Consumer acceptance and continuance of mobile money

Alhassan, Abidin; Li, Leon; Reddy, Krishna; Duppati, Geeta

doi:10.3127/ajis.v24i0.2579

Cited by 9 publications

(6 citation statements)

References 50 publications

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“…Reference New SEM, PLS, Path analysis 21 (Alhassan et al, 2020), (Khalilzadeh et al, 2017), (Sharma, 2019), (Bailey et al, 2017), (Suhartanto et al, 2020), (Yen & Wu, 2016), (Giovanis et al, 2019), (Baabdullah et al, 2019), (Hussain et al, 2019), (Rafdinal & Senalasari, 2021) (PLS-SEM), a less restrictive method, is receiving widespread popularity and success with scholars (Souiden et al, 2019). PLS-SEM applications have grown exponentially in the past decade (Leguina, 2015), especially in the social sciences (e.g., (Ali et al, 2018) (Ringle et al, 2020)), and its use is expanding in marketing (Kumar et al, 2020) (Buzeta et al, 2020) (Gbongli et al, 2019) and information system research (Chin et al, 2020).…”

Section: Main Methods Of Analysis Frequencymentioning

confidence: 99%

“…It was also argued that TAM has an efficient explanatory power and has been validated through several measurement scales (Venkatesh & Bala, 2008). The solid empirical support of TAM to its core variables, namely "perceived ease of use" and "perceived usefulness" in examining the individuals' adoption of several technologies, increased the applicability of the model across different disciplines (Alhassan et al, 2020) (Al Khasawneh, 2015) (Al-Qaysi et al, 2020 (Gbongli et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Understanding Mobile Financial Services Adoption through a Systematic Review of the Technology Acceptance Model

Gbongli¹

2022

OJBM

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Various review studies were performed earlier to apprehend the applicability of the technology acceptance model (TAM) in the mobile financial services (MFS) context by assessing several issues. Despite each of those studies offering a valuable synthesis of TAM, further issues are still uncovered and call for further research. Therefore, this paper contributes to the existing literature by comprehensively reviewing TAM-based MFS studies through the analysis of various concerns, entailing the drivers of novelty technology of MFS adoption, analysis methods, TAM progress over publication years, participated countries, and sample size. From a yield of 217 studies collected, 24 empirical studies published between 2011 and 2021 have met the eligibility criteria and were extensively analyzed. The main results revealed that compatibility and perceived security were TAM's most common external factors influencing the adoption of mobile financial services, followed by subjective norm and trust. While it was developed in 1989, the results unveiled an increasing number of TAM-based MFS studies, yet, expanding the model's credibility in elucidating the users' intentions regarding technology adoption. Most analyzed studies have relied on questionnaires to collect empirical data. It was also found that the USA is leading the research on technology acceptance in MFS. This review will enhance practitioners' understanding through several contributions and implications by presenting the full potential of technology acceptance in MFS that could yield future attempts.

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Section: Main Methods Of Analysis Frequencymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Understanding Mobile Financial Services Adoption through a Systematic Review of the Technology Acceptance Model

Gbongli¹

2022

OJBM

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“…Mobile money is a digital payment platform that transfers money between cellphone devices. (Alhassan et al, 2020) investigated consumer acceptance and continuance of mobile money in Africa using secondary data with the TAM model and employed SEM for data analysis. The research model tests the context-based constructs to determine how these constructs affect peoples' intentions and attitudes toward the continued use of mobile money.…”

Section: Mobile Moneymentioning

confidence: 99%

“…Frequency Reference 1 Perceived Usefulness 24 (Alhassan et al, 2020), (Sharma, 2019), (Bailey et al, 2017), (Suhartanto et al, 2019), (Yen & Wu, 2016), (Goh & Sun, 2014), (Giovanis et al, 2021), (Giovanis et al, 2019), (Baabdullah et al, 2019), 2019), (Rafdinal & Senalasari, 2021), (Purohit & Arora, 2021), (N. Singh et al, 2020), (Francisco Liébana-Cabanillas et al, 2014, (Alalwan et al, 2016), (Al Khasawneh, 2015), (Kalinic et al, 2019), (Talwar et al, 2020), (Peng et al, 2012), (Zhang & Mao, 2020) Perceived Ease of-use (Alhassan et al, 2020), (Sharma, 2019), (Bailey et al, 2017), (Suhartanto et al, 2019), (Yen & Wu, 2016), (Johnson et al, 2018), (Giovanis et al, 2021), (Zhou, 2012), (Giovanis et al, 2019), (Baabdullah et al, 2019), , (Purohit & Arora, 2021), (N. Singh et al, 2020), (Lin, 2011), (Francisco Liébana-Cabanillas et al, 2014, (Alalwan et al, 2016), (Al Khasawneh, 2015), (Peng et al, 2012), (Zhang & Mao, 2020), (Koenig-Lewis et al, 2015), (Francisco Liébana-Caba...…”

