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The study examines how process/organizational innovation and R&D spending mediate the relationship between financial performance and the resource dependence theory in Fintech, providing insights into effective innovation strategies for achieving sustainable financial performance.

Data from 191 financial firms in Taiwan was collected from annual reports using the Taiwan Economic Journal (TEJ), a financial information provider. Content analysis was used to measure innovation activities and financial performance, with process and organizational innovation defined. R&D expenditures were also collected and used in statistical analysis to explore the relationship between variables.

This study on the financial services industry shows that process innovation and R&D expenditure positively impact firm performance, while organizational innovation may have a negative short-term effect but could have long-term benefits.

Limitations of this study include vulnerability to spurious effects and the use of data from only listed financial service firms. Future research should use more short-term performance data and include unlisted firms in the financial services industry to extend the study’s coverage.

This study extends resource dependence theory to financial services and explores the effects of process and organizational innovation on firm performance. Results show that internal process management boosts performance, while external collaboration with startups enhances Fintech innovation and efficiency, with positive short-term effects. The study highlights the importance of interacting with external organizations to access resources and improve performance in financial services.

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.

Bank–fintech associations are significant globally, establishing purposeful eco-systems towards extending and complementing capabilities, reach and customer experiences. This paper aims to explore 39 leading fintechs in India catering across payments, lending, wealth management, regulation, neo-banks and other banking functions. Alongside fintechs, the research studies 19 leading banks (public and private) to understand the nature of bank–fintech associations in the Indian context.

The research focuses on narratives from leading banks and top fintechs in India, captured from public disclosures and leadership interviews. The study leverages qualitative research techniques, including grounded theory approaches of inductive analysis, to codify interview and narrative observations to discover relevant objectives, scenarios, challenges and outcomes in India-centric bank–fintech associations.

Bank–fintech associations in India are increasingly focusing on financial services portfolio diversification and improvement in customer experience. Simultaneously, both banks and fintechs, differentiate with innovations and extend offerings to target underserved customer segments. The associations are beneficial for both banks and fintechs in transforming offerings and improving efficiency, scale across channels. Through codification of observations, review of existing literature and evaluation of best practices, alongside subject matter expertise, the study evolves a generalized “Association Model”. The model can steer meaningful bank–fintech associations in India and globally. The association model relates to observables like objectives, enablers of bank–fintech associations, challenges and association-driven value outcomes. Built from study of practices, the proposed model is relevant for strategic orientation in bank–fintech associations.

The findings reveal practices in bank–fintech associations in India with significant learning opportunity for organizational leaders globally. Understanding the nature of association is relevant for strategic interventions, particularly in scenarios of inter-organization collaborations. Central banks, policymakers, governments, investors, banks and fintechs can use the derived association model to establish, govern and steer purposeful value-driven associations.

This study aims to analyse the existing literature on the utilisation of financial technology (FinTech) in the Islamic social finance (ISF) sector, focusing on tools, applications and benefits. From this study, it is to provide insights for literature or for practitioners on how FinTech can be used in ISF, such as using blockchain (tools) in waqf (application) that can help to enhance transparency and trust (benefits) with donors. It is important to explore new available tools or applications in ISF markets so that such effort can benefit the industry in promoting its growth.

A systematic literature review (SLR) was carried out using Reporting Standards for Systematic Evidence Syntheses (ROSES) which has been based on quality evaluation criteria, beginning with 41,945 entries in Scopus, 25,386 entries in the Web of Science and 1,590 entries in the Google Scholar databases and ending with 35 articles from data abstraction and analysis, all of which focus on tools, applications and benefits of FinTech in ISF sector.

This review yielded three primary themes and eleven sub-themes addressing FinTech, namely applications (four sub-themes: crowdfunding, blockchain, banking service and peer-to-peer (P2P), tools (three sub-themes: waqf, zakat and sadaqah), as well as benefits (four sub-themes: transparency, innovation, inclusiveness and efficiency).

