly, after all the relevant keywords are determined, electronic searching starts with search strings on
a selected electronic database. The quantity and type of database that should be used are among the important
things in a systematic literature review; however, there is no ideal database (Shaffril et al., 2020). Therefore, the
researcher took the approach by categorising the systematic search according to the leading and supporting
databases.
The search process in leading and supporting databases is based on search string criteria such as field code search, advanced search, Boolean functionality, phrase extract, parentheses search and truncation/ wildcards depending on certain database requirements (Gusenbauer and Haddaway, 2020). Google Scholar only allows searches with a maximum search string length of up to 256 characters without Boolean functionality support (Haddaway et al., 2015), while ScienceDirect allows a maximum of eight Booleans used in the search string. The search strings for the database searching for this study are presented in Table 3.
Table 3. Search string from the database searching.
RQ. What are the determinants that influence mobile payments adoption among users?
Database Search strings
SCOPUS: TITLE-ABS-KEY (("mobile payment system" OR "m-payment" OR "electronic wallet" OR "E- Wallet" OR "electronic money" OR "E-money" OR "mobile contactless payment" AND NOT
"bitcoin*" AND NOT "crypto*") AND ("consumer*" OR "user*") AND ("adopt*" OR "accept*" OR
"favo*rable" OR "favo*r" OR "continua* usage" OR "actual use" OR "usage" OR "intent*" OR
"inten*") AND ("determinant*" OR "factor*"))
WoS: (TS=(("mobile payment system" OR "m-payment" OR "electronic wallet" OR "E-Wallet" OR
"electronic money" OR "E-money" OR "mobile contactless payment" NOT "bitcoin*" NOT
"crypto*") AND ("consumer*" OR "user*") AND ("adopt*" OR "accept*" OR "favo*rable" OR
"favo*r" OR "continua* usage" OR "actual use" OR "usage" OR "intent*" OR "inten*") AND ("determinant*" OR "factor*")))
EBSCO TI (("mobile payment*" OR "mobile payment system*" OR "m-payment*" OR "electronic wallet"
OR "E-Wallet*" OR "electronic money*" OR "E-money*" OR "mobile contactless payment*") NOT ("bitcoin*" NOT "crypto*") AND ("user*" OR "consumer*") AND ("adopt*" OR "accept*" OR
"favo*rable" OR "favo*r" OR "continua* usage" OR "actual use" OR "usage" OR "intent*" OR
"inten*") AND ("determinant*" OR "factor*"))
ProQuest ft("mobile payment system" OR "m-payment" OR "electronic wallet" OR "E-Wallet" OR "electronic money" OR "E-money" OR "mobile contactless payment" NOT "bitcoin*" NOT "crypto*") AND ft("consumer*" OR "user*") AND ft("adopt*" OR "accept*" OR "favo*rable" OR "favo*r" OR
"continua* usage" OR "actual use" OR "usage" OR "intent*" OR "inten*") AND ft("determinant*"
OR "factor*")
Mendeley ("mobile payment system" OR "m-payment" OR "electronic wallet" OR "E-Wallet" OR "electronic money" OR "E-money" OR "mobile contactless payment") AND ("consumer" OR "user") AND ("adoption" OR "acceptance" OR "usage" OR "actual use" OR "actual usage" OR "intention") AND ("determinant*" OR "factor*") year: [2010 TO 2021]
Google Scholar ("mobile payment" OR "electronic wallet” OR "electronic money" OR "mobile contactless payment") ("user" OR "consumer") ("adoption" OR "acceptance" OR "intention") ("determinant" OR "factor")
2.3.2 Screening
After searching articles from the database, in screening phases, the identified articles with inclusion criteria will be included, while the articles that did not meet the criteria set in the exclusion level are excluded. Based on timeline publication criteria, Onkoli (2015) stated that reviews often focus on studies in certain date ranges the ability to review and limit the time span is coveted (Gusenbauer and Haddaway (2020). The Scopus database shows that a study on mobile payment use began 1989 years earlier, followed by several publications in 2010 consistently with less than 10 per year until 2018 and an aggressively increased start in 2019. This shows that the field of study still needs further research (Kraus et al., 2020) to explore up-to-date information (Gusenbauer and Haddaway, 2020), which aligns with the study to examine the variation of mobile payment in various fields of study. This study limit searches between January 2010 and June 2021 because the search process begins in June 2021 and does not end (Onkoli, 2015). For publication types, to ensure the quality of the review, this research focuses on primary sources (Shaffril et al., 2020) that offer empirical data from journals or research articles that have been published (Shaffril, Abu Samah, et al., 2019). Kraus et al. (2020) emphasised the quality of articles found through the journal rankings and other resources such as review articles, while newspapers and magazines were excluded. To ensure accessibility, English is more practical (Fisch and Block, 2018) as a research language (Kraus et al., 2020) that can avoid confusion and reduce misunderstanding (Shaffril et al., 2019). Hence, this study focuses on articles written in English as the author can read and have access to scholarly databases (Gusenbauer and Haddaway, 2020; Onkoli, 2015).
The searching process has revealed documents from Scopus (281), WoS (324), ProQuest (387), EBSCO (193), Mendeley (376) and Google Scholar (15,700). After the inclusion and exclusion criteria and duplication were taken into account, the screening process successfully identified 402 articles to proceed to the eligibility process.
