Search results

This paper aims to discuss the importance and impact of performance appraisals on morale and productivity of employees while describing one of the most popular tools for appraisals, the bell curve. It draws attention to how owing to the various flaws of the bell curve system, few organizations, such as Infosys, are now adopting alternative systems of appraisals.

This paper describes various advantages and disadvantages of the bell curve in detail. It also describes iCount, an appraisal system based on open ranking that has been adopted by Infosys, and discusses the expected advantages and disadvantages of the new system vis-à-vis the bell curve.

Organizations are now questioning the effectiveness of the bell curve, as a performance management tool, in light of its drawbacks. Infosys Limited has, therefore, moved to an alternative system named iCount, which is expected to be more effective and to enhance the morale of its employees.

This paper scrutinizes the bell curve approach to performance appraisals, its premise, distinct advantages, and adverse impact on employees, that have led Infosys Limited to move on to a feedback-based system.

This paper aims to highlight the importance of analytics and its advantages in the human resource domain using the example of Google, which has extensively used analytics to improve various aspects of people management.

The paper discusses human resource analytics and illustrates how it has been successfully implemented by Google to enable better decision-making.

Implementation of analytics in the area of human resources can make people-related decision-making objective, transparent and data-driven and, thus, make the function “quantitative” in nature.

Although analytics has been widely implemented in functions such as finance and marketing, it is yet to gain a strong foothold in the domain of human resources. This paper discusses how Google, a leading organization in the field of technology, has been able to take impactful people-related decisions with the help of analytics.

This article aims to establish the need for professionals and industry to get together on a common platform to engage in discussions, identify innovations and set standards. The movement of employees from unorganized to organized segment is accelerating and subsequently the cost of managing employees is also going to increase manifold for Indian organizations. The HR Tech landscape is pegged at $400m annually and expected to grow significantly.

The paper looks at the HR Tech landscape and posits how HR technologies can help companies save significant costs, and also bring in advanced techniques such as automation and analytics which will improve work efficiency.

While big enterprises are also working in the area of HR technology, startups are showing rapid progress, owing to the fact that they do not have to cope with legacy data/technology/operations. Challenges still remain such as failure to lay groundwork for adoption by employees.

While there are diverse products and technologies in the market, the core challenge is to find the right product-market fit. HR buyers have to ensure that the solutions are future proof.

Automation is going to affect a lot of jobs, certain profiles more so than others. At a larger scale, integrating automation in work processes will have a substantial adverse impact on employees in these job profiles.

The HR Tech landscape is inundated with technology-first startups. There is a dearth of academic literature. There is also a cogent need for professionals and industry to get together on a common platform to engage in discussions, identify innovations, and set standards.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

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.

This study aims to analyse and understand customer sentiments and perceptions from neobanking mobile applications by using advanced machine learning and text mining techniques.

This study explores a substantial large data set of 330,399 user reviews available in the form of unstructured textual data from neobanking mobile applications. This study is aimed to extract meaningful patterns, topics, sentiments and themes from the data.

The results show that the success of neobanking mobile applications depends on user experience, security features, personalised services and technological innovation.

This study is limited to textual resources available in the public domain, and hence may not present the entire range of user experiences. Further studies should incorporate a wider range of data sources and investigate the impact of regional disparities on user preferences.

This study provides actionable ideas for neobanking service providers, enabling them to improve service quality and mobile application user experience by integrating customer input and the latest trends. These results can offer important inputs to the process of user interaction design, implementation of new features and customer support services.

This study uses text mining approaches to analyse neobanking mobile applications, which further contribute to the growing literature on digital banking and FinTech. This study offers a unique view of consumer behaviour and preferences in the realm of digital banking, which will add to the literature on the quality of service concerning mobile applications.

The purpose of this study is to integrate customer value theory (CVT) and protection motivation theory (PMT) to understand the factors that have an impact on customer experience, e-trust and intention to recommend, which influence the adoption behaviour of digital currency users.

