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The purpose of this study is to gauge the awareness and perception of Indian individual investors about a new fintech innovation known as robo-advisors in the wealth management scenario. Robo-advisors are comprehensive automated online advisory platforms that help investors in managing wealth by recommending portfolio allocations, which are based on certain algorithms.

This is a phenomenological qualitative study that used five focussed group discussions to gather the stipulated information. Purposive sampling was used and the sample comprised investors who actively invest in the Indian stock market. A semi-structured questionnaire and homogeneous discussions were used for this study. Discussion time for all the groups was 203 min. One of the authors moderated the discussions and translated the audio recordings verbatim. Subsequently, content analysis was carried out by using the NVIVO 12 software (QSR International) to derive different themes.

Factors such as cost-effectiveness, trust, data security, behavioural biases and sentiments of the investors were observed as crucial points which significantly impacted the perception of the investors. Furthermore, several suggestions on different ways to enhance the awareness levels of investors were brought up by the participants during the discussions. It was observed that some investors perceive robo-advisors as only an alternative for fund/wealth managers/brokers for quantitative analysis. Also, they strongly believe that human intervention is necessary to gauge the emotions of the investors. Hence, at present, robo-advisors for the Indian stock market, act only as a supplementary service rather than a substitute for financial advisors.

Due to the explorative nature of the study and limited participants, the findings of the study cannot be generalised to the overall population. Future research is imperative to study the dynamic nature of artificial intelligence (AI) theories and investigate whether they are able to capture the sentiments of individual investors and human sentiments impacting the market.

This study gives an insight into the awareness, perception and opinion of the investors about robo-advisory services. From a managerial perspective, the findings suggest that additional attention needs to be devoted to the adoption and inculcation of AI and machine learning theories while building algorithms or logic to come up with effective models. Many investors expressed discontent with the current design of risk profiles of the investors. This helps to provide feedback for developers and designers of robo-advisors to include advanced and detailed programming to be able to do risk profiling in a more comprehensive and precise manner.

In the future, robo-advisors will change the wealth management scenario. It is well-established that data is the new oil for all businesses in the present times. Technologies such as robo-advisor, need to evolve further in terms of predicting unstructured data, improvising qualitative analysis techniques to include the ability to gauge emotions of investors and markets in real-time. Additionally, the behavioural biases of both the programmers and the investors need to be taken care of simultaneously while designing these automated decision support systems.

This study fulfils an identified gap in the literature regarding the investors’ perception of new fintech innovation, that is, robo-advisors. It also clarifies the confusion about the awareness level of robo-advisors amongst Indian individual investors by examining their attitudes and by suggesting innovations for future research. To the best of the authors’ knowledge, this study is the first to investigate the awareness, perception and attitudes of individual investors towards robo-advisors.

The purpose of this paper was to examine how community engagement can be influenced by responsible leadership during crises. It looks at the phenomenon of community engagement and responsible leadership in India during the Covid-19 pandemic, using the collective responses of community.

This paper uses netnography, which studies community interpretations through their online social communication. The perceptions on how engaged the Indian community felt during the pandemic were studied by collecting and analysing their postings on social media.

The findings suggest that responsible leadership – through the building of trust, open communication, collective consciousness and mindful action – is an effective way to positively engage stakeholders and influence community response during a pandemic.

This paper contributes to the literature of responsible leadership and community engagement during crises. It is an attempt to link public leadership with responsible leadership and its impact on community engagement in a novel way, filling a void in the literature.

The aim of this study is to empirically examine firm-specific factors that influence the financing decisions of companies listed on BSE-500 index. Firm-specific variables such as profitability, company size, growth potential, liquidity, non-debt tax shields, age and tangibility were evaluated in this study.

This empirical research is performed using longitudinal data of 366 companies listed on the BSE 500 index during 2006–2020. Pooled ordinary least square method is employed to classify primary determinants of capital structure.

The results show that profitability, liquidity and non-debt tax shield are negatively associated whereas, company size, growth potential, age and tangibility are positively associated with the capital structure. The authors’ observations are aligned with either the trade-off hypothesis or the principle of the pecking order.