Section: No Considered Variables As Drivers Of Mfs Adoptionmentioning

confidence: 99%

A Systematic Review and Weight Analysis of Mobile Financial Services Adoption Literature from 2011 to 2021

Gbongli

2022

TMP

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The global extent and use of the internet and mobile have increased the importance of mobile financial services (MFS) and payments. However, only limited numbers of review studies are accessible on the topic. Therefore, this paper aims to offer a systematic literature review (SLR) methodology and perform a weight analysis of articles published between 2011 and 2021. By reviewing 61 studies, the results indicate that the unified theory of acceptance and usage of technology (UTAUT) followed by the technology of acceptance model (TAM) are the main conceptual frameworks and models adopted. It reveals that attitude, perceived ease of use, performance expectancy, habit, social norms, and perceived usefulness are the best behavioral intention predictors. The critical technological factors of using MFS were provided, followed by future research opportunities.

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“…With growing internet and smartphone penetration, the launch and use of the mobile app or m-app is gaining importance as a business phenomenon for service providers and as a differentiated value offering (content, information, or service-oriented) for users (Alhassan, Li, Reddy, & Duppati, 2020;Gu et al, 2017;Lee, 2010;Lu, Yao, & Yu, 2005;Sarkar, Chauhan, & Khare, 2020;Singh, 2020).…”

Section: Theoretical Background and Hypothesis Developmentmentioning

confidence: 99%

E-governance using mobile applications: A case study of India during the COVID-19 pandemic

Goyal

Pillai²,

Chauhan

2021

AJIS

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Healthcare initiatives backed by electronic-governance (e-governance) principles have contributed well to the extant literature and practice. Governments and healthcare systems across the world were taken aback by the swamping impact of the COVID-19 pandemic. However, they reacted quickly by developing contact-tracing mobile applications (apps) for creating awareness, providing information about various healthcare initiatives, and helping citizens to use the required information in case of emergency. The major challenge was to develop such e-governance interventions in a short time and ensure their quick adoption among the masses. Hence, it is worthwhile to investigate the factors leading to the adoption of such e-governance initiatives, especially in the context of a widespread pandemic situation. The present study is an attempt to analyze the factors driving the intention to use contact tracing mobile apps launched by governments globally during the COVID-19 pandemic. We have conducted the study in the context of India, where the government launched a community-driven contact tracing mobile app for its citizens during the COVID-19 pandemic in April 2020. The study adopted an empirical approach to test how epistemic value, convenience value, conditional value, functional value, and privacy concerns influenced the intention to use this approach. The study found that intention to use such an app was positively influenced by functional value, which in turn was positively influenced by convenience and conditional values. It suggests that the convenience of using the app, perceived seriousness of the pandemic (i.e., conditional value), and utilitarian benefits (i.e., functional value) of the contact-tracing mobile app enhanced its acceptance. However, its novelty (i.e., epistemic value) and privacy concerns are not significant predictors of intention to use. The study recommends that the government should place more emphasis on improving the functional value which is driven by convenience and context-specific features to push the use of an e-governance initiative during the crisis.

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Consumer acceptance and continuance of mobile money

Cited by 9 publications

References 50 publications

Understanding Mobile Financial Services Adoption through a Systematic Review of the Technology Acceptance Model

Understanding Mobile Financial Services Adoption through a Systematic Review of the Technology Acceptance Model

A Systematic Review and Weight Analysis of Mobile Financial Services Adoption Literature from 2011 to 2021

E-governance using mobile applications: A case study of India during the COVID-19 pandemic

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