Digital by Default? A Critical Review of Age-Driven Inequalities in Payment Innovation
Abstract
1. Introduction
- RQ1: What are the main barriers (e.g., lack of trust, usability issues, security concerns) preventing elderly people from adopting digital payment systems?
- RQ2: How does the digital divide (e.g., lack of digital literacy, limited internet access) contribute to the difficulties that elderly people face in adopting digital payment systems?
2. Materials and Methods
3. Results
3.1. Cluster 1: Demographic Drivers of Digital Payment Adoption
3.2. Cluster 2: Behavioural Drivers of Digital Payment Adoption
3.3. Cluster 3: The Grey Digital Divide: Structural Barriers to Digital Engagement Among Older Adults
3.4. Cluster 4: Brain Function
4. Discussion: Barriers, Digital Divide, and Strategies for Inclusion
5. Conclusions
- How do specific cognitive factors (e.g., memory retention, attentional control, decision fatigue) influence the usability of and trust in digital payment platforms among users aged 65 and over?
- What role do interface complexity and visual design features play in shaping digital payment behaviour across different cognitive ageing profiles?
- To what extent can intergenerational learning environments or peer-support interventions mitigate cognitive barriers to adoption?
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
References
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Generation | Birth Years | Definition | References |
---|---|---|---|
Silent Generation | 1928–1945 | Characterised by a strong work ethic, loyalty, frugality, and a preference for stability. Shaped by the Great Depression and World War II. | Sabaitytė and Davidavičius (2017) |
Baby Boomers | 1946–1964 | Known for ambition, social change advocacy, a strong work ethic, and hierarchical views of work. Influenced by post-war economic prosperity and civil rights movements. | Patterson (2006) |
Generation X | 1965–1980 | Independent, sceptical of authority, adaptable, and entrepreneurial. Value work–life balance and experienced economic shifts and the rise of technology. | Bulbeck (2012) |
Generation Y (Millennials) | 1981–1996 | Digital natives with an emphasis on technology, social justice, and work–life balance. Value transparency, collaboration, flexibility, and meaningful work. | Jung and Yoon (2021); Bencsik et al. (2016) |
Generation Z | 1997–2012 | Digital natives focused on authenticity, inclusivity, mental health, and sustainability. Prefer flexible work environments and have an entrepreneurial mindset. | Nabahani and Riyanto (2020); Schroth (2019); Basid and Atmaja (2022) |
Authors (Year) | Country | Research Questions | Main Findings |
---|---|---|---|
Andaregie et al. (2024) | Ethiopia | How do socio-economic characteristics influence digital payment adoption? | Mobile ownership, ATM/debit cards, and internet access significantly impact digital payment adoption. |
Al-Qudah et al. (2024) | Malaysia | What variables affect Millennials’ acceptance of digital payments within Generation Z? | Perceived convenience, security, cost, and social influence impact digital payment adoption. Privacy and security concerns, lack of information, and aversion to change are prevalent challenges among Millennials. |
Baviskar et al. (2023) | India |
| The UAE’s 1 digital transformation strategy is bolstered by high electronic payment adoption, with positive correlations between education and income levels, but no significant associations found with gender, marital status, age group, or professional position. |
Behera et al. (2023) | India |
| The use of digital payments rises with educational attainment and income levels, but the percentage of cash transactions has diminished following the recent pandemic. |
Colline et al. (2022) | Global (Literature Review) |
| Digital payment adoption is influenced by security, convenience, efficiency, and transparency, but faces barriers like age, internet access, and technological literacy. |
Jaiswal et al. (2022) | India |
| The study highlights that performance expectancy, effort expectancy, facilitating conditions, and individual mobility are key drivers of confirmation. Satisfaction partially mediates the link between confirmation and continuance intentions, while age and education moderate the confirmation–satisfaction relationship. |
M. A. Khan (2021) | India | How do demographic factors and service-related attributes influence digital payment adoption in India? | Digital payment adoption is influenced by demographic factors, service quality, reliability, satisfaction, security, and user-friendliness, with government efforts and increased smartphone penetration likely to boost adoption. |
