Search results

The purpose of this paper is to explore the mediating role of demonetisation in the usage of IT-enabled banking services (ITeBS). The study extends the theory of technology readiness (TR) (Parasuraman and Colby, 2015) by incorporating the behavioural intention and actual usage of ITeBS.

Based on the theory of TR and encompassing the impact of demonetisation, the study examines the functional relationship of TR, behavioural intention and actual usage. Structural equation modelling and mediation analysis are applied on a data set of 474 usable responses.

The study confirms that TR is a significant factor in customer’s intention to use ITeBS. The demonetisation variable fully mediates the relationship model, which implies a significant finding in the consumer acceptance literature.

The result of this study proposes three major implications. Primarily, the banks should focus on providing simple and user-friendly ITeBS interface and its uninterrupted access. It is necessary to educate the customers by giving them a trial of the service. Furthermore, social media platforms may be utilised as an effective and efficient tool to resolve customer complaints.

This study is first of the attempts to investigate government’s digital push in the technology adoption literature. The results indicate significant influence of demonetisation on the usage of ITeBS.

India started economic reforms at a rapid pace to catch up the world economy by following the services-led-growth model during the post-liberalisation period. Over the years, the growing unemployment rate posits a re-look into the dynamics of growth model for wider work force participation. In this backdrop, the paper aims to examine the dynamics of structural changes in employment pattern in view of economic growth led by services-led growth model in India.

The study employs a non-linear autoregressive model (NARDL) to examine the effect of the growth rates in three broad economic sectors namely agriculture and allied, services and industry on work force participation representing the employment opportunities in India.

The results highlight that the rapid expansion of the service sector has not occurred with enough employment opportunities by the same rate. By contrast, the growth in the industrial sector significantly creates employment opportunities in the short and long run. These results support the industry led growth model over the services for sustainable and inclusive economic growth in the country.

The study relies on combined labour force participation rates rather than gender-specific rates. Further, the regulatory, working conditions and economic incentives may affect the gender-specific engagement of the labour force in three broad sectors.

The results offer important insight into changing patterns in employment with policy lessons. A wider workforce force participation calls for expansion of manufacturing activities through pro-industry programmes.

The study makes pioneer efforts to examine the dynamics of labour force participation with respect to the growth of three broad economic sectors of the Indian economy. The results provide new insights with policy implications for the changing employment pattern and policy response.

This study aims to understand the importance and challenges of adopting artificial intelligence (AI) in the banking industry in Malaysia and examine the factors that are important in investigating consumers' intention to adopt AI in banking services.

The qualitative research was carried out using in-depth interviews from officials in the baking industry to understand the importance and challenges of adopting AI in the banking industry. In the quantitative study, a total of 302 completed questionnaires were received from Malaysian banking customers. The data were analysed using the SmartPLS 3.0 software to identify the important predictors of their intention to adopt AI.

The qualitative results reveal that AI is an essential tool for fraud detection and risk prevention. The absence of regulatory requirements, data privacy and security, and lack of relevant skills and IT infrastructure are significant challenges of AI adoption. The quantitative results indicate that attitude towards AI, perceived usefulness, perceived risk, perceived trust, and subjective norms significantly influence intention to adopt AI in banking services while perceived ease of use and awareness do not. The results also show that attitude towards AI significantly mediates the relationship between perceived usefulness and intention to adopt AI in banking services.

Financial technology (FinTech) is regarded as a critical determinant of strategic planning in the banking industry. While AI provides various disruptive opportunities in the FinTech space in terms of data collection, analysis, safeguarding and streamlining processes, it also poses a sea of threats to incumbent banks. This study provides vital insights for the policymakers of the banking industry to address the challenges of adopting AI in banking. It also provides the important predictors of the bank customers' intention to adopt AI in banking services. Policymakers can devise their strategies to enhance AI adoption considering the facts.

This study is amongst the pioneer in exploring the importance and potential challenges in implementing AI technology in banking services and identifying the essential factors influencing the intention to adopt AI in Malaysia's banking services.

