Purpose The purpose of this study is to assess the nexus between the vast dimensions of financial inclusion and economic development of the emerging Indian economy. Design/methodology/approach In this study, vector auto-regression (VAR) models and Granger causality test were followed to test the main research question in Indian context. The data were collected on various dimensions of financial inclusion and economic development for the period 2004-2013. Findings Empirical results and discussion suggest that there is a positive association between economic growth and various dimensions of financial inclusion, specifically banking penetration, availability of banking services and usage of banking services in terms of deposits. Granger causality analysis reveals a bi-directional causality between geographic outreach and economic development and a unidirectional causality between the number of deposits/loan accounts and gross domestic product. The results obtained favor social banking experiments in India with a deepening of banking institutions. Research limitations/implications This study is limited to the banking institutions and specifically to the emerging and developing economies. Practical implications This study analyzes the quantitative value of social banking experiments and governments’ efforts to enhance financial inclusion in terms of economic growth. Social implications Financial inclusion plays a key role in developing a strong and an efficient financial infrastructure, which facilitates the growth of an economy. The findings of the study reveal that there is a strong association between banking penetration and growth. The discussion leads in the favor of deepening of the banking institutions, and therefore, policymakers can look forward to these findings to maintain a sustainable-inclusive-developed economic system in an emerging economy like India. Originality/value This study is original in nature and includes recent evidence and efforts to promote financial inclusion in the Indian economy. The findings of this study will be of value to banks and policymakers.
Sustainable finance is a rich field of research. Yet, existing reviews remain limited due to the piecemeal insights offered through a sub-set rather than the entire corpus of sustainable finance. To address this gap, this study aims to conduct a large-scale review that would provide a state-of-the-art overview of the performance and intellectual structure of sustainable finance. To do so, this study engages in a review of sustainable finance research using big data analytics through machine learning of scholarly research. In doing so, this study unpacks the most influential articles and top contributing journals, authors, institutions, and countries, as well as the methodological choices and research contexts for sustainable finance research. In addition, this study reveals insights into seven major themes of sustainable finance research, namely socially responsible investing, climate financing, green financing, impact investing, carbon financing, energy financing, and governance of sustainable financing and investing. To drive the field forward, this study proposes several suggestions for future sustainable finance research, which include developing and diffusing innovative sustainable financing instruments, magnifying and managing the profitability and returns of sustainable financing, making sustainable finance more sustainable, devising and unifying policies and frameworks for sustainable finance, tackling greenwashing of corporate sustainability reporting in sustainable finance, shining behavioral finance on sustainable finance, and leveraging the power of new-age technologies such as artificial intelligence, blockchain, internet of things, and machine learning for sustainable finance.
Purpose This study aims to understand the consumer behavior in the context of online food delivery services that has become crucial for all the players in the market to meet their bottom line, especially given the fact that COVID-19 has altered the mindset of consumers. The current perception was addressed and analyzed to understand the trends. So, this study examined various parameters such as e-services quality, food quality (FQ), safety measures (SM), customer satisfaction (CS) and customer loyalty (CL) in correlation to each other. Design/methodology/approach An online survey was conducted for users of the online food delivery services to understand the intentions during the month of June 2020. The total number of responses gathered were 201. The responses collected were analyzed based on the constructs formed for the following tests: reliability, convergent and discriminant analysis. Also, principal component analysis was performed to ensure that the variables are correlated to each other. This ensured that the structural equation model built is valid and of best fit. The hypotheses were tested for the discussed variables, and the results were presented accordingly. Findings The research has indicated that FQ plays a vital role for CS which indirectly influences CL. Also, the SM adopted by a restaurant and delivery service will help retain their customer base, thus ensuring loyalty. Practical implications The study will help managers of restaurants and online food platforms reorient their business model and framework according to the parameters that affect the mindset of the consumer and also help improve the retention of their customer base. Originality/value This study is original in nature and takes onto account the COVID-19 situation. The study provides insights for online food platforms to touch mainly the pain points and insights by the consumer which will aid in developing new strategies for business development and customer retention in the future.
Purpose The purpose of this study is to determine the impact of environment, social and governance (ESG) disclosure on credit ratings of companies in India. Design/methodology/approach Firms under study are listed on the Bombay Stock Exchange (BSE) 500 and represent almost 93 per cent of the total market capitalization on BSE. This study considers a sample of 122 firms from a population of 500 to examine the relationship between ESG scores and Credit Rating. The scope of this study is confined to those firms listed on the S&P BSE 500 which have made ESG disclosures and were rated by various credit rating agencies like Crisil, ICRA and CARE. Data were sourced from Bloomberg. Ratings were given in ascending order. In the first model, credit rating was used as predicted variable; ESG score as predictor variable and market capitalization, net debt to equity, and total debt to asset as control considering the ordered nature of dependent variable in the study, ordered logistic regression was applied. It was repeated taking individual scores on environment rating, social rating and governance rating as predictors. The authors further segregated the 122 selected firms into large, medium and low capital firms and assessed separate logistic regression models taking credit rating as the predicted variable and overall ESG score as the predictor. Findings It was found that overall ESG performance and performance of individual components (environment, social and financial variables such as market capitalization, and debt to equity ratio) had significant positive indicators of creditworthiness as measured through credit rating. Governance score had a positive and insignificant relation with credit rating. Market capitalization was observed to have significant direct relationship with credit worthiness. On the other hand, number of independent directors in companies showed significant inverse relationship with creditworthiness. ESG significantly impacted credit rating in the desired direction only for small- and middle-level firms; for large firms which already had higher credit rating, ESG showed no effect. It was also found that credit rating itself determined significantly the extent of overall ESG reporting and disclosure of its components. Originality/value This is unique study that covers the aspects of ESG reports and its impact on credit rating.
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