A. Kumar and Lim (2008) |
| The study reveals significant differences in satisfaction between Gen Y and baby boomers, with network quality being crucial for both groups, while emotional value is more significant for Gen Y. | |
Lohana and Roy (2023) | India | In what ways do demographic characteristics affect the use of digital payment systems following the demonetisation period? | Gender, age, education, marital status, and income impact the use of digital payments. |
Saha and Kiran (2022) | India |
| COVID-19 significantly influenced UPI adoption among baby boomers, with perceived security playing a crucial role in influencing risk, ubiquity, and behavioural intention. |
Said et al. (2021) | United Arab Emirates |
| The UAE’s digital transformation strategy is bolstered by high e-payment adoption, with positive correlations between education and income levels, but no significant associations found with gender, marital status, age group, or professional position. |
Sanchez-Diaz et al. (2021) | Sweden | How do demographic factors influence the usage of digital payment systems during the post-demonetisation period? | Significant inequalities in access to OHDS 4, with marginalised groups (e.g., elderly, high-risk COVID areas) facing compounded marginalisation due to limited access. |
Saroy et al. (2022) | India |
| The lockdown determined by COVID-19 led to a significant shift towards digital payments, affecting trust, fraud, and consumer protection, requiring increased access to digital literacy and technology. |
Authors (Year) | Country | Research Questions | Main Findings |
---|---|---|---|
Al Arif et al. (2023) | Indonesia | What factors influence Indonesian Muslim youths’ intention to use digital Zakat payments? | The pandemic has led to an increase in public donations, indicating the need for improved digital payment features and data security measures in Zakat management organisations. |
Aurazo and Vega (2021) | Peru |
| The use of digital payments in Peru is minimal. Utilisation is more prevalent among those aged 25 to 40, those possessing higher education, those with formal jobs, those with an urban domicile, those with an internet connection, and those with elevated household expenditure. The existence of financial institutions further enhances the acceptance of digital payments. |
Berraies et al. (2017) | Tunisia |
| Perceived values (quality, price, emotional) of mobile banking apps predict e-trust. E-trust positively affects e-satisfaction and e-loyalty. Age moderates the relationship between perceived value and e-trust. |
Beura et al. (2023) | India | What are the determinants of continuance intention towards digital payment, focusing on user experience and expectations? | Mobile expectancy confirmation explains continuance intention. Perceived usefulness, perceived experience, and satisfaction also contribute. Perceived experience moderates the confirmation–continuance relationship. |
Chaveesuk et al. (2022) | Bangkok, Thailand | What factors influenced the continuous intention to use digital payments during COVID-19? | Ease of use, satisfaction, and social distancing impact digital payment adoption. |
Danisman and Tarazi (2020) | Europe | How does financial inclusion impact banking stability? | Financial inclusion, particularly through increased account ownership and digital payments, enhances banking system stability. The stabilising effect is strongest when targeting disadvantaged groups (young, undereducated, unemployed, and rural residents). |
Das and Mahapatra (2020) | India | What influences consumer perception of bank payments? | Privacy, security, and convenience influence usage. |
Daştan and Gürler (2016) | Turkey | What factors influence the adoption of mobile payment systems by consumers? | Trust, mobility, and attitudes positively influence MPS adoption, while usefulness and ease of use do not. Trust is positively related to reputation, while environmental risk negatively affects trust. |
Dimitrova et al. (2021) | Sweden | What barriers prevent digital payment adoption? | Privacy, security, and access barriers affect digital payment adoption. For adopter–acceptors (young bank customers), privacy and access barriers hinder full adoption of digital payment methods. |
Ebubedike et al. (2022) | Malaysia | What factors influence mobile payment adoption in Kuala Lumpur? | Trust, effort expectancy, and performance influence adoption. |
Kamal et al. (2023) | Indonesia |
| Millennials prefer digital wallets over mobile banking due to promotions and usability. |