This study emphasises on innovative application of FinTech used in ISF industry which focuses on applications, tools and benefits of FinTech to the industry. However, the findings indicate that there is plenty of room for future investigation. The current work outlines several methodological issues and concerns as well as provides recommendations for future research. Various challenges associated with FinTech applications include inadequate regulations, complex permit application procedures, misuse of FinTech for terrorist financing, the existence of fraudulent FinTech companies and consumer disputes in the FinTech sector concerning ISF. There are few in-depth studies on the possible use of FinTech models in ISF, compared to studies focusing on upcoming challenges. This study also highlights the methodological limitations in previous research efforts, which can be used to improve future studies in this area. To offer a more comprehensive analysis, additional search keywords and engines that have not been included in this study could be used in future investigations with different methodologies.

For practitioners, the paper has significant managerial consequences. The analysis provides insights into real-life opportunities, limits and solutions for improving performance management by looking at FinTech applications from a larger and more diverse perspective. The practitioners, especially the State Islamic Religious Council, can recognise the benefits of using FinTech technology in ISF (waqf, zakat and sadaqah), namely under their jurisdiction.

This systematic literature assessment identifies critical knowledge gaps that must be addressed such as the applications of FinTech that are still ambiguous, with certain applications not completely embraced in the ISF industry. This study uses SLR technique to categorise literature, identify gaps in current studies and provide recommendations for the research issue (Paul and Criado, 2020), instead of using the other previous methodology such as content analysis or qualitative review. Hence, FinTech is considered an innovative or new approach in ISF industry.

This review aims to present the state of the art regarding the impact of financial technology (FinTech) on financial inclusion and its implications for consumers and institutions in terms of accessibility, usage and quality. An integrated framework is developed to illustrate the primary thematic areas for future research.

We performed a systematic literature review (SLR) to summarize and synthesize existing research published in peer-reviewed academic journals. Forty-two eligible studies were identified from the Web of Science database and a cross-reference search.

The results suggest that FinTech promotes financial inclusion for consumers and businesses by increasing the accessibility, usage and quality of financial products. We present a multidisciplinary integrative framework that links the three dimensions of financial inclusion (i.e. access, usage and quality) to financial technology. Finally, we propose several avenues for future research.

To the best of the author’s knowledge, this is the first SLR on how FinTech is associated with the accessibility, usage and quality of financial products. We provide an integrative framework for understanding the topic with implications in different fields.

In the evolving landscape of global remittances, this study systematically explores cryptocurrency's transformative impact on remittance services through a comprehensive literature review and bibliometric analysis.

Through meticulous PRISMA-guided analysis, the research identifies cryptocurrency technology as a pivotal force in enhancing remittance efficiency, reducing costs and broadening access contributing significantly to financial inclusion.

Findings revealed that cryptocurrency technology could significantly enhance remittance services, offering improved efficiency, reduced costs and increased accessibility. This suggests a transformative potential for financial inclusion, presenting a compelling case for broader adoption and regulatory support to leverage these benefits effectively.

By integrating recent research, this work underlines the urgent need for broader adoption and regulatory support to leverage these benefits effectively. It offers novel insights for institutions and policymakers, highlighting the potential for technology adoption in remittances to enhance financial inclusivity.

More cryptocurrency studies are needed to concentrate on remittance markets. Thus, this investigation constitutes a unique addition to the field. Additional investigation in this domain presents significant possibilities for future exploration and progress.

Although the financial shared service (FSS) mode has become a well-established organizational arrangement, current information system (IS) research remains limited and mixed. The purpose of this study is to narrow research gaps in the literature on shared services from an FSS practice perspective. The following research questions guide this study: (1) what are the important antecedents of FSS implementation? (2) what is the impact of FSS implementation on firm performance?

Drawing on the technology–organization–environment (TOE) framework and previous innovation studies, this study explores the impact of FSS implementation on firm performance. A questionnaire survey was conducted on Chinese firms using partial least squares (PLS) for data analysis.