2.3.3 Eligibility
Manual screening is applied in this process. This process is important to minimise the fault generated by the
database, and this process can be done by reading the title and abstract of the articles. The identification and
screening process using a computer is prone to errors, so, during the manual screening process, articles that meet
the set criteria can be included. Otherwise, they could be excluded from consideration (Shaffril et al., 2020). All
402 articles were scrutinised to ensure the articles were in line with inclusion criteria and fit to be selected in this study that consistently achieved the study objectives. Then the article content will be checked to continue finding the article's relevance. Some articles were unrelated to mobile payment adoption, and there were also incomplete articles, broken links or inaccessible articles. The remaining 155 articles were appraised for their quality to avoid any bias and maintain a high-quality level (Shaffril et al., 2020). For quality appraisal, based on the criteria set, the co-author categorised the quality of the articles only high-quality and moderate-quality articles were included and excluded the low-quality articles. Finally, 67 articles were selected for data synthesis and analysis.
2.4 Data synthesis and Analysis
Data can be synthesised quantitatively, qualitatively, or combined with both (Shaffri et al., 2020). Quantitative synthesis or meta-analysis, in which researchers statistically combine and summarise the results of multiple studies (Moher et al., 2015). In contrast, qualitative synthesis is analysis with a creative approach through realistic and critical interpretation and explanation, such as thematic analysis (Shaffril et al., 2020). According to Braun and Clarke (2006), the thematic analysis identifies prominent or recurring themes in the collected data, which are then summarised under thematic headings. This study performed a thematic analysis using ATLAS. ti 8 in interpreting and explaining the present status of the research on mobile payment adoption among users and analyses the determinants that influence mobile payment adoption among the users.
With 67 final articles selected (see Appendix A), all were transferred to Mendeley as the main document, and later each article was exported to the ATLAS ti.8 software in EndNote XML Export file (*.xml) format and automatically in document group generated by Mendeley metadata (Figure 2). Using ATLAS.ti 8 for classification has made the sorting much easier and systematic (Zairul 2020). All articles are grouped according to 1) author, 2) publication and 3) year of publication. Initially, this study coded five main themes and three sub- themes to identify the determinants of mobile payments adoption among users. And three sub-themes are coded—
personal, environment and barriers, to locate the determinants. Through the analysis, this study clarifies the findings to illuminate the future research direction discussed further in the next section.
Figure 2. The code group generated from Mendeley metadata
3. Results and Discussions
3.1 Present status of previous research
The number of publications published a decade ago. The study of mobile payments was attentively focused in
2015 with 9 publications, then the number of publications shows an upward trend until 2020 with 17 publications,
and estimated to increase until the end of 2021 (Figure 3). This figure shows that research on mobile payment
adoption has become vital in different research areas (Figure 4). Numerous research found in areas of business,
management, marketing, accounting, finance and economics, with 27 articles published a decade ago. Other fields
also received researchers' attention on mobile payments adoption, such as Arts and Humanities (6), Artificial
intelligence (4), communication (4), automotive engineering, geography development, and library information
science, one publication respectively.
Figure 3. Publications status by the year
Figure 4. Publications contributing to a research area
This study also identifies the venue of the study. In Figure 5, the country with dark shades shows the highest number of research conducted. China is a country that regularly conducts studies on mobile payments in 14 publications—followed by India in 10, Malaysia in 8 and Spain in 7 publications. Meanwhile, research venues according to the region (Figure 6), most research was conducted in East Asia and the Pacific region (in 30 publications), followed by Europe and Central Asia region (in 18 publications). Research on mobile payments is still fresh in countries with upper-middle-income economies (China-14, Colombia-1, Jordon-1, Malaysia-9, South Africa-3). However, high-income countries remain continuing research on mobile payments (Europe-1, France- 2, Germany-2, Hungary-1, Italy-1, Korea-2, Kuwait-1, Portugal-1, Spain-7, Sweden-1, Taiwan-4, Unites Kingdom-2, Unites States-2). Lower-middle-income countries (Bangladesh-1, India-9, Indonesia-1) and lower- income regions (Syria-1) have begun to explore mobile payments.
Figure 5. Research venue by country (data plotted generated from Microsoft Excel Workbook powered by Microsoft Bing- www.bing.com/maps/)
27 17
6 3
4 4 1 1 1
0 5 10 15 20 25 30
Business, Management, Marketing, Accounting, Finance, Economics Computer, Information Sysytems, Network,
Innovation
Arts and Humanities Artificial Intelligence, Science Applied Psychology Communication Automotive Engineering Geography, Planning and Development Library and Information Science
Figure 6. Research venue by (a) region and (a) income level
Figure 7. Word cloud generated from 67 articles
In the word count depicted in Figure 7, from the selected articles, the word mobile seems to have the highest frequency, 8652 times, followed by the word payment 7257 times, m-payment 1807 times. The word online 1271 times to combine the word as online payment and word card 301 times to combine the word as card payment.
Thus, the trends of mobile payment or m-payment are popularly used in prior research. On top of that, the word intention 3042 times compared to word usage 996 times, word adoption 3073 times compared to word acceptance 1513 times, which shows that consumers mainly intend to accept mobile payment via near-field-communication or NFC (601-word counts), and quick-response or QR (315-word counts) code scanning.
3.2 Determinants that influence mobile payment adoption among users
Using Atlas ti.8, this study created the code group name of the independent variable (IV). All relevant variables stated in the article were identified and extracted into code group IV. The Code-Document Table in Atlas ti.8 generated determinants of mobile payment usage among users from 67 selected articles (refer to Appendix B).
Following that, this study identified the factors that were frequently examined for a decade, as shown in Table 4.
The most frequent factors examined in prior research were relative advantage, perceived ease of use and social
influence. Mobile payments are innovative digital financial tools containing consumers' sensitive information,
including identification numbers. Thus, users' perceptions of risk and security on mobile payment systems have
also been focused on by researchers to date. Subsequently enabled service providers to build consumer trust in
this new payment method.
