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This study examines the Robo-Advisors (RA) based on Artificial Intelligence (AI), a new service that digitises and automates investment decisions in the financial and banking industries to provide low-cost and personalised financial advice. The RAs use objective algorithms to select portfolios, reduce behavioural biases, and improve transactions. They are inexpensive, accessible, and transparent platforms. Objective algorithms improve the believability of portfolio selection.

This study adopts a qualitative approach consisting of an exploratory examination of seven different RA case studies and analyses the RA platforms used in the banking industry.

The findings provide two different approaches to running a business that are appropriate for either fully automated or hybrid RAs through the realisation of two platform model frameworks. The research reveals that relying solely on algorithms and not including any services involving human interaction in a company model is inadequate to meet the requirements of customers in decision-making.

This study emphasises key robo-advisory features, such as investor profiling, asset allocation, investment strategies, portfolio rebalancing, and performance evaluation. These features provide managers and practitioners with new information on enhancing client satisfaction, improving services, and adjusting to dynamic market demands.

This study fills the research gap related to the analysis of RA platform models by providing a meticulous analysis of two different types of RAs, namely, fully automated and hybrid, which have not received adequate attention in the literature.

This study aims to scrutinize existing end-user comprehension regarding e-wallet technology through an examination of apparent usefulness, ease of use and levels of trust, and how these factors may influence a consumer’s attitudes toward the adoption of this new payment method.

The quota sampling method was used, and residents over the age of 22 years were targeted in online and offline questionnaires, and partial least squares-structural equation modeling was used to analyze the data.

This study indicates that existing consumer mindsets and intentions to adopt new technology, such as the e-wallet, are greatly influenced by their perception of the practicality of the product, its ease of use and their levels of trust in the technology to protect their online safety, privacy and economic affairs. Contrastingly, those participants who were offered deferred reimbursements and those given no information were demonstrably less likely to adopt the new service.

The study sample was from a developing nation – Saudi Arabia. Similar cohorts from developing and developed countries could provide a unique cross-nation comparison.

This study stresses the importance of thoroughly explaining and demonstrating an innovative technology to customers while simultaneously promoting the product. Consumers can be encouraged to use and evaluate the new technology by providing inducements, such as effective reimbursement policies.

This paper contributes to literature by critically reflecting on the question: What are the factors influencing customer intentions to adopt the e-wallet, and how do the guarantee of reimbursement and the time frame following unauthorized use influence consumer adoption intentions when deciding to use the new payment technology?

The purpose of this study is to investigate the factors affecting behaviour intention (BI) to use and actual usages of investment-related FinTech services among the zoomers (Gen Z) and millennials (Gen M) retail investors of India.

The study explores the predictive relevance of actual adoption behaviour among the two different age categories of Indian retail investors. It uses the Unified Theory of Acceptance and Use of Technology-2 and the prospect theory framework as guiding frameworks. Data has been collected from 294 retail investors, actively engaged in the investment-related FinTech services. The multi-group analysis using variance-based partial least square structured equation modelling has been used to compare the two groups. The invariance between the two groups was achieved through measurement invariance assessment.

The study reveals distinct factors significantly affecting BI to use investment-related FinTech services among Gen Z and Gen M retail investors are performance expectancy (PE) to BI, perceived risk (PR) to BI, price value (PV) to BI and PR to service trust (ST).

This study provides insights for financial providers and policymakers, emphasizing different factors influencing BI to use investment-related FinTech services in both age groups. Notably, habit emerges as a common factor influencing the actual usage of investment-related FinTech services across Gen M and Gen Z retail investors in India.

This study explores the heterogeneous behaviour of the heterogenous population in the domain of technological adoption of investment-related FinTech services in India.

The aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.

To investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.

The findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.

The findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.

The findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.

The purpose of this study is to examine the behaviour of retail investors while making an investment decision and how it gets affected by the behavioural biases of the investors using a moderated-mediation framework.

A mixed method approach has been used to fulfil the objectives of the study. In the first study, a qualitative analysis of the interviews with 15 retail investors was conducted. As part of the quantitative study, a total of 201 responses from Indian retail investors were collected using systematic sampling and analysed using structural equation modelling and Process Macro.

The results indicate that anchoring bias, availability bias, herding bias, switching cost, sunk cost, regret avoidance and perceived threat have a significant effect on retail investors’ investing intention. The attitude of the investors towards investing decisions mediates the effects of behavioural bias and the status quo on investment intention. The results of the moderated-mediation analysis indicate that mediating effect of attitude varied at the low and high-risk aversion of investors.

The findings of this study will help regulators and retail investors to understand the critical behavioural biases which affect the investors’ investing intention.

The paper contributes to the literature on investors’ behaviour, status quo bias theory (SQB) and behavioural bias. This study uniquely proposes a moderated-mediation framework to understand the effects of biases on retail investors’ investment intention.