C. Li et al. (2022) | China | How does heterogeneity (e.g., age, education, financial access) influence the relationship? How do big data-based digital payments impact household healthcare expenditure? | The impact of digital payments is stronger in households with high traditional financial accessibility, younger or middle-aged heads, and higher education levels. |
Mavlutova et al. (2023) | EU and Baltic countries (Lithuania, Latvia, Estonia) | How does digital transformation drive financial sector sustainability? | Digital payments enhance financial inclusion and operational efficacy. There exists a positive correlation among the intensity of digital payments, financial inclusion, and operational efficiency in EU nations. Digital transformation improves customer satisfaction, reduces operational risks, and minimises environmental impact. |
Niankara and Traoret (2023) | Global |
| Financial inclusion significantly increased digital payments; gender gap in digital payment usage. |
Niankara (2023) | Gulf Cooperation Council (GCC) | What role does financial inclusion play in digital payment adoption? | Financial inclusion indicators significantly influence digital payments. |
Ocansey et al. (2024) | Ghana | How do mobile money and digital banking influence money velocity? | Mobile money, digital banking, and money velocity are interdependent. |
Patil et al. (2020) | India | What factors drive mobile payment adoption in India? | Performance expectancy, grievance redressal, and social influence drive adoption. |
Patnaik et al. (2023) | India |
| Trust, privacy, and financial literacy influence digital payment adoption; improving financial literacy is essential for broader acceptance. |
Petrikova and Kocisova (2024) | Euro Area |
| Higher income, education, and younger age groups increase digital payments; the digital access index influences adoption. |
Poudel et al. (2023) | Nepal (Pokhara metropolitan city) | What factors influence the intention to adopt digital payment systems among the youth in Pokhara, Nepal? | Security and privacy, performance expectancy, and facilitating conditions significantly influence adoption intentions. Effort expectancy and social influence have no significant effect. |
Purwanto et al. (2023) | Jakarta, Tangerang, South Tangerang, Indonesia |
| Social influence and facilitating conditions drive adoption. |
Santosa et al. (2021) | Indonesia | What factors influence the continuance intentions of baby boomers and Generation X towards digital payment use after the pandemic? | During the COVID-19 pandemic, Baby Boomers and Generation X adopted digital payments, with UTAUT2 constructs like performance expectancy and price value significantly impacting user satisfaction. |
Seldal and Nyhus (2022) | Norway | How do demographic factors (e.g., age, gender, financial literacy) influence digital payment adoption and financial behaviour? | Mobile payment users are less financially vulnerable; women use digital payments more than men. |
Sholihah and Ariyani (2023) | N/A | What factors influence Generation Z’s intention to continue using digital payments in the post-COVID-19 era? | Perceived ease of use and satisfaction are significant predictors for continuance intention, while perceived usefulness is not. |
Sivathanu (2019) | India | What factors influenced the actual usage (AU) of digital payment systems during India’s demonetisation period? How does stickiness to cash affect the relationship between BI and AU? | Behavioural intention (BI) and innovation resistance (IR) affect the actual usage (AU) of digital payment systems. Stickiness to cash payments moderates the relationship between BI and AU. |
Sutresna et al. (2023) | West Java, Indonesia | What factors influence the intention to use digital payments in rural communities during the COVID-19 pandemic? | Rural residents favour digital payments due to performance expectations and social influence, with perceived health risks like COVID-19 being less significant. Social influence significantly influenced adoption during the pandemic. |
Tang et al. (2021) | China | What factors drive WeChat payment adoption? | Service quality, perceived risk, perceived security, perceived ease of use, social influence, and compatibility significantly influence consumers’ intention to adopt WeChat as a digital payment platform. Age does not significantly influence adoption intentions. |
Thoumrungroje and Suprawan (2024) | Thailand | What is the effect of technological self-efficacy and perceived values on mobile payment acceptance among various generations following COVID-19? | Technological self-efficacy influences m-payment intentions, with perceived values mediating for Gen B and X, and partially for Gen Y and Z, with younger generations less influenced. |