A purposive sampling technique was used, and data were gathered through an online survey of 414 respondents. The measurement and structural models were tested using partial least squares structural equation modelling to establish linkages between the constructs.

Functional, emotional and social values positively impact customer experience. Furthermore, perceived severity, perceived vulnerability, response efficacy and self-efficacy had a positive impact on e-trust. E-trust positively affects customer experience and intention to use the digital currency directly. The study demonstrated that perceived value and protection motivation factors play a significant role in influencing the use of digital currency.

For managers and policymakers interested in the Indian digital currency market, it is suggested that functional utility and emotional and social benefits can enhance user satisfaction. In an e-trust model, user education to increase risk and protection awareness, effectiveness of responses and self-efficacy are critical to building e-trust.

Building on CVT and PMT’s usage in the broader financial services domain, this research empirically confirms the significance of perceived value and protection motivation factors while adopting digital currency. It provides an extensive and multifaceted approach to comprehending customer involvement and trust in digital financial services, thus enhancing the theoretical and empirical knowledge of both the fintech and blockchain industries.

This study builds on a conceptual model by integrating AI features – Perceived intelligence (PIN) and anthropomorphism (PAN) – while extending expectation confirmation theory (ECT) factors – interaction quality (IQU), confirmation (CON), and customer experience (CSE) – to evaluate the continued intention to use (CIU) of AI-enabled digital banking services.

Data were collected through an online questionnaire administered to 390 digital banking customers in India. The data were further analysed, and the presented hypotheses were evaluated using partial least squares structural equation modelling (PLS-SEM).

The research indicates that perceived intelligence and anthropomorphism predict interaction quality. Interaction quality significantly impacts expectation confirmation, consumer experience, and the continuous intention to use digital banking services powered by AI technology. AI design will become a fundamental factor; thus, all interactions should be user-friendly, efficient, and reliable, and the successful implementation of AI in digital banking will largely depend on AI features.

This study is the first to demonstrate the effectiveness of an AI-ECT model for AI-enabled Indian digital banks. The user continuance intention to use digital banking in the context of AI has not yet been studied. These findings further enrich the literature on AI, digital banking, and information systems by focusing on the AI's Intelligence and Anthropomorphism variables in digital banks.

This study aims to integrate Delone and McLean’s information system success (DMISS) model with the innovation resistance model to evaluate the relationship between behavioural intention to use (BIU) and innovation resistance in the context of neo-banking. The primary objective of this study is to identify the drivers of neo-banking adoption and the barriers to its adoption and incorporate constructs such as e-trust (ETR) and personal innovativeness (PIV) to provide a more comprehensive understanding of the factors influencing neo-banking adoption.

A structured survey-based questionnaire was used to gather data from a diverse sample population in India. The Partial Least Squares Structural Equation Modeling (PLS-SEM) model was employed to further examine the adoption of neobanking services and users' intention to use neobanking services.

This study reveals a significant correlation between BIU and the uptake of neobanking services, demonstrating the value of consumers' readiness to embrace these offerings. However, resistance to usage has emerged as a major obstacle for consumers concerned about data security, technology reluctance and perceived risks associated with digital-only neobanks.

Analysing the driving and restraining factors will provide substantial information on the formation of consumers' decision-making processes in the Indian banking industry, which is undergoing rapid digital transformation. This information is of great importance to scholars, practitioners and policymakers, as it highlights the factors that may facilitate or impede the adoption of neobanking in India. The outcomes of this analysis will be of particular interest to researchers, experts and stakeholders in the field as they will provide valuable insights into the dynamics of consumer behaviour in the Indian banking sector.

This study represents an initial effort to examine BIUs and usage resistance within the rapidly developing neobanking sector in India. The findings of this study build on the existing research in this area and contribute to the ongoing discussion on the adoption of neo-banking.