Table 4. Frequent determinants derived from articles.
Determinants Qty (no.) References
Relative advantage/
perceived usefulness/
performance expectancy/
perceived benefits
40 Bailey et al., 2019; de Luna et al., 2019; Daragmeh et al., 2021; de Luna et al., 2015; Di Pietro et al., 2015; Fan et al., 2020; Hampshire, 2017; Humbani and Wiese, 2019; Hussain et al, 2019;
Ibrahim et al., 2019; Johnson et al. , 2018; Kalinić, et al., 2020; Kalinić, et al., 2019; Kapoor et al., 2015; Kim et al., 2010; Koenig-Lewis et al., 2015; Leong et al., 2021; Li et al., 2019; Liébana- Cabanillas et al., 2020; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas et al., 2017; Liébana- Cabanillas, et al., 2015; Lin et al., 2020; Moorthy et al., 2019; Lu and Wung, 2020; Oliveira et al., 2016; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Rabaa'i and Zhu, 2021; Schierz et al., 2010; Shankar and Datta, 2018; Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Teo et al., 2015; Teo et al., 2015; Thakur and Srivastava, 2014; Yeh, 2020; Zhang and Mao, 2019; Wu et al., 2017;
Perceived ease of use/ complexity/
effort expectancy
36 Alwi et al., 2019; Arvidsson, 2014; Bailey et al., 2019; Daragmeh et al., 2021; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015; Kim et al., 2010; Hampshire, 2017; Humbani and Wiese, 2019; Ibrahim et al., 2019; Johnson et al., 2018; Kapoor et al., 2015; Koenig-Lewis et al., 2015; Leong et al., 2021; Li et al., 2019; Liébana-Cabanillas et al., 2020; Liébana- Cabanillas et al., 2018; Liébana-Cabanillas et al., 2017; Liébana-Cabanillas, et al., 2015; Moorthy et al., 2019; Oliveira et al., 2016; Pal et al., 2020; Patil et al., 2020; Qasim and Abu-Shanab, 2016;
Rabaa'i and Zhu, 2021; Shankar and Datta, 2018; Schierz et al., 2010; Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Teo et al., 2015; Teo et al., 2015; Thakur and Srivastava, 2014; Yeh, 2020; Zhang and Mao, 2019;
Social influence/
Subjective norms/
social norms/ social benefits/
29 Daragmeh et al., 2021; de Kerviler et al., 2016; de Luna et al., 2019; de Luna et al., 2015;
Handarkho et al., 2020; Hussain et al, 2019; Ibrahim et al., 2019; Kalinić, et al., 2020; Kalinić, et al., 2019; Koenig-Lewis et al., 2015; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas et al., 2017; Liébana-Cabanillas, et al., 2015; Lin et al., 2020; Oliveira et al., 2016; Moorthy et al., 2019;
Patil et al., 2020; Qasim and Abu-Shanab, 2016; Schierz et al., 2010; Shankar and Datta, 2018;
Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Sun et al., 2019; Teo et al., 2015; Teo et al., 2015; Thakur and Srivastava, 2014; Verma et al., 2019; Zhang and Mao, 2019;
Perceived risk 20 Bailey et al., 2019; de Kerviler et al., 2016; Hampshire, 2017; Handarkho et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Kalinić, et al., 2020; Kalinić, et al., 2019; Kapoor et al., 2015; Koenig-Lewis et al., 2015; Li et al., 2019; Liébana-Cabanillas et al., 2020; Liébana- Cabanillas et al., 2017; Pal et al., 2020; Slade et al., 2015; Su et al., 2018; Thakur and Srivastava, 2014; Wiese and Humbani, 2019; Wu et al., 2017;
Perceived security 19 Arvidsson, 2014; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015; Humbani and Wiese,201 9; Humbani and Wiese, 2018; Ibrahim et al., 2019; Johnson et al.,2018; Leong et al., 2021; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas, et al., 2015; Lin et al., 2020; Loh et al., 2020; Moorthy et al., 2019; Oliveira et al., 2016; Rabaa'i and Zhu, 2021; Ramadan and Aita, 2018; Schierz et al., 2010; Wiese and Humbani, 2019;
Innovativeness 18 Fan et al., 2020; Handarkho et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017;
Haidar et al., 2019; Kalinić, et al., 2020; Kalinić, et al., 2019; Kim et al., 2010; Leong et al., 2021;
Liébana-Cabanillas et al., 2020; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas et al., 2015;
Lui et al., 2021; Oliveira et al., 2016; Patil et al., 2020; Shankar and Datta, 2018; Slade et al., 2015; Wiese and Humbani, 2019
Perceived trust 17 Bailey et al., 2019; Gong et al., 2019; Hampshire, 2017; Kalinić et al., 2020; Kalinić et al., 2019;
Liébana-Cabanillas et al., 2020; Loh et al., 2020; Pal et al., 2020; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Rabaa'i and Zhu, 2021; Shankar and Datta, 2018; Slade et al., 2015; Teo et al., 2015; Yu et al., 2016; Yuan et al., 2020; Zhou, 2015;
Compatibility 16 Arvidsson, 2014; de Luna et al., 2015; Di Pietro et al., 2015; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Hussain et al, 2019; Kapoor et al., 2015; Kim et al., 2010; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas, et al., 2015; Leong et al., 2021; Lin et al., 2020; Lui et al., 2021;
Oliveira et al., 2016; Schierz et al. 2010; Yeh, 2020;
Perceived cost 15 Arvidsson, 2014; Fan et al., 2020; Gong et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Kapoor et al., 2015; Kuo, 2020; Lin et al., 2020; Loh et al., 2020; Rabaa'i and Zhu, 2021; Teo et al., 2015; Wiese and Humbani, 2019; Yeh, 2020; Zhou, 2013; Zhou, 2015;
Attitude 12 Bailey et al., 2019; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015; Hampshire, 2017; Li et al., 2019; Liébana-Cabanillas et al., 2017; Liébana-Cabanillas, et al., 2015; Patil et al., 2020; Schierz et al., 2010; Sun et al., 2019; Verma et al., 2019; Zhang and Mao, 2019;
The articles selected in this study are derived from a user-perspective study on mobile payments that considered factors related to the use of technology (Renaud and Biljon, 2008). As noted in the Social Cognitive Theory of Bandura (1986), personal factors, environmental factors and behaviour influenced each other.