J. Zhang et al. (2019) | N/A | How does perceived security affect continuous mobile payment usage? | Perceived control, interface design, and conscientiousness impact security perceptions. |
Zhong and Moon (2022) | China | What factors influence consumer adoption of contactless payment methods? | QR-code payment users are more satisfied than facial recognition users. |
Zhu et al. (2023) | India | What factors influenced elderly users’ intentions to adopt digital payments during the COVID-19 pandemic? How did motivation factors moderate these influences? | The study reveals that the TPB 1, perceived value, perceived risk, and COVID-19 influence elderly users’ adoption of digital payments, with motivation factors like personal innovativeness and intergenerational support influencing these effects. |
Authors (Year) | Country | Research Questions | Main Findings |
---|---|---|---|
Audrin and Audrin (2022) | Global |
| Key digital literacy factors for education: (1) Digital literacy; (2) Digital learning; (3) Twenty-first-century digital skills. |
Brandtzaeg et al. (2011) | Europe (Norway, Sweden, Austria, the UK, and Spain) |
| Identified five user types (Non-Users, Sporadic Users, Instrumental Users, Entertainment Users, Advanced Users) for digital divide analysis in Europe. |
Brink (2024) | Luxembourg, Romania | How can digital inclusion for older adults be improved through training and system design? |
|
Chee (2024) | Unspecified | What barriers do older adults in senior care facilities face in adopting digital technology? | Older adults in senior care facilities struggle with digital technologies due to poor connectivity, functional impairments, and generational attitudes. |
Friemel (2016) | Switzerland |
| Individual and social variables influence the digital divide among seniors, with social networks having tremendous potential to overcome barriers such as physical restrictions and perceived complexities through focused support and benefit promotion. |
Hargittai et al. (2019) | USA | How do socio-economic factors and available access points influence digital skills in older adults? | Socio-economic background and available access points affect digital skills among older Americans. |
Helsper and Reisdorf (2017) | UK and Sweden | What motivates internet non-use among vulnerable groups? | Vulnerable groups represent a higher share of internet non-users, especially older adults. |
Hunsaker and Hargittai (2018) | Developed nations | How does digital engagement affect well-being among older adults? | Digital engagement impacts health and well-being, and varies with age, income, and education. |
Kaila (2023) | Vietnam | What factors hinder mobile phone adoption among ethnic minorities? | Education and socio-economic factors are barriers to mobile phone adoption among minorities. |
H. Li and Kostka (2024) | China | How effective are government-led digital inclusion programmes for older adults in China? | Older Chinese adults lack digital understanding, which limits the effectiveness of government digital inclusion programmes. Outreach and training are needed. |
Lythreatis et al. (2021) | Global | How are digital divides evolving across demographic lines? | Sociodemographic and economic factors drive the digital divide, shifting access types. |
Mohan and Lyons (2024) | Ireland | How does broadband access impact digital engagement among older adults? | High-speed broadband access is linked with increased internet use and online engagement among older adults. |
Raihan et al. (2024) | Unspecified | What intersectional strategies can promote digital fairness among older populations? | Addressing the digital divide requires intersectional approaches, including affordable internet, culturally sensitive training, and community-led literacy programmes. |
Rosenberg (2024) | Unspecified | How does internet use influence older adults’ perception of digital technology in social interactions? | Online group involvement and internet use improve perceptions of technology’s impact on social interactions. |
Deursen and Van Dijk (2019) | The Netherlands | How do device disparities affect digital skills and outcomes? | Device-related disparities persist despite high internet access in the Netherlands. |
Yang and Du (2020) | China | What are the main barriers to digital access among rural women? | Rural women in China face barriers due to low socio-economic capital, affecting digital access. |
Yao et al. (2021) | China | How can policies mitigate pandemic-related digital exclusion among older adults? | The findings emphasise the need for policies to prevent pandemic-related digital exclusion in seniors. |