The authors find technological, organizational and environmental factors affect the extent and depth of FSS implementation. The empirical results show that relative advantage, compatibility, top management support, managerial obstacles and competitive pressure significantly affect FSS implementation, but bandwagon pressure does not have a direct impact on it. Top management support is the most important factor, and managerial obstacles and compatibility are controllable and manageable factors for firms. The study confirms that FSS improves the financial and non-financial performance of firms significantly, and the degree of improvement in non-financial is greater than that in financial performance.

A comprehension of the key factors influencing FSS implementation will help companies predict weaknesses in their implementation plan and design suitable strategies to handle deployment to achieve these benefits. Managers can make a comprehensive decision regarding the long-term development of combining FSS and the suitability of companies.

The findings contribute to the shared services implementation theory by identifying a set of theoretical factors that shape a firm's shared service implementation. This study provides empirical support to gauge the impact of FSS implementation on firm performance and provides new evidence for a shared-service payoff study. Moreover, the study extends the applicability of the TOE framework and the balanced scorecard (BSC) viewpoint to the FSS implementation field.

Integrating artificial intelligence (AI) into various industries, including the financial sector, has transformed them. This paper aims to examine the influence of integrating AI, including machine learning, process automation, predictive analytics and chatbots, on financial institutions and explores its various aspects and areas. The study aims to determine the impact of AI integration on financial services, products and customer experience.

The research study uses quantitative and qualitative methods, as well as secondary data analysis. It investigates four AI subfields: machine learning, process automation, predictive analytics and chatbots.

The research findings indicate that integrating AI, particularly in machine learning and chatbot subfields, holds promise and high strategic potential for financial institutions. These subfields can contribute significantly to enhancing financial services and customer experience. However, the significance of predictive analytics integration and process automation is relatively lower. Although these subfields retain their usefulness, they might necessitate alternative workflows and tools that incorporate human involvement. Overall, AI integration minimizes human interactions and errors in financial institutions.

The research study contributes original insights by exploring the specific subfields of AI within the financial industry and assessing their strategic significance. It provides recommendations for financial institutions to adopt AI integration partially in multiple phases, measure and evaluate the impact of the transformation and structure internal units and expertise to strategize adoption and change.

This study aims to investigate the drivers of bank automation system performance expectancy compared to that of bank employees. The purpose is to shed light on the role played by consumers' cognitive schema on automation that is the perfect automation schema (PAS).

A survey was administered to about 500 Italian subjects to measure their PAS; financial knowledge, anxiety, and security; and sociodemographic and socioeconomic variables. Ordered probit regressions and an instrumental variable two-stage least squares regression are run.

The analyses reveal that cognitive schemas play a crucial role in consumer expectations in banking. Individuals with stronger PAS tend to have more positive expectations about bank automation performance compared to employee performance. Financial anxiety and knowledge positively affect bank automation performance expectancy while women, older people, and financially insecure subjects have poor expectations of automated banking systems.

This study extends the understanding of key consumer characteristics that affect bank automation performance expectancy compared to that of bank employees in services delivery in the Italian context. Moreover, it provides useful results for researchers, practitioners, banking institutions, and regulators.

As an alternative to hiring financial specialists or investment consultants, robo-advisors offer financially automated investment services. This study aims to investigate how robo-advisors' service attributes, risk attitude and financial self-efficacy influence customers' choice preferences of adopting robo-advisors.

Two hundred fifty-one online surveys were used to collect data, and choice-based conjoint analysis was conducted.

Results show that increasing annual fees negatively impact customers' choice preferences. Promotion, general investment education and additional human assistance have a positive impact. Furthermore, risk-seeking and risk-averse customers require more human assistance than risk-neutral customer and customers with high levels of financial self-efficacy prefer more general investment education and additional human assistance than those with lower levels. In addition, customers in the older age group prefer promotion, general investment education and additional human assistance, while wealthy customers prefer lower annual fees, higher general investment education and more additional human assistance compared to middle-class and low-income groups.

This study contributes to robo-advisor providers to provide appropriate service attributes for each customer group.