Moreover, Peter and Tapey (1975) stated that consumers make purchasing decisions to minimise negative affect, maximise positive affect and maximise overall net worth. And this study argues that analysing the factors that influence positively or negatively the adoption of mobile payments is fairly important. Therefore, all determinants identified are categorised into three sub-groups: personal, environmental and barrier, and Table 5 shows the frequent determinant examined a decade ago.
Personal factors explain individual differences (Bandura, 1986), which consists of any cognitive, personality,
or demographic aspects (Carillo, 2010) that could explain customers' perceptions and behaviours because of
people's dissimilarities traits (Agarwal and Prasad, 1999). From the findings, this study grouped the individual
characteristics that differ in terms of their innovativeness, attitude, satisfaction, individual mobility, perceived
enjoyment, habit, image, experience, knowledge and self-efficacy. Personal innovation is "an individual's
willingness to try any new information technology" (Agarwal and Prasad, 1998). And mobile payments are a new digital financial innovation. Thus, it is frequently studied as a determinant that plays an important role in consumer adoption of mobile payment as new technology.
Meanwhile, environmental factors refer to the social and physical environment factors that can influence an individual's behaviour which consists of the system and task characteristics and social factors or social pressure (Carillo, 2010). The study's findings indicate that system and task characteristics include determinants of relative advantage, ease of use, compatibility, security, quality, and network externality. Relative advantage refers to "the degree to which an innovation is perceived as better than the idea it supersedes" (Rogers, 1983), and perceived usefulness is "the degree to which a person believes that using a particular system would enhance his or her job performance" (Davis, 1989). These determinants indicate that mobile payments are advantageous and have been frequently studied for a decade. In addition, perceived ease of use is also often received by researcher attention in mobile payment research. Perceived ease of use refers to "the degree to which a person believes that using a particular system will be effortless" (Davis, 1989) and imply that mobile payments are free from any difficulties.
Social factors and social pressure include determinants of social influences or subjective norms and facilitating conditions are also categorised as environmental factors.
Social cognitive theory by Bandura in 1986 indicates that resistance factors such as anxiety, stress and other effects are included as personal factors (Carillo, 2010). Yet, this study separated the resistance from personal factors because mobile payment is an innovative product that leads to innovation resistance which creates potential changes from a satisfactory status quo to a functional and psychological barrier that results in individuals' resistance to technology adoption (Ram and Sheth, 1989). The study's findings indicate that the main determinants decade ago to date are perceived risk, trust, cost and privacy. Bauer (1960) defined perceived risk in consumer behaviour as the uncertainty consumers face when they cannot predict outcomes which may negatively impact their decision to use new technologies (Bauer, 1967), such as mobile payments. There are several perceived risk categories that prior research focused on, like financial risk, performance risk, psychological risk, social risk, time risk, privacy risk, and overall risk (Featherman and Pavlou, 2003; Peter and Tarpey, 1975).
Table 5. Sub-group determinants.
Sub-group Qty (#) Determinants
Personal 18 Innovativeness, Fan et al., 2020; Handarkho et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Haidar et al., 2019; Kalinić, et al., 2020; Kalinić, et al., 2019;
Kim et al., 2010; Leong et al., 2021; Liébana-Cabanillas et al., 2020; Liébana- Cabanillas et al., 2018; Liébana-Cabanillas et al., 2015; Lui et al., 2021; Oliveira et al., 2016; Patil et al., 2020; Shankar and Datta, 2018; Slade et al., 2015; Wiese and Humbani, 2019
12 attitude Bailey et al., 2019; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015; Hampshire, 2017; Li et al., 2019; Liébana-Cabanillas et al., 2017; Liébana- Cabanillas, et al., 2015; Patil et al., 2020; Schierz et al., 2010; Sun et al., 2019;
Verma et al., 2019; Zhang and Mao, 2019;
9 Satisfaction Fan et al., 2020; Garrett et al., 2014; Humbani and Wiese, 2019; Kalinić, et al., 2019; Liébana-Cabanillas et al., 2020; Ramadan and Aita, 2018; Yuan et al., 2020; Zhou, 2013; Zhou, 2015
6 Individual mobility
de Luna et al., 2016; Kim et al., 2010; Liébana-Cabanillas et al., 2018; Liébana- Cabanillas, et al., 2015; Schierz et al., 2010; Zhang and Mao, 2019;
4 Perceived
enjoyment Bailey et al., 2019; Handarkho et al., 2020; Kalinić, et al., 2019; Koenig-Lewis et al., 2015
4 Habit Hussain et al, 2019; Loh et al, 2020; Lu and Wung, 2020; Pal et al., 2020;
4 Social Image Kapoor et al., 2015; Liébana-Cabanillas et al., 2017; Lin et al., 2020; Zhang and Mao, 2019;
3 Use experience de Kerviler et al., 2016; Ramadan and Aita, 2018; Teo et al., 2015;