Authors (Year) | Research Questions | Main Findings |
---|---|---|
Ceravolo et al. (2019) | How do colour and impulsivity modulate attention distribution while reading financial documents? | Eye movements during reading financial documents are influenced by colour and impulsivity, with colour playing a larger role. |
A. Khan and Mubarik (2020) | How do different neurotransmitters influence financial decision-making and investment behaviour? | Developed an eight-dimensional neurotransmitter measurement scale to study their role in financial decisions. |
Miendlarzewska et al. (2019) | How does neuroscience contribute to financial decision-making? | Neurofinance integrates psychology, neuroscience, and finance to understand financial decision-making and challenges classic finance theories. |
Sudirjo et al. (2023) | What factors influence individuals’ decisions to use multiple digital wallets simultaneously? | Convenience, utility, and sales promotions significantly influence the choice to use multiple digital wallets. |
Research Question | Category | Key Issues | Supporting Authors | Proposed Strategies |
---|---|---|---|---|
RQ1 | Technological Barriers | Complex interfaces, unfriendly design, low usability | Daştan and Gürler (2016), Dimitrova et al. (2021), J. Zhang et al. (2019), Sivathanu (2019), Sholihah and Ariyani (2023), Beura et al. (2023), Tang et al. (2021) | Age-friendly interfaces, voice assistants, simplified UI 1, inclusive UX 2 design |
Trust, Risk, and Privacy | Security/privacy concerns, fear of fraud, low trust | Kamal et al. (2023), Zhong and Moon (2022), Berraies et al. (2017), Ebubedike et al. (2022), J. Zhang et al. (2019), Tang et al. (2021) | Stronger data protection standards, transparent communication, fraud detection tools | |
Cognitive and Physical Limits | Memory decline, dexterity, eyesight, cognitive load | Santosa et al. (2021), Zhu et al. (2023), Thoumrungroje and Suprawan (2024), Ceravolo et al. (2019) | Cognitive-aware design, larger fonts/buttons, tailored onboarding | |
Social Support and Influence | Family help, peer encouragement, intergenerational support | Zhu et al. (2023), Santosa et al. (2021), Poudel et al. (2023), Al Arif et al. (2023), Sutresna et al. (2023), Sholihah and Ariyani (2023) | Peer mentoring, community-based support groups | |
RQ1/RQ2 | Socio-economic Factors | Education, income, employment, financial literacy | Aurazo and Vega (2021), Hargittai et al. (2019), Petrikova and Kocisova (2024), Niankara and Traoret (2023), Patnaik et al. (2023), Seldal and Nyhus (2022), Beura et al. (2023), Lythreatis et al. (2021), Kaila (2023) | Subsidised access to tech, digital and financial literacy programmes |
RQ2 | Access Divide | No broadband, smartphone, or stable connectivity | Dimitrova et al. (2021), Niankara (2023), Petrikova and Kocisova (2024), Aurazo and Vega (2021), Deursen and Van Dijk (2019), Mohan and Lyons (2024) | Public Wi-Fi, rural broadband rollout, device donation programmes |
Skills Divide | Lack of digital literacy, inability to learn new technologies, low training capacity | Deursen and Van Dijk (2019), Santosa et al. (2021) | Targeted training, experiential learning, user testing with seniors | |
Motivational Divide | Low perceived usefulness, inertia, resistance to changes | Beura et al. (2023), Sholihah and Ariyani (2023), Zhong and Moon (2022), Zhu et al. (2023), Sivathanu (2019), Sholihah and Ariyani (2023) | Highlight real-world benefits, gamified learning, social norm reinforcement |
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Panetta, I.C.; Anjomrouz, E.; Paiardini, P.; Leo, S. Digital by Default? A Critical Review of Age-Driven Inequalities in Payment Innovation. J. Risk Financial Manag. 2025, 18, 313. https://doi.org/10.3390/jrfm18060313
Panetta IC, Anjomrouz E, Paiardini P, Leo S. Digital by Default? A Critical Review of Age-Driven Inequalities in Payment Innovation. Journal of Risk and Financial Management. 2025; 18(6):313. https://doi.org/10.3390/jrfm18060313
Chicago/Turabian StylePanetta, Ida Claudia, Elaheh Anjomrouz, Paola Paiardini, and Sabrina Leo. 2025. "Digital by Default? A Critical Review of Age-Driven Inequalities in Payment Innovation" Journal of Risk and Financial Management 18, no. 6: 313. https://doi.org/10.3390/jrfm18060313
APA StylePanetta, I. C., Anjomrouz, E., Paiardini, P., & Leo, S. (2025). Digital by Default? A Critical Review of Age-Driven Inequalities in Payment Innovation. Journal of Risk and Financial Management, 18(6), 313. https://doi.org/10.3390/jrfm18060313