Banks in emerging markets such as Brazil provide a wide range of services to companies to facilitate the export process. The objective of the present study was to analyze, from the perspective of Brazilian export companies, the relationships between banking intellectual capital (human and organizational), banking agility, banking technologies and company size in banking service provision.

A sample of 318 Brazilian export companies was surveyed with questionnaires. The research model was tested using structural equation modeling, namely the partial least squares (PLS-SEM) technique and SmartPLS.

Banking intellectual capital affects banking service provision, banking agility mediates the relationship between intellectual capitals and banking service provision and technology does not moderate the relationship between agility and banking service provision. The size of the company does not moderate the relationship between intellectual capital and banking service provision.

This work indicates that intellectual capital and the banking agility strategy are critical in the provision of banking service provision for exports.

This work illustrates the effect of banks' intangible resources on the provision of banking services from the perspective of Brazilian export companies.

The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

The purpose of present study is to identify influential aspects of published literature, research streams and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis.

The study analyzed 285 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis.

The study identified influential aspects of published literature; identified five significant research streams: (1) Demonetization and financial system, (2) Demonetization and financial technology, (3) Demonetization and financial market, (4) Demonetization and digital payment system and (5) Demonetization and governance and proposed 27 key future research questions to develop future research agenda.

The present study makes significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among five identified research streams as future research agenda.

The present work is unique in its way of contribution, as to the best of researchers' knowledge no work was witnessed in published literature to cover demonetization in a detailed and comprehensive manner. The present study fills this gap by conducting bibliometric analysis and content analysis. The study proposed conceptual framework for demonetization characterization to understand the demonetization literature well; and also proposed framework for future researcher to be explored further.

This study aims to understand the impacts of Covid-19 on the progression of digitalization of banks in an emerging market. For this purpose, business model canvas (BMC) is used as a theoretical framework to explore these effects on each business elements of Turkish Banks’ business strategies.

Data are collected through structured interviews with the top managers of seven diversified banks. Interview questions are designed based on BMC.

The results show that the onset of the Covid-19 is a shock that has made digitalization a strategic issue that necessitates an urgent change in many business elements of banks such as customer relationships, communication channels, resource allocation, partnerships and financing. Further, it has stimulated redefining value proposition and collaboration/interaction among all financial institutions through digital platforms.

BMC can be used to explain decision-making and business processes of banks for exploring the effect of recent and/or unexpected developments in the business environment of an emerging economy. The results provide insights and recommendations to managers of financial institutions into the impacts of Covid-19 on banks’ operational and strategic processes. That allows financial institutions, including Fintechs, to use this information for taking precautions and proactive actions against shocks.

This study is an initial attempt to explore the impacts of the Covid-19 on banks in an emerging economy by using BMC. With that, this study contributes to the literature by explaining the effect of progression of digitalization in banking from a strategic business model perspective using a qualitative research method.

The purpose of this study is to explore and evaluate potential nonmonotonicity in the determinants of profit efficiency, specifically IT and R&D investments in the Indian commercial banking sector.

The study employs an alternative stochastic profit efficiency framework and introduces nonmonotonic effects by parameterizing the location and scale parameters of the inefficiency component on an unbalanced panel data set of 72 commercial banks in the 2008–2019 period. Marginal effects across quartiles are calculated using a bias-corrected and accelerated bootstrap procedure of 500 simulations. The study disaggregates across ownership and size for gauging the impact of structure on the associations between determinants of profit efficiency.

The study partially rejects the productivity paradox as it discovers a negative association of IT and R&D with profit inefficiency. However, the observed nonmonotonicity of IT is of significance for bank managers, as the study concludes that overinvestment in IT is detrimental to a bank’s profit-maximizing interests. Further, bank size, loan default and credit risk depict a nonmonotonic relationship across the sample with large banks, high NPAs and high credit risk associated with reducing profit efficiency. In addition, higher margins and greater diversification are related positively to efficiency, and banks with cost-heavy structures or having high liquidity risk associated negatively with efficiency.

To the best knowledge of the authors, the study is perhaps the first to acknowledge and incorporate nonmonotonic associations of IT investments amidst other exogenous determinants under a stochastic profit efficiency framework.