3 Hedonic
Motivation
Hussain et al., 2019; Moorthy et al., 2019; Oliveira et al., 2016;
3 Mobile payment
knowledge Kim et al., 2010; Koenig-Lewis et al., 2015; Lui et al., 2021 3 self-efficacy Lui et al., 2021; Shankar and Datta, 2018; Wang et al., 2019;
Environmental 40 Relative advantage/
perceived usefulness/
performance expectancy/
perceived benefits
Bailey et al., 2019; de Luna et al., 2019; Daragmeh et al., 2021; de Luna et al., 2015; Di Pietro et al., 2015; Fan et al., 2020; Hampshire, 2017; Humbani and Wiese, 2019; Hussain et al, 2019; Ibrahim et al., 2019; Johnson et al. , 2018;
Kalinić, et al., 2020; Kalinić, et al., 2019; Kapoor et al., 2015; Kim et al., 2010;
Koenig-Lewis et al., 2015; Leong et al., 2021; Li et al., 2019; Liébana-Cabanillas et al., 2020; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas et al., 2017;
Liébana-Cabanillas, et al., 2015; Lin et al., 2020; Moorthy et al., 2019; Lu and Wung, 2020; Oliveira et al., 2016; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Rabaa'i and Zhu, 2021; Schierz et al., 2010; Shankar and Datta, 2018; Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Teo et al., 2015; Teo et al., 2015;
Thakur and Srivastava, 2014; Yeh, 2020; Zhang and Mao, 2019; Wu et al., 2017;
36 Perceived ease of use/ complexity/
effort expectancy
Alwi et al., 2019; Arvidsson, 2014; Bailey et al., 2019; Daragmeh et al., 2021; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015; Kim et al., 2010;
Hampshire, 2017; Humbani and Wiese, 2019; Ibrahim et al., 2019; Johnson et al.,
2018; Kapoor et al., 2015; Koenig-Lewis et al., 2015; Leong et al., 2021; Li et al., 2019; Liébana-Cabanillas et al., 2020; Liébana-Cabanillas et al., 2018; Liébana- Cabanillas et al., 2017; Liébana-Cabanillas, et al., 2015; Moorthy et al., 2019;
Oliveira et al., 2016; Pal et al., 2020; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Rabaa'i and Zhu, 2021; Shankar and Datta, 2018; Schierz et al., 2010; Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Teo et al., 2015; Teo et al., 2015;
Thakur and Srivastava, 2014; Yeh, 2020; Zhang and Mao, 2019;
29 Social influence/
Subjective norms/
social norms/
social benefits/
Daragmeh et al., 2021; de Kerviler et al., 2016; de Luna et al., 2019; de Luna et al., 2015; Handarkho et al., 2020; Hussain et al, 2019; Ibrahim et al., 2019;
Kalinić, et al., 2020; Kalinić, et al., 2019; Koenig-Lewis et al., 2015; Liébana- Cabanillas et al., 2018; Liébana-Cabanillas et al., 2017; Liébana-Cabanillas, et al., 2015; Lin et al., 2020; Oliveira et al., 2016; Moorthy et al., 2019; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Schierz et al., 2010; Shankar and Datta, 2018; Sinha et al., 2019; Slade et al., 2015; Su et al., 2018; Sun et al., 2019; Teo et al., 2015; Teo et al., 2015; Thakur and Srivastava, 2014; Verma et al., 2019;
Zhang and Mao, 2019;
19 Perceived security
Arvidsson, 2014; de Luna et al., 2019; de Luna et al., 2015; Di Pietro et al., 2015;
Humbani and Wiese,201 9; Humbani and Wiese, 2018; Ibrahim et al., 2019;
Johnson et al.,2018; Leong et al., 2021; Liébana-Cabanillas et al., 2018; Liébana- Cabanillas, et al., 2015; Lin et al., 2020; Loh et al., 2020; Moorthy et al., 2019;
Oliveira et al., 2016; Rabaa'i and Zhu, 2021; Ramadan and Aita, 2018; Schierz et al., 2010; Wiese and Humbani, 2019;
16 Compatibility Arvidsson, 2014; de Luna et al., 2015; Di Pietro et al., 2015; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Hussain et al, 2019; Kapoor et al., 2015; Kim et al., 2010; Liébana-Cabanillas et al., 2018; Liébana-Cabanillas, et al., 2015;
Leong et al., 2021; Lin et al., 2020; Lui et al., 2021; Oliveira et al., 2016; Schierz et al. 2010; Yeh, 2020;
9 Convenience Alwi et al., 2019; de Kerviler et al., 2016; Handarkho et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Kim et al., 2010; Leong et al., 2021; Lu and Wung, 2020; Lui et al., 2021; Teo et al., 2015;
9 Facilitating conditions
Hussain et al., 2019; Moorthy et al., 2019; Oliveira et al., 2016; Pal et al., 2020;
Patil et al., 2020; Sinha et al., 2019; Teo et al., 2015; Teo et al., 2015;
7 Service quality Alwi et al., 2019; Fan et al., 2020; Kuo, 2020; Ramadan and Aita (2018); Yeh, 2020; Yuan et al., 2020; Zhou, 2013;
4 System quality Fan et al., 2020; Kuo, 2020; Yuan et al., 2020; Zhou, 2013;
3 Information quality
Kuo, 2020; Yuan et al., 2020; Zhou, 2013;
3 Alternative attractiveness
Kuo, 2020; Loh et al., 2020; Rabaa'i and Zhu, 2021;
3 Network
externality
Gong et al., 2020b; Pal et al., 2020; Qasim and Abu-Shanab, 2016;
Barrier 20 Perceived risk Bailey et al., 2019; de Kerviler et al., 2016; Hampshire, 2017; Handarkho et al., 2020; Humbani and Wiese, 2019; Humbani and Wiese, 2017; Kalinić, et al., 2020; Kalinić, et al., 2019; Kapoor et al., 2015; Koenig-Lewis et al., 2015; Li et al., 2019; Liébana-Cabanillas et al., 2020; Liébana-Cabanillas et al., 2017; Pal et al., 2020; Slade et al., 2015; Su et al., 2018; Thakur and Srivastava, 2014; Wiese and Humbani, 2019; Wu et al., 2017;
18 Perceived trust Bailey et al., 2019; Gong et al., 2019; Hampshire, 2017; Kalinić et al., 2020;
Kalinić et al., 2019; Liébana-Cabanillas et al., 2020; Loh et al., 2020; Pal et al., 2020; Patil et al., 2020; Qasim and Abu-Shanab, 2016; Rabaa'i and Zhu, 2021;
Shankar and Datta, 2018; Slade et al., 2015; Teo et al., 2015; Yu et al., 2016;
Yuan et al., 2020; Zhou, 2015;
15 Perceived cost Arvidsson, 2014; Fan et al., 2020; Gong et al., 2020; Humbani and Wiese, 2019;
Humbani and Wiese, 2017; Kapoor et al., 2015; Kuo, 2020; Lin et al., 2020; Loh et al., 2020; Rabaa'i and Zhu, 2021; Teo et al., 2015; Wiese and Humbani, 2019;
Yeh, 2020; Zhou, 2013; Zhou, 2015;
5 Perceived privacy Johnson et al., 2018; Gong et al., 2020; Sinha et al., 2019; Su et al., 2018; Wang et al., 2019
4. Future Direction
This review study has identified the determinants influencing mobile payment adoption among users. Even so, several research areas need to be scrutinised in future research. First, this review study focuses on mobile payment adoption among users, mainly on the end-user consumer. In the future, the researcher may consider merchants, retailers or other industry users to extend the scope of the study. And this study is limited to the mobile payment context. Perhaps bitcoins and cryptocurrencies or other electronic money might be included in future research. The literature selected should include conference papers, dissertations and book series, with a great number appearing in the database, while this review study only includes articles published in refereed academic journals.
Moreover, to add resources, future research may consider citation tracking techniques to track articles cited in
the paper being studied, other than through online searches (Shaffril et al., 2018; Wright et al., 2014). This review
study analyses qualitatively through the thematic analysis method using Atlas ti.8. Future research is encouraged to use the latest software version with various great functions that help produce more interesting findings. Also, future researchers could use other software for qualitative data analysis, such as NVivo. On top of thematic analysis, future research is worth analysing using meta-analysis in detail. Apart from the existing area of research, in the future, other research areas can explore the adoption of mobile payments, like in the area of politics and legislation, gerontology and technology (gerontechnology), and environmental perspective.
Apart from existing research areas, in the future, other research areas can be explored related to mobile payments, such as in the fields of politics and policy, gerontology and technology (gerontechnology), and environmental perspectives. Also, other determinants can be explored, such as shariah compliance in managing deposited money (Mohamed Naim et al., 2019; Sharma et al., 2017). Determinants that differentiate the use of mobile payments among households between rural and urban areas (Zhang et al., 2022). Moreover, determinants of financial literacy in choosing effective and profitable payment methods include electronic money (Foster et al., 2022). Finally, the cultural determinants underlying Hofstede's various dimensions are also an issue to the uniqueness of mobile payment acceptance (Liu et al., 2019).
5. Conclusion
Overall, the study found a high concurrence among researchers over the past decade on mobile payments adoption among users. Prior research has been extensively researched to find a determinant that influenced mobile payment adoption among users across economic and geographic backgrounds. Innovative is the most frequently examined personal factor, relative advantage and ease of use are the most frequently evaluated environmental factors, and perceived risk has also been the most frequently examined obstacle in the past decade. Overall, the identified determinants yield ideas for future academic research undertaking. Thus, more studies are needed to unravel the complex problems related to mobile payments adoptions.
Acknowledgements
The authors thank the Ministry of Higher Education, Malaysia and Universiti Sains Islam Malaysia for
carrying out this study.
Appendix A. The final article in a systematic literature review
No Authors Publications No Authors Publications
1 Daragmeh et al. (2021) Journal of Behavioral and Experimental Finance 35 Li et al. (2019) IEEE Access
2 Rabaa'i and Zhu (2021) Interdisciplinary Journal of Information, Knowledge, and
Management 36 Wang et al. (2019) Information and Management
3 Leong et al. (2021) European Business Review 37 Haidar et al. (2019) Jurnal Pengurusan
4 Lui et al. (2021) Pertanika Journal of Social Sciences and Humanities 38 Liébana-Cabanillas et al. (2018) Technological Forecasting and Social Change 5 Yeh (2020) Journal of Theoretical and Applied Electronic Commerce
Research
39 Grover and Kar (2020) Journal of Retailing and Consumer Services 6 Kalinić, et al. (2020) International Journal of Bank Marketing 40 Shankar and Datta (2018) Global Business Review
7 Choi et al. (2020) Telematics and Informatics 41 Ramadan and Aita (2018) International Journal of Bank Marketing
8 Pal et al. (2020) Information Technology for Development 42 Johnson et al. (2018) Computers in Human Behavior
9 Yuan et al. (2020) Electronic Commerce Research and Applications 43 Su et al. (2018) Technology Analysis and Strategic Management 10 Patil et al. (2020) International Journal of Information Management 44 Cao et al. (2018) Internet Research