This study helps to better understand how firm-specific factors play a vital part in deciding the capital structure of businesses and makes a significant contribution to the literature. Thus, the present study examines the drivers of the capital structure among sample Indian companies, which allow firm managers and regulators to recognise relevant variables that optimise performance. This study is limited to Indian companies and only firm-specific variables were considered.

The current research focuses on the impact of firm-specific variables upon the financing decisions of Indian companies. In the background of developed countries, numerous studies in this field have been carried out. In the Indian context, however, there are not many researches in this area. However, the existing studies use one or two ordinary least square (OLS) models, resulting in a lack of thorough research and robust results. To address this gap in the analysis, the current study used four models and used a 15-year time frame, as well as a bigger sample size, which was not used in earlier investigations.

The novel blockchain technology can be leveraged, owing to the growth in computing power and its widespread applications. This study aims to understand the challenges of adopting blockchain technology in the financial sector, organise them into a model and classify them for systematic address.

Interpretive Structural Modeling (ISM) has been carried out along with MICMAC (Matrice d’impacts croisés multiplication appliquée á un classment) analysis to hierarchically structure blockchain adoption problems and categorise the challenges into four classes-autonomous, dependent, linkage and independent for better addressing. The study also uses content analysis using NVivo software.

The digraph depicts the hierarchical challenge model. Vulnerability to financial crimes and glitches, privacy issues and geopolitical tensions due to cross-border transactions are the dependent variables. Complex architecture to comprehend, code and fix, the need for new financial intermediaries, complexity in auditing and the lack of unified governance and coordination among institutions and regulators are the independent variables. The digraph, which is also justified by the qualitative content analysis, is beneficial for stakeholders to systematically address the interdependent challenges associated with blockchain implementations in finance to foster its favourable adoption.

The challenges in the adoption of blockchain should be resolved to allow the implementation of this technology in various finance domains. This study enables organisations to carry out resource planning and systematically address these challenges to leverage the advantages of blockchain.

The results of the present study can help in promoting the proliferation of blockchain for faster, cost-effective, transparent and secure financial transactions and foster innovative and new business models for economic growth.

The development of technology has brought about significant changes in the financial sector. Blockchain is a technological advancement that aims to bring security and transparency to transactions. There has been no research leveraging ISM-MICMAC to hierarchically organise and classify the blockchain challenges in the financial sector, a critical one. The research also uses content analysis which is seldom found along with ISM-MICMAC.

Innovation is the way of life and we see various innovative techniques and methods being introduced in our daily life. This study aims to focus on digital innovation in the wealth management domain. This study examines the effect of usage of robo-advisory services in investment decision-making and behavioural biases, i.e. overconfidence and loss aversion. Such studies are more pronounced in developed countries and little has been studied about investor behaviour in association with advisory services in developing countries such as India.

Overconfidence and loss-aversion biases, investment decision-making and advisory services questions are measured using a five-point Likert scale. The number of respondents was 172 investors. A purposive sampling is used for gathering responses from investors. Structural equation modeling model was run using AMOS 22 version software package.

The authors found that behavioural biases positively and significantly influence the irrationalities of investment decision-making. The findings of this study also provide empirical evidence that the usage of robo-advisory services, by individual investors, is still incapable of mitigating behavioural biases, such as overconfidence bias and loss-aversion bias.

The sample size of this study could be a limiting factor. This study is limited only to two biases, while other behavioural biases affect the investment decision-making of the investors, which can be considered for future research along with the impact of robo-advisory services in different socio-cultural backgrounds.

This study will assist fintech start-ups, banks, architecture of robo advisors, product owners and wealth management service providers improvise their products, platforms and offerings of these automated advisory services. This could help individual investors to mitigate their behavioural biases in investment decision-making.

This study is useful to society as the awareness of robo-advisory services is very less, at present, and there is a need to increase the usage of these services to extend the benefit of this to the lower stratum of society. These services would be useful to all investors who find it difficult to afford financial advisors and help them mitigate their behavioural biases for investment decision-making.

This study is the first of its type that establishes the linkage between behavioural biases, digital innovation in fintech, i.e. robo-advisory services and individual investor’s investment decision-making in individual investor of the Indian stock market.