11 Liébana-Cabanillas et al.
(2020) Telecommunications Policy 45 Liébana-Cabanillas (2017) Service Business
12 Lin et al. (2020) Online Information Review 46 Humbani and Wiese (2017) Journal of African Business
13 Gong et al. (2020) International Journal of Electronic Commerce 47 Hampshire (2017) International Journal of Bank Marketing 15 Gong et al. (2020) International Journal of Information Management 48 Wu et al. (2017) Industrial Management and Data Systems
16 Gong et al. (2020) Information Technology and People 49 Falk et al. (2016) Journal of Business Research
17 Kaur et al. (2020) Journal of Retailing and Consumer Services 50 Qasim and Abu-Shanab (2016) Information Systems Frontiers
18 Loh et al. (2020) Internet Research 51 de Kerviler et al. (2016) Journal of Retailing and Consumer Services
19 Lu and Wung (2020) Journal of Theoretical and Applied Electronic Commerce Research
52 Oliveira et al. (2016) Computers in Human Behavior
20 Kuo (2020) Technology in Society 53 de Luna et al. (2016) Information System and e-Business Management
21 Fan et al. (2020) Journal of Theoretical and Applied Electronic Commerce Research
54 Teo et al. (2015) Industrial Management and Data Systems 22 Handarkho and
Harjoseputro (2020)
Journal of Enterprise Information Management 55 Teo et al. (2015) International Journal of Mobile Communications
14 Gong et al. (2019) Information and Management 56 Slade et al. (2015) Psychology and Marketing
23 Kalinić et al. (2019) Journal of Retailing and Consumer Services 57 Di Pietro et al. (2015) Transportation Research Part C-Emerging Technologies
24 Zhang and Mao (2019) Psychology and Marketing 58 Kapoor et al. (2015) Information Systems Frontiers
25 Sun et al. (2019) International Journal of Hospitality Management 59 Zhou (2015) International Journal of Technology and Human Interaction 26 Hussain et al. (2019) International Journal of Bank Marketing 60 Koenig-Lewis et al. (2015) Service Industries Journal
27 Sinha et al. (2019) International Journal of Bank Marketing 61 Liébana-Cabanillas et al. (2015) Technology Analysis and Strategic Management 28 Humbani and Wiese
(2019)
International Journal of Bank Marketing 62 Thakur and Srivastava (2014) Internet Research 29 Wiese and Humbani
(2019)
International Review of Retail, Distribution and Consumer Research
63 Arvidsson (2014) International Journal of Bank Marketing 30 Moorthy et al. (2019) International Journal of Finance and Economics 64 Garrett et al. (2014) Family and Consumer Sciences Research Journal
31 Verma et al. (2019) International Journal of Bank Marketing 65 Zhou (2013) Decision Support Systems
32 Alwi et al. (2019) International Journal of Advanced Science and Technology 66 Schierz et al. (2010) Electronic Commerce Research and Applications 33 Bailey et al. (2019) International Review of Retail, Distribution and Consumer
Research
67 Kim et al. (2010) Computers in Human Behavior 34 de Luna et al. (2019) Technological Forecasting and Social Change
Appendix B. Determinants derived from 67 articles
Reference Determinants
Alwi et al. (2019) ease of use, security and privacy, information presentation, convenience, service and quality
Arvidsson (2014) relative advantage, costs, compatibility, ease of use, network externalities, trust in actors, perceived security risks Bailey et al. (2019) system trust, perceived risk, perceived enjoyment, perceived ease of use, perceived usefulness
Cao et al. (2018) trust in online payment, perceived similarity, perceived entitativity, trust in mobile payment Choi et al. (2020) mobile payment platform, assurance policy, mileage program, authentication method, affiliated stores
Zhang and Mao (2019) perceived ease of use, usefulness, relative advantage, attitude, emotion, responsiveness, smartness, mobility, subjective norms. number of users, number of peers who use, perceived availability of NFC mobile payments at retailers, perceived social image of using
Daragmeh et al. (2021) subjective norm, perceived ease of use, perceived usefulness, perceived COVID-19 risk
de Kerviler et al. (2016) perceived risks, perceived benefits (utilitarian, hedonic, and social), experience with an in-store mobile service de Luna et al. (2019) subjective norms, perceived ease of use, attitude, perceived security
Di Pietro et al. (2015) ease of use, usefulness, security, attitude. compatibility Falk et al. (2016) mobile payment and basket price judgments
Fan et al. (2020) dissatisfaction on system quality, dissatisfaction on service quality, perceived switching cost, personal innovativeness, relative advantage of substitute it, critical mass
Garrett et al. (2014) age, education, (household) income, difficulty paying bills, use of online payment services, use of mobile phone for checkout, number of credit cards, credit card use, have bank account
financial knowledge, financial satisfaction
Gong et al. (2020) brand equity, platform-application complementarity, application-service complementarity, service-strategy complementarity Gong et al. (2019) cognitive trust, emotional trust, perceived entitativity
Gong et al. (2020) privacy concerns, perceived effectiveness of privacy setting, perceived effectiveness of privacy policy, perceived effectiveness of industry self-regulation, perceived effectiveness of government legislation
Gong et al. (2020) transition costs, sunk costs, loss aversion, inertia Grover (2020) user participation, user engagement, content frequency
Haidar et al. (2019) perceived usefulness, perceived ease of use, personal innovativeness, subjective norm, perceived security Handarkho and Harjoseputro
(2020)
perceived risk, perceived enjoyment, convenience, deal proneness, consumer innovativeness, subjective norms, perceived herd behaviour Yeh (2020) relative advantage, compatibility, complexity, trialability, observability
Humbani and Wiese (2017) optimism, innovativeness, convenience, compatibility, insecurity, discomfort, perceived cost, perceived risk
Humbani and Wiese (2019) optimism, innovativeness, convenience, compatibility, discomfort, insecurity, perceived cost, perceived risk, adoption, ease-of-use, usefulness, satisfaction Hussain et al. (2019) performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit, lifestyle, compatibility Kalinić et al. (2019) customers' satisfaction, subjective norms, trust
perceived usefulness, perceived risk, perceived enjoyment, personal innovativeness
Kapoor et al. (2015) relative advantage, compatibility, complexity, trialability, observability, cost, communicability, riskiness, social approval, voluntariness, image, result demonstrability, visibility Kaur et al. (2020) usage barriers, value barriers, risk barriers, tradition barriers, image barriers
Koenig-Lewis et al. (2015) perceived usefulness, perceived ease of use, perceived risk, knowledge, perceived enjoyment, social influence
Kuo (2020) information quality, system quality, service quality, regret, alternative attractiveness, perceived network size of the alternative, perceived complementarity of the alternative, inertia, benefit loss costs, transition costs, uncertainty costs, sunk costs
Leong et al. (2021) perceived usefulness, perceived ease of use, perceived security, perceived compatibility, user mobility, personal innovativeness Li et al. (2019) risk perception, attitude, perceived usefulness, perceived ease of use
Liébana-Cabanillas et al.
(2015)
attitude, perceived usefulness, perceived ease of use, personal innovativeness in information technology, individual mobility, perceived compatibility, perceived security, subjective norms
Liébana-Cabanillas et al.
(2017)
social image, subjective norms, ease of use, perceived usefulness, attitudes, trust, perceived risk
Liébana-Cabanillas et al.
(2018) perceived ease of use, perceived usefulness, perceived compatibility, subjective norms, individual mobility, personal innovativeness, perceived security Liébana-Cabanillas (2020) innovativeness, stress, perceived ease of use, perceived satisfaction, perceived usefulness, perceived risk, perceived trust
Lin et al. (2020) relative advantage, service compatibility, security risk, perceived fees, perceived value, social norms, social self-image
Loh et al. (2020) monetary value, alternative attractiveness, trust, perceived security and privacy, switching costs, traditional payment habit, inertia
Lu and Wung (2020) perceived trouble, lack of transaction records, difficulty of paying large amounts in cash, perceived convenience, perceived benefit, perceived time-saving, habits Lui et al. (2021) personal innovativeness, mobile payment knowledge, self-efficacy, convenience, compatibility
Moorthy et al. (2019) performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, perceived security
Oliveira et al. (2016) performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, innovativeness, compatibility, perceived technology security Pal et al. (2020) price benefit, network externalities, trust, habit, perceived risk, facilitating conditions, operational constraints
Patil et al. (2020) performance expectancy, effort expectancy, social influence, facilitating conditions, personal innovativeness, anxiety, trust, grievance redressal, attitude, behavioural intention Qasim and Abu-Shanab (2016) effort expectancy, performance expectancy, social influence, trust, number of mobile payment users (merchants and customers)
Rabaa'i and Zhu (2021) perceived usefulness, perceived ease of use, perceived security, trust, perceived cost, attractiveness of alternatives
Ramadan and Aita (2018) perceived satisfaction with mobile payment system quality, perceived expectations, perceived experience, perceived brand loyalty Schierz et al. (2010) perceived usefulness, attitude, perceived ease of use, perceived security, perceived compatibility, subjective norm, individual mobility Slade et al. (2015) performance expectancy, effort expectancy, social influence, innovativeness, risk, trust
Hampshire (2017) trust, risk
Shankar and Datta (2018) perceived ease of use, perceived usefulness, personal innovativeness, self-efficacy, subjective norm, trust Su et al. (2018) internet experience, functionality, usability, attitude, subjective norms, perceived behavioural Teo et al. (2015) social influence, effort expectancy, performance expectancy, facilitating condition
Teo et al. (2015) performance expectancy, effort expectancy, social influence, facilitating conditions, trust, perceived financial cost Thakur and Srivastava (2014) perceived risk, adoption readiness
Verma et al. (2019) Perceived demonetisation regulation, attitude, perceived behavioral control, subjective norms. Moral norm, merchant pro-activeness Wang et al. (2019) privacy concerns, monetary rewards of alternatives, inertia, perceived economic value, users' past investment, technological self-efficacy Wiese and Humbani (2019) optimism, innovativeness, discomfort, ease-of-use, usefulness, attitudes
Wu et al. (2017) perceived risk, perceived usefulness, positive emotion
Yuan et al. (2020) information quality, system quality, service quality, satisfaction, intimacy, trust
Zhou (2013) trust, flow, system quality, information quality, service quality, trust in online payment, trust in mobile payment, satisfaction, switching costs Kim et al. (2010) innovativeness, m-payment knowledge, mobility, reachability, compatibility, convenience, perceived ease of use, perceived usefulness Sinha et al. (2019) technology readiness, technology readiness, performance expectancy, ease of use, social influences, facilitating conditions, adoption readiness Johnson et al. (2018) ease of use, relative advantage, visibility, perceived security, privacy risk, perceived ubiquity, trialability
de Luna et al. (2016) attitude, perceived usefulness, perceived ease-of-use, personal innovation in information technology, individual mobility, perceived compatibility, perceived security, subjective norms Kalinić et al. (2020) perceived usefulness, perceived ease of use, perceived trust, perceived risk, subjective norms, personal innovativeness
Sun et al. (2019) attitude, subjective norms and perceived behaviour control.
Zhou (2015) Trust in online payment, trust in mobile payment, flow using mobile payment, satisfaction